Relative strengths of benthic algal nutrient and grazer limitation along a lake productivity gradient

Abstract

The relative effects of nutrients and herbivores on primary producers are rarely compared across ecosystems that vary in potential primary productivity. Furthermore, proposed mechanisms to explain such patterns remain understudied. Here, I examine the strength of nutrient and grazer (herbivore) limitation (i.e., the extent to which producers' growth is limited by insufficient nutrient supply or herbivory) of benthic algae across 13 southwest Michigan lakes that vary widely in productivity (i.e., resource supply). I compare the observed patterns of algal limitation and species composition to those predicted by two simple models: one that includes multiple species and species' traits (the food-web model) and one that includes no variation in species or traits (the food-chain model). Species in the food-web model are assumed to display a tradeoff between resource competitive ability and resistance to herbivory (the "keystone predator" tradeoff). Among these lakes, benthic algal nutrient limitation was positive (x=0.083 day-1) and declined significantly along a lake N:P gradient. In contrast, grazer limitation was negative (x=-0.019 day-1) and was not significantly related to any of the measured lake productivity variables. Negative grazer limitation indicated that the removal of grazers caused unexpected declines in algal biomass, which were potentially due to indirect, positive effects (e.g., nutrient recycling) of grazers. Nutrient limitation was significantly stronger than grazer limitation across lakes, which was more consistent with the food-web versus food-chain model. Changes in algal composition were also broadly consistent with predictions of the food-web model in that vulnerable, superior nutrient competitors dominated in low productivity lakes and more grazer-resistant species were observed in high productivity lakes. In general, these results point to the importance of examining limiting factors across systems and the consideration of key species' traits when predicting and interpreting patterns.