@article{mckerrow_davidson_rubino_faber-langendoen_dockter_2021, title={Quantifying the Representation of Plant Communities in the Protected Areas of the US: An Analysis Based on the US National Vegetation Classification Groups}, volume={12}, ISSN={["1999-4907"]}, DOI={10.3390/f12070864}, abstractNote={Plant communities represent the integration of ecological and biological processes and they serve as an important component for the protection of biological diversity. To measure progress towards protection of ecosystems in the United States for various stated conservation targets we need datasets at the appropriate thematic, spatial, and temporal resolution. The recent release of the LANDFIRE Existing Vegetation Data Products (2016 Remap) with a legend based on U.S. National Vegetation Classification allowed us to assess the conservation status of plant communities of the U.S. The map legend is based on the Group level of the USNVC, which characterizes the regional differences in plant communities based on dominant and diagnostic plant species. By combining the Group level map with the Protected Areas Database of the United States (PAD-US Ver 2.1), we quantified the representation of each Group. If the mapped vegetation is assumed to be 100% accurate, using the Aichi Biodiversity target (17% land in protection by 2020) we found that 159 of the 265 natural Groups have less than 17% in GAP Status 1 & 2 lands and 216 of the 265 Groups fail to meet a 30% representation target. Only four of the twenty ecoregions have >17% of their extent in Status 1 & 2 lands. Sixteen ecoregions are dominated by Groups that are under-represented. Most ecoregions have many hectares of natural or ruderal vegetation that could contribute to future conservation efforts and this analysis helps identify specific targets and opportunities for conservation across the U.S.}, number={7}, journal={FORESTS}, author={McKerrow, Alexa and Davidson, Anne and Rubino, Matthew and Faber-Langendoen, Don and Dockter, Daryn}, year={2021}, month={Jul} } @article{cooper_tsang_infante_daniel_mckerrow_wieferich_2019, title={Protected areas lacking for many common fluvial fishes of the conterminous USA}, volume={25}, ISSN={["1472-4642"]}, DOI={10.1111/ddi.12937}, abstractNote={AbstractAimTo assess the effectiveness of protected areas in two catchment scales (local and network) in conserving regionally common fluvial fishes using modelled species distributions.LocationConterminous United States.MethodsA total of 150 species were selected that were geographically widespread, abundant, non‐habitat specialists and native within nine large ecoregions. Species distribution models were developed using boosted regression trees, and modelled distributions were assessed for protection status under two alternatives: lands strictly managed for biodiversity (Highly Restricted Use) and those allowing multiple uses (Multiple Use), with protection target levels (i.e., the amount of protected area required for protection) for local and network catchments being developed from ecoregion‐based urban and agricultural land use thresholds from fish responses.ResultsOverall, less than 2% of fluvial catchments in the conterminous USA are meeting both local and network catchment protection target levels under the Highly Restricted Use alternative, whereas 16% of catchments met protection levels for the Multiple Use alternative, with protection largely concentrated in the western USA. For common native species distributions within ecoregions, only one species had >10% of streams meeting combined local and network catchment protection target levels under the Highly Restricted Use alternative, whereas 50 distributions (~14% of species distribution models) met this level under the Multiple Use alternative.Main conclusionsEven for fishes considered widespread and abundant, protection levels are lacking, particularly when considering only lands that are actively managed for biodiversity. Given the increasing intensification of anthropogenic activities and substantial uncertainty associated with climate change, considering the conservation status for all species, including those currently considered common, is warranted.