Gulf Marine Mammals (Southeast Blueprint Indicator)

Reason for Selection Marine mammals help identify key areas of ocean productivity and overall ocean health in the Gulf of America, are regularly monitored, and resonate with a variety of audiences. Marine mammals are often used as ocean health indicators due to their long lifespans, feeding at a high trophic levels, and large blubber stores that can serve as repositories for anthropogenic chemicals and toxins (Bossart 2011). Input Data * Gulf of Mexico Marine Assessment Program for Protected Species (GoMMAPPS): [GoMMAPPS marine mammal spatial density model outputs] (version 2.2), accessed 12-14-2022 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 National Oceanic and Atmospheric Administration (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). * [2019 National Land Cover Database] (NLCD): Land cover * [Southeast Blueprint 2023 subregions]: Marine (combined Atlantic & Gulf of America) * [Southeast Blueprint 2023 extent] Mapping Steps * Replace all values of -9999 with 0. * Convert to monthly rasters for each species/species group 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”. The pygmy/dwarf sperm whale model only includes data for April through November. The rest of the species/species group models include data for all months. Use the Southeast Blueprint 2023 marine subregion for pixel size and snap. * Use the beaked whale data and the NLCD to create a mask to define the extent of the Zonation analysis. The beaked whale data represents the full sample area for the other species in GoMMAPPS. The area covered by the marine mammal 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 of11 in the NLCD) within the extent of the NLCD. The resulting Zonation maskcovers open water areas where there is both modeled data for marine mammals and NLCD data to remove land. * To identify important areas for each species, use the core area algorithm (CAZMAX) in Zonation 5. First, include all species but do separate runs by season: Spring (Mar, Apr, May), Summer (Jun, Jul, Aug), Fall (Sep, Oct, Nov), and Winter (Dec, Jan, Feb). We did this for two reasons: 1) Some conservation decisions in the marine environmental are seasonal and 2) Computational limitations prevented a full run for all species and months. Then do a final Zonation run with the seasonal results as inputs. This creates a single layer that accounts for different species and monthly variation while also producing seasonal intermediary products to help with specific marine decisions. * Reproject the Zonation results 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 values of 1-10 based on increments of 10 to produce the indicator values seen below. * 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: 10 = >90th percentile of importance for marine mammal index species (across larger analysis 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 * While this layer has a 30 m resolution, the source data was coarser than that. We downsampled hexagons with an area of 40 sq km to 30 m pixels. * The indicator may underrepresent striped dolphin habitat. While model results are available for this species, there were processing issues that prevented the use of models for this species in the indicator. Other Things to Keep in Mind * We ran the Zonation analysis across open water areas where there were both marine mammal 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 marine boundary. 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 Bossart, G. D. “Marine Mammals as Sentinel Species for Oceans and Human Health.” Veterinary Pathology Online 48, no. 3 (May 1, 2011): 676–90. [[https://doi.org/10.1177/0300985810388525]]. 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. 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]].