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AquaMaps: An Overview Kathleen Kesner-Reyes, Eli E. Agbayani, Rainer Froese, Jonathan Ready, Ma. Josephine France R. Barile and Kristin Kaschner FishBase Project-The WorldFish Center, Leibniz-Institut für Meereswissenschaften -GEOMAR, Swedish Museum of Natural History, Sea Around Us Project-University of British Columbia What are AquaMaps? • Model-based, large-scale predictions of known natural occurrence of marine species • Originally developed by Kaschner et al. (2006) to predict global distributions of marine mammals • Uses estimates of environmental tolerances of a given species with respect to a set environmental parameters • Predictions made by matching species tolerances (environmental envelope) against local environmental conditions to determine suitability of a geographical area for a given species • Color-coded species range map showing relative likelihood of species occurrence in a global grid of half-degree latitude and longitude dimensions • Supplements existing occurrence data with independent knowledge about species distribution and habitat usage to correct for biases in species occurrence records. Environmental envelope type modeling approach Physical • bathymetry • sea temperature • salinity • land distance • ice concentration Species-specific environmental envelope Relative probability of occurrence PMax Biological • primary production Predictor Min Preferred min Preferred max Max How does AquaMaps work? Getting Minimum Information Grey triggerfish Balistes capriscus Gmelin, 1789 Depth range Pelagic? FAO areas Bounding box coordinates occurrence points (minimum of 10) OBIS – Ocean Biogeographic Information System (www.iobis,org) GBIF – Global Biodiversity Information Facility (www.gbif.org) Species and online point databases are primary sources of key minimum input data. Selecting “Good Cells” • “good cells” - within bounding box or known FAO areas • minimum of 10 “good cells” for needed for extracting parameters Bounding box or FAO area limits serve as independent verification of the validity of occurrence records. Extracting Environmental Parameters Global grid of 259,200 half degree cells Good cells are used to derive the range of environmental parameters within the species’ native range. Building Environmental Envelopes • Depth ranges: typically from literature; depth estimate based on habitat description • Min = 25th percentile - 1.5 * interquartile or absolute minimum in extracted data (whichever is lesser) Max = 75th percentile + 1.5 * interquartile or absolute maximum in extracted data (whichever is greater) PrefMin = 10th percentile of observed variation in an environmental parameter PrefMax = 90th percentile of observed variation in an environmental parameter • Surface values for species with min depth ≤ 200m Bottom values for species with min depth > 200m The environmental envelopes describe tolerances of a species with respect to each environmental parameter. Predicting Probability of Occurrence Relative probability of occurrence PMax Predictor Min Preferred min Preferred max Max Pc = Pbathymetryc x PSSTc x Psalinityc x Pchl ac x PIceDistc x PLandDistc Probabilities of species occurrence are generated by matching the species environmental envelope against local environmental conditions to determine relative suitability of a given area. Plotting Species AquaMaps Predictions document large-scale and long-term presence of a species. They cannot be assumed to precisely represent local occurrence of a species on a specific day of a specific year. Balistes capriscus All suitable habitat Point data Collaborators FishBase RFroese, NBailly, SRius, KReyes, EAgbayani, NGarilao FishBase, compiling of tables, implementation of prototype for fish KGS Mapper JBartley Environmental data C-square Mapper TReese Editing tools SAUP/SAUP Mapper DPauly, VChristensen, RWatson Environmental data, editing, future user VLIZ/MARBEF EVBerghe Mapping, editing tools NRM Mapper SKullander Point data, extension to freshwater fishes, future user JReady WhaleBase KKaschner OBIS Technical Team PZStocks, DFautin KGS/LOICZ BBuddemeier SeaLifeBase MLPalomares, KTabaranza, LPaglinawan, PSorongon CRIA D4Science GBIF Half-degree cell maps for marine mammals, programming, data exploration SeaLifeBase, extension to other non-fish marine metazoans www.aquamaps.org Kaschner, K., J. S. Ready, E. Agbayani, J. Rius, K. Kesner-Reyes, P. D. Eastwood, A. B. South, S. O. Kullander, T. Rees, C. H. Close, R. Watson, D. Pauly, and R. Froese. 2008 AquaMaps: Predicted range maps for aquatic species. World wide web electronic publication, www.aquamaps.org, Version MM/YYYY.
