Increasing climatic sensitivity of global grassland vegetation biomass and species diversity correlates with water availability

Abstract

Grasslands are key repositories of biodiversity and carbon storage and are heavily impacted by effects of global warming and changes in precipitation regimes. Patterns of grassland dynamics associated with variability in future climate conditions across spatiotemporal scales are yet to be adequately quantified. Here, we performed a global meta-analysis of year and growing season sensitivities of vegetation aboveground biomass (AGB), aboveground net primary productivity (ANPP), and species richness (SR) and diversity (Shannon index, H) to experimental climate warming and precipitation shifts. All four variables were sensitive to climate change. Their sensitivities to shifts in precipitation were correlated with local background water availability, such as mean annual precipitation (MAP) and aridity, and AGB and ANPP sensitivities were greater in dry habitats than in nonwater-limited habitats. There was no effect of duration of experiment (short vs long term) on sensitivities. Temporal trends in ANPP and SR sensitivity depended on local water availability; ANPP sensitivity to warming increased over time and SR sensitivity to irrigation decreased over time. Our results provide a global overview of the sensitivities of grassland function and diversity to climate change that will improve the understanding of ecological responses across spatiotemporal scales and inform policies for conservation in dry climates.

Keywords: carbon storage; ecological sensitivity; global warming; precipitation alteration; structural changes; temporal dynamics.

Fig. 1

Study sites and analyses of sensitivity to climate treatments. (a) Distribution of grassland ecosystem study sites testing effects of warming (n = 50), drought (n = 54), irrigation (n = 63), warming and drought (n = 5) and warming and irrigation (n = 8). Colours represent the climate treatments: W, warming; D, drought; I, irrigation; WD, warming + drought; and WI, warming + irrigation. Sensitivity of aboveground biomass (AGB), aboveground net primary productivity (ANPP), species richness (SR) and species diversity (H) to climate treatments for whole years (WY) (b) and growing seasons (GS) (c). Error bars represent the standard error. The significance was tested by weighted Student's t‐tests ((*), P < 0.1; *, P < 0.05; **, P < 0.01; and ***, P < 0.001).

Fig. 2

Correlations between aboveground biomass (AGB) (a–c) and aboveground net primary production (ANPP) (d–f) sensitivity to treatments over whole‐year and local climate conditions. AI and MAP represent the aridity index and mean annual precipitation of the study sites. The x‐axis shows the best‐fitted climate variables based on model selection; R ² is the coefficient of determination for the regression. Circle sizes (small and large) represent short‐term (1–4 yr) and long‐term (≥5 yr) studies, respectively. Statistical significance across spatial scales was tested using a general linear model and only the significant relationships (P < 0.05) are shown (brown and blue lines). The shading with the lines indicates the standard error. The dashed line (y = 0) separates positive and negative values.

Fig. 3

Comparison of aboveground biomass (AGB) and aboveground net primary production (ANPP) sensitivity for whole year (WY) to treatments at dry (mean annual precipitation: MAP < 500 mm) and nonwater‐limited (MAP > 500 mm) study sites, tested using analyses of variance and Tukey's honest significant difference test. Error bars represent the standard error. The asterisk indicates the different significance analysed with Tukey's honest significant difference (HSD) tests ((*), P < 0.1; *, P < 0.05; **, P < 0.01; and ***, P < 0.001).

Fig. 4

Correlations between species richness (SR) (a–c) and species diversity (H) (d–f) sensitivities for whole year (WY) under climate change treatments and local climate factors. MATm, MAP and AI represent the modified mean annual temperature (MAT + 15), mean annual precipitation and aridity index, respectively. Relationships with MATm and MAP were tested by logistic linear regression analysis; the best‐fit regressions are shown. Solid and dashed fitted regression lines indicate the significance P < 0.05 and P < 0.1, respectively, and small and large circles represent short‐term (< 5 yr) and long‐term (≥ 5 yr) experiments. The shading with the lines indicates the standard error. The dashed black line at y = 0 separates positive and negative values.

Fig. 5

Overall temporal trends in year aboveground net primary production (ANPP) and species diversity (SR) sensitivity under experimental climate warming (a, c) and irrigation (b, d) treatment. Blue and brown dots represent nonwater‐limited (MAP > 500 mm) and dry (MAP < 500 mm) study sites, respectively. The red line (a, d) indicates the significant trend tested using a linear mixed model. The shading with the lines indicates the standard error.