Datasets archived here consist of all data analyzed in Duan et al. 2015 from Journal of Applied Ecology. Specifically, these data were collected from annual sampling of emerald ash borer (Agrilus planipennis) immature stages and associated parasitoids on infested ash trees (Fraxinus) in Southern Michigan, where three introduced biological control agents had been released between 2007 - 2010. Detailed data collection procedures can be found in Duan et al. 2012, 2013, and 2015.

For large areas, like Washington State, download as a file geodatabase.  Large data sets like this one, for the State of Washington, may exceed the limits for downloading as shape files, excel files, or KML files.  For areas less than a county, you may use the map to zoom to your area and download as shape file, excel or KML, if that format is desired.Every summer for approximately the past seventy years, an insect and disease aerial detection survey has been flown of all the forested acres of Washington state (except where noted in the digital data by large 'NF' (not flown) areas). This survey is a cooperative effort between the U.S. Forest Service and the WADNR with two different flight observers each sketching a two mile swath out their side of the plane. The primary mission of the survey is to record recently killed and defoliated groups of trees throughout the state, and to continually build a historical record of these trends. The vast majority of damage found is caused by insect and disease damage agents; however, trees killed by early spring feeding of black bears or by events such as winter storms, fires, floods and landslides are recorded as well. Current defoliation can be detected as soon as the affected foliage changes color that year. However, whole tree mortality is not current since only flagged trees (i.e., trees which have a bright red, orange, or yellow foliage color) are recorded. This means that trees killed the year of the survey will not have changed color yet and so a one year lag time results. Since only this distinctive color or "signature" of the tree can be seen. It is an educated guess as to the causal agent. We therefore use ground surveys to reinforce our estimates as much as possible. Example: When bear damage is spotted while surveying, a polygon is drawn on the map of the size and location of the damage. The polygon is then labeled with the appropriate damage agent (i.e. Bear) and the number of trees affected rounded to the nearest five. No vertical data is recorded.

The attached dataset comprises 187 records, summarized by 2010 census tract. There are 40 variable fields including percent landcover type from the 2011 30m National Land Cover Dataset, density of greenway trails from Wake County (NC) gov't, and demographic attributes from the 2014 American Community Survey. Two fields reflect count (during 2013-2015) and rate of sudden death; these fields are blank because these human-health data are protected under IRB agreement through UNC. The EPA/ORD point of contact for this analysis is Dr. Laura Jackson (jackson.laura@epa.gov). If interested in acessing the Wake County sudden death dataset, please contact Dr. Ross Simpson (ross_simpson@med.unc.edu). This dataset is associated with the following publication: Wu, J., K. Rappazzo, R. Simpson, G. Joodi, I. Pursell, P. Mounsey, W. Cascio, and L. Jackson. Exploring links between greenspace and sudden unexpected death: a spatial analysis. ENVIRONMENT INTERNATIONAL. Elsevier B.V., Amsterdam, NETHERLANDS, 113: 114-121, (2018).

The MANAGE (Measured Annual Nutrient loads from AGricultural Environments) database was developed to be a readily-accessible, easily-queried database of site characteristic and field-scale nutrient export data (Harmel et al., 2006). Initial funding for MANAGE was provided by USDA-ARS to support the USDA Conservation Effects Assessment Project (CEAP) and the Texas State Soil and Water Conservation Board as part of their mission to understand and mitigate agricultural impacts on water quality. The original version of MANAGE, which drew heavily from an early 1980’s compilation of nutrient export data (Reckhow et al., 1980; Beaulac, 1980; Beaulac and Reckhow, 1982), created an electronic database with nutrient load data and corresponding site characteristics from 40 studies on agricultural (cultivated and pasture/range) land uses. The first revision in 2008 added N and P load data from 15 additional studies along with N and P runoff concentration data for all 55 studies (Harmel et al., 2008). The second revision in 2016 added 30 runoff studies from forested land uses, 91 drainage water quality studies from drained land, and 12 additional runoff studies from cultivated and pasture/range (Christianson and Harmel, 2015; Harmel et al., 2016). In this expansion, fertilizer application timing, crop yield, and N and P uptake data were added to facilitate analysis of 4R Nutrient Stewardship. The latest revision (Harmel et al., 2022) added 27 studies and Level II ecoregion delineations for each of the 94 studies such that data are now available from 11 of the 50 North American Level II ecoregions, representing the major U.S. agricultural regions. With these updates, MANAGE contains data from a vast majority of published peer-reviewed N and P export studies on homogeneous cultivated, pasture/range, and forested land uses in the US under natural rainfall-runoff conditions, as well as artificially drained agricultural land. Thus MANAGE facilitates expanded spatial analyses and improved understanding of regional differences, management practice effectiveness, and impacts of land use conversions and management techniques, and it provides valuable data for modeling and decision-making related to agricultural runoff. The Manage Database v5 04-04-2018 zip file resource superseded the previously available v4 and was added to this record on May 30, 2018. Resource MANAGE Database v6 added Nov 17, 2022.

