Multiple non-linear responses to a gradient of nitrogen addition in grasslands
Human alterations of the global nitrogen (N) cycle and biodiversity loss are two of the most impacted of Earth’s planetary systems. The interaction between these two planetary systems is of additional concern because N deposition is one of the leading drivers of terrestrial plant diversity loss. Recent studies suggest that N deposition causes non-linear losses of species diversity with greatest rates of species loss occurring at relatively low levels of N deposition. Here we used experimental gradients of added N to test for non-linear responses of plant diversity and other, higher trophic level metrics. We added increasing rates of N to two USA grasslands (Chichaqua Bottoms Greenbelt, IA and Cedar Creek, MN), both part of the Nutrient Network (NutNet). Plot design and sampling protocols were identical to standard NutNet plots except for additional treatment levels of N to create an experimental gradient of 0, 1, 5 and 10 g m-2 yr-1, and we replicated treatments in 6 (IA) and 5 blocks (MN).
Our results showed various non-linear responses to gradients of added N after only 2 years of treatment application. Specifically, the greatest relative species loss occurred at the lowest level of added N (1 g m-2 yr-1), which is in the range of regional ambient total N deposition rates. Multiple model testing showed non-linear (e.g. Monod) or significant third-order models with lowest AIC compared to alternatives. Non-linear loss of seed bank diversity occurred significantly at lowest rates of N addition: seed bank richness was reduced by more than half with 1 g m-2 yr-1 added N (p=0.0009). In contrast, N-addition effects on higher trophic levels showed opposite patterns: both insect density and diversity significantly increased with greater levels of added N. Our results, taken together, suggest that multiple components of communities respond non-linearly to environmental change drivers such as N-deposition, but responses differ in direction as well as potential threshold levels or tipping points.