Atlantic Marine Birds (Southeast Blueprint Indicator)

Marine birds help identify key areas of ocean productivity and overall ocean health. According to Parsons et al. 2008, seabirds are often considered useful ecological indicators for the marine environment because they “essentially represent the top of the food chain” and therefore are likely to signal changes in lower trophic levels and the surrounding environment. Seabird populations also respond to anthropogenic pressures such as “overexploitation of their food resources and pollution from industrial discharge.” Long-term monitoring has “generated high-quality data on population counts and demographic parameters” and seabirds “are considered to be of international importance and have high resonance with the public and policy-makers” (Parsons et al. 2008). This indicator complements the Atlantic marine mammals indicator by providing finer spatial resolution and stronger connections to forage fish productivity. Input Data * [Southeast Blueprint 2023 extent] * [2019 National Land Cover Database] (NLCD): Land cover * [Seasonal avian abundance models (Version 2.0) from Duke University’s Marine-life Data and Analysis Team] (Avian abundance ZIP), accessed 6-8-2021 These models use aggregated survey information and oceanographic variables to predict the relative abundance of marine birds across the entire U.S. Atlantic. Potential species to include in this indicator began with Tier 1 and Tier 2 priority species in Bird Conservation Region 27 (the Southeastern Coastal Plain) in the [Southeast United States Regional Waterbird Conservation Plan]. This plan did not include waterfowl species, so additional waterfowl were added from priority species identified by the Northwest Atlantic Birds at Sea Conservation Cooperative (now [the Atlantic Marine Bird Cooperative]). We narrowed down this larger combined list in two ways. First, we removed species from the list that didn’t have spatial models available. Then, we removed species that had models with poor predictive performance and/or large spatial errors. Species with seasonal models used in this indicator are: Audubon’s shearwater (fall, spring, summer), band-rumped storm-petrel (summer), black-capped petrel (spring, summer, winter), black scoter (fall, spring, winter), Bonaparte’s gull (spring, winter), bridled tern (fall, summer), brown pelican (fall), common loon (spring, summer, winter), common tern (fall, spring, summer), Cory’s shearwater (fall, spring, summer), great shearwater (fall, spring, summer), Manx shearwater (fall, spring, summer), Northern gannet (spring, summer, winter), parasitic jaeger (fall, spring, summer), red-throated loon (spring, winter), royal tern (fall, spring, summer), sooty shearwater (fall, spring, summer), sooty tern (spring, summer) and white-winged scoter (fall, spring, winter). Mapping Steps * To identify important areas for each species, use the core area algorithm (CAZMAX) in Zonation 5. Include each seasonal abundance layer as a separate input and weight them equally. To account for boundary effects, run all the models across the full extent of the input data (entire U.S. Atlantic). * Reproject the resulting data to Albers Equal area. * Resample the data to 30 m cell size using the nearest neighbor method (the source data is 2 km cells). * Convert from a floating point raster with a range of 0-1 to an integer raster ranging from 0-100. * Reclassify to values of 1-10 based on increments of 10 to produce the indicator values seen below. * Add a zero class for land by reclassifying the NLCD to identify areas of land included in the marine mammal models, which are outside the scope of this indicator. Assign a value of 0 to all pixels that are not a value of 0 or 11 in the NLCD. * 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: 10 = >90th percentile of importance for marine bird index species (across the full East Coast study area) 9 = >80th-90th percentile of importance 8 = >70th-80th percentile of importance 7 = >60th-70th percentile of importance 6 = >50th-60th percentile of importance 5 = >40th-50th percentile of importance 4 = >30th-40th percentile of importance 3 = >20th-30th percentile of importance 2 = >10th-20th percentile of importance 1 = ≤10th percentile of importance 0 = Land Known Issues * Models are likely underpredicting the importance of areas in the eastern part of the Atlantic marine ecosystem. Survey effort was very low in that area and many input models did not extend their predictions into the eastern area. * This indicator does not capture fine resolution patterns nearshore. Model predictions are fairly coarse and do not capture finer variations in relative abundance nearshore and near estuaries. * This indicator does not cover the estuarine ecosystem. Many of these marine bird species could also be excellent indicators in the open water portion of the estuarine ecosystem; however, spatial models covering the full area of the estuarine ecosystem are not available at this time. * While this layer has a 30 m resolution, the source data was coarser than that. We downsampled 2 km pixels to 30 m. * There are a small number of pixels on the eastern edge of the Atlantic marine subregion, east of central and southern Florida, where the Duke models have no data. As a result, those areas are not scored in this indicator. Other Things to Keep in Mind * We ran the Zonation analysis across the full East Coast study area because some of the important areas for some species during some months were mostly in an area north of the Blueprint area and just barely extended into the northernmost tip of the Southeast Blueprint marine area. If we ran Zonation only within the Southeast Blueprint Atlantic marine subregion, the indicator would have overprioritized those areas, since they would appear to be very rare features, when in actuality they are common features that just more frequently occur further north. While doing the Zonation run across the full East Coast study area addressed this problem, it means that the percentile calculations are for the full East Coast study area, which included areas outside the extent of the final indicator. As a result, the various classes within the indicator do not cover equal areas within the indicator’s extent, as you might expect with a percentile-based indicator—they cover equal areas within the full East Coast study area, and then are clipped down to produce the indicator. 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 Curtice, C., Cleary J., Shumchenia E., Halpin P.N. 24 June 2019. Marine-life Data and Analysis Team (MDAT) technical report on the methods and development of marine-life data to support regional ocean planning and management. Prepared on behalf of the Marine-life Data and Analysis Team (MDAT). [[https://seamap.env.duke.edu/models/mdat/MDAT-Technical-Report.pdf]]. Hunter, W.C., Golder, W., Melvin, S., Wheeler, J., 2006. Southeast United States Regional Waterbird Conservation Plan. U.S. Fish and Wildlife Service, Atlanta, GA. [[https://static1.squarespace.com/static/5bb3865d2727be6f94acf2fc/t/5c79a2efe5e5f0214c34c48c/1551475442564/SE_US_Waterb_Plan_2006.pdf]]. Moilanen, A., Lehtinen, P., Kohonen, I., Virtanen, E., Jalkanen, J. and Kujala, H. 2022. Novel methods for spatial prioritization with applications in conservation, land use planning and ecological impact avoidance. Methods in Ecology and Evolution. [[https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.13819]]. Parsons, Matt, Ian Mitchell, Adam Butler, Norman Ratcliffe, Morten Frederiksen, Simon Foster, James B. Reid, Seabirds as indicators of the marine environment, ICES Journal of Marine Science, Volume 65, Issue 8, November 2008, Pages 1520–1526. [[https://doi.org/10.1093/icesjms/fsn155]].