Statistical biodiversity:  analyses of carrion-feeding insects as a function of local weather and stage of decomposition

Monday, November 11, 2013
Exhibit Hall 4 (Austin Convention Center)
Michelle L. Lewis , Department of Biological Sciences, Sam Houston State University, Huntsville, TX
Natalie K. Lindgren , Department of Biological Sciences, Sam Houston State University, Huntsville, TX
Sibyl, R. Bucheli , Department of Biological Sciences, Sam Houston State University, Huntsville, TX
Species diversity is an ecological function of how many different species exist in a given ecosystem at a specific place and time and is affected by several different environmental factors.   By treating a cadaver like a small scale ecosystem, we tested our primary hypothesis that seasonal and climatic changes, as well as characteristics of a cadaver’s decompositional scoring, alter the biodiversity of significant carrion flies and beetles.  Insect succession was shown to be all inclusive in early decomposition with the gradual exiting of more specialized forensic species, with a shift from flies to beetles.  Individual and combined probabilities of fly and beetle taxa were calculated according to a continuous decomposition index based on accumulated degree-days that can be used to predict the minimum postmortem interval of an unknown cadaver.  Shifts in insect occurrence probabilities varied throughout decomposition that display different strategies in the exploitation of a resource, with Calliphoridae and Cleridae showing the highest probability of occurrence for early and late decomposition respectively.  We are exploring the best model through the use of regression, generalized estimating equations, and mixed multilevel modeling in order to most accurately predict accumulated degree-days of a cadaver.  The decomposition models are implemented into an interactive program that we developed to allow accurate estimatation of the postmortem interval by accounting for significant abiotic and biotic factors known to alter the rate of decomposition.  The program enables a deeper understanding of the decomposition process and provides less user error for prediction through implementation of dropdown menus.