arising from C. Liu et al. Nature Communications https://doi.org/10.1038/s41467-023-42136-2, (2023)

Stomata with various morphologies exhibit distinct capacities among different plants in regulating leaf carbon acquisition and water transpiration during gas-exchange control1. A recent study by Liu et al.2 on the variation of community-weighted stomatal traits across forest and grassland communities has provided valuable insights into plant adaptive strategies in various environments. The study established an unparalleled stomatal characteristic database and pioneered exploring the relationship between these characteristics and the environment at the community level. As we know, plant stomatal traits reflect the plant’s function in gas exchange, water management, and environmental adaptation directly or indirectly. The short-term precision regulation is mainly associated with the speed of stomatal responses, and the long-term potential regulation is associated with stomatal size and density3,4,5. In angiosperms, there are two major types of stomata, each having distinct morphological structures and being associated with a different plant group. Non-grasses have stomata with kidney-shaped guard cells (Fig. 1a, b), and grasses have stomata with dumbbell-shaped guard cells (Fig. 1c, d). There are important functional differences between the stomata types in plants adaptingto various environments. However, in the study by Liu et al.2, community-weighted stomatal traits were calculated without accounting for the different stomatal types in grasses and non-grasses, which may have obscured the correlation between the community-weighted stomatal traits (especially for stomatal length: SL) and the environmental factors, especially in the grassland communities where grasses and non-grasses coexist. Fig. 1: Stomatal traits vary between species. The non-grasses (a) Arabidopsis thaliana and (b) Phaseolus vulgaris display kidney-shaped guard cells (coloured in green). The grasses (c) Oryza sativa and (d) Triticum aestivum show dumbbell-shaped guard cells (solid green) and specialized subsidiary cells (light green gradient) (authorized by Julie Gray4 released under a Creative Commons Attribution License (CC BY) https://creativecommons.org/licenses/by/4.0/). Full size image

We believe that the difference between the two stomatal types should not be overlooked for at least two reasons. First, the regulatory mechanisms of stomatal opening and closure differ significantly between the two types. The unique morphology and mechanics of dumbbell-shaped guard cells require only small changes in volume to bring about stomatal opening and to achieve a higher diffusible pore area6. As a result, stomata with dumbbell-shaped guard cells open and close much faster than do stomata with kidney-shaped guard cells1,7. Second, the morphological characteristics of fully opened stomata obviously differ between the two types. The fully opened stomata of grasses are approximately the shape of a narrow rectangle, while the fully opened non-grass stomata are more like an ellipse in shape (Fig. 1b, d). These characteristics of stomata with dumbbell-shaped guard cells allow grasses to exploit available light more efficiently and without losing unnecessary amounts of water1 and enhance the drought-tolerance of grasses, and may underlie why the geographical expansion of grasses at the late Eocene epoch occurred, given the drier climate6,8. Therefore, the functional consequences of stomatal length (SL) will differ between grasses and non-grasses. In other words, SL may not be a universal proxy trait of stomatal function when both types of stomata are included in a study.

