Source: USDA Forest Service - Southern Research Station submitted to
FOREST HEALTH MONITORING RESEARCH
Sponsoring Institution
Forest Service/USDA
Project Status
TERMINATED
Funding Source
USDA INHOUSE
Reporting Frequency
Annual
Accession No.
0217157
Grant No.
(N/A)
Project No.
SRS-4854-1
Proposal No.
(N/A)
Multistate No.
(N/A)
Program Code
(N/A)
Project Start Date
Oct 1, 2007
Project End Date
Sep 30, 2018
Grant Year
(N/A)
Project Director
Lee, D.
Recipient Organization
USDA Forest Service - Southern Research Station
200 WEAVER BLVD., PO BOX 2680
ASHEVILLE,NC 28804
Performing Department
(N/A)
Non Technical Summary
Tracking the health of forest ecosystems is a legal mandate essential to effective management. Distinguishing symptomatic changes in forest structure, composition, and productivity from natural variation is a challenge at scales ranging from individual stands to regional landscapes. The Forest Health Monitoring Program is a national collaborative effort involving State and Federal agencies to monitor long-term trends in forest conditions and productivity. Continued improvement is needed to overcome key scientific obstacles and to demonstrate technical advances for implementation.
Animal Health Component
0%
Research Effort Categories
Basic
15%
Applied
45%
Developmental
40%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
1230699107030%
1230699209040%
1317210208015%
1360699107015%
Knowledge Area
131 - Alternative Uses of Land; 123 - Management and Sustainability of Forest Resources; 136 - Conservation of Biological Diversity;

Subject Of Investigation
0699 - Trees, forests, and forest products, general; 7210 - Remote sensing equipment and technology;

Field Of Science
1070 - Ecology; 2080 - Mathematics and computer sciences; 2090 - Statistics, econometrics, and biometrics;
Goals / Objectives
Problem 1a. Key elements are needed to improve existing monitoring systems and to develop new sampling and survey designs, measurement techniques, and estimation procedures for forest survey and inventory. 1) Complete an analysis of the power of the Phase 3 Crown Indicator to detect change. Present results at the national FIA symposium and publish in proceedings. 2) Develop a spatial scan tool designed to identify spatial clustering of Phase 3 Detection plot locations that exhibit signs of adverse forest health. 3) Assist Mexican scientists with pilot testing of forest health indicators on a monitoring system based on the FHM/FIA Phase 3 plot network. 4) Publish GTR to serve as a reference manual to help citizen scientist groups plan and implement practical monitoring systems. 5) Publish journal article on the use of Densiometers for forest health monitoring. 6) Develop ground-based monitoring system along Appalachian Trail to detect early signs of climate change and other regional stressors. 7) Coordinate Production of FIA Phase 2 and Phase 3 Field Guides, and FIA Database (FIADB) User Guides. Problem 1b. Protocols are needed to integrate data, models, and interpretation techniques to assess forest health and conduct risk assessments and analyses at multiple scales. 1) Produce the FHM national technical reports 2) Publish Mid-Atlantic Integrated Assessment (MAIA) GTR, and post technical summary and other key information on EFETAC website . 3) Complete three chapters for GTR synthesizing results of FHM Evaluation Monitoring projects funded between 1998 and 2007: 4) Produce risk map for Mediterranean Pine Engraver. 5) Publish instruction manual describing risk-map production techniques. 6) Journal article on special detection surveys for introduced pests. 7) Publish articles on risk analysis and pest invasion models, Montreal Process conceptual models, and impact of fypsy moth in urban areas. 8) Develop software to model the spread of invasive pests using a Bayesian network approach. Problem 1c. Protocols are needed to utilize spatial analyses and principles of landscape ecology in forest health monitoring and assessment, including interactions between nature and society. 1) Analyze forest fragmentation and publish results two RPA reports. 2) Analyze rangeland fragmentation for FIA's Oregon Range Pilot 3) Analyze forest fragmentation and publish results in the 2010 Montreal Process 5-year report. 4) Publish an analysis of fragmentation change based on comparisons between the current and previous NLCD cover maps. 5) Develop standard set of fragmentation analytical products for state-level analyses for use by S&PF and FIA analysts. Problem 1d. Protocols are needed to utilize data from long-term comprehensive monitoring of key ecosystem processes and components in forest health assessments. 1) Utilize historic FHM and FIA data to analyze increased levels of crown dieback observed in Northern White Cedars in Maine and Michigan. 2) Deliver software necessary to integrate data from FIA forest plots in urban areas with FIA nonforest (urban pilot) plots in urban areas. 3) Publish paper based on FHM urban street-tree data collected in MA and MD.
Project Methods
The studies needed in order to meet the objectives identified above involve a broad range of statistical techniques, spatial analyses, and computer simulation and modeling. Few of the studies require acquisition of new field data. Instead, the research teams involved in these analyses rely upon data collected by the Forest Inventory and Analysis Program (FIA) or other State or Federal partners. Production of the National Forest Health Monitoring Reports, which serve as an outlet for much of the research identified here, is accomplished through a cooperative agreement with the North Carolina State University.

Progress 10/01/07 to 09/30/18

Outputs
OUTPUTS: The final work on the problem area ended in FY2015

Impacts
(N/A)