}, number={8}, journal={DIVERSITY AND DISTRIBUTIONS}, author={Cooper, Arthur R. and Tsang, Yin-Phan and Infante, Dana M. and Daniel, Wesley M. and McKerrow, Alexa J. and Wieferich, Daniel}, year={2019}, month={Aug}, pages={1289–1303} } @article{mckerrow_tarr_rubino_williams_2018, title={Patterns of species richness hotspots and estimates of their protection are sensitive to spatial resolution}, volume={24}, ISSN={["1472-4642"]}, url={http://dx.doi.org/10.1111/ddi.12779}, DOI={10.1111/ddi.12779}, abstractNote={AbstractAimSpecies richness is a measure of biodiversity often used in spatial conservation assessments and mapped by summing species distribution maps. Commission errors inherent those maps influence richness patterns and conservation assessments. We sought to further the understanding of the sensitivity of hotspot delineation methods and conservation assessments to commission errors, and choice of threshold for hotspot delineation.LocationUnited States.MethodsWe created range maps and 30‐m and 1‐km resolution habitat maps for terrestrial vertebrates in the United States and generated species richness maps with each dataset. With the richness maps and the GAP Protected Areas Dataset, we created species richness hotspot maps and calculated the proportion of hotspots within protected areas; calculating protection under a range of thresholds for defining hotspots. Our method allowed us to identify the influence of commission errors by comparing hotspot maps.ResultsCommission errors from coarse spatial grain data and lack of porosity in the range data inflated richness estimates and altered their spatial patterns. Coincidence of hotspots from different data types was low. The 30‐m hotspots were spatially dispersed, and some were very long distances from the hotspots mapped with coarser data. Estimates of protection were low for each of the taxa. The relationship between estimates of hotspot protection and threshold choice was nonlinear and inconsistent among data types (habitat and range) and grain size (30‐m and 1‐km).Main conclusionsCoarse mapping methods and grain sizes can introduce commission errors into species distribution data that could result in misidentifications of the regions where hotspots occur and affect estimates of hotspot protection. Hotspot conservation assessments are also sensitive to choice of threshold for hotspot delineation. There is value in developing species distribution maps with high resolution and low rates of commission error for conservation assessments.}, number={10}, journal={DIVERSITY AND DISTRIBUTIONS}, author={McKerrow, Alexa J. and Tarr, Nathan M. and Rubino, Matthew J. and Williams, Steven G.}, year={2018}, month={Oct}, pages={1464–1477} } @article{pacifici_reich_miller_gardner_stauffer_singh_mckerrow_collazo_2017, title={Integrating multiple data sources in species distribution modeling: a framework for data fusion}, volume={98}, ISSN={["1939-9170"]}, DOI={10.1002/ecy.1710}, abstractNote={AbstractThe last decade has seen a dramatic increase in the use of species distribution models (SDMs) to characterize patterns of species’ occurrence and abundance. Efforts to parameterize SDMs often create a tension between the quality and quantity of data available to fit models. Estimation methods that integrate both standardized and non‐standardized data types offer a potential solution to the tradeoff between data quality and quantity. Recently several authors have developed approaches for jointly modeling two sources of data (one of high quality and one of lesser quality). We extend their work by allowing for explicit spatial autocorrelation in occurrence and detection error using a Multivariate Conditional Autoregressive (MVCAR) model and develop three models that share information in a less direct manner resulting in more robust performance when the auxiliary data is of lesser quality. We describe these three new approaches (“Shared,” “Correlation,” “Covariates”) for combining data sources and show their use in a case study of the Brown‐headed Nuthatch in the Southeastern U.S. and through simulations. All three of the approaches which used the second data source improved out‐of‐sample predictions relative to a single data source (“Single”). When information in the second data source is of high quality, the Shared model performs the best, but the Correlation and Covariates model also perform well. When the information quality in the second data source is of lesser quality, the Correlation and Covariates model performed better suggesting they are robust alternatives when little is known about auxiliary data collected opportunistically or through citizen scientists. Methods that allow for both data types to be used will maximize the useful information available for estimating species distributions.}, number={3}, journal={ECOLOGY}, author={Pacifici, Krishna and Reich, Brian J. and Miller, David A. W. and Gardner, Beth and Stauffer, Glenn and Singh, Susheela and McKerrow, Alexa and Collazo, Jaime A.