@article{white_petrasova_petras_tateosian_vukomanovic_mitasova_meentemeyer_2023, title={An open-source platform for geospatial participatory modeling in the cloud}, volume={167}, ISSN={["1873-6726"]}, url={https://doi.org/10.1016/j.envsoft.2023.105767}, DOI={10.1016/j.envsoft.2023.105767}, abstractNote={Participatory modeling facilitates the co-production of knowledge and action by engaging stakeholders in research. However, the spatial dimensions of socio-environmental systems and decision-making are challenging to incorporate in participatory models, as developing interactive geospatial models requires specialized knowledge. Yet, many of society’s most pressing and complex socio-environmental problems require participatory modeling that is geospatial. Existing interactive online applications have broadened the audiences who can engage with geospatial models, but often do not provide a robust framework for interactive model development. Here, we develop an open-source platform, OpenPlains, to address barriers to participation in geospatial modeling by enabling researchers to develop interactive models that remove barriers to data aggregation and user engagement. OpenPlains consists of six new open-source libraries: OpenPlains, django-actina, grass-js-client, react-openplains, react-ol, and openplains-cli. We demonstrate OpenPlains through two web applications that work anywhere in the contiguous United States: a spatial–temporal watershed analysis application and an urban growth forecasting application.}, journal={ENVIRONMENTAL MODELLING & SOFTWARE}, publisher={Elsevier BV}, author={White, Corey T. and Petrasova, Anna and Petras, Vaclav and Tateosian, Laura G. and Vukomanovic, Jelena and Mitasova, Helena and Meentemeyer, Ross K.}, year={2023}, month={Sep} }
 @article{montgomery_walden-schreiner_saffer_jones_seliger_worm_tateosian_shukunobe_kumar_meentemeyer_2023, title={Forecasting global spread of invasive pests and pathogens through international trade}, volume={14}, ISSN={["2150-8925"]}, url={http://dx.doi.org/10.1002/ecs2.4740}, DOI={10.1002/ecs2.4740}, abstractNote={Abstract}, number={12}, journal={ECOSPHERE}, author={Montgomery, Kellyn and Walden-Schreiner, Chelsey and Saffer, Ariel and Jones, Chris and Seliger, Benjamin J. and Worm, Thom and Tateosian, Laura and Shukunobe, Makiko and Kumar, Sunil and Meentemeyer, Ross K.}, year={2023}, month={Dec} }
 @article{petras_petrasova_mccarter_mitasova_meentemeyer_2023, title={Point Density Variations in Airborne Lidar Point Clouds}, volume={23}, ISSN={["1424-8220"]}, url={https://doi.org/10.3390/s23031593}, DOI={10.3390/s23031593}, abstractNote={In spite of increasing point density and accuracy, airborne lidar point clouds often exhibit point density variations. Some of these density variations indicate issues with point clouds, potentially leading to errors in derived products. To highlight these issues, we provide an overview of point density variations and show examples in six airborne lidar point cloud datasets that we used in our topographic and geospatial modeling research. Using the published literature, we identified sources of point density variations and issues indicated or caused by these variations. Lastly, we discuss the reduction in point density variations using decimations, homogenizations, and their applicability.}, number={3}, journal={SENSORS}, author={Petras, Vaclav and Petrasova, Anna and McCarter, James B. and Mitasova, Helena and Meentemeyer, Ross K.}, year={2023}, month={Feb} }
 @article{sanchez_petrasova_skrip_collins_lawrimore_vogler_terando_vukomanovic_mitasova_meentemeyer_2023, title={Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk}, volume={13}, ISSN={["2045-2322"]}, url={http://dx.doi.org/10.1038/s41598-023-46195-9}, DOI={10.1038/s41598-023-46195-9}, abstractNote={Abstract}, number={1}, journal={SCIENTIFIC REPORTS}, publisher={Springer Science and Business Media LLC}, author={Sanchez, Georgina M. and Petrasova, Anna and Skrip, Megan M. and Collins, Elyssa L. and Lawrimore, Margaret A. and Vogler, John B. and Terando, Adam and Vukomanovic, Jelena and Mitasova, Helena and Meentemeyer, Ross K.}, year={2023}, month={Nov} }
 @article{inglis_vukomanovic_petrasova_meentemeyer_2023, title={Viewscape change highlights shifting drivers of exurban development over time}, volume={238}, ISSN={["1872-6062"]}, url={https://doi.org/10.1016/j.landurbplan.2023.104833}, DOI={10.1016/j.landurbplan.2023.104833}, abstractNote={Exurban development has increased over recent decades, characterized by low-density, amenity-driven housing development, and shaped by the landscape’s visual quality, rural character and perceived quality of life. Viewscapes—the 3-dimensional portions of landscapes with which people form a connection—are one way to quantify visual character and assess how those aesthetic amenities interact with other drivers to shape exurban development. The extent to which a landscape changes over time due to anthropogenic and natural processes—such as new housing development or wildfire—has largely been overlooked in models of development that include viewscape metrics. In this study, we use an event-history analysis approach to model the relationship between known drivers, including viewscape metrics (area, land cover, terrain complexity and visible neighbors), and the timing of exurban development of 1,807 single-family residences in Boulder County, Colorado, USA between 1990 and 2020. Most viewscape metrics’ effects on the timing of new home builds varied by 5-year time interval, underscoring the constraints of temporally static development models. We found that houses were more likely to be located close to major roads, and with views of less complex terrain. Larger views and fewer visible neighbors emerged as predictors of development over the study period. In the early-2000s, developed sites favored sunnier aspects, and views that avoided burn scars and developed areas. After 2010, new homes sites avoided views of developed areas and favored forested views. Insight into changing relationships between viewscapes and exurban housing development can highlight the effects of landscape change on visual quality and the trade-offs inherent in housing location decisions. Exploring how viewscape drivers and their effects on development change over time offers land managers and policymakers a more detailed picture of the amenity factors shaping exurban development.}, journal={LANDSCAPE AND URBAN PLANNING}, publisher={Elsevier BV}, author={Inglis, Nicole C. and Vukomanovic, Jelena and Petrasova, Anna and Meentemeyer, Ross K.}, year={2023}, month={Oct} }
 @article{sanchez_eaton_garcia_keisman_ullman_blackwell_meentemeyer_2022, title={Integrating principles and tools of decision science into value-driven watershed planning for compensatory mitigation}, volume={12}, ISSN={["1939-5582"]}, url={https://doi.org/10.1002/eap.2766}, DOI={10.1002/eap.2766}, abstractNote={Abstract}, journal={ECOLOGICAL APPLICATIONS}, author={Sanchez, Georgina M. M. and Eaton, Mitchell J. J. and Garcia, Ana M. M. and Keisman, Jennifer and Ullman, Kirsten and Blackwell, James and Meentemeyer, Ross K. K.}, year={2022}, month={Dec} }
 @article{collins_sanchez_terando_stillwell_mitasova_sebastian_meentemeyer_2022, title={Predicting flood damage probability across the conterminous United States}, volume={17}, ISSN={["1748-9326"]}, url={https://doi.org/10.1088/1748-9326/ac4f0f}, DOI={10.1088/1748-9326/ac4f0f}, abstractNote={Abstract}, number={3}, journal={ENVIRONMENTAL RESEARCH LETTERS}, author={Collins, Elyssa L. and Sanchez, Georgina M. and Terando, Adam and Stillwell, Charles C. and Mitasova, Helena and Sebastian, Antonia and Meentemeyer, Ross K.}, year={2022}, month={Mar} }
 @article{white_reckling_petrasova_meentemeyer_mitasova_2022, title={Rapid-DEM: Rapid Topographic Updates through Satellite Change Detection and UAS Data Fusion}, volume={14}, ISSN={["2072-4292"]}, url={https://www.mdpi.com/2072-4292/14/7/1718}, DOI={10.3390/rs14071718}, abstractNote={As rapid urbanization occurs in cities worldwide, the importance of maintaining updated digital elevation models (DEM) will continue to increase. However, due to the cost of generating high-resolution DEM over large spatial extents, the temporal resolution of DEMs is coarse in many regions. Low-cost unmanned aerial vehicles (UAS) and DEM data fusion provide a partial solution to improving the temporal resolution of DEM but do not identify which areas of a DEM require updates. We present Rapid-DEM, a framework that identifies and prioritizes locations with a high likelihood of an urban topographic change to target UAS data acquisition and fusion to provide up-to-date DEM. The framework uses PlanetScope 3 m satellite imagery, Google Earth Engine, and OpenStreetMap for land cover classification. GRASS GIS generates a contextualized priority queue from the land cover data and outputs polygons for UAS flight planning. Low-cost UAS fly the identified areas, and WebODM generates a DEM from the UAS survey data. The UAS data is fused with an existing DEM and uploaded to a public data repository. To demonstrate Rapid-DEM a case study in the Walnut Creek Watershed in Wake County, North Carolina is presented. Two land cover classification models were generated using random forests with an overall accuracy of 89% (kappa 0.86) and 91% (kappa 0.88). The priority queue identified 109 priority locations representing 1.5% area of the watershed. Large forest clearings were the highest priority locations, followed by newly constructed buildings. The highest priority site was a 0.5 km2 forest clearing that was mapped with UAS, generating a 15 cm DEM. The UAS DEM was resampled to 3 m resolution and fused with USGS NED 1/9 arc-second DEM data. Surface water flow was simulated over the original and updated DEM to illustrate the impact of the topographic change on flow patterns and highlight the importance of timely DEM updates.}, number={7}, journal={REMOTE SENSING}, publisher={MDPI AG}, author={White, Corey T. and Reckling, William and Petrasova, Anna and Meentemeyer, Ross K. and Mitasova, Helena}, year={2022}, month={Apr} }
 @article{amindarbari_baran_meentemeyer_2022, title={Spatially disaggregated simulation of interactions between home prices and land-use change}, volume={12}, ISSN={["2399-8091"]}, url={https://doi.org/10.1177/23998083221142603}, DOI={10.1177/23998083221142603}, abstractNote={ Land-use regulations play a key role on both sides of the real estate market by regulating the supply of housing (e.g., through restrictions on unit density or building height) and by controlling the location and density of places of work, which are the primary drivers of the demand for housing. Developing geospatial models for this interaction between land use and home price on a spatially disaggregated level enables decisionmakers to evaluate the impact of their land-use decisions from the housing affordability perspective. However, existing standalone residential real estate pricing models are insensitive to changes in land use. In addition, the data preparation, calibration, and training of integrated land-use and transportation models is nontrivial too, and still impractical for most municipalities and planning agencies. This paper presents a simple-to-implement framework, SimP-R, for simulating changes in housing prices on a spatially disaggregated level in response to land-use change. It is composed of a residential real estate pricing model and an algorithm for computing a novel measure of supply-to-demand ratio. This paper then demonstrates the implementation of SimP-R in the city of San Francisco, with the entire Bay Area serving as the influence geography. Our findings showed our proposed measure of the supply-to-demand ratio is a strong predictor of and inversely related to housing prices. Simulation experimentation results highlighted SimP-R’s ability to capture the effect of local land-use changes on housing prices across the metropolitan area. }, journal={ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE}, author={Amindarbari, Reza and Baran, Perver and Meentemeyer, Ross K. K.}, year={2022}, month={Dec} }
 @article{jones_skrip_seliger_jones_wakie_takeuchi_petras_petrasova_meentemeyer_2022, title={Spotted lanternfly predicted to establish in California by 2033 without preventative management}, volume={5}, ISSN={["2399-3642"]}, url={https://doi.org/10.1038/s42003-022-03447-0}, DOI={10.1038/s42003-022-03447-0}, abstractNote={Abstract}, number={1}, journal={COMMUNICATIONS BIOLOGY}, author={Jones, Chris and Skrip, Megan M. and Seliger, Benjamin J. and Jones, Shannon and Wakie, Tewodros and Takeuchi, Yu and Petras, Vaclav and Petrasova, Anna and Meentemeyer, Ross K.}, year={2022}, month={Jun} }
 @article{zhang_chen_myint_zhou_hay_vukomanovic_meentemeyer_2022, title={UrbanWatch: A 1-meter resolution land cover and land use database for 22 major cities in the United States}, volume={278}, ISSN={["1879-0704"]}, DOI={10.1016/j.rse.2022.113106}, abstractNote={Very-high-resolution (VHR) land cover and land use (LCLU) is an essential baseline data for understanding fine-scale interactions between humans and the heterogeneous landscapes of urban environments. In this study, we developed a Fine-resolution, Large-area Urban Thematic information Extraction (FLUTE) framework to address multiple challenges facing large-area, high-resolution urban mapping, including the view angle effect, high intraclass and low interclass variation, and multiscale land cover types. FLUTE builds upon a teacher-student deep learning architecture, and includes two new feature extraction modules – Scale-aware Parsing Module (SPM) and View-aware Embedding Module (VEM). Our model was trained with a new benchmark database containing 52.43 million labeled pixels (from 2014 to 2017 NAIP airborne Imagery) to capture diverse LCLU types and spatial patterns. We assessed the credibility of FLUTE by producing a 1-meter resolution database named UrbanWatch for 22 major cities across the conterminous United States. UrbanWatch contains nine LCLU classes – building, road, parking lot, tree canopy, grass/shrub, water, agriculture, barren, and others, with an overall accuracy of 91.52%. We have further made UrbanWatch freely accessible to support urban-related research, urban planning and management, and community outreach efforts: https://urbanwatch.charlotte.edu.}, journal={REMOTE SENSING OF ENVIRONMENT}, author={Zhang, Yindan and Chen, Gang and Myint, Soe W. and Zhou, Yuyu and Hay, Geoffrey J. and Vukomanovic, Jelena and Meentemeyer, Ross K.}, year={2022}, month={Sep} }
 @article{gaydos_jones_jones_millar_petras_petrasova_mitasova_meentemeyer_2021, title={Evaluating online and tangible interfaces for engaging stakeholders in forecasting and control of biological invasions}, volume={9}, ISSN={["1939-5582"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85115251448&partnerID=MN8TOARS}, DOI={10.1002/eap.2446}, abstractNote={Abstract}, number={8}, journal={ECOLOGICAL APPLICATIONS}, publisher={Wiley}, author={Gaydos, Devon A. and Jones, Chris M. and Jones, Shannon K. and Millar, Garrett C. and Petras, Vaclav and Petrasova, Anna and Mitasova, Helena and Meentemeyer, Ross K.}, year={2021}, month={Sep} }
 @article{he_chen_cobb_zhao_meentemeyer_2021, title={Forest landscape patterns shaped by interactions between wildfire and sudden oak death disease}, volume={486}, ISSN={["1872-7042"]}, DOI={10.1016/j.foreco.2021.118987}, abstractNote={Forest ecosystems are increasingly affected by a range of tree mortality events, which may permanently alter forest functional traits and disrupt their ecosystem services. While individual forest disturbances are well studied, interactions between multiple disturbances and changes of spatial patterns of forested landscapes are rarely quantified. In this study, we aim to analyze the role of wildfire in the Big Sur ecoregion of California on the spread of Phytophthora ramorum, an invasive pathogen which causes sudden oak death, the most important driver of mortality across 1000 km of coastal, fire-prone mixed conifer, evergreen hardwood, and woodlands. We investigated two questions specific to the impacts of these disturbances at the landscape scale: (i) did rates of P. ramorum caused tree mortality change after wildfire? (ii) Following the wildfire, to what degree did the continued disease-driven mortality alter forest distribution? To answer these questions, we analyzed remote-sensing-derived products of post-fire burn severity and maps of disease-driven tree mortality. Quantification of burn severity and post fire disease mortality for the burned and unburned areas provided reference conditions for statistical hypothesis tests. The results from statistical and three landscape pattern analyses (area, shape, and isolation) suggest a significant role of wildfire in the reemergence of this invasive pathogen. First, rates of disease caused mortality after wildfire was negatively associated with burn severity suggesting some fire-driven containment of disease during post-fire forest recovery. Second, disease was positively correlated with the distance to fire boundary in unburned areas suggesting the effects of fire on disease extended into unburned areas while attenuating with distance from the burn. Lastly, wildfire reduced area, edge density and isolation of healthy tree patches and these effects did not recover to pre-fire levels for any of the three metrics after eight years of vegetation recovery. Given the widespread prevalence of disease-driven mortality, the importance and frequency of fire, as well as the naturalization of Phytophthora ramorum across a broad geographic area, these fire-disease interactions have potential to shape forest structure and disease dynamics across millions of acres of forested wildlands in California and Oregon.}, journal={FOREST ECOLOGY AND MANAGEMENT}, author={He, Yinan and Chen, Gang and Cobb, Richard C. and Zhao, Kaiguang and Meentemeyer, Ross K.}, year={2021}, month={Apr} }
 @article{jones_jones_petrasova_petras_gaydos_skrip_takeuchi_bigsby_meentemeyer_2021, title={Iteratively forecasting biological invasions with PoPS and a little help from our friends}, volume={6}, ISSN={["1540-9309"]}, url={http://dx.doi.org/10.1002/fee.2357}, DOI={10.1002/fee.2357}, abstractNote={Ecological forecasting has vast potential to support environmental decision making with repeated, testable predictions across management‐relevant timescales and locations. Yet resource managers rarely use co‐designed forecasting systems or embed them in decision making. Although prediction of planned management outcomes is particularly important for biological invasions to optimize when and where resources should be allocated, spatial–temporal models of spread typically have not been openly shared, iteratively updated, or interactive to facilitate exploration of management actions. We describe a species‐agnostic, open‐source framework – called the Pest or Pathogen Spread (PoPS) Forecasting Platform – for co‐designing near‐term iterative forecasts of biological invasions. Two case studies are presented to demonstrate that iterative calibration yields higher forecast skill than using only the earliest‐available data to predict future spread. The PoPS framework is a primary example of an ecological forecasting system that has been both scientifically improved and optimized for real‐world decision making through sustained participation and use by management stakeholders.}, number={7}, journal={FRONTIERS IN ECOLOGY AND THE ENVIRONMENT}, publisher={Wiley}, author={Jones, Chris M. and Jones, Shannon and Petrasova, Anna and Petras, Vaclav and Gaydos, Devon and Skrip, Megan M. and Takeuchi, Yu and Bigsby, Kevin and Meentemeyer, Ross K.}, year={2021}, month={Jun} }
 @article{white_mitasova_bendor_foy_pala_vukomanovic_meentemeyer_2021, title={Spatially Explicit Fuzzy Cognitive Mapping for Participatory Modeling of Stormwater Management}, volume={10}, ISSN={["2073-445X"]}, url={https://doi.org/10.3390/land10111114}, DOI={10.3390/land10111114}, abstractNote={Addressing “wicked” problems like urban stormwater management necessitates building shared understanding among diverse stakeholders with the influence to enact solutions cooperatively. Fuzzy cognitive maps (FCMs) are participatory modeling tools that enable diverse stakeholders to articulate the components of a socio-environmental system (SES) and describe their interactions. However, the spatial scale of an FCM is rarely explicitly considered, despite the influence of spatial scale on SES. We developed a technique to couple FCMs with spatially explicit survey data to connect stakeholder conceptualization of urban stormwater management at a regional scale with specific stormwater problems they identified. We used geospatial data and flooding simulation models to quantitatively evaluate stakeholders’ descriptions of location-specific problems. We found that stakeholders used a wide variety of language to describe variables in their FCMs and that government and academic stakeholders used significantly different suites of variables. We also found that regional FCM did not downscale well to concerns at finer spatial scales; variables and causal relationships important at location-specific scales were often different or missing from the regional FCM. This study demonstrates the spatial framing of stormwater problems influences the perceived range of possible problems, barriers, and solutions through spatial cognitive filtering of the system’s boundaries.}, number={11}, journal={LAND}, publisher={MDPI AG}, author={White, Corey T. and Mitasova, Helena and BenDor, Todd K. and Foy, Kevin and Pala, Okan and Vukomanovic, Jelena and Meentemeyer, Ross K.}, year={2021}, month={Nov} }
 @article{smart_taillie_poulter_vukomanovic_singh_swenson_mitasova_smith_meentemeyer_2020, title={Aboveground carbon loss associated with the spread of ghost forests as sea levels rise}, volume={15}, ISSN={["1748-9326"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85092484857&partnerID=MN8TOARS}, DOI={10.1088/1748-9326/aba136}, abstractNote={Abstract}, number={10}, journal={ENVIRONMENTAL RESEARCH LETTERS}, author={Smart, Lindsey S. and Taillie, Paul J. and Poulter, Benjamin and Vukomanovic, Jelena and Singh, Kunwar K. and Swenson, Jennifer J. and Mitasova, Helena and Smith, Jordan W. and Meentemeyer, Ross K.}, year={2020}, month={Oct} }
 @article{petrasova_gaydos_petras_jones_mitasova_meentemeyer_2020, title={Geospatial simulation steering for adaptive management}, volume={133}, url={https://doi.org/10.1016/j.envsoft.2020.104801}, DOI={10.1016/j.envsoft.2020.104801}, abstractNote={Spatio-temporal simulations are becoming essential tools for decision makers when forecasting future conditions and evaluating effectiveness of alternative decision scenarios. However, lack of interactive steering capabilities limits the value of advanced stochastic simulations for research and practice. To address this gap we identified conceptual challenges associated with steering stochastic, spatio-temporal simulations and developed solutions that better represent the realities of decision-making by allowing both reactive and proactive, spatially-explicit interventions. We present our approach, in a participatory modeling case study engaging stakeholders in developing strategies to contain the spread of a tree disease in Oregon, USA. Using intuitive interfaces, implemented through web-based and tangible platforms, stakeholders explored management options as the simulation progressed. Spatio-temporal steering allowed them to combine currently used management practices into novel adaptive management strategies, which were previously difficult to test and assess, demonstrating the utility of interactive simulations for decision-making.}, journal={Environmental Modelling & Software}, publisher={Elsevier BV}, author={Petrasova, Anna and Gaydos, Devon A. and Petras, Vaclav and Jones, Chris M. and Mitasova, Helena and Meentemeyer, Ross K.}, year={2020}, month={Nov}, pages={104801} }
 @article{tabrizian_petrasova_baran_vukomanovic_mitasova_meentemeyer_2020, title={High Resolution Viewscape Modeling Evaluated Through Immersive Virtual Environments}, volume={9}, url={https://doi.org/10.3390/ijgi9070445}, DOI={10.3390/ijgi9070445}, abstractNote={Visual characteristics of urban environments influence human perception and behavior, including choices for living, recreation and modes of transportation. Although geospatial visualizations hold great potential to better inform urban planning and design, computational methods are lacking to realistically measure and model urban and parkland viewscapes at sufficiently fine-scale resolution. In this study, we develop and evaluate an integrative approach to measuring and modeling fine-scale viewscape characteristics of a mixed-use urban environment, a city park. Our viewscape approach improves the integration of geospatial and perception elicitation techniques by combining high-resolution lidar-based digital surface models, visual obstruction, and photorealistic immersive virtual environments (IVEs). We assessed the realism of our viewscape models by comparing metrics of viewscape composition and configuration to human subject evaluations of IVEs across multiple landscape settings. We found strongly significant correlations between viewscape metrics and participants’ perceptions of viewscape openness and naturalness, and moderately strong correlations with landscape complexity. These results suggest that lidar-enhanced viewscape models can adequately represent visual characteristics of fine-scale urban environments. Findings also indicate the existence of relationships between human perception and landscape pattern. Our approach allows urban planners and designers to model and virtually evaluate high-resolution viewscapes of urban parks and natural landscapes with fine-scale details never before demonstrated.}, number={7}, journal={ISPRS International Journal of Geo-Information}, publisher={MDPI AG}, author={Tabrizian, Payam and Petrasova, Anna and Baran, Perver and Vukomanovic, Jelena and Mitasova, Helena and Meentemeyer, Ross}, year={2020}, month={Jul}, pages={445} }