Publications

  • Clark, Stacy L.; Schweitzer, Callie J.; Saunders, Mike R.; Belair, Ethan P.; Torreano, Scott J.; Schlarbaum, Scott E. 2014. The American chestnut and fire: 6-year research results. Waldrop, Thomas A., ed. 2014. In proceedings, Wildland fire in the Appalachians: Discussions among managers and scientists. Gen. Tech. Rep. SRS-199. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 10 p.
  • Fei, Songlin; Desprez, Johanna M.; Potter, Kevin M.; Jo, Insu; Knott, Jonathan A.; Oswalt, Christopher M. 2017.Divergence of species responses to climate change. Science Advances. 3(5): e1603055-. DOI: 10.1126/sciadv.1603055 1-9 pp.
  • Gamon, John A.; Huemmrich, K. Fred; Wong, Christopher Y. S.; Ensminger, Ingo; Garrity, Steven; Hollinger, David Y.; Noormets, Asko; Peñuelas, Josep 2016.A remotely sensed pigment index reveals photosynthetic phenology in evergreen conifers. Proceedings of the National Academy of Sciences. 113(46): 13087-13092. https://doi.org/10.1073/pnas.1606162113.
  • Guo, Qinfeng 2017.Temporal changes in native-exotic richness correlations during early post-fire succession. Acta Oecologica. 80: 47-50. https://doi.org/10.1016/j.actao.2017.03.002.
  • Hallema, Dennis W.; Sun, Ge; Caldwell, Peter V.; Norman, Steven P.; Cohen, Erika C.; Liu, Yongqiang; Ward, Eric J.; McNulty, Steven G. 2016. Assessment of wildland fire impacts on watershed annual water yield: Analytical framework and case studies in the United States. Ecohydrology. DOI: 10.1002/eco.1794
  • Hao, L.; Sun, G.; Liu, Y.-Q.; Zhou, G. S.;  Wan, J. H.; Zhang, L. B.; Niu, J. L.; Sang, Y. H.; He, J. J 2015. Evapotranspiration and soil moisture dynamics in a temperate grassland ecosystem in Inner Mongolia China. American Society of Agricultural and Biological Engineersa. Vol. 59(2): 577- 590.  14 p.  DOI 10.13031/trans.58.11099.
  • Hastings, John M.; Potter, Kevin M.; Koch, Frank H.; Megalos, Mark; Jetton, Robert M. 2017. Prioritizing conservation seed banking locations for imperiled hemlock species using multi-attribute frontier mapping. New Forests, 48:301-316. 16 p. DOI:10.1007/s11056-017-9575-7
  • Li, Gen; Zhang, Fangmin; Jing, Yuanshu; Liu, Yibo; Sun, Ge 2017.Response of evapotranspiration to changes in land use and land cover and climate in China during 2001⿿2013. Science of The Total Environment. 596-597: 256-265p https://doi.org/10.1016/j.scitotenv.2017.04.080.
  • Lin, Wen; Noormets, Asko; King, John S.; Sun, Ge; McNulty, Steve; Domec, Jean-Christophe; Cernusak, Lucas 2017. An extractive removal step optimized for a high-throughput α-cellulose extraction method for δ 13 C and δ 18 O stable isotope ratio analysis in conifer tree rings . Tree Physiology 37, 142⿿150. 9 p.  doi:10.1093/treephys/tpw084.
  • Liu, Chunwei; Sun, Ge; McNulty, Steven G.; Noormets, Asko; Fang, Yuan 2017. Environmental controls on seasonal ecosystem evapotranspiration/potential evapotranspiration ratio as determined by the global eddy flux measurements. Hydrology and Earth System Sciences, Vol. 21(1): 12 pages.: 311-322.
  • Musavi, Talie; Migliavacca, Mirco; van de Weg, Martine Janet; Kattge, Jens; Wohlfahrt, Georg; van Bodegom, Peter M.; Reichstein, Markus; Bahn, Michael; Carrara, Arnaud; Domingues, Tomas F.; Gavazzi, Michael; Gianelle, Damiano; Gimeno, Cristina; Granier, André; Gruening, Carsten; Havránková, Kateſina; Herbst, Mathias; Hrynkiw, Charmaine; Kalhori, Aram; Kaminski, Thomas; Klumpp, Katja; Kolari, Pasi; Longdoz, Bernard; Minerbi, Stefano; Montagnani, Leonardo; Moors, Eddy; Oechel, Walter C.; Reich, Peter B.; Rohatyn, Shani; Rossi, Alessandra; Rotenberg, Eyal; Varlagin, Andrej; Wilkinson, Matthew; Wirth, Christian; Mahecha, Miguel D. 2016.Potential and limitations of inferring ecosystem photosynthetic capacity from leaf functional traits. Ecology and Evolution. 6(20): 7352-7366. https://doi.org/10.1002/ece3.2479.
  • Norman, Steven P.;Hargrove, William W.; Christie, William M. 2017.Spring and autumn phenological variability across environmental gradients of Great Smoky Mountains National Park, USA. Remote Sensing. 9(5): 407-424. 18 p.  https://doi.org/10.3390/rs9050407.
  • Nunez-Mir, Gabriela C.; Liebhold, Andrew M.; Guo, Qinfeng; Brockerhoff, Eckehard G.; Jo, Insu; Ordonez, Kimberly; Fei, Songlin 2017.Biotic resistance to exotic invasions: its role in forest ecosystems, confounding artifacts, and future directions. Biological Invasions. 95(1): 3259-. https://doi.org/10.1007/s10530-017-1413-5.
  • Oswalt, Christopher M.; Fei, Songlin; Guo, Qinfeng; Iannone III, Basil V.; Oswalt, Sonja N.; Pijanowski, Bryan C.; Potter, Kevin M. 2016. Corrigendum: A subcontinental view of forest plant invasions. NeoBiota, Vol. 31: 2 pages.: 105-106. DOI:10.3897/neobiota.31.8785
  • Riitters, Kurt; Costanza, Jennifer K.; Buma, Brian 2017.Interpreting multiscale domains of tree cover disturbance patterns in North America. Ecological Indicators. 80: 147-152. 6 p.  https://doi.org/10.1016/j.ecolind.2017.05.022.
  • Sun, S.; Sun, G.; Cohen, E.; McNulty, S. G.; Caldwell, P.; Duan, K.; Zhang, Y. 2015. Predicting future US water yield and ecosystem productivity by linking an ecohydrological model to WRF dynamically downscaled climate projections. Hydrology and Earth System Sciences Discussions, Vol. 12(12): 44 pages.: 12703-12746.  DOI: 10.5194/hessd-12-12703-2015
  • Vogt, Peter; Riitters, Kurt 2017.GuidosToolbox: universal digital image object analysis. European Journal of Remote Sensing. 50(1): 352-361 p https://doi.org/10.1080/22797254.2017.1330650.
  • Hughes, M. A.; Riggins, J. J.; Koch, F. H.; Cognato, A. I.; Anderson, C.; Formby, J. P.; Dreaden, T. J.; Ploetz, R. C.; Smith, J. A. 2017.No rest for the laurels: symbiotic invaders cause unprecedented damage to southern USA forests. Biological Invasions. 79(7): 22-. 36. 15 p.  https://doi.org/10.1007/s10530-017-1427-z.
  • Khorram, S.; van der Wiele, C.F.; Koch, F.H.; Nelson, S.A.C.; Potts, M.D. 2016. Principles of Applied Remote Sensing. Springer, New York. 307 p.
  • Wickham, James; Riitters, Kurt; Vogt, Peter; Costanza, Jennifer; Neale, Anne 2017.An inventory of continental U.S. terrestrial candidate ecological restoration areas based on landscape context. Restoration Ecology. 18: 143-. https://doi.org/10.1111/rec.12522.
  • Yang, Yun; Anderson, Martha C.; Gao, Feng; Hain, Christopher R.; Semmens, Kathryn A.; Kustas, William P.; Noormets, Asko; Wynne, Randolph H.; Thomas, Valerie A.; Sun, Ge 2017.Daily Landsat-scale evapotranspiration estimation over a forested landscape in North Carolina, USA, using multi-satellite data fusion. Hydrology and Earth System Sciences. 21(2): 1017-1037. https://doi.org/10.5194/hess-21-1017-2017.
  • Yao, Yunjun; Liang, Shunlin; Li, Xianglan; Liu, Shaomin; Chen, Jiquan; Zhang, Xiaotong; Jia, Kun; Jiang, Bo; Xie, Xianhong; Munier, Simon; Liu, Meng; Yu, Jian; Lindroth, Anders; Varlagin, Andrej; Raschi, Antonio; Noormets, Asko; Pio, Casimiro; Wohlfahrt, Georg; Sun, Ge; Domec, Jean-Christophe; Montagnani, Leonardo; Lund, Magnus; Eddy, Moors; Blanken, Peter D.; Grunwald, Thomas; Wolf, Sebastian; Magliulo, Vincenzo 2016. Assessment and simulation of global terrestrial latent heat flux by synthesis of CMIP5 climate models and surface eddy covariance observations. Agricultural and Forest Meteorology, Vol. 223: 17 pages.: 151-167.
  • Zhang, Yulong; Song, Conghe; Band, Lawrence E.; Sun, Ge; Li, Junxiang 2017.Reanalysis of global terrestrial vegetation trends from MODIS products: Browning or greening?. Remote Sensing of Environment. 191: 145-155. https://doi.org/10.1016/j.rse.2016.12.018.
  • Zhou, Decheng; Li, Dan; Sun, Ge; Zhang, Liangxia; Liu, Yongqiang; Hao, Lu 2016. Contrasting effects of urbanization and agriculture on surface temperature in eastern China. Journal of Geophysical Research: Atmospheres, Vol. 121(16): 10 pages.: 9597-9606.


Progress 10/01/14 to 09/30/15

Outputs
OUTPUTS: Eastern Forest Environmental Threat Assessment Center researchers and partners contributed significantly to forest health monitoring research at national and international scales: 1. Assessed risk of extinction and predicted the location and quality of habitat for forest tree species under different climate scenarios for the Forecasts of Climate-Associated Shifts in Tree Species (ForeCASTS) project. 2. Led Project CAPTURE (Conservation Assessment and Prioritization of Forest Trees Under Risk of Extirpation) to determine which forest tree species to target for monitoring, management, and conservation. 3. Used measurements of evolutionary diversity on forest inventory plots across the United States to examine how biodiversity influences the ecological functions of forests. 4. Assessed genetic variation and evolutionary history across the ranges of three at-risk species, ponderosa pine, eastern hemlock, and Carolina hemlock. 5. Analyzed data from a variety of sources to produce annual national reports that provide an overview of forest health at regional to national reporting scales. 6. Assessed pathways for human-assisted spread of forest pest species, including merchandise imports and firewood transport, to anticipate where and how often invasive alien forest insects are likely to be established in the United States and Canada. 7. Furthered techniques to account for uncertainty in the inputs and underlying assumptions of risk maps as well as the analytical models used to create them. 8. Expanded the web-based ForWarn forest monitoring and assessment tool, characterized the start of seasonal greening across forests and grasslands, agricultural lands, and urban areas, and developed retrospective map products providing views of disturbances prior to ForWarn⿿s release. 9. Developed a protocol for using recent satellite imagery and land cover maps to update information about fragmentation and loss of interior area of U.S. forests between 2001 and 2011 and updated summaries of forest areas that qualify as protected land under International Union for Conservation of Nature criteria for the 2015 update of the 2010 Forest Service Resources Planning Act Assessment. 10. Partnered with the Appalachian Landscape Conservation Cooperative (LCC) to take inventory of ecosystem services in the Appalachian mountain region, assess vulnerabilities to environmental stressors, synthesize existing knowledge, and deliver online resources. 11. Devised a new method to identify and map global fire regimes from wildfires and human-caused fires (including prescribed fires, agricultural fires, and land-clearing fires) on all land cover types. 12. Developed a new way to use LiDAR remote sensing data to group together all forests with similar vertical aboveground structural profiles and map forest structures at the landscape scale. 13. Began developing a method from information theory⿿a mathematical process for quantifying information⿿to leverage satellite-based monitoring of forests and grassland ecosystems in order to follow large-scale phenological changes in plant activity (seasonal cycles of vegetation development). PARTICIPANTS: 1. EFETAC cooperating researcher Kevin Potter (North Carolina State University ⿿ NCSU), EFETAC research ecologist William Hargrove, EFETAC research ecologist Frank Koch, and partners from USDA Forest Service Forest Health Monitoring Program 2. EFETAC cooperating researcher Kevin Potter (NCSU) and partners from NCSU; USDA Forest Service Southern and Pacific Northwest Pacific Southwest, Northern, Rocky Mountain, Southwestern, Intermountain, Eastern and Alaska Regions; Forest Health Monitoring Program; Forest Health Protection; Pacific Northwest Research Station; Pacific Southwest Research Station; Northern Research Station; Rocky Mountain Research Station 3. EFETAC cooperating researcher Kevin Potter (NCSU) and partners from NCSU, the USDA Forest Service Northern Research Station and Forest Health Monitoring Program 4. EFETAC cooperating researcher Kevin Potter (NCSU) and partners from NCSU; Forest Service Forest Health Protection, National Forest System, and Southern Research Station (Southern Institute of Forest Genetics); North Carolina State University; and Bureau of Land Management 5. EFETAC research ecologist Kurt Riitters and partners from NCSU and Forest Service Forest Health Monitoring Program and Forest Inventory and Analysis 6. EFETAC research ecologist Frank Koch and partners from the Canadian Forest Service, USDA Animal and Plant Health Inspection Service, and Michigan State University 7. EFETAC research ecologist Frank Koch and partners from the Canadian Forest Service, Canadian Food Inspection Agency, and the University of New Hampshire 8. EFETAC research ecologists William Hargrove and Steve Norman and biological scientist William Christie and partners from the Western Wildland Threat Assessment Center, Forest Health Monitoring Program, NASA Stennis Space Center, Oak Ridge National Laboratory, USGS, and University of North Carolina Asheville⿿s National Environmental Modeling and Analysis Center 9. EFETAC research ecologist Kurt Riitters and partners from Forest Service Quantitative Sciences and Forest Inventory and Analysis, and the Environmental Protection Agency 10. EFETAC director Danny C. Lee and ecologist Lars Pomara and partners from Appalachian Landscape Conservation Cooperative, and the University of North Carolina Asheville⿿s National Environmental Modeling and Analysis Center 11. EFETAC research ecologists William Hargrove and Steve Norman and partners from Oak Ridge National Laboratory 12. EFETAC research ecologists William Hargrove and Steve Norman and partners from U.S. Fish and Wildlife Service and Oak Ridge National Laboratory 13. EFETAC director Danny C. Lee, ecologist (ORISE fellow) Bjorn-Gustaf Brooks, research ecologist William Hargrove, biological scientist William Christie, and partners from Oak Ridge National Laboratory and NASA Stennis Space Center TARGET AUDIENCES: Researchers, natural resource managers, planners, policy makers, researchers, landowners, general public PROJECT MODIFICATIONS: N/A

