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Impact of temporal precipitation variability on ecosystem productivity

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Abstract Projected increases in temporal precipitation variability, including intra‐annual and interannual variability, will likely have important impacts on terrestrial ecosystem productivity. The direction and magnitude of these impacts and how they vary across biomes, however, remain largely uncertain. Here, we review published literature that investigated the effect of different characteristics of temporal precipitation variability on vegetation productivity. We first reviewed commonly used methods, including manipulation experiments, process‐based modeling, and data‐driven analysis, and further discussed their strengths and limitations. Then, we summarized state‐of‐the‐art research on this topic by categorizing the results based on the characteristics of temporal precipitation variability. Given the same amount of growing season precipitation, a more extreme precipitation regime, characterized as fewer but larger precipitation events, tends to have a negative impact on vegetation productivity of most ecosystems except xeric grasslands and wet‐cold forests. Precipitation in the early growing season was found to be particularly important to vegetation productivity. Greater interannual precipitation variability tends to decrease vegetation productivity, but the reported patterns are complex, as both concave‐up and concave‐down precipitation‐productivity relations were found. Despite the progress made so far, critical challenges and knowledge gaps remain, such as the global‐scale impacts across different biomes, the role of biological adaption, and the contribution of individual precipitation events. Future research needs to combine manipulation experiments across a broad spectrum of ecosystem types and environmental gradients with model‐data integration strategies to disentangle the interactions between abiotic and biotic factors controlling vegetation responses to precipitation variability. This article is categorized under: Science of Water > Hydrological Processes Water and Life > Nature of Freshwater Ecosystems
Synthesis of existing manipulation experiments on the impact of more extreme precipitation regimes on grassland productivity. The annotations of the points in the plots are the site names (SNWR: Sevilleta National Wildlife Refuge site in New Mexico, USA; SGS: Shortgrass Steppe Long‐Term Ecological Research site in Colorado, USA; SER: Saline Experimental Range in Kansas, USA; KNZ: Konza Prairie Biological Station in Kansas, USA; IM: a semiarid steppe site in Inner Mongolia, China). KNZ‐m1 to KNZ‐m4 represent the mesocosm treatments in the KNZ (Fay et al., 2008). “Contingent” in the legend means there is an optimal “extremeness” below which the impact of more extreme precipitation is positive and above which the impact is negative. “Contingent (more positive/negative)” means the impact is contingent and is positive/negative in most cases (see Figure 2 in Fay et al., 2008 for details). The ambient mean annual precipitation (MAP) in the SNWR is 250 mm, and as shown in the plot, its MAP is 310 mm considering the addition of 60 mm of precipitation in the experiment. The MAP and mean annual precipitation (MAT) were obtained from the literature, and the potential evapotranspiration (PET) was obtained from the CGIAR‐CSI GeoPortal at https://cgiarcsi.community
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A conceptual diagram of the impact of precipitation on vegetation productivity. The orange links are only active under water‐limited conditions. The plus symbols on the links represent positive impacts, while the minus symbols represent negative impacts
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(a) The concave‐down curve for the annual precipitation‐ANPP (aboveground net primary productivity) relationship as suggested by manipulation experiments and the analysis based on long‐term observations. (b) The concave‐up curve for the annual precipitation‐ANPP relationship as suggested by the synthesis of precipitation addition/reduction experiments. The bar shows the average sensitivity of ANPP to altered precipitation, where P+ represents precipitation addition and P‐ represents precipitation reduction. △ANPPP+ in Figure 3a,b means the productivity increases in wet years, while △ANPPP− means the decrease in dry years. (c) The “double asymmetry” model that describes the relationship between annual precipitation and ANPP. This conceptual model was proposed by Knapp et al. (2017) and consists of a concave‐up part under nominal precipitation conditions and a concave‐down part under extreme dry or wet years. The red arrowed lines indicate the relationships between the double asymmetry model and the concave up/down model. The black circle represents the mean state. The nonlinearity in the nominal precipitation range is often difficult to detect because of the large interannual variability in ANPP for most ecosystems (green circles), so a linear regression model (dashed line) is usually adopted. Figure 3c is reprinted with permission from Knapp et al. (2017) Wiley 2016
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Illustration of how the change of rainy season length affect soil water in different rainfall regimes. The blue bars represent precipitation events, and the black solid lines represent the temporal fluctuations of soil water. The gray shade area indicates soil water levels with no significant water stress. We referred to Guan et al. (2014) to draw the soil water curves and Knapp et al. (2008) to draw the gray shade areas
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Water and Life > Nature of Freshwater Ecosystems
Science of Water > Hydrological Processes

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