Individual-based modelling of tropical forests: role of biodiversity and responses to drought

La faible représentation de la biodiversité dans les modèles de végétation a longtemps été un obstacle à la compréhension et à la projection des processus écosystémiques. La forte biodiversité des forêts tropicales, leur rôle clé dans les cycles biogéochimiques globaux, ainsi que leur vulnérabilité aux perturbations anthropiques directes et indirectes, amplifient les difficultés et enjeux de ces questions de recherche. En particulier, l'augmentation prédite de la fréquence et de l'intensité des sécheresses pourrait impacter la structure et composition floristique de ces forêts, comme dors et déjà observé au cours d'expériences naturelles et artificielles. Cette thèse explore ces questions de recherche à travers deux approches complémentaires, de modélisation et de mesures écophysiologiques. Dans le premier chapitre, je décris un simulateur de croissance forestière individu-centré et spatialement-explicite, TROLL, qui intègre les progrès récents en physiologie des plantes. Les processus sont paramétrés à l'aide de traits fonctionnels espèce-spécifiques, pour une forêt tropicale amazonienne. Une régénération forestière est simulée, et validée par des observations faites en Guyane française. La sensibilité du modèle à plusieurs paramètres globaux clés est évaluée. Enfin, l'influence de la variation de la richesse et composition spécifiques sur les propriétés écosystémiques est explorée. La réponse des forêts tropicales à la sécheresse est mal connue, empêchant la représentation pertinente des processus en jeu dans les modèles de végétation. Les chapitres 2 à 5 de cette thèse ont ainsi pour but de documenter la tolérance à la sécheresse et sa diversité dans une forêt amazonienne. Une méthode récente et rapide de détermination d'un trait de tolérance des feuilles à la sécheresse, le potentiel hydrique des feuilles au point de perte de turgescence (ptlp), est validée et utilisée, permettant de quantifier pour la première fois un tel trait de tolérance à la sécheresse dans une forêt amazonienne à l'échelle de la communauté. Ce jeu de données permet l'exploration des déterminants de la tolérance à la sécheresse des feuilles, à travers les espèces d'arbres, les tailles des individus, les stades de succession, les expositions à la lumière, ainsi que les lianes. La variabilité de ptlp observée suggère une large diversité de réponses à la sécheresse au sein des communautés de plantes amazoniennes. Ceci est confirmé par le suivi direct du flux de sève au cours d'une saison sèche sur divers arbres de canopée. Enfin, je discute les implications de ces résultats pour le développement des futurs modèles de végétation.A great part of uncertainties in our current understanding and projections of the carbon cycle lies in the vegetation compartment. The problem of biodiversity representation in vegetation models has long been an impediment to a detailed understanding of ecosystem processes. The high biodiversity of tropical forests, their disproportionate role in global biogeochemical cycles, together with their vulnerability to direct and indirect anthropogenic perturbations, amplify the relevance of this research challenge. In particular, the predicted increase in drought intensity and frequency in the tropics may impact forest structure and composition, as already observed in natural and artificial experiments. This thesis explores how new advances in modelling and ecophysiology should help improve our understanding of these processes in the future. In the first chapter, I describe an individual-based and spatially-explicit forest growth simulator, TROLL, that integrates recent advances in plant physiology. Processes are linked to species-specific functional traits parameterized for an Amazonian tropical rainforest. This model is used to simulate a forest regeneration, which is validated against observations in French Guiana. Model sensitivity is assessed for a number of key global parameters. Finally, we test the influence of varying the species richness and composition on ecosystem properties. Tropical forest response to drought is not well understood, and this hampers attempts to model these processes. In chapters 2 to 5 I aimed at documenting drought-tolerance and its diversity in an Amazonian forest. A rapid method of determination of a leaf drought tolerance trait, the leaf water potential at turgor loss point (ptlp), was validated and applied to a range of plant species. We established the first community-wide assessment of drought tolerance in an Amazonian forest. These results inform on the drivers and determinants of leaf drought tolerance, across tree species and lianas, tree size, successional stages, light exposition, and seasons. Variability in ptlp among species indicates the potential for a range of species responses to drought within Amazonian forest communities. This is further confirmed by direct monitoring of whole-plant water use on diverse canopy trees during a marked dry season. Finally, I discuss the implications of these results to increase the dialogue between the vegetation modeling community and ecology, to enhance model's predictive ability, and to inform policy choices

