Biodiversity research and conservation efforts in the tropics are hindered by the lack of knowledge of the assemblages found there, with many species undescribed or poorly known. Our initiative, the Tree Biodiversity Network (BIOTREE-NET), aims to ad-dress this problem by assembling georeferenced data from a wide range of sources, making these data easily accessible and easily que-ried, and promoting data sharing. The database (GIVD ID NA-00-002) currently comprises ca. 50,000 tree records of ca. 5,000 species (230 in the IUCN Red List) from >2,000 forest plots in 11 countries. The focus is on trees because of their pivotal role in tropical for-est ecosystems (which contain most of the world's biodiversity) in terms of ecosystem function, carbon storage and effects on other species. BIOTREE-NET currently focuses on southern Mexico and Central America, but we aim to expand coverage to other parts of tropical America. The database is relational, comprising 12 linked data tables. We summarise its structure and contents. Key tables contain data on forest plots (including size, location and date(s) sampled), individual trees (including diameter, when available, and both recorded and standardised species name), species (including biological traits of each species) and the researchers who collected the data. Many types of queries are facilitated and species distribution modelling is enabled. Examining the data in BIOTREE-NET to date, we found an uneven distribution of data in space and across biomes, reflecting the general state of knowledge of the tropics. More than 90% of the data were collected since 1990 and plