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Marechaux, I.

Publications and source records attributed to Marechaux, I..

3 recordsLinked to original sources

Trait diversity enhances biomass gains via canopy packing in old-growth but not in disturbed Amazon forests.

The existence of a causal link between biodiversity and forest productivity remains largely unexplored in natural systems, especially in hyper-diverse tropical forests. Canopy packing-- greater crown complementarity, resulting in more densely packed canopies--has recently emerged as a key structural pathway through which diversity influences forest functioning, though evidence remains limited and sometimes contradictory.In this study, we used repeated airborne LiDAR acquisitions and long-term field monitoring from a tropical logging experiment in French Guiana to quantify canopy packing using the Shannon evenness of plant area density (PAD) and assess its role in mediating the relationship between trait diversity and biomass gains in old-growth and disturbed Amazonian forest stands.Our results show that, in undisturbed forests, functionally diverse communities promote greater canopy packing, which in turn enhances biomass gains. However, this effect was absent in previously logged stands, where forest structural diversity did not fully recover even after 40 years. Our findings indicate that logging reduces canopy structural complexity and disrupts the link between species composition, canopy packing, and productivity in these hyper-diverse, hyper-productive ecosystems. Significance StatementIn this study, measurements from repeated airborne LiDAR acquisitions and long-term field monitoring from a tropical logging experiment in the Amazon forest are used to understand the causal link between biodiversity and forest productivity. The study shows that greater crown complementarity mediates diversity-productivity relationships, with functionally diverse communities promoting greater canopy packing, which in turn enhances biomass gains. However, this effect is lost in disturbed forests. These findings are relevant for understand the ecological mechanisms driving forest productivity and tropical forests response to disturbance and for forest carbon management strategies.

ecology↗

Beyond variance: simple random distributions are not a good proxy for intraspecific variability in systems with environmental structure

The role of intraspecific variability (IV) in shaping community dynamics and species coexistence has been intensively discussed over the past decade and modelling studies have played an important role in that respect. However, these studies often implicitly assume that IV can be represented by independent random draws around speciesspecific mean parameters. This major assumption has largely remained undiscussed, although a great part of observed IV is structured in space or time, in particular when environmental dimensions that influence individual performance are imperfectly characterised or unobserved in the field. To test the impact of this strong assumption on the outcome of community dynamics models, we designed a simulation experiment where we varied the level of knowledge of the environment in virtual communities, resulting in different relative importance of explained vs unexplained spatial individual variation in performance. We used a community dynamics simulator to generate communities where the unexplained individual variation is, or is not, added as an unstructured random noise. Communities simulated with unstructured IV never reached the community diversity and composition of those where all the variation was explained and structured (perfect knowledge model). This highlights that incorporating unstructured IV (i.e. a random noise) to account for unexplained (but structured) variation can lead to incorrect simulations of community dynamics. In addition, the effects of unstructured IV on community diversity and composition depended on the relative importance of structured vs unstructured IV, i.e. on the level of knowledge of the environment, which may partly explain the contrasting results of previous studies on the effect of IV on species coexistence. In particular, the effect of unstructured IV on community diversity was positive when the proportion of structured IV vs unstructured IV in the model was low, but negative when this proportion was high. This is because unstructured random noise can either limit the competitive exclusion of inferior competitors in low dimensions or destabilise tight niche partitioning in high dimension. Our study suggests that it is crucial to account for the sources and structure of observed IV in real communities to better understand its effect on community assembly and properly include it in community dynamics models.

ecology↗

Rethinking the role of intraspecific variability in species coexistence

ContextIntraspecific variability (IV) has been proposed to explain species coexistence in diverse communities. Assuming, sometimes implicitly, that conspecific individuals can perform differently in the same environment and that IV blurs species differences, previous studies have found contrasting results regarding the effect of IV on species coexistence. ObjectiveWe aim at showing that the large IV observed in data does not mean that conspecific individuals are necessarily different in their response to the environment and that the role of high-dimensional environmental variation in determining IV has been largely underestimated in forest plant communities. Methods and ResultsWe first used a simulation experiment where an individual attribute is derived from a high-dimensional model, representing "perfect knowledge" of individual response to the environment, to illustrate how a large observed IV can result from "imperfect knowledge" of the environment. Second, using growth data from clonal Eucalyptus plantations in Brazil, we estimated a major contribution of the environment in determining individual growth. Third, using tree growth data from long-term tropical forest inventories in French Guiana, Panama and India, we showed that tree growth in tropical forests is structured spatially and that despite a large observed IV at the population level, conspecific individuals perform more similarly locally than compared with heterospecific individuals. SynthesisAs the number of environmental dimensions that are typically quantified is generally much lower than the actual number of environmental dimensions influencing individual attributes, a great part of observed IV might be misinterpreted as random variation across individuals when in fact it is environmentally-driven. This mis-representation has important consequences for inference about community dynamics. We emphasize that observed IV does not necessarily impact species coexistence per se but can reveal species response to high-dimensional environment, which is consistent with niche theory and the observation of the many differences between species in nature.

ecology↗