Search

Illustrations and guidelines for selecting statistical methods for quantifying spatial pattern in ecological data

This paper aims to provide guidance to ecologists with limited experience in spatial analysis to help in their choice of techniques. It uses examples to compare methods of spatial analysis for ecological field data. A taxonomy of different data types is presented, including point- and area-referenced data, with and without attributes. Spatially and non-spatially explicit data are distinguished. The effects of sampling and other transformations that convert one data type to another are discussed; the possible loss of spatial information is considered.

The consequences of spatial structure for the design and analysis of ecological field surveys

In ecological field surveys, observations are gathered at different spatial locations. The purpose may be to relate biological response variables (e.g., species abundances) to explanatory environmental variables (e.g., soil characteristics). In the absence of prior knowledge, ecologists have been taught to rely on systematic or random sampling designs.

Accounting for spatial pattern when modeling organism-environment interactions

Statistical models of environment-abundance relationships may be influenced by spatial autocorrelation in abundance, environmental variables, or both. Failure to account for spatial autocorrelation can lead to incorrect conclusions regarding both the absolute and relative importance of environmental variables as determinants of abundance.

A balanced view of scale in spatial statistical analysis

Concepts of spatial scale, such as extent, grain, resolution, range, footprint, support and cartographic ratio are not interchangeable. Because of the potential confusion among the definitions of these terms, we suggest that authors avoid the term ¿¿scale¿¿ and instead refer to specific concepts. In particular, we are careful to discriminate between observation scales, scales of ecological phenomena and scales used in spatial statistical analysis.

Stoichiometric food quality and herbivore dynamics

Habitat patchiness and plant species richness

The pattern of woody species richness decline with a decrease in woody vegetation cover was studied within a tallgrass prairie. The decline in species richness is highly non‐linear, with a well‐defined threshold below which species richness collapses. This relationship can be understood after considering information on how landscape structure changes with woody vegetation cover, and how species richness is related to landscape structure.

Assessing multi-species recovery plans under the Endangered Species Act

Evaluating the internal consistency of recovery plans for federally endangered species

Factors affecting implementation of recovery plans

Jurisdiction over endangered species' habitat: The impacts of people and property on recovery planning