In our first analysis, as suggested by Xing et al.9, we address the potential differences between the two ecosystem types—grasslands and forests—in their association of stomatal traits with environment. That question was beyond the scope of our original paper, but we agree with Xing et al.9 that it is a highly relevant one, and thus we test for contrasting stomatal trait-environment relationships that may be linked with the different guard cell shapes of their dominant species. Our detailed analysis shows some differences in the environmental associations of stomatal traits for forest and grassland communities using community weighted metrics, though perhaps surprisingly, most environmental associations are similar for the two ecosystem types. When we use a principal components analysis of 30 environmental variables (including, e.g., mean annual temperature and precipitation and many others; Table S1), the PC axes 1, 2 and 3 explain 82.1% of the total variation (Table S2). We analyze environmental trends for community-weighted means of SL and stomatal density (SL CWM and SD CWM , respectively) with these PCA axes and with individual climate variables (Tables S3, 4). Across forests, the SL CWM increases strongly with climate PC1 (R2 = 0.32, t = 3.94, df = 26, p = 0.001), corresponding to a negative trend with moister, warmer climates, whereas grasslands do not show a significant association (R2 = 0.009, t = −0.58, df = 27, p = 0.56). However, forests and grasslands show statistically similar slopes for their responses of SL CWM to climate PC2 and PC3, and differ only in intercepts, consistent with the larger SL of grasslands than forests (Fig. 1). Further, the forests and grasslands do not differ in the slopes of their responses of SD CWM to climate PC1, PC2 and PC3 (Fig. 1). Tests of the responses of SL CWM and SD CWM to individual environmental variables are consistent; respectively, 19/30 (63.3%) and 28/30 (93.3%) of their associations with environment variables have similar slopes for grasslands and forests (Tables S3, 4). For six of the 11 SL CWM -environment associations that differ significantly in slope, forest ecosystems show a significant association with environment and the grasslands do not. The possible reason for the greater responses of SL CWM of forests than grasslands might relate to differences in leaf or stomatal type of the component species, with a greater advantage for relatively smaller stomata in colder and drier conditions on average for forest species. Alternatively, the stronger trends for forests than grasslands may be due to the larger range of climates occupied by forests than grasslands in our study.

Fig. 1: Relationships of community-weighted means of stomatal traits across 28 forests and 29 grasslands to the environment. CWM community-weighted mean, SL stomatal length, SD stomatal density, PC1, PC2, and PC3 represent the first three axes of the Principal Component Analysis (PCA) for 30 environmental variables, respectively. a–c Relationships of CWMs of SL to PC1, PC2, and PC3, respectively. d–f Relationships of CWMs of SD to PC1, PC2, and PC3, respectively. Statistical analysis was performed using linear mixed-effects models, with vegetation type (forests vs. grasslands), environment, and their interaction as fixed effects, and plot nested within site as a random effect. The solid lines depict significant linear regressions and the dashed lines non-significant linear regressions, and the gray shading indicates 95% confidence intervals. We included the regression lines for both significant and non-significant relationships to allow for direct visual comparison of slopes and intercepts between the two groups. The p-value of < 0.05 signifies significant differences in the slopes and intercepts of the relationships of stomatal traits for forests and grasslands to the environment. For additional details, please refer to Tables S3, 4. Source data are provided as a Source Data file. Full size image

Yet, that analysis, as suggested by Xing et al.9, does not directly address their question of whether grasses and non-grasses, with their different stomatal types, differ in their environmental associations across communities. Indeed, forests and grasslands both include a mixture of many lineage groups, and grasslands contain both grasses and non-grass species. Therefore, for a more appropriate analysis of the differences between species of contrasting stomatal types in their climate associations, for the 29 grassland sites we calculate “community lineage mean” values of SL and SD (SL CLM and SD CLM , respectively), representing the grasses (dumb-bell shaped guard cells) and non-grasses (kidney bean shaped guard cells) and test their associations with environment across sites. Notably, across these 29 grassland sites, SL CLM is higher and SD CLM lower for grasses than non-grasses (Fig. 2), and grasses and non-grasses are positively related in their SL CLM (R2 = 0.35, p < 0.001, F 1,27 = 14.39), and independent in their SD CLM (R2 = 0.068, p = 0.17, F 1,27 = 1.97; Fig. 2). When we use a principal components analysis of 30 environmental variables across 29 grassland sites, the PC axes 1, 2 and 3 explain 85.2% of the total variation (Table S5). In our analyses of trends for SL CLM and SD CLM for grasses and non-grasses with environmental variables, the SL CLM for grasses and non-grasses show similar relationships with environment, with no differences in slope with PC1, PC2 or PC3, whereas SD CLM for grasses and non-grasses show different slopes for PC1 but not PC2 and PC3 (Fig. 3). Tests of the responses of SL CLM and SD CLM to individual environmental variables are consistent. For SL CLM , 30/30 (100%) of associations have similar slopes for grasses and non-grasses (Tables S6, 7). For SD CLM , 19/30 (63.3%) of associations have similar slopes for grasses and non-grasses (Tables S6, 7); for one of the 11 SD CLM -environment associations that differs significantly in slope for grasses and non-grasses, the grasses show a significant association with environment and the non-grasses do not, and for 9 the non-grasses show a significant association with environment and the grasses do not. We conclude that the observed differences in SL CWM -environment relationships between forests and grasslands (Fig. 1) are not likely due to the differences between grasses and non-grasses in their stomatal types, as the responses of SL to the environment are almost identical for community lineage means representing the two stomatal types in grassland species.