 @article{tabrizian_baran_van berkel_mitasova_meentemeyer_2020, title={Modeling restorative potential of urban environments by coupling viewscape analysis of lidar data with experiments in immersive virtual environments}, volume={195}, ISSN={["1872-6062"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85076054188&partnerID=MN8TOARS}, DOI={10.1016/j.landurbplan.2019.103704}, abstractNote={• We propose an approach for modeling experiential qualities of urban landscape. • We use lidar data to generate detailed model of landscape structure and patterns. • We combine GIS analysis of viewscapes with survey of immersive virtual environment. • We identify spatial metrics that predict urban landscape’s restorative potential (RP). • We develop a predictive map of RP that can support decision-making and urban design.}, journal={LANDSCAPE AND URBAN PLANNING}, author={Tabrizian, Payam and Baran, Perver K. and Van Berkel, Derek and Mitasova, Helena and Meentemeyer, Ross}, year={2020}, month={Mar} }
 @article{modeling the impacts of urbanization on watershed-scale gross primary productivity and tradeoffs with water yield across the conterminous united states_2020, url={http://dx.doi.org/10.1016/j.jhydrol.2020.124581}, DOI={10.1016/j.jhydrol.2020.124581}, abstractNote={The objective of this study was to examine the impacts of urbanization on gross primary productivity (GPP) and the interactions between carbon and water fluxes, including precipitation, evapotranspiration (ET), and water yield (Q). A water-centric ecosystem model, Water Supply Stress Index model (WaSSI) that operates at the 12-digit (81,900 watersheds) Hydrologic Unit Code (HUC) scale for the conterminous United States (CONUS) during 2000–2010, 2000–2050, and 2000–2100 was used. Linear regression and causal-based models were then applied to identify key factors controlling urbanization impact on GPP. Simulations of GPP patterns compared favorably with a global, 0.05-degree product of solar-induced chlorophyll fluorescence (SIF). We found that total CONUS GPP declined from 8.68 Pg C yr−1 in 2000, to 8.54 Pg C yr−1 in 2010, to 8.36 Pg C yr−1 in 2050, and to 8.13 Pg C yr−1 in 2100. Total GPP decreased from 6.81 Pg C yr−1 to 6.26 Pg C yr−1 for those watersheds affected by urbanization (~55,000). Total CONUS Q increased from 2.03 × 106 million m3 yr−1 in 2000, to 2.04 × 106 million m3 yr−1 in 2010, to 2.06 × 106 million m3 yr−1 in 2050, and 2.09 × 106 million m3 yr−1 in 2100, while Q increased from 1.68 × 106 million m3 yr−1 to 1.74 × 106 million m3 yr−1 for urbanized watersheds alone (~55,000). Although total CONUS ΔGPP was less than 0.55 Pg C yr−1, or <8%, large changes (ΔGPP >300 g C m−2 yr−1) were found in 245, 1984, and 5655 of the 81,900 watersheds by 2010, 2050 and 2100, respectively. Overall, the impacts of urbanization on GPP in the CONUS were influenced by background climate, previous land cover characteristics, and the magnitudes of land use change. Effective integrated watershed management that attempts to minimize the negative ecological and environmental impacts of urbanization must consider regional hydrologic differences and fit local climatic and watershed conditions.}, journal={Journal of Hydrology}, year={2020}, month={Apr} }
 @article{protection status and proximity to public‐private boundaries influence land use intensification near u.s. parks and protected areas_2020, url={http://dx.doi.org/10.1111/csp2.190}, DOI={10.1111/csp2.190}, abstractNote={Abstract}, journal={Conservation Science and Practice}, year={2020}, month={Feb} }
 @article{zhang_chen_vukomanovic_singh_liu_holden_meentemeyer_2020, title={Recurrent Shadow Attention Model (RSAM) for shadow removal in high-resolution urban land-cover mapping}, volume={247}, ISSN={["1879-0704"]}, DOI={10.1016/j.rse.2020.111945}, abstractNote={Shadows are prevalent in urban environments, introducing high uncertainties to fine-scale urban land-cover mapping. In this study, we developed a Recurrent Shadow Attention Model (RSAM), capitalizing on state-of-the-art deep learning architectures, to retrieve fine-scale land-cover classes within cast and self shadows along the urban-rural gradient. The RSAM differs from the other existing shadow removal models by progressively refining the shadow detection result with two attention-based interacting modules – Shadow Detection Module (SDM) and Shadow Classification Module (SCM). To facilitate model training and validation, we also created a Shadow Semantic Annotation Database (SSAD) using the 1 m resolution (National Agriculture Imagery Program) NAIP aerial imagery. The SSAD comprises 103 image patches (500 × 500 pixels each) containing various types of shadows and six major land-cover classes – building, tree, grass/shrub, road, water, and farmland. Our results show an overall accuracy of 90.6% and Kappa of 0.82 for RSAM to extract the six land-cover classes within shadows. The model performance was stable along the urban-rural gradient, although it was slightly better in rural areas than in urban centers or suburban neighborhoods. Findings suggest that RSAM is a robust solution to eliminate the effects in high-resolution mapping both from cast and self shadows that have not received equal attention in previous studies.}, journal={REMOTE SENSING OF ENVIRONMENT}, author={Zhang, Yindan and Chen, Gang and Vukomanovic, Jelena and Singh, Kunwar K. and Liu, Yong and Holden, Samuel and Meentemeyer, Ross K.}, year={2020}, month={Sep} }
 @article{spatiotemporal patterns and drivers of soil contamination with heavy metals during an intensive urbanization period (1989–2018) in southern china_2020, url={http://dx.doi.org/10.1016/j.envpol.2020.114075}, DOI={10.1016/j.envpol.2020.114075}, abstractNote={This three-decade long study was conducted in the Pearl River Delta (PRD), a rapidly urbanizing region in southern China. Extensive soil samples for a diverse land uses were collected in 1989 (113), 2005 (1384), 2009 (521), and 2018 (421) for heavy metals of As, Cr, Cd, Cu, Hg, Ni, Pb and Zn. Multiple pollution indices and Structural Equation Models (SEMs) were used in attribution analysis and comprehensive assessments. Data showed that majority of the sampling sites was contaminated by one or more heavy metals, but pollutant concentrations had not reached levels of concerns for food security or human health. There was an increasing trend in heavy metal contamination over time and the variations of soil contamination were site-, time- and pollutant-dependent. Areas with high concentrations of heavy metals overlapped with highly industrialized and populated areas in western part of the study region. A dozen SEMs path analyses were used to compare the relative influences of key environmental factors on soil contamination across space and time. The high or elevated soil contaminations by As, Cr, Ni, Cu and Zn were primarily affected by soil properties during the study period, except 1989–2005, followed by land use patterns. Parent materials had a significant effect on elevated soil contamination of Cd, Cr, Ni, Pb and overall soil pollution during 1989–2005. We hypothesized that other factors not considered in the present study, such as atmospheric deposition, sewage irrigation, and agrochemical uses, may be also important to explain the variability of soil contamination. This study implied that strategies to improve soil physiochemical properties and optimize landscape structures are viable methods to mitigate soil contamination. Future studies should monitor pollutant sources identified by this study to fully understand the causes of heavy metal contamination in rapidly industrialized regions in southern China.}, journal={Environmental Pollution}, year={2020}, month={May} }
 @article{cobb_haas_kruskamp_dillon_swiecki_rizzo_frankel_meentemeyer_2020, title={The Magnitude of Regional-Scale Tree Mortality Caused by the Invasive PathogenPhytophthora ramorum}, volume={8}, ISSN={["2328-4277"]}, url={https://doi.org/10.1029/2020EF001500}, DOI={10.1029/2020EF001500}, abstractNote={Abstract}, number={7}, journal={EARTHS FUTURE}, author={Cobb, Richard C. and Haas, Sarah E. and Kruskamp, Nicholas and Dillon, Whalen W. and Swiecki, Tedmund J. and Rizzo, David M. and Frankel, Susan J. and Meentemeyer, Ross K.}, year={2020}, month={Jul} }
 @article{he_chen_de santis_roberts_zhou_meentemeyer_2019, title={A disturbance weighting analysis model (DWAM) for mapping wildfire burn severity in the presence of forest disease}, volume={221}, ISSN={["1879-0704"]}, DOI={10.1016/j.rse.2018.11.015}, abstractNote={Forest ecosystems are subject to recurring fires as one of their most significant disturbances. Accurate mapping of burn severity is crucial for post-fire land management and vegetation regeneration monitoring. Remote-sensing-based monitoring of burn severity faces new challenges when forests experience both fire and non-fire disturbances, which may change the biophysical and biochemical properties of trees in similar ways. In this study, we develop a Disturbance Weighting Analysis Model (DWAM) for accurately mapping burn severity in a forest landscape that is jointly affected by wildfire and an emerging infectious disease – sudden oak death. Our approach treats burn severity in each basic mapping unit (e.g., 30 m grid from a post-fire Landsat image) as a linear combination of burn severity of trees affected (diseased) and not affected by the disease (healthy), weighted by their areal fractions in the unit. DWAM is calibrated using two types of inputs: i) look-up tables (LUTs) linking burn severity and post-fire spectra for diseased and healthy trees, derived from field observations, hyperspectral sensors [e.g., Airborne Visible InfraRed Imaging Spectrometer (AVIRIS)], and radiative transfer models; and ii) pre-fire fractional maps of diseased and healthy trees, derived by decomposing a pre-fire Landsat image using Multiple Endmember Spectral Mixture Analysis (MESMA). Considering the presence of tree disease in DWAM improved the overall map accuracy by 42%. The superior performance is consistent across all three stages of disease progression. Our approach demonstrates the potential for improved mapping of forest burn severity by reducing the confounding effects of other biotic disturbances.}, journal={REMOTE SENSING OF ENVIRONMENT}, author={He, Yinan and Chen, Gang and De Santis, Angela and Roberts, Dar A. and Zhou, Yuyu and Meentemeyer, Ross K.}, year={2019}, month={Feb}, pages={108–121} }
 @article{shoemaker_bendor_meentemeyer_2019, title={Anticipating trade-offs between urban patterns and ecosystem service production: Scenario analyses of sprawl alternatives for a rapidly urbanizing region}, volume={74}, ISSN={["1873-7587"]}, DOI={10.1016/j.compenvurbsys.2018.10.003}, abstractNote={Expanding demand for low-density development has restructured the urban-rural frontier throughout North America, shifting the burden of ecosystem provisioning to increasingly fragmented green infrastructure remnants. Planners have responded with approaches to control low-density development (‘sprawl’) that dominates North American exurbia. However, the ability of sprawl alternatives to preserve ecosystem services have not been systematically evaluated. Using a novel integration of land change simulation and ecosystem services modeling, we used proxies to estimate changes in water quality, climate regulation and biodiversity, and returns to landowners associated with sprawl alternatives and business-as-usual trends for the rapidly urbanizing Charlotte (NC) region by 2030. We found no single growth scenario simultaneously reduced pollution, stored additional carbon, and retained sensitive habitat, underscoring trade-offs likely encountered when balancing development and environmental outcomes. Watersheds at the extremes of the urban-rural gradient exhibited significantly different and often opposing responses to policies aimed at reducing environmental impacts. Scenarios of increased land use density yielded stronger financial returns to landowners as concentrated economic activity drove up land rents while minimizing broader pollution costs. Our simulated landscape approach overcame limitations associated with scale and data, and projected regional environmental outcomes emerging from local development events.}, journal={COMPUTERS ENVIRONMENT AND URBAN SYSTEMS}, author={Shoemaker, Douglas A. and BenDor, Todd K. and Meentemeyer, Ross K.}, year={2019}, month={Mar}, pages={114–125} }
 @article{simler-williamson_metz_frangioso_meentemeyer_rizzo_2019, title={Compound disease and wildfire disturbances alter opportunities for seedling regeneration in resprouter-dominated forests}, volume={10}, ISSN={["2150-8925"]}, DOI={10.1002/ecs2.2991}, abstractNote={Abstract}, number={12}, journal={ECOSPHERE}, author={Simler-Williamson, Allison B. and Metz, Margaret R. and Frangioso, Kerri M. and Meentemeyer, Ross K. and Rizzo, David M.}, year={2019}, month={Dec} }
 @article{dillon_meentemeyer_2019, title={Direct and indirect effects of forest microclimate on pathogen spillover}, volume={100}, ISSN={["1939-9170"]}, DOI={10.1002/ecy.2686}, abstractNote={Abstract}, number={5}, journal={ECOLOGY}, author={Dillon, Whalen W. and Meentemeyer, Ross K.}, year={2019}, month={May} }
 @article{gaydos_petrasova_cobb_meentemeyer_2019, title={Forecasting and control of emerging infectious forest disease through participatory modelling}, volume={374}, ISSN={["1471-2970"]}, url={https://doi.org/10.1098/rstb.2018.0283}, DOI={10.1098/rstb.2018.0283}, abstractNote={
            Epidemiological models are powerful tools for evaluating scenarios and visualizing patterns of disease spread, especially when comparing intervention strategies. However, the technical skill required to synthesize and operate computational models frequently renders them beyond the command of the stakeholders who are most impacted by the results. Participatory modelling (PM) strives to restructure the power relationship between modellers and the stakeholders who rely on model insights by involving these stakeholders directly in model development and application; yet, a systematic literature review indicates little adoption of these techniques in epidemiology, especially plant epidemiology. We investigate the potential for PM to integrate stakeholder and researcher knowledge, using
            Phytophthora ramorum
            and the resulting sudden oak death disease as a case study. Recent introduction of a novel strain (European 1 or EU1) in southwestern Oregon has prompted significant concern and presents an opportunity for coordinated management to minimize regional pathogen impacts. Using a PM framework, we worked with local stakeholders to develop an interactive forecasting tool for evaluating landscape-scale control strategies. We find that model co-development has great potential to empower stakeholders in the design, development and application of epidemiological models for disease control.
          }, number={1776}, journal={PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES}, publisher={The Royal Society}, author={Gaydos, Devon A. and Petrasova, Anna and Cobb, Richard C. and Meentemeyer, Ross K.}, year={2019}, month={Jul} }
 @article{he_chen_potter_meentemeyer_2019, title={Integrating multi-sensor remote sensing and species distribution modeling to map the spread of emerging forest disease and tree mortality}, volume={231}, ISSN={["1879-0704"]}, DOI={10.1016/j.rse.2019.111238}, abstractNote={Forest ecosystems have been increasingly affected by a variety of disturbances, including emerging infectious diseases (EIDs), causing extensive tree mortality in the Western United States. Especially over the past decade, EID outbreaks occurred more frequently and severely in forest landscapes, which have killed large numbers of trees. While tree mortality is observable from remote sensing, its symptom may be associated with both disease and non-disease disturbances (e.g., wildfire and drought). Species distribution modeling is widely used to understand species spatial preferences for certain habitat conditions, which may constrain uncertain remote sensing approaches due to limited spatial and spectral resolution. In this study, we integrated multi-sensor remote sensing and species distribution modeling to map disease-caused tree mortality in a forested area of 80,000 ha from 2005 to 2016. We selected sudden oak death (caused by pathogen P. ramorum) as a case study of a rapidly spreading emerging infectious disease, which has killed millions of oak (Quercus spp.) and tanoak (Lithocarpus densiflorus) in California over the past decades. To balance the needs for fine-scale monitoring of disease distribution patterns and satisfactory coverage at broad scales, our method applied spectral unmixing to extract sub-pixel disease presence using yearly Landsat time series. The results were improved by employing the probability of disease infection generated from a species distribution model. We calibrated and validated the method with image samples from high-spatial resolution NAIP (National Agriculture Imagery Program), and hyperspectral AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) sensors, Google Earth® imagery, and field observations. The findings reveal an annual sudden oak death infection rate of 7% from 2005 to 2016, with overall mapping accuracies ranging from 76% to 83%. The integration of multi-sensor remote sensing and species distribution modeling considerably reduced the overestimation of disease effects as compared to the use of remote sensing alone, leading to an average of 26% decrease in detecting disease-affected trees. Such integration strategy proved the effectiveness of mapping long-term, disease-caused tree mortality in forest landscapes that have experienced multiple disturbances.}, journal={REMOTE SENSING OF ENVIRONMENT}, author={He, Yinan and Chen, Gang and Potter, Christopher and Meentemeyer, Ross K.}, year={2019}, month={Sep} }
 @article{vukomanovic_skrip_meentemeyer_2019, title={Making It Spatial Makes It Personal: Engaging Stakeholders with Geospatial Participatory Modeling}, volume={8}, ISSN={["2073-445X"]}, url={https://www.mdpi.com/2073-445X/8/2/38}, DOI={10.3390/land8020038}, abstractNote={Participatory research methods are increasingly used to collectively understand complex social-environmental problems and to design solutions through diverse and inclusive stakeholder engagement. But participatory research rarely engages stakeholders to co-develop and co-interpret models that conceptualize and quantify system dynamics for comparing scenarios of alternate action. Even fewer participatory projects have engaged people using geospatial simulations of dynamic landscape processes and spatially explicit planning scenarios. We contend that geospatial participatory modeling (GPM) can confer multiple benefits over non-spatial approaches for participatory research processes, by (a) personalizing connections to problems and their solutions through visualizations of place, (b) resolving abstract notions of landscape connectivity, and (c) clarifying the spatial scales of drivers, data, and decision-making authority. We illustrate through a case study how GPM is bringing stakeholders together to balance population growth and conservation in a coastal region facing dramatic landscape change due to urbanization and sea level rise. We find that an adaptive, iterative process of model development, sharing, and revision drive innovation of methods and ultimately improve the realism of land change models. This co-production of knowledge enables all participants to fully understand problems, evaluate the acceptability of trade-offs, and build buy-in for management actions in the places where they live and work.}, number={2}, journal={LAND}, author={Vukomanovic, Jelena and Skrip, Megan M. and Meentemeyer, Ross K.}, year={2019}, month={Feb} }
 @article{koch_dorning_van berkel_beck_sanchez_shashidharan_smart_zhang_smith_meentemeyer_et al._2019, title={Modeling landowner interactions and development patterns at the urban fringe}, volume={182}, ISSN={["1872-6062"]}, url={http://dx.doi.org/10.1016/j.landurbplan.2018.09.023}, DOI={10.1016/j.landurbplan.2018.09.023}, abstractNote={Population growth and unrestricted development policies are driving low-density urbanization and fragmentation of peri-urban landscapes across North America. While private individuals own most undeveloped land, little is known about how their decision-making processes shape landscape-scale patterns of urbanization over time. We introduce a hybrid agent-based modeling (ABM) – cellular automata (CA) modeling approach, developed for analyzing dynamic feedbacks between landowners’ decisions to sell their land for development, and resulting patterns of landscape fragmentation. Our modeling approach builds on existing conceptual frameworks in land systems modeling by integrating an ABM into an established grid-based land-change model – FUTURES. The decision-making process within the ABM involves landowner agents whose decision to sell their land to developers is a function of heterogeneous preferences and peer-influences (i.e., spatial neighborhood relationships). Simulating landowners’ decision to sell allows an operational link between the ABM and the CA module. To test our hybrid ABM-CA approach, we used empirical data for a rapidly growing region in North Carolina for parameterization. We conducted a sensitivity analysis focusing on the two most relevant parameters—spatial actor distribution and peer-influence intensity—and evaluated the dynamic behavior of the model simulations. The simulation results indicate different peer-influence intensities lead to variable landscape fragmentation patterns, suggesting patterns of spatial interaction among landowners indirectly affect landscape-scale patterns of urbanization and the fragmentation of undeveloped forest and farmland.}, journal={LANDSCAPE AND URBAN PLANNING}, author={Koch, Jennifer and Dorning, Monica A. and Van Berkel, Derek B. and Beck, Scott M. and Sanchez, Georgina M. and Shashidharan, Ashwin and Smart, Lindsey S. and Zhang, Qiang and Smith, Jordan W. and Meentemeyer, Ross K. and et al.}, year={2019}, month={Feb}, pages={101–113} }
 @article{berkel_shashidharan_mordecai_vatsavai_petrasova_petras_mitasova_vogler_meentemeyer_2019, title={Projecting Urbanization and Landscape Change at Large Scale Using the FUTURES Model}, volume={8}, url={https://doi.org/10.3390/land8100144}, DOI={10.3390/land8100144}, abstractNote={Increasing population and rural to urban migration are accelerating urbanization globally, permanently transforming natural systems over large extents. Modelling landscape change over large regions, however, presents particular challenges due to local-scale variations in social and environmental factors that drive land change. We simulated urban development across the South Atlantic States (SAS), a region experiencing rapid population growth and urbanization, using FUTURES—an open source land change model that uses demand for development, local development suitability factors, and a stochastic patch growing algorithm for projecting alternative futures of urban form and landscape change. New advances to the FUTURES modelling framework allow for high resolution projections over large spatial extents by leveraging parallel computing. We simulated the adoption of different urban growth strategies that encourage settlement densification in the SAS as alternatives to the region’s increasing sprawl. Evaluation of projected patterns indicate a 15% increase in urban lands by 2050 given a status quo development scenario compared to a 14.8% increase for the Infill strategy. Status quo development resulted in a 3.72% loss of total forests, 2.97% loss of highly suitable agricultural land, and 3.69% loss of ecologically significant lands. An alternative Infill scenario resulted in similar losses of total forest (3.62%) and ecologically significant lands (3.63%) yet consumed less agricultural lands (1.23% loss). Moreover, infill development patterns differed qualitatively from the status quo and resulted in less fragmentation of the landscape.}, number={10}, journal={Land}, publisher={MDPI AG}, author={Berkel, Derek Van and Shashidharan, Ashwin and Mordecai, Rua and Vatsavai, Raju and Petrasova, Anna and Petras, Vaclav and Mitasova, Helena and Vogler, John and Meentemeyer, Ross}, year={2019}, month={Sep}, pages={144} }
