Taxonomic diversity effects on forest productivity and response to climate extremes range from positive to negative, suggesting a key role for complex interactions among neighbouring trees. To elucidate how neutral interactions, hierarchical competition and resource partitioning between neighbours’ shape tree growth and climate response in a highly diverse Amazonian forest, we combined 30 years of tree censuses with measurements of water‐ and carbon‐related traits. We modelled individual tree growth response to climate and neighbourhood to disentangle the relative effect of neighbourhood densities, trait hierarchies and dissimilarities. While neighbourhood densities consistently decreased growth, trait dissimilarity increased it, and both had the potential to influence climate response. Greater water conservatism provided a competitive advantage to focal trees in normal years, but water–spender neighbours reduced this effect in dry years. By underlining the importance of density and trait‐mediated neighbourhood interactions, our study offers a way towards improving predictions of forest dynamics.

The biodiversity of tropical rainforest is difficult to assess. Yet, its estimation is necessary for conservation purposes, to evaluate our level of knowledge and the risks faced by the forest in relation to global change. Our contribution is to estimate the regional richness of tree species from local but widely spread inventories. We reviewed the methods available, which are nonparametric estimators based on abundance or occurrence data, log-series extrapolation and the universal species–area relationship based on maximum entropy. Appropriate methods depend on the scale considered. Harte’s self-similarity model is suitable at the regional scale, while the log-series extrapolation is not. GuyaDiv is a network of forest plots installed over the whole territory of French Guiana, where trees over 10 cm DBH are identified. We used its information (1315 species censused in 68 one-hectare plots) to estimate the exponent of the species–area relationship, assuming Arrhenius’s power law. We could then extrapolate the number of species from three local, wide inventories (over 2.5 km2). We evaluated the number of tree species around 2200 over the territory.

Over the last decade, distance-based methods have been introduced and then improved in the field of spatial economics to gauge the geographic concentration of activities. There is a growing literature on this theme including new tools, discussions on their specific properties and various applications. However, there is currently no typology of distance-based methods. This paper fills that gap. The proposed classification helps understand all the properties of distance-based methods and proves that they are variations on the same framework.

Measuring functional or phylogenetic diversity is the object of an active literature. The main issues to address are relating measures to a clear conceptual framework, allowing unavoidable estimation-bias correction and decomposing diversity along spatial scales. We provide a general mathematical framework to decompose measures of species-neutral, phylogenetic or functional diversity into $\alpha$ and $\beta$ components. We first unify the definitions of phylogenetic and functional entropy and diversity as a generalization of HCDT entropy and Hill numbers when an ultrametric tree is considered. We then derive the decomposition of diversity. We propose a bias correction of the estimates allowing meaningful computation from real, often undersampled communities. Entropy can be transformed into true diversity, that is an effective number of species or communities. Estimators of $\alpha$- and $\beta$-entropy, phylogenetic and functional entropy are provided. Proper definition and estimation of diversity is the first step towards better understanding its underlying ecological and evolutionary mechanisms.

Species’ traits and environmental conditions determine the abundance of tree species across the globe. The extent to which traits of dominant and rare tree species differ remains untested across a broad environmental range, limiting our understanding of how species traits and the environment shape forest functional composition. We use a global dataset of tree composition of >22,000 forest plots and 11 traits of 1663 tree species to ask how locally dominant and rare species differ in their trait values, and how these differences are driven by climatic gradients in temperature and water availability in forest biomes across the globe. We find three consistent trait differences between locally dominant and rare species across all biomes; dominant species are taller, have softer wood and higher loading on the multivariate stem strategy axis (related to narrow tracheids and thick bark). The difference between traits of dominant and rare species is more strongly driven by temperature compared to water availability, as temperature might affect a larger number of traits. Therefore, climate change driven global temperature rise may have a strong effect on trait differences between dominant and rare tree species and may lead to changes in species abundances and therefore strong community reassembly.

Lianas are important components of tropical forest diversity and dynamics, yet little is known about the drivers of their community structure and composition. Combining extensive field and LiDAR data, we investigated the influence of local topography, forest structure, and tree composition on liana community structure, and their floristic and functional composition, in a moist forest in northern Republic of Congo. We inventoried all lianas ≥ 1 cm in diameter in 144 20 × 20‐m quadrats located in four 9‐ha permanent plots, where trees and giant herbs were inventoried. We characterized the functional strategies of selected representatives of the main liana taxa using a set of resource‐use leaf and wood traits. Finally, we used complementary statistical analyses, including multivariate and randomization approaches, to test whether forest structure, topography, and tree composition influence the structure, floristic composition, and functional composition of liana communities. The structure of liana communities was strongly shaped by local forest structure, with higher abundances and total basal areas in relatively open‐canopy forests, where lianas competed with giant herbs. Liana floristic composition exhibited a weak spatial structure over the study site but was marginally influenced by the local forest structure and topography. Only forest structure had a weak but significant effect on liana functional composition, with more conservative strategies—higher stem tissue density and lower PO4 leaf concentration and SLA values—in tall and dense forests. Finally, we found evidence of host specificity with significant attraction/repulsion for 19% of the tested liana and tree species associations, suggesting that the unexplained floristic variation may be partly attributed to these host‐species‐specific associations, although the underlying mechanisms behind remain elusive. Overall, our findings demonstrate that liana communities’ structure can be much better predicted than their composition, calling for a better understanding of the implications of the large functional diversity observed in liana communities.