Identifying uncertainties in scenarios and models of socio-ecological systems in support of decision-making

There are many sources of uncertainty in scenarios and models of socio-ecological systems, and understanding these uncertainties is critical in supporting informed decision-making about the management of natural resources. Here, we review uncertainty across the steps needed to create socio-ecological scenarios, from narrative storylines to the representation of human and biological processes in models and the estimation of scenario and model parameters. We find that socio-ecological scenarios and models would benefit from moving away from “stylized” approaches that do not consider a wide range of direct drivers and their dependency on indirect drivers. Indeed, a greater focus on the social phenomena is fundamental in understanding the functioning of nature on a human-dominated planet. There is no panacea for dealing with uncertainty, but several approaches to evaluating uncertainty are still not routinely applied in scenario modeling, and this is becoming increasingly unacceptable. However, it is important to avoid uncertainties becoming an excuse for inaction in decision-making when facing environmental challenges.</p

The function-dominance correlation drives the direction and strength of biodiversity-ecosystem functioning relationships

Community composition is a primary determinant of how biodiversity change influences ecosystem functioning and, therefore, the relationship between biodiversity and ecosystem functioning (BEF). We examine the consequences of community composition across six structurally realistic plant community models. We find that a positive correlation between species' functioning in monoculture versus their dominance in mixture with regard to a specific function (the "function-dominance correlation") generates a positive relationship between realised diversity and ecosystem functioning across species richness treatments. However, because realised diversity declines when few species dominate, a positive function-dominance correlation generates a negative relationship between realised diversity and ecosystem functioning within species richness treatments. Removing seed inflow strengthens the link between the function-dominance correlation and BEF relationships across species richness treatments but weakens it within them. These results suggest that changes in species' identities in a local species pool may more strongly affect ecosystem functioning than changes in species richness

Global transpiration data from sap flow measurements : the SAPFLUXNET database

Plant transpiration links physiological responses of vegetation to water supply and demand with hydrological, energy, and carbon budgets at the land-atmosphere interface. However, despite being the main land evaporative flux at the global scale, transpiration and its response to environmental drivers are currently not well constrained by observations. Here we introduce the first global compilation of whole-plant transpiration data from sap flow measurements (SAPFLUXNET, https://sapfluxnet.creaf.cat/, last access: 8 June 2021). We harmonized and quality-controlled individual datasets supplied by contributors worldwide in a semi-automatic data workflow implemented in the R programming language. Datasets include sub-daily time series of sap flow and hydrometeorological drivers for one or more growing seasons, as well as metadata on the stand characteristics, plant attributes, and technical details of the measurements. SAPFLUXNET contains 202 globally distributed datasets with sap flow time series for 2714 plants, mostly trees, of 174 species. SAPFLUXNET has a broad bioclimatic coverage, with woodland/shrubland and temperate forest biomes especially well represented (80 % of the datasets). The measurements cover a wide variety of stand structural characteristics and plant sizes. The datasets encompass the period between 1995 and 2018, with 50 % of the datasets being at least 3 years long. Accompanying radiation and vapour pressure deficit data are available for most of the datasets, while on-site soil water content is available for 56 % of the datasets. Many datasets contain data for species that make up 90 % or more of the total stand basal area, allowing the estimation of stand transpiration in diverse ecological settings. SAPFLUXNET adds to existing plant trait datasets, ecosystem flux networks, and remote sensing products to help increase our understanding of plant water use, plant responses to drought, and ecohydrological processes. SAPFLUXNET version 0.1.5 is freely available from the Zenodo repository (https://doi.org/10.5281/zenodo.3971689; Poyatos et al., 2020a). The "sapfluxnetr" R package - designed to access, visualize, and process SAPFLUXNET data - is available from CRAN.Peer reviewe

