South Atlantic Beach Birds (Southeast Blueprint Indicator)

Reason for Selection The relative use of beach habitat by shorebird species for nesting, foraging, and breeding is an indicator of beach health and quality. Shorebird populations are highly responsive to threats like sea-level rise, changes in freshwater inflow, shoreline alteration and loss, human disturbances, and contaminants. In particular, the American oystercatcher “has been proposed as a ‘sentinel’ bio-indicator of ecosystem integrity because of the depth of life history information available, its specialized dependence on oysters and associated marine invertebrates, and known reproductive responses to a variety of natural and anthropogenic pressures” (Ogden et al. 2014). As a result of these pressures, North American shorebird populations are experiencing “consistent, steep population loss” (Ronenberg et al. 2019). The species included in this index are already monitored by state and Federal agencies and collectively represent a variety of coastal ecosystem features (e.g., nesting habitat availability and quality, fish and marine invertebrate populations). Input Data * [South Atlantic Blueprint 2021 extent] * [Base Blueprint 2022 extent] * [Southeast Blueprint 2023 extent] * [2019 National Land Cover Database] (NLCD): Land cover * [2023 U.S. Census TIGER/Line state boundaries], accessed 5-15-2023; [download the data] * The following beach bird datasets: Wilson’s plover and American oystercatcher Betsy Von Holle (University of Central Florida) led a project that included state waterbird biologists in the South Atlantic: Tim Keyes, Felicia Sanders, Sara Schweitzer, and Janell Brush. They mapped habitat suitability based on nest, or breeding pair, density per beach segment, as was used for Von Holle et al.’s sea turtle research. The approach is documented in Von Holle et al. 2018. The following nesting years were used for the analysis: * American oystercatcher: FL (2005-2011), GA (2010-2011), SC (2008), NC (2007) * Wilson’s plover: FL (2005-2011), GA (2010-2011), SC (2009-2011), NC (2007) Piping plover and least tern A previous post-doctoral researcher, Bradley Pickens, processed the following datasets by ranking least tern nest abundance and piping plover individuals by quantile (0-6). They were exported as 90 m rasters. Least tern The point locations and number of least tern nests, or breeding pairs, were provided by waterbird biologists from each state’s natural resource department (Tim Keyes, Felicia Sanders, Sara Schweitzer, and Janell Brush). All least tern locations were buffered by 1 km. Although least tern do not actively forage on the beach itself, the buffer characterizes habitat selected by least tern (i.e., beach width, predator abundance, etc.) and accounts for interannual variability in nesting locations. Among years, data showed least tern often shifted the location of nests in the general vicinity of previous years. Piping plover (winter distribution) The 2011 winter population census of piping plover was provided by the U.S. Geological Survey, as the international census is repeated every five years. Locations were buffered with a 2 km radius. Although home range estimates exist for piping plover (Cohen et al. 2008, Drake et al. 2001), these measures depict primarily linear habitats. We used a 2 km buffer, as this is similar to the mean linear distance of 4.2 km that piping plover moved during winter in Texas (Drake et al. 2001). The resulting buffer was also substantiated by maps in Cohen et al. (2008). Mapping Steps * Von Holle et al. used a categorical habitat suitability ranking based on six quantiles of nest density, or breeding pair density, for each species on the Atlantic Coast. Convert to numeric scores by assigning a value of 0 to polygons rated as “none”, a value of 1 to those rated as “low”, a value of 2 to those rated as “moderate”, a value of 3 to those rated as “moderately high”, a value of 4 to those rated as “high”, a value of 5 to those rated as “very high”, and a value of 6 to those rated “extremely high”. Convert the polygons to a separate raster for each species (Wilson’s plover and American oystercatcher), assigning those numeric values. * Resample and reproject the least tern and piping plover source data from 90 m pixels to 30 m pixels so it can be used in Zonation in a later step. * Create a mask to define the extent of the Zonation run that will be used to create this indicator. Use cell statistics to combine all 4 bird rasters (the two Von Holle rasters created in the previous step, and the 90 m piping plover and least tern rasters) with the output statistic maximum value. Include in the mask all pixels with a value >0 on any of the bird rasters. * To create the beach bird index, use the software program Zonation v4 with the core-area algorithm and without the edge removal option (removal rule = 1, edge removal = 0, warp = 1). Input the mask and the rasters for all four species. Zonation produces a continuous ranking of all pixels within the mask based on