US Geological Survey

 

Date of this Version

2006

Citation

Published in The Endangered Species Act at Thirty, Volume 2: Conserving Biodiversity in Human-Dominated Landscapes, edited by J. Michael Scott, Dale D. Goble, & Frank W. Davis (Washington: Island Press, 2006), pp. 164-177.

Abstract

The U.S. Endangered Species Act (ESA) requires that critical habitat-areas essential to the persistence or recovery of a species or population-be identified and protected (Goble and Freyfogle 2002). Despite apprehension that requiring critical habitat designation at the time (or within a year) of listing under the ESA would reduce the rate at which species were listed, this does not appear to have happened (Greenwald et al., this volume; Suckling and Taylor 2006). In fact, critical habitat has been designated for only a fraction of listed species (Scott et al. 2006). Reasons for the poor rate of designation include concerns that it provides litde additional protection to species (e.g., Hoekstra et al. 2002a, but see Suckling and Taylor 2006) and that sufficient data to determine critical habitat are not available. One problem is lack of a systematic framework for determining critical habitat using various types and amounts of data.

There are two key steps to determining critical habitat. The first is to characterize habitat requirements of a species based on its ecology and life history. Ideally, this is achieved by identif)ring variables that contribute to presence, density, and demography in different landscapes. The end product is a set of quantitative, functional relationships that predict presence or abundance. When sufficient data are lacking, descriptive habitat preferences based on known occurrences of the species are used to identify habitat requirements and elicit structured opinions from experts.

The second step is to evaluate how different amounts and configurations of habitat affect survival or recovery of the species. In making this determination, different scenarios for the amount and configuration of habitat under protection, and/or characteristics of the population inhabiting that area, are compared to each other and to a criterion, a threshold, or a critical level that embodies an acceptable risk of decline or loss. Again, when sufficient data are lacking, expert opinion can be used, cautiously, to evaluate risks of different scenarios for protecting critical habitat.

The Endangered Species Act mandates designating critical habitat based on the best available scientific data (Ruckelshaus and Darm, this volume). Data availability differs by species, which in turn affects the approach used for determining suitable and critical habitats (Karl et al. 2002; Scott et al. 2002). Models are the primary means of assessing habitat relationships and predicting consequences of habitat change (Wiens 2002). Ideally, sufficient data are needed to effectively determine if the designated habitat would support a viable population. However, often we cannot wait for these data to be collected. As Ruckelshaus and Darm (this volume) point out, logistics of model selection and development for determining critical habitat can be daunting.

In this chapter, we discuss a hierarchical approach to predicting species occurrence and designating critical habitat appropriate for the type and amount of data available to managers.

Share

COinS