SOFIA - A new parameterization for estimating co-occurrence of interacting species

A new parameterization for estimating co-occurrence of interacting species

Citation: Waddle, J. Hardin, Robert M. Dorazio, Susan C. Walls, Kenneth G. Rice, Jeff Beauchamp, Melinda J. Schuman, and Frank J. Mazzotti. 2010. A new parameterization for estimating co-occurrence of interacting species. Ecological Applications 20:1467–1475.

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J. Hardin Waddle,^1,6 Robert M. Dorazio,^2,3 Susan C. Walls,³ Kenneth G. Rice,³ Jeff Beauchamp,⁴ Melinda J. Schuman,⁵ and Frank J. Mazzotti⁴

¹U.S. Geological Survey, National Wetlands Research Center, Lafayette, Louisiana 70506 USA
²University of Florida, Department of Statistics, Gainesville, Florida 32611 USA
³U.S. Geological Survey, Southeast Ecological Science Center, Gainesville, Florida 32653 USA
⁴University of Florida, Fort Lauderdale Research and Educational Center, Davie, Florida 33314 USA
⁵Conservancy of Southwest Florida, Naples, Florida 34102 USA

Abstract. Models currently used to estimate patterns of species co-occurrence while accounting for errors in detection of species can be difficult to fit when the effects of covariates on species occurrence probabilities are included. The source of the estimation problems is the particular parameterization used to specify species co-occurrence probability. We develop a new parameterization for estimating patterns of co-occurrence of interacting species that allows the effects of covariates to be specified quite naturally without estimation problems. In our model, the occurrence of one species is assumed to depend on the occurrence of another, but the occurrence of the second species is not assumed to depend on the presence of the first species. This pattern of co-occurrence, wherein one species is dominant and the other is subordinate, can be produced by several types of ecological interactions (predator–prey, parasitism, and so on).

A simulation study demonstrated that estimates of species occurrence probabilities were unbiased in samples of 50–100 locations and three surveys per location, provided species are easily detected (probability of detection ≥0.5). Higher sample sizes (>200 locations) are needed to achieve unbiasedness when species are more difficult to detect. An analysis of data from treefrog surveys in southern Florida indicated that the occurrence of Cuban treefrogs, an invasive predator species, was highest near the point of its introduction and declined with distance from that location. Sites occupied by Cuban treefrogs were 9.0 times less likely to contain green treefrogs and 15.7 times less likely to contain squirrel treefrogs compared to sites without Cuban treefrogs. The detection probabilities of native treefrog species did not depend on the presence of Cuban treefrogs, suggesting that the native treefrog species are naive to the introduced species.