Report on terrestrial carbon sequestration opportunities in New Jersey regarding agricultural land, forest lands, wetlands, mine lands, and the demonstration project piloting enhanced forested wetland.

Note: This is a large dataset. To download, go to ArcGIS Open Data Set and click the download button, and under additional resources select the shapefile or geodatabase option. America's private forests provide a vast array of public goods and services, including abundant, clean surface water. Forest loss and development can affect water quality and quantity when forests are removed and impervious surfaces, such as paved roads, spread across the landscape. We rank watersheds across the conterminous United States according to the contributions of private forest land to surface drinking water and by threats to surface water from increased housing density. Private forest land contributions to drinking water are greatest in the East but are also important in Western watersheds. Development pressures on these contributions are concentrated in the Eastern United States but are also found in the North-Central region, parts of the West and Southwest, and the Pacific Northwest; nationwide, more than 55 million acres of rural private forest land are projected to experience a substantial increase in housing density from 2000 to 2030. Planners, communities, and private landowners can use a range of strategies to maintain freshwater ecosystems, including designing housing and roads to minimize impacts on water quality, managing home sites to protect water resources, and using payment schemes and management partnerships to invest in forest stewardship on public and private lands.This data is based on the digital hydrologic unit boundary layer to the Subwatershed (12-digit) 6th level for the continental United States. To focus this analysis on watersheds with private forests, only watersheds with at least 10% forested land and more than 50 acres of private forest were analyzed. All other watersheds were labeled ?Insufficient private forest for this analysis'and coded -99999 in the data table. This dataset updates forest and development statistics reported in the the 2011 Forests to Faucet analysis using 2006 National Land Cover Database for the Conterminous United States, Grid Values=41,42,43,95. and Theobald, Dr. David M. 10 March 2008. bhc2000 and bhc2030 (Housing density for the coterminous US in 2000 and 2030, respectively.) Field Descriptions:HUC_12: Twelve Digit Hydrologic Unit Code: This field provides a unique 12-digit code for each subwatershed.HU_12_DS: Sixth Level Downstream Hydrologic Unit Code: This field was populated with the 12-digit code of the 6th level hydrologic unit that is receiving the majority of the flow from the subwatershed.IMP1: Index of surface drinking water importance (Appendix Map). This field is from the 2011 Forests to Faucet analysis and has not been updated for this analysis.HDCHG_AC: Acres of housing density change on private forest in the subwatershed. HDCHG_PER: Percent of the watershed to experience housing density change on private forest. IMP_HD_PFOR: Index Private Forest importance to Surface Drinking Water with Development Pressure - identifies private forested areas important for surface drinking water that are likely to be affected by future increases in housing density, Ptle_IMP_HD: Private Forest importance to Surface Drinking Water with Development Pressure (Figure 7), percentile. Ptle_HDCHG: Percentage of each subwatershed to Experience an increase in House Density in Private Forest (Figure 6), percentile. FOR_AC: Acres forest (2006) in the subwatershed. PFOR_AC: Acres private forest (2006) in the subwatershed. PFOR_PER: Percent of the subwatershed that is private forest. HU12_AC: Acreage of the subwatershedFOR_PER: Percent of the subwatershed that is forest. PFOR_IMP: Index of Private Forest Importance to Surface Drinking Water. .Ptle_PFIMP: Private forest importance to surface drinking water(Figure 4), percentile. TOP100: Top 100 subwatersheds. 50 from the East, 50 from the west (using the Mississippi River as the divide.) Metadata

Web Soil Survey (WSS) provides soil data and information produced by the National Cooperative Soil Survey. It is operated by the USDA Natural Resources Conservation Service (NRCS) and provides access to the largest natural resource information system in the world. NRCS has soil maps and data available online for more than 95 percent of the nation’s counties and anticipates having 100 percent in the near future. The site is updated and maintained online as the single authoritative source of soil survey information.