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1 Electronic Atlas for All Marine Species Rainer Froese IFM-GEOMAR rfroese@ifm-geomar.de
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2 Rainer’s Project Ambitious goals: Create an online Atlas with standardized maps for eventually all marine species –Maps for 100,000 species –3-D maps (with depth) –Before-After maps –Seasonal maps –Predictive maps
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3 Rainer’s Project Assumptions: Algorithms and partners available (BiOSC, WhyWhere, Lifemapper) Enough point data available (OBIS) Suitable ‘future ocean’ data available Reality check: LifeMapper stopped mapping, GARP-maps not reproducible, can not be edited Not enough points in OBIS
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4 Point Data in OBIS 13.7 million records for 80,000 species Only ~ 22,000 species with > 10 points (11/2007)
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5 Rainer’s Project Assumptions: Algorithms and partners available (BiOSC, WhyWhere, Lifemapper) Enough point data available (OBIS) Suitable ‘future ocean’ data available Reality check: LifeMapper stopped mapping, GARP-maps not reproducible, can not be edited OBIS has points (>10) for only 22,000 species ‘Future ocean’ data problematic (modeling of primary production unsatisfactory) So???
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6 Actions More money: INCOFISH WP Biomapping ( 0.5 M$, Sven Kullander, Jonathan Ready ) More support: FishBase ( Kathy Reyes ), SealifeBase (M.D.L. Palomares), CSIRO (Tony Rees), SAUP (Kristin Kaschner, Reg Watson), Hexacorals (Daphne Fautin) Three workshops to develop, test and implement a suitable algorithm
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7 Environmental envelope type modeling approach Predictor Species-specific environmental envelope P Max Relative probability of occurrence Preferred min Preferred max MinMax Physical bathymetry sea temperature salinity ice concentration Biological primary production
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8 Depth range Pelagic (No) FAO areas Bounding box coordinates occurrence points (minimum of 10) OBIS – Ocean Biogeographic Information System (www.iobis,org)www.iobis,org GBIF – Global Biodiversity Information Facility (www.gbif.org)www.gbif.org Species and online point databases are primary sources of key minimum input data. Grey triggerfish Balistes capriscus Gmelin, 1789 Getting Minimum Information
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9 Occurrence points within bounding box or known FAO areas Bounding box or FAO area limits serve as independent verification of the validity of occurrence records. Selecting “Good Point Data”
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10 Global grid of 259,200 half degree cells Good cells are used to derive the range of environmental parameters within the species’ native range. Extracting Environmental Parameters
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11 depth from the literature range minima and maxima are derived from “good cells” preferred min = 10th percentile; preferred max = 90th percentile The environmental envelopes describe tolerances of a species with respect to each environmental parameter. Building Environmental Envelopes
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12 Predictor Preferred min Preferred max MinMax P Max Relative probability of occurrence P c = P bathymetry c x P temperature c x P salinity c x P PP c x P IceConc c The overall probability of species occurrence for a given cell is the product of the probabilities under the different environmental parameters. Predicting Probability of Occurrence
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13 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.
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14 Actions More money: INCOFISH WP Biomapping ( 0.5 M$, Sven Kullander, Johnathan Ready ) More support: FishBase ( Kathy Reyes ), SealifeBase (M.D.L. Palomares), CSIRO (Tony Rees), SAUP (Kristin Kaschner), Hexacorals (Daphne Fautin) Three workshops to develop, test and implement a suitable algorithm More data: ZIN collection, Gazetteer (Nina Bogutskaya)
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15 St. Petersburg Fish Collection 30,000 records with 15,000 coordinates from Russia
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16 Gazetteer of Type Localities 7,000 coordinates from W. Eschmeyer’s Catalogue of fishes 20,000 coordinates added by ZIN
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17 Actions More money: INCOFISH WP Biomapping ( 0.5 M$, Sven Kullander, Johnathan Ready ) More support: FishBase ( Kathy Reyes ), SealifeBase (M.D.L. Palomares), CSIRO (Tony Rees), SAUP (Kristin Kaschner), Hexacorals (Daphne Fautin) Three workshops to develop, test and implement a suitable algorithm More data: ZIN collection, Gazetteer (Nina Bogutskaya) Design map interface, start mapping Internet ExampleInternet Example
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18 www.aquamaps.org
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19 Whale Shark
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20 Latimeria chalumnae
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21 Blackfin Spiderfish (deep sea)
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22 Porbeagle (Lamna nasus)
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23 Actions More money: INCOFISH WP Biomapping ( 0.5 M$, Sven Kullander, Johnathan Ready ) More support: FishBase ( Kathy Reyes ), SealifeBase (M.D.L. Palomares), CSIRO (Tony Rees), SAUP (Kristin Kaschner), Hexacorals (Daphne Fautin) Three workshops to develop, test and implement a suitable algorithm More data: ZIN collection, Gazetteer (Nina Bogutskaya) Design map interface Internet ExampleInternetExample Start mass-production of maps Do cross-species maps
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24 Species Richness of 7,237 Species (of 230,000)
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26 Species Richness of Sharks & Rays Including 437 maps of altogether 968 sharks & rays (45%)
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27 Species Richness Merlucciidae
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28 Mean Trophic Level of Merlucciidae
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29 Atlantic Deep Lobster
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30 Seasonal distribution of Mola mola
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31 Before – After Map
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32 Foto R. Freitas Modelled effects of climate change from 2000 to 2050 on the suitable habitat for Bogue (Boops boops) Move north! Predictive Map by Jonathan Ready
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33 Next Steps Involve OBIS (CoML), GBIF, EoL –10-12 December 2007 4th Mapping workshop in Kiel, on mass-production of maps Find more funding –European SpeciesBase initiative Write 10,000 Maps paper in 2007 Go freshwater –NRM Stockholm Go terrestrial –SMNS Stuttgart
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34 Thanks to the Pew Fellows Program for making this possible
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