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PREDICTING AND UNDERSTANDING BIOGEOGRAPHIC RANGES FROM OCCURRENCE RECORDS AND CORRELATED ENVIRONMENTAL DATA J. M. Guinottte, J. D. Bartley, A. Iqbal, D.

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Presentation on theme: "PREDICTING AND UNDERSTANDING BIOGEOGRAPHIC RANGES FROM OCCURRENCE RECORDS AND CORRELATED ENVIRONMENTAL DATA J. M. Guinottte, J. D. Bartley, A. Iqbal, D."— Presentation transcript:

1 PREDICTING AND UNDERSTANDING BIOGEOGRAPHIC RANGES FROM OCCURRENCE RECORDS AND CORRELATED ENVIRONMENTAL DATA J. M. Guinottte, J. D. Bartley, A. Iqbal, D. G. Fautin, R. W. Buddemeier University of Kansas: Kansas Geological Survey, Department of Ecology and Evolutionary Biology, and Biodiversity Research Center

2 PREDICTING AND UNDERSTANDING BIOGEOGRAPHIC RANGES, HABITATS, AND NICHES FROM OCCURRENCE RECORDS AND CORRELATED ENVIRONMENTAL DATA National Science Foundation grants OCE 00-03970 (NOPP), DEB95-21819 (PEET), DEB 99-78106 (PEET) Land-Ocean Interactions in the Coastal Zone (LOICZ, an IGBP project)

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7 but occurrence records are sparse – typical of marine organisms of little or no commercial value

8 Macrodactyla doreensis – sparse distributional data Point occurrences and generalized range maps data convey very different impressions and types of information. How should the range polygon be drawn?

9 Occurrence records use symbols of a different color for each synonymous name -- can be used for investigating whether a synonymy is justified. MAPPINGSPECIESOCCURRENCES SUMMARIZES KNOWN RANGE OF SPECIES

10 To infer where else animals of this species may occur

11 ASSOCIATESORGANISMOCCURRENCESWITHENVIRONMENTALCONDITIONS ANALYSED STATISTICALLY

12 maximum and minimum SST and minimum depth SUMMARIZES DISTRIBUTION OF HABITAT MATCHING THAT OF PLACES WHERE SPECIES OCCURS

13 maximum and minimum SST, maximum and minimum salinity ALLOWS INVESTIGATION OF ENVIRONMENTAL PARAMETERS THAT CONTROL SPECIES DISTRIBUTION

14 to predict where else the species might occur

15 to predict where else the species might NATURALLY occur POTENTIAL NATURAL RANGE

16 to predict where the species might UNnaturally occur POTENTIAL INVASIVE RANGE

17 “Is there are any way of assessing such predictions??” The lionfish, Pterois volitans (from FishBase)

18 using max and min SST and min depth

19 only environmental correlates of occurrences NICHE Is not just habitat – it includes biotic attributes that control occurrence In addition to distribution of anemones and environmental parameters, anemonefishes (FishBase)

20 CLOSER TO TRULY ILLUSTRATING THE DISTRIBUTION OF THE NICHE Fishes predict anemones = 95% Anemones predict fishes = 100%

21 = NICHE ?

22 RANGES, HABITATS, AND NICHES

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