1. 1 Electronic Atlas for All Marine Species Rainer Froese IFM-GEOMAR rfroese@ifm-geomar.de

2. 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

3. 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

4. 4 Point Data in OBIS 13.7 million records for 80,000 species Only ~ 22,000 species with > 10 points (11/2007)

5. 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???

6. 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

7. 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

8. 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

9. 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”

10. 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

11. 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

12. 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

13. 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.

14. 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)

15. 15 St. Petersburg Fish Collection 30,000 records with 15,000 coordinates from Russia

16. 16 Gazetteer of Type Localities 7,000 coordinates from W. Eschmeyer’s Catalogue of fishes 20,000 coordinates added by ZIN

17. 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

18. 18 www.aquamaps.org

19. 19 Whale Shark

20. 20 Latimeria chalumnae

21. 21 Blackfin Spiderfish (deep sea)

22. 22 Porbeagle (Lamna nasus)

23. 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

24. 24 Species Richness of 7,237 Species (of 230,000)

25. 25

26. 26 Species Richness of Sharks & Rays Including 437 maps of altogether 968 sharks & rays (45%)

27. 27 Species Richness Merlucciidae

28. 28 Mean Trophic Level of Merlucciidae

29. 29 Atlantic Deep Lobster

30. 30 Seasonal distribution of Mola mola

31. 31 Before – After Map

32. 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

33. 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

34. 34 Thanks to the Pew Fellows Program for making this possible