Evol Ecol Res 9: 1329-1347 (2007)     Full PDF if your library subscribes.

Effects of population-level aggregation, autocorrelation, and interspecific association on the species–time relationship in two desert communities

Ethan P. White1,2* and Michael A. Gilchrist3

1Department of Biology, Utah State University, Logan, UT 84322,  2Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ 85721, and  3Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN 37996, USA

Address all correspondence to E.P. White, Department of Biology, Utah State University, Logan, UT 84322, USA.
e-mail: epwhite@biology.usu.edu

ABSTRACT

Question: Can population-level patterns be used to model the species–time relationship? Which non-random patterns in population time-series are necessary for modelling the species–time relationship?

Statistical modelling methods: The presence of aggregation, autocorrelation, and interspecific association was determined using Morisita’s IM, Moran’s I, and Ive’s C respectively. Models for the species–time relationship were constructed from these sub-patterns using a combination of analytical models and randomization methods.

Data studied: Observational time-series of rodents and annual plants in the Chihuahuan Desert.

Conclusions: Aggregation was observed in the majority of population time-series. Most rodent species, but fewer than 10% of plant species, exhibited significant temporal autocorrelation in abundance. Models that included temporal autocorrelation as well as aggregation provided the best fit to the species–time relationship. The species–time relationship is intimately connected to the population dynamics of individual species. Models that attempt to connect the apparently general behaviour of the species–time relationship to the complex dynamics of populations are important for understanding the dynamics of ecological communities.

Keywords: aggregation, species–area relationship, species–time relationship, temporal autocorrelation, temporal turnover.

DOWNLOAD A FREE, FULL PDF COPY
IF you are connected using the IP of a subscribing institution (library, laboratory, etc.)
or through its VPN.

 

        © 2007 Ethan P. White. All EER articles are copyrighted by their authors. All authors endorse, permit and license Evolutionary Ecology Ltd. to grant its subscribing institutions/libraries the copying privileges specified below without additional consideration or payment to them or to Evolutionary Ecology, Ltd. These endorsements, in writing, are on file in the office of Evolutionary Ecology, Ltd. Consult authors for permission to use any portion of their work in derivative works, compilations or to distribute their work in any commercial manner.

       Subscribing institutions/libraries may grant individuals the privilege of making a single copy of an EER article for non-commercial educational or non-commercial research purposes. Subscribing institutions/libraries may also use articles for non-commercial educational purposes by making any number of copies for course packs or course reserve collections. Subscribing institutions/libraries may also loan single copies of articles to non-commercial libraries for educational purposes.

       All copies of abstracts and articles must preserve their copyright notice without modification.