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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 species-specific 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.

Intraspecific 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 increases niche overlap, previous studies have found contrasting results regarding the effect of IV on species coexistence. We 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 largely remained unexplored in forest plant communities. We 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 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. As the number of environmental dimensions that are well quantified at fine scale is generally lower than the actual number of dimensions influencing individual attributes, a great part of observed IV might be represented 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

Background and aims: Several studies have shown an increase in tree mortality in intact tropical forests in recent decades. However, most studies are based on networks of field plots whose representativeness is debated. We examine the potential of repeated Airborne LiDAR Scanning data to map forest structure change over large areas with high spatial resolution and to detect tree mortality patterns at landscape level. Methods: The study site is a complex forested landscape in French Guiana with varied topographic positions, vegetation structures and disturbance history. We computed a Gap Dynamics Index from Canopy Height Models derived from successive LiDAR data sets (2009, 2015 and 2019) that we compared to field-measured mortality rates (in stem number and basal area loss) obtained from regular monitoring of 74 1.56-ha permanent plots. Results: At the plot level, the relation between gap dynamics and absolute basal area loss rate (combining fallen and standing dead trees) was overall highly significant (R2 = 0.60) and especially tight for the 59 ha of unlogged forest (R2 = 0.72). Basal area loss rate was better predicted from gap dynamics than stem loss rate. In particular, in previously logged plots, intense self-thinning of small stems did not translate into detectable gaps, leading to poor predictability of stem mortality by LiDAR in those forests severely disturbed 30 years before. At the landscape scale, LiDAR data revealed spatial patterns of gap creation that persisted over the successive analysis periods. Those spatial patterns were related to local topography and canopy height. High canopy forests and bottomlands were more dynamic, with a higher fraction of canopy affected by gaps per unit time indicating higher basal area loss rates. Conclusion: Gap detection and mapping via multitemporal LiDAR data is poised to become instrumental in characterizing landscape-scale forest response to current global change. Meaningful comparison of gap dynamics across time

The role of biodiversity on ecosystem functioning is increasingly discussed in a multifunctionality context. However, assessing multiple performances in natura is complex and applied perspectives remain scarce. Interestingly, the growing interest for varietal mixtures in agronomy represents a unique opportunity to challenge the role of intraspecific diversity for the regulation of multiple outcomes at the same time. This is the case for rice production in Madagascar. Especially, as the highlands region is increasingly impacted by climate change and by the socio-economic burden resulting from these environmental changes. Pests and pathogens are placing undue pressure on rice crops while disease resistance is also being affected by climate change. The effect of varietal diversity on upland-rice multifunctionality, as well as yield components and resistance to Pyricularia were assessed and quantified during a two-year trial in the highlands of Madagascar. In the first year of the trial, binary mixtures of ten phenotypically contrasted varieties were established. Based on these first-year results, the four most contrasting varieties were selected to repeat the field trial the following season, this time with the inclusion of two levels of fertilization (high and low). First-year results showed that the crop susceptibility to blast disease was reduced by 6.5% in the mixed plots compared to plots with pure stand. Furthermore, varietal mixture generated a yield gain of 13% compared to pure crops in the first year and a yield gain of 17% in the second year under low fertilization. In the highly fertilized treatment, however, the gain was reduced to 4%. In order to identify the multifunctional variety combinations, a functional classification using a combinatorial model was used. Our results suggest that varietal association composed of different functional groups promotes the multifunctionality of cropping systems, when cultivated in suboptimal conditions for plant growth.

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.

Aim: Tree crowns determine light interception, carbon and water exchange. Thus, understanding the factors causing tree crown allometry to vary at the tree and stand level matters greatly for the development of future vegetation modelling and for the calibration of remote sensing products. Nevertheless, we know little about large-scale variation and determinants in tropical tree crown allometry. In this study, we explored the continental variation in scaling exponents of site-specific crown allometry and assessed their relationships with environmental and stand-level variables in the tropics. Location: Global tropics. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: Using a dataset of 87,737 trees distributed among 245 forest and savanna sites across the tropics, we fitted site-specific allometric relationships between crown dimensions (crown depth, diameter and volume) and stem diameter using power-law models. Stand-level and environmental drivers of crown allometric relationships were assessed at pantropical and continental scales. Results: The scaling exponents of allometric relationships between stem diameter and crown dimensions were higher in savannas than in forests. We identified that continental crown models were better than pantropical crown models and that continental differences in crown allometric relationships were driven by both stand-level (wood density) and environmental (precipitation, cation exchange capacity and soil texture) variables for both tropical biomes. For a given diameter, forest trees from Asia and savanna trees from Australia had smaller crown dimensions than trees in Africa and America, with crown volumes for some Asian forest trees being smaller than those of trees in African forests. Main conclusions: Our results provide new insight into geographical variability, with large continental differences in tropical tree crown allometry that were driven by stand-level and environmental variables. They have implic, SCOPUS: ar.j, info:eu-repo/semantics/published

