@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{dunn_unruh snyder_mccarter_frey_idassi_schnake_cubbage_2021, title={Bioeconomic Assessment of an Alley Cropping Field Trial in North Carolina, US: Tree Density, Timber Production, and Forage Relationships}, volume={13}, ISSN={["2071-1050"]}, url={http://dx.doi.org/10.3390/su132011465}, DOI={10.3390/su132011465}, abstractNote={Silvopasture, the combination of trees, forage, and livestock, is a management practice that is gaining interest throughout the southeastern U.S. This research analyzed a hay-based alley cropping field trial that is transitioning into a silvopasture system. We planted four different tree spacings—2.4 × 2.4 m, 2.4 × 3.0 m, 3.0 × 3.0 m, and 1.8 × 3.0 m (8 × 8 ft, 8 × 10 ft, 10 × 10ft, and 6 × 10 ft)—of loblolly pine (Pinus taeda L.) and used secondary data for the possible planting of two different grass species—big bluestem (Andropogon gerardii Vitman) and switchgrass (Panicum virgatum L.). Tree inventories, forage samples, biometric modeling, and economic analysis of forage and timber monocultures and mixed systems were analyzed with discounted cash flow and capital budgeting analyses. Tree growth on the pasture site was exceptionally fast, generating high projected returns for timber monocultures, which exceeded returns for monoculture grass crops. Projected timber stand returns had the greatest Net Present Values (NPV) at the 4% discount rate, ranging between USD 3196 and USD 3552 per ha (USD 1294 and USD 1438 per ac) for a 2.4 × 3.0 m or 2.4 × 2.4 m tree spacing yield. Representative grass yields were obtained from secondary sources and had lower productivity, with switchgrass having the highest returns at USD 2581 per ha (USD 1045 per ac). Optimal NPVs for mixed silvopasture stands ranged between about USD 1500 per ha and USD 3500 per ha (USD 600/ac and USD 1400/ac), depending on the tree spacing within bands, the alley spacing, and the degree of competition between trees and grasses.}, number={20}, journal={SUSTAINABILITY}, publisher={MDPI AG}, author={Dunn, Kenneth and Unruh Snyder, Lori and McCarter, James and Frey, Gregory and Idassi, Joshua and Schnake, David and Cubbage, Frederick}, year={2021}, month={Oct} }
 @article{junqueira junior_mello_mello_scolforo_beskow_mccarter_2019, title={Rainfall partitioning measurement and rainfall interception modelling in a tropical semi-deciduous Atlantic forest remnant}, volume={275}, ISSN={["1873-2240"]}, DOI={10.1016/j.agrformet.2019.05.016}, abstractNote={Understanding the interaction between the hydrological cycle and native forests is essential to improve watershed management and support ecological services. The objectives of this study were to analyse and evaluate rainfall interception models applied to an ecosystem from the Brazilian Atlantic Forest Biome (BAFB), classified as “Montane Semi-Deciduous Forest.” The variables Gross Rainfall (P) (rainfall that reaches the canopy), Throughfall (Tf), Stemflow (Sf), and Interception Loss (I) were measured from September 2012 to March 2015. Weather variables were quantified above the canopy by a weather station and then used for canopy evaporation estimation. This estimation was based on two approaches: the slope of the linear regression of gross rainfall against interception, or the Gash procedure (Ev1), and the Penman–Monteith equation (Ev2). Two rainfall interception models (Liu and Gash) were employed, using both Ev1 and Ev2. Thirty-two fixed rain gauges were used for Tf measurements and 32 trees were selected across species and diameter at breast height ranges for Sf observations. The revised version of the analytical Gash model underestimated I by -17.5% and -11.1% for Ev1 and Ev2, respectively, resulting in less accurate estimates. Based on these relative errors, the performance of the Gash model was classified as “fair.” The Liu model overestimated I by 5.3% and 11.3% for Ev1 and Ev2, resulting in assessments of “good” and “fair” respectively, and thus indicating improved performance compared to the Gash model. Therefore, the Liu model coupled with Ev1 is preferable for simulation of rainfall interception in semi-deciduous forests of the BAFB. However, slight overestimation bias was observed, and the model requires tweaking with respect to the estimation of forest storage capacity for this ecosystem. Interception loss modelling is a strategic tool for assessing the influence of different weather patterns and forest vegetative features on water balance in semi-deciduous forest ecosystems.}, journal={AGRICULTURAL AND FOREST METEOROLOGY}, author={Junqueira Junior, Jose Alves and Mello, Carlos Rogerio and Mello, Jose Marcio and Scolforo, Henrique Ferraco and Beskow, Samuel and McCarter, James}, year={2019}, month={Sep}, pages={170–183} }
