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. 2015 Sep 25:5:14454.
doi: 10.1038/srep14454.

Latitudinal variation of leaf stomatal traits from species to community level in forests: linkage with ecosystem productivity

Ruili Wang  1   2 , Guirui Yu  1 , Nianpeng He  1 , Qiufeng Wang  1 , Ning Zhao  1   2 , Zhiwei Xu  1   2 , Jianping Ge  3
Affiliations

Latitudinal variation of leaf stomatal traits from species to community level in forests: linkage with ecosystem productivity

Ruili Wang et al. Sci Rep. .

Abstract

To explore the latitudinal variation of stomatal traits from species to community level and their linkage with net primary productivity (NPP), we investigated leaf stomatal density (SDL) and stomatal length (SLL) across 760 species from nine forest ecosystems in eastern China, and calculated the community-level SD (SDC) and SL (SLC) through species-specific leaf area index (LAI). Our results showed that latitudinal variation in species-level SDL and SLL was minimal, but community-level SDC and SLC decreased clearly with increasing latitude. The relationship between SD and SL was negative across species and different plant functional types (PFTs), but positive at the community level. Furthermore, community-level SDC correlated positively with forest NPP, and explained 51% of the variation in NPP. These findings indicate that the trade-off by regulating SDL and SLL may be an important strategy for plant individuals to adapt to environmental changes, and temperature acts as the main factor influencing community-level stomatal traits through alteration of species composition. Importantly, our findings provide new insight into the relationship between plant traits and ecosystem function.

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Figures

Figure 1
Figure 1. Geographic locations and vegetation types of the sampling sites.
JF, Jianfengling; DH, Dinghu; JL, Jiulian; SN, Shennongjia; TY, Taiyue; DL, Dongling; CB, Changbai; LS, Liangshui; HZ, Huzhong. The north-south transect of eastern China (NSTEC) is highlighted with different colors representing different vegetation types. The map is generated using ArcGIS 10.0 software.
Figure 2
Figure 2. Statistics of stomatal density (SDL, (A)) and stomatal length (SLL, (B)) across 760 species.
N, species number; Max, maximum; Min, minimum; SE, standard error; CV, coefficient of variation.
Figure 3
Figure 3. Box plots of stomatal density (SDL, (A)) and stomatal length (SLL, (B)) across different plant functional types (PFTs).
The solid and dashed lines across the middle of the box are mean and median values, respectively. N, species number. Statistical differences (P < 0.05) are denoted by different letters using one-way analysis of variance (ANOVA).
Figure 4
Figure 4
Relationships between stomatal density (SD) and stomatal length (SL) at the species (A) and community levels (B). n, number of observations. Error bars in panel (B) represent ± 1 standard error.
Figure 5
Figure 5
Standardized major axis (SMA) regressions between species-level stomatal density (SDL) and stomatal length (SLL) across different growth types (A) and leaf habits (B). “Slope”, difference in SMA slopes; “Elevation”, difference in SMA elevations (i.e. y-axis intercept); *significantly different (P < 0.05); NS, not significantly different (P > 0.05). Sample size and results of regression analyses are presented in Supplementary Table S3.
Figure 6
Figure 6
Latitudinal trends of stomatal density (SD) and stomatal length (SL) at the species (A) and community levels (B). n, number of observations. Error bars in panel (B) represent ± 1 standard error.
Figure 7
Figure 7. Relationships between stomatal traits and environmental variables.
SDL, SLL, SDC, and SLC are the stomatal density and length at the species and community levels, respectively. Environmental variables include mean annual temperature (MAT), mean annual precipitation (MAP), and soil N. n, number of observations. Error bars in panels (D) and (E) represent ± 1 standard error.
Figure 8
Figure 8. Relationships between net primary productivity (NPP) and community-level stomatal density (SDC, (A)) and stomatal length (SLC, (B)).
n, number of observations. Error bars represent ± 1 standard error.
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