Impacts
1. Natural resource managers, land use planners, and conservation organizations can better determine which forest tree species and populations may be most vulnerable to climate change and are able to target species for monitoring, conservation, and management activities. 2. Managers have a useful and flexible tool for planning conservation efforts, evaluating species⿿ genetic resources and detecting species vulnerabilities, while allowing for the effective use of limited resources. 3. New indicators of forest biodiversity change allow for the robust and rapid monitoring of climate change effects on biodiversity and ecological goods and services across broad regions. 4. Resource managers understand genetic diversity across the range of vulnerable tree species and can target gene conservation and management activities in the face of exotic pest infestation, climate change, and land use change pressures. 5. Annual synthesis reports provide an overview of forest health based on criteria and indicators of sustainable forestry and serve as a useful guide to forest health issues and trends that may require further monitoring and research. 6. Pest risk modelers can build better integrated risk models, and regulatory decision makers can use this information to determine where their resources may be used efficiently with regard to border control efforts, post-border surveillance, and rapid-response measures. 7. Risk maps for decision support are improved and show decision makers which locations face the greatest risk of invasion by a pest, allowing prioritization of scarce resources for monitoring and management. 8. Forest and natural resource managers can rapidly detect, identify, and respond to unexpected changes in the nation⿿s forests. 9. Congressional staffers and federal and non-federal agencies and organizations can access useful information about forest fragmentation trends that could be early warning indicators of changes in wildlife habitat and water quality. 10. New online tools help managers and the public understand ecosystem service sustainability. This research also provides a foundation for new ecosystem service assessments, and ongoing research will identify vulnerabilities and resiliencies associated with key drivers of landscape change across the Appalachian LCC. 11. A synoptic perspective of the complex patterns of fire characteristics across the entire planet allows users to recognize and compare diverse types of global fire regimes, increases understanding of fire as an ecological and social process, and informs management strategies. 12. New maps provide a straightforward way for forest and wildlife managers to utilize LiDAR results to understand forest aboveground structure, which is an important habitat characteristic for many species of animals and plants. 13. Drawing connections between the information theory metrics of an ecosystem where disturbance is currently underway and a similar ecosystem that has already recovered from disturbance presents a new way for land managers to gauge the likelihood of certain outcomes following disturbance events.

Publications

  • Ambrose MJ. 2015. Tree Mortality. Chapter 5 in: Potter KM and Conkling BL (eds) 2015. The Forest Health Monitoring: National Status, Trends, and Analysis, 2013. GTR-SRS-207. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 199 p.
  • Ambrose, MA. 2015. Tree mortality. Chapter 5 in K.M. Potter and B.L. Conkling, eds., Forest Health Monitoring: National Status, Trends and Analysis, 2014. General Technical Report SRS-209. Asheville, North Carolina: U.S. Department of Agriculture, Forest Service, Southern Research Station. pp. 73-84.
  • Ambrose, MJ. 2014. Tree mortality. Chapter 5 in: Potter and Conkling (eds), Forest health monitoring: national status, trends, and analysis, 2012. Gen. Tech. Rep. SRS-198. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 192 p.
  • Koch FH, Smith WD, Coulston JW. 2015. Drought Patterns in the Conterminous United States, 2012. Chapter 4 in: Potter KM and Conkling BL (eds) 2015. The Forest Health Monitoring: National Status, Trends, and Analysis, 2013. GTR-SRS-207. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 199 p.
  • Koch, FH and Coulston JW. 2015. 1-year (2013), 3-year (2011-13), and 5-year (2009-13) drought maps for the conterminous United States. Chapter 4 in K.M. Potter and B.L. Conkling, eds., Forest Health Monitoring: National Status, Trends and Analysis, 2014. General Technical Report SRS-209. Asheville, North Carolina: U.S. Department of Agriculture, Forest Service, Southern Research Station. pp. 57-72.
  • Koch, FH, Smith WD, Coulston JW. 2014. Drought patterns in the conterminous united states and hawaii. Chapter 4 in: Potter and Conkling (eds), Forest health monitoring: national status, trends, and analysis, 2012. Gen. Tech. Rep. SRS-198. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 192 p.
  • Koch, Frank H; Yemshanov, Denys 2015. Identifying and assessing critical uncertainty thresholds in a forest pest risk model. In:Venette, RC (ed.) Pest Risk Modelling and Mapping for Invasive Alien Species. CABI, Wallingford, UK, 189-205. 17 p.
  • Potter KM. 2015. Introduction. Chapter 1 in: Potter KM and Conkling BL (eds) 2015. The Forest Health Monitoring: National Status, Trends, and Analysis, 2013. GTR-SRS-207. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 199 p. (informally reviewed)
  • Potter KM. 2015. Large-Scale Patterns of Forest Fire Occurrence in the Conterminous United States and Alaska, 2012. Chapter 3 in: Potter KM and Conkling BL (eds) 2015. The Forest Health Monitoring: National Status, Trends, and Analysis, 2013. GTR-SRS-207. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 199 p.
  • Potter, K.M. 2015. Introduction. Chapter 1 in K.M. Potter and B.L. Conkling, eds., Forest Health Monitoring: National Status, Trends and Analysis, 2014. General Technical Report SRS-209. Asheville, North Carolina: U.S. Department of Agriculture, Forest Service, Southern Research Station. pp. 5-16.
  • Potter, K.M. 2015. Large-scale patterns of forest fire occurrence in the conterminous United States and Alaska, 2013. Chapter 3 in K.M. Potter and B.L. Conkling, eds., Forest Health Monitoring: National Status, Trends and Analysis, 2014. General Technical Report SRS-209. Asheville, North Carolina: U.S. Department of Agriculture, Forest Service, Southern Research Station. pp. 39-55.
  • Potter, KM. 2014. Introduction. Chapter 1 in: Potter and Conkling (eds), Forest Health Monitoring: National Status, Trends, and Analysis, 2012. Gen. Tech. Rep. SRS-198. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 192 p.
  • Potter, Kevin M.; Hipkins, Valerie D.; Mahalovich, Mary F.; Means, Robert E. 2015. Nuclear genetic variation across the range of ponderosa pine (Pinus ponderosa): Phylogeographic, taxonomic and conservation implications. Tree Genetics & Genomes (2015) 11:38. 23 p.
  • Riitters, Kurt; Wickham, James; Costanza, Jennifer K.; Vogt, Peter 2015. A global evaluation of forest interior area dynamics using tree cover data from 2000 to 2012. Landscape Ecology. 12 p. 10.1007/s10980-015-0270-9
  • Yemshanov, D.; Koch, F.H.; Ducey, M.J.; Haack, R.A. 2015. Towards reliable mapping of biosecurity risk: incorporating uncertainty and decision-makers⿿ risk aversion. Wallingford, UK: Biosecurity Surveillance Quantitative Approaches CABI Publishing. 12:217-237 pp.
  • Yemshanov, Denys; Koch, Frank H; Ducey, Mark 2015. Making Invasion models useful for decision makers; incorporating uncertainty, knowledge gaps, and decision-making preferences. In Venette, RC (ed.); Pest Risk Modelling and Mapping for Invasive Alien Species. CABI, Wallingford, UK. 14: 206-222. 17 p.
  • Yemshanov, Denys; Koch, Frank; Riitters, Kurt H.; McConkey, Brian; Huffmand, Ted; Smithe,Stephen 2015. Assessing land clearing potential in the Canadian agriculture⿿forestry interface with a multi-attribute frontier approach. Ecological Indicators 54 (2015) 71⿿81, Elsevier Ltd. 11 p.


