Abstract
AbstractPredictive modeling is used increasingly often in freshwater bioassessment. These models are routinely applied across broad geographical areas, yet the influence of spatial extent on model performance has not been assessed directly. We examined the influence of changing geographical extent on the performance of River InVertebrate Prediction and Classification System (RIVPACS)–type predictive models of benthic macroinvertebrates in boreal headwater streams representative of reference conditions. Separate models were constructed for 2 hierarchical extents: within ecoregions (middle boreal and north boreal) and across ecoregions. We assessed the accuracy and precision of the models using root mean squared error (RMSE) of the observed/expected (O/E) ratio of the number of predicted taxa. We compared the RMSE of the within-ecoregion models to that of the across-ecoregions models. We tested the models using 2 thresholds for probability of species occurrence (Pt): Pt = 0+ (all predicted taxa) and Pt = 0....
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