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Tropical forests are global biodiversity hotspots and are crucial in the global carbon (C) cycle. Understanding the drivers of aboveground carbon stock (AGC) in a heterogeneous and biodiverse system can shed light on the processes underlying the relationship between biodiversity and carbon accumulation. Here, we investigate how biodiversity, environment, and landscape structure affect AGC. We examined such associations in 349 plots comprising over 95,346 km 2 the Atlantic Forest of southern Brazil, encompassing three forest types: Dense Ombrophylous Forest (DF), Mixed Ombrophylous Forest (MF), and Seasonal Deciduous Forest (SF). Each plot was described by environmental variables, landscape metrics, and biodiversity (species richness and functional diversity). We used diversity, environmental, and landscape variables to build generalized linear mixed models and understand which can affect the forest AGC. We found that species richness is associated positively with AGC in all forest types, combined and separately. Seasonal temperature and isothermality affect AGC in all forest types; additionally, stocks are positively influenced by annual precipitation in SF and isothermality in MF. Among landscape metrics, total fragment edge negatively affects carbon stocks in MF. Our results show the importance of species diversity for carbon stocks in subtropical forests. The climate effect was also relevant, showing the importance of these factors, especially in a world where climate change tends to affect forest stock capacity negatively., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Plant recruitment interactions (i.e., what recruits under what) shape the composition, diversity, and structure of plant communities. Despite the huge body of knowledge on the mechanisms underlying recruitment interactions among species, we still know little about the structure of the recruitment networks emerging in ecological communities. Modeling and analyzing the community-level structure of plant recruitment interactions as a complex network can provide relevant information on ecological and evolutionary processes acting both at the species and ecosystem levels. We report a data set containing 143 plant recruitment networks in 23 countries across five continents, including temperate and tropical ecosystems. Each network identifies the species under which another species recruits. All networks report the number of recruits (i.e., individuals) per species. The data set includes >850,000 recruiting individuals involved in 118,411 paired interactions among 3318 vascular plant species across the globe. The cover of canopy species and open ground is also provided. Three sampling protocols were used: (1) The Recruitment Network (RN) protocol (106 networks) focuses on interactions among established plants ("canopy species") and plants in their early stages of recruitment ("recruit species"). A series of plots was delimited within a locality, and all the individuals recruiting and their canopy species were identified; (2) The paired Canopy-Open (pCO) protocol (26 networks) consists in locating a potential canopy plant and identifying recruiting individuals under the canopy and in a nearby open space of the same area; (3) The Georeferenced plot (GP) protocol (11 networks) consists in using information from georeferenced individual plants in large plots to infer canopy-recruit interactions. Some networks incorporate data for both herbs and woody species, whereas others focus exclusively on woody species. The location of each study site, geographical coordinates, country, locality, responsible author, sampling dates, sampling method, and life habits of both canopy and recruit species are provided. This database will allow researchers to test ecological, biogeographical, and evolutionary hypotheses related to plant recruitment interactions. There are no copyright restrictions on the data set; please cite this data paper when using these data in publications., (© 2022 The Authors. Ecology published by Wiley Periodicals LLC on behalf of The Ecological Society of America.)