}, year={2017}, month={Mar}, pages={840–850} } @article{rose_simons_klein_mckerrow_2016, title={Normalized burn ratios link fire severity with patterns of avian occurrence}, volume={31}, ISSN={0921-2973 1572-9761}, url={http://dx.doi.org/10.1007/s10980-015-0334-x}, DOI={10.1007/s10980-015-0334-x}, number={7}, journal={Landscape Ecology}, publisher={Springer Science and Business Media LLC}, author={Rose, Eli T. and Simons, Theodore R. and Klein, Rob and McKerrow, Alexa J.}, year={2016}, month={Jan}, pages={1537–1550} } @inbook{terando_reich_pacifici_costanza_mckerrow_collazo_2017, title={Uncertainty Quantification and Propagation for Projections of Extremes in Monthly Area Burned Under Climate Change: A Case Study in the Coastal Plain of Georgia, USA}, volume={223}, ISBN={0}, ISSN={2328-8779}, url={http://dx.doi.org/10.1002/9781119028116.ch16}, DOI={10.1002/9781119028116.ch16}, abstractNote={Human-caused climate change is predicted to affect the frequency of hazard-linked extremes. Unusually large wildfires are a type of extreme event that is constrained by climate and can be a hazard to society but also an important ecological disturbance. This chapter focuses on changes in the frequency of extreme monthly area burned by wildfires for the end of the 21st century for a wildfire-prone region in the southeast United States. Predicting changes in area burned is complicated by the large and varied uncertainties in how the climate will change and in the models used to predict those changes. The chapter characterizes and quantifies multiple sources of uncertainty and propagate the expanded prediction intervals of future area burned. It illustrates that while accounting for multiple sources of uncertainty in global change science problems is a difficult task, it will be necessary in order to properly assess the risk of increased exposure to these society-relevant events.}, booktitle={NATURAL HAZARD UNCERTAINTY ASSESSMENT: MODELING AND DECISION SUPPORT}, publisher={John Wiley & Sons, Inc.}, author={Terando, Adam J. and Reich, Brian and Pacifici, Krishna and Costanza, Jennifer and McKerrow, Alexa and Collazo, Jaime A.}, year={2017}, pages={245–256} } @article{martinuzzi_withey_pidgeon_plantinga_mckerrow_williams_helmers_radeloff_2015, title={Future land-use scenarios and the loss of wildlife habitats in the southeastern United States}, volume={25}, ISSN={["1939-5582"]}, DOI={10.1890/13-2078.1}, abstractNote={Land‐use change is a major cause of wildlife habitat loss. Understanding how changes in land‐use policies and economic factors can impact future trends in land use and wildlife habitat loss is therefore critical for conservation efforts. Our goal here was to evaluate the consequences of future land‐use changes under different conservation policies and crop market conditions on habitat loss for wildlife species in the southeastern United States. We predicted the rates of habitat loss for 336 terrestrial vertebrate species by 2051. We focused on habitat loss due to the expansion of urban, crop, and pasture. Future land‐use changes following business‐as‐usual conditions resulted in relatively low rates of wildlife habitat loss across the entire Southeast, but some ecoregions and species groups experienced much higher habitat loss than others. Increased crop commodity prices exacerbated wildlife habitat loss in most ecoregions, while the implementation of conservation policies (reduced urban sprawl, and payments for land conservation) reduced the projected habitat loss in some regions, to a certain degree. Overall, urban and crop expansion were the main drivers of habitat loss. Reptiles and wildlife species associated with open vegetation (grasslands, open woodlands) were the species groups most vulnerable to future land‐use change. Effective conservation of wildlife habitat in the Southeast should give special consideration to future land‐use changes, regional variations, and the forces that could shape land‐use decisions.}, number={1}, journal={ECOLOGICAL APPLICATIONS}, author={Martinuzzi, Sebastian and Withey, John C. and Pidgeon, Anna M. and Plantinga, Andrew J. and Mckerrow, Alexa J. and Williams, Steven G. and Helmers, David P. and Radeloff, Volker C.