 @article{pickard_meentemeyer_2019, title={Validating land change models based on configuration disagreement}, volume={77}, ISSN={["1873-7587"]}, DOI={10.1016/j.compenvurbsys.2019.101366}, abstractNote={Land change models are increasingly being employed to predict future landscapes and influence policy and decision-making. To ensure the highest model accuracy, validation methods have become commonplace following a land change simulation. The most common validation method employed uses quantity and allocation disagreement. However, these current measures may not account for differences in the configurations of land change, placing them in potential conflict with the principals of heterogeneity and spatial patterning of landscape ecology. We develop a new metric, termed configuration disagreement, designed to focus on the size, shape, and complexity of land change simulations. Using this metric, we demonstrate the value of including errors of configuration disagreement – in addition to quantity and allocation error – in the assessment of land change models. Four computational experiments of land change that vary only in spatial pattern are developed using the FUTURES land change model. For each experiment, configuration disagreement and the traditional validation metrics are computed simultaneously. Results indicate that models validated only with consideration of quantity and allocation error may misrepresent, or not fully account for, spatial patterns of landscape change. The research objective will ultimately guide which component, or components, of model disagreement are most critical for consideration. Yet, our work reveals why it may be more helpful to validate simulations in terms of configuration accuracy. Specifically, if a study requires accurately modeling the spatial patterns and arrangements of land cover. Configuration disagreement could add critical information with respect to a model's simulated changes in size, shape, and spatial arrangements, and possibly enhance ecologically meaningful land change science.}, journal={COMPUTERS ENVIRONMENT AND URBAN SYSTEMS}, author={Pickard, Brian R. and Meentemeyer, Ross K.}, year={2019}, month={Sep} }
 @article{tabrizian_baran_smith_meentemeyer_2018, title={Exploring perceived restoration potential of urban green enclosure through immersive virtual environments}, volume={55}, ISSN={["1522-9610"]}, DOI={10.1016/j.jenvp.2018.01.001}, abstractNote={We examine the effects of green space enclosure on perceived restorativeness and perceived safety in two urban setting, and in turn, we explore the extent to which perceived safety mediates the casual pathways between enclosure and perceived restorativeness. Photorealistic 360o panoramas taken from a plaza and a park were digitally manipulated to create 18 immersive virtual environment (IVE) stimuli that depict variations of spatial arrangement and permeability of vegetation. Using a head-mounted display, 87 participants viewed the IVEs and rated each on perceived restorativeness and perceived safety. Anova results revealed a significant interaction between enclosure indicators and setting type. Spatial arrangement positively affected perceived restorativeness in urban plaza while in park setting, spatial arrangement and permeability inversely influenced both perceived restorativeness and safety. Perception of safety mediated the causal pathways between enclosure and perceived restorativeness with more pronounced effects in park setting.}, journal={JOURNAL OF ENVIRONMENTAL PSYCHOLOGY}, author={Tabrizian, Payam and Baran, Perver K. and Smith, William R. and Meentemeyer, Ross K.}, year={2018}, month={Feb}, pages={99–109} }
 @article{shashidharan_vatsavai_meentemeyer_2018, title={FUTURES-DPE: Towards Dynamic Provisioning and Execution of Geosimulations in HPC environments}, DOI={10.1145/3274895.3274948}, abstractNote={Geosimulations using computer simulation models provideGI scientists an effective way to study complex geographic phenomena and predict future outcomes. Typically, geosimulations are developed to execute in an HPC environment with parallel and distributed execution capabilities. However, traditional HPC environments limit these simulations to a static runtime environment, where resources for execution must be decided before execution. Traditional simulation approaches such as a data parallel approach assigns fixed computing resources on every unit of data (e.g., a tile or a county). However, in many practical situations, a user may want to assign additional computing resources to speedup or perform more computation in a specific region. For example, in an urban growth model (UGM) simulation, to explore the outcomes of changes due to urban policy in a tile or a group of tiles at a given time-step, an urban geographer may want to assign more computing resources to those group of tiles to quickly determine impacts of policy on urbanization. In the absence of a dynamic resource allocation mechanism, the utility of a geosimulation to explore what-if scenarios on-the-fly is limited to pre-allocated computing resources. Thus, to effectively leverage existing resources, we first design a co-scheduling approach for geosimulations in a resource constrained HPC environment. We then present a second design for a geosimulation which allows dynamic provisioning of resources in an HPC environment based on run-time users' demands. Finally, to demonstrate the utility of the two approaches we modify the FUTURES geosimulation to support computationally expensive high-resolution simulation in regions of interest (ROIs) as specified by a user using the FUTURES-DPE framework.}, journal={26TH ACM SIGSPATIAL INTERNATIONAL CONFERENCE ON ADVANCES IN GEOGRAPHIC INFORMATION SYSTEMS (ACM SIGSPATIAL GIS 2018)}, author={Shashidharan, Ashwin and Vatsavai, Ranga Raju and Meentemeyer, Ross K.}, year={2018}, pages={464–467} }
 @article{singh_chen_smart_gray_meentemeyer_2018, title={Intra-annual phenology for detecting understory plant invasion in urban forests}, volume={142}, ISSN={0924-2716}, url={http://dx.doi.org/10.1016/J.ISPRSJPRS.2018.05.023}, DOI={10.1016/J.ISPRSJPRS.2018.05.023}, abstractNote={Accurate and repeatable mapping of biological plant invasions is essential to develop successful management strategies for conserving native biodiversity. While overstory invasive plants have been successfully detected and mapped using multiple methods, understory invasive detection remains a challenge, particularly in dense forested environments. Very few studies have utilized an approach that identifies and aligns the acquisition timing of remote sensing imagery with peak phenological differences between understory and overstory vegetation types. We investigated this opportunity by analyzing a monthly time-series of 2011 Landsat TM data to identify acquisition periods with the highest phenological differences between understory and overstory vegetation for detecting the spatial distribution of the exotic understory plant Ligustrum sinense Lour., a rapidly spreading invader in urbanizing regions of the southeastern United States. We used vegetation indices (VI) to establish intra-annual phenological trends for L. sinense, evergreen forest, and deciduous forest located in Mecklenburg County, North Carolina, USA. We developed Random Forest (RF) models to detect L. sinense from those time steps exhibiting the highest phenological differences. We assessed the relative contribution of VI and topographic indices (TI) to the detection of L. sinense. We compared the top performing models and used the best overall model to produce a map of L. sinense for the study area. RF models that included VI, TI, and Landsat TM bands for March 13 and 29, 2011 (the periods with highest detected phenological differences), produced the highest overall accuracy and Kappa estimates, outperforming the combination of VI and TI by 8.5% in accuracy and 20.5% in Kappa. The top performing model from the RF produced a Kappa of 0.75. Our findings suggest that selecting remote sensing data for a period when phenological differences between L. sinense and forest types are at their peak can improve the detection and mapping of L. sinense.}, journal={ISPRS Journal of Photogrammetry and Remote Sensing}, publisher={Elsevier BV}, author={Singh, Kunwar K. and Chen, Yin-Hsuen and Smart, Lindsey and Gray, Josh and Meentemeyer, Ross K.}, year={2018}, month={Aug}, pages={151–161} }
 @article{tonini_jones_miranda_cobb_sturtevant_meentemeyer_2018, title={Modeling epidemiological disturbances in LANDIS-II}, volume={41}, ISSN={["1600-0587"]}, url={http://dx.doi.org/10.1111/ecog.03539}, DOI={10.1111/ecog.03539}, abstractNote={Forest landscape simulation models (FLSMs) – often used to understand and project forest dynamics over space and time in response to environmental disturbance – have rarely included realistic epidemiological processes of plant disease transmission and impacts. Landscape epidemiological models, by contrast, frequently treat forest ecosystems as static or make simple assumptions regarding ecosystem change following disease. Here we present the Base Epidemiological Disturbance Agent (EDA) extension that allows users of the LANDIS‐II FLSM to simulate forest pathogen spread and host mortality within a spatially explicit forest simulation. EDA enables users to investigate forest pathogen spread and impacts over large landscapes (> 105 ha) and long time periods. We evaluate the model extension using Phytophthora ramorum as a case study of an invasive plant pathogen causing emerging infectious disease and considerable tree mortality in California. EDA will advance the utility of LANDIS‐II and forest disease modeling in general.}, number={12}, journal={ECOGRAPHY}, author={Tonini, Francesco and Jones, Chris and Miranda, Brian R. and Cobb, Richard C. and Sturtevant, Brian R. and Meentemeyer, Ross K.}, year={2018}, month={Dec}, pages={2038–2044} }
 @article{simler_metz_frangioso_meentemeyer_rizzo_2018, title={Novel disturbance interactions between fire and an emerging disease impact survival and growth of resprouting trees}, volume={99}, ISSN={["1939-9170"]}, DOI={10.1002/ecy.2493}, abstractNote={Abstract}, number={10}, journal={ECOLOGY}, author={Simler, Allison B. and Metz, Margaret R. and Frangioso, Kerri M. and Meentemeyer, Ross K. and Rizzo, David M.}, year={2018}, month={Oct}, pages={2217–2229} }
 @article{burke_peterson_sawyer_moorman_serenari_meentemeyer_deperno_2018, title={Predicting private landowner hunting access decisions and hunter density}, volume={24}, ISSN={1087-1209 1533-158X}, url={http://dx.doi.org/10.1080/10871209.2018.1545147}, DOI={10.1080/10871209.2018.1545147}, abstractNote={ABSTRACT Urbanization and shifting landowner demographics are changing how and where hunting occurs. We surveyed nonindustrial private landowners (N = 1,843) in North Carolina, USA to examine how demographics and land-use predict whether hunting occurred and hunter density. The optimal logistic regression model correctly predicted whether hunting occurred on 96% of properties. Larger properties, male property ownership, longer ownership tenure, income generation from a property, and landowners originating from rural environments were positively related to whether a property was hunted. Properties with older landowners and properties surrounded by greater housing and road density were less likely to be hunted. Hunter density declined with property size, longer ownership tenure, and the presence of a landowner or family member(s) hunting the property. In the future, increases in hunter density on small properties may facilitate wildlife management through hunting as landscapes become more urbanized.}, number={2}, journal={Human Dimensions of Wildlife}, publisher={Informa UK Limited}, author={Burke, Conner R. and Peterson, M. Nils and Sawyer, David T. and Moorman, Christopher E. and Serenari, Christopher and Meentemeyer, Ross K. and DePerno, Christopher S.}, year={2018}, month={Nov}, pages={99–115} }
 @article{van berkel_tabrizian_dorning_smart_newcomb_mehaffey_neale_meentemeyer_2018, title={Quantifying the visual-sensory landscape qualities that contribute to cultural ecosystem services using social media and LiDAR}, volume={31}, ISSN={["2212-0416"]}, url={http://dx.doi.org/10.1016/j.ecoser.2018.03.022}, DOI={10.1016/j.ecoser.2018.03.022}, abstractNote={Landscapes are increasingly recognized for providing valuable cultural ecosystem services with numerous non-material benefits by serving as places of rest, relaxation, and inspiration that ultimately improve overall mental health and physical well-being. Maintaining and enhancing these valuable benefits through targeted management and conservation measures requires understanding the spatial and temporal determinants of perceived landscape values. Content contributed through mobile technologies and the web are emerging globally, providing a promising data source for localizing and assessing these landscape benefits. These georeferenced data offer rich in situ qualitative information through photos and comments that capture valued and special locations across large geographic areas. We present a novel method for mapping and modeling landscape values and perceptions that leverages viewshed analysis of georeferenced social media data. Using a high resolution LiDAR (Light Detection and Ranging) derived digital surface model, we are able to evaluate landscape characteristics associated with the visual-sensory qualities of outdoor recreationalists. Our results show the importance of historical monuments and attractions in addition to specific environmental features which are appreciated by the public. Evaluation of photo-image content highlights the opportunity of including temporally and spatially variable visual-sensory qualities in cultural ecosystem services (CES) evaluation like the sights, sounds and smells of wildlife and weather phenomena.}, journal={ECOSYSTEM SERVICES}, author={Van Berkel, Derek B. and Tabrizian, Payam and Dorning, Monica A. and Smart, Lindsey and Newcomb, Doug and Mehaffey, Megan and Neale, Anne and Meentemeyer, Ross K.}, year={2018}, month={Jun}, pages={326–335} }
 @article{sanchez_smith_terando_sun_meentemeyer_2018, title={Spatial Patterns of Development Drive Water Use}, volume={54}, ISSN={["1944-7973"]}, url={https://doi.org/10.1002/2017WR021730}, DOI={10.1002/2017wr021730}, abstractNote={Abstract}, number={3}, journal={WATER RESOURCES RESEARCH}, publisher={American Geophysical Union (AGU)}, author={Sanchez, G. M. and Smith, J. W. and Terando, A. and Sun, G. and Meentemeyer, R. K.}, year={2018}, month={Mar}, pages={1633–1649} }
 @article{harmon_petrasova_petras_mitasova_meentemeyer_2018, title={Tangible topographic modeling for landscape architects}, volume={16}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85044342339&partnerID=MN8TOARS}, DOI={10.1177/1478077117749959}, abstractNote={ We present Tangible Landscape—a technology for rapidly and intuitively designing landscapes informed by geospatial modeling, analysis, and simulation. It is a tangible interface powered by a geographic information system that gives three-dimensional spatial data an interactive, physical form so that users can naturally sense and shape it. Tangible Landscape couples a physical and a digital model of a landscape through a real-time cycle of physical manipulation, three-dimensional scanning, spatial computation, and projected feedback. Natural three-dimensional sketching and real-time analytical feedback should aid landscape architects in the design of high performance landscapes that account for physical and ecological processes. We conducted a series of studies to assess the effectiveness of tangible modeling for landscape architects. Landscape architecture students, academics, and professionals were given a series of fundamental landscape design tasks—topographic modeling, cut-and-fill analysis, and water flow modeling. We assessed their performance using qualitative and quantitative methods including interviews, raster statistics, morphometric analyses, and geospatial simulation. With tangible modeling, participants built more accurate models that better represented morphological features than they did with either digital or analog hand modeling. When tangibly modeling, they worked in a rapid, iterative process informed by real-time geospatial analytics and simulations. With the aid of real-time simulations, they were able to quickly understand and then manipulate how complex topography controls the flow of water. }, number={1}, journal={International Journal of Architectural Computing}, author={Harmon, B. A. and Petrasova, Anna and Petras, Vaclav and Mitasova, Helena and Meentemeyer, Ross K.}, year={2018}, pages={4–21} }
 @article{singh_madden_gray_meentemeyer_2018, title={The managed clearing: An overlooked land-cover type in urbanizing regions?}, volume={13}, ISSN={["1932-6203"]}, DOI={10.1371/journal.pone.0192822}, abstractNote={Urban ecosystem assessments increasingly rely on widely available map products, such as the U.S. Geological Service (USGS) National Land Cover Database (NLCD), and datasets that use generic classification schemes to detect and model large-scale impacts of land-cover change. However, utilizing existing map products or schemes without identifying relevant urban class types such as semi-natural, yet managed land areas that account for differences in ecological functions due to their pervious surfaces may severely constrain assessments. To address this gap, we introduce the managed clearings land-cover type–semi-natural, vegetated land surfaces with varying degrees of management practices–for urbanizing landscapes. We explore the extent to which managed clearings are common and spatially distributed in three rapidly urbanizing areas of the Charlanta megaregion, USA. We visually interpreted and mapped fine-scale land cover with special attention to managed clearings using 2012 U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) images within 150 randomly selected 1-km2 blocks in the cities of Atlanta, Charlotte, and Raleigh, and compared our maps with National Land Cover Database (NLCD) data. We estimated the abundance of managed clearings relative to other land use and land cover types, and the proportion of land-cover types in the NLCD that are similar to managed clearings. Our study reveals that managed clearings are the most common land cover type in these cities, covering 28% of the total sampled land area– 6.2% higher than the total area of impervious surfaces. Managed clearings, when combined with forest cover, constitutes 69% of pervious surfaces in the sampled region. We observed variability in area estimates of managed clearings between the NAIP-derived and NLCD data. This suggests using high-resolution remote sensing imagery (e.g., NAIP) instead of modifying NLCD data for improved representation of spatial heterogeneity and mapping of managed clearings in urbanizing landscapes. Our findings also demonstrate the need to more carefully consider managed clearings and their critical ecological functions in landscape- to regional-scale studies of urbanizing ecosystems.}, number={2}, journal={PLOS ONE}, author={Singh, Kunwar K. and Madden, Marguerite and Gray, Josh and Meentemeyer, Ross K.}, year={2018}, month={Feb} }
 @article{singh_bianchetti_chen_meentemeyer_2017, title={Assessing effect of dominant land-cover types and pattern on urban forest biomass estimated using LiDAR metrics}, volume={20}, DOI={10.1007/s11252-016-0591-8}, number={2}, journal={Urban Ecosystems}, author={Singh, K. K. and Bianchetti, R. A. and Chen, G. and Meentemeyer, Ross K.}, year={2017}, pages={265–275} }
 @article{chen_he_de santis_li_cobb_meentemeyer_2017, title={Assessing the impact of emerging forest disease on wildfire using Landsat and KOMPSAT-2 data}, volume={195}, ISSN={0034-4257}, url={http://dx.doi.org/10.1016/J.RSE.2017.04.005}, DOI={10.1016/J.RSE.2017.04.005}, abstractNote={Environmental disturbance regimes are more frequently being altered by historically novel events and disturbance interactions, which may trigger reorganizations of new ecosystem states and processes. Here we examine synergies between emerging forest disease and wildfire to determine whether disease outbreak changes environmental drivers of burn severity using sudden oak death and the basin complex fire in California as a case study of novel disturbance interaction. We mapped the spatial distribution of sudden oak death tree mortality using a new object-based filter with 1.0 m resolution KOMPSAT-2 images. We integrated these data with a physical simulation model of burn severity informed by post-fire Landsat data. Model performance varied across stages of disease establishment (early, middle and late) with stronger relationships occurring during later stages of disease progression. Multiscale statistical analysis of environmental drivers of burn severity in diseased compared to healthy forests showed that sudden oak death tree mortality altered relationships between burn severity and the biophysical environment. Specifically, compared to the healthy forests, those affected by disease exhibited higher landscape heterogeneity at smaller spatial scales (e.g., 25 and 50 m), which has been associated with decreased burn severity in the literature. Our results showed the opposite pattern. That is, a disease-affected landscape comprising less connected patches and higher patch shape complexity was more likely to experience greater burn severity. This suggests that disease-caused increases in surface fuels may have reduced the landscape's resistance to fire and in turn increased burn severity in forest patches neighboring disease-impacted forests.}, journal={Remote Sensing of Environment}, publisher={Elsevier BV}, author={Chen, Gang and He, Yinan and De Santis, Angela and Li, Guosheng and Cobb, Richard and Meentemeyer, Ross K.}, year={2017}, month={Jun}, pages={218–229} }
 @article{smith_smart_dorning_dupéy_méley_meentemeyer_2017, title={Bayesian methods to estimate urban growth potential}, volume={163}, ISSN={0169-2046}, url={http://dx.doi.org/10.1016/J.LANDURBPLAN.2017.03.004}, DOI={10.1016/J.LANDURBPLAN.2017.03.004}, abstractNote={Urban growth often influences the production of ecosystem services. The impacts of urbanization on landscapes can subsequently affect landowners’ perceptions, values and decisions regarding their land. Within land-use and land-change research, very few models of dynamic landscape-scale processes like urbanization incorporate empirically-grounded landowner decision-making processes. Very little attention has focused on the heterogeneous decision-making processes that aggregate to influence broader-scale patterns of urbanization. We examine the land-use tradeoffs faced by individual landowners in one of the United States’ most rapidly urbanizing regions − the urban area surrounding Charlotte, North Carolina. We focus on the land-use decisions of non-industrial private forest owners located across the region’s development gradient. A discrete choice experiment is used to determine the critical factors influencing individual forest owners’ intent to sell their undeveloped properties across a series of experimentally varied scenarios of urban growth. Data are analyzed using a hierarchical Bayesian approach. The estimates derived from the survey data are used to modify a spatially-explicit trend-based urban development potential model, derived from remotely-sensed imagery and observed changes in the region’s socioeconomic and infrastructural characteristics between 2000 and 2011. This modeling approach combines the theoretical underpinnings of behavioral economics with spatiotemporal data describing a region’s historical development patterns. By integrating empirical social preference data into spatially-explicit urban growth models, we begin to more realistically capture processes as well as patterns that drive the location, magnitude and rates of urban growth.}, journal={Landscape and Urban Planning}, publisher={Elsevier BV}, author={Smith, Jordan W. and Smart, Lindsey S. and Dorning, Monica A. and Dupéy, Lauren Nicole and Méley, Andréanne and Meentemeyer, Ross K.}, year={2017}, month={Jul}, pages={1–16} }
 @article{pickard_gray_meentemeyer_2017, title={Comparing Quantity, Allocation and Configuration Accuracy of Multiple Land Change Models}, volume={6}, ISSN={["2073-445X"]}, DOI={10.3390/land6030052}, abstractNote={The growing numbers of land change models makes it difficult to select a model at the beginning of an analysis, and is often arbitrary and at the researcher’s discretion. How to select a model at the beginning of an analysis, when multiple are suitable, represents a critical research gap currently understudied, where trade-offs of choosing one model over another are often unknown. Repeatable methods are needed to conduct cross-model comparisons to understand the trade-offs among models when the same calibration and validation data are used. Several methods to assess accuracy have been proposed that emphasize quantity and allocation, while overlooking the accuracy with which a model simulates the spatial configuration (e.g., size and shape) of map categories across landscapes. We compared the quantity, allocation, and configuration accuracy of four inductive pattern-based spatial allocation land change models (SLEUTH, GEOMOD, Land Change Modeler (LCM), and FUTURES). We simulated urban development with each model using identical input data from ten counties surrounding the growing region of Charlotte, North Carolina. Maintaining the same input data, such as land cover, drivers of change, and projected quantity of change, reduces differences in model inputs and allows for focus on trade-offs in different types of model accuracy. Results suggest that these four land change models produce representations of urban development with substantial variance, where some models may better simulate quantity and allocation at the trade-off of configuration accuracy, and vice versa. Trade-offs in accuracy exist with respect to the amount, spatial allocation, and landscape configuration of each model. This comparison exercise illustrates the range of accuracies for these models, and demonstrates the need to consider all three types of accuracy when assessing land change model’s projections.}, number={3}, journal={LAND}, author={Pickard, Brian and Gray, Joshua and Meentemeyer, Ross}, year={2017}, month={Sep} }
