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Title: Drivers of variation in aboveground net primary productivity and plant community composition differe across a broad precipitation gradient

Author
item LA PIERRE, KIMBERLY - Yale University
item Blumenthal, Dana
item BROWN, CYNTHIA - Colorado State University
item KLEIN, JULIA - Colorado State University
item SMITH, MELINDA - Yale University

Submitted to: Ecosystems
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/23/2015
Publication Date: 1/7/2016
Citation: La Pierre, K.J., Blumenthal, D.M., Brown, C.S., Klein, J., Smith, M.D. 2016. Drivers of variation in aboveground net primary productivity and plant community composition differe across a broad precipitation gradient. Ecosystems. Doi: 10.1007/s10021-015-9949-7.

Interpretive Summary: It has long been a goal of ecology to determine what factors control plant productivity. Total annual precipitation has been shown to be a strong predictor of plant productivity across broad spatial scales, but a poor predictor at local scales. Here we show that biotic factors, particularly plant species richness, were most closely associated with plant productivity across three grassland sites spanning the broad precipitation gradient of the North American Great Plains (318-735 mm mean annual precipitation). However, within sites abiotic factors (seasonal precipitation and nutrient availability) were much stronger predictors of plant productivity. The specific nutrients and seasonal precipitation periods that best predicted plant productivity varied across the three sites studied here. Additionally, we show experimentally that precipitation and nutrient availability co-limit plant productivity across the Central Great Plains. The dominant grasses were shown to drive the productivity response to nutrient availability; however, the proportional (per-unit biomass) responses of less common plant species were shown to be greater than those of the dominant grasses, providing a mechanism for species turnover with chronic nutrient additions. Overall, these results will help to improve predictions of plant productivity under future global change scenarios.

Technical Abstract: It has long been a goal of ecology to determine what factors drive variation in aboveground net primary production (ANPP). Total annual precipitation has been shown to be a strong predictor of ANPP across broad spatial scales, but a poor predictor at local scales. Here we aim to determine the amount of variation in ANPP that can be explained by total annual precipitation as compared to seasonal precipitation, nutrient availability, and biotic factors (plant species richness and the abundance of the dominant plant species) across three grassland sites spanning the broad precipitation gradient of the North American Great Plains (318-735 mm mean annual precipitation). We further aim to determine how precipitation and nutrient availability may interact to drive variation in ANPP using a resource addition experiment, and the role that dominant and rare species play in determining this interaction. Overall, we found that biotic factors, particularly plant species richness, predicted most variation in ANPP across sites, likely due to the high species turnover across this broad resource gradient. However, within sites abiotic variables (seasonal precipitation periods and nutrient availability) were much stronger predictors of ANPP. The specific nutrients and seasonal precipitation periods that best predicted ANPP varied across the three sites studied here. Additionally, we show experimentally that precipitation and nutrient availability co-limit ANPP across the Central Great Plains. The dominant grasses were shown to drive the ANPP response to nutrient availability; however, the relative responses of the rare grasses and forbs were shown to be greater than those of the dominant grasses to experimental nutrient additions, thus providing a mechanism for species turnover with chronic nutrient additions. Overall, our improved understanding of the factors driving variation in ANPP will aid predictions of variation in ANPP under future global change scenarios.