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Anthropogenic disturbances are changing the structure and composition of tropical forests worldwide. Multiple disturbances often occur simultaneously in forests: for example, hunting and logging are within-forest disturbances that impact vast areas of seemingly intact rainforests. Despite recent work on the individual effects of these disturbances, our understanding of how they interact to influence tree communities is still limited. In northern Republic of Congo, we explored the effects of hunting and logging on tree communities. Over an 8-year period, we monitored 12,552 tree stems (≥ 10 cm diameter-at-breast height) spread over 30 1-ha plots along a gradient of human disturbance to compare the tree diversity between hunted and logged forest, once-logged forest, and protected forest free of both disturbances. Tree density, species richness, and community composition were affected by both hunting and logging. Forest close to human settlements was richer, more heterogenous, and more dynamic in species composition across censuses. In hunted and logged forest, fast-growing secondary species with low shade tolerance replaced old growth species. Comparatively, the once-logged forest had the greatest stem density and intermediate species richness with an increased density of shade-bearing species over time. Both tree species spatial turnover and tree recruitment were greatly affected by proximity to human settlements. A shift towards abiotically dispersed trees and increasing seed predation by rodents near villages can partly explain the differences in tree recruitment across the forest types. The combination of hunting and logging seems to have a greater impact on tree communities than either single disturbance, especially with nearness to villages. 

One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ∼73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness. 

A number of different models have been proposed as descriptions of the species-abundance distribution (SAD). Most evaluations of these models use only one or two models, focus on only a single ecosystem or taxonomic group, or fail to use appropriate statistical methods. We use likelihood and AIC to compare the fit of four of the most widely used models to data on over 16,000 communities from a diverse array of taxonomic groups and ecosystems. Across all datasets combined the log-series, Poisson lognormal, and negative binomial all yield similar overall fits to the data. Therefore, when correcting for differences in the number of parameters the log-series generally provides the best fit to data. Within individual datasets some other distributions performed nearly as well as the log-series even after correcting for the number of parameters. The Zipf distribution is generally a poor characterization of the SAD.