Trait interactions effects on tropical tree demography depend on the environmental context

Kamimura, Vitor de Andrade; Loiola, Priscilla de Paula; Carmona, Carlos P.; Assis, Marco Antônio; Joly, Carlos A.; Santos, Fábio Lúcio; Vieira, Simone Aparecida; Alves, Luciana F.; Martins, Valéria Forni; Ramos, Eliana; Ramos, Rafael; Bello, Francesco de

doi:10.1016/j.ppees.2023.125732

Cited by 2 publications

(9 citation statements)

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“…To explore the relationship between traits and growth rates, we used a decision tree‐based machine learning approach (RF). This type of model allows us to account for potential nonlinear relationships as well as interactions among predictors, and has been successfully used to analyze similar questions (Pistón et al., 2019; Kamimura et al., 2023). We generated a set of models using mixed‐effect RF with the SAEforest package in R (R Core Team, R Foundation for Statistical Computing, Vienna, AT) (Krennmair, 2022), specifying the species as a random intercept and individual relative growth as the response variable.…”

Section: Methodsmentioning

confidence: 99%

“…To explore the relationship between traits and growth rates, we used a decision tree-based machine learning approach (RF). This type of model allows us to account for potential nonlinear relationships as well as interactions among predictors, and has been successfully used to analyze similar questions (Pistón et al, 2019;Kamimura et al, 2023).…”

Section: Statistical Analysesmentioning

confidence: 99%

“…As a consequence, trait interactions could lead to many alternative functional designs, which may lead to similar fitness values in a given environment (Marks & Lechowicz, 2006). However, trait interactions are rarely considered when examining trait–performance relationships, potentially impacting the outcome of the model (Pistón et al., 2019; Worthy et al., 2020; Kamimura et al., 2023).…”

Section: Introductionmentioning

confidence: 99%

“…These different ecological strategies exhibited by the two leaf habits can lead to variations in relative growth rates (Tomlinson et al., 2014). However, some studies ignore that the relationship between traits and plant performance is context‐dependent (Kamimura et al., 2023) and model this relationship by pooling individuals growing in different environments, which can impede fully disentangling the trait–performance relationship (Yang et al., 2018).…”

Section: Introductionmentioning

confidence: 99%

“…In this sense, using simple models that disregard nonlinear relationships may not provide an accurate representation of the true trait–performance relationship. Using more holistic methods that allow us to analyze these relationships accounting for non‐linearities can help to better assess functional changes and plant performance within an environment (Pistón et al., 2019; Kamimura et al., 2023).…”

Section: Introductionmentioning

confidence: 99%

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Trait–growth relationships in Colombian tropical dry forests: Incorporating intraspecific variation and trait interactions

Rodríguez‐Alarcón,

González‐M,

Carmona

et al. 2024

J Vegetation Science

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QuestionTrait‐based ecology is built on the notion that traits impact individual performance, but trait–growth relationships have rarely been tested considering the intraspecific variation, trait interactions, and potential nonlinearity in these relationships.LocationSeven tropical dry forests throughout Colombia.MethodsWe examined trait–growth relationships in 263 woody species of tropical dry forests in Colombia, including trait and growth information measured in the same individuals. We measured height, stem, and leaf traits related to growth and hydraulic safety–efficiency in 967 individuals in seven permanent plots (1 ha). We assessed trait–growth relationships using random forest models for each plot with different trait resolutions (individual, plot, area) and complexity of trait interactions (low, medium, high).ResultsTrait–growth relationships were generally weak without significant differences among trait resolutions or levels of interactions between traits. However, when considering leaf phenology, the proportion of growth variation explained in deciduous species was almost three times higher than in evergreen species. Finally, we found that the effect of traits on growth was consistent across plots and phenological strategies, with both stem (vessel area and pit diameter aperture) and leaf (leaf area and specific leaf area) traits ranked as important predictors, the relevance of which depended on the species’ leaf phenology.ConclusionsOur findings indicate that growth is probably limited by different factors depending on the species’ physiology according to the leaf habit considered. However, other factors not included in the analysis, such as microenvironmental variability, might influence trait–growth relationships in tropical dry forests. Overall, our results suggest that a trait coordination approach at the whole‐plant level is needed to better understand plants’ performance and demographic rates in this ecosystem. Further studies on the traits of regional flora and consideration of longer growth periods would help to elucidate the dynamics governing trait composition in these forests, which is essential for the design of adequate forest restoration and conservation practices.

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Section: Methodsmentioning

confidence: 99%

Section: Statistical Analysesmentioning

confidence: 99%