02388nas a2200205 4500008004100000022001400041245010800055210006900163300001400232490000800246520170300254100003001957700002801987700002202015700002602037700002402063700001602087700002002103856005902123 2018 eng d a1385-023700aLegacy effects of a regional drought on aboveground net primary production in six central US grasslands0 aLegacy effects of a regional drought on aboveground net primary  a505 - 5150 v2193 a

Global climate models predict increases in the frequency and severity of drought worldwide, directly affecting most ecosystem types. Consequently, drought legacy effects (drought-induced alterations in ecosystem function postdrought) are expected to become more common in ecosystems varying from deserts to grasslands to forests. Drought legacies in grasslands are usually negative and reduce ecosystem function, particularly after extended drought. Moreover, ecosystems that respond strongly to drought (high sensitivity) might be expected to exhibit the largest legacy effects the next year, but this relationship has not been established. We quantified legacy effects of a severe regional drought in 2012 on postdrought (2013) aboveground net primary productivity (ANPP) in six central US grasslands. We predicted that (1) the magnitude of drought legacy effects measured in 2013 would be positively related to the sensitivity of ANPP to the 2012 drought, and (2) drought legacy effects would be negative (reducing 2013 ANPP relative to that expected given normal precipitation amounts). The magnitude of legacy effects measured in 2013 was strongly related (r2 = 0.88) to the sensitivity of ANPP to the 2012 drought across these six grasslands. However, contrary to expectations, positive legacy effects (greater than expected ANPP) were more commonly observed than negative legacy effects. Thus, while the sensitivity of ANPP to drought may be a useful predictor of the magnitude of legacy effects, short-term (1-year) severe droughts may cause legacy effects that are more variable than those observed after multiyear droughts.

1 aGriffin-Nolan, Robert, J.1 aCarroll, Charles, J. W.1 aDenton, Elsie, M.1 aJohnston, Melissa, K.1 aCollins, Scott., L.1 aSmith, M.D.1 aKnapp, Alan, K. uhttp://link.springer.com/10.1007/s11258-018-0813-7.pdf03181nas a2200289 4500008004100000245012300041210006900164300001600233490000700249520223100256100003002487700002202517700002802539700002002567700001802587700002102605700002102626700002102647700002302668700002002691700002102711700002402732700002202756700002002778700001702798856007602815 2018 eng d00aTrait selection and community weighting are key to understanding ecosystem responses to changing precipitation regimes0 aTrait selection and community weighting are key to understanding a1746 - 17560 v323 a

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.

1 aGriffin-Nolan, Robert, J.1 aBushey, Julie, A.1 aCarroll, Charles, J. W.1 aChallis, Anthea1 aChieppa, Jeff1 aGarbowski, Magda1 aHoffman, Ava, M.1 aPost, Alison, K.1 aSlette, Ingrid, J.1 aSpitzer, Daniel1 aZambonini, Dario1 aOcheltree, Troy, W.1 aTissue, David, T.1 aKnapp, Alan, K.1 aFox, Charles uhttps://besjournals.onlinelibrary.wiley.com/doi/10.1111/1365-2435.13135