 @article{pickard_van berkel_petrasova_meentemeyer_2017, title={Forecasts of urbanization scenarios reveal trade-offs between landscape change and ecosystem services}, volume={32}, ISSN={["1572-9761"]}, DOI={10.1007/s10980-016-0465-8}, abstractNote={Expansion of urban settlements has caused observed declines in ecosystem services (ES) globally, further stressing the need for informed urban development and policies. Incorporating ES concepts into the decision making process has been shown to support resilient and functional ecosystems. Coupling land change and ES models allows for insights into the impacts and anticipated trade-offs of specific policy decisions. The spatial configuration of urbanization likely influences the delivery and production of ES. When considering multiple ES simultaneously, improving the production of one ecosystem service often results in the decrease in the provision of other ES, giving rise to trade-offs. We examine the impact of three urban growth scenarios on several ES to determine the degree to which spatial configuration of urbanization and the development of natural land cover impacts these services over 25 years. We couple land change and ES models to examine impacts to carbon sequestration, surface water-run off, nitrogen and phosphorus export, organic farming and camping site suitability, to determine trade-offs among the six ES associated with each spatial configuration for western North Carolina. Consequences of urban configurations are dramatic, with degraded ES across all scenarios and substantial variation depending on urban pattern, revealing trade-offs. Counter-intuitive trade-offs between carbon sequestration and lands available for organic farming and camping were observed, suggesting that no configurations result in mutual benefits for all ES. By understanding trade-offs associated with urban configurations, decision makers can identify ES critical to an area and promote configurations that enhance those.}, number={3}, journal={LANDSCAPE ECOLOGY}, author={Pickard, Brian R. and Van Berkel, Derek and Petrasova, Anna and Meentemeyer, Ross K.}, year={2017}, month={Mar}, pages={617–634} }
 @article{davis_thill_meentemeyer_2017, title={Multi-temporal trajectories of landscape change explain forest biodiversity in urbanizing ecosystems}, volume={32}, ISSN={["1572-9761"]}, DOI={10.1007/s10980-017-0541-8}, number={9}, journal={LANDSCAPE ECOLOGY}, author={Davis, Amy J. S. and Thill, Jean-Claude and Meentemeyer, Ross K.}, year={2017}, month={Sep}, pages={1789–1803} }
 @article{smith_dorning_shoemaker_meley_dupey_meentemeyer_2017, title={Payments for carbon sequestration to alleviate development pressure in a rapidly urbanizing region}, volume={63}, DOI={10.5849/forsci.2016-084r1}, number={3}, journal={Forest Science}, author={Smith, J. W. and Dorning, M. and Shoemaker, D. A. and Meley, A. and Dupey, L. N. and Meentemeyer, Ross K.}, year={2017}, pages={270–282} }
 @article{tonini_shoemaker_petrasova_harmon_petras_cobb_mitasova_meentemeyer_2017, title={Tangible geospatial modeling for collaborative solutions to invasive species management}, volume={92}, ISSN={["1873-6726"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85014320386&partnerID=MN8TOARS}, DOI={10.1016/j.envsoft.2017.02.020}, abstractNote={Managing landscape-scale environmental problems, such as biological invasions, can be facilitated by integrating realistic geospatial models with user-friendly interfaces that stakeholders can use to make critical management decisions. However, gaps between scientific theory and application have typically limited opportunities for model-based knowledge to reach the stakeholders responsible for problem-solving. To address this challenge, we introduce Tangible Landscape, an open-source participatory modeling tool providing an interactive, shared arena for consensus-building and development of collaborative solutions for landscape-scale problems. Using Tangible Landscape, stakeholders gather around a geographically realistic 3D visualization and explore management scenarios with instant feedback; users direct model simulations with intuitive tangible gestures and compare alternative strategies with an output dashboard. We applied Tangible Landscape to the complex problem of managing the emerging infectious disease, sudden oak death, in California and explored its potential to generate co-learning and collaborative management strategies among actors representing stakeholders with competing management aims.}, journal={ENVIRONMENTAL MODELLING & SOFTWARE}, author={Tonini, Francesco and Shoemaker, Douglas and Petrasova, Anna and Harmon, Brendan and Petras, Vaclav and Cobb, Richard C. and Mitasova, Helena and Meentemeyer, Ross K.}, year={2017}, month={Jun}, pages={176–188} }
 @article{chen_ozelkan_singh_zhou_brown_meentemeyer_2017, title={Uncertainties in mapping forest carbon in urban ecosystems}, volume={187}, ISSN={["1095-8630"]}, DOI={10.1016/j.jenvman.2016.11.062}, abstractNote={Spatially explicit urban forest carbon estimation provides a baseline map for understanding the variation in forest vertical structure, informing sustainable forest management and urban planning. While high-resolution remote sensing has proven promising for carbon mapping in highly fragmented urban landscapes, data cost and availability are the major obstacle prohibiting accurate, consistent, and repeated measurement of forest carbon pools in cities. This study aims to evaluate the uncertainties of forest carbon estimation in response to the combined impacts of remote sensing data resolution and neighborhood spatial patterns in Charlotte, North Carolina. The remote sensing data for carbon mapping were resampled to a range of resolutions, i.e., LiDAR point cloud density - 5.8, 4.6, 2.3, and 1.2 pt s/m2, aerial optical NAIP (National Agricultural Imagery Program) imagery - 1, 5, 10, and 20 m. Urban spatial patterns were extracted to represent area, shape complexity, dispersion/interspersion, diversity, and connectivity of landscape patches across the residential neighborhoods with built-up densities from low, medium-low, medium-high, to high. Through statistical analyses, we found that changing remote sensing data resolution introduced noticeable uncertainties (variation) in forest carbon estimation at the neighborhood level. Higher uncertainties were caused by the change of LiDAR point density (causing 8.7-11.0% of variation) than changing NAIP image resolution (causing 6.2-8.6% of variation). For both LiDAR and NAIP, urban neighborhoods with a higher degree of anthropogenic disturbance unveiled a higher level of uncertainty in carbon mapping. However, LiDAR-based results were more likely to be affected by landscape patch connectivity, and the NAIP-based estimation was found to be significantly influenced by the complexity of patch shape.}, journal={JOURNAL OF ENVIRONMENTAL MANAGEMENT}, author={Chen, Gang and Ozelkan, Emre and Singh, Kunwar K. and Zhou, Jun and Brown, Marilyn R. and Meentemeyer, Ross K.}, year={2017}, month={Feb}, pages={229–238} }
 @article{mcalister_moorman_meentemeyer_fuller_howell_deperno_2017, title={Using Landscape Characteristics to Predict Distribution of Temperate-Breeding Canada Geese}, volume={16}, ISSN={["1938-5412"]}, DOI={10.1656/058.016.0201}, abstractNote={Abstract 
 Accurate estimates of species' distributions are needed to ensure that conservation-planning efforts are directed at appropriate areas. Since the early 1980s, temperate-breeding populations of Branta canadensis (Canada Goose) have increased, yet reliable estimates of the species' distribution are lacking in many regions. Our objective was to identify the landcover features that best predicted Canada Goose distribution. In April 2015, we surveyed 300 one-km2 plots across North Carolina and observed 449 Canada Geese. We quantified percent coverage of 7 continuous landcover variables at 5 different spatial extents for each of the 300 plots. We fit logistic regression models using presence and absence at the 300 plots as the dependent variable and percent-cover covariates as independent variables. The best model for predicting Canada Goose presence included percent pasture within the 9 km2 surrounding the survey plot and percent open water within the 1-km2 survey plot. The probability of Canada Goose presence increased with increasing percent open water and percent pasture, albeit at different spatial extents, which provided important cover and food resources, respectively. Our approach using remote-sensing data to accurately predict Canada Goose presence across a large spatial extent can be employed to determine distributions for other easily surveyed, widely distributed species.}, number={2}, journal={SOUTHEASTERN NATURALIST}, author={McAlister, Mark A. and Moorman, Christopher E. and Meentemeyer, Ross K. and Fuller, Joseph C. and Howell, Douglas L. and DePerno, Christopher S.}, year={2017}, month={Jun}, pages={127–139} }
 @article{wang_thill_meentemeyer_2017, title={Who Wants More Open Space? Study of Willingness to Be Taxed to Preserve Open Space in an Urban Environment}, volume={24}, ISBN={["978-981-10-0097-3"]}, ISSN={["2199-5974"]}, DOI={10.1007/978-981-10-0099-7_7}, abstractNote={The presence of open space is often regarded as one of the considerations that enhance the quality of the living experience of populations in urban regions and cities and that enhance the long-term sustainability of urban environments. However, the provision of open space comes at a price. This chapter examines people’s willingness to support tax increases for the preservation of open space in a fast-growing urban area where pressure to marketize land to its highest and best use is high. In particular, we study how a respondent’s socioeconomic characteristics influence their willingness to pay in the city of Charlotte, United States. We use and analyze detailed survey data at the household level collected from a phone interview survey conducted in the Charlotte, North Carolina, area. The econometric models allow us to identify a systematic response bias which arises from protest zeros and respondents’ tendency to underreport their willingness. Results show that a respondent’s willingness is affected by the respondent’s gender, age, ethnicity, and level of educational attainment. An individual is more willing to support if the individual is younger, Caucasian, and has reached a higher level of education. Individual behaviors are aggregated to obtain the regional level of willingness. Finally, results reveal that respondents have a well-marked tendency to underreport their willingness to support and report protest zeros in the survey.}, journal={SOCIOECONOMIC ENVIRONMENTAL POLICIES AND EVALUATIONS IN REGIONAL SCIENCE: ESSAYS IN HONOR OF YOSHIRO HIGANO}, author={Wang, Chunhua and Thill, Jean-Claude and Meentemeyer, Ross}, year={2017}, pages={125–146} }
 @article{davis_singh_thill_meentemeyer_2016, title={Accounting for residential propagule pressure improves prediction of urban plant invasion}, volume={7}, ISSN={["2150-8925"]}, DOI={10.1002/ecs2.1232}, abstractNote={Abstract}, number={3}, journal={ECOSPHERE}, author={Davis, Amy J. S. and Singh, Kunwar K. and Thill, Jean-Claude and Meentemeyer, Ross K.}, year={2016}, month={Mar} }
 @article{serra-diaz_franklin_dillon_syphard_davis_meentemeyer_2016, title={California forests show early indications of both range shifts and local persistence under climate change}, volume={25}, ISSN={["1466-8238"]}, DOI={10.1111/geb.12396}, abstractNote={Abstract}, number={2}, journal={GLOBAL ECOLOGY AND BIOGEOGRAPHY}, author={Serra-Diaz, Josep M. and Franklin, Janet and Dillon, Whalen W. and Syphard, Alexandra D. and Davis, Frank W. and Meentemeyer, Ross K.}, year={2016}, month={Feb}, pages={164–175} }
 @misc{johnstone_allen_franklin_frelich_harvey_higuera_mack_meentemeyer_metz_perry_et al._2016, title={Changing disturbance regimes, ecological memory, and forest resilience}, volume={14}, ISSN={["1540-9309"]}, DOI={10.1002/fee.1311}, abstractNote={Ecological memory is central to how ecosystems respond to disturbance and is maintained by two types of legacies – information and material. Species life‐history traits represent an adaptive response to disturbance and are an information legacy; in contrast, the abiotic and biotic structures (such as seeds or nutrients) produced by single disturbance events are material legacies. Disturbance characteristics that support or maintain these legacies enhance ecological resilience and maintain a “safe operating space” for ecosystem recovery. However, legacies can be lost or diminished as disturbance regimes and environmental conditions change, generating a “resilience debt” that manifests only after the system is disturbed. Strong effects of ecological memory on post‐disturbance dynamics imply that contingencies (effects that cannot be predicted with certainty) of individual disturbances, interactions among disturbances, and climate variability combine to affect ecosystem resilience. We illustrate these concepts and introduce a novel ecosystem resilience framework with examples of forest disturbances, primarily from North America. Identifying legacies that support resilience in a particular ecosystem can help scientists and resource managers anticipate when disturbances may trigger abrupt shifts in forest ecosystems, and when forests are likely to be resilient.}, number={7}, journal={FRONTIERS IN ECOLOGY AND THE ENVIRONMENT}, author={Johnstone, Jill F. and Allen, Craig D. and Franklin, Jerry F. and Frelich, Lee E. and Harvey, Brian J. and Higuera, Philip E. and Mack, Michelle C. and Meentemeyer, Ross K. and Metz, Margaret R. and Perry, George L. W. and et al.}, year={2016}, month={Sep}, pages={369–378} }
 @article{zanten_van berkel_meentemeyer_smith_tieskens_verburg_2016, title={Continental-scale quantification of landscape values using social media data}, volume={113}, ISSN={["1091-6490"]}, DOI={10.1073/pnas.1614158113}, abstractNote={Significance}, number={46}, journal={PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA}, author={Zanten, Boris T. and Van Berkel, Derek B. and Meentemeyer, Ross K. and Smith, Jordan W. and Tieskens, Koen F. and Verburg, Peter H.}, year={2016}, month={Nov}, pages={12974–12979} }
 @article{haas_cushman_dillon_rank_rizzo_meentemeyer_2016, title={Effects of individual, community, and landscape drivers on the dynamics of a wildland forest epidemic}, volume={97}, DOI={10.1890/15-0767}, abstractNote={The challenges posed by observing host–pathogen–environment interactions across large geographic extents and over meaningful time scales limit our ability to understand and manage wildland epidemics. We conducted a landscape-scale, longitudinal study designed to analyze the dynamics of sudden oak death (an emerging forest disease caused by Phytophthora ramorum) across hierarchical levels of ecological interactions, from individual hosts up to the community and across the broader landscape. From 2004 to 2011, we annually assessed disease status of 732 coast live oak, 271 black oak, and 122 canyon live oak trees in 202 plots across a 275-km2 landscape in central California. The number of infected oak stems steadily increased during the eight-year study period. A survival analysis modeling framework was used to examine which level of ecological heterogeneity best predicted infection risk of susceptible oak species, considering variability at the level of individuals (species identity, stem size), the community (host density, inoculum load, and species richness), and the landscape (seasonal climate variability, habitat connectivity, and topographic gradients). After accounting for unobserved risk shared among oaks in the same plot, survival models incorporating heterogeneity across all three levels better predicted oak infection than did models focusing on only one level. We show that larger oak trees (especially coast live oak) were more susceptible, and that interannual variability in inoculum production by the highly infectious reservoir host, California bay laurel, more strongly influenced disease risk than simply the density of this important host. Concurrently, warmer and wetter rainy-season conditions in consecutive years intensified infection risk, presumably by creating a longer period of inoculum build-up and increased probability of pathogen spillover from bay laurel to oaks. Despite the presence of many alternate host species, we found evidence of pathogen dilution, where less competent hosts in species-rich communities reduce pathogen transmission and overall risk of oak infection. These results identify key parameters driving the dynamics of emerging infectious disease in California woodlands, while demonstrating how multiple levels of ecological heterogeneity jointly determine epidemic trajectories in wildland settings.}, number={3}, journal={Ecology}, author={Haas, S. E. and Cushman, J. H. and Dillon, W. W. and Rank, N. E. and Rizzo, D. M. and Meentemeyer, Ross K.}, year={2016}, pages={649–660} }
 @article{karlin_vaclavik_chadwick_meentemeyer_2016, title={Habitat use by adult red wolves, Canis rufus, in an agricultural landscape, North Carolina, USA}, volume={41}, DOI={10.3106/041.041.0206}, abstractNote={Abstract. 
 We used a species distribution model to characterize habitat use by red wolves, Canis rufus, on the Albemarle Peninsula of North Carolina, USA. Using more than 4,000 VHF telemetry locations of 178 individual animals from 1999–2008, we quantified habitat use and modeled potential habitat suitability of red wolves. Areas of agriculture where secondary road density was high (up to 1 km/km2) and human population density was low (less than 1.67 individuals/km2) were most suitable. Our study supports the baseline knowledge of red wolf suitable habitat, and shows that red wolves will use habitats altered by humans and occupied by humans at low densities. This research represents the use of the most comprehensive red wolf VHF telemetry dataset for habitat suitability modeling to date, and the results should contribute to the growing knowledge of suitable red wolf habitat. This knowledge is critical to identifying future reintroduction sites and protecting the future of this species.}, number={2}, journal={Mammal Study}, author={Karlin, M. and Vaclavik, T. and Chadwick, J. and Meentemeyer, Ross K.}, year={2016}, pages={87–95} }
 @article{johnston_cohen_torok_meentemeyer_rank_2016, title={Host Phenology and Leaf Effects on Susceptibility of California Bay Laurel to Phytophthora ramorum}, volume={106}, ISSN={["1943-7684"]}, DOI={10.1094/phyto-01-15-0016-r}, abstractNote={ Spread of the plant pathogen Phytophthora ramorum, causal agent of the forest disease sudden oak death, is driven by a few competent hosts that support spore production from foliar lesions. The relationship between traits of a principal foliar host, California bay laurel (Umbellularia californica), and susceptibility to P. ramorum infection were investigated with multiple P. ramorum isolates and leaves collected from multiple trees in leaf-droplet assays. We examined whether susceptibility varies with season, leaf age, or inoculum position. Bay laurel susceptibility was highest during spring and summer and lowest in winter. Older leaves (>1 year) were more susceptible than younger ones (8 to 11 months). Susceptibility was greater at leaf tips and edges than the middle of the leaf. Leaf surfaces wiped with 70% ethanol were more susceptible to P. ramorum infection than untreated leaf surfaces. Our results indicate that seasonal changes in susceptibility of U. californica significantly influence P. ramorum infection levels. Thus, in addition to environmental variables such as temperature and moisture, variability in host plant susceptibility contributes to disease establishment of P. ramorum. }, number={1}, journal={PHYTOPATHOLOGY}, author={Johnston, Steven F. and Cohen, Michael F. and Torok, Tamas and Meentemeyer, Ross K. and Rank, Nathan E.}, year={2016}, month={Jan}, pages={47–55} }
 @article{tabrizian_petrasova_harmon_petras_mitasova_meentemeyer_2016, title={Immersive Tangible Geospatial Modeling}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85011015621&partnerID=MN8TOARS}, DOI={10.1145/2996913.2996950}, abstractNote={Tangible Landscape is a tangible interface for geographic information systems (GIS). It interactively couples physical and digital models of a landscape so that users can intuitively explore, model, and analyze geospatial data in a collaborative environment. Conceptually Tangible Landscape lets users hold a GIS in their hands so that they can feel the shape of the topography, naturally sculpt new landforms, and interact with simulations like water flow. Since it only affords a bird's-eye view of the landscape, we coupled it with an immersive virtual environment so that users can virtually walk around the modeled landscape and visualize it at a human-scale. Now as users shape topography, draw trees, define viewpoints, or route a walkthrough, they can see the results on the projection-augmented model, rendered on a display, or rendered on a head-mounted display. In this paper we present the Tangible Landscape Immersive Extension, describe its physical setup and software architecture, and demonstrate its features with a case study.}, journal={24TH ACM SIGSPATIAL INTERNATIONAL CONFERENCE ON ADVANCES IN GEOGRAPHIC INFORMATION SYSTEMS (ACM SIGSPATIAL GIS 2016)}, author={Tabrizian, Payam and Petrasova, Anna and Harmon, Brendan and Petras, Vaclav and Mitasova, Helena and Meentemeyer, Ross}, year={2016} }
 @article{cunniffe_cobb_meentemeyer_rizzo_gilligan_2016, title={Modeling when, where, and how to manage a forest epidemic, motivated by sudden oak death in California}, volume={113}, ISSN={["0027-8424"]}, DOI={10.1073/pnas.1602153113}, abstractNote={Significance}, number={20}, journal={PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA}, author={Cunniffe, Nik J. and Cobb, Richard C. and Meentemeyer, Ross K. and Rizzo, David M. and Gilligan, Christopher A.}, year={2016}, month={May}, pages={5640–5645} }
 @article{tonini_dillon_money_meentemeyer_2016, title={Spatio-temporal reconstruction of missing forest microclimate measurements}, volume={218}, ISSN={["1873-2240"]}, DOI={10.1016/j.agrformet.2015.11.004}, abstractNote={Scientists and land managers are increasingly monitoring forest microclimate environments to better understand ecosystem processes, such as carbon sequestration and the population dynamics of species. Obtaining reliable time-series measurements of microclimate conditions is often hindered by missing and erroneous values. In this study, we compare spatio-temporal techniques, space–time kriging (probabilistic) and empirical orthogonal functions (deterministic), for reconstructing hourly time series of near-surface air temperature recorded by a dense network of 200 forest understory sensors across a heterogeneous 349 km2 region in northern California. The reconstructed data were also aggregated to daily mean, minimum, and maximum in order to understand the sensitivity of model predictions to temporal scale of measurement. Empirical orthogonal functions performed best at both the hourly and daily time scale. We analyzed several scenarios to understand the effects that spatial coverage and patterns of missing data may have on model accuracy: (a) random reduction of the sample size/density by 25%, 50%, and 75% (spatial coverage); and (b) random removal of either 50% of the data, or three consecutive months of observations at randomly chosen stations (random and seasonal temporal missingness, respectively). Here, space–time kriging was less sensitive to scenarios of spatial coverage, but more sensitive to temporal missingness, with less marked differences between the two approaches when data were aggregated on a daily time scale. This research contextualizes trade-offs between techniques and provides practical guidelines, with free source code, for filling data gaps depending on the spatial density and coverage of measurements.}, journal={AGRICULTURAL AND FOREST METEOROLOGY}, publisher={Elsevier BV}, author={Tonini, Francesco and Dillon, Whalen W. and Money, Eric S. and Meentemeyer, Ross K.}, year={2016}, month={Mar}, pages={1–10} }
 @inproceedings{harmon_petrasova_petras_mitasova_meentemeyer_2016, title={Tangible landscape: cognitively grasping the flow of water}, volume={41}, DOI={10.5194/isprs-archives-xli-b2-647-2016}, abstractNote={Abstract. Complex spatial forms like topography can be challenging to understand, much less intentionally shape, given the heavy cognitive load of visualizing and manipulating 3D form. Spatiotemporal processes like the flow of water over a landscape are even more challenging to understand and intentionally direct as they are dependent upon their context and require the simulation of forces like gravity and momentum. This cognitive work can be offloaded onto computers through 3D geospatial modeling, analysis, and simulation. Interacting with computers, however, can also be challenging, often requiring training and highly abstract thinking. Tangible computing – an emerging paradigm of human-computer interaction in which data is physically manifested so that users can feel it and directly manipulate it – aims to offload this added cognitive work onto the body. We have designed Tangible Landscape, a tangible interface powered by an open source geographic information system (GRASS GIS), so that users can naturally shape topography and interact with simulated processes with their hands in order to make observations, generate and test hypotheses, and make inferences about scientific phenomena in a rapid, iterative process. Conceptually Tangible Landscape couples a malleable physical model with a digital model of a landscape through a continuous cycle of 3D scanning, geospatial modeling, and projection. We ran a flow modeling experiment to test whether tangible interfaces like this can effectively enhance spatial performance by offloading cognitive processes onto computers and our bodies. We used hydrological simulations and statistics to quantitatively assess spatial performance. We found that Tangible Landscape enhanced 3D spatial performance and helped users understand water flow.