 @article{scolforo_mctague_burkhart_roise_mccarter_alvares_stape_2019, title={Stand-level growth and yield model system for clonal eucalypt plantations in Brazil that accounts for water availability}, volume={448}, ISSN={["1872-7042"]}, DOI={10.1016/j.foreco.2019.06.006}, abstractNote={Growth and yield (G &Y) model systems aim at forecasting forest productivity. The lack of environmental variables to account for how water availability constrains eucalyptus production in Brazil, however, is argued to be a major drawback of these model systems. Thus, this study aimed to develop a stand-level G & Y model system that accounts for water availability (G & Y with SWD), highlighting its usefulness when applied for clonal eucalypt stands under drier climatic conditions. The dataset is composed of remeasurement information of sixteen research sites that span all climatic regions in Brazil. A total of eleven eucalypt clones were planted in single block plots at each site, and extra replications under the rainfall exclusion system were also installed for these eleven clones in fourteen sites. Linear algebra techniques were used to simultaneously fit a compatible set of prediction and projection basal area equations. A stand-level volume equation was also developed. These equations were validated through the use of an independent dataset composed of the rainfall exclusion plots. Finally, the accuracy and usefulness of a conventional G & Y model system applied to clonal eucalypt stands in Brazil was compared to the new proposed G & Y model system, which accounts for the impact of water availability in eucalyptus productivity. The prediction and projection basal area equations accounting for water availability displayed estimates in the order of 5% more accurate compared to the conventional basal area modeling. Stand-level volume estimates were 40% and 74% less biased through the use of the new G & Y model system. This result highlighted how useful and powerful the newly developed approach is, since the model system was capable to provide accurate estimates through the use of the rainfall exclusion plots. The new G & Y model system is a powerful alternative to estimate forest afforestation yield and is fully capable to accurately update forest inventories. The model system can also be used for projecting how forest growth may be impacted by short-term climate variation.}, journal={FOREST ECOLOGY AND MANAGEMENT}, author={Scolforo, Henrique Ferraco and McTague, John Paul and Burkhart, Harold and Roise, Joseph and McCarter, James and Alvares, Clayton Alcarde and Stape, Jose Luiz}, year={2019}, month={Sep}, pages={22–33} }
 @article{zhao_healey_huang_mccarter_garrard_goeking_zhu_2018, title={Assessing the Effects of Fire Disturbances and Timber Management on Carbon Storage in the Greater Yellowstone Ecosystem}, volume={62}, ISSN={["1432-1009"]}, DOI={10.1007/s00267-018-1073-y}, abstractNote={Accurate characterization of Carbon (C) consequences of forest disturbances and management is critical for informed climate mitigation and adaptation strategies. While research into generalized properties of the forest C cycle informs policy and provides abstract guidance to managers, most management occurs at local scales and relies upon monitoring systems that can consistently provide C cycle assessments that explicitly apply to a defined time and place. We used an inventory-based forest monitoring and simulation tool to quantify C storage effects of actual fires, timber harvests, and forest regeneration conditions in the Greater Yellowstone Ecosystem (GYE). Results show that (1) the 1988 fires had a larger impact on GYE's C storage than harvesting during 1985-2011; (2) continuation of relatively high harvest rates of the region's National Forest land, which declined after 1990, would have shifted