September 01, 2017
Variations of Leaf Longevity in Tropical Moist Forests Predicted by a Trait-Driven Carbon Optimality Model
Developing a new model to capture large intraspecific variability in leaf longevity of 105 tropical tree species within two tropical moist forests in Panama.
Leaf longevity (LL), how long a leaf lives, is closely linked to plant resource use, carbon uptake, and growth strategy. In tropical forests, there is remarkable diversity in LL across species, ranging from several weeks to six years or more. However, it remains unclear how to capture such large variation using predictive models. Here, the scientists present a meta-analysis of 49 species across temperate and tropical biomes. Their results show that the leaf aging rate is positively correlated with the mass-based carbon uptake rate of mature leaves. They further developed an LL model to capture leaf aging rate and evaluated it with LL data for 105 species, measured in two tropical forests in Panama. Their results show that the new model explains over 40% of the cross-species variation in LL, including those species sampled from both canopy and understory. Collectively, the results reveal how variation in LL is constrained by both leaf structural traits and the growth environment.
Leaf longevity has been recognized as critical for understanding tropical seasonality and carbon dynamics. The proposed leaf longevity model can be used in next-generation Earth system models (ESMs) to improve projections of carbon dynamics and potential climate feedbacks in the tropics.
The scientists use a trait-based carbon optimality approach to model LL, in days, and assess the model performance with in situ LL data for 105 species in two tropical forests in Panama. More specifically, they examine the relative impact of leaf aging rate (i.e., the rate at which leaf photosynthetic capacity declines with age) and within-canopy variation in light environment on the modeled LL. They first assumed that all species have the same leaf aging rate (i.e., the community average value) and receive the same light condition (i.e., canopy-level light). The results are correlated with coefficient r = 0.08, which is not significant. Then they performed the analysis with species-specific leaf aging rates, while assuming that all species receive the same light condition (i.e., canopy-level light), and the results are r = 0.53 and p-value <<0.001. Lastly, they performed the analysis with species-specific leaf aging rate and light environment, and the results are r = 0.66 and p-value <<0.001. Their results thus suggest that both leaf aging rate and within-canopy variation in light environment are essential for modeling LL in the tropics, and the best model can capture over 40% of interspecific variability in LL, including those species from canopy and understory.
Brookhaven National Laboratory
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Environmental System Science
J. Wu was supported by the Next-Generation Ecosystem Experiments (NGEE)–Tropics project. The NGEE-Tropics project is supported by the Office of Biological and Environmental Research within the U.S. Department of Energy Office of Science.
Xu, X., D. Medvigy, S. J. Wright, and K. Kitajima, et al. "Variations of leaf longevity in tropical moist forests predicted by a trait-driven carbon optimality model." Ecology Letters 20 (9), 1097–1106 (2017). https://doi.org/10.1111/ele.12804.