Plant species richness and ecosystem multifunctionality in global drylands

Abstract

Experiments suggest that biodiversity enhances the ability of ecosystems to maintain multiple functions, such as carbon storage, productivity, and the buildup of nutrient pools (multifunctionality). However, the relationship between biodiversity and multifunctionality has never been assessed globally in natural ecosystems. We report here on a global empirical study relating plant species richness and abiotic factors to multifunctionality in drylands, which collectively cover 41% of Earth's land surface and support over 38% of the human population. Multifunctionality was positively and significantly related to species richness. The best-fitting models accounted for over 55% of the variation in multifunctionality and always included species richness as a predictor variable. Our results suggest that the preservation of plant biodiversity is crucial to buffer negative effects of climate change and desertification in drylands.

Figure 1

Relationship between perennial plant species richness and ecosystem multifunctionality (A) measured in a global survey of drylands. Similar relationships for carbon (B), nitrogen (C) and phosphorus (D) cycling are shown. Red and green lines are the fitted lines from ordinary least squares (OLS) and spatial autoregressive (SAR) regressions, respectively. Results of regressions are as follows: A) OLS, R² = 0.030, P = 0.009; SAR, R² = 0.022, P = 0.027; B) OLS, R² = 0.029, P = 0.011; SAR, R² = 0.022, P = 0.027; C) OLS, R² = 0.018, P = 0.044; SAR, R² = 0.014, P = 0.082; and D) OLS, R² = 0.032, P = 0.008; SAR, R² = 0.016, P = 0.061.

Figure 2

Relative importance of perennial plant species richness (red column) and other predictor variables in models of ecosystem multifunctionality (A), and carbon (B), nitrogen (C) and phosphorus (D) cycling. The height of each bar is the sum of the Akaike weights of all models that included the predictor of interest, taking into account the number of models in which each predictor appears. Variable abbreviations as in Table 1.