In the study of Liu et al.2, the tight correlations between stomatal morphology and environmental factors were based on all data used in the study, including those from both grasslands and forests, regardless of the different stomatal types. This choice of statistical method may have masked the biological meaning of the linkages among stomatal function, morphological traits, and environmental change. In fact, when we compared the paired relationships between community-weighted mean of stomatal length (SL_mean) and climatic variables within forests and grasslands, there are only four out of the 19 paired relationships are consistent (meaning both the trend and significance were the same), but four paired relationships were reversed (meaning the trend was obverse and significance was the same), and 11 paired relationships were inconsistent (See Table S6 in Liu et al.2). When analysing the effects of the first three environmental variables (the same as variables in Figure 4a–c from Liu et al.2) on log10(SL_mean) of forests and grasslands separately, we found that the effects of Precipitation of the Warmest Quarter (PWQ) and Mean Temperature of the Wettest Quarter (MTWQ) on log10(SL_mean) were both reversed (Fig. 2a, c). Therefore, we extracted the first three principal components from the 19 climate variables and estimated the SL_mean-PC score relationships within forests, grasslands, and all plots. The results show that all PC scores were significantly associated with the SL_mean of forests, but only the PC2 score was significantly associated with the SL_mean of grasslands (Fig. 2d–f). Our analysis directly shows that forests and grasslands differed significantly in the relationship between SL_mean and climate factors. The coexistence of grasses and forbs in grassland sites may help explain the ambiguous relationship found between SL_mean and climate factors at the community scale in grasslands. A more refined analysis based on exact species information could provide more insight into this question. Still, we believe that the above analysis can make readers acutely aware of the differences in stomatal trait-environment relationships between grasslands and forests. Fig. 2: Associations of community-weighted traits of stomatal morphology with environmental variables. Relationships between community-weighted mean of stomatal length (SL_mean) and precipitation of warmest quarter (a), temperature seasonality (b), temperature seasonality (c) and the first 3 principal components (d, e, f), within forests (F), grasslands (G) and all plots. PC1_score, PC2_score and PC3_score explained 62.7%, 19.7%, and 10.1% of total 19 climate variances. The green circle and yellow triangle represent forest and grassland sampling sites, respectively. All linear regressions with a confidence interval of 95% are estimated using the linear mixed model with plot nested within sites as a random factor. R2 is the marginal R2 (fixed effects only). Statistical analysis was performed using a two-sided t-test, and all results were considered significant at the p < 0.05 level. ns represents not significant. Full size image

A suite of models of different levels of complexity will be needed to fully understand the consequences of suppressing or incorporating detail into models, while insufficiently-detailed models may ignore critical internal heterogeneity9. The functional differences between different stomatal types is directly reflected by the speed of stomatal opening or closure, and is indirectly reflected by gas and water exchange speed. The differences in SL_mean and climatic factors between forests and grasslands observed in our analysis may reflect the influence of different stomatal types on the relationships between stomatal traits and environmental factors. Therefore, before further analyzing plant stomatal trait-environment relationships, it is necessary to establish a clear classification of stomatal types at different scales.

Clarifying the underlying mechanism of plant diverse adaptive strategies is the reason why we establish the relationship between plant traits and the environment. Here, we propose two basic principles of consistency should be followed when analyzing plant trait-environment relationships across increasingly expansive objects and scales.

Firstly, the function of one trait should be consistent for all research objects. For instance, the stomatal pore area index (SPI, calculated as stomatal density × stomatal length2; see also in Liu et al.2) is the most important trait to reflect the hydraulic conductance of the leaf lamina (K lamina ) for species with kidney-shaped guard cells10. However, for grasses with dumbbell-shaped guard cells, the leaves with equal SPI may have very different K lamina . This will lead to the mismatch between stomatal morphological traits and their functional implications and physiological consequences when grasses and non-grasses mixted together.

Secondly, the response patterns of a plant trait to a given environmental factor should be consistent across different plant groups. If inconsistent, researchers should conduct comparative analyses among these groups, rather than combining them, to scale up these relationships to broader levels and uncover more universal patterns. Taking the inconsistent (Fig. 2d, e) and even reversed (Fig. 2a, c) responses of log10(SL_mean) to climate variables between forests and grasslands for examples, we believe research on these responses cannot be extended to all study plots, but rather should be examined within the groups of grasslands and forests separately. For example, the responses of leaf lifespan to environmental conditions have been contrasted between deciduous and evergreen species11, where deciduous and evergreen oaks show contrasting adaptive responses in leaf mass per area across environments12; and specific leaf area has been found to decrease significantly in grasses of temperate systems in response to drought, but no significant response was found in forbs13.

Following the two principles above, we can avoid misleading generalizations and ensure that the unique traits and their responses to environmental variations of each ecosystem type are properly accounted for in analyses.