                    }, number={B2}, booktitle={International archives of the photogrammetry remote sensing and spatial}, author={Harmon, B. A. and Petrasova, Anna and Petras, Vaclav and Mitasova, Helena and Meentemeyer, K.}, year={2016}, pages={647–653} }
 @article{gagne_sherman_singh_meentemeyer_2016, title={The effect of human population size on the breeding bird diversity of urban regions}, volume={25}, ISSN={["1572-9710"]}, DOI={10.1007/s10531-016-1080-3}, number={4}, journal={BIODIVERSITY AND CONSERVATION}, author={Gagne, Sara A. and Sherman, Peter J. and Singh, Kunwar K. and Meentemeyer, Ross K.}, year={2016}, month={Apr}, pages={653–671} }
 @article{cobb_meentemeyer_rizzo_2016, title={Wildfire and forest disease interaction lead to greater loss of soil nutrients and carbon}, volume={182}, ISSN={["1432-1939"]}, DOI={10.1007/s00442-016-3649-7}, abstractNote={Fire and forest disease have significant ecological impacts, but the interactions of these two disturbances are rarely studied. We measured soil C, N, Ca, P, and pH in forests of the Big Sur region of California impacted by the exotic pathogen Phytophthora ramorum, cause of sudden oak death, and the 2008 Basin wildfire complex. In Big Sur, overstory tree mortality following P. ramorum invasion has been extensive in redwood and mixed evergreen forests, where the pathogen kills true oaks and tanoak (Notholithocarpus densiflorus). Sampling was conducted across a full-factorial combination of disease/no disease and burned/unburned conditions in both forest types. Forest floor organic matter and associated nutrients were greater in unburned redwood compared to unburned mixed evergreen forests. Post-fire element pools were similar between forest types, but lower in burned-invaded compared to burned-uninvaded plots. We found evidence disease-generated fuels led to increased loss of forest floor C, N, Ca, and P. The same effects were associated with lower %C and higher PO4-P in the mineral soil. Fire-disease interactions were linear functions of pre-fire host mortality which was similar between the forest types. Our analysis suggests that these effects increased forest floor C loss by as much as 24.4 and 21.3 % in redwood and mixed evergreen forests, respectively, with similar maximum losses for the other forest floor elements. Accumulation of sudden oak death generated fuels has potential to increase fire-related loss of soil nutrients at the region-scale of this disease and similar patterns are likely in other forests, where fire and disease overlap.}, number={1}, journal={OECOLOGIA}, author={Cobb, Richard C. and Meentemeyer, Ross K. and Rizzo, David M.}, year={2016}, month={Sep}, pages={265–276} }
 @article{shashidharan_berkel_vatsavai_meentemeyer_2016, title={pFUTURES: A Parallel Framework for Cellular Automaton Based Urban Growth Models}, volume={9927}, ISBN={["978-3-319-45737-6"]}, ISSN={["1611-3349"]}, DOI={10.1007/978-3-319-45738-3_11}, abstractNote={Simulating structural changes in landscape is a routine task in computational geography. Owing to advances in sensing and data collection technologies, geospatial data is becoming available at finer spatial and temporal resolutions. However, in practice, these large datasets impede land simulation based studies over large geographic regions due to computational and I/O challenges. The memory overhead of sequential implementations and long execution times further limit the possibilities of simulating future urban scenarios. In this paper, we present a generic framework for co-ordinating I/O and computation for geospatial simulations in a distributed computing environment. We present three parallel approaches and demonstrate the performance and scalability benefits of our parallel implementation pFUTURES, an extension of the FUTURES open-source multi-level urban growth model. Our analysis shows that although a time synchronous parallel approach obtains the same results as a sequential model, an asynchronous parallel approach provides better scaling due to reduced disk I/O and communication overheads.}, journal={GEOGRAPHIC INFORMATION SCIENCE, (GISCIENCE 2016)}, author={Shashidharan, Ashwin and Berkel, Derek B. and Vatsavai, Ranga Raju and Meentemeyer, Ross K.}, year={2016}, pages={163–177} }
 @article{dorning_smith_shoemaker_meentemeyer_2015, title={Changing decisions in a changing landscape: How might forest owners In an urbanizing region respond to emerging bioenergy markets?}, volume={49}, ISSN={["1873-5754"]}, DOI={10.1016/j.landusepol.2015.06.020}, abstractNote={The global bioenergy market has considerable impacts on local land use patterns, including landscapes in the Southeastern United States where increased demand for bioenergy feedstocks in the form of woody biomass is likely to affect the management and availability of forest resources. Despite extensive research investigating the productivity and impacts of different bioenergy feedstocks, relatively few studies have assessed the preferences of private landowners, who control the majority of forests in the eastern U.S., to harvest biomass for the bioenergy market. To better understand contingent behaviors given emerging biomass markets, we administered a stated preference experiment to private forest owners in the rapidly urbanizing Charlotte Metropolitan region. Respondents indicated their preferences for harvesting woody biomass under a set of hypothetical market-based scenarios with varying forest management plans and levels of economic return. Our analytical framework also incorporated data from a previously-administered revealed preference survey and spatially-explicit remote sensing data, enabling us to analyze how individuals’ ownership characteristics, their emotional connection the forests they manage, and the spatial patterns of nearby land uses, influence willingness to grow bioenergy feedstocks. We found conditional support for feedstock production, even among woodland owners with no history of active management. Landowners preferred higher economic returns for each management plan. However low-intensity harvest options were always preferred to more intensive management alternatives regardless of economic return, suggesting that these landowners may be more strongly motivated by aesthetic or quality-of-life concerns than feedstock revenues. Our analysis indicated preferences were dependent upon individual and environmental characteristics, with younger, more rural landowners significantly more interested in growing feedstocks relative to their older and more urban counterparts. While this study focuses on one small sample of urban forest owners, our results do suggest that policy makers and resource managers can better inform stand-level decision-making by understanding how feedstock production preferences vary across populations.}, journal={LAND USE POLICY}, author={Dorning, Monica A. and Smith, Jordan W. and Shoemaker, Douglas A. and Meentemeyer, Ross K.}, year={2015}, month={Dec}, pages={1–10} }
 @article{meentemeyer_dorning_vogler_schmidt_garbelotto_2015, title={Citizen science helps predict risk of emerging infectious disease}, volume={13}, ISSN={["1540-9309"]}, DOI={10.1890/140299}, abstractNote={Engaging citizen scientists is becoming an increasingly popular technique for collecting large amounts of ecological data while also creating an avenue for outreach and public support for research. Here we describe a unique study, in which citizen scientists played a key role in the spatial prediction of an emerging infectious disease. The yearly citizen‐science program called “Sudden Oak Death (SOD) Blitz” engages and educates volunteers in detecting the causal pathogen during peak windows of seasonal disease expression. We used these data – many of which were collected from under‐sampled urban ecosystems – to develop predictive maps of disease risk and to inform stakeholders on where they should prioritize management efforts. We found that continuing the SOD Blitz program over 6 consecutive years improved our understanding of disease dynamics and increased the accuracy of our predictive models. We also found that self‐identified non‐professionals were just as capable of detecting the disease as were professionals. Our results indicate that using long‐term citizen‐science data to predict the risk of emerging infectious plant diseases in urban ecosystems holds substantial promise.}, number={4}, journal={FRONTIERS IN ECOLOGY AND THE ENVIRONMENT}, author={Meentemeyer, Ross K. and Dorning, Monica A. and Vogler, John B. and Schmidt, Douglas and Garbelotto, Matteo}, year={2015}, month={May}, pages={189–194} }
 @article{singh_davis_meentemeyer_2015, title={Detecting understory plant invasion in urban forests using LiDAR}, volume={38}, ISSN={["1872-826X"]}, DOI={10.1016/j.jag.2015.01.012}, abstractNote={Light detection and ranging (LiDAR) data are increasingly used to measure structural characteristics of urban forests but are rarely used to detect the growing problem of exotic understory plant invaders. We explored the merits of using LiDAR-derived metrics alone and through integration with spectral data to detect the spatial distribution of the exotic understory plant Ligustrum sinense, a rapidly spreading invader in the urbanizing region of Charlotte, North Carolina, USA. We analyzed regional-scale L. sinense occurrence data collected over the course of three years with LiDAR-derived metrics of forest structure that were categorized into the following groups: overstory, understory, topography, and overall vegetation characteristics, and IKONOS spectral features – optical. Using random forest (RF) and logistic regression (LR) classifiers, we assessed the relative contributions of LiDAR and IKONOS derived variables to the detection of L. sinense. We compared the top performing models developed for a smaller, nested experimental extent using RF and LR classifiers, and used the best overall model to produce a predictive map of the spatial distribution of L. sinense across our country-wide study extent. RF classification of LiDAR-derived topography metrics produced the highest mapping accuracy estimates, outperforming IKONOS data by 17.5% and the integration of LiDAR and IKONOS data by 5.3%. The top performing model from the RF classifier produced the highest kappa of 64.8%, improving on the parsimonious LR model kappa by 31.1% with a moderate gain of 6.2% over the county extent model. Our results demonstrate the superiority of LiDAR-derived metrics over spectral data and fusion of LiDAR and spectral data for accurately mapping the spatial distribution of the forest understory invader L. sinense.}, journal={INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION}, author={Singh, Kunwar K. and Davis, Amy J. and Meentemeyer, Ross K.}, year={2015}, month={Jun}, pages={267–279} }
 @article{singh_chen_mccarter_meentemeyer_2015, title={Effects of LiDAR point density and landscape context on estimates of urban forest biomass}, volume={101}, ISSN={["1872-8235"]}, DOI={10.1016/j.isprsjprs.2014.12.021}, abstractNote={Light Detection and Ranging (LiDAR) data is being increasingly used as an effective alternative to conventional optical remote sensing to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and improved data accuracies accompanied by challenges for procuring and processing voluminous LiDAR data for large-area assessments. Reducing point density lowers data acquisition costs and overcomes computational challenges for large-area forest assessments. However, how does lower point density impact the accuracy of biomass estimation in forests containing a great level of anthropogenic disturbance? We evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing region of Charlotte, North Carolina, USA. We used multiple linear regression to establish a statistical relationship between field-measured biomass and predictor variables derived from LiDAR data with varying densities. We compared the estimation accuracies between a general Urban Forest type and three Forest Type models (evergreen, deciduous, and mixed) and quantified the degree to which landscape context influenced biomass estimation. The explained biomass variance of the Urban Forest model, using adjusted R2, was consistent across the reduced point densities, with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models at the representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, highlighting a distance impact of development on biomass estimation. Our evaluation suggests that reducing LiDAR point density is a viable solution to regional-scale forest assessment without compromising the accuracy of biomass estimates, and these estimates can be further improved using development density.}, journal={ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING}, author={Singh, Kunwar K. and Chen, Gang and McCarter, James B. and Meentemeyer, Ross K.}, year={2015}, month={Mar}, pages={310–322} }
 @article{king_darrah_money_meentemeyer_maguire_nye_michener_murtha_jirtle_murphy_et al._2015, title={Geographic clustering of elevated blood heavy metal levels in pregnant women}, volume={15}, ISSN={["1471-2458"]}, DOI={10.1186/s12889-015-2379-9}, abstractNote={Cadmium (Cd), lead (Pb), mercury (Hg), and arsenic (As) exposure is ubiquitous and has been associated with higher risk of growth restriction and cardiometabolic and neurodevelopmental disorders. However, cost-efficient strategies to identify at-risk populations and potential sources of exposure to inform mitigation efforts are limited. The objective of this study was to describe the spatial distribution and identify factors associated with Cd, Pb, Hg, and As concentrations in peripheral blood of pregnant women.Heavy metals were measured in whole peripheral blood of 310 pregnant women obtained at gestational age ~12 weeks. Prenatal residential addresses were geocoded and geospatial analysis (Getis-Ord Gi* statistics) was used to determine if elevated blood concentrations were geographically clustered. Logistic regression models were used to identify factors associated with elevated blood metal levels and cluster membership.Geospatial clusters for Cd and Pb were identified with high confidence (p-value for Gi* statistic <0.01). The Cd and Pb clusters comprised 10.5 and 9.2 % of Durham County residents, respectively. Medians and interquartile ranges of blood concentrations (μg/dL) for all participants were Cd 0.02 (0.01-0.04), Hg 0.03 (0.01-0.07), Pb 0.34 (0.16-0.83), and As 0.04 (0.04-0.05). In the Cd cluster, medians and interquartile ranges of blood concentrations (μg/dL) were Cd 0.06 (0.02-0.16), Hg 0.02 (0.00-0.05), Pb 0.54 (0.23-1.23), and As 0.05 (0.04-0.05). In the Pb cluster, medians and interquartile ranges of blood concentrations (μg/dL) were Cd 0.03 (0.02-0.15), Hg 0.01 (0.01-0.05), Pb 0.39 (0.24-0.74), and As 0.04 (0.04-0.05). Co-exposure with Pb and Cd was also clustered, the p-values for the Gi* statistic for Pb and Cd was <0.01. Cluster membership was associated with lower education levels and higher pre-pregnancy BMI.Our data support that elevated blood concentrations of Cd and Pb are spatially clustered in this urban environment compared to the surrounding areas. Spatial analysis of metals concentrations in peripheral blood or urine obtained routinely during prenatal care can be useful in surveillance of heavy metal exposure.}, number={1}, journal={BMC PUBLIC HEALTH}, publisher={Springer Science and Business Media LLC}, author={King, Katherine E. and Darrah, Thomas H. and Money, Eric and Meentemeyer, Ross and Maguire, Rachel L. and Nye, Monica D. and Michener, Lloyd and Murtha, Amy P. and Jirtle, Randy and Murphy, Susan K. and et al.}, year={2015}, month={Oct} }
 @article{petras_petrasova_harmon_meentemeyer_mitasova_2015, title={Integrating Free and Open Source Solutions into Geospatial Science Education}, volume={4}, ISSN={["2220-9964"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84948970902&partnerID=MN8TOARS}, DOI={10.3390/ijgi4020942}, abstractNote={While free and open source software becomes increasingly important in geospatial research and industry, open science perspectives are generally less reflected in universities’ educational programs. We present an example of how free and open source software can be incorporated into geospatial education to promote open and reproducible science. Since 2008 graduate students at North Carolina State University have the opportunity to take a course on geospatial modeling and analysis that is taught with both proprietary and free and open source software. In this course, students perform geospatial tasks simultaneously in the proprietary package ArcGIS and the free and open source package GRASS GIS. By ensuring that students learn to distinguish between geospatial concepts and software specifics, students become more flexible and stronger spatial thinkers when choosing solutions for their independent work in the future. We also discuss ways to continually update and improve our publicly available teaching materials for reuse by teachers, self-learners and other members of the GIS community. Only when free and open source software is fully integrated into geospatial education, we will be able to encourage a culture of openness and, thus, enable greater reproducibility in research and development applications.}, number={2}, journal={ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION}, author={Petras, Vaclav and Petrasova, Anna and Harmon, Brendan and Meentemeyer, Ross K. and Mitasova, Helena}, year={2015}, month={Jun}, pages={942–956} }
 @article{chen_metz_rizzo_meentemeyer_2015, title={Mapping burn severity in a disease-impacted forest landscape using Landsat and MASTER imagery}, volume={40}, ISSN={["0303-2434"]}, DOI={10.1016/j.jag.2015.04.005}, abstractNote={Abstract Global environmental change has increased forest vulnerability to the occurrence of interacting disturbances, including wildfires and invasive diseases. Mapping post-fire burn severity in a disease-affected forest often faces challenges because burned and infested trees may exhibit a high similarity in spectral reflectance. In this study, we combined (pre- and post-fire) Landsat imagery and (post-fire) high-spectral resolution airborne MASTER data [MODIS (moderate resolution imaging spectroradiometer)/ASTER (advanced spaceborne thermal emission and reflection radiometer)] to map burn severity in a California coastal forest environment, where a non-native forest disease sudden oak death (SOD) was causing substantial tree mortality. Results showed that the use of Landsat plus MASTER bundle performed better than using the individual sensors in most of the evaluated forest strata from ground to canopy layers (i.e., substrate, shrubs, intermediate-sized trees, dominant trees and average), with the best model performance achieved at the dominant tree layer. The mid to thermal infrared spectral bands (3.0–12.5 μm) from MASTER were found to augment Landsat’s visible to shortwave infrared bands in burn severity assessment. We also found that infested and uninfested forests similarly experienced moderate to high degrees of burns where CBI (composite burn index) values were higher than 1. However, differences occurred in the regions with low burn severity (CBI values lower than 1), where uninfested stands revealed a much lower burn effect than that in infested stands, possibly due to their higher resilience to small fire disturbances as a result of higher leaf water content.}, journal={INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION}, author={Chen, Gang and Metz, Margaret R. and Rizzo, David M. and Meentemeyer, Ross K.}, year={2015}, month={Aug}, pages={91–99} }
 @article{chen_metz_rizzo_dillon_meentemeyer_2015, title={Object-based assessment of burn severity in diseased forests using high-spatial and high-spectral resolution MASTER airborne imagery}, volume={102}, ISSN={["1872-8235"]}, DOI={10.1016/j.isprsjprs.2015.01.004}, abstractNote={Forest ecosystems are subject to a variety of disturbances with increasing intensities and frequencies, which may permanently change the trajectories of forest recovery and disrupt the ecosystem services provided by trees. Fire and invasive species, especially exotic disease-causing pathogens and insects, are examples of disturbances that together could pose major threats to forest health. This study examines the impacts of fire and exotic disease (sudden oak death) on forests, with an emphasis on the assessment of post-fire burn severity in a forest where trees have experienced three stages of disease progression pre-fire: early-stage (trees retaining dried foliage and fine twigs), middle-stage (trees losing fine crown fuels), and late-stage (trees falling down). The research was conducted by applying Geographic Object-Based Image Analysis (GEOBIA) to MASTER airborne images that were acquired immediately following the fire for rapid assessment and contained both high-spatial (4 m) and high-spectral (50 bands) resolutions. Although GEOBIA has gradually become a standard tool for analyzing high-spatial resolution imagery, high-spectral resolution data (dozens to hundreds of bands) can dramatically reduce computation efficiency in the process of segmentation and object-based variable extraction, leading to complicated variable selection for succeeding modeling. Hence, we also assessed two widely used band reduction algorithms, PCA (principal component analysis) and MNF (minimum noise fraction), for the delineation of image objects and the subsequent performance of burn severity models using either PCA or MNF derived variables. To increase computation efficiency, only the top 5 PCA and MNF and top 10 PCA and MNF components were evaluated, which accounted for 10% and 20% of the total number of the original 50 spectral bands, respectively. Results show that if no band reduction was applied the models developed for the three stages of disease progression had relatively similar performance, where both spectral responses and texture contributed to burn assessments. However, the application of PCA and MNF introduced much greater variation among models across the three stages. For the early-stage disease progression, neither band reduction algorithms improved or retained the accuracy of burn severity modeling (except for the use of 10 MNF components). Compared to the no-band-reduction scenario, band reduction led to a greater level of overestimation of low-degree burns and underestimation of medium-degree burns, suggesting that the spectral variation removed by PCA and MNF was vital for distinguishing between the spectral reflectance from disease-induced dried crowns (still retaining high structural complexity) and fire ash. For the middle-stage, both algorithms improved the model R2 values by 2–37%, while the late-stage models had comparable or better performance to those using the original 50 spectral bands. This could be explained by the loss of tree crowns enabling better signal penetration, thus leading to reduced spectral variation from canopies. Hence, spectral bands containing a high degree of random noise were correctly removed by the band reduction algorithms. Compared to the middle-stage, the late-stage forest stands were covered by large piles of fallen trees and branches, resulting in higher variability of MASTER imagery. The ability of band reduction to improve the model performance for these late-stage forest stands was reduced, because the valuable spectral variation representing the actual late-stage forest status was partially removed by both algorithms as noise. Our results indicate that PCA and MNF are promising for balancing computation efficiency and the performance of burn severity models in forest stands subject to the middle and late stages of sudden oak death disease progression. Compared to PCA, MNF dramatically reduced image spectral variation, generating larger image objects with less complexity of object shapes. Whereas, PCA-based models delivered superior performance in most evaluated cases suggesting that some key spectral variability contributing to the accuracy of burn severity models in diseased forests may have been removed together with true spectral noise through MNF transformations.}, journal={ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING}, author={Chen, Gang and Metz, Margaret R. and Rizzo, David M. and Dillon, Whalen W. and Meentemeyer, Ross K.}, year={2015}, month={Apr}, pages={38–47} }
 @article{dorning_koch_shoemaker_meentemeyer_2015, title={Simulating urbanization scenarios reveals tradeoffs between conservation planning strategies}, volume={136}, ISSN={["1872-6062"]}, DOI={10.1016/j.landurbplan.2014.11.011}, abstractNote={Land that is of great value for conservation can also be highly suitable for human use, resulting in competition between urban development and the protection of natural resources. To assess the effectiveness of proposed regional land conservation strategies in the context of rapid urbanization, we measured the impacts of simulated development patterns on two distinct conservation goals: protecting priority natural resources and limiting landscape fragmentation. Using a stochastic, patch-based land change model (FUTURES) we projected urbanization in the North Carolina Piedmont according to status quo trends and several conservation-planning strategies, including constraints on the spatial distribution of development, encouraging infill, and increasing development density. This approach allows simulation of population-driven land consumption without excluding the possibility of development, even in areas of high conservation value. We found that if current trends continue, new development will consume 11% of priority resource lands, 21% of forested land, and 14% of farmlands regionally by 2032. We also found that no single conservation strategy was optimal for achieving both conservation goals. For example, strategies that excluded development from priority areas caused increased fragmentation of forests and farmlands, while infill strategies increased loss of priority resources proximal to urban areas. Exploration of these land change scenarios not only confirmed that a failure to act is likely to result in irreconcilable losses to a conservation network, but that all conservation plans are not equivalent in effect, highlighting the importance of analyzing tradeoffs between alternative conservation planning approaches.}, journal={LANDSCAPE AND URBAN PLANNING}, author={Dorning, Monica A. and Koch, Jennifer and Shoemaker, Douglas A. and Meentemeyer, Ross K.}, year={2015}, month={Apr}, pages={28–39} }
