The dataset contains information of Diameter at Breast Height (DBH) of 8,729 trees. These trees are distributed in 29 RAINFOR network forest plots across the Brazilian Amazon, comprising the states of Acre, Mato Grosso and Pará. All the plot censuses are located in terra-firme non-flooded lowland forests. The measurements were collected between 2017 and 2019. The Amazon Forest Inventory Network is a long-term, international collaboration to understand the dynamics of Amazon ecosystems. Since 2000 they have developed a framework for systematic monitoring of forests from the ground-up, centred on plots that track the fate of trees and species, and includes soil and plant biogeochemical records, as well as intensive monitoring of carbon cycle processes at some sites. RAINFOR works with partners across the nations of Amazonia to support and sustain forest monitoring and help develop new generations of Amazon ecologists. The work of RAINFOR is currently supported by funding agencies in Brazil, the UK, and the EU. Full details about this dataset can be found at https://doi.org/10.5285/63d4b774-4e03-4db2-95ad-dcca18f0d681

[This dataset is embargoed until May 1, 2025]. This dataset includes charcoal reflectance measurements. The charcoal pieces were collected from the soil surface in tropical rainforest plots in Feliz Natal (southern Brazil, n= 75) and Pucallpa (Peru, n=14) in 2015. In total, 89 charcoal pieces were measured for reflectance. The reflectance measurements were taken in a minimum of 24 and a maximum of 70 repetitions per sample. Full details about this dataset can be found at https://doi.org/10.5285/b2b5498c-8eef-44b0-9610-844784f9f16b

[This dataset is embargoed until May 1, 2025]. This dataset contains measurements of soil pyrogenic carbon, ratio of %PyC to %Bulk Carbon and organic carbon, which were collected in a soil fertility gradient in the Amazon Basin. All samples were taken in old-growth forests. In total, 49 forest plots were sampled and analysed for PyC soil concentration, representing 395 soil samples. Full details about this dataset can be found at https://doi.org/10.5285/6410a578-d21a-4285-8e9c-57efbe2b60d5

This dataset contains radiocarbon dating of pieces of macrocharcoal (~ ≥ 1 mm) collected from soil in Guyana, Peru and Brazil in plots located in the Amazon forest. All the sites are terra-firme, non-seasonally flooded and are part of the RAINFOR network. In total, 60 pieces of macrocharcoal were dated. The Amazon Forest Inventory Network is a long-term, international collaboration to understand the dynamics of Amazon ecosystems. Since 2000 they have developed a framework for systematic monitoring of forests from the ground-up, centred on plots that track the fate of trees and species, and includes soil and plant biogeochemical records, as well as intensive monitoring of carbon cycle processes at some sites. RAINFOR works with partners across the nations of Amazonia to support and sustain forest monitoring and help develop new generations of Amazon ecologists. The work of RAINFOR is currently supported by funding agencies in Brazil, the UK, and the EU. Full details about this dataset can be found at https://doi.org/10.5285/b06a08bc-39e5-4401-87dd-9568fd5048fd

This dataset contains measurements of herbivory and the potential controls on herbivory for nitrogen-fixing and non-fixing trees in a mature tropical forest of Panama. Data include herbivory measures on 1,626 leaves from 350 seedlings belonging to 43 species, 23 nitrogen-fixing species, 20 non-fixing species. Herbivory metrics are presented at the leaf and seedling level. The data also includes leaf chemical and physical traits hypothesized to influence herbivory at the species level, and seedling-level traits such as stem length and growth rate. Data were collected in 2017 by measuring leaf area missing on seedlings in the BCI 50 ha plot seedling census in order to determine whether fixers have higher rates of herbivory than non-fixers, and what traits govern herbivory. Data were collected by W. Barker, S.J. Wright, L. Comita, B. Sedio and colleagues. Funders of research generating the data include the Natural Environment Research Council, U.S. National Science Foundation, Leverhulme Trust, British Council, Society of Experimental Biology Company of Biologists, University of Leeds Priestly International Centre for Climate and Smithsonian Tropical Research Institute Full details about this dataset can be found at https://doi.org/10.5285/67c95112-edee-435f-9355-9d8bab3a5634