Tropical rainforests are among the most emblematic ecosystems in terms of biodiversity. However, our understanding of the structure of tropical biodiversity is still incomplete, particularly for certain groups of soil organisms such as earthworms, whose importance for ecosystem functioning is widely recognised. This study aims at determining the relative contribution of alpha and beta components to earthworm regional diversity at a hierarchy of nested spatial scales in natural ecosystems of French Guiana. For this, we performed a hierarchical diversity partitioning of a large dataset on earthworm communities, in which DNA barcode‐based operational taxonomic units (OTUs) were used as species surrogates. Observed regional diversity comprised 256 OTUs. We found that alpha diversity was lower than predicted by chance, regardless of the scale considered. Community‐scale alpha diversity was on average 7 OTUs. Beta diversity among remote landscapes was higher than expected by chance, explaining as much as 87% of regional diversity. This points to regional mechanisms as the main driver of species diversity distribution in this group of organisms with low dispersal capacity. At more local scales, multiplicative beta diversity was higher than expected by chance between habitats, while it was lower than expected by chance between communities in the same habitat. This highlights the local effect of environmental filters on the species composition of communities. The calculation of a Chao 2 index predicts that as many as 1700 species could be present in French Guiana, which represents a spectacular increase compared with available checklists, and calls into question the commonly accepted estimates of global number of earthworm species.

The density of wood is a key indicator of the carbon investment strategies of trees, impacting productivity and carbon storage. Despite its importance, the global variation in wood density and its environmental controls remain poorly understood, preventing accurate predictions of global forest carbon stocks. Here we analyse information from 1.1 million forest inventory plots alongside wood density data from 10,703 tree species to create a spatially explicit understanding of the global wood density distribution and its drivers. Our findings reveal a pronounced latitudinal gradient, with wood in tropical forests being up to 30% denser than that in boreal forests. In both angiosperms and gymnosperms, hydrothermal conditions represented by annual mean temperature and soil moisture emerged as the primary factors influencing the variation in wood density globally. This indicates similar environmental filters and evolutionary adaptations among distinct plant groups, underscoring the essential role of abiotic factors in determining wood density in forest ecosystems. Additionally, our study highlights the prominent role of disturbance, such as human modification and fire risk, in influencing wood density at more local scales. Factoring in the spatial variation of wood density notably changes the estimates of forest carbon stocks, leading to differences of up to 21% within biomes. Therefore, our research contributes to a deeper understanding of terrestrial biomass distribution and how environmental changes and disturbances impact forest ecosystems.

• Aim: Ecological and anthropogenic factors shift the abundances of dominant and rare tree species within local forest communities, thus affecting species composition and ecosystem functioning. To inform forest and conservation management it is important to understand the drivers of dominance and rarity in local tree communities. We answer the following research questions: (1) What are the patterns of dominance and rarity in tree communities? (2) Which ecological and anthropogenic factors predict these patterns? And (3) what is the extinction risk of locally dominant and rare tree species? Location Global.
• Time period: 1990-2017.
• Major taxa studied: Trees.
• Methods: We used 1.2 million forest plots and quantified local tree dominance as the relative plot basal area of the single most dominant species and local rarity as the percentage of species that contribute together to the least 10% of plot basal area. We mapped global community dominance and rarity using machine learning models and evaluated the ecological and anthropogenic predictors with linear models. Extinction risk, for example threatened status, of geographically widespread dominant and rare species was evaluated.
• Results: Community dominance and rarity show contrasting latitudinal trends, with boreal forests having high levels of dominance and tropical forests having high levels of rarity. Increasing annual precipitation reduces community dominance, probably because precipitation is related to an increase in tree density and richness. Additionally, stand age is positively related to community dominance, due to stem diameter increase of the most dominant species. Surprisingly, we find that locally dominant and rare species, which are geographically widespread in our data, have an equally high rate of elevated extinction due to declining populations through large-scale land degradation.
• Main conclusions: By linking patterns and predictors of community dominance and rarity to extinction risk, our results suggest that also widespread species should be considered in large-scale management and conservation practices.