 @article{wine_gagne_meentemeyer_2015, title={Understanding Human-Coyote Encounters in Urban Ecosystems Using Citizen Science Data: What Do Socioeconomics Tell Us?}, volume={55}, ISSN={["1432-1009"]}, DOI={10.1007/s00267-014-0373-0}, abstractNote={The coyote (Canis latrans) has dramatically expanded its range to include the cities and suburbs of the western US and those of the Eastern Seaboard. Highly adaptable, this newcomer's success causes conflicts with residents, necessitating research to understand the distribution of coyotes in urban landscapes. Citizen science can be a powerful approach toward this aim. However, to date, the few studies that have used publicly reported coyote sighting data have lacked an in-depth consideration of human socioeconomic variables, which we suggest are an important source of overlooked variation in data that describe the simultaneous occurrence of coyotes and humans. We explored the relative importance of socioeconomic variables compared to those describing coyote habitat in predicting human-coyote encounters in highly-urbanized Mecklenburg County, North Carolina, USA using 707 public reports of coyote sightings, high-resolution land cover, US Census data, and an autologistic multi-model inference approach. Three of the four socioeconomic variables which we hypothesized would have an important influence on encounter probability, namely building density, household income, and occupation, had effects at least as large as or larger than coyote habitat variables. Our results indicate that the consideration of readily available socioeconomic variables in the analysis of citizen science data improves the prediction of species distributions by providing insight into the effects of important factors for which data are often lacking, such as resource availability for coyotes on private property and observer experience. Managers should take advantage of citizen scientists in human-dominated landscapes to monitor coyotes in order to understand their interactions with humans.}, number={1}, journal={ENVIRONMENTAL MANAGEMENT}, author={Wine, Stuart and Gagne, Sara A. and Meentemeyer, Ross K.}, year={2015}, month={Jan}, pages={159–170} }
 @article{bendor_shoemaker_thill_dorning_meentemeyer_2014, title={A mixed-methods analysis of social-ecological feedbacks between urbanization and forest persistence}, volume={19}, ISSN={["1708-3087"]}, DOI={10.5751/es-06508-190303}, abstractNote={BenDor, T., D. A. Shoemaker, J.-C. Thill, M. A. Dorning, and R. K. Meentemeyer. 2014. A mixed-methods analysis of social-ecological feedbacks between urbanization and forest persistence. Ecology and Society 19(3): 3. https://doi.org/10.5751/ES-06508-190303}, number={3}, journal={ECOLOGY AND SOCIETY}, author={BenDor, Todd and Shoemaker, Douglas A. and Thill, Jean-Claude and Dorning, Monica A. and Meentemeyer, Ross K.}, year={2014} }
 @article{hohl_vaclavik_meentemeyer_2014, title={Go with the flow: geospatial analytics to quantify hydrologic landscape connectivity for passively dispersed microorganisms}, volume={28}, ISSN={["1362-3087"]}, DOI={10.1080/13658816.2013.854900}, abstractNote={Understanding the diverse ways that landscape connectivity influences the distribution of microbial species is central to managing the spread and persistence of numerous biological invasions. Here, we use geospatial analytics to examine the degree to which the hydrologic connectivity of landscapes influences the transport of passively dispersed microbes, using the invasive plant pathogen Phytophthora ramorum as a case study. Pathogen occurrence was analyzed at 280 stream baiting stations across a range of watersheds – exposed to variable inoculum pressure – in California over a 7-year period (2004–2010). Using logistic regression, we modeled the probability of pathogen occurrence at a baiting station based on nine environmental variables. We developed a novel geospatial approach to quantify the hydrologic connectivity of host vegetation and inoculum pressure derived from least cost distance analyses in each watershed. We also examined the influence of local environmental conditions within the immediate neighborhood of a baiting station. Over the course of the sampling period, the pathogen was detected at 67 baiting stations associated with coastal watersheds with mild climate conditions, steep slopes, and higher levels of inoculum pressure. At the watershed scale, hydrologic landscape connectivity was a key predictor of pathogen occurrence in streams after accounting for variation in climate and exposure to inoculum. This study illustrates a geospatial approach to modeling the degree to which hydrologic systems play a role in shaping landscape structures conducive for the transport of passively dispersed microbes in heterogeneous watersheds.}, number={8}, journal={INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE}, author={Hohl, Alexander and Vaclavik, Tomas and Meentemeyer, Ross K.}, year={2014}, pages={1626–1641} }
 @article{dillon_haas_rizzo_meentemeyer_2014, title={Perspectives of spatial scale in a wildland forest epidemic}, volume={138}, ISSN={["1573-8469"]}, DOI={10.1007/s10658-013-0376-3}, number={3}, journal={EUROPEAN JOURNAL OF PLANT PATHOLOGY}, author={Dillon, Whalen W. and Haas, Sarah E. and Rizzo, David M. and Meentemeyer, Ross K.}, year={2014}, month={Mar}, pages={449–465} }
 @article{cobb_rizzo_garbelotto_filipe_gilligan_meentemeyer_dillon_valachovic_swieki_hansen_et al._2013, title={Biodiversity conservation in the face of dramatic forest disease: an integrated conservation strategy for tanoak (notholithocarpus densiflorus) threatened by sudden oak death}, volume={60}, DOI={10.3120/0024-9637-60.2.151}, abstractNote={Abstract Non-native diseases of dominant tree species have diminished North American forest biodiversity, structure, and ecosystem function over the last 150 years. Since the mid-1990s, coastal California forests have suffered extensive decline of the endemic overstory tree tanoak, Notholithocarpus densiflorus (Hook. & Arn.) Manos, Cannon & S. H. Oh (Fagaceae), following the emergence of the exotic pathogen Phythophthora ramorum and the resulting disease sudden oak death. There are two central challenges to protecting tanoak: 1) the pathogen P. ramorum has multiple pathways of spread and is thus very difficult to eradicate, and 2) the low economic valuation of tanoak obscures the cultural and ecological importance of this species. However, both modeling and field studies have shown that pathogen-centric management and host-centric preventative treatments are effective methods to reduce rates of spread, local pathogen prevalence, and to increase protection of individual trees. These management strategies are not mutually exclusive, but we lack precise understanding of the timing and extent to apply each strategy in order to minimize disease and the subsequent accumulation of fuels, loss of obligate flora and fauna, or destruction of culturally important stands. Recent work identifying heritable disease resistance traits, ameliorative treatments that reduce pathogen populations, and silvicultural treatments that shift stand composition hold promise for increasing the resiliency of tanoak populations. We suggest distinct strategies for pathogen invaded and uninvaded areas, place these in the context of local management goals, and suggest a management strategy and associated research priorities to retain the biodiversity and cultural values associated with tanoak.}, number={2}, journal={Madrono}, author={Cobb, R. C. and Rizzo, D. M. and Garbelotto, M. and Filipe, J. A. N. and Gilligan, C. A. and Meentemeyer, Ross K. and Dillon, W. and Valachovic, Y. and Swieki, T. and Hansen, E. M. and et al.}, year={2013}, pages={151–164} }
 @article{meentemeyer_tang_dorning_vogler_cunniffe_shoemaker_2013, title={FUTURES: Multilevel Simulations of Emerging Urban-Rural Landscape Structure Using a Stochastic Patch-Growing Algorithm}, volume={103}, ISSN={["1467-8306"]}, DOI={10.1080/00045608.2012.707591}, abstractNote={We present a multilevel modeling framework for simulating the emergence of landscape spatial structure in urbanizing regions using a combination of field-based and object-based representations of land change. The FUTure Urban-Regional Environment Simulation (FUTURES) produces regional projections of landscape patterns using coupled submodels that integrate nonstationary drivers of land change: per capita demand, site suitability, and the spatial structure of conversion events. Patches of land change events are simulated as discrete spatial objects using a stochastic region-growing algorithm that aggregates cell-level transitions based on empirical estimation of parameters that control the size, shape, and dispersion of patch growth. At each time step, newly constructed patches reciprocally influence further growth, which agglomerates over time to produce patterns of urban form and landscape fragmentation. Multilevel structure in each submodel allows drivers of land change to vary in space (e.g., by jurisdiction), rather than assuming spatial stationarity across a heterogeneous region. We applied FUTURES to simulate land development dynamics in the rapidly expanding metropolitan region of Charlotte, North Carolina, between 1996 and 2030, and evaluated spatial variation in model outcomes along an urban–rural continuum, including assessments of cell- and patch-based correctness and error. Simulation experiments reveal that changes in per capita land consumption and parameters controlling the distribution of development affect the emergent spatial structure of forests and farmlands with unique and sometimes counterintuitive outcomes.}, number={4}, journal={ANNALS OF THE ASSOCIATION OF AMERICAN GEOGRAPHERS}, author={Meentemeyer, Ross K. and Tang, Wenwu and Dorning, Monica A. and Vogler, John B. and Cunniffe, Nik J. and Shoemaker, Douglas A.}, year={2013}, month={Jul}, pages={785–807} }
 @article{cord_meentemeyer_leitao_vaclavik_2013, title={Modelling species distributions with remote sensing data: bridging disciplinary perspectives}, volume={40}, ISSN={["1365-2699"]}, DOI={10.1111/jbi.12199}, abstractNote={Over the last few decades, correlative species distribution models (SDMs) have been adopted as the most widely used approach for describing and predicting spatial patterns of relationships between species occurrence and environmental conditions (Elith & Leathwick, 2009). Over this same period, the discipline of remote sensing (RS) has produced a breadth of novel geospatial datasets and analytical algorithms for mapping biogeographical heterogeneity. It is not surprising that RS data are now commonly used in SDMs: spaceand airborne RS data provide a low cost means to map environmental changes across multiple spatio-temporal scales and are attractive for their ability to measure spatial factors often impossible to quantify otherwise (e.g. landscape connectivity). Looking into this trend further, our literature search – with keywords ‘remote sensing’ and ‘species distribution’ or ‘habitat suitability’ – returned 210 articles where remote sensing was integrally used in SDMs, 60% of which were published just in the past 5 years (ISI Web of Science, 2 May 2013). This development should be a good thing, right? However, several scientists have critically pointed out that the content and spatial scale of RS predictors do not often match species’ life-history strategies (e.g. Bradley et al., 2012; Lechner et al., 2012). Our objective here is not to disagree with their recently proposed methodological guidelines, but rather to reflect on the various facets of using RS in SDMs in an effort to bridge disciplinary perspectives. Despite the rapidly increasing number of interdisciplinary approaches, we believe that some remaining discrepancies between geographical and ecological perspectives still influence current SDM studies. To illustrate this diversity of disciplinary viewpoints, we build on the proposition of Carl Troll, who coined the term ‘landscape ecology’ in an attempt to integrate the ‘spatial’ approach of geographers and the ‘functional’ approach of ecologists. In SDM studies, at one extreme, RS researchers may tend to focus on mapping spatial patterns of species distributions, while ecologists may be as much concerned with the explanations of these distributions. By this generalized point of view, we do not wish to draw boxes around disciplines but believe that inherited disciplinary perspectives, differing research priorities and associated methodological advancements remain the core reasons why the integration of RS in SDMs has not yet reached its full potential. Below, we discuss how the application of RS data in SDMs can be improved by (1) a greater awareness of the differing sample size and characteristics of RS and ecological data, (2) the combination of different RS predictors in multi-scale modelling frameworks, (3) the use of RS data to infer information on species absence, and (4) a clearer definition of the modelling purpose. First, remotely sensed and field-based ecological data typically vary in their sample sizes and functional relationships to the focal species. Ecological perspectives may sometimes lead to using relatively small samples of data compared with RS; however, those field samples are often relatively accurate and typically capture information that is ecologically relevant to the distribution of the species (direct predictors, e.g. temperature or soil type). In contrast, RS data provide a wall-to-wall census of biophysical factors with relatively low accuracies (due to errors introduced during data acquisition, processing or analysis) which may serve only as indirect surrogates for functional variables (see Elith & Leathwick, 2009). Recognizing and accepting these differences between the two data sources is crucial. In particular, relationships between species occurrence and such indirect surrogates may be non-stationary in space and time. For example, the same values of the normalized difference vegetation index (NDVI) or other indices can be observed for habitat patches with completely different plant community compositions. While the importance of this spatio-temporal non-stationarity of RS signals along elevational or climatic gradients has been recognized in vegetation mapping (see Guyon et al., 2011), we do not see careful contextualization for the use of RS data in SDMs so far. It is therefore essential to develop approaches that will allow us to extract ecological meaning from the censuses provided by RS data and design new RS indicators that capture direct environmental drivers. While this has been accomplished for modelling animal species by approximating habitat heterogeneity from RS data (Goetz et al., 2010), there is an apparent research gap for plant species. We specifically suggest continuing to explore the potential of functionally relevant biophysical parameters, such as leaf area index (LAI) or fraction of absorbed photosynthetically active radiation (fPAR), instead of using the more common vegetation indices (e.g. NDVI or enhanced vegetation index) that consist of combinations of spectral bands and are only indirectly linked to biophysical properties of vegetation. In addition, remotely sensed land surface temperature (LST), which is one of the most important parameters for quantifying surface energy and water balances (Quattrochi & Luvall, 2004), is a valuable, yet largely untapped source of data in SDMs. Second, although the importance of considering scale-dependency of patterns and processes is well established in both disciplines, we see differences in implementation. Both ecologists and RS specialists widely accept that the choice of spatial scale, defined by extent (the geographical area considered) and grain (smallest measurement unit within a dataset), has to be driven by the objective and the potential application of the research. Obviously, there may be exceptions, where published studies fail to establish that their observation scale does correspond to the phenomena scale (at which the organism interacts with the environment; Lechner et al., 2012). Pearson & Dawson (2003) proposed a hierarchical framework for conceptualizing the scales at which different environmental factors affect species distributions. However, most RSbased studies that embrace multi-scale approaches compare the utility of the same}, number={12}, journal={JOURNAL OF BIOGEOGRAPHY}, author={Cord, Anna F. and Meentemeyer, Ross K. and Leitao, Pedro J. and Vaclavik, Tomas}, year={2013}, month={Dec}, pages={2226–2227} }
 @article{dillon_vogler_cobb_metz_rizzo_meentemeyer_2013, title={Range-wide risks to a foundation tree species from disturbance interactions}, volume={60}, url={http://dx.doi.org/10.3120/0024-9637-60.2.139}, DOI={10.3120/0024-9637-60.2.139}, abstractNote={Abstract The geographic range of tanoak, Notholithocarpus densiflorus (Hook. & Arn.) Manos, Cannon & S. H. Oh (Fagaceae), encompasses tremendous physiographic variability, diverse plant communities, and complex disturbance regimes (e.g., development, timber harvest, and wildfire) that now also include serious threats posed by the invasive forest pathogen Phytophthora ramorum S. Werres, A.W.A.M. de Cock. Knowing where these disturbance factors interact is critical for developing comprehensive strategies for conserving the abundance, structure, and function of at-risk tanoak communities. In this study, we present a rule-based spatial model of the range-wide threat to tanoak populations from four disturbance factors that were parameterized to encode their additive effects and two-way interactions. Within a GIS, we mapped threats posed by silvicultural activities; disease caused by P. ramorum; human development; and altered fire regimes across the geographic range of tanoak, and we integrated spatially coinciding disturbances to quantify and map the additive and interacting threats to tanoak. We classified the majority of tanoak's range at low risk (3.7 million ha) from disturbance interactions, with smaller areas at intermediate (222,795 ha), and high (10,905 ha) risk. Elevated risk levels resulted from the interaction of disease and silviculture factors over small extents in northern California and southwest Oregon that included parts of Hoopa and Yurok tribal lands. Our results illustrate tanoak populations at risk from these interacting disturbances based on one set of hypothesized relationships. The model can be extended to other species affected by these factors, used as a guide for future research, and is a point of departure for developing a comprehensive understanding of threats to tanoak populations. Identifying the geographic location of disturbance interactions and risks to foundation species such as tanoak is critical for prioritizing and targeting conservation treatments with limited resources.}, number={2}, journal={Madrono}, author={Dillon, W. and Vogler, J. B. and Cobb, R. and Metz, M. R. and Rizzo, D. M. and Meentemeyer, Ross K.}, year={2013}, pages={139–150} }
 @article{metz_varner_frangioso_meentemeyer_rizzo_2013, title={Unexpected redwood mortality from synergies between wildfire and an emerging infectious disease}, volume={94}, ISSN={["1939-9170"]}, DOI={10.1890/13-0915.1}, abstractNote={An under‐examined component of global change is the alteration of disturbance regimes due to warming climates, continued species invasions, and accelerated land‐use change. These drivers of global change are themselves novel ecosystem disturbances that may interact with historically occurring disturbances in complex ways. Here we use the natural experiment presented by wildfires in redwood forests impacted by an emerging infectious disease to demonstrate unexpected synergies of novel disturbance interactions. The dominant tree, coast redwood (fire resistant without negative disease impacts), experienced unexpected synergistic increases in mortality when fire and disease co‐occurred. The increased mortality risk, more than fourfold at the peak of the effect, was not predictable from impacts of either disturbance alone. Changes in fire behavior associated with changes to forest fuels that occurred through disease progression overwhelmed redwood's usual resilience to wildfire. Our results demonstrate the potential for interacting disturbances to initiate novel successional trajectories and compromise ecosystem resilience.}, number={10}, journal={ECOLOGY}, author={Metz, Margaret R. and Varner, J. Morgan and Frangioso, Kerri M. and Meentemeyer, Ross K. and Rizzo, David M.}, year={2013}, month={Oct}, pages={2152–2159} }
 @article{vaclavik_kupfer_meentemeyer_2012, title={Accounting for multi-scale spatial autocorrelation improves performance of invasive species distribution modelling (iSDM)}, volume={39}, ISSN={["1365-2699"]}, DOI={10.1111/j.1365-2699.2011.02589.x}, abstractNote={Abstract}, number={1}, journal={JOURNAL OF BIOGEOGRAPHY}, author={Vaclavik, Tomas and Kupfer, John A. and Meentemeyer, Ross K.}, year={2012}, month={Jan}, pages={42–55} }
 @article{metz_frangioso_wickland_meentemeyer_rizzo_2012, title={An emergent disease causes directional changes in forest species composition in coastal California}, volume={3}, ISSN={["2150-8925"]}, DOI={10.1890/es12-00107.1}, abstractNote={Non‐native forest pathogens can cause dramatic and long‐lasting changes to the composition of forests, and these changes may have cascading impacts on community interactions and ecosystem functioning. Phytophthora ramorum, the causal agent of the emergent forest disease sudden oak death (SOD), has a wide host range, but mortality is concentrated in a few dominant tree species of coastal forests in California and Oregon. We examined interactions between P. ramorum and its hosts in redwood and mixed evergreen forest types over an 80,000 ha area in the Big Sur ecoregion of central California, an area that constitutes the southernmost range of the pathogen and includes forest stands on the advancing front of pathogen invasion. We established a network of 280 long‐term forest monitoring plots to understand how host composition and forest structure facilitated pathogen invasion, and whether selective mortality from SOD has led to shifts in community composition. Infested and uninfested sites differed significantly in host composition due to both historical trends and disease impacts. A reconstruction of pre‐disease forest composition showed that stands that eventually became infested with the pathogen tended to be more mature with larger stems than stands that remained pathogen‐free, supporting the hypothesis of aerial dispersal by the pathogen across the landscape followed by local understory spread. The change in species composition in uninfested areas was minimal over the study period, while infested stands had large changes in composition, correlated with the loss of tanoak (Notholithocarpus densiflorus), signaling the potential for SOD to dramatically change coastal forests through selective removal of a dominant host. Forest diversity plays an important role in pathogen establishment and spread, and is in turn changed by pathogen impacts. Asymmetric competency among host species means that impacts of P. ramorum on forest diversity are shaped by the combination and dominance of hosts present in a stand.}, number={10}, journal={ECOSPHERE}, author={Metz, Margaret R. and Frangioso, Kerri M. and Wickland, Allison C. and Meentemeyer, Ross K. and Rizzo, David M.}, year={2012}, month={Oct} }
 @article{cobb_chan_meentemeyer_rizzo_2012, title={Common Factors Drive Disease and Coarse Woody Debris Dynamics in Forests Impacted by Sudden Oak Death}, volume={15}, ISSN={["1435-0629"]}, DOI={10.1007/s10021-011-9506-y}, number={2}, journal={ECOSYSTEMS}, author={Cobb, Richard C. and Chan, Maggie N. and Meentemeyer, Ross K. and Rizzo, David M.}, year={2012}, month={Mar}, pages={242–255} }
 @article{cobb_filipe_meentemeyer_gilligan_rizzo_2012, title={Ecosystem transformation by emerging infectious disease: loss of large tanoak from California forests}, volume={100}, ISSN={["1365-2745"]}, DOI={10.1111/j.1365-2745.2012.01960.x}, abstractNote={Summary}, number={3}, journal={JOURNAL OF ECOLOGY}, author={Cobb, Richard C. and Filipe, Joao A. N. and Meentemeyer, Ross K. and Gilligan, Christopher A. and Rizzo, David M.}, year={2012}, month={May}, pages={712–722} }
 @article{vaclavik_meentemeyer_2012, title={Equilibrium or not? Modelling potential distribution of invasive species in different stages of invasion}, volume={18}, ISSN={["1472-4642"]}, DOI={10.1111/j.1472-4642.2011.00854.x}, abstractNote={Abstract}, number={1}, journal={DIVERSITY AND DISTRIBUTIONS}, author={Vaclavik, Tomas and Meentemeyer, Ross K.}, year={2012}, month={Jan}, pages={73–83} }
 @article{wang_thill_meentemeyer_2012, title={Estimating the demand for public open space: Evidence from North Carolina municipalities}, volume={91}, ISSN={["1435-5957"]}, DOI={10.1111/j.1435-5957.2011.00372.x}, abstractNote={This paper empirically identifies socio-economic, physical, and geographic factors of the demand for open space in the state of North Carolina in the United States. Estimated coefficients suggest that spatial dependency exists in open space demand and that open space is a normal good. The paper provides the first empirical investigation of how open space demand is affected by local weather conditions. It is found that the demand has a statistically significant substitution relationship with nice weather. We discuss the socio-economic rationale for the estimated demand models within the regional context of North Carolina and point to some relevant policy implications.



