From a line in the sand to a landscape of decisions: A hierarchical diversity decision framework for estimating and communicating biodiversity loss along anthropogenic gradients
When setting water quality criteria, managers must choose thresholds for stressors that are protective of aquatic biodiversity. Setting such thresholds requires making implicit judgments about the degree of biodiversity loss that managers are willing to accept. We present a new modelling approach, the hierarchical diversity decision framework (HiDDeF) that explicitly communicates the sensitivity of water quality benchmarks to these implicit judgments. We apply HiDDeF to a data set of stream macroinvertebrate abundances across 218 sites in south-western West Virginia, USA, where alkaline mine drainage increases streamwater conductivity and leads to the loss of sensitive taxa throughout regional river networks. By integrating responses of individual taxa within a flexible hierarchical framework, HiDDeF reliably predicts macroinvertebrate assemblages across the full range of conductivities observed in the training data set but requires only a fraction (~10%) of the sites required in previous studies. HiDDeF results suggest that the current conductivity benchmark (300 μS cm-1) for regional streams translates to 50% loss in abundance for at least one-quarter of regional macroinvertebrate taxa. HiDDeF produces a 'decision landscape' that allows decision-makers to assess sensitivity of proposed benchmarks to their choice of protective level. HiDDeF allows users to investigate both individual- and community-level responses to environmental gradients and generates output that includes a comprehensive summary of uncertainty in model parameters.
Voss, KA; King, RS; Bernhardt, ES
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