Global patterns of species richness: spatial models for conservation planning using bioindicator and precipitation data

Article Abstract:

Spatial statistical analysis techniques can be used to suggest biological diversity, especially when correlated with precipitation data. Different territories yielded varying results. Numbers of tiger beetle species can suggest numbers of butterfly species in North America and numbers of bird species in India, but this model does not apply to Australia. Mean annual precipitation can help predict the number of butterfly species in Australia.

Analysis, Evaluation, Environmental aspects, Wildlife research, Rain and rainfall, Rain

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Application of the new keystone-species concept to prairie dogs: how well does it work?

Article Abstract:

An argument is presented for de-emphasizing the dualism inherent in the keystone-species concept, or the theory that specific species have significant impacts on ecosystem function and community structure while others do not. The author supports an overall approach addressing how species affect abundance, and how they react under various ecological conditions and across temporal and spatial scales.

Wildlife management

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Detecting and modeling spatial and temporal dependence in conservation biology

Article Abstract:

Techniques are presented to avoid adverse statistical results that can occur when spatial and temporal data dependencies are disregarded. These techniques include autocorrelation, partial autocorrelation plots, variograms, covariograms, and Gaussian autoregressive models.

Habitat (Ecology), Habitats, Autocorrelation (Statistics), Gaussian processes

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