their importance for the 4 beach-nesting bird species. * Reclassify the output Zonation rank raster into 5 classes, seen in the final indicator values below. This layer represents the relative use of habitat for beach nesting birds in the South Atlantic. Generally, areas with higher values in this layer are considered to have greater relative abundance of beach nesting birds than areas with lower values. * To create an analysis extent for the indicator, buffer the polygons provided by Von Holle by 25 km. Assign a value of 0 to all pixels within the analysis extent that do not already receive a score elsewhere in the indicator. Zero values are intended to help users better understand the extent of this indicator and make it perform better in online tools. * Clip to the South Atlantic Blueprint 2021 extent. * Further limit the extent of the zero class by removing pixels from Virginia, because the source data did not cover Virginia. Also, remove deep marine areas that are not covered by a value of 0 or greater in the 2019 NLCD, where this terrestrial indicator does not apply. * 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 = >80th percentile of importance for bird index species (American oystercatcher, Wilson’s plover,least tern, and piping plover) 4 = >60th-80th percentile of importance 3 = >40th-60th percentile of importance 2 = >20th-40th percentile of importance 1 = ≤20th percentile of importance 0 = Open water or not identified as a priority for bird index species Known Issues * Beach bird survey data are summarized by beach segment and do not account for variations in density within those segments. * Volunteers often collect beach bird data in discrete time frames and survey effort may differ by location. Some areas may not have been surveyed or nests may have been missed. Therefore, this data does not imply absence of species. * Red knot is not included due to lack of data. * This indicator may underestimate beach bird use of dune areas inland of beach segments because of inconsistencies in the extent of the various bird models. * The spatial resolution of the source data for least tern and piping plover has been degraded. While the indicator has a 30 m resolution, it was not created directly from the spatially precise input data for those two birds. Here, we resampled the 90 m resolution data used in the previous version of the indicator back down to 30 m resolution so that we could use it in Zonation. * The indicator has an extraneous “tail” of zero values at its southern edge. This is an artifact of how the buffer of zero values was created. Since zero values do not influence Zonation, this does not affect the final Blueprint priorities. It was discovered too late to fix in this update cycle. We hope to make a larger improvement to this indicator in the future to better depict important areas for beach birds across more of the region’s coastline. 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 Cohen, J.B., Karpanty, S.M., Catlin, D.H., Fraser, J.D., Fischer, R.A., 2008. Winter Ecology of Piping Plovers at Oregon Inlet, North Carolina. Waterbirds 31, 472-479. [[https://doi.org/10.1675/1524-4695-31.3.472]]. Drake, K.R., Thompson, J.E., Drake, K.L., Zonick, C., 2001. Movements, habitat use, and survival of nonbreeding Piping Plovers. The Condor 103, 259-267. [[https://doi.org/10.1093/condor/103.2.259]]. Moilanen, A., L. Meller, J. Leppänen, F.M. Pouzols, H. Kujala, A. Arponen. 2014. Zonation Spatial Conservation Planning Framework and Software V4.0, User Manual. [[https://github.com/cbig/zonation-core/releases/download/4.0.0/zonation_manual_v4_0.pdf]]. Ogden, John C., John D. Baldwin, Oron L. Bass, Joan A. Browder, Mark I. Cook, Peter C. Frederick, Peter E. Frezza, Rafael A. Galvez, Ann B. Hodgson, Kenneth D. Meyer, Lori D. Oberhofer, Ann F. Paul, Pamela J. Fletcher, Steven M. Davis, Jerome J. Lorenz. Waterbirds as indicators of ecosystem health in the coastal marine habitats of southern Florida: 1. Selection and justification for a suite of indicator species, Ecological Indicators, Volume 44, 2014, Pages 148-163, ISSN 1470-160X, [[https://doi.org/10.1016/j.ecolind.2014.03.007]]. Von Holle, B., Irish, J. L., Spivy, A., Weishampel, J. F., Meylan, A., Godfrey, M. H., Dodd, M., Schweitzer, S.H., Keyes, T., Sanders, F., Chaplin, M. K. 2018. Effects of future sea level rise on coastal habitat. The Journal of Wildlife Management 9999. [[https://wildlife.onlinelibrary.wiley.com/doi/epdf/10.1002/jwmg.21633]]. Rosenberg, Kenneth & Dokter, Adriaan & Blancher, Peter & Sauer, John & Smith, Adam & Smith, Paul & Stanton, Jessica & Panjabi, Arvind & Helft, Laura & Parr, Michael & Marra, Peter. (2019). Decline of the North American avifauna. Science. 366. [[https://www.science.org/doi/10.1126/science.aaw1313]]. U.S. Department of Commerce, U.S. Census Bureau, Geography Division, Spatial Data Collection and Products Branch. TIGER/Line Shapefile, 2023, U.S. Current State and Equivalent National. 2023. [[https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html]].