A set of relatively easy to measure functional traits have become stock standard methods in plant ecology for assessing the impacts of disturbance and environmental change on the functioning of ecosystems. These functional traits include leaf traits such specific leaf area (a ratio measure of leaf area divided by leaf mass), and leaf nutrient content such leaf nitrogen content, leaf phosphorus content and leaf potassium content. The use of leaf traits as predictors of individual, community and ecosystem response originates from the findings of numerous studies that these traits correlate with carbon acquisition strategies known to predict the responses of plants to environmental factors such as gradients in availability and anthropogenic disturbance. For example, SLA has been found to represent a plant’s investment in growing light-capturing area per dry mass content. Species with a relatively high SLA tend to have a higher rate of return on the resources invested into making tissue (cheaper leaves in terms of energy and resources needed to produce them) when compared to species with a lower SLA (more expensive leaves to produce as carbon investments are higher). The strength of these predictions have come from global analyses of data combined from numerous independent studies, but not necessarily with standardized treatments in an experimental framework. The Nutrient Network experiment, globally distributed experiment, presents a unique opportunity to examine the responsiveness of leaf traits across grassland ecosystems characterized by a diverse range of climatic conditions and subjected to the same set of experimental treatments. The main aim of this paper is to quantify how changes in nutrient availability (NPK fertilizer application in all factorial combinations) and grazing alter the functional leaf traits of species over the short-term.
Our results show that SLA varies at a site level (~75% of the variation in SLA in response to treatments were explained at the site level). Leaf nitrogen (%), leaf phosphorous and leaf potassium content varied significantly depending on treatment and where respective nutrients were added. Variation in leaf potassium showed the highest variation between species (~60%). Overall, we show that leaf nutrient content levels are a stronger indicator of functional response to short-term nutrient additions among grasslands than morphological traits like specific leaf area. These findings have important implications for how leaf functional traits are used to infer responses to pervasive environmental change within and across grassland sites.