Gulf Sea Turtles (Southeast Blueprint Indicator)

Reason for Selection As a keystone species, even at diminished population levels, sea turtles play an important role in ocean ecosystems by maintaining healthy seagrass beds and coral reefs, providing key habitat for other marine life, helping to balance marine food webs, and facilitating nutrient cycling from water to land (Wilson 2010). Sea turtles use large areas of the ocean for feeding and reproduction, making them a good indicator of ocean productivity and overall ocean health. For example, Kemp’s ridley sea turtles nesting in southern Texas consistently forage in areas near the Yucatán Peninsula, the Gulf coast of Florida, the Mississippi River Delta, and the Texas-Louisiana shelf (Gredzens and Shaver 2020). Input Data * Gulf of Mexico Marine Assessment Program for Protected Species (GoMMAPPS) -[GoMMAPPS sea turtle spatial density model outputs] (version 2.2) Based on ship-based and aerial line-transect surveys conducted in the U.S. waters of the Gulf of America between 2003 and 2019, the NOAA Southeast Fisheries Science Center developed spatial density models (SDMs) for cetacean and sea turtle species for the entire Gulf of America. SDMs were developed using a generalized additive modeling framework to determine the relationship between species abundance and environmental variables (monthly averaged oceanographic conditions during 2015-2019). * [Southeast Blueprint 2023 subregions]– marine (combined Atlantic & Gulf of America) * [Southeast Blueprint 2023 extent] * [2019 National Land Cover Database] (NLCD): Land cover Mapping Steps * Replace all values of -9999 with 0. * Convert to monthly rasters for each species using the following fields: “Jan_n”, “Feb_n”, “Mar_n”, “Apr_n”, “May_n”, “Jun_n”, “Jul_n”, “Aug_n”, “Sep_n”, “Oct_n”, “Nov_n”, and “Dec_n”. Use the marine subregion for pixel size, snap, and extent. * Use the loggerhead sea turtle data and the NLCD to create a mask to define the extent of the Zonation analysis. The loggerhead data represents the full sample area for the other species in GoMMAPPS. The area covered by the sea turtle models overlaps with land in a few areas. This mask removes from the analysis all landcover classes that are not open water (not a value of 11 in the NLCD) within the extent of NLCD. The resulting Zonation mask covers open water areas where there is both modeled data for sea turtles and NLCD data to remove land. * To identify important areas for each species, use the core area algorithm (CAZMAX) in Zonation 5. Include each monthly density layer as a separate input and weight them equally. * Reproject the Zonation results data to Albers Equal Area. * Convert from a floating point raster with a range of 0-1 to an integer raster ranging from 0-100. * Reclassify to produce the indicator values seen below so that 0-65 is 1, 66-70 is 2, 71-80 is 3, 81-90 is 4, and 91-100 is 5. The variation in values from Zonation below 65 was less helpful than the other higher classes so we classified all values from 65 and below as 1. * Use the NLCD and the modeling extent of the source data to identify areas of land not used in the analysis and assign those pixels a value of 0, since they are outside the scope of this marine indicator. * 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 = >90th percentile of importance for sea turtle index species (across larger analysis area) 4 = >80th-90th percentile of importance 3 = >70th-80th percentile of importance 2 = >65th-70th percentile of importance 1 = ≤65th percentile of importance 0 = Land Known Issues * While this layer has a 30 m resolution, the source data was coarser than that. We downsampled hexagons with an area of 40 km2 to 30 m pixels. Other Things to Keep in Mind * We ran the Zonation analysis across open water areas where there were both sea turtle models and NLCD data present to discriminate between land and water. We did this for multiple reasons. We didn’t run Zonation across the full area covered by the GoMMAPPS data because the full files were very large and required long processing times. We also anticipated that Zonation would not have been able to computationally handle the full area. We extended the Zonation run beyond U.S. waters to try to account for areas of high mammal density just south of the Blueprint’s Gulf of America subregion. 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 analysis 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 Gredzens C, Shaver DJ. 2020. Satellite tracking can inform population-level dispersal to foraging grounds of post-nesting Kemp’s ridley sea turtles. Frontiers in Marine Science, section Marine Megafauna, Special Theme Issue Research Topic: Advances in Understanding Sea Turtle Use of the Gulf of Mexico. [[https://doi.org/10.3389/fmars.2020.00559]]. Litz J, Aichinger Dias L, Rappucci G, Martinez A, Soldevilla M, Garrison L, Mullin K, Barry K, Foster M. 2022. Cetacean and sea turtle spatial density model outputs from visual observations using line-transect survey methods aboard NOAA vessel and aircraft platforms in the Gulf of Mexico from 2003-06-12 to 2019-07-31 (NCEI Accession 0256800). NOAA National Centers for Environmental Information. Dataset. [[https://doi.org/10.25921/efv4-9z56]]. Moilanen A, Lehtinen P, Kohonen I, Virtanen E, Jalkanen J, 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]]. Wilson, E.G., Miller, K.L., Allison, D. and Magliocca, M. 2010. Why Healthy Oceans Need Sea Turtles: The Importance of Sea Turtles to Marine Ecosystems. [[https://oceana.org/wp-content/uploads/sites/18/Why_Healthy_Oceans_Need_Sea_Turtles_0.pdf]].