Fig. 2: Changes in community lineage means of stomatal traits for stomata with dumbbell versus kidney-shaped guard cells and their relationships across 29 grassland sites. CLM community lineage mean, SL stomatal length, SD stomatal density. a, b Differences in CLM of SL and SD between plants with dumbbell-shaped and kidney-shaped guard cell stomatal types, respectively. c, d Relationships of CLM of SL and SD between plants with dumbbell-shaped and kidney-shaped guard cell stomatal types across 29 grassland sites, respectively. Violin plots of stomatal traits for dumbbell-shaped and kidney-shaped guard cell stomatal types are filled with different colors. Two-sided paired sample t-tests were employed to investigate differences in stomatal traits between stomatal types. Ordinary least squares regression was used to explore relationship between the CLM of stomatal traits for dumbbell-type and kidney-type stomata. The solid and dashed lines depict significant and non-significant linear regressions, respectively, while the gray shading indicates the 95% confidence interval. We included the regression lines for both significant and non-significant relationships to allow for direct visual comparison of slopes and intercepts between the two groups. Source data are provided as a Source Data file. Full size image

Fig. 3: Relationships of the community lineage means of stomatal traits for grasses versus non-grasses (with stomata with dumbbell- versus kidney-shaped guard cells, respectively) to the environment across 29 grassland sites. CLM community lineage mean, SL stomatal length, SD stomatal density. PC1, PC2, and PC3 represent the first three axes of the Principal Component Analysis (PCA) for 30 environmental variables, respectively. a–c Relationships of CLM of SL to PC1, PC2, and PC3, respectively. d–f Relationships of CLM of SD to PC1, PC2, and PC3, respectively. Ordinary least squares regression was used to explore relationship between the CLM of stomatal traits and environment. The differences in regression slopes and intercepts were assessed using analysis of covariance (ANCOVA). The solid lines depict significant linear regressions and the dashed lines non-significant linear regression; the gray shading indicates 95% confidence intervals. We included the regression lines for both significant and non-significant relationships to allow for direct visual comparison of slopes and intercepts between the two groups. The p-value of <0.05 signifies significant differences in the slopes and intercepts of the relationships of stomatal traits for dumbbell-shaped and kidney-shaped guard cell stomatal types to the environment. For additional details, please refer to Table S6, 7. Source data are provided as a Source Data file. Full size image

We conduct a third analysis to consider one of our original study’s major findings—the stomatal length-density trade-off across communities at continental scale10—and whether this relationship may vary for community weighted means for grasslands versus forests, or for community lineage means for grasses versus non-grass species of grasslands. The trade-off between stomatal length and density is robust in all tests for forests and grasslands, and for grasses and non-grasses (Fig. 4). The slope and intercept of the SL CWM versus SD CWM regression are both higher for forests than grasslands, but the slopes and intercepts are statistically similar for SL CLM versus SD CLM for grasses and non-grasses across the 29 grassland sites. As in the previous analysis, we conclude that stomatal trait versus environment relationships do differ between forests and grasslands, but likely not due to the differences between grasses and non-grasses in their stomatal types.

Fig. 4: Trade-off between stomatal density and length. a Trade-off between community-weighted means of stomatal density and length across 28 forest sites and 29 grassland sites. b Trade-off between stomatal density and length across grasses (with dumbbell shaped guard cells) and non-grass (with kidney-bean shaped guard cells) species. All stomatal traits are log-transformed. Ordinary least squares regression was used to explore relationship between stomatal density and length. The solid lines depict significant linear regressions, and the gray shading indicates the 95% confidence intervals. The differences in regression slopes and intercepts were assessed using analysis of covariance (ANCOVA). The p-value of <0.05 signifies significant differences in the slopes and intercepts of the linear regression between stomatal density and length. Source data are provided as a Source Data file. Full size image

Overall, our results suggest that the majority of environmental associations of SL and SD are consistent between grasslands and forests, considering their community weighted means, and between grasses and non-grasses, considering their community lineage means. These findings are consistent with the stomatal types (dumbbell-shaped and kidney-shaped guard cells) exhibiting similar adaptation to environmental factors at the scale of communities across the continent. That convergence may be explained by the vast differences in timescale between stomatal dynamic movements (minute to second scale) and community assembly and environmental adaptation across a continent (many years to millennia). Thus, while dumbbell-shaped and kidney-shaped stomata would exhibit differences in speed of dynamic opening and closing, our results suggest that their long-term adaptations tend to be similar given the many other processes that would influence adaptation across larger scales of space and time.

Finally, we wish to address the conclusions of Xing et al.9 that “principles of consistency” should prohibit testing the associations of community weighted means with climate when communities are comprised of diverse lineage groups with strong differences in physiology. We found broadly similar patterns when comparing community weighted means and community lineage means for the adaptation of stomatal traits to the environment at continental scale. Recent studies have emphasized that for inputting traits to represent ecosystems in vegetation models, using values averaged for species within lineages can provide improved resolution over values averaged for species within coarse categories of plant functional types based on growth form, phenology, photosynthetic pathway and climate (e.g., temperate vs tropical)11,12. Yet, we argue that when trait data are available for a majority of plant species, or the dominant species of communities, community weighted means remain highly informative to represent ecosystems13, and thereby to address many questions in evolution, community assembly and global change biology, including ecosystem responses to climate.