the disturbance agent primary importance on those lands from fire to harvest; and (3) accounting for local heterogeneity of post-disturbance regeneration patterns translates into large regional effects on total C storage. Large fires in 1988 released about 8.3 ± 0.3 Mg/ha of C across Yellowstone National Park (YNP, including both disturbed and undisturbed area), compared with total C storage reductions due to harvest of about 2.3 ± 0.3 Mg/ha and 2.6 ± 0.2 Mg/ha in adjacent Caribou-Targhee and Gallatin National Forests, respectively, from 1985-2011. If the high harvest rates observed in 1985-1989 had been maintained through 2011 in GYE National Forests, the C storage effect of harvesting would have quintupled to 10.5 ± 1.0 Mg/ha, exceeding the immediate losses associated with YNP's historic fire but not the longer-term net loss of carbon (16.9 ± 0.8 Mg/ha). Following stand-replacing disturbance such as the 1988 fires, the actual regeneration rate was slower than the default regional average rate assumed by empirically calibrated forest growth models. If regeneration following the 1988 fire had reached regionally average rates, either through different natural circumstances or through more active management, YNP would have had approximately 4.1 Mg/ha more forest carbon by year 2020. This study highlights the relative effects of fire disturbances and management activities on regional C storage, and demonstrates a forest carbon monitoring system that can be both applied consistently across the US and tailored to questions of specific local management interest.}, number={4}, journal={ENVIRONMENTAL MANAGEMENT}, author={Zhao, Feng and Healey, Sean P. and Huang, Chengquan and McCarter, James B. and Garrard, Chris and Goeking, Sara A. and Zhu, Zhiliang}, year={2018}, month={Oct}, pages={766–776} }
 @article{dugan_birdsey_healey_pan_zhang_mo_chen_woodall_hernandez_mccullough_et al._2017, title={Forest sector carbon analyses support land management planning and projects: assessing the influence of anthropogenic and natural factors}, volume={144}, ISSN={["1573-1480"]}, DOI={10.1007/s10584-017-2038-5}, abstractNote={Management of forest carbon stocks on public lands is critical to maintaining or enhancing carbon dioxide removal from the atmosphere. Acknowledging this, an array of federal regulations and policies have emerged that requires US National Forests to report baseline carbon stocks and changes due to disturbance and management and assess how management activities and forest plans affect carbon stocks. To address these requirements with the best-available science, we compiled empirical and remotely sensed data covering the National Forests (one fifth of the area of US forest land) and analyzed this information using a carbon modeling framework. We demonstrate how integration of various data and models provides a comprehensive evaluation of key drivers of observed carbon trends, for individual National Forests. The models in this framework complement each other with different strengths: the Carbon Calculation Tool uses inventory data to report baseline carbon stocks; the Forest Carbon Management Framework integrates inventory data, disturbance histories, and growth and yield trajectories to report relative effects of disturbances on carbon stocks; and the Integrated Terrestrial Ecosystem Carbon Model incorporates disturbance, climate, and atmospheric data to determine their relative impacts on forest carbon accumulation and loss. We report results for several National Forests across the USA and compare their carbon dynamics. Results show that recent disturbances are causing some forests to transition from carbon sinks to sources, particularly in the West. Meanwhile, elevated atmospheric carbon dioxide and nitrogen deposition are consistently increasing carbon stocks, partially offsetting declines due to disturbances and aging. Climate variability introduces concomitant interannual variability in net carbon uptake or release. Targeting forest disturbance and post-disturbance regrowth is critical to management objectives that involve maintaining or enhancing future carbon sequestration.}, number={2}, journal={CLIMATIC CHANGE}, author={Dugan, Alexa J. and Birdsey, Richard and Healey, Sean P. and Pan, Yude and Zhang, Fangmin and Mo, Gang and Chen, Jing and Woodall, Christopher W. and Hernandez, Alexander J. and McCullough, Kevin and et al.}, year={2017}, month={Sep}, pages={207–220} }