The Paris Climate Agreements and Sustainable Development Goals, signed by 197 countries, present agendas and address key issues for implementing multi-scale responses for sustainable development under climate change—an effort that must involve local, regional, national, and supra-national stakeholders. In that regard, Continental Carbon Sequestration (CoCS) and conservation of carbon sinks are recognized increasingly as having potentially important roles in mitigating climate change and adapting to it. Making that potential a reality will require indicators of success for various stakeholders from multidisciplinary backgrounds, plus promotion of long-term implementation of strategic action towards civil society (e.g., law and policy makers, economists, and farmers). To help meet those challenges, this discussion paper summarizes the state of the art and uncertainties regarding CoCS, taking an interdisciplinary, holistic approach toward understanding these complex issues. The first part of the paper discusses the carbon cycle's bio-geophysical processes, while the second introduces the plurality of geographical scales to be addressed when dealing with landscape management for CoCS. The third part addresses systemic viability, vulnerability, and resilience in CoCS practices, before concluding with the need to develop inter-disciplinarity in sustainable science, participative research, and the societal implications of sustainable CoCS actions.

Wood density (WD) relates to important tree functions such as stem mechanics and resistance against pathogens. This functional trait can exhibit high intraindividual variability both radially and vertically. With the rise of LiDAR-based methodologies allowing nondestructive tree volume estimations, failing to account for WD variations related to tree function and biomass investment strategies may lead to large systematic bias in AGB estimations. Here, we use a unique destructive dataset from 822 trees belonging to 51 phylogenetically dispersed tree species harvested across forest types in Central Africa to determine vertical gradients in WD from the stump to the branch tips, how these gradients relate to regeneration guilds and their implications for AGB estimations. We find that decreasing WD from the tree base to the branch tips is characteristic of shade-tolerant species, while light-demanding and pioneer species exhibit stationary or increasing vertical trends. Across all species, the WD range is narrower in tree crowns than at the tree base, reflecting more similar physiological and mechanical constraints in the canopy. Vertical gradients in WD induce significant bias (10%) in AGB estimates when using database-derived species-average WD data. However, the correlation between the vertical gradients and basal WD allows the derivation of general correction models. With the ongoing development of remote sensing products providing 3D information for entire trees and forest stands, our findings indicate promising ways to improve greenhouse gas accounting in tropical countries and advance our understanding of adaptive strategies allowing trees to grow and survive in dense rainforests.

Aim: Examining tree species–environment association can offer insight into the drivers of vegetation patterns and key information of practical relevance to forest management. Here, we aim to quantify the contribution of climate and soil gradients to variation in Central African tree species composition (abundance and occurrence). Location: Tropical rain forests of southern and eastern Cameroon. Methods: We established 82 1-ha permanent plots across seven localities and censused all trees ≥10 cm in diameter, representing a total of 37,733 trees and 455 species. In 60 of those plots, we measured 10 soil variables describing texture and nutrients levels and extracted 10 bioclimatic variables from global-gridded climate databases. We synthesized the main environmental gradients by conducting principal component analyses on climate and soil data, respectively. We performed unconstrained and constrained non-symmetric correspondence analyses to account for the individual and joint contributions of climate and soil on species abundance and occurrence. Results: Climate and soil contributed similarly to variances of species abundance and occurrence (12–15% variance for climate vs 11–12% variance for soil). Climate influence mostly concerns some abundant species, while some of the less abundant species were mainly driven by soil. Fractions of species variances accounted for by climate and soil show strong correlation when assessed from species occurrence and abundance data. Conclusion: Variation in occurrence and abundance of tropical forest trees can be partly shaped by both climate and soil gradients in Cameroon, which emphasizes the importance to jointly consider soil and climate in species distribution modeling. Less abundant species may express environmental influence differently than abundant species and convey complementary information about community assemblage. Though showing congruent patterns here, species abundance and occurrence reflect different interacting commu, SCOPUS: ar.j, info:eu-repo/semantics/published