Atlantic Marine Mammals (Southeast Blueprint Indicator)

Reason for Selection Marine mammals help identify key areas of ocean productivity and overall ocean health, 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 high trophic levels, and large blubber stores that can serve as repositories for anthropogenic chemicals and toxins (Bossart 2011). This indicator complements the Atlantic marine birds indicator by identifying important habitats in areas too deep for marine birds to reach. Input Data * [Southeast Blueprint 2023 extent] * [2019 National Land Cover Database] (NLCD): Land cover * [Habitat-based Marine Mammal Density Models for the U.S. Atlantic] (last updated 6-20-2022), accessed 12-12-2023 These models use aggregated survey information, distance-sampling, and oceanographic variables to predict cetacean density throughout the region. We used data for all available species with the exception of blue whale, common minke whale, false killer whale, Fraser’s dolphin, killer whale, melon-headed whale, Northern bottlenose whale, pygmy killer whale, sei whale, spinner dolphin, and white-beaked dolphin. Those species had significant spatial problems in the Southeast. The indicator used monthly predictions for 11 species: Atlantic spotted dolphin, Atlantic white-sided dolphin, common bottlenose dolphin, fin whale, harbor porpoise, humpback whale (2009-2019), North Atlantic right whale (2003-2019), Risso’s dolphin, seals, short-beaked common dolphin, and sperm whale. It used yearly predictions for 9 rarer species/species groups: Clymene dolphin, Cuvier’s beaked whale, dwarf and pygmy sperm whales, mesoplodont beaked whales, pantropical spotted dolphin, pilot whales, rough-toothed dolphin, striped dolphin, and unidentified beaked whales. Mapping Steps * To identify important areas for each species, use the core area algorithm (CAZMAX) in Zonation 5. Include each monthly density layer for each marine mammal species 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 source data to Albers Equal Area. * Resample to a 30 m cell size using the nearest neighbor method (the source data is 5 km by 5 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 from 1-10 based on increments of 10. * Add in a zero class for land by reclassifying 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 mammal 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 * While this layer has a 30 m resolution, the source data was coarser than that. We downsampled 5 km pixels to 30 m. * There are a small number of pixels on the eastern edge of the Atlantic marine subregion just south of 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 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]]. 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]]. Roberts, J., Best, B., Mannocci, L. et al. Habitat-based cetacean density models for the U.S. Atlantic and Gulf of Mexico. Sci Rep 6, 22615 (2016). [[https://doi.org/10.1038/srep22615]]. Roberts JJ, Yack TM, Halpin PN (2023) Marine mammal density models for the U.S. Navy Atlantic Fleet Training and Testing (AFTT) study area for the Phase IV Navy Marine Species Density Database (NMSDD). Document version 1.3. Report prepared for Naval Facilities Engineering Systems Command, Atlantic by the Duke University Marine Geospatial Ecology Lab, Durham, NC. [[https://seamap.env.duke.edu/seamap-models-files/Duke/Reports/AFTT_Marine_Mammal_Density_Models_2022_v1.3.pdf]].