1. BIODIVERSITY OF REEFS: INFERRING FROM SPARSE DATA Daphne G. Fautin Ecology & Evolutionary Biology Natural History Museum University of Kansas Photo by Mark Baine

2. to infer occurrence of members of a species in places where sampling has not been done at times in the past and future inferences are based on knowledge of the habitat of the species determining where else those habitat parameters occur precision of such an inference depends on accurate and precise knowledge of the species’ habitat detailed spatially-explicit environmental data comprehensive taxonomic and nomenclatural information such inferences can be important in understanding biogeographic consequences of climate change recognizing invasive species predicting where invasive species might persist With gratitude for grants from NSF (DEB 99-78106, OCE 00-03970, EF-0531779, NBII, the Alfred P. Sloan Foundation; and to individuals too numerous to mention other than Adorian Ardelean, Jeremy Bartley, Asif Iqbal, and Suman Kansakar

3. Distribution of the sea anemone Heteractis aurora Fautin and Allen 1992 Photo by Mark Baine

4. Distribution of the sea anemone Heteractis aurora Fautin and Allen 1992 OBIS: www.iobis.org

5. Distribution of the sea anemone Heteractis aurora Fautin and Allen 1992 OBIS: www.iobis.org Abstract; over-represents Concrete; under-represents

6. Guinotte, J. M., J. D. Bartley, A. Iqbal, D. G. Fautin, & R. W. Buddemeier. 2006. Modeling habitat distribution from organism occurrences and environmental data: a case study using anemonefishes and their sea anemone hosts Marine Ecology Progress Series 316: 269-283. [open access http://www.int- res.com/abstracts/meps/v316]

7. ASSOCIATES ORGANISM OCCURRENCES WITH ENVIRONMENTAL CONDITIONS Calculates where habitat is similar and therefore where animals of this species could occur Displays values of 52 environmental parameters (mean, sd)

8. Based on 75 published occurrence records (red spots) And the environmental parameters mean depth, mean and minimum surface seawater temperature, maximum and minimum monthly salinity Distribution of habitat suitable for Heteractis aurora

9. POTENTIAL NATURAL RANGE – where to do field work to infer occurrence of members of a species in places where sampling has not been done

10. to infer where the species might UNnaturally occur predicting where species might invade

11. allows investigation of ENVIRONMENTAL PARAMETERS that control species distribution temperature and salinity the same – no depth precision of such an inference depends on accurate and precise knowledge of the species’ habitat can be used to infer importance of habitat parameters – and possible future scenarios

12. Taxonomy and nomenclature are vital to consider in such analyses

14. using symbols of a different color for each synonymous name. Can be used for investigating whether a synonymy is justified. And occurrences of homonymous species are not mapped. MAP RECORDS OCCURRENCES OF THAT SPECIES

15. KGSMapper allows editing points – so the remainder can be analyzed

16. For the species Heteractis aurora, regardless of name used in the record For records of Heteractis aurora that used the name Radianthus koseirensis

17. Inference of probable distribution benefits from knowledge of natural history (what is relevant to the organism’s life) biogeography (where the organism would be expected) taxonomy and nomenclature (what other names might have been applied to it – and which have not) THANK YOU FOR LISTENING