Use of taxon-specific models of phytoplankton assemblage composition and biomass for detecting impact

摘要: Abstract Phytoplankton is a functionally important taxonomic group commonly used in the assessment of lakes. Using data from minimally disturbed lakes (n = 151) and relatively easily obtained environmental variables, we modeled probability taxon occurrence taxon-specific biomass (mg L−1) 183 phytoplankton taxa using variables characterizing spatial context, ecosystem size land cover. Data putatively affected by one or more pressures (n = 162) were to evaluate responses anthropogenic stress. Longitude latitude two best predictors biomass, followed percent catchment area classified as coniferous forest altitude. Model accuracy was highest for predominant taxa, with wide distributions did not improve model accuracy. Assemblage similarity (1-BC index) trophic index (PTI) calculated predicted observed assemblages performance. Significant changes associated agricultural forestry pressures. Encouragingly PTI responded use but forestry, implying that robust indicator effects on assemblage composition related increased nutrients. Combined, our findings showed can be reliably few, often readily available, predictions biological metrics based are reliable indicators pressures, supporting their lake management.