We introduce a new method for quantifying the ecological condition (C) of sites based on documented species' responses to environmental stress. Preliminary research is needed to establish species-specific logistic functions, representing probabilities of finding individual species across an explicit reference gradient, ranging from maximally stressed (C = 0) to minimally stressed (C = 10) localities. Each function takes into account the species' tolerance to stress, the species' overall ubiquity, and the probability of detecting the species when it is present. Given a set of standardized species-specific functions, the ecological condition of any site can be derived by iteration, converging on the value of C that best "predicts" the species that are actually present. Species from multiple taxonomic groups can be included in the calculations, and results are not directly affected by species richness or sampling area. We demonstrate a successful application of this method for bird species assemblages in the U.S. portion of the Great Lakes coastal zone. Approximately, 28% of the bird species observed in the Eastern Deciduous Forest Ecological Province and 35% of the species in the Laurentian Mixed Forest Ecological Province showed strong relationships with a reference gradient of land cover variables. Functional stress-response relationships of these species can be used effectively to estimate ecological condition at new sites. The estimated condition based on bird species generally mirrors the reference condition, but deviations from the expected 1:1 relationship provide meaningful insights about ecological condition of the target areas. Sensitivity analysis using different numbers of species shows that our method is robust and can be applied consistently with 25-30 species exhibiting strong stress-response functions.
|Original language||English (US)|
|Number of pages||14|
|State||Published - Nov 2007|
Bibliographical noteFunding Information:
This research was supported by a grant from the U.S. Environmental Protection Agency's Science to Achieve Results (STAR) Estuarine and Great Lakes (EaGLe) program through funding to the Great Lakes Environmental Indicators (GLEI) project, U.S. EPA Agreement EPA/R-8286750. This document has not been subjected to the Agency's required peer and policy review and therefore does not necessarily reflect the views of the Agency, and no official endorsement should be inferred. We are grateful for contributions by other scientists involved with the GLEI project, especially T. Hollenhorst, P. Wolter, C. Smith, V. Brady, T. Brown, J. Brazner, S. Price, D. Marks, and others, including more than 20 student field investigators. K. McKeefry assisted with data management. Important ideas underlying this analysis were communicated by J. Karr, D. Simberloff, P. Bertram, A. Tyre, H. Possingham, and an anonymous reviewer.
- Environmental stress
- Great Lakes
- Indicator method
- Probability model