Speaker
Description
Chemical pollution is a major driver of biodiversity loss and is projected to triple in the next 3 decades. Traditionally, laboratory measures of toxin sensitivity have been extended to quantify the contribution of chemical pollution to biodiversity loss. However, this approach ignores important biotic interactions and therefore performs poorly when predicting extinctions in nature. To solve this, we employed simulated food webs to assess the importance of biotics interactions in modulating chemically-driven extinction. Specifically, we exposed 200 food webs of varying complexity to 140 different concentrations of a hypothetical toxin. Models including food web traits predicted extinction twice as well as models that only included species’ toxin sensitivity alone. We find that trophic level and eigencentrality are key predictors of extinction risk. Our findings have important implications for wildlife conservation and management practice, where risk assessment is crucial in determining vulnerability statuses.
| Status Group | Doctoral Researcher |
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