Climate shapes and shifts functional biodiversity in forests worldwide

Abstract

Much ecological research aims to explain how climate impacts biodiversity and ecosystem-level processes through functional traits that link environment with individual performance. However, the specific climatic drivers of functional diversity across space and time remain unclear due largely to limitations in the availability of paired trait and climate data. We compile and analyze a global forest dataset using a method based on abundance-weighted trait moments to assess how climate influences the shapes of whole-community trait distributions. Our approach combines abundance-weighted metrics with diverse climate factors to produce a comprehensive catalog of trait-climate relationships that differ dramatically-27% of significant results change in sign and 71% disagree on sign, significance, or both-from traditional species-weighted methods. We find that (i) functional diversity generally declines with increasing latitude and elevation, (ii) temperature variability and vapor pressure are the strongest drivers of geographic shifts in functional composition and ecological strategies, and (iii) functional composition may currently be shifting over time due to rapid climate warming. Our analysis demonstrates that climate strongly governs functional diversity and provides essential information needed to predict how biodiversity and ecosystem function will respond to climate change.

Keywords: biodiversity; climate; ecosystem function; functional ecology; macroecology.

Fig. 1.

Shifts in the community-weighted moments of several key functional plant traits along latitudinal and elevational gradients. (A) Geographic distribution of the 421 forest communities in this study (triangles designate the 66 locally sampled communities). (B–E) Abundance-weighted moments of whole-community trait distributions across (absolute) latitude and elevation. For mean and variance (B and C), lines represent linear regressions on the percent deviation between individual community values and the average moment value for a given trait and geographic gradient. For skewness and kurtosis (D and E), lines are regressions on raw moment values and absolute values of latitude and elevation to enable comparison with normality (skewness/kurtosis = 0). Stars signify significant regressions, and dashes are used to visualize overlapping lines. (F–I) Cartoons illustrating how variation in trait distribution shape is captured by each of the respective moments.

Fig. 2.

Relationships between the community-weighted moments of individual traits and all environmental variables across all forests. (A) Radar plots showing all trait moment–environment correlations. Each symbol represents a different trait moment, and its position along the radial axis indicates the strength of correlation between that moment and a given environmental variable. The solid black line represents zero correlation, the region inside (outside) this line represents negative (positive) correlations. Gray shading represents nonsignificant correlations. Filled shapes highlight the environmental variables that are most strongly correlated with each of the four trait moments. (B) Mean magnitudes (absolute values) of all significant correlations between all trait moments and each environmental variable. Environmental variables are abbreviated as follows: absolute value of latitude (|Lat|), elevation (Elev), mean annual temperature/precipitation (MAT/MAP), isothermality (ISO), temperature diurnal range (TDR), temperature annual range (TAR), temperature/precipitation seasonality (TS/PS), climate water deficit (CWD), vapor air pressure (VAP), vapor pressure deficit (VPD), potential evapotranspiration (PET), wind velocity (Wind), and solar radiation (SR).

Fig. 3.

The first two principal component axes of community-weighted mean trait space (traits PC1 and PC2) across all traits and communities and the strength of their correlations with each environmental variable. (A) The first two principal trait axes (traits PC1 and PC2). Gray points show the principal coordinates for each community, and colored lines represent loadings (eigenvalues) for individual traits, which indicate the relative contribution of each trait to variation in each PC axis. Both the coordinates and loadings have been rescaled to the interval [−1,1]. (B and C) Correlations between the first two principal trait axes and individual environmental variables.

Fig. 4.

Signatures of community trait shifts in response to rapid climate warming. (A) Expected shifts in mean and skewness relative to an initial distribution. (B and C) Community relative mean (B) and skewness (C) values for all communities shown as deviations between local and global (a proxy for initial) moment values (SI Appendix, Supplementary Methods). Circles indicate individual communities, and colors designate underlying relationships (correlations) between traits and temperature (MAT). Stars indicate significantly nonzero averages. Bars are nonsignificant. (D and E) Regressions of relative mean (D) and skewness (E) for all traits combined against the historical rate of change in MAT. Stars indicate significant trends.