Biomass distribution among size classes follows a power law where the Log-abundance of taxa scales to Log-size with a slope that responds to environmental abiotic and biotic conditions. The interactions between ecological mechanisms controlling the slope of locally realized size-abundance relationships (SAR) are however not well understood. Here we tested how warming, nutrient levels, and grazing affect the slope of phytoplankton community SARs in decadal time-series from eight Swiss lakes of the peri-alpine region, which underwent environmental forcing due to climate change and oligotrophication. We expected rising temperature to have a negative effect on slope (favoring small phytoplankton), and increasing nutrient levels and grazing pressure to have a positive effect (benefiting large phytoplankton). Using a random forest approach to extract robust patterns from the noisy data, we found that the effects of temperature (direct and indirect through water column stability), nutrient availability (phosphorus and total biomass), and large herbivore (copepods and daphnids) grazing and selectivity on slope were non-linear and interactive. Increasing water temperature or total grazing pressure, and decreasing phosphorus levels, had a positive effect on slope (favoring large phytoplankton, which are predominantly mixotrophic in the lake dataset). Our results therefore showed patterns that were opposite to the expected long-term effects of temperature and nutrient levels, and support a paradigm in which (i) small phototrophic phytoplankton appear to be favored under high nutrients levels, low temperature and low grazing, and (ii) large mixotrophic algae are favored under oligotrophic conditions when temperature and grazing pressure are high. The effects of temperature were stronger under nutrient limitation, and the effects of nutrients and grazing were stronger at high temperature. Our study shows that the phytoplankton local SARs in lakes respond to both the independent and the interactive effects of resources, grazing and water temperature in a complex, unexpected way, and observations from long-term studies can deviate significantly from general theoretical expectations.
- Size spectra
- Bottom–up and top–down controls
- Main effects and interactions
- Non-linear effects
- Random forests
- Climate change