 @article{scolforo_soares scolforo_stape_mctague_burkhart_mccarter_castro neto_loos_sartorio_2017, title={Incorporating rainfall data to better plan eucalyptus clones deployment in eastern Brazil}, volume={391}, ISSN={["1872-7042"]}, DOI={10.1016/j.foreco.2017.02.025}, abstractNote={The goals of this study were to identify and group three eucalyptus clones, each under coppice and clear-cut management regimes, into two or more groups based on similar growth rates; and fit a site index equation as a function of rainfall variables for each group to evaluate how different groups were impacted by climatic variation. The database came from the Continuous Forest Inventory (CFI) and weather stations. The CFI was conducted between 1994 and 2012, with climatic data also being gathered for the same period. The study area was managed by clear-cut and coppice regimes, with 126 and 72 CFI plots, respectively. The relationship between clones, management regimes and stand age with annual dominant height growth was assessed by linear mixed effects modeling. Ridge regression was applied for fitting each group as a function of the rainfall variables. Finally, ordinary Kriging was applied for each of the rainfall variables in the study area. Then, site index equations were applied to the generated maps enabling the observation of their pattern throughout the study area as well as their evaluation under a pessimistic climatic scenario. Three groups were defined, since each clone exhibited similar growth behavior under either management regimes; however, the 3 clones differ among each other. A significant reduction in the annual dominant height growth over time was observed for all 3 clones. Ridge regressions afforded good accuracy and equations with sound biological behavior. Applying the fitted site index equations to the maps of precipitation and rainy days enabled the definition of the most appropriate clone to be planted throughout the area. Site quality as a function of rainfall variables could be an important tool to better enable silvicultural planning, since it provides estimates of the site index and also enables the incorporation of short-term climate change.}, journal={FOREST ECOLOGY AND MANAGEMENT}, author={Scolforo, Henrique Ferraco and Soares Scolforo, Jose Roberto and Stape, Jose Luiz and McTague, John Paul and Burkhart, Harold and McCarter, James and Castro Neto, Fernando and Loos, Rodolfo Araujo and Sartorio, Robert Cardoso}, year={2017}, month={May}, pages={145–153} }
 @article{roise_harnish_mohan_scolforo_chung_kanieski_catts_mccarter_posse_shen_2016, title={Valuation and production possibilities on a working forest using multi-objective programming, Woodstock, timber NPV, and carbon storage and sequestration}, volume={31}, ISSN={["1651-1891"]}, DOI={10.1080/02827581.2016.1220617}, abstractNote={ABSTRACT This study analyzes the trade-off between net present value (NPV) of timber resources, and carbon sequestration and storage for a working forest, the Hofmann Forest in North Carolina, USA. Multi-objective optimization is used to determine the production possibility curves showing the relationship between NPV and carbon. We then perform a sensitivity analysis to explore alternative management strategies. For carbon yields we used aboveground pools: branches, leaves, tops and bole as estimated by the Forest Vegetation Simulator (FVS) and LOBDSS using the California Carbon Market Protocols, including product carbon. Timber yields of sawtimber, chip-n-saw and pulpwood were estimated by LOBDSS for planted stands less than 49 years of age, and FVS was used for all natural stands and planted stands 49 years and over. Our results reveal that NPV opportunity costs associated with increasing carbon sequestration at Hofmann Forest are less than the current California carbon market price.}, number={7}, journal={SCANDINAVIAN JOURNAL OF FOREST RESEARCH}, author={Roise, J. P. and Harnish, K. and Mohan, M. and Scolforo, H. and Chung, J. and Kanieski, B. and Catts, G. P. and McCarter, J. B. and Posse, J. and Shen, T.}, year={2016}, pages={674–680} }