Progress 10/01/13 to 09/30/14

Outputs
OUTPUTS: Eastern Forest Environmental Threat Assessment Center researchers and partners contributed significantly to forest health monitoring research at national and international scales: 1.Assessed risk of extinction and predicted the location and quality of habitat for forest tree species under different climate scenarios for a project known as Forecasts of Climate-Associated Shifts in Tree Species (ForeCASTS). Researchers developed maps of future suitable habitat for 335 North American tree species, indicating where these species could be expected to survive and thrive. 2.Led the three-year Project CAPTURE (Conservation Assessment and Prioritization of Forest Trees Under Risk of Extirpation) to determine which forest tree species to target for monitoring, management, and conservation. These activities will be critical for the Forest Service and other federal and state agencies as they work to maintain the adaptive genetic potential of forest tree species at risk of genetic variation from climate change and other threats. 3.Used measurements of evolutionary diversity on forest inventory plots across the United States to examine how biodiversity influences the ecological functions of forests. Published results quantified the relationship between tree biodiversity and biomass on forest plots across the United States. 4.Assessed genetic variation and evolutionary history across the ranges of ponderosa pine and eastern hemlock. Published results characterize genetic diversity, structure, conservation, and seed transfer strategies to support management decisions. 5.Produced annual national reports describing the health of the nation⿿s forests to provide forest managers, scientists, and decision makers with current and relevant information about issues impacting forest resources. 6.Contributed innovative research to the field of forest pest risk assessment by focusing on pathways for human-assisted spread of forest pest species, including merchandise imports and firewood transport. The analysis anticipates where and how often invasive alien forest insects are likely to be established in the United States and Canada. 7.Furthered innovative research to forest pest risk assessment by developing new techniques to account for uncertainty in the inputs and underlying assumptions of risk maps. Key advances include a methodology that allows analysts to account for these uncertainties from the perspective of a ⿿risk-averse⿝ decision maker who prefers to take management action in cases where the risk of invasion is more certainly known. 8.Expanded ForWarn, the Center⿿s forest disturbance and monitoring web-based tool, with new map products that improve ForWarn's ability to detect potential forest disturbances in spite of normal year-to-year climatic variations and to recognize disturbances more rapidly in forest areas where cloud cover is not obscuring satellite views. ForWarn products are also now available on mobile devices, including smart phones and tablet computers. 9.Contributed to the 2015 Update of the 2010 Forest Service Resources Planning Act Assessment, the 2015 Forest Service National Report on Sustainable Forests, and the Environmental Protection Agency 2015 Report on the Environment by using more recent satellite imagery and land cover maps along with Forest Inventory and Analysis field plot data to update fragmentation and loss of interior area of US forests. 10.Collaborated with the University of North Carolina Asheville⿿s National Environmental Modeling and Analysis Center to develop advanced tools and technologies that support integrated threat assessment,; advanced the application of the Comparative Risk Assessment Framework and Tools (CRAFT) to support development of the National Cohesive Wildland Fire Management Strategy; and improved PARTICIPANTS: 1.EFETAC cooperating researcher Kevin Potter (North Carolina State University ⿿ NCSU), EFETAC research ecologist William Hargrove, EFETAC research ecologist Frank Koch, and partners from USDA Forest Service Forest Health Monitoring Program. 2.EFETAC cooperating researcher Kevin Potter (NCSU) and partners from NCSU; USDA Forest Service Southern and Pacific Northwest Pacific Southwest, Northern, Rocky Mountain, Southwestern, Intermountain, Eastern and Alaska Regions; Forest Health Monitoring Program; Forest Health Protection; Pacific Northwest Research Station; Pacific Southwest Research Station; Northern Research Station; Rocky Mountain Research Station 3.EFETAC cooperating researcher Kevin Potter (NCSU) and partners from NCSU, the USDA Forest Service Northern Research Station and Forest Health Monitoring Program. 4.EFETAC cooperating researcher Kevin Potter (NCSU) and partners from NCSU, the USDA Forest Service Forest Health Protection; National Forest System; Southern Research Station (Southern Institute of Forest Genetics); North Carolina State University; Bureau of Land Management 5.EFETAC research ecologist Kurt Riitters and partners from NCSU and USDA Forest Service Forest Health Monitoring Program and Forest Inventory and Analysis 6.EFETAC research ecologist Frank Koch and partners from the Canadian Forest Service, USDA Animal and Plant Health Inspection Service, and Michigan State University. 7.EFETAC research ecologist Frank Koch and partners from the Canadian Forest Service, Canadian Food Inspection Agency, and the University of New Hampshire.8.EFETAC research ecologists William Hargrove and Steve Norman in partnership with researchers from the Western Wildland Threat Assessment Center, Forest Health Monitoring Program, NASA Stennis Space Center, Oak Ridge National Laboratory, USGS, and University of North Carolina Asheville⿿s National Environmental Modeling and Analysis Center9.EFETAC research ecologist Kurt Riitters, Forest Service Quantitative Sciences and Forest Inventory and Analysis, and the Environmental Protection Agency10.EFETAC director Danny C. Lee, research ecologists William Hargrove and Steve Norman, the University of North Carolina Asheville's National Environmental Modeling and Analysis Center TARGET AUDIENCES: Researchers, natural resource managers, planners, policy makers, researchers, landowners, general public

Impacts
1.Natural resource managers, land use planners, and conservation organizations can better determine which forest tree species and populations may be most vulnerable to climate change and are able to target species for monitoring, conservation, and management activities. 2.Managers have a useful and flexible tool for planning conservation efforts, evaluating species' genetic resources and detecting species vulnerabilities, while allowing for the effective use of limited resources. 3.New indicators of forest biodiversity change allow for the robust and rapid monitoring of climate change effects on biodiversity and ecological goods and services across broad regions. 4.Resource managers understand genetic diversity across the range of vulnerable tree species and can target gene conservation and management activities in the face of exotic pest infestation, climate change, and land use change pressures. 5.Annual reports synthesize data from a variety of sources to provide an overview of forest health based on criteria and indicators of sustainable forestry and serve as a useful guide to forest health issues and trends that may require further monitoring and research. 6.Pest risk modelers can build better integrated risk models, and regulatory decision makers can use this information to determine where their resources may be used efficiently with regard to border control efforts, post-border surveillance, and rapid-response measures. 7.Risk maps for decision support are improved and show decision makers which locations in their regions of concern face the greatest risk of invasion by a pest, allowing prioritization of scarce resources for monitoring and management. 8.Forest and natural resource managers can rapidly detect, identify, and respond to unexpected changes in the nation's forests. 9.Trends in forest fragmentation are early warning indicators of changes in wildlife habitat and water quality. The assessments are useful references for congressional staffers and federal and non-federal agencies and organizations interested in forest trends. 10.Diverse audiences can understand and use products and tools developed by the Eastern Threat Center.

