U.S. Fish & Wildlife ServiceReason for Selection Highly migratory fish species travel long distances and often cross domestic and international boundaries (NOAA Fisheries). They are often the focus of sport and commercial fishing, and the management of their populations can have far-reaching impacts. As top predators in the marine food chain, highly migratory fish are good indicators for areas of high ocean productivity. In particular, sharks and tunas play an important role in marine food webs by helping regulate populations of lower-level predators that, if left unchecked, could compromise the integrity of marine ecosystems across the Gulf and Atlantic (Baum 2009).In effect, the places where these species feed and spawn are also important for other types of marine life. Input Data Southeast Blueprint 2023 extent Southeast Blueprint 2023 subregions : Marine (combined Atlantic & Gulf of America) European Commission global fish models, accessed 6-14-2023: Bluefin tuna ( adult feeding , adult spawning , juvenile feeding ), skipjack tuna ( adult feeding ), blue shark ( adult female foraging, adult male foraging, large juvenile female foraging, large juvenile male foraging, small juvenile foraging ) Note: While these data are global in scope, they use large amounts of data from U.S. Atlantic and Gulf waters and include a spawning model specific to the Gulf of America. Mapping Steps Clip all global input data to the Southeast Blueprint 2023 marine subregion. Reproject the blue shark data to match the tuna data. Use the Southeast Blueprint 2023 marine subregion to make a Zonation mask for tuna and blue shark. The species data are global, and we wanted to limit the analysis just to the Southeast Blueprint marine subregion. To identify important areas for tunas and blue shark, use the core area algorithm (CAZMAX) in Zonation 5. For bluefin and skipjack tuna, include each monthly density layer for each tuna species and life stage for 2015, 2016, and 2017 and weight them equally. For blue shark, include each monthly density layer for each life stage for 2015, 2016, and 2017 and weight them equally. We did two separate runs, one for tunas and one for blue shark, due to differences in the input datasets. We chose 2015-2017 so we had matching years across the species and focused on more recent conditions to reduce the overall impact of climate change on the estimates. Reproject the Zonation results to Albers Equal Area and resample to 30 m pixels. Convert the tuna and blue shark layers from floating point rasters with a range of 0-1 to integer rasters ranging from 0-100. Reclassify each raster to produce the indicator values seen below so that 0-30 is 1, 31-40 is 2, 41-50 is 3, 51-60 is 4, 61-70 is 5, 71-80 is 6, 81-90 is 7, and 91-100 is 8. The variation in values from Zonation below 30 was less helpful than the other higher classes so we classified all values from 30 and below as 1. This was primarily due to large low probability areas for tuna in part of the Atlantic that all had the same low value. Combine the reclassified tuna and blue shark rasters into a single indicator by using the maximum value in CellStatistics. 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: 8 = >90th percentile of importance for bluefin and skipjack tuna or blue shark 7 = >80th-90th percentile of importance 6 = >70th-80th percentile of importance 5 = >60th-70th percentile of importance 4 = >50th-60th percentile of importance 3 = >40th-50th percentile of importance 2 = >30th-40th percentile of importance 1 = ≤30th percentile of importance Known Issues While this layer has a 30 m resolution, the source data was coarser than that. We downsampled1/24° pixels (~4 km)to 30 m. This indicator doesn't fully represent the specialized habitat requirements of other highly migratory fish not used in the indicator. The indicator focuses on highly productive currents and eddies. While these are important for many highly migratory species, especially for feeding, this approach likely misses important areas for some species. Other Things to Keep in Mind We weren't able to run all the tuna and blue shark data together in Zonation, so we ran them separately and took the maximum value of the two resulting outputs. 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 underlying tunas run and shark run and are then combined. While these are global models, we did the Zonation run just within the Blueprint marine subregion. We could explore running them over a larger ecological region in the future. For this year, given we were already running into processing challenges and didn't have an alternative subglobal subregion in mind for these species, we stuck with the Blueprint marine subregion. 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 Baum, J.K., and B. Worm, "Cascading top-down effects of changing oceanic predator abundances," Journal of Animal Ecology, 78: 699-714 (2009), p. 11. [ https://besjournals.onlinelibrary.wiley.com/doi/10.1111/j.1365-2656.2009.01531.x ]. European Commission, Joint Research Centre (JRC) (2022): Foraging habitat of blue shark (Prionace glauca) - Global Ocean MONTHLY - 2003-2018 (% of daily favorable occurrence, 1/24° by 1/24°). European Commission, Joint Research Centre (JRC) [Dataset] PID: [ https://data.europa.eu/89h/6062ddae-2478-409a-89bf-8121902dc70e ]. Druon, Jean-Noel (2019): GMIS - Favourable feeding habitat of skipjack tuna (SKJT) Monthly 1998-2017 (frequency of occurrence, %). European Commission, Joint Research Centre (JRC) [Dataset] PID: [ https://data.europa.eu/89h/98b2254b-aca4-4f0b-9777-4814d1e635ad ]. Druon, Jean-Noel (2019): GMIS - Favourable feeding habitat of adult Atlantic bluefin tuna (ABFT) Monthly 1998-2017 (frequency of occurrence, %). European Commission, Joint Research Centre (JRC) [Dataset] PID: [ https://data.europa.eu/89h/60a0a5b0-b63c-473f-b8bc-207ea037eb3b ]. Druon, Jean-Noel (2019): GMIS - Favourable feeding habitat of juvenile Atlantic bluefin tuna (ABFT) Monthly 2003-2017 (frequency of occurrence, %). European Commission, Joint Research Centre (JRC) [Dataset] PID: [ https://data.europa.eu/89h/8f566919-c88f-4c2d-84dc-7862800d5385 ]. Druon, Jean-Noel (2019): GMIS - Favourable spawning habitat of adult Atlantic bluefin tuna (ABFT) Monthly 1998-2017 (frequency of occurrence, %). European Commission, Joint Research Centre (JRC) [Dataset] PID: [ https://data.europa.eu/89h/a60cc972-2a78-461b-b8bd-9aae008e9c03 ]. NOAA Fisheries: National Oceanic and Atmospheric Administration - Highly Migratory Species. Accessed June 16, 2023. PID: [ https://www.fisheries.noaa.gov/highly-migratory-species ].ArcGIS ImageMapLayerhttps://hub.arcgis.com/datasets/8d893f24147a47f7bb48f8071c2d3a6aengU.S. Fish and Wildlife Service Open DataPublicMarine Highly Migratory Fish (Southeast Blueprint Indicator) [United States]Web servicesUnited StatesLast Modified: 2025-12-04