Resumen. Este articulo identifica empiricamente los factores socioeconomicos, fisicos y geograficos de la demanda de espacios al aire libre en el estado de Carolina del Norte en los Estados Unidos. Los coeficientes estimados sugieren que existe una dependencia espacial en la demanda de espacios al aire libre y que los espacios al aire libre son un bien normal. El articulo ofrece la primera investigacion empirica sobre como se ve afectada la demanda de espacios al aire libre por las condiciones meteorologicas locales. Se ha encontrado que la demanda tiene una relacion de substitucion estadisticamente significativa con una meteorologia benigna. Discutimos el fundamento socioeconomico de los modelos de demanda estimados dentro del contexto regional de Carolina del Norte e indicamos varias implicaciones relevantes para la formulacion de politicas.}, number={1}, journal={PAPERS IN REGIONAL SCIENCE}, author={Wang, Chunhua and Thill, Jean-Claude and Meentemeyer, Ross K.}, year={2012}, month={Mar} }
 @article{filipe_cobb_meentemeyer_lee_valachovic_cook_rizzo_gilligan_2012, title={Landscape Epidemiology and Control of Pathogens with Cryptic and Long-Distance Dispersal: Sudden Oak Death in Northern Californian Forests}, volume={8}, ISSN={["1553-7358"]}, DOI={10.1371/journal.pcbi.1002328}, abstractNote={Exotic pathogens and pests threaten ecosystem service, biodiversity, and crop security globally. If an invasive agent can disperse asymptomatically over long distances, multiple spatial and temporal scales interplay, making identification of effective strategies to regulate, monitor, and control disease extremely difficult. The management of outbreaks is also challenged by limited data on the actual area infested and the dynamics of spatial spread, due to financial, technological, or social constraints. We examine principles of landscape epidemiology important in designing policy to prevent or slow invasion by such organisms, and use Phytophthora ramorum, the cause of sudden oak death, to illustrate how shortfalls in their understanding can render management applications inappropriate. This pathogen has invaded forests in coastal California, USA, and an isolated but fast-growing epidemic focus in northern California (Humboldt County) has the potential for extensive spread. The risk of spread is enhanced by the pathogen's generalist nature and survival. Additionally, the extent of cryptic infection is unknown due to limited surveying resources and access to private land. Here, we use an epidemiological model for transmission in heterogeneous landscapes and Bayesian Markov-chain-Monte-Carlo inference to estimate dispersal and life-cycle parameters of P. ramorum and forecast the distribution of infection and speed of the epidemic front in Humboldt County. We assess the viability of management options for containing the pathogen's northern spread and local impacts. Implementing a stand-alone host-free “barrier” had limited efficacy due to long-distance dispersal, but combining curative with preventive treatments ahead of the front reduced local damage and contained spread. While the large size of this focus makes effective control expensive, early synchronous treatment in newly-identified disease foci should be more cost-effective. We show how the successful management of forest ecosystems depends on estimating the spatial scales of invasion and treatment of pathogens and pests with cryptic long-distance dispersal.}, number={1}, journal={PLOS COMPUTATIONAL BIOLOGY}, author={Filipe, Joao A. N. and Cobb, Richard C. and Meentemeyer, Ross K. and Lee, Christopher A. and Valachovic, Yana S. and Cook, Alex R. and Rizzo, David M. and Gilligan, Christopher A.}, year={2012}, month={Jan} }
 @article{meentemeyer_haas_vaclavik_2012, title={Landscape Epidemiology of Emerging Infectious Diseases in Natural and Human-Altered Ecosystems}, volume={50}, ISSN={["1545-2107"]}, DOI={10.1146/annurev-phyto-081211-172938}, abstractNote={ A central challenge to studying emerging infectious diseases (EIDs) is a landscape dilemma: Our best empirical understanding of disease dynamics occurs at local scales, whereas pathogen invasions and management occur over broad spatial extents. The burgeoning field of landscape epidemiology integrates concepts and approaches from disease ecology with the macroscale lens of landscape ecology, enabling examination of disease across spatiotemporal scales in complex environmental settings. We review the state of the field and describe analytical frontiers that show promise for advancement, focusing on natural and human-altered ecosystems. Concepts fundamental to practicing landscape epidemiology are discussed, including spatial scale, static versus dynamic modeling, spatially implicit versus explicit approaches, selection of ecologically meaningful variables, and inference versus prediction. We highlight studies that have advanced the field by incorporating multiscale analyses, landscape connectivity, and dynamic modeling. Future research directions include understanding disease as a component of interacting ecological disturbances, scaling up the ecological impacts of disease, and examining disease dynamics as a coupled human-natural system. }, journal={ANNUAL REVIEW OF PHYTOPATHOLOGY, VOL 50}, author={Meentemeyer, Ross K. and Haas, Sarah E. and Vaclavik, Tomas}, year={2012}, pages={379–402} }
 @article{singh_vogler_shoemaker_meentemeyer_2012, title={LiDAR-Landsat data fusion for large-area assessment of urban land cover: Balancing spatial resolution, data volume and mapping accuracy}, volume={74}, ISSN={["1872-8235"]}, url={http://dx.doi.org/10.1016/j.isprsjprs.2012.09.009}, DOI={10.1016/j.isprsjprs.2012.09.009}, abstractNote={The structural characteristics of Light Detection and Ranging (LiDAR) data are increasingly used to classify urban environments at fine scales, but have been underutilized for distinguishing heterogeneous land covers over large urban regions due to high cost, limited spectral information, and the computational difficulties posed by inherently large data volumes. Here we explore tradeoffs between potential gains in mapping accuracy with computational costs by integrating structural and intensity surface models extracted from LiDAR data with Landsat Thematic Mapper (TM) imagery and evaluating the degree to which TM, LiDAR, and LiDAR-TM fusion data discriminated land covers in the rapidly urbanizing region of Charlotte, North Carolina, USA. Using supervised maximum likelihood (ML) and classification tree (CT) methods, we classified TM data at 30 m and LiDAR data and LiDAR-TM fusions at 1 m, 5 m, 10 m, 15 m and 30 m resolutions. We assessed the relative contributions of LiDAR structural and intensity surface models to classification map accuracy and identified optimal spatial resolution of LiDAR surface models for large-area assessments of urban land cover. ML classification of 1 m LiDAR-TM fusions using both structural and intensity surface models increased total accuracy by 32% compared to LiDAR alone and by 8% over TM at 30 m. Fusion data using all LiDAR surface models improved class discrimination of spectrally similar forest, farmland, and managed clearings and produced the highest total accuracies at 1 m, 5 m, and 10 m resolutions (87.2%, 86.3% and 85.4%, respectively). At all resolutions of fusion data and using either ML or CT classifier, the relative contribution of the LiDAR structural surface models (canopy height and normalized digital surface model) to classification accuracy is greater than the intensity surface. Our evaluation of tradeoffs between data volume and thematic map accuracy for this study system suggests that a spatial resolution of 5 m for LiDAR surface models best balances classification performance and the computational challenges posed by large-area assessments of land cover.}, journal={ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING}, author={Singh, Kunwar K. and Vogler, John B. and Shoemaker, Douglas A. and Meentemeyer, Ross K.}, year={2012}, month={Nov}, pages={110–121} }
 @article{lamsal_rizzo_meentemeyer_2012, title={Spatial variation and prediction of forest biomass in a heterogeneous landscape}, volume={23}, DOI={10.1007/s11676-012-0228-6}, number={1}, journal={Journal of Forestry Research}, author={Lamsal, S. and Rizzo, D. M. and Meentemeyer, Ross K.}, year={2012}, pages={13–22} }
 @article{meentemeyer_cunniffe_cook_filipe_hunter_rizzo_gilligan_2011, title={Epidemiological modeling of invasion in heterogeneous landscapes: spread of sudden oak death in California (1990-2030)}, volume={2}, ISSN={["2150-8925"]}, DOI={10.1890/es10-00192.1}, abstractNote={The spread of emerging infectious diseases (EIDs) in natural environments poses substantial risks to biodiversity and ecosystem function. As EIDs and their impacts grow, landscape- to regional-scale models of disease dynamics are increasingly needed for quantitative prediction of epidemic outcomes and design of practicable strategies for control. Here we use spatio-temporal, stochastic epidemiological modeling in combination with realistic geographical modeling to predict the spread of the sudden oak death pathogen (Phytophthora ramorum) through heterogeneous host populations in wildland forests, subject to fluctuating weather conditions. The model considers three stochastic processes: (1) the production of inoculum at a given site; (2) the chance that inoculum is dispersed within and among sites; and (3) the probability of infection following transmission to susceptible host vegetation. We parameterized the model using Markov chain Monte Carlo (MCMC) estimation from snapshots of local- and regional-scale data on disease spread, taking account of landscape heterogeneity and the principal scales of spread. Our application of the model to Californian landscapes over a 40-year period (1990–2030), since the approximate time of pathogen introduction, revealed key parameters driving the spatial spread of disease and the magnitude of stochastic variability in epidemic outcomes. Results show that most disease spread occurs via local dispersal (<250 m) but infrequent long-distance dispersal events can substantially accelerate epidemic spread in regions with high host availability and suitable weather conditions. In the absence of extensive control, we predict a ten-fold increase in disease spread between 2010 and 2030 with most infection concentrated along the north coast between San Francisco and Oregon. Long-range dispersal of inoculum to susceptible host communities in the Sierra Nevada foothills and coastal southern California leads to little secondary infection due to lower host availability and less suitable weather conditions. However, a shift to wetter and milder conditions in future years would double the amount of disease spread in California through 2030. This research illustrates how stochastic epidemiological models can be applied to realistic geographies and used to increase predictive understanding of disease dynamics in large, heterogeneous regions.}, number={2}, journal={ECOSPHERE}, author={Meentemeyer, Ross K. and Cunniffe, Nik J. and Cook, Alex R. and Filipe, Joao A. N. and Hunter, Richard D. and Rizzo, David M. and Gilligan, Christopher A.}, year={2011}, month={Feb} }
 @article{haas_hooten_rizzo_meentemeyer_2011, title={Forest species diversity reduces disease risk in a generalist plant pathogen invasion}, volume={14}, ISSN={["1461-0248"]}, DOI={10.1111/j.1461-0248.2011.01679.x}, abstractNote={Empirical evidence suggests that biodiversity loss can increase disease transmission, yet our understanding of the 'diversity-disease hypothesis' for generalist pathogens in natural ecosystems is limited. We used a landscape epidemiological approach to examine two scenarios regarding diversity effects on the emerging plant pathogen Phytophthora ramorum across a broad, heterogeneous ecoregion: (1) an amplification effect exists where disease risk is greater in areas with higher plant diversity due to the pathogen's wide host range, or (2) a dilution effect where risk is reduced with increasing diversity due to lower competency of alternative hosts. We found evidence for pathogen dilution, whereby disease risk was lower in sites with higher species diversity, after accounting for potentially confounding effects of host density and landscape heterogeneity. Our results suggest that although nearly all plants in the ecosystem are hosts, alternative hosts may dilute disease transmission by competent hosts, thereby buffering forest health from infectious disease.}, number={11}, journal={ECOLOGY LETTERS}, author={Haas, Sarah E. and Hooten, Mevin B. and Rizzo, David M. and Meentemeyer, Ross K.}, year={2011}, month={Nov}, pages={1108–1116} }
 @article{swei_meentemeyer_briggs_2011, title={Influence of Abiotic and Environmental Factors on the Density and Infection Prevalence of Ixodes pacificus (Acari: Ixodidae) With Borrelia burgdorferi}, volume={48}, ISSN={["1938-2928"]}, DOI={10.1603/me10131}, abstractNote={ABSTRACT 
 The abiotic and biotic factors that govern the spatial distribution of Lyme disease vectors are poorly understood. This study addressed the influence of abiotic and biotic environmental variables on Ixodes pacificus Cooley & Kohls (Acari: Ixodidae) nymphs, because it is the primary vector of Borrelia burgdorferi Johnson, Schmidt, Hyde, Steigerwaldt & Brenner in the far-western United States. Three metrics of Lyme disease risk were evaluated: the density of nymphs, the density of infected nymphs, and the nymphal infection prevalence. This study sampled randomly located plots in oak (Quercus spp.) woodland habitat in Sonoma County, CA. Each plot was drag-sampled for nymphal ticks and tested for B. burgdorferi infection. Path analysis was used to evaluate the direct and indirect relationship between topographic, forest structure and microclimatic variables on ticks. Significant negative correlations were found between maximum temperature in the dry season and the density of infected ticks in 2006 and tick density in 2007, but we did not find a significant relationship with nymphal infection prevalence in either year. Tick density and infected tick density had an indirect, positive correlation with elevation, mediated through temperature. This study found that in certain years but not others, temperature maxima in the dry season may constrain the density and density of infected I. pacificus nymphs. In other years, biotic or stochastic factors may play a more important role in determining tick density.}, number={1}, journal={JOURNAL OF MEDICAL ENTOMOLOGY}, author={Swei, A. and Meentemeyer, R. and Briggs, C. J.}, year={2011}, month={Jan}, pages={20–28} }
 @article{metz_frangioso_meentemeyer_rizzo_2011, title={Interacting disturbances: wildfire severity affected by stage of forest disease invasion}, volume={21}, ISSN={["1939-5582"]}, DOI={10.1890/10-0419.1}, abstractNote={Sudden oak death (SOD) is an emerging forest disease causing extensive tree mortality in coastal California forests. Recent California wildfires provided an opportunity to test a major assumption underlying discussions of SOD and land management: SOD mortality will increase fire severity. We examined prefire fuels from host species in a forest monitoring plot network in Big Sur, California (USA), to understand the interactions between disease-caused mortality and wildfire severity during the 2008 Basin Complex wildfire. Detailed measurements of standing dead woody stems and downed woody debris 1-2 years prior to the Basin fire provided a rare picture of the increased fuels attributable to SOD mortality. Despite great differences in host fuel abundance, we found no significant difference in burn severity between infested and uninfested plots. Instead, the relationship between SOD and fire reflected the changing nature of the disease impacts over time. Increased SOD mortality contributed to overstory burn severity only in areas where the pathogen had recently invaded. Where longer-term disease establishment allowed dead material to fall and accumulate, increasing log volumes led to increased substrate burn severity. These patterns help inform forest management decisions regarding fire, both in Big Sur and in other areas of California as the pathogen continues to expand throughout coastal forests.}, number={2}, journal={ECOLOGICAL APPLICATIONS}, author={Metz, Margaret R. and Frangioso, Kerri M. and Meentemeyer, Ross K. and Rizzo, David M.}, year={2011}, month={Mar}, pages={313–320} }
 @article{meng_meentemeyer_2011, title={Modeling of multi-strata forest fire severity using Landsat TM Data}, volume={13}, ISSN={["0303-2434"]}, DOI={10.1016/j.jag.2010.08.002}, abstractNote={Most of fire severity studies use field measures of composite burn index (CBI) to represent forest fire severity and fit the relationships between CBI and Landsat imagery derived differenced normalized burn ratio (dNBR) to predict and map fire severity at unsampled locations. However, less attention has been paid on the multi-strata forest fire severity, which represents fire activities and ecological responses at different forest layers. In this study, using field measured fire severity across five forest strata of dominant tree, intermediate-sized tree, shrub, herb, substrate layers, and the aggregated measure of CBI as response variables, we fit statistical models with predictors of Landsat TM bands, Landsat derived NBR or dNBR, image differencing, and image ratioing data. We model multi-strata forest fire in the historical recorded largest wildfire in California, the Big Sur Basin Complex fire. We explore the potential contributions of the post-fire Landsat bands, image differencing, image ratioing to fire severity modeling and compare with the widely used NBR and dNBR. Models using combinations of post-fire Landsat bands perform much better than NBR, dNBR, image differencing, and image ratioing. We predict and map multi-strata forest fire severity across the whole Big Sur fire areas, and find that the overall measure CBI is not optimal to represent multi-strata forest fire severity.}, number={1}, journal={INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION}, author={Meng, Qingmin and Meentemeyer, Ross K.}, year={2011}, month={Feb}, pages={120–126} }
 @article{kovacs_vaclavik_haight_pang_cunniffe_gilligan_meentemeyer_2011, title={Predicting the economic costs and property value losses attributed to sudden oak death damage in California (2010-2020)}, volume={92}, ISSN={["1095-8630"]}, DOI={10.1016/j.jenvman.2010.12.018}, abstractNote={Phytophthora ramorum, cause of sudden oak death, is a quarantined, non-native, invasive forest pathogen resulting in substantial mortality in coastal live oak (Quercus agrifolia) and several other related tree species on the Pacific Coast of the United States. We estimate the discounted cost of oak treatment, removal, and replacement on developed land in California communities using simulations of P. ramorum spread and infection risk over the next decade (2010-2020). An estimated 734 thousand oak trees occur on developed land in communities in the analysis area. The simulations predict an expanding sudden oak death (SOD) infestation that will likely encompass most of northwestern California and warrant treatment, removal, and replacement of more than 10 thousand oak trees with discounted cost of $7.5 million. In addition, we estimate the discounted property losses to single family homes of $135 million. Expanding the land base to include developed land outside as well as inside communities doubles the estimates of the number of oak trees killed and the associated costs and losses. The predicted costs and property value losses are substantial, but many of the damages in urban areas (e.g. potential losses from increased fire and safety risks of the dead trees and the loss of ecosystem service values) are not included.}, number={4}, journal={JOURNAL OF ENVIRONMENTAL MANAGEMENT}, author={Kovacs, Kent and Vaclavik, Tomas and Haight, Robert G. and Pang, Arwin and Cunniffe, Nik J. and Gilligan, Christopher A. and Meentemeyer, Ross K.}, year={2011}, month={Apr}, pages={1292–1302} }
 @article{lamsal_cobb_cushman_meng_rizzo_meentemeyer_2011, title={Spatial estimation of the density and carbon content of host populations for Phytophthora ramorum in California and Oregon}, volume={262}, ISSN={["1872-7042"]}, DOI={10.1016/j.foreco.2011.05.033}, abstractNote={Outbreak of the emerging infectious disease sudden oak death continues to threaten California and Oregon forests following introduction of the exotic plant pathogen Phytophthora ramorum. Identifying areas at risk and forecasting changes in forest carbon following disease outbreak requires an understanding of the geographical distribution of host populations, which is unknown. In this study, we quantify and map the population density and carbon contents of five key host species for P. ramorum in California and Oregon, including four hosts killed by the pathogen (Notholithocarpus densiflorus, Quercus agrifolia, Quercus kelloggii and Quercus chrysolepis) and the foliar host Umbellularia californica which supports high sporulation rates. We integrate multiple sources of vegetation data, assembled from sparsely distributed (regional-scale) forest inventory and analysis (FIA) plots and more densely distributed (landscape-scale) plots for monitoring sudden oak death, and develop spatial prediction models based on correlation with environmental variables and spatial dependencies in host abundance. We estimate that 1.8 billion N. densiflorus trees (68 Tg C) and 2.6 billion Quercus host trees (227 Tg C) occur across 3.9 and 17.7 million ha of their respective habitat. A total of 436 million U. californica trees (14 Tg C) occur across 4.2 million ha which frequently overlap with Quercus and N. densiflorus host populations. Combination of landscape-scale data with FIA data resulted in more accurate estimation of host populations and their carbon contents. Forests of northern California and southwest Oregon have the highest concentration of the most susceptible hosts along with climatic conditions that favor pathogen spread. This study represents the first spatially-explicit estimate of P. ramorum host populations and their carbon contents which exceed previously published estimates. Our results will inform landscape- to regional-scale models of disease dynamics and guide management decisions regarding ecosystem impacts including risk of C release following widespread tree mortality.}, number={6}, journal={FOREST ECOLOGY AND MANAGEMENT}, author={Lamsal, Sanjay and Cobb, Richard C. and Cushman, J. Hall and Meng, Qingmin and Rizzo, David M. and Meentemeyer, Ross K.}, year={2011}, month={Sep}, pages={989–998} }
 @inbook{rizzo_meentemeyer_garbelotto_2011, title={The emergence of Phytophthora ramorum in North America and Europe}, ISBN={9780309212267}, booktitle={Fungal diseases: an emerging threat to human, animal, and plant health : workshop summary}, publisher={Washington, D.C.:  The National Academies Press}, author={Rizzo, D. M. and Meentemeyer, R. K. and Garbelotto, M.}, editor={L. Olsen, E.R. Choffnes and D.A. Relman and Pray, L.Editors}, year={2011} }
 @article{butkiewicz_meentemeyer_shoemaker_chang_wartell_ribarsky_2010, title={Alleviating the Modifiable Areal Unit Problem within Probe-Based Geospatial Analyses}, volume={29}, ISSN={["0167-7055"]}, DOI={10.1111/j.1467-8659.2009.01707.x}, abstractNote={Abstract}, number={3}, journal={COMPUTER GRAPHICS FORUM}, author={Butkiewicz, Thomas and Meentemeyer, Ross K. and Shoemaker, Douglas A. and Chang, Remco and Wartell, Zachary and Ribarsky, William}, year={2010}, pages={923–932} }
 @inbook{rodman_jackson_meentemeyer_2010, title={An association rule discovery system applied to geographic data}, ISBN={9783540882633}, DOI={10.1007/978-3-540-88264-0_9}, abstractNote={An association rule discovery system has been developed for geographic data. Association rules are applicable to the interpretation of remote sensing images, in which rules derived from another data set can provide ancillary data to guide land cover mapping. The software system developed, called Aspect, works with standard geographic data formats and extends the association rule formulation to handle spatial relationships. Multiple strategies provide guidance for selecting the relevant variables to include in the rules. Association rule results are presented that are derived from environmental conditions, anthropogenic features, land cover, and vegetation.}, booktitle={Standard-based data and information systems for Earth observation}, publisher={New York:  Springer}, author={Rodman, L. C. and Jackson, J. and Meentemeyer, Ross K.}, editor={Liping Di, H.K. RamapriyanEditor}, year={2010} }
 @article{cobb_meentemeyer_rizzo_2010, title={Apparent competition in canopy trees determined by pathogen transmission rather than susceptibility}, volume={91}, ISSN={["1939-9170"]}, DOI={10.1890/09-0680.1}, abstractNote={Epidemiological theory predicts that asymmetric transmission, susceptibility, and mortality within a community will drive pathogen and disease dynamics. These epidemiological asymmetries can result in apparent competition, where a highly infectious host reduces the abundance of less infectious or more susceptible members in a community via a shared pathogen. We show that the exotic pathogen Phytophthora ramorum and resulting disease, sudden oak death, cause apparent competition among canopy trees and that transmission differences among canopy trees drives patterns of disease severity in California coast redwood forests. P. ramorum ranges in its ability to infect, sporulate on, and cause mortality of infected hosts. A path analysis showed that the most prolific inoculum producer, California bay laurel (Umbellularia californica), had a greater impact on the mortality rate of tanoak (Lithocarpus densiflorus) than did other inoculum‐supporting species. In stands experiencing high tanoak mortality, lack of negative impacts by P. ramorum on bay laurel may increase bay laurel density and subsequently result in positive feedback on pathogen populations. This study demonstrates the degree to which invasive, generalist pathogens can cause rapid changes in forest canopy composition and that differences in transmission can be more important than susceptibility in driving patterns of apparent competition.}, number={2}, journal={ECOLOGY}, author={Cobb, Richard C. and Meentemeyer, Ross K. and Rizzo, David M.}, year={2010}, month={Feb}, pages={327–333} }
 @article{davis_borchert_meentemeyer_flint_rizzo_2010, title={Pre-impact forest composition and ongoing tree mortality associated with sudden oak death in the Big Sur region; California}, volume={259}, ISSN={["1872-7042"]}, DOI={10.1016/j.foreco.2010.03.007}, abstractNote={Mixed-evergreen forests of central coastal California are being severely impacted by the recently introduced plant pathogen, Phytophthora ramorum. We collected forest plot data using a multi-scale sampling design to characterize pre-infestation forest composition and ongoing tree mortality along environmental and time-since-fire gradients. Vegetation pattern was described using trend surface analysis, spatial autocorrelation analysis and redundancy analysis. Species-environment associations were modeled using non-parametric multiplicative regression (NPMR). Tanoak (Lithocarpus densiflorus) mortality was analyzed with respect to environmental and biotic factors using trend surface analysis and multivariate regression. Mixed-evergreen forest occurs throughout the Big Sur region but is most widespread in the north, on north facing slopes, at mid-elevations near the coast. Relative basal area of the dominant tree species changes fairly predictably from north to south and from coast to interior in relation to mapped patterns of precipitation, temperature factors and soil characteristics. Most dominant tree species sprout vigorously after fire. The forests experience a mixed-fire regime in this region ranging from low severity understory burns to high severity crown fires, with the latter increasing above the marine inversion layer and at more interior locations. Ceanothus spp. can dominate mixed-evergreen sites for several decades after severe fires. All of the dominant broadleaf evergreen tree species are hosts of P. ramorum, although not all will die from infection. Tanoak mortality decreases from northwest to southeast and is significantly correlated with climate, especially growing degree days and mean annual precipitation, and with basal area of the foliar host bay laurel (Umbellularia californica) in a 0.5–1 ha neighborhood. Adaptive management of mixed-evergreen forest to mitigate P. ramorum impacts in the region will need to consider large local and regional variation in forest composition and the potentially strong interactions between climate, fire, forest composition and disease severity.}, number={12}, journal={FOREST ECOLOGY AND MANAGEMENT}, author={Davis, Frank W. and Borchert, Mark and Meentemeyer, Ross K. and Flint, Alan and Rizzo, David M.}, year={2010}, month={May}, pages={2342–2354} }
 @article{vaclavik_kanaskie_hansen_ohmann_meentemeyer_2010, title={Predicting potential and actual distribution of sudden oak death in Oregon: Prioritizing landscape contexts for early detection and eradication of disease outbreaks}, volume={260}, ISSN={["1872-7042"]}, DOI={10.1016/j.foreco.2010.06.026}, abstractNote={An isolated outbreak of the emerging forest disease sudden oak death was discovered in Oregon forests in 2001. Despite considerable control efforts, disease continues to spread from the introduction site due to slow and incomplete detection and eradication. Annual field surveys and laboratory tests between 2001 and 2009 confirmed a total of 802 infested locations. Here, we apply two invasive species distribution models (iSDMs) of sudden oak death establishment and spread risk to target early detection and control further disease spread in Oregon forests. The goal was to develop (1) a model of potential distribution that estimates the level and spatial variability of disease establishment and spread risk for western Oregon, and (2) a model of actual distribution that quantifies the relative likelihood of current invasion in the quarantine area. Our predictions were based on four groups of primary parameters that vary in space and time: climate conditions, topographical factors, abundance and susceptibility of host vegetation, and dispersal pressure. First, we used multi-criteria evaluation to identify large-scale areas at potential risk of infection. We mapped and ranked host abundance and susceptibility using geospatial vegetation data developed with gradient nearest neighbor imputation. The host vegetation and climate variables were parameterized in accordance to their epidemiological importance and the final appraisal scores were summarized by month to represent a cumulative spread risk index, standardized as five categories from very low to very high risk. Second, using the field data for calibration we applied the machine-learning method, maximum entropy, to predict the actual distribution of the sudden oak death epidemic. The dispersal pressure incorporated in the statistical model estimates the force of invasion at all susceptible locations, allowing us to quantify the relative likelihood of current disease incidence rather than its potential distribution. Our predictions show that 65 km2 of forested land was invaded by 2009, but further disease spread threatens more than 2100 km2 of forests across the western region of Oregon (very high and high risk). Areas at greatest risk of disease spread are concentrated in the southwest region of Oregon where the highest densities of susceptible host species exist. This research identifies high priority locations for early detection and invasion control and illustrates how iSDMs can be used to analyze the actual versus potential distribution of emerging infectious disease in a complex, heterogeneous ecosystem.}, number={6}, journal={FOREST ECOLOGY AND MANAGEMENT}, author={Vaclavik, Tomas and Kanaskie, Alan and Hansen, Everett M. and Ohmann, Janet L. and Meentemeyer, Ross K.}, year={2010}, month={Aug}, pages={1026–1035} }
 @article{ellis_vaclavik_meentemeyer_2010, title={When is connectivity important? A case study of the spatial pattern of sudden oak death}, volume={119}, ISSN={["1600-0706"]}, DOI={10.1111/j.1600-0706.2009.17918.x}, abstractNote={Although connectivity has been examined from many different angles and in many ecological disciplines, few studies have tested in which systems and under what conditions connectivity is important in determining ecological dynamics. Identifying general rules governing when connectivity is important is crucial not only for basic ecology, but also for our ability to manage natural systems, particularly as increasing fragmentation may change the degree to which connectivity influences ecological dynamics. 
 
 
 
In this study, we used statistical regression, least-cost path analysis, and model selection techniques to test the relative importance of potential connectivity in determining the spatial pattern of sudden oak death, a tree disease that is killing millions of oak and tanoak trees along coastal forests of California and Oregon. We hypothesized that potential connectivity, in addition to environmental conditions, is important in determining the spatial distribution of sudden oak death, the importance of connectivity is more apparent when measured using biologically meaningful metrics that account for the effects of landscape structure on disease spread, and the relative importance of environmental variables and connectivity is approximately equal. 
 
 
 
Results demonstrate that potential connectivity was important in determining the spatial pattern of sudden oak death, though it was relatively less important than environmental variables. Moreover, connectivity was important only when using biologically meaningful metrics as opposed to simple distance-based metrics that ignore landscape structure. These results demonstrate that connectivity can be important in systems not typically considered in connectivity studies – highlighting the importance of examining connectivity in a variety of different systems – and demonstrate that the manner in which connectivity is measured may govern our ability to detect its importance.}, number={3}, journal={OIKOS}, author={Ellis, Alicia M. and Vaclavik, Tomas and Meentemeyer, Ross K.}, year={2010}, month={Mar}, pages={485–493} }
 @article{vaclavik_meentemeyer_2009, title={Invasive species distribution modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?}, volume={220}, ISSN={["1872-7026"]}, DOI={10.1016/j.ecolmodel.2009.08.013}, abstractNote={Species distribution models (SDMs) based on statistical relationships between occurrence data and underlying environmental conditions are increasingly used to predict spatial patterns of biological invasions and prioritize locations for early detection and control of invasion outbreaks. However, invasive species distribution models (iSDMs) face special challenges because (i) they typically violate SDM's assumption that the organism is in equilibrium with its environment, and (ii) species absence data are often unavailable or believed to be too difficult to interpret. This often leads researchers to generate pseudo-absences for model training or utilize presence-only methods, and to confuse the distinction between predictions of potential vs. actual distribution. We examined the hypothesis that true-absence data, when accompanied by dispersal constraints, improve prediction accuracy and ecological understanding of iSDMs that aim to predict the actual distribution of biological invasions. We evaluated the impact of presence-only, true-absence and pseudo-absence data on model accuracy using an extensive dataset on the distribution of the invasive forest pathogen Phytophthora ramorum in California. Two traditional presence/absence models (generalized linear model and classification trees) and two alternative presence-only models (ecological niche factor analysis and maximum entropy) were developed based on 890 field plots of pathogen occurrence and several climatic, topographic, host vegetation and dispersal variables. The effects of all three possible types of occurrence data on model performance were evaluated with receiver operating characteristic (ROC) and omission/commission error rates. Results show that prediction of actual distribution was less accurate when we ignored true-absences and dispersal constraints. Presence-only models and models without dispersal information tended to over-predict the actual range of invasions. Models based on pseudo-absence data exhibited similar accuracies as presence-only models but produced spatially less feasible predictions. We suggest that true-absence data are a critical ingredient not only for accurate calibration but also for ecologically meaningful assessment of iSDMs that focus on predictions of actual distributions.}, number={23}, journal={ECOLOGICAL MODELLING}, author={Vaclavik, Tomas and Meentemeyer, Ross K.}, year={2009}, month={Dec}, pages={3248–3258} }
 @article{vanwalleghem_meentemeyer_2009, title={Predicting Forest Microclimate in Heterogeneous Landscapes}, volume={12}, ISSN={["1435-0629"]}, DOI={10.1007/s10021-009-9281-1}, number={7}, journal={ECOSYSTEMS}, author={Vanwalleghem, T. and Meentemeyer, R. K.}, year={2009}, month={Nov}, pages={1158–1172} }
 @article{meentemeyer_anacker_mark_rizzo_2008, title={Early detection of emerging forest disease using dispersal estimation and ecological niche modeling}, volume={18}, ISSN={["1939-5582"]}, DOI={10.1890/07-1150.1}, abstractNote={Distinguishing the manner in which dispersal limitation and niche requirements control the spread of invasive pathogens is important for prediction and early detection of disease outbreaks. Here, we use niche modeling augmented by dispersal estimation to examine the degree to which local habitat conditions vs. force of infection predict invasion of Phytophthora ramorum, the causal agent of the emerging infectious tree disease sudden oak death. We sampled 890 field plots for the presence of P. ramorum over a three-year period (2003-2005) across a range of host and abiotic conditions with variable proximities to known infections in California, USA. We developed and validated generalized linear models of invasion probability to analyze the relative predictive power of 12 niche variables and a negative exponential dispersal kernel estimated by likelihood profiling. Models were developed incrementally each year (2003, 2003-2004, 2003-2005) to examine annual variability in model parameters and to create realistic scenarios for using models to predict future infections and to guide early-detection sampling. Overall, 78 new infections were observed up to 33.5 km from the nearest known site of infection, with slightly increasing rates of prevalence across time windows (2003, 6.5%; 2003-2004, 7.1%; 2003-2005, 9.6%). The pathogen was not detected in many field plots that contained susceptible host vegetation. The generalized linear modeling indicated that the probability of invasion is limited by both dispersal and niche constraints. Probability of invasion was positively related to precipitation and temperature in the wet season and the presence of the inoculum-producing foliar host Umbellularia californica and decreased exponentially with distance to inoculum sources. Models that incorporated niche and dispersal parameters best predicted the locations of new infections, with accuracies ranging from 0.86 to 0.90, suggesting that the modeling approach can be used to forecast locations of disease spread. Application of the combined niche plus dispersal models in a geographic information system predicted the presence of P. ramorum across approximately 8228 km2 of California's 84785 km2 (9.7%) of land area with susceptible host species. This research illustrates how probabilistic modeling can be used to analyze the relative roles of niche and dispersal limitation in controlling the distribution of invasive pathogens.}, number={2}, journal={ECOLOGICAL APPLICATIONS}, author={Meentemeyer, Ross K. and Anacker, Brian L. and Mark, Walter and Rizzo, David M.}, year={2008}, month={Mar}, pages={377–390} }
 @article{meentemeyer_rank_shoemaker_oneal_wickland_frangioso_rizzo_2008, title={Impact of sudden oak death on tree mortality in the Big Sur ecoregion of California}, volume={10}, ISSN={["1573-1464"]}, DOI={10.1007/s10530-007-9199-5}, number={8}, journal={BIOLOGICAL INVASIONS}, author={Meentemeyer, R. K. and Rank, N. E. and Shoemaker, D. A. and Oneal, C. B. and Wickland, A. C. and Frangioso, K. M. and Rizzo, D. M.}, year={2008}, month={Dec}, pages={1243–1255} }
 @article{meentemeyer_rank_anacker_rizzo_cushman_2008, title={Influence of land-cover change on the spread of an invasive forest pathogen}, volume={18}, ISSN={["1939-5582"]}, DOI={10.1890/07-0232.1}, abstractNote={Human-caused changes in land use and land cover have dramatically altered ecosystems worldwide and may facilitate the spread of infectious diseases. To address this issue, we examined the influence of land-cover changes between 1942 and 2000 on the establishment of an invasive pathogen, Phytophthora ramorum, which causes the forest disease known as Sudden Oak Death. We assessed effects of land-cover change, forest structure, and understory microclimate on measures of inoculum load and disease prevalence in 102 15 x 15 m plots within a 275-km2 region in northern California. Within a 150 m radius area around each plot, we mapped types of land cover (oak woodland, chaparral, grassland, vineyard, and development) in 1942 and 2000 using detailed aerial photos. During this 58-year period, oak woodlands significantly increased in area by 25%, while grassland and chaparral decreased by 34% and 51%, respectively. Analysis of covariance revealed that vegetation type in 1942 and woodland expansion were significant predictors of pathogen inoculum load in bay laurel (Umbellularia californica), the primary inoculum-producing host for P. ramorum in mixed evergreen forests. Path analysis showed that woodland expansion resulted in larger forests with higher densities of the primary host trees (U. californica, Quercus agrifolia, Q. kelloggii) and cooler understory temperatures. Together, the positive effects of woodland size and negative effects of understory temperature explained significant variation in inoculum load and disease prevalence in bay laurel; host stem density had additional positive effects on inoculum load. We conclude that enlargement of woodlands and closure of canopy gaps, likely due largely to years of fire suppression, facilitated establishment of P. ramorum by increasing the area occupied by inoculum-production foliar hosts and enhancing forest microclimate conditions. Epidemiological studies that incorporate land-use change are rare but may increase understanding of disease dynamics and improve our ability to manage invasive forest pathogens.}, number={1}, journal={ECOLOGICAL APPLICATIONS}, author={Meentemeyer, Ross K. and Rank, Nathan E. and Anacker, Brian L. and Rizzo, David M. and Cushman, J. Hall}, year={2008}, month={Jan}, pages={159–171} }
 @article{cushman_meentemeyer_2008, title={Multi-scale patterns of human activity and the incidence of an exotic forest pathogen}, volume={96}, ISSN={["1365-2745"]}, DOI={10.1111/j.1365-2745.2008.01376.x}, abstractNote={Summary}, number={4}, journal={JOURNAL OF ECOLOGY}, author={Cushman, J. Hall and Meentemeyer, Ross K.}, year={2008}, month={Jul}, pages={766–776} }
 @article{anacker_rank_huberli_garbelotto_gordon_harnik_whitkus_meentemeyer_2008, title={Susceptibility to Phytophthora ramorum in a key infectious host: landscape variation in host genotype, host phenotype, and environmental factors}, volume={177}, ISSN={["1469-8137"]}, DOI={10.1111/j.1469-8137.2007.02297.x}, abstractNote={Sudden oak death is an emerging forest disease caused by the invasive pathogen Phytophthora ramorum. Genetic and environmental factors affecting susceptibility to P. ramorum in the key inoculum-producing host tree Umbellularia californica (bay laurel) were examined across a heterogeneous landscape in California, USA. Laboratory susceptibility trials were conducted on detached leaves and assessed field disease levels for 97 host trees from 12 225-m(2) plots. Genotype and phenotype characteristics were assessed for each tree. Effects of plot-level environmental conditions (understory microclimate, amount of solar radiation and topographic moisture potential) on disease expression were also evaluated. Susceptibility varied significantly among U. californica trees, with a fivefold difference in leaf lesion size. Lesion size was positively related to leaf area, but not to other phenotypic traits or to field disease level. Genetic diversity was structured at three spatial scales, but primarily among individuals within plots. Lesion size was significantly related to amplified fragment length polymorphism (AFLP) markers, but local environment explained most variation in field disease level. Thus, substantial genetic variation in susceptibility to P. ramorum occurs in its principal foliar host U. californica, but local environment mediates expression of susceptibility in nature.}, number={3}, journal={NEW PHYTOLOGIST}, author={Anacker, Brian L. and Rank, Nathan E. and Huberli, Daniel and Garbelotto, Matteo and Gordon, Sarah and Harnik, Tami and Whitkus, Richard and Meentemeyer, Ross}, year={2008}, pages={756–766} }
 @article{condeso_meentemeyer_2007, title={Effects of landscape heterogeneity on the emerging forest disease sudden oak death}, volume={95}, ISSN={["1365-2745"]}, DOI={10.1111/j.1365-2745.2006.01206.x}, abstractNote={Summary}, number={2}, journal={JOURNAL OF ECOLOGY}, author={Condeso, T. Emiko and Meentemeyer, Ross K.}, year={2007}, month={Mar}, pages={364–375} }
 @article{rodman_meentemeyer_2006, title={A geographic analysis of wind turbine placement in Northern California}, volume={34}, ISSN={["0301-4215"]}, DOI={10.1016/j.enpol.2005.03.004}, abstractNote={The development of new wind energy projects requires a significant consideration of land use issues. An analytic framework using a Geographic Information System (GIS) was developed to evaluate site suitability for wind turbines and to predict the locations and extent of land available for feasible wind power development. The framework uses rule-based spatial analysis to evaluate different scenarios. The suitability criteria include physical requirements as well as environmental and human impact factors. By including socio-political concerns, this technique can assist in forecasting the acceptance level of wind farms by the public. The analysis was used to evaluate the nine-county region of the Greater San Francisco Bay Area. The model accurately depicts areas where large-scale wind farms have been developed or proposed. It also shows that there are many locations available in the Bay Area for the placement of smaller-scale wind turbines. The framework has application to other regions where future wind farm development is proposed. This information can be used by energy planners to predict the extent that wind energy can be developed based on land availability and public perception.}, number={15}, journal={ENERGY POLICY}, author={Rodman, LC and Meentemeyer, RK}, year={2006}, month={Oct}, pages={2137–2149} }
 @article{rodman_jackson_huizar_meentemeyer_2006, title={An Association Rule Discovery System for Geographic Data}, ISBN={["978-0-7803-9509-1"]}, ISSN={["2153-6996"]}, DOI={10.1109/igarss.2006.892}, abstractNote={An association rule discovery system has been developed for geographic data. Association rules are applicable to the interpretation of remote sensing images, in which ancillary data are used to guide land cover mapping. The software system developed, called Aspect, works with standard geographic data formats and extends the association rule formulation to handle spatial relationships. Multiple strategies provide guidance for selecting the relevant variables to include in the rules. Association rule results are presented that are derived from environmental conditions, anthropogenic features, land cover, and vegetation. Many of the data layers used in geospatial analysis are derived from remote sensing data products. These data sets might include vegetation conditions, land use, human structures, and terrain. In some cases, the results from an association rule analysis can be used as ancillary information to assist in the interpretation of remote sensing images. Associations between data layers can be used to guide image recognition and identification (1), or can be applied to validation and error checking of data. Association rules can also be applied to prediction, in which rules found in one domain are applied to new domains where the data are not complete. In those cases it may be useful to infer the presence of features in an area based on the known patterns of occurrence elsewhere.}, journal={2006 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-8}, author={Rodman, Laura C. and Jackson, John and Huizar, Robert, III and Meentemeyer, Ross K.}, year={2006}, pages={3478-+} }
 @article{gordon_meentemeyer_2006, title={Effects of dam operation and land use on stream channel morphology and riparian vegetation}, volume={82}, ISSN={["1872-695X"]}, DOI={10.1016/j.geomorph.2006.06.001}, abstractNote={Dams are well known for influencing channel and vegetation dynamics downstream, but little work has focused on distinguishing effects of land use and channel responses to the impoundment. In this paper, we examined interacting effects of a dam and land use on downstream changes in channel morphology and riparian vegetation along an agricultural stream system in northern California. Measurements of planform channel morphology, vegetation area, and land use were mapped along multiple stream segments based on a chronological sequence of historical aerial photographs over a 34-yr period prior to operation of the dam in 1983 and over a 17-yr period after dam operation, and compared to a nearby, undammed reference stream. A two-factor analysis of covariance (ANCOVA) was used to examine the effect of the dam on changes in bankfull area, stream length, and riparian vegetation area while accounting for the effect of land use and distance downstream. The dammed stream's bankfull area contracted 94% after dam operation. Prior to dam operation, bankfull area decreased when land use area increased, but not after operation of the dam. Stream length varied 64% less after dam operation as a consequence of less frequent episodic channel migration and entrenchment. The area of riparian vegetation was decreasing during the pre-dam period, but then increased 72% after operation of the dam. Across time periods, decreases in the area of riparian vegetation were also associated with increases in land use area in both the dammed and reference stream. After operation of the dam, reduced peak discharges and sediment reduction likely lead to channel incision and constrained channel migration, which allowed vegetation to increase 50% on less accessible, abandoned banks. Rating curve and hydraulic exponent analyses based on stream gauge measurements corroborate statistical analyses of the mapped changes. In conclusion, we found that operation of the dam and land use patterns together influenced spatial and temporal changes in channel morphology and riparian vegetation. Use of a nearby undammed reference stream in conjunction with multivariable analysis of spatially and temporally replicated observations provided an effective framework for unraveling interacting effects of dams and land use activities on stream channel and vegetation dynamics.}, number={3-4}, journal={GEOMORPHOLOGY}, author={Gordon, Eric and Meentemeyer, Ross K.}, year={2006}, month={Dec}, pages={412–429} }
 @article{hunter_meentemeyer_2005, title={Climatologically aided mapping of daily precipitation and temperature}, volume={44}, ISSN={["0894-8763"]}, DOI={10.1175/jam2295.1}, abstractNote={Abstract}, number={10}, journal={JOURNAL OF APPLIED METEOROLOGY}, author={Hunter, RD and Meentemeyer, RK}, year={2005}, month={Oct}, pages={1501–1510} }
 @article{meentemeyer_rizzo_mark_lotz_2004, title={Mapping the risk of establishment and spread of sudden oak death in California}, volume={200}, ISSN={["1872-7042"]}, DOI={10.1016/j.foreco.2004.06.021}, abstractNote={Sudden oak death, caused by the recently described pathogen Phytophthora ramorum, is an emerging forest disease that has reached epidemic levels in coastal forests of central California. We present a rule-based model of P. ramorum establishment and spread risk in California plant communities. The model, which is being used as a management tool to target threatened forests for early-detection monitoring and protection, incorporates the effects of spatial and temporal variability of multiple variables on pathogen persistence. Model predictions are based on current knowledge of host susceptibility, pathogen reproduction, and pathogen transmission with particular regard to host species distribution and climate suitability. Maps of host species distributions and monthly weather conditions were spatially analyzed in a GIS and parameterized to encode the magnitude and direction of each variable's effect on disease establishment and spread. Spread risk predictions were computed for each month of the pathogen's general reproductive season and averaged to generate a cumulative risk map (Fig. 6a and b). The model identifies an alarming number of uninfected forest ecosystems in California at considerable risk of infection by Phytophthora ramorum. This includes, in particular, a broad band of high risk north of Sonoma County to the Oregon border, a narrow band of high risk south of central Monterey County south to central San Luis Obispo County, and scattered areas of moderate and high risk in the Sierra Nevada foothills in Butte and Yuba counties. Model performance was evaluated by comparing spread risk predictions to field observations of disease presence and absence. Model predictions of spread risk were consistent with disease severity observed in the field, with modeled risk significantly higher at currently infested locations than at uninfested locations (P < 0.01, n = 323). Based on what is known about the ecology and epidemiology of sudden oak death, this model provides a simple and effective management tool for identifying emergent infections before they become established.}, number={1-3}, journal={FOREST ECOLOGY AND MANAGEMENT}, author={Meentemeyer, R and Rizzo, D and Mark, W and Lotz, E}, year={2004}, month={Oct}, pages={195–214} }
 @article{meentemeyer_moody_2002, title={Distribution of plant life history types in California chaparral: the role of topographically-determined drought severity}, volume={13}, DOI={10.1111/j.1654-1103.2002.tb02024.x}, abstractNote={Abstract.  Spatial patterns of shrub life history and Ceanothus distribution are examined in relation to topographically‐mediated differences in drought severity within 3 watersheds on the coastal and inland flank of the Santa Ynez Mountains, California. Spatially distributed fields of drought severity are simulated for the studied watersheds using high‐resolution digital terrain data and daily climate data in combination with a process‐based hydro‐ecological model (RHESSys). Field samples of species composition are spatially integrated with the distributed drought data for analysis of ecological relationships. Patterns of seedling recruitment type correspond to topographic variability in drought severity in ways that are consistent with concepts presented in the literature. Species that depend on fire for recruitment are increasingly represented with increasing drought severity, the converse also applies. Sites that experience moderate drought severity permit co‐dominance of species from both recruitment modes. Residual analysis suggests that some of the unexplained variability is related to substrate. Analyses also indicate that the distribution of 5 Ceanothus shrubs reflect differences in drought severity in ways that are consistent with their resistance to water stress‐induced xylem dysfunction. Species from the subgenus Cerastes sort in accordance with moisture availability and have unique spatial distributions. Results are evaluated and discussed with respect to studies on plant morphology, resource use and seedling establishment patterns.}, number={1}, journal={Journal of Vegetation Science}, author={Meentemeyer, Ross K. and Moody, A.}, year={2002}, pages={67–78} }
 @article{kelly_meentemeyer_2002, title={Landscape dynamics of the spread of sudden oak death}, volume={68}, number={10}, journal={Photogrammetric Engineering and Remote Sensing}, author={Kelly, M. and Meentemeyer, R. K.}, year={2002}, pages={1001–1009} }
 @article{moody_meentemeyer_2001, title={Environmental factors influencing spatial patterns of shrub diversity in chaparral, Santa Ynez Mountains, California}, volume={12}, DOI={10.1111/j.1654-1103.2001.tb02615.x}, abstractNote={We examined patterns of shrub species diversity relative to landscape‐scale variability in environmental factors within two watersheds on the coastal flank of the Santa Ynez Mountains, California. Shrub species richness and dominance was sampled at a hierarchy of spatial units using a high‐powered telescope from remote vantage points. Explanatory variables included field estimates of total canopy cover and percentage rock cover, and modeled distributions of slope, elevation, photosynthetically active radiation, topographic moisture index, and local topographic variability. Correlation, multiple regression, and regression tree analyses showed consistent relationships between field‐based measurements of species richness and dominance, and topographically‐mediated environmental variables. In general, higher richness and lower dominance occurred where environmental conditions indicated greater levels of resource limitation with respect to soil moisture and substrate availability. Maximum richness in shrub species occurred on high elevation sites with low topographic moisture index, rocky substrate, and steep slopes. Maximum dominance occurred at low elevation sites with low topographic variability, high potential solar insolation, and high total shrub canopy cover. The observed patterns are evaluated with respect to studies on species‐environment relations, resource use, and regeneration of shrubs in chaparral and coastal sage scrub. The results are discussed in the context of existing species‐diversity hypotheses that hinge on reduced competitive dominance and increased resource heterogeneity under conditions of resource limitation.}, number={1}, journal={Journal of Vegetation Science}, author={Moody, A. and Meentemeyer, Ross K.}, year={2001}, pages={41–52} }
 @article{meentemeyer_moody_franklin_2001, title={Landscape-scale patterns of shrub-species abundance in California chaparral - The role of topographically mediated resource gradients}, volume={156}, ISSN={["1385-0237"]}, DOI={10.1023/a:1011944805738}, number={1}, journal={PLANT ECOLOGY}, author={Meentemeyer, RK and Moody, A and Franklin, J}, year={2001}, month={Sep}, pages={19–41} }
 @article{meentemeyer_moody_2000, title={Automated mapping of conformity between topographic and geological surfaces}, volume={26}, ISSN={["0098-3004"]}, DOI={10.1016/s0098-3004(00)00011-x}, abstractNote={We present a technique to produce spatially distributed fields of geometric alignment between topography and the orientation of geologic bedding planes (topographic/bedding-plane intersection angle). Computation and digital mapping of the topographic/bedding-plane intersection angle (TOBIA) requires the derivation of four spatially distributed variables: topographic slope, slope aspect, bedding dip, and dip azimuth. Slope and slope aspect surfaces are derived from a high resolution (10 m) digital elevation model. Ordinary kriging is used to interpolate spatially continuous fields of dip azimuth and dip from point measurements of strike and dip. Using these variables, TOBIA can be mapped either categorically as slope types, or as a continuous index. Categorical mapping requires two steps. First, slopes are classified into three functional types based on the alignment between the dip azimuth and slope aspect. Slopes are then further partitioned based on the alignment between slope angle and dip angle. Continuous computations of TOBIA rely on a geometric equation using all four variables. The methods provide an efficient means for estimating topographic/bedding plane intersection angles over large areas. Resulting surfaces are useful for a variety of landscape-scale modeling applications, such as the prediction of potential hillslope failure, hydrologic flow paths, and vegetation patterns.}, number={7}, journal={COMPUTERS & GEOSCIENCES}, author={Meentemeyer, RK and Moody, A}, year={2000}, month={Aug}, pages={815–829} }
 @article{meentemeyer_moody_2000, title={Rapid sampling of plant species composition for assessing vegetation patterns in rugged terrain}, volume={15}, ISSN={["1572-9761"]}, DOI={10.1023/a:1008175612254}, number={8}, journal={LANDSCAPE ECOLOGY}, author={Meentemeyer, RK and Moody, A}, year={2000}, month={Dec}, pages={697–711} }
 @article{meentemeyer_butler_1999, title={Hydrogeomorphic effects of beaver dams in Glacier National Park, Montana}, volume={20}, ISSN={["0272-3646"]}, DOI={10.1080/02723646.1999.10642688}, abstractNote={Sediment depth and stream-flow data from 10 beaver ponds illustrate that beavers (Castor canadensis) considerably influence hydrogeomorphic processes in low-order stream systems of Glacier National Park (GNP), Montana. Beaver ponds clearly trap sediment, and the depth and volume of sediment substantially increase with dam age. Beaver impoundments also reduce the velocity and discharge of streams emerging downstream of dams. Older beaver dams more efficiently reduce stream velocity and discharge than young dams. Three older dams actually precluded downstream discharge, redistributing water as hyporheic outflow. The ability of beavers to alter the hydrogeomorphic environment in the near vicinity of their ponds is dramatic, but future work is still needed to elucidate the relative importance of lowered stream energy versus the erosive potential of underloaded water downstream. [Key words: Castor canadensis, beaver dams, beaver ponds, sedimentation, biogeomorphology, hydrogeomorphology.]}, number={5}, journal={PHYSICAL GEOGRAPHY}, author={Meentemeyer, RK and Butler, DR}, year={1999}, pages={436–446} }
 @article{meentemeyer_vogler_butler_1998, title={The geomorphic influences of burrowing beavers on streambanks, Bolin creek, North Carolina}, volume={42}, number={4}, journal={Zeitschrift fur geomorphologie}, author={Meentemeyer, R. K. and Vogler, J. B. and Butler, D. R.}, year={1998}, pages={453–468} }
 @article{meentemeyer_butler_1996, title={Temporal and spatial changes in beaver pond locations, eastern Glacier National Park, Montana, USA}, volume={37}, number={2}, journal={Geographical Bulletin}, author={Meentemeyer, R. K. and Butler, D. R.}, year={1996}, pages={97–104} }