}, year={2015}, month={Jan}, pages={160–171} } @article{costanza_abt_mckerrow_collazo_2015, title={Linking state-and-transition simulation and timber supply models for forest biomass production scenarios}, volume={2}, ISSN={2372-0352}, url={http://dx.doi.org/10.3934/environsci.2015.2.180}, DOI={10.3934/environsci.2015.2.180}, abstractNote={We linked state-and-transition simulation models (STSMs) with an economics-based timber supply model to examine landscape dynamics in North Carolina through 2050 for three scenarios of forest biomass production. Forest biomass could be an important source of renewable energy in the future, but there is currently much uncertainty about how biomass production would impact landscapes. In the southeastern US, if forests become important sources of biomass for bioenergy, we expect increased land-use change and forest management. STSMs are ideal for simulating these landscape changes, but the amounts of change will depend on drivers such as timber prices and demand for forest land, which are best captured with forest economic models. We first developed state-and-transition model pathways in the ST-Sim software platform for 49 vegetation and land-use types that incorporated each expected type of landscape change. Next, for the three biomass production scenarios, the SubRegional Timber Supply Model (SRTS) was used to determine the annual areas of thinning and harvest in five broad forest types, as well as annual areas converted among those forest types, agricultural, and urban lands. The SRTS output was used to define area targets for STSMs in ST-Sim under two scenarios of biomass production and one baseline, business-as-usual scenario. We show that ST-Sim output matched SRTS targets in most cases. Landscape dynamics results indicate that, compared with the baseline scenario, forest biomass production leads to more forest and, specifically, more intensively managed forest on the landscape by 2050. Thus, the STSMs, informed by forest economics models, provide important information about potential landscape effects of bioenergy production.}, number={2}, journal={AIMS Environmental Science}, publisher={American Institute of Mathematical Sciences (AIMS)}, author={Costanza, Jennifer K. and Abt, Robert C. and McKerrow, Alexa J. and Collazo, Jaime A.}, year={2015}, pages={180–202} } @article{costanza_terando_mckerrow_collazo_2015, title={Modeling climate change, urbanization, and fire effects on Pinus palustris ecosystems of the southeastern U.S.}, volume={151}, ISSN={0301-4797}, url={http://dx.doi.org/10.1016/j.jenvman.2014.12.032}, DOI={10.1016/j.jenvman.2014.12.032}, abstractNote={Managing ecosystems for resilience and sustainability requires understanding how they will respond to future anthropogenic drivers such as climate change and urbanization. In fire-dependent ecosystems, predicting this response requires a focus on how these drivers will impact fire regimes. Here, we use scenarios of climate change, urbanization and management to simulate the future dynamics of the critically endangered and fire-dependent longleaf pine (Pinus palustris) ecosystem. We investigated how climate change and urbanization will affect the ecosystem, and whether the two conservation goals of a 135% increase in total longleaf area and a doubling of fire-maintained open-canopy habitat can be achieved in the face of these drivers. Our results show that while climatic warming had little effect on the wildfire regime, and thus on longleaf pine dynamics, urban growth led to an 8% reduction in annual wildfire area. The management scenarios we tested increase the ecosystem's total extent by up to 62% and result in expansion of open-canopy longleaf by as much as 216%, meeting one of the two conservation goals for the ecosystem. We find that both conservation goals for this ecosystem, which is climate-resilient but vulnerable to urbanization, are only attainable if a greater focus is placed on restoration of non-longleaf areas as opposed to maintaining existing longleaf stands. Our approach demonstrates the importance of accounting for multiple relevant anthropogenic threats in an ecosystem-specific context in order to facilitate more effective management actions.}, journal={Journal of Environmental Management}, publisher={Elsevier BV}, author={Costanza, Jennifer K. and Terando, Adam J. and McKerrow, Alexa J. and Collazo, Jaime A.