East Coastal Plain Open Pine Birds (Southeast Blueprint Indicator)

Reason for Selection Open longleaf pine forests once spanned nearly 90 million acres across the Southeast, supporting a rich community of wildlife and plants. Fire suppression, deforestation, and conversion to ecosystems dominated by loblolly and slash pine have dramatically reduced the extent of longleaf and caused the decline of many associated species. In addition, pine and prairie birds are experiencing significant declines and are [currently off-track for meeting the SECAS 10% goal], so it is important that the Blueprint capture opportunities to conserve, restore, and manage open pine habitat. This indicator also promotes consistency with the longleaf and open pine ecosystem priorities of the East Gulf Coastal Plain Joint Venture (EGCPJV). Input Data * Bird priorities from [Prioritization of areas for open pine ecosystem restoration in the Southeastern United States] (bird_priority.tif); [read the project final report]; [read a news article about the project]; [explore the data in the EGCPJV Open Pine Decision Support Tool] * Estimated Floodplain Map of the Conterminous U.S. from the [Environmental Protection Agency’s (EPA) EnviroAtlas]; [see this factsheet] for more information; [download the data] The EPA Estimated Floodplain Map of the Conterminous U.S. displays “...areas estimated to be inundated by a 100-year flood (also known as the 1% annual chance flood). These data are based on the Federal Emergency Management Agency (FEMA) 100-year flood inundation maps with the goal of creating a seamless floodplain map at 30-m resolution for the conterminous United States. This map identifies a given pixel’s membership in the 100-year floodplain and completes areas that FEMA has not yet mapped” (EPA 2018). * [2019 National Land Cover Database] (NLCD): Land cover * [Base Blueprint 2022 extent] * [Southeast Blueprint 2023 extent] Mapping Steps * Reproject the EGCPJV bird priority data to NAD 1983 Contiguous USA Albers (EPSG 5070). * If an area intersects an EPA Estimated Floodplain, change the value to NoData. * If an area is something besides Evergreen Forest or Mixed Forest in the 2019 NLCD, change the value to NoData. Because the bird priority layer was made with older landcover data, this step helps remove areas that do not currently have pine trees. * The EGCPJV bird data provides a raster with scores of 0-100 representing the relative potential for open pine bird response to conservation action. Reclassify this raster as shown in in the legend below. * Add zero values to represent the extent of the source data and to make it perform better in online tools. Assign a value of 0 to any pixel that had a value ≥ 0 in the original bird priorities layer but was converted to NoData above. * Clip to the spatial extent of Base Blueprint 2022. * As a final step, clip to the spatial extent of Southeast Blueprint 2023. Note: For more details on the mapping steps, code used to create this layer is available in the [Southeast Blueprint Data Download] under > 6_Code. Final indicator values Indicator values are assigned as follows: 5 = High priority for open pine conservation for focal bird species (Bachman’s sparrow, red-cockaded woodpecker, Henslow’s sparrow, red-headed woodpecker, Northern bobwhite, and brown-headed nuthatch) (score >80-100) 4 = Medium-high priority (score >60-80) 3 = Medium priority (score >40-60) 2 = Medium-low priority (score >20-40) 1 = Low priority (score 0-20) 0 = Not a priority (not identified as upland pine) Known Issues * The EGCPJV’s open pine bird model includes frequently inundated floodplain areas. These areas are unlikely to be potential open pine habitat. To address this in the indicator, we removed areas within the EPA estimated floodplain. * This indicator prioritizes some areas outside of the floodplain that were not historically open pine habitat. * The 2019 NLCD classes used to exclude non-pine areas of the open pine bird model (evergreen forest and mixed forests) do not exclusively target pine trees. For example, the evergreen class can include other evergreen tree species like Eastern red cedar or southern magnolia. In addition, the NLCD likely misclassifies other types of land cover as evergreen or mixed forests. As a result, this indicator may leave in some areas prioritized in the bird model that are not actually pine. Conversely, the NLCD also likely misclassifies some areas of pine as other land cover classes, which could cause pine areas prioritized in the model to be inadvertently excluded from the indicator. * This indicator does not capture areas where planting new pine stands in existing agricultural areas would benefit open pine birds. Disclaimer: Comparing with Older Indicator Versions There are numerous problems with using Southeast Blueprint indicators for change analysis. Please consult Blueprint staff if you would like to do this (email [hilary_morris@fws.gov]). Literature Cited Grand, J.B., and Kleiner, K.J., 2017, Prioritization of areas for open pine ecosystem restoration in the Southeastern United States: U.S. Geological Survey data release, [[https://doi.org/10.5066/F7P26WN2]]. Grand, James B. and Kevin J. Kleiner. 2016. Prioritizing Landscapes for Longleaf Pine Conservation. Report provided by the Cooperative Fish and Wildlife Research Unit Program under agreement with the U.S. Fish and Wildlife Service. U.S. Department of Interior, Fish and Wildlife Service, Cooperator Science Series FWS/CSS-119-2016, National Conservation Training Center. [[https://digitalmedia.fws.gov/digital/collection/document/id/2131]]. Open Pine Decision Support Tool. [[https://scagulf.shinyapps.io/opdst/]]. U.S. Geological Survey (USGS). Published June 2021. National Land Cover Database (NLCD) 2019 Land Cover Conterminous United States. Sioux Falls, SD. [[https://doi.org/10.5066/P9KZCM54]]. Yang, L., Jin, S., Danielson, P., Homer, C., Gass, L., Case, A., Costello, C., Dewitz, J., Fry, J., Funk, M., Grannemann, B., Rigge, M. and G. Xian. 2018. A New Generation of the United States National Land Cover Database: Requirements, Research Priorities, Design, and Implementation Strategies, ISPRS Journal of Photogrammetry and Remote Sensing, 146, pp.108-123. [[https://doi.org/10.1016/j.isprsjprs.2018.09.006]].