 @article{gharis_roise_mccarter_2015, title={A compromise programming model for developing the cost of including carbon pools and flux into forest management}, volume={232}, ISSN={["1572-9338"]}, DOI={10.1007/s10479-013-1519-9}, number={1}, journal={ANNALS OF OPERATIONS RESEARCH}, author={Gharis, L. and Roise, J. and McCarter, J.}, year={2015}, month={Sep}, pages={115–133} }
 @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{kershaw_richards_mccarter_oborn_2010, title={Spatially correlated forest stand structures: A simulation approach using copulas}, volume={74}, ISSN={["1872-7107"]}, DOI={10.1016/j.compag.2010.07.005}, abstractNote={Spatial structure of forest stands is one of the main drivers of forest growth and yield, and is an important indicator of wildlife habitat, aesthetics, and other non-timber forest uses. Because spatial structure is costly to measure, a number of approaches for simulating spatial structures have been proposed. In this paper, we propose a simple approach that is capable of generating multispecies stand structures. Based on the method of copulas (Genest and MacKay, 1986, Am. Stat. 40:280–283), we utilize a normal copula to simulate spatially correlated stand structures. Species composition, diameter, height, and crown ratio distributions of each species, and their correlation with underlying spatial patterns are all controlled by user inputs. Example data sets are used to demonstrate how to estimate required parameters and compare simulated spatial structures with observed spatial structures. Except at the smallest scales (<10 m in the longleaf pine dataset and <2 m in the mixed Acadian Forest dataset), the simulated stand structures adequately captured the observed spatial patterns. Based on these comparisons, we conclude that the system is capable of simulating a range of forest stand spatial structures.}, number={1}, journal={COMPUTERS AND ELECTRONICS IN AGRICULTURE}, author={Kershaw, John A., Jr. and Richards, Evelyn W. and McCarter, James B. and Oborn, Sven}, year={2010}, month={Oct}, pages={120–128} }
 @article{oliver_mccarter_comnick_ceder_nelson_millspaugh_thompson_2009, title={Simulating Landscape Change Using the Landscape Management System}, ISBN={["978-0-12-373631-4"]}, DOI={10.1016/b978-0-12-373631-4.00013-7}, abstractNote={This chapter describes the scientific basis for managing wildlife and other values across forested landscapes, and discusses the organization of the Landscape Management System (LMS) and how its modularity allows it to be improved and integrated with other systems. Managing landscapes can enhance their value to humans by providing appropriate habitats for desired wildlife species. The habitat management is an important determinant of wildlife presence and abundance in addition to hunter harvest of the target species, its prey, or its predators. The overall management system consists of two sets of tools: the Landscape Management System containing the LMS tool and the Decision Analysis System (DAS) Tools containing the “Scope & Group” and “Toggle” tools. The Landscape Management System coordinates the activities of approximately 50 computer programs to facilitate the evaluation of alternative management approaches. The LMS software package uses a point-and-click graphical user interface (GUI) with dropdown menus to interact with information for a specific landscape. A portfolio in LMS consists of a group of stands that are combined into a larger planning unit or landscape. Any user can create a portfolio by using minimal inventory and stand attribute information about individual stands or polygons. Menus within LMS facilitate the performance of functions such as growth, stand treatments, and visualization of stands, and landscapes.}, journal={MODELS FOR PLANNING WILDLIFE CONSERVATION IN LARGE LANDSCAPES}, author={Oliver, Chadwick D. and McCarter, James B. and Comnick, Jeffrey M. and Ceder, Kevin and Nelson, Christopher S. and Millspaugh, JJ and Thompson, FR}, year={2009}, pages={339–366} }
 @article{arseneault_kershaw_mccarter_maclean_2008, title={Forest vegetation simulator ingrowth tool: Incorporating Ingrowth Tree Lists into forest simulator growth projections}, volume={25}, number={3}, journal={Northern Journal of Applied Forestry}, author={Arseneault, J. E. and Kershaw, J. A. and McCarter, J. B. and MacLean, D. A.}, year={2008}, pages={158–160} }