Plant functional trait diversity regulates the nonlinear response of productivity to regional climate change in Tibetan alpine grasslands

Abstract

The biodiversity-productivity relationship is still under debate for alpine grasslands on the Tibetan Plateau. We know little about direct and indirect effects of biotic and abiotic drivers on this relationship, especially in regard to plant functional trait diversity. Here, we examine how aboveground net primary productivity (ANPP) and precipitation use efficiency (PUE) respond to climate, soil and community structure across alpine grasslands on the Northern Tibetan Plateau. We found that both ANPP and PUE showed nonlinear patterns along water availability and site altitude variation, which together accounted for 80.3% and 68.8% of variation in ANPP and PUE, respectively, by optimal generalized additive models. Functional trait divergence (FTD) and community weighted mean (CWM) of plant functional traits were as important as plant species diversity (PSD) for explaining the nonlinear productivity-climate relationship. These findings were confirmed by results from principal component analyses and structural equation models. We also found that FTD was negatively correlated with PSD across different alpine grasslands. Our results implicate: first, the combinatorial influences of temperature and precipitation gradients are important for predicting alpine grassland dynamics; second, the convergence and divergence of plant functional traits may have the potential to elucidate the effect of plant diversity on ecosystem functionality.

Figure 1. Study region, climate and sites sampled across the Northern Tibetan Plateau.

(a)-regional context of alpine grassland types (AGTs) showed site locations. (b)-mean annual temperature (MAT) and (c)-mean annual precipitation (MAP) over the Tibetan Autonomous Region, China, indicating the climatic conditions of our sampling sites. ArcGIS10.2 was used to create these maps. Climatic data ranges from 1979 to 2008 and daily weather records are available from the China Meteorological Data Sharing Service System.

Figure 2. Hypothetical interrelations among climate, soil, community structure, and ecosystem function (sensitivity) of alpine grasslands on the Northern Tibetan Plateau.

Red lines are for direct impacts, blue lines for indirect impacts, and green lines for covariations. Habitat moisture index (HMI) equals the ratio of growing season precipitation (GSP) to accumulated temperature when daily mean is over 5 °C (AccT). Soil C: N ratio (SCNR) was also considered in this study. Plant species diversity (PSD) includes the indices of richness, Shannon, Simpson, Pielou evenness at the plot level. Community weighted means (CWM) and functional trait divergence (FTD) were calculated from general leaf height (GLH, cm), specific leaf area (SLA, cm² g⁻¹) and leaf mass fraction (LMF, %).

Figure 3

The estimated smoothers for ANPP (a,b, solid lines) and PUE (c,d, dashed lines), respectively, obtained by the optimal generalized additive models (GAMs) that include habitat moisture index (HMI, a,c) and site altitude (b,d) as explanatory variables. The grey areas show the 95% point-wise confidence bands.

Figure 4. Principal component analyses (PCA).

(a)-based on plant species diversity (PSD) that includes species richness at the plot level (Plot_SR), Shannon diversity index (Shannon), Simpson dominance index (Simpson) and Pielou evenness index (Pielou); (b)-based on community weight means (CWM) of general leaf height (CWM_GLH), leaf mass fraction (CWM_LMF) and specific leaf area (CWM_SLA); (c)-based on functional trait divergence (FTD) of general leaf height (FTD_GLH), leaf mass fraction (FTD_LMF) and specific leaf area (FTD_SLA); and (d)-with all potential explanatory variables being pooled together. Yellow diamonds, blue triangles and green squares represent alpine meadow (AM), steppe (AS) and desert-steppe (ADS), respectively. For each component we indicate the percentage of variance explained. See Supplementary Figure S1 for correlations between PSD, CWM and FTD values, Figure S3 for site locations within each alpine grassland type (AGTs) and climatic background, and Figure S4 for variable comparisons among the three AGTs.

Figure 5

Structural equation models examining effects of environmental factors and biodiversity components on ANPP (a) and PUE (b), respectively, at the regional scale across zonal alpine grassland types on the Northern Tibetan Plateau. Green and red arrows indicate significant positive and negative effects, respectively. Line width illustrates path strength. Values associated with path arrows represent standardized path coefficients. Values near to the round arrows show the residuals. Non-significant paths and variables were eliminated from the final SEMs. Results of model fitting: (a) χ² = 1.513, P = 0.679; (b) χ² = 1.513, P = 0.679 (Note: higher P-values associated with χ² tests indicate better fitting to data. See Supplementary Table S3 for summaries of the full SEMs with non-significant relationships included for ANPP and PUE, respectively.