A new method for bioassessment of ecosystems with complex communities and environmental gradients
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Abstract
Bioassessment of complex and heterogeneous ecosystems is a challenge when there are multiple, strong, natural environmental gradients; unknown, or spatially varying, mixtures of stressors; and large numbers of taxa with unknown responses to both the environmental gradients and the stressors. Current methods of bioassessment are not designed for use under this set of constraints. To address this gap, we have developed an assessment method appropriate for well-sampled, heterogeneous systems with many taxa. In the bioassessment described below, we model taxa occurrence as a function of natural environmental gradients, then use residual covariance patterns between all pairs of taxa to estimate the impact of human disturbance across sites as a latent construct. The derivation of the method from an underlying causal model allows the metric value at each site and the associated taxa responses to be partitioned into contributions from a set of putative stressors. We apply this method as a case study to the subtidal benthic invertebrate community of Puget Sound, WA (USA) and demonstrate a partial decomposition of the metric values to a set of stressors including sediment organic carbon, nitrogen, metals, and organic pollutants. While this method provides new opportunities to estimate, communicate, and understand the ecological condition of complex, heterogeneous ecosystems, due to the requirement for broad, detailed data to inform its estimates, it will likely be most appropriate for monitoring programs.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | A new method for bioassessment of ecosystems with complex communities and environmental gradients |
| Series title | Ecological Indicators |
| DOI | 10.1016/j.ecolind.2023.111413 |
| Volume | 158 |
| Year Published | 2024 |
| Language | English |
| Publisher | Elsevier |
| Contributing office(s) | Wetland and Aquatic Research Center |
| Description | 111413, 12 p. |
| Country | United States |
| State | Washington |
| Other Geospatial | Puget Sound ecosystem |
| Google Analytic Metrics | Metrics page |