COS 96-6
Turnover in functional diversity of avian assemblages across continental scales: Accounting for imperfect detection in the estimates of biodiversity change

Thursday, August 13, 2015: 9:50 AM
302, Baltimore Convention Center
Marta A. Jarzyna, Ecology and Evolutionary Biology, Yale University, New Haven, CT
Walter Jetz, Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT

Estimates of functional diversity can provide insights into the mechanisms controlling the structure and dynamics of biological communities and are of key interest to ecology. Traditional metrics of functional diversity generally assume perfect detectability and do not account for species that might have gone undetected during the survey event. Failure to account for imperfect detection, however, might result in flawed estimates of community functional diversity, ultimately hindering biodiversity conservation efforts. Our goal was to incorporate imperfect detection into the estimates of community functional diversity (CFD) of avian assemblages and quantify temporal changes in CFD over the past five decades. We used Breeding Bird Survey as our model dataset. To evaluate CFD, we quantified the multivariate trait dissimilarity between all species in a community. To account for imperfect detection resulting from survey-, site-, and species-level factors, we used hierarchical multi-species occupancy models (MSOMs). The estimated true probability of occurrence of each species resulting from the MSOMs was then incorporated into the estimates of CFD.


We found that functionally-distinct species tend to be especially underrepresented in the traditional estimates of functional diversity. We also found that accounting for imperfect detection increases estimates of functional diversity. Furthermore, we show that functional diversity of avian communities increased over the past five decades, presumably as a response to climatic changes. We conclude that future work regarding different attributes of community structure needs to explicitly integrate factors affecting species detectability if we are to accurately quantify the impacts of global change on biodiversity.