|Title||Trait selection and community weighting are key to understanding ecosystem responses to changing precipitation regimes|
|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Griffin-Nolan, RJ, Bushey, JA, Carroll, CJW, Challis, A, Chieppa, J, Garbowski, M, Hoffman, AM, Post, AK, Slette, IJ, Spitzer, D, Zambonini, D, Ocheltree, TW, Tissue, DT, Knapp, AK|
|Secondary Authors||Fox, C|
|Pagination||1746 - 1756|
1. Plant traits can be used to predict ecosystem responses to environmental change using a response–effect trait framework. To do this, appropriate traits must be identified that explain a species' influence on ecosystem function (“effect traits”) and the response of those species to environmental change (“response traits”). Response traits are often identified and measured along gradients in plant resources, such as water availability; however, precipitation explains very little variation in most plant traits globally. Given the strong relationship between plant traits and ecosystem functions, such as net primary productivity (NPP), and between NPP and precipitation, the lack of correlation between precipitation and plant traits is surprising.
2. We address this issue through a systematic review of >500 published studies that describe plant trait responses to altered water availability. The overarching goal of this review was to identify potential causes for the weak relationship between commonly measured plant traits and water availability so that we may identify more appropriate “response traits.”
3. We attribute weak trait–precipitation relationships to an improper selection of traits (e.g., nonhydraulic traits) and a lack of trait‐based approaches that adjust for trait variation within communities (only 4% of studies measure community‐weighted traits). We then highlight the mechanistic value of hydraulic traits as more appropriate “response traits” with regard to precipitation, which should be included in future community‐scale trait surveys.
4. Trait‐based ecology has the potential to improve predictions of ecosystem responses to predicted changes in precipitation; however, this predictive power depends heavily on the identification of reliable response and effect traits. To this end, trait surveys could be improved by a selection of traits that reflect physiological functions directly related to water availability with traits weighted by species relative abundance.