The extent to which pre-Columbian societies altered Amazonian landscapes is hotly debated. We performed a basin-wide analysis of pre-Columbian impacts on Amazonian forests by overlaying known archaeological sites in Amazonia with the distributions and abundances of 85 woody species domesticated by pre-Columbian peoples. Domesticated species are five times more likely than nondomesticated species to be hyperdominant. Across the basin, the relative abundance and richness of domesticated species increase in forests on and around archaeological sites. In southwestern and eastern Amazonia, distance to archaeological sites strongly influences the relative abundance and richness of domesticated species. Our analyses indicate that modern tree communities in Amazonia are structured to an important extent by a long history of plant domestication by Amazonian peoples

Aim Tropical forests store 25% of global carbon and harbour 96% of the world's tree species, but it is not clear whether this high biodiversity matters for carbon storage. Few studies have teased apart the relative importance of forest attributes and environmental drivers for ecosystem functioning, and no such study exists for the tropics. Location Neotropics. Methods We relate aboveground biomass (AGB) to forest attributes (diversity and structure) and environmental drivers (annual rainfall and soil fertility) using data from 144,000 trees, 2050 forest plots and 59 forest sites. The sites span the complete latitudinal and climatic gradients in the lowland Neotropics, with rainfall ranging from 750 to 4350 mm year−1. Relationships were analysed within forest sites at scales of 0.1 and 1 ha and across forest sites along large‐scale environmental gradients. We used a structural equation model to test the hypothesis that species richness, forest structural attributes and environmental drivers have independent, positive effects on AGB. Results Across sites, AGB was most strongly driven by rainfall, followed by average tree stem diameter and rarefied species richness, which all had positive effects on AGB. Our indicator of soil fertility (cation exchange capacity) had a negligible effect on AGB, perhaps because we used a global soil database. Taxonomic forest attributes (i.e. species richness, rarefied richness and Shannon diversity) had the strongest relationships with AGB at small spatial scales, where an additional species can still make a difference in terms of niche complementarity, while structural forest attributes (i.e. tree density and tree size) had strong relationships with AGB at all spatial scales. Main conclusions Biodiversity has an independent, positive effect on AGB and ecosystem functioning, not only in relatively simple temperate systems but also in structurally complex hyperdiverse tropical forests. Biodiversity conservation should therefore be a key component of the UN Reducing Emissions from Deforestation and Degradation strategy.

The sensitivity of tropical forest carbon to climate is a key uncertainty in predicting global climate change. Although short-term drying and warming are known to affect forests, it is unknown if such effects translate into long-term responses. Here, we analyze 590 permanent plots measured across the tropics to derive the equilibrium climate controls on forest carbon. Maximum temperature is the most important predictor of aboveground biomass (−9.1 megagrams of carbon per hectare per degree Celsius), primarily by reducing woody productivity, and has a greater impact per °C in the hottest forests (>32.2°C). Our results nevertheless reveal greater thermal resilience than observations of short-term variation imply. To realize the long-term climate adaptation potential of tropical forests requires both protecting them and stabilizing Earth’s climate.

Analyses of forest loss and protected areas suggest that 36 to 57% of Amazonian tree flora may qualify as “globally threatened.”

Species distribution models (SDMs) are widely used in ecology and conservation. Presence-only SDMs such as MaxEnt frequently use natural history collections (NHCs) as occurrence data, given their huge numbers and accessibility. NHCs are often spatially biased which may generate inaccuracies in SDMs. Here, we test how the distribution of NHCs and MaxEnt predictions relates to a spatial abundance model, based on a large plot dataset for Amazonian tree species, using inverse distance weighting (IDW). We also propose a new pipeline to deal with inconsistencies in NHCs and to limit the area of occupancy of the species. We found a significant but weak positive relationship between the distribution of NHCs and IDW for 66% of the species. The relationship between SDMs and IDW was also significant but weakly positive for 95% of the species, and sensitivity for both analyses was high. Furthermore, the pipeline removed half of the NHCs records. Presence-only SDM applications should consider this limitation, especially for large biodiversity assessments projects, when they are automatically generated without subsequent checking. Our pipeline provides a conservative estimate of a species’ area of occupancy, within an area slightly larger than its extent of occurrence, compatible to e.g. IUCN red list assessments.