Publications

  • Potter, Kevin M. 2013. Large-Scale Patterns of Forest Fire Occurrence in the Conterminous United States and Alaska, 2010. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2013. Forest health monitoring: national status, trends, and analysis 2011. Gen. Tech. Rep. SRS-GTR-185. Asheville, NC: USDA- Forest Service, Southern Research Station. 29-40.
  • Potter, Kevin M.; Conkling, Barbara L., eds. 2013. Forest health monitoring: national status, trends, and analysis 2011. Gen. Tech. Rep. SRS-GTR-185. Asheville, NC: USDA-Forest Service, Southern Research Station. 149 p.
  • Potter, Kevin M.; Paschke, Jeanine L. 2013. Large-scale patterns of insect and disease activity in the conterminous United States and Alaska from the National Insect and Disease Detection Survey Database, 2010. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2013. Forest health monitoring: national status, trends, and analysis 2011. Gen. Tech. Rep. SRS-GTR-185. Asheville, NC: USDA- Forest Service, Southern Research Station. 15-28.
  • Potter, Kevin M.; Woodall, Christopher W. 2014. Does biodiversity make a difference? Relationships between species richness, evolutionary diversity, and aboveground live tree biomass across U.S. forests. Forest Ecology and Management. 321: 117-129.
  • Riitters, Kurt H.; Coulston, John W. 2013. Fragmentation of eastern United States forest types. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2013. Forest health monitoring: national status, trends, and analysis 2011. Gen. Tech. Rep. SRS-GTR-185. Asheville, NC: USDA-Forest Service, Southern Research Station. 71-77.
  • Riitters, Kurt; Potter, Kevin; Tkacz, Borys 2013. Forest health monitoring in the United States: focus on national reports. In: Proceedings of International Symposium on Forest Health. Seoul, Korea: Korea Forest Research Institute. 12-27.
  • Yemshanov, Denys; Koch, Frank H.; Lu, Bo; Lyons, D. Barry; Prestemon, Jeffrey P.; Scarr, Taylor; Koehler, Klaus 2014. There is no silver bullet: the value of diversification in planning invasive species surveillance. Ecological Economics 104:61-72.
  • Zurlini, Giovanni; Jones, Kenneth Bruce; Riitters, Kurt Hans; Li, Bai-Lian; Petrosillo, Irene 2014. Early warning signals of regime shifts from cross-scale connectivity of land-cover patterns. Ecological Indicators 45:549-560.
  • Ambrose, Mark J. 2013. Tree mortality. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2013. Forest health monitoring: national status, trends, and analysis 2011. Gen. Tech. Rep. SRS-GTR-185. Asheville, NC: USDA-Forest Service, Southern Research Station. 59-68.
  • Bigsby,Kevin M.; Ambrose, Mark J.; Tobin, Patrick C.; Sills, Erin O. 2014. The cost of gypsy moth sex in the city. Urban Forestry and Urban Greening 13(3):459-468.
  • Gavazzi, M.J.; McNulty, S.G. 2014. The influence of prescribed fire and burn interval on fuel loads in four North Carolina forest ecosystems. In: Wade, DD; Fox, RL, eds. Proceedings of the 4th Fire Behavior and Fuels Conference, 18-22 February 2013, Raleigh, NC. International Association of Wildland Fire: Missoula, MT. 26-48.
  • Koch, Frank H.; Smith, William D.; Coulston, John W. 2013. Recent drought conditions in the Conterminous United States. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2013. Forest health monitoring: national status, trends, and analysis 2011. Gen. Tech. Rep. SRS-GTR-185. Asheville, NC: USDA-Forest Service, Southern Research Station. 41-58.
  • Koch, Frank H.; Yemshanov, Denys; Haack, Robert A.; Magarey, Roger D. 2014. Using a network model to assess risk of forest pest spread via recreational travel. PLoS ONE 9(7): e102105. DOI:10.1371/journal.pone.0102105.
  • Potter, Kevin M. 2013. Introduction. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2013. Forest health monitoring: national status, trends, and analysis 2011. Gen. Tech. Rep. SRS-GTR-185. Asheville, NC: USDA- Forest Service, Southern Research Station. 5-12.


Progress 10/01/12 to 09/30/13

Outputs
OUTPUTS: Eastern Forest Environmental Threat Assessment Center researchers and partners contributed significantly to forest health monitoring research at national and international scales: 1. Assessed risk of extinction and predicted the location and quality of habitat for forest tree species under different climate scenarios for a project known as Forecasts of Climate-Associated Shifts in Tree Species (ForeCASTS); published description of quantitative measurements of predicted climate change pressure on forest tree species; a new version will contain predicted future range maps for more than 325 tree species. 2. Began coordinating the three-year Project CAPTURE (Conservation Assessment and Prioritization of Forest Trees Under Risk of Extirpation) to determine which forest tree species to target for monitoring, management, and conservation. These activities will be critical for the Forest Service and other federal and state agencies as they work to maintain the adaptive genetic potential of forest tree species at risk of genetic variation from climate change and other threats. 3. Used measurements of evolutionary diversity on forest inventory plots across the United States to examine how biodiversity influences the ecological functions of forests; the evolutionary diversity measures account for the evolutionary relationships among species in a community based on their position on a phylogenetic ⿿tree of life," and should be good indicators of ecological services provided by forest communities; published results quantified the relationship between tree biodiversity and biomass on forest plots across the United States. 4. Assessed genetic variation and evolutionary history across the ranges of ponderosa pine, a species with isolated populations of special concern given their susceptibility to climate change, development, and bark beetles, and of eastern hemlock, a species being decimated by an exotic insect; published results characterize genetic diversity, structure, conservation, and seed transfer strategies. 5. Produced annual reports describing the health of the nation's forests. 6. Contributed innovative research to the field of forest pest risk assessment by focusing on pathways for human-assisted spread of forest pest species, including merchandise imports and firewood transport. 7. Furthered innovative research to forest pest risk assessment by developing new techniques to account for uncertainty in the inputs and underlying assumptions of risk maps as well as the analytical models used to create them. 8. Expanded ForWarn, the Center's forest disturbance and monitoring web-based tool. ForWarn now captures recent disturbances almost immediately after they occur while detecting slow-acting change in vegetation greenness. A highlights document was published, covering detected disturbances since 2010. 9. Contributed to the Forest Service Resources Planning Act Assessment by assessing the fragmentation and landscape context of US forest, grass, and shrub lands. 10. Collaborated with the University of North Carolina Asheville⿿s National Environmental Modeling and Analysis Center to develop advanced tools and technologies that support integrated threat assessment, including ForWarn. PARTICIPANTS: 1. EFETAC cooperating researcher Kevin Potter (North Carolina State University - NCSU), EFETAC research ecologist Bill Hargrove, EFETAC research ecologist Frank Koch, and partners from USDA Forest Service Forest Health Monitoring Program 2. EFETAC cooperating researcher Kevin Potter (NCSU) and partners from USDA Forest Service Forest Health Protection, the USDA Forest Service National Forest System, USDA Forest Service Research, and the USDA Forest Service Forest Health Monitoring Program 3. EFETAC cooperating researcher Kevin Potter (NCSU) and partners from the USDA Forest Service Northern Research Station and Forest Health Monitoring Program 4. EFETAC cooperating researcher Kevin Potter (NCSU) and partners from the USDA Forest Service National Genetics Laboratory (Washington Office), USDA Forest Service National Forest System, USDI Bureau of Land Management, USDA Forest Service Forest Health Protection, and NCSU 5. EFETAC research ecologist Kurt Riitters and partners from NCSU and USDA Forest Service Forest Health Monitoring Program 6. EFETAC research ecologist Frank Koch, EFETAC researcher Bill Smith, and partners from the Canadian Forest Service, USDA Animal and Plant Health Inspection Service, and Michigan State University 7. EFETAC research ecologist Frank Koch and partners from the Canadian Forest Service, Canadian Food Inspection Agency, and the University of New Hampshire. 8. EFETAC research ecologist Bill Hargrove in partnership with researchers from the Western Wildland Threat Assessment Center, Forest Health Monitoring Program, NASA Stennis Space Center, Oak Ridge National Laboratory, USGS, and University of North Carolina Asheville⿿s National Environmental Modeling and Analysis Center 9. EFETAC research ecologist Kurt Riitters, Forest Service Quantitative Sciences and Forest Inventory and Analysis 10. EFETAC director Danny C. Lee, research ecologist William Hargrove and the University of North Carolina Asheville⿿s National Environmental Modeling and Analysis Center TARGET AUDIENCES: Researchers, natural resource managers, planners, policy makers, researchers, landowners, general public

Impacts
1. Natural resource managers, land use planners, and conservation organizations can better determine which forest tree species and populations may be most vulnerable to climate change and are able to target species for monitoring, conservation, and management activities. 2. Managers have a useful and flexible tool for planning conservation efforts, evaluating species⿿ genetic resources and detecting species vulnerabilities, while allowing for the effective use of limited resources. 3. New indicators of forest biodiversity change allow for the robust and rapid monitoring of climate change effects on biodiversity and ecological goods and services across broad regions. 4. Resource managers understand genetic diversity across the range of vulnerable tree species and can target gene conservation and management activities in the face of exotic pest infestation, climate change, and land use change pressures. 5. Annual reports synthesize data from a variety of sources to provide an overview of forest health based on criteria and indicators of sustainable forestry and serve as a useful guide to forest health issues and trends that may require further monitoring and research. 6. Pest risk modelers can build better integrated risk models, and regulatory decision makers can use this information to determine where their resources may be used efficiently with regard to border control efforts, post-border surveillance, and rapid-response measures. 7. Key advances include a methodology that allows analysts to account for these uncertainties from the perspective of a ⿿risk-averse⿝ decision maker who prefers to take management action in cases where the risk of invasion is more certainly known. 8. Forest and natural resource managers can rapidly detect, identify, and respond to unexpected changes in the nation's forests. 9. The assessment is a useful reference for congressional staffers and federal and non-federal agencies and organizations interested in forest trends. 10. Diverse audiences can understand and use products and tools developed by the Eastern Threat Center.

