The research group led by Prof. Dr. Sylvia Haider recently published a study about the diversity of leaf designs in forests, aiming at understanding the importance of the variability within species (and even within single trees). Being involved in TreeDì, a Sino-German graduate school which aims at understanding the causes and consequences of tree-tree interactions in Chinese subtropical forests, the research group conducted their study in BEF-China, the world’s largest experiment investigating the relationship between forest diversity and ecosystem functions.

The many facets of trait-based ecology

The field of trait-based ecology, which examines how plant characteristics (’traits’) explain ecological processes, has focused mostly on differences between species. However, the intraspecific (within species) and even intraindividual (within individual plants) trait variability that occurs in leaves should not be overlooked as it could explain hidden aspects of ecosystem processes. In their study, Castro Sánchez-Bermejo and colleagues showed that the diversity of leaf designs within a tree species itself also contributes significantly to the functional diversity of a forest.

Functional traits of leaves can vary, even within a species

Little is known about this fine-scale variability of traits, yet it may be crucial for forest functioning. That’s why the researchers wanted to find out how intraspecific and intraindividual variability change along a diversity gradient and what that means for tree-tree interactions. To find an answer they examined leaves from eight tree species in forest stands representing a diversity gradient from species-poor monocultures to species-rich mixed forests. Various leaf characteristics related to the use of resources were recorded to analyse differences between individuals of the same species (e.g. the content of leaf nitrogen, which is abundant in photosynthetic molecules, was used as a proxy of photosynthetic activity).

Behind the scenes of measuring leaf diversity

Examining 4,568 leaves from 381 trees including five functional traits in each leaf resulted in a total of 22,840 measurements. If you think that sounds like a lot of work, well, you’re right! That’s why the researchers decided to combine leaf spectroscopy and machine learning pipelines to ‘phenotype’ all leaves. With the help of this method, they could detect the morphological and chemical traits of leaves optically.

A glimpse at the results

To give you an overview of the study’s results, here’s what the researchers found out:

Intraspecific variability decreases with a higher species richness. What does this mean? In species-poor monocultures, trees of the same species try to have different leaves to reduce competition within their species. This reflects a kind of ‘functional trait shyness’, as the trees seem to avoid each other in terms of their functional strategies. In mixtures, i.e. more species-rich forests, that is less necessary since ecological niches are already divided by differences between the species. Therefore, in mixtures the trees have more similar leaves. Regarding intraindividual variability, monocultures, which are characterized by less structured canopies, create an uneven light distribution within individual trees that could explain the high leaf variation within a single tree compared to mixtures.

Info: Functional richness & functional divergence:

Functional richness and functional divergence are two metrics that describe how a ‘trait space’ that represents the range of trait values possible, is being occupied by, for instance, one tree species. A higher functional richness relates to a higher number of functional strategies used. Meanwhile, a high functional divergence means that the dominant functional strategies within a species are very different from each other. Therefore, a low functional divergence indicates that there is one very common strategy while other traits present are rarely represented. The following figure helps envisioning the metrics.

Trees use their resources cleverly

The study’s results show that both sources of trait variation, intraspecific and intraindividual, make tree communities functionally richer. Intraspecific variability increases functional richness while intraindividual variability contributes to functional divergence – leading to a more complex distribution of traits. The patterns found suggest that trees occupy different parts of the ‘trait space’, meaning that the set of strategies used by one trait is different compared to the neighbour tree. As Castro Sánchez-Bermejo explains, each tree seems to develop different strategies to minimise competitions with its neighbours, even with those that are from the same species. Isn’t that something? This leads to an astonishing amount and diversity of trees’ strategies to use the forests’ resources such as water, light or nutrients efficiently.

What can future research learn from this study?

As the findings reveal, the phenotypic diversity within a species can be of great importance. Therefore, protecting species alone may not be as sufficient to maintain biodiversity as one might think. Understanding the patterns of trait variation could reveal new facets of the mechanisms behind ecosystem functioning of forests. In order to fully grasp processes occurring at local levels, we also need to move from a species-based trait ecology to an individual-based trait ecology.

You want to learn more about the trait variability of trees and the study’s findings or methods? Then read the full article here, at the journal Nature Communications:  https://www.nature.com/articles/s41467-025-67265-8

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