Caribbean Fish Hotpots (Southeast Blueprint Indicator)

Reason for Selection Nearshore waters where mangroves, seagrass, and coral are all present and within close proximity to one another are likely to support higher densities and diversity of fish species (Pittman et al. 2007). The co-occurrence of these three habitats supports healthy coastal ecosystems and connected seascapes (Gillis et al. 2017). While the movement and dispersal patterns for different fish species can vary widely, mangroves, seagrass, and coral provide key ecological services and functions for many species. For example, mangroves and seagrass beds serve as important nursery habitats, especially for fish species that, as adults, also depend on coral reefs (Nagelkerken et. al 2001). Many fish species, like mangrove snapper and yellowtail snapper, move through all three habitat types within their home ranges (Pittman et al. 2007). The 300 m and 600 m distance thresholds used in this indicator draw on personal communication with Dr. Simon Pittman (1-25-2023) and several studies examining seascape structure and the number and diversity of fish species present at different distances from various habitat types. Research in southwest Puerto Rico shows that the positive impact of co-occurring mangrove, seagrass, and coral reef habitat on fish abundance is species-specific and strongest at 100 m but ranges between 50 and 600 m (Pittman et al. 2007). In a decision support framework developed for the U.S. Virgin Islands, “coral reefs were deemed strongly connected where they existed within 300 m of seagrasses, mangroves and other reefs” (Pittman et al. 2018). These findings align with research in Australia and the western Pacific that considered habitats within 250-500 m of one another to be highly connected (Olds et al. 2012; Martin et al. 205), and a study in the United Arab Emirates that used a 500 m buffer to prioritize relationships between mangrove, seagrass, and reefs (Pittman et al. 2022). Input Data * The Nature Conservancy’s (TNC) [Caribbean benthic habitat maps]; [read a press release about the data]; [read a scientific journal article about the data]; [request to download the data] * 2012 [National Oceanic and Atmospheric Administration (NOAA) Coastal Change Analysis Program (C-CAP) land cover files for the U.S. Virgin Islands] (St. Thomas, St. John, and St. Croix are provided as separate rasters) accessed 4-26-2022; learn more about [C-CAP high resolution land cover and change products] * 2010 [NOAA C-CAP land cover files for Puerto Rico], accessed 4-26-2022; learn more about [C-CAP high resolution land cover and change products] * [Southeast Blueprint 2023 subregions]: Caribbean * [Southeast Blueprint 2023 extent] Mapping Steps * Mosaic the benthic data for Puerto Rico and the U.S. Virgin Islands. * Mosaic the C-CAP landcover data for Puerto Rico and the U.S. Virgin Islands. * Reproject and do a majority resample of the TNC benthic data to 30 m pixels. * Reproject and do a majority resample of the C-CAP data to 30 m pixels. * Create a seagrass raster by reclassifying the TNC benthic data so that “dense seagrass” is 1, all other data is 0, and NoData is 1,000. The NoData value helps later in the analysis to remove land and deal with differences in NoData between the C-CAP and TNC benthic data. * Create a coral raster by reclassifying the TNC benthic data so that “Reef Crest”, “Fore Reef”, “Back Reef”, “Coral/Algae”, and “Spur and Groove Reef” are 1, all other classes are 0, and NoData is 0. * Create a mangrove raster by reclassifying the C-CAP data so that “Estuarine forested wetland” is 1, all other classes are 0, and NoData is 0. * Combine the mangrove and seagrass data to make a water mask to remove land (including mangroves) from the final indicator. * 600 m analysis: For each habitat raster (mangrove, seagrass, and coral), use a 20 cell radius circle and maximum in focal statistics to identify areas with at least one pixel of those habitats. Sum these rasters together and multiply by the presence of mangrove (0/1) to get habitat diversity. This step calculates how many of the distinct habitat types occur within a 600 m radius. It also removes the actual mangrove pixels, as this indicator targets the estuarine and marine habitats near mangroves. * 300 m analysis: Repeat the same steps from the 600 m analysis but use a 10 