Publications

  • Wickham, James D.; Wade, Timothy G.; Riitters, Kurt H. 2013. Empirical analysis of the influence of forest extent on annual and seasonal surface temperatures for the Continental United States. Global Ecology and Biogeography 22:620⿿629.
  • Ambrose, M.J. 2012. How urban forest tree species composition compares with that of the natural forest. In: 97th Annual Meeting of the Ecological Society of America, Portland, Oregon, August 5-10, 2012.
  • Ambrose, Mark J. 2013. Tree mortality. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2013. Forest Health Monitoring: national status, trends, and analysis 2010. Gen. Tech. Rep. SRS-GTR-176. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 41-50.
  • Ambrose, Mark J. 2012. Tree Mortality. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2012. Forest health monitoring: 2009 national technical report. Gen. Tech. Rep. SRS-167. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 95-107.
  • Conkling, B.L.; Ambrose, M.J. 2012. Forest Health Monitoring. In: Society of American Foresters 2012 National Convention, Spokane, Washington, October 24-28, 2012.
  • Devine, W.; Aubry, C.; Miller, J.; Potter, K.; Bower, A. 2012. Climate change and forest trees in the Pacific Northwest: guide to vulnerability assessment methodology. Olympia, WA: U.S. Department of Agriculture, Forest Service, Pacific Northwest Region. 49 p.
  • Jones, William E.; Smith, William D.; Twardus, Daniel B. 2012. Tracking population loss in Cornus florida since discovery of Discula destructiva, causal agent of dogwood anthracnose, in eastern North America. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2012. Forest health monitoring: 2009 national technical report. Gen. Tech. Rep. SRS-167. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 191-197.
  • Koch, F.H.; Ambrose, M.J.; Yemshanov, D.; Wiseman, P.E. 2013. Estimating urban distributions of key host trees for invasive forest pests. In: 24th USDA Invasive Species Forum, Loews Annapolis Hotel, Annapolis, MD, Jan 8-11, 2013.
  • Koch, Frank H.; Smith, William D. 2012. A revised sudden oak death risk map to facilitate national surveys. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2012. Forest health monitoring: 2009 national technical report. Gen. Tech. Rep. SRS-167. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 109-136.
  • Koch, Frank H.; Smith, William D.; Coulston, John W. 2013. An improved method for standardized mapping of drought conditions. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2013. Forest Health Monitoring: national status, trends, and analysis 2010. Gen. Tech. Rep. SRS-GTR-176. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 67-83.
  • Koch, Frank H.; Yemshanov, Denys; Haack, Robert A. 2013. Representing uncertainty in a spatial invasion model that incorporates human-mediated dispersal. NeoBiota 18:173⿿191.
  • Kriticos, Darren J.; Venette, Robert C.; Baker, Richard H.A.; Brunel, Sarah; Koch, Frank H.; Rafoss, Trond; van der Werf, Wopke; Worner, Susan P. 2013. Invasive alien species in the food chain: Advancing risk assessment models to address climate change, economics and uncertainty. NeoBiota 18:1⿿7.
  • McKelvey, Steven C.; Smith, William D.; Koch, Frank 2012. Probabilistic commodity-flow-based focusing of monitoring activities to facilitate early detection of Phytophthora ramorum outbreaks. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2012. Forest health monitoring: 2009 national technical report. Gen. Tech. Rep. SRS-167. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 225-231.
  • Mills, Richard Tran; Kumar, Jitendra; Hoffman, Forrest M.; Hargrove, William W.; Spruce, Joseph P.; Norman, Steven P. 2013. Identification and visualization of dominant patterns and anomalies in remotely sensed vegetation phenology using a parallel tool for principal components analysis. Procedia Computer Science 18:2396⿿2405.
  • Koch, Frank H.; Coulston, John W.; Smith, William D. 2012. Mapping drought conditions using multi-year windows. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2012. Forest health monitoring: 2009 national technical report. Gen. Tech. Rep. SRS-167. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 163-179.
  • Norman, Steven P.; Hargrove, William W.; Spruce, Joseph P.; Christie, William M.; Schroeder, Sean W. 2013. Highlights of satellite-based forest change recognition and tracking using the ForWarn System. Gen. Tech. Rep. SRS-GTR-180. Asheville, NC: USDA-Forest Service, Southern Research Station. 30 p.
  • Potter, K.M.; Woodall, C.W. 2012. Incorporating evolutionary relationships into regional assessments of forest biodiversity across forest inventory and analysis plots. In: Morin, R.S.; Liknes, G.C., eds. Moving from status to trends: forest inventory and analysis symposium 2012. Gen Tech. Rep. GTR-NRS-P-105. Newtown Square, PA: U.S. Department of Agriculture Forest Service, Northern Research Station. p.157.
  • Potter, Kevin M. 2013. Introduction. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2013. Forest Health Monitoring: national status, trends, and analysis 2010. Gen. Tech. Rep. SRS-GTR-176. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 5-12.
  • Potter, Kevin M. 2013. Large-scale patterns of forest fire occurrence in the conterminous United States and Alaska, 2009. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2013. Forest Health Monitoring: national status, trends, and analysis 2010. Gen. Tech. Rep. SRS-GTR-176. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 31-39.
  • Potter, Kevin M. 2013. Large-scale patterns of insect and disease activity in the conterminous United States and Alaska from the national insect and disease detection survey, 2009. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2013. Forest Health Monitoring: national status, trends, and analysis 2010. Gen. Tech. Rep. SRS-GTR-176. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 15-29.
  • Potter, Kevin M. 2012. Introduction. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2012. Forest health monitoring: 2009 national technical report. Gen. Tech. Rep. SRS-167. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 9-18.
  • Potter, Kevin M. 2012. Large-scale patterns of forest fire occurrence in the Conterminous United States and Alaska, 2001-08. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2012. Forest health monitoring: 2009 national technical report. Gen. Tech. Rep. SRS-167. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 151-162.
  • Potter, Kevin M. 2012. Large-scale patterns of insect and disease activity in the Conterminous United States and Alaska from the National Insect and Disease Detection Survey Database, 2007 and 2008. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2012. Forest health monitoring: 2009 national technical report. Gen. Tech. Rep. SRS-167. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 63-78.
  • Potter, Kevin M.; Conkling, Barbara L., eds. 2013. Forest Health Monitoring: national status, trends, and analysis 2010. Gen. Tech. Rep. SRS-GTR-176. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 164 p.
  • Potter, Kevin M.; Crane, Barbara S. 2012. Silviculture and the assessment of climate change genetic risk for southern Appalachian forest tree species. In: Butnor, John R., ed. 2012. Proceedings of the 16th biennial southern silvicultural research conference. e-Gen. Tech. Rep. SRS-156. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 257-258.
  • Potter, Kevin M.; Hargrove, William W. 2012. Determining suitable locations for seed transfer under climate change: a global quantitative method. New Forests 43:581⿿599.
  • Potter, Kevin M.; Hipkins, Valerie D.; Mahalovich, Mary F.; Means, Robert E. 2013. Mitochondrial DNA haplotype distribution patterns in Pinus ponderosa (pinaceae): range-wide evolutionary history and implications for conservation. American Journal of Botany 100(8):1562⿿1579.
  • Potter, Kevin M.; Smith, William D. 2012. Large-Scale Assessment of Invasiveness and Potential for Ecological Impact by Nonnative Tree Species. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2012. Forest health monitoring: 2009 national technical report. Gen. Tech. Rep. SRS-167. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 79-94.
  • Prestemon, Jeffery P.; Abt, Karen L.; Potter, Kevin M.; Koch, Frank H. 2013. An economic assessment of mountain pine beetle timber salvage in the west. Western Journal of Applied Forestry 28(4):143-153.
  • Randolph, KaDonna; Bechtold, William A.; Morin, Randall S.; Zarnoch, Stanley J. 2012. Evaluating elevated levels of crown dieback among northern white-cedar (Thuja occidentalis L.) trees in Maine and Michigan: a summary of evaluation monitoring. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2012. Forest health monitoring: 2009 national technical report. Gen. Tech. Rep. SRS-167. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 219-223.
  • Riitters, Kurt H. 2012. Landscape pattern and context of forest and grassland in Alaska, Hawaii, and Puerto Rico. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2012. Forest health monitoring: 2009 national technical report. Gen. Tech. Rep. SRS-167. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 19-35.
  • Potter, Kevin M.; Conkling, Barbara L., eds. 2012. Forest health monitoring: 2009 national technical report. Gen. Tech. Rep. SRS-167. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 252 p.
  • Riitters, Kurt H. 2013. Fragmentation of forest, grassland, and shrubland. In: Potter, Kevin M.; Conkling, Barbara L., eds. 2013. Forest Health Monitoring: national status, trends, and analysis 2010. Gen. Tech. Rep. SRS-GTR-176. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 53-65.
  • Riitters, Kurt H.; Wickham, James D. 2012. Decline of forest interior conditions in the conterminous United States. Scientific Reports 2(653):1-4. DOI: 10.1038/srep00653
  • Yemshanov, Denys; Koch, Frank H.; Ben-Haim, Yakov; Downing, Marla; Sapio, Frank; Siltanen, Marty 2013. A new multicriteria risk mapping approach based on a multiattribute frontier concept. Risk Analysis 33(9):1694-1709.
  • Yemshanov, Denys; Koch, Frank H.; Ducey, Mark J.; Haack, Robert A.; Siltanen, Marty; Wilson, Kirsty 2013. Quantifying uncertainty in pest risk maps and assessments: adopting a risk-averse decision maker⿿s perspective. NeoBiota 18:193⿿218.
  • Yemshanov, Denys; Koch, Frank H.; Ducey, Mark J.; Siltanen, Marty; Wilson, Kirsty; Koehler, Klaus 2013. Exploring critical uncertainties in pathway assessments of human-assisted introductions of alien forest species in Canada. Journal of Environmental Management 129:173-182.
  • Yemshanov, Denys; Koch, Frank H.; Ducey, Mark; Koehler, Klaus 2013. Mapping ecological risks with a portfolio-based technique: incorporating uncertainty and decision-making preferences. Diversity and Distributions 19:567⿿579.
  • Zurlini, Giovanni; Petrosillo, Irene; Jones, Kenneth Bruce; Li, Bai-Lian; Riitters, Kurt Hans; Medagli, Pietro; Marchiori, Silvano; Zaccarelli, Nicola 2013. Towards the planning and design of disturbance patterns across scales to counter biological invasions. Journal of Environmental Management 128:192-203.