The value of coarse species range maps to inform local biodiversity conservation in a global context

International audienc

Improving plant allometry by fusing forest models and remote sensing

International audienceAllometry determines how tree shape and function scale with each other, related through size. Allometric relationships help scale processes from individual to global scale, and they constitute a core component of vegetation models. Allometric relationships have been expected to emerge from optimization theory, yet this does not suitably predict empirical data. Here we argue that the fusion of high-resolution data, such as those derived from airborne laser scanning, with individual-based forest modelling offers insight into how plant size contributes to large scale biogeochemical processes. We review the challenges in allometric scaling, how they can be tackled by advances in data-model fusion, and how individual-based models can serve as data integrators for dynamic global vegetation models

Rethinking the role of intraspecific variability in species coexistence

International audienceHow species coexist while competiting for the same resources is a long-standing question in community ecology, particularly for hyperdiverse communities like tropical forests. In the past decades, intraspecific variability (IV) and its ecological consequences became of major interest, and IV was perceived as a potential mechanism enabling species coexistence, with contrasting results in the literature however.We argue that taking the nature of IV into account is important to understand its effects on coexistence, and hypothesise that environmental variation alone can produce IV in performance.Focusing on spatial environmental variation, we build a body of evidence to support this idea. First, we use a theoretical model using virtual data of individual growth across environmental gradients, using less explicative environmental variables in the model than to generate the data. Second we analyse a Eucalyptus clonal dataset in Brazil. Lastly we analyse three datasets from contrasting tropical forests : Paracou in French Guiana (Amazonia), Barro Colorado Island in Panama (Central America) and Uppangala in the Western Ghats in India (Southeast Asia).The theoretical model shows that observed IV can emerge due to the lower dimensionality of field observations compared with the high dimensionality of the environment, without any intrinsic differences between conspecifics; the clonal dataset analysis shows that IV can emerge from exogenous factors; the tropical dataset analyses show that IV in growth is high in tropical forests, that growth is broadly spatially autocorrelated, which we suppose is a mark of its environmental origin, and that locally, conspecifics have a more similar growth than heterospecifics.This body of evidence shows that IV can emerge from environmental variation and without any intrinsic differences between conspecific individuals. Based on theory, which shows that intraspecific competition must be stronger than interspecific competition to enable species coexistence, we link higher local similarity to higher competition and conclude that intraspecific variability does not preclude this condition, enabling multiple species to coexist in high dimensional and spatially structured environments

Causes of variation in leaf-level drought tolerance within an Amazonian forest

International audienceAmazonian tree communities have already been seriously impacted by extreme natural droughts, and intense droughts are predicted to increase in frequency. However, our current knowledge of Amazonian tree species' responses to water stress remains limited, as plant trait databases include few drought tolerance traits, impeding the application and predictive power of models. Here we explored how leaf water potential at turgor loss point (π tlp), a determinant of leaf drought tolerance, varies with species life history, season, tree size and irradiance within a forest in French Guiana. First, we provided a further direct validation of a rapid method of π tlp determination based on osmometer measurements of leaf osmotic potential at full hydration for five Amazonian tree species. Next, we analysed a dataset of 131 π tlp values for a range of species, seasons, size (including saplings), and leaf exposure. We found that early-successional species had less drought-tolerant leaves than late-successional species. Species identity was the major driver of π tlp variation, whereas season, canopy tree size and leaf exposure explained little variation. Shifts in π tlp from saplings to canopy trees varied across species, and sapling leaf drought tolerance was a moderate predictor of canopy tree leaf drought tolerance. Given its low within-species variability, we propose that π tlp is a robust trait, and is useful as one index of species' drought tolerance. We also suggest that measuring this trait would considerably advance our knowledge on leaf drought tolerance in hyperdiverse communities and would thus likely shed light on the resilience of such vulnerable species-rich ecosystem