cell radius. * Combine the 600 m analysis and 300 m analysis to get final indicator classes. * Clip to the Caribbean Blueprint 2023 subregion. * 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 2025 Data Download] or [Caribbean-only Southeast Blueprint 2025 Data Download] under > 6_Code. Final indicator values Indicator values are assigned as follows: 4 = Highest predicted fish density/diversity (mangrove, coral, and dense seagrass all present within 300 m) 3 = Very high predicted fish density/diversity (either mangrove and coral, mangrove and dense seagrass, or coral and dense seagrass present within 300 m) 2 = High predicted fish density/diversity (mangrove, coral, and dense seagrass all present within 600 m) 1 = Medium predicted fish density/diversity (either mangrove and coral, mangrove and dense seagrass, or coral and dense seagrass present within 600 m) 0 = Low predicted fish density/diversity (no coral, mangrove, or dense seagrass present within 600 m of one other) Known Issues * For some pixels at the edge of the Caribbean subregion, less than half of the 30 m pixel is covered by the finer resolution TNC benthic data. These cells are classified as NoData in the indicator. * The distances used in this indicator are primarily based on a study conducted in southwest Puerto Rico (Pittman et al. 2007), a decision support framework developed for the U.S. Virgin Islands, and personal communication with the principal investigator of those projects, Dr. Simon Pittman (1-25-2023). While other similar studies in Australia, the western Pacific, and the United Arab Emirates support the distance thresholds chosen for this analysis (Olds et al. 2012, Martin et al. 2015, Pittman et al. 2022), different distances may be more appropriate for other parts of the U.S. Caribbean. * This indicator may overestimate the fish habitat value of some terrestrial areas that were evaluated by the TNC benthic habitat dataset (e.g., areas near Limetree Bay Refinery in the southern part of St. Croix, USVI). 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 Gillis, L. G., Jones, C. G., Ziegler, A. D., van der Wal, D., Breckwoldt, A., and Bouma, T. J. 2017. Opportunities for protecting and restoring tropical coastal ecosystems by utilizing a physical connectivity approach. Front. Marine Sci. 4:374. [[https://www.frontiersin.org/articles/10.3389/fmars.2017.00374/full]]. Martin TSH, Olds AD, Pitt KA, Johnston AB, Butler IR, Maxwell PS, Connolly RM. 2015. Effective protection of fish on inshore coral reefs depends on the scale of mangrove-reef connectivity. Mar Ecol Prog Ser 527:157-165. [[https://doi.org/10.3354/meps11295]]. Nagelkerken, Ivan & Kleijnen, Sarah & Klop, T & Brand, RACJ & Morinière, EC & Van der Velde, Gerard. (2001). Dependence of Caribbean reef fishes on mangroves and seagrass beds as nursery habitats: A comparison of fish faunas between bays with and without mangroves/seagrass beds. Marine Ecology-progress Series - MAR ECOL-PROGR SER. 214. 225-235. 10.3354/meps214225. [[https://www.int-res.com/articles/meps/214/m214p225.pdf]]. Olds, AD, Connolly, RM, Pitt, KA., Maxwell, PS. (2012). Habitat connectivity improves reserve performance. Conservation Letters 5: 56–63. [[https://conbio.onlinelibrary.wiley.com/doi/10.1111/j.1755-263X.2011.00204.x]]. Pittman SJ, Caldow C, Hile SD, Monaco ME. 2007. Using seascape types to explain the spatial patterns of fish in the mangroves of SW Puerto Rico. Marine Ecology Progress Series. Vol. 348: 273–284. [[https://doi.org/10.3354/meps07052]]. Pittman, S.J., Poti, M., Jeffrey, C.F., Kracker, L.M. and Mabrouk, A., 2018. Decision support framework for the prioritization of coral reefs in the US Virgin Islands. Ecological Informatics, 47, pp.26-34. [[https://www.sciencedirect.com/science/article/abs/pii/S1574954117300614]]. Pittman, S.J. et al 2022. Rapid site selection to prioritize coastal seascapes for nature-based solutions with multiple benefits. Frontiers in Marine Science, 9, p.571. [[https://www.frontiersin.org/articles/10.3389/fmars.2022.832480/full]]. Schill SR, McNulty VP, Pollock FJ, Lüthje F, Li J, Knapp DE, Kington JD, McDonald T, Raber GT, Escovar-Fadul X, Asner GP. Regional High-Resolution Benthic Habitat Data from Planet Dove Imagery for Conservation Decision-Making and Marine Planning. Remote Sensing. 2021; 13(21):4215. [[https://doi.org/10.3390/rs13214215]].