Progress 10/01/09 to 09/30/10

Outputs
OUTPUTS: Eastern Forest Environmental Threat Assessment Center researchers and partners contributed significantly to forest health monitoring research at national and international scales: 1. Used spatial models of future environment conditions to assess the risk of extinction and predict the location and quality of habitat for forest tree species under different climate scenarios. 2. Developed a framework, called the Forest Tree Genetic Risk Assessment System, to rank the predisposition of forest tree species to genetic degradation from climate change and other threats. 3. Developed a set of forest community diversity metrics, incorporating both evolutionary diversity change over time and tree age class, as regional indicators of potential biodiversity impacts associated with climate change. 4. Using microsatellite molecular markers, assessed the genetic variation across the range of eastern hemlock (Tsuga canadensis), a species being decimated by an exotic insect. 5. Produced annual reports describing the health of the nation's forests. 6. Completed the Mid-Atlantic Integrated Assessment highlighting the status and changes in forests across areas such as history, land use change, population growth and urbanization, and carbon sequestration. 7. Developed methods and implemented data collection to assess the relationships between yellow birch and acidic deposition in the Southern Appalachian mountains. 8. Developed methods to establish a north-south transect of ridge ecotone plots along the Appalachian Trail (AT) to identify early impacts of climate change on eastern forests. 9. Applied Monte Carlo sensitivity analysis techniques to a spatial model of forest pest invasion risk in order to characterize and evaluate the effects of added uncertainty on key model parameters. 10. Applied info-gap analysis, a non-probabilistic approach for making decisions under severe uncertainty, to determine which of a set of detection survey networks developed from pest risk maps were most robust to severe uncertainties regarding the pest of interest. 11. Applied info-gap analysis to identify surveillance strategies, developed from a pest risk map, that offer the best trade-offs between robustness to uncertainty (in the form of timely, certain pest detections) and opportuneness (i.e., the ability to maximize knowledge gain about the pest via unanticipated detections). 12. Developed a set of research and methodological recommendations to improve the overall quality of pest risk mapping as a science. 13. Used historical trade and insect species occurrence data, combined with commodity flow information, to estimate the annual establishment rate of alien forest insect species for >3000 U.S. urban areas. 14. Contributed to a user's guide for the Forest Inventory and Analysis public database for the phase 3 indicators. 15. Assessed green infrastructure at national scale using hub/corridor model and landcover data. 16. Conducted a national assessment of the landscape context (natural, semi-natural, urban, agriculture) of all grassland and forest. 17. Produced a series of high resolution phenology (seasonal changes in vegetation) map products, derived from satellite imagery, for the conterminous United States to support regional scale risk assessments. PARTICIPANTS: 1. EFETAC cooperating researcher Kevin Potter (North Carolina State University - NCSU), EFETAC research ecologist Bill Hargrove, and EFETAC cooperating researcher Frank Koch (North Carolina State University - NCSU) 2. EFETAC cooperating researcher Kevin Potter (NCSU)and partners from the National Forest System in the South and in the Pacific Northwest 3. EFETAC cooperating researcher Kevin Potter (NCSU) and Northern Research Station research forester Christopher Woodall 4. EFETAC cooperating researcher Kevin Potter (NCSU) and cooperators in the Southern Research Station, Pacific Southwest Research Station, Forest Health Protection, and NCSU. 5. EFETAC research forester Kurt Riitters, retired research forester Bill Bechtold and partners from NCSU 6. EFETAC research ecologist Ken Stolte and partners from the Environmental Protection Agency, U.S. Forest Service, and other agencies. 7. EFETAC research ecologist Ken Stolte and partners from Forest Health Protection and Equinox Environmental, Inc. 8. EFETAC research ecologist Ken Stolte and partners from NASA, National Park Service, Appalachian Trail Conservancy, U.S. Geological Survey, University of Rhode Island, and others. 9. EFETAC cooperating researcher Frank Koch (NCSU), EFETAC researcher Bill Smith, and partners from the Canadian Forest Service (Denys Yemshanov and Dan McKenney). 10. EFETAC cooperating researcher Frank Koch (NCSU), EFETAC researcher Bill Smith, and partners from the Canadian Forest Service (Denys Yemshanov) and Technion University-Israel (Yakov Ben-Haim). 11. EFETAC cooperating researcher Frank Koch (NCSU), EFETAC researcher Bill Smith, and partners from the Canadian Forest Service (Denys Yemshanov) and Technion University-Israel (Yakov Ben-Haim). 12. EFETAC cooperating researcher Frank Koch (NCSU) and other members of the International Pest Risk Mapping and Modeling Group, including scientists from the Northern Research Station, USDA Animal and Plant Health Inspection Service, Commonwealth Scientific and Industrial Research Organisation - Australia, UK Food and Environment Research Agency, Lincoln University (NZ), and the Canadian Forest Service. 13. EFETAC cooperating researcher Frank Koch (NCSU), EFETAC researcher Bill Smith, and partners from the Canadian Forest Service (Denys Yemshanov), Michigan State University (Manuel Colunga), and the North Carolina State University Center for Integrated Pest Management (Roger Magarey). 14. EFETAC cooperating researcher Barbara Conkling (NCSU) and Forest Inventory and Analysis scientists from several other Research Stations, and scientists from two additional universities. 15. US Environmental Protection Agency researchers and EFETAC researcher Kurt Riitters. 16. EFETAC researcher Kurt Riitters and US Environmental Protection Agency researchers. 17. EFETAC ecologist William Hargrove and partners from USDA Forest Service Forest Inventory and Analysis and Forest Health Monitoring; International Cooperative Programme on Assessment and Monitoring of Air Pollution Effects on Forests; NASA Stennis Space Center; University of North Carolina Asheville's National Environmental Modeling and Analysis Center TARGET AUDIENCES: Researchers, natural resource managers, planners, policy makers, landowners, general public PROJECT MODIFICATIONS: As a result of staff reduction, (1) research related to the FHM crown indicator was eliminated (moved to the FIA program), (2) cooperation with Mexico and Oregon State University was suspended, (3) end-of-year reporting information was not available for ¼ FTE during FY10, and (3) the team leader for this problem area was changed.

Impacts
1. Scientists and policymakers can better determine which forest tree species and populations may be most vulnerable to a change in climate. 2. Managers have a useful and flexible tool for planning conservation efforts, evaluating species' genetic resources and detecting species vulnerabilities, while allowing for the effective use of limited resources. 3. Demographic indicators of evolutionary diversity can refine understanding of possible climate change impacts to forest communities across broad regions, particularly to the diversity of ecological goods and services provided by those communities. 4. An understanding of the genetic diversity across the range of eastern hemlock will help target gene conservation and management activities in the face of the exotic pest infestation and of projected climate change pressures. 5. The annual reports synthesize data from a variety of sources to provide an overview of forest health based on criteria and indicators of sustainable forestry. 6. The Mid-Atlantic assessment provides forest sector information to land managers and policy analysts in that region. 7. Methods and data will assess whether yellow birch species in the Southern Appalachians may be impacted by acidic deposition and therefore more susceptible to effects of climate change and serve as a regional bioindicator of climate change effects. 8. Development of a climate change-early warning system along the AT will inform land managers and owners of where climate change is threatening surrounding forests. 9. Specifically, researchers determined that model parameters related to dispersal were the most critically affected by uncertainty; more generally, risk modelers have a technique for evaluating parametric uncertainties in a high-resolution, stochastic model designed to yield a probabilistic estimate of risk integrated across all phases of invasion (i.e., introduction, spread, establishment, impact). 10. Decision makers who use pest risk maps to prioritize and plan their response activities have a method for choosing options that are the most robust to uncertainty, and thus provide the best chance for success. 11. Decision makers who use pest risk maps to prioritize and plan their response activities have a method for choosing strategies that best balance robustness to uncertainty with the opportunity to exploit some of that uncertainty in order to reduce critical knowledge gaps, which are common for newly emerging invasive species threats. 12. Pest risk mappers now have a set of strategic targets for their further research (related, for example, to uncertainty, climate change, and human dimensions of biological invasions), while decision makers should have a better understanding of the current limitations of risk maps and what can be done to improve their quality and increase their utility for decision support. 13. Pest risk modelers can use this information to build better integrated risk models, and regulatory decision makers can use this information to determine where their resources may be used efficiently (e.g., for border inspections or long-term detection monitoring). 14. The Forest Inventory and Analysis public database is widely used by researchers across the country and the user's guide is vital to efficient use of the database. 15. This was the first nationally-consistent assessment of green infrastructure, and it enables state and local land managers to evaluate trans-boundary infrastructure. 16. This was the first nationally-consistent assessment of the landscape context of forest and grassland, and the work is or has been reported in the United States Forest Assessment and the United States Resource Planning Act Assessment. 17. Detailed satellite detections of forest change are providing scientists and managers with more accurate predictions focused on where future forest change is likely to occur and why.