}, year={2015}, month={Mar}, pages={186–199} } @article{terando_costanza_belyea_dunn_mckerrow_collazo_2014, title={The Southern Megalopolis: Using the Past to Predict the Future of Urban Sprawl in the Southeast U.S}, volume={9}, ISSN={1932-6203}, url={http://dx.doi.org/10.1371/journal.pone.0102261}, DOI={10.1371/journal.pone.0102261}, abstractNote={The future health of ecosystems is arguably as dependent on urban sprawl as it is on human-caused climatic warming. Urban sprawl strongly impacts the urban ecosystems it creates and the natural and agro-ecosystems that it displaces and fragments. Here, we project urban sprawl changes for the next 50 years for the fast-growing Southeast U.S. Previous studies have focused on modeling population density, but the urban extent is arguably as important as population density per se in terms of its ecological and conservation impacts. We develop simulations using the SLEUTH urban growth model that complement population-driven models but focus on spatial pattern and extent. To better capture the reach of low-density suburban development, we extend the capabilities of SLEUTH by incorporating street-network information. Our simulations point to a future in which the extent of urbanization in the Southeast is projected to increase by 101% to 192%. Our results highlight areas where ecosystem fragmentation is likely, and serve as a benchmark to explore the challenging tradeoffs between ecosystem health, economic growth and cultural desires.}, number={7}, journal={PLoS ONE}, publisher={Public Library of Science (PLoS)}, author={Terando, Adam J. and Costanza, Jennifer and Belyea, Curtis and Dunn, Robert R. and McKerrow, Alexa and Collazo, Jaime A.}, editor={Layman, Craig A.Editor}, year={2014}, month={Jul}, pages={e102261} } @article{wickham_homer_vogelmann_mckerrow_mueller_herold_coulston_2014, title={The multi-resolution land characteristics (MRLC) consortium-20 years of development and integration of USA national land cover data}, volume={6}, number={8}, journal={Journal of Remote Sensing}, author={Wickham, J. and Homer, C. and Vogelmann, J. and McKerrow, A. and Mueller, R. and Herold, N. and Coulston, J.}, year={2014}, pages={7424–7441} } @article{costanza_hulcr_koch_earnhardt_mckerrow_dunn_collazo_2012, title={Simulating the effects of the southern pine beetle on regional dynamics 60 years into the future}, volume={244}, ISSN={0304-3800}, url={http://dx.doi.org/10.1016/j.ecolmodel.2012.06.037}, DOI={10.1016/j.ecolmodel.2012.06.037}, abstractNote={We developed a spatially explicit model that simulated future southern pine beetle (Dendroctonus frontalis, SPB) dynamics and pine forest management for a real landscape over 60 years to inform regional forest management. The SPB has a considerable effect on forest dynamics in the Southeastern United States, especially in loblolly pine (Pinus taeda) stands that are managed for timber production. Regional outbreaks of SPB occur in bursts resulting in elimination of entire stands and major economic loss. These outbreaks are often interspersed with decades of inactivity, making long-term modeling of SPB dynamics challenging. Forest management techniques, including thinning, have proven effective and are often recommended as a way to prevent SPB attack, yet the robustness of current management practices to long-term SPB dynamics has not been examined. We used data from previously documented SPB infestations and forest inventory data to model four scenarios of SPB dynamics and pine forest management. We incorporated two levels of beetle pressure: a background low level, and a higher level in which SPB had the potential to spread among pine stands. For each level of beetle pressure, we modeled two scenarios of forest management: one assuming forests would be managed continuously via thinning, and one with a reduction in thinning. For our study area in Georgia, Florida, and Alabama, we found that beetle pressure and forest management both influenced the landscape effects of SPB. Under increased SPB pressure, even with continuous management, the area of pine forests affected across the region was six times greater than under baseline SPB levels. However, under high SPB pressure, continuous management decreased the area affected by nearly half compared with reduced management. By incorporating a range of forest and SPB dynamics over long time scales, our results extend previous modeling studies, and inform forest managers and policy-makers about the potential future effects of SPB. Our model can also be used to investigate the effects of additional scenarios on SPB dynamics, such as alternative management or climate change.}, journal={Ecological Modelling}, publisher={Elsevier BV}, author={Costanza, Jennifer K. and Hulcr, Jiri and Koch, Frank H. and Earnhardt, Todd and McKerrow, Alexa J. and Dunn, Rob R. and Collazo, Jaime A.}, year={2012}, month={Oct}, pages={93–103} } @article{iglecia_collazo_mckerrow_2012, title={Use of Occupancy Models to Evaluate Expert Knowledge-based Species-Habitat Relationships}, volume={7}, ISSN={["1712-6568"]}, DOI={10.5751/ace-00551-070205}, abstractNote={Expert knowledge-based species-habitat relationships are used extensively to guide conservation planning, particularly when data are scarce. Purported relationships describe the initial state of knowledge, but are rarely tested. We assessed support in the data for suitability rankings of vegetation types based on expert knowledge for three terrestrial avian species in the South Atlantic Coastal Plain of the United States. Experts used published studies, natural history, survey data, and field experience to rank vegetation types as optimal, suitable, and marginal. We used single-season occupancy models, coupled with land cover and Breeding Bird Survey data, to examine the hypothesis that patterns of occupancy conformed to species-habitat suitability rankings purported by experts. Purported habitat suitability was validated for two of three species. As predicted for the Eastern Wood-Pewee (Contopus virens) and Brown-headed Nuthatch (Sitta pusilla), occupancy was strongly influenced by vegetation types classified as “optimal habitat” by the species suitability rankings for nuthatches and wood-pewees. Contrary to predictions, Red-headed Woodpecker (Melanerpes erythrocephalus) models that included vegetation types as covariates received similar support by the data as models without vegetation types. For all three species, occupancy was also related to sampling latitude. Our results suggest that covariates representing other habitat requirements might be necessary to model occurrence of generalist species like the woodpecker. The modeling approach described herein provides a means to test expert knowledge-based species-habitat relationships, and hence, help guide conservation planning. RESUME. Les relations especes-habitat etablies a partir des connaissances d’experts sont largement utilisees pour orienter la planification de la conservation, surtout lorsque les donnees sont rares. Ces relations presumees representent les rudiments de la connaissance, mais sont rarement testees. L’adequation du classement de milieux etabli par des experts a ete evaluee pour trois especes de passereaux de la Plaine cotiere de l’Atlantique Sud, aux Etats-Unis. Les experts ont utilise des donnees publiees (recherches, histoire naturelle, releves) et leur experience sur le terrain afin de classer les milieux selon trois categories, soit optimaux, adequats ou marginaux. Nous avons applique des modeles de presence, fondes sur une seule saison, a des donnees d’occupation du sol et de releves d’oiseaux nicheurs afin d’examiner l’hypothese voulant que les profils de presence concordent avec le classement de la qualite des milieux presume par les experts. La qualite presumee des milieux a ete validee pour deux des trois especes. Comme predit pour le Pioui de l’Est (Contopus virens) et la Sittelle a tete brune (Sitta pusilla), la presence de l’espece s’est revelee fortement liee aux milieux classes comme « optimaux » pour les sittelles et les piouis. Contrairement aux predictions pour le Pic a tete rouge (Melanerpes erythrocephalus), les modeles qui incluaient les milieux comme covariables etaient equivalents aux modeles qui ne les incluaient pas. Chez les trois especes, la presence etait aussi correlee a la latitude de l’echantillonnage. Nos resultats semblent indiquer qu’il serait peut-etre necessaire d’inclure des covariables relatives a d’autres besoins en matiere d’habitat afin de modeliser la presence d’especes generalistes comme le pic. L’approche de modelisation decrite dans cette etude permet de tester les relations especes-habitat etablies d’apres les connaissances d’experts et, par consequent, contribue a orienter la planification de la conservation.}, number={2}, journal={AVIAN CONSERVATION AND ECOLOGY}, author={Iglecia, Monica N. and Collazo, Jaime A. and McKerrow, Alexa J.}, year={2012}, month={Dec} } @article{homer_dewitz_fry_coan_hossain_larson_herold_mckerrow_vandriel_wickham_2007, title={Completion of the 2001 National Land Cover Database for the conterminous United States}, volume={73}, number={4}, journal={Photogrammetric Engineering and Remote Sensing}, author={Homer, C. and Dewitz, J. and Fry, J. and Coan, M. and Hossain, N. and Larson, C. and Herold, N. and McKerrow, A. and Vandriel, J. N. and Wickham, J.