Publications

  • Woodall, Christopher W.; Conkling, Barbara L.; Amacher, Michael C.; Coulston, John W.; Jovan, Sarah; Perry, Charles H.; Schulz, Beth; Smith, Gretchen C.; Will Wolf, Susan. 2010. The Forest Inventory and Analysis Database Version 4.0: Database Description and Users Manual for Phase 3. Gen. Tech. Rep. NRS-61. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern Research Station. 180 p.
  • Ambrose, M.J. 2009. Introduction. IN: Ambrose, M.J. and B.L. Conkling, eds. Forest Health Monitoring 2006 National Technical Report. Gen. Tech. Rep. SRS-117. Asheville, NC: US Department of Agriculture Forest Service, Southern Research Station: 1-8. Chapter 1.
  • Ambrose, M.J. 2009. Summary. IN: Ambrose, M.J. and B.L. Conkling, eds. Forest Health Monitoring 2006 National Technical Report. Gen. Tech. Rep. SRS-117. Asheville, NC: US Department of Agriculture Forest Service, Southern Research Station: 111-113. Chapter 9.
  • Ambrose, Mark J.; Conkling, Barbara L., eds. 2009. Forest health monitoring: 2006 national technical report. Gen. Tech. Rep. SRS-117. Asheville, NC: U.S. Department of Agriculture Forest Service, Southern Research Station. 118 p.
  • Downing, M.C.; Coleman, T.C.; Koch, F.H.; Seybold, S.J.; Smith, S.; Smith, W.D.; Venette, R.C. 2009. Wildland oak resources at risk map for gold-spotted oak borer (Agrilus coxalis). Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Forest Health Technology Enterprise Team. http://www.fs.fed.us/foresthealth/technology/invasives_agriluscoxalis_riskmaps.s html
  • Jetton, Robert; Dvorak, William; Whittier, Andrew; Potter, Kevin; Rhea, Rusty. 2009. Genetics and conservation of hemlock species threatened by the hemlock woolly adelgid
  • Koch, F.H. 2009. Marine cargo imports and forest pest introductions. IN: Ambrose, M.J. and B.L. Conkling, eds. Forest Health Monitoring 2006 National Technical Report. Gen. Tech. Rep. SRS-117. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station: 53-64. Chapter 7.
  • Koch, F.H. 2009. Relating lightning data to fire occurrence data. IN: Ambrose, M.J. and B.L. Conkling, eds. Forest Health Monitoring 2006 National Technical Report. Gen. Tech. Rep. SRS-117. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station: 15-25. Chapter 3.
  • Koch, Frank H.; Yemshanov, Denys; McKenney, Daniel W.; Smith, William D. 2009. Evaluating critical uncertainty thresholds in a spatial model of forest pest invasion risk. Risk Analysis, Vol. 29(9): 1227-1241
  • Potter, Kevin M.; Frampton, John; Josserand, Sedley A.; Nelson, C. Dana 2010. Evolutionary history of two endemic Appalachian conifers revealed using microsatellite markers. Conserv Genet 11:1499-1513.
  • Riitters, K.H. 2009. Fragmentation. Pp 22-26 in Smith, W.B, Miles, P.D., Perry, C.H., Pugh, S.A. (eds), Forest Resources of the United States, 2007. Gen. Tech. Rep. WO-78. Washington, DC: U.S. Department of Agriculture, Forest Service, Washington Office. 336 p.
  • Riitters, Kurt; Wickham, James; Wade, Timothy 2009. Evaluating anthropogenic risk of grassland and forest habitat degradation using land-cover data. Landscape Online 13:1-14.
  • Venette, Robert C.; Kriticos, Darren J.; Magarey, Roger D.; Koch, Frank H.; Baker, Richard H. A.; Worner, Susan P.; Raboteaux, Nadila N. Gomez; McKenney, Daniel W.; Dobesberger, Erhard J.; Yemshanov, Denys; De Barro, Paul J.; Hutchinson, William D.; Fowler, Glenn; Kalaris, Tom M.; Pedlar, John. 2010. Pest risk maps for invasive alien species: a roadmap for improvement. Bioscience 60(5):349-362.


Progress 10/01/08 to 09/30/09

Outputs
OUTPUTS: Eastern Forest Environmental Threat Assessment Center researchers and partners contributed significantly to national forest health monitoring research: 1. Produced a series of high resolution phenology (seasonal changes in vegetation) map products, derived from satellite imagery for the conterminous United States, to support regional scale risk assessments. 2. Used spatial models of future environment conditions to assess the risk of extinction and predict the location and quality of habitat for forest tree species under different climate scenarios. 3. Adapted a generic bioeconomic modeling framework for examining pest invasions through time with sirex woodwasp (Sirex noctilio) in eastern North America as a specific example for the purpose of mapping risk and associated output uncertainties. 4. Applied a statistical power analysis to Forest Inventory and Analysis Crown-Indicator variables (crown density, foliage transparency, and crown dieback). 5. Identified a second, qualitatively different type of phase transition corresponding to an abrupt change of edge context from interior to exterior (or vice versa). 6. Developed an analysis that quantifies forest community evolutionary diversity across the conterminous United States and used to conduct large-scale risk assessments. 7. Developed and posted several Google Earth applications to enable visualization of three landscape and forest spatial metrics at local to national scale. 8. Produced annual reports describing the health of the nation's forests. 9. Participated in a workshop to implement a pilot test of forest health indicators in Mexico. 10. Presented invasive species research and participated in sessions and field activities at the International Union of Forest Research Organizations International Forest Biosecurity Conference in New Zealand. 11. Adapted a Canadian model to create a generalized framework for Sirex noctilio spread and impact in the United States and eastern North America 12. Completed the Mid-Atlantic Integrated Assessment highlighting the status and changes in forests across areas such as history, land use change, population growth and urbanization, and carbon sequestration. PARTICIPANTS: 1. EFETAC ecologist William Hargrove and partners from USDA Forest Service Forest Inventory and Analysis and Forest Health Monitoring; International Cooperative Programme on Assessment and Monitoring of Air Pollution Effects on Forests; NASA Stennis Space Center; University of North Carolina Asheville's National Environmental Modeling and Analysis Center 2. EFETAC cooperating researcher Kevin Potter (North Carolina State University NCSU) and partners from the Southern Research Station 3. EFETAC cooperating researcher Frank Koch (NCSU) and partners from the Southern Research Station 4. EFETAC research forester Bill Bechtold and partners from NCSU and the Southern Research Station 5. EFETAC landscape ecologist Kurt Riitters and partners from the European Commission, Joint Research Center, Institute for Environment and Sustainability and the Southern Research Station 6. EFETAC cooperating researcher Kevin Potter (NCSU) and EFETAC research ecologist Bill Hargrove 7. EFETAC landscape ecologist Kurt Riitters and partners from the European Commission, Joint Research Center, Institute for Environment and Sustainability; University of North Carolina at Asheville's National Environmental Modeling and Analysis Center; and the Southern Research Station 8. EFETAC research forester Bill Bechtold and partners from NCSU 9. EFETAC research forester Bill Bechtold and partners from Mexico; Forest Service State and Private Forestry and Research and Development; and Oregon State University 10. EFETAC cooperating research Frank Koch (NCSU) and partners from the International Union of Forest Research Organizations 11. EFETAC collaborating researcher Frank Koch (NCSU) and partners from the Canadian Forest Service and USDA Animal and Plant Health Inspection Service 12. EFETAC research ecologist Ken Stolte and partners from the Environmental Protection Agency TARGET AUDIENCES: Researchers, natural resource managers, planners, policy makers, landowners, general public PROJECT MODIFICATIONS: None

Impacts
1. Detailed satellite detections of forest change are providing scientists and managers with more accurate predictions focused on where future forest change is likely to occur and why. 2. Scientists and policymakers can better determine which forest tree species and populations may be most vulnerable to a change in climate. 3. By improving understanding of how invasives spread, managers can more effectively slow their spread, predict when and where ecological effects are likely to occur, and when and where mitigation efforts may be warranted. 4. Scientists can determine how many plots are necessary to detect various degrees of change at various levels of statistical power. 5. The research lends further insight into abrupt changes in ecological functions, focusing on interior and exterior edges. 6. When regional forest planners have deeper insights into the evolutionary reasons for why some forests are more vulnerable than others, this provides strategic insights that can be used to improve long-term forest heath. 7. A wide range of users, including readers of official forest assessment reports, are able to more easily view and understand U.S. landscape patterns and the implications of landscape change. 8. The annual reports synthesize data from a variety of sources to provide an overview of forest health based on criteria and indicators of sustainable forestry. 9. Forest health indicators will provide information to decision makers and land managers on the status and trends of Mexico's forests, including tree vitality, biodiversity, fire risk, and invasive species. 10. Research exchange encouraged potential advancement in areas including pest detection and sampling, pest risk analysis, biological control, and characterization of economic and ecological impacts. 11. More effective prevention and control methods are possible with risk mapping, as well as greater understanding of uncertainties inherent in risk mapping 12. The mid-Atlantic assessment provides forest sector information to land managers and policy analysts in that region.

Publications