}, year={2007}, pages={337–341} } @article{lunetta_ediriwickrema_johnson_lyon_mckerrow_2002, title={Impacts of vegetation dynamics on the identification of land-cover change in a biologically complex community in North Carolina, USA}, volume={82}, ISSN={["0034-4257"]}, DOI={10.1016/S0034-4257(02)00042-1}, abstractNote={A land-cover (LC) change detection experiment was performed in the biologically complex landscape of the Neuse River Basin (NRB), North Carolina using Landsat 5 and 7 imagery collected in May of 1993 and 2000. Methods included pixel-wise Normalized Difference Vegetation Index (NDVI) and Multiband Image Difference (MID) techniques. The NDVI method utilized non-normalized (raw) imagery data, while the MID method required normalized imagery. Image normalization techniques included both automatic scattergram-controlled regression (ASCR) and localized relative radiometric normalization (LRRN) techniques. Change/no-change thresholds for each method were optimized using calibration curves developed from reference data and a series of method-specific binary change masks. Cover class-specific thresholds were derived for each of the four methods using a previously developed NRB-LC classification (1998–1999) to support data stratification. An independent set of accuracy assessment points was selected using a disproportionate stratified sampling strategy to support the development of error matrices. Area-weighted conditional probability accuracy statistics were calculated based on the areal extent of change and no change for each cover class. All methods tested exhibited acceptable accuracies, ranging between 80% and 91%. However, change omission errors for woody cover types were unacceptably high, with values ranging between 60% and 79%. Overall commission errors in the change category were also high (42–51%) and strongly affected by the agriculture class. There were no significant differences in the Kappa coefficient between the NDVI, MID ASCR, and LRRN normalization methods. The MID non-normalized method was inferior to both the NDVI and MID ASCR methods. Stratification by major LC type had no effect on overall accuracies, regardless of method.}, number={2-3}, journal={REMOTE SENSING OF ENVIRONMENT}, author={Lunetta, RS and Ediriwickrema, J and Johnson, DM and Lyon, JG and McKerrow, A}, year={2002}, month={Oct}, pages={258–270} } @article{harding_crone_elderd_hoekstra_mckerrow_perrine_regetz_rissler_stanley_walters_2001, title={The scientific foundations of habitat conservation plans: a quantitative assessment}, volume={15}, ISSN={["0888-8892"]}, DOI={10.1046/j.1523-1739.2001.015002488.x}, abstractNote={Abstract: The number of habitat conservation plans ( HCP) has risen dramatically since the first plan was written over 18 years ago. Until recently, no studies have quantitatively investigated the scientific foundations underlying these documents. As part of a larger study of HCPs, we examined 43 plans primarily to assess the availability and use of scientific data and secondarily to determine the extent of involvement by, and influence of, independent scientists within the process. Specifically, our analysis focused on five key steps taken when an HCP is developed: assessing status of a species, determining take, predicting the project effects, mitigating for those effects, and monitoring of take and mitigation. In general, we found that the preparers of HCPs utilized existing scientific information fairly well, with 60% of plans not missing any available information described by our study as “starkly necessary.” The most common types of underutilized available data included those describing the influence of stochastic processes and habitat quality or quantity on species persistence. For many species, however, data on biology or status simply did not exist, as demonstrated by the fact that we could locate quantitative population estimates for only 10% of the species. Furthermore, for 42% of the species examined we had insufficient data and analysis to determine clearly how predicted take might affect the population. In many cases, mitigation measures proposed to offset take frequently addressed the most important local threats to the species with moderately reliable strategies. Species with monitoring programs rated as sufficient had plans that proposed to collect a greater amount of “quantitative” data than did those programs rated insufficient. Finally, when species “experts” were consulted, plan quality was generally higher. Overall, available scientific information in a majority of categories was fairly well utilized, but for many species additional studies and more in‐depth analyses were required to provide adequate support for issuance of an incidental take permit.}, number={2}, journal={CONSERVATION BIOLOGY}, author={Harding, EK and Crone, EE and Elderd, BD and Hoekstra, JM and McKerrow, AJ and Perrine, JD and Regetz, J and Rissler, LJ and Stanley, AG and Walters, EL}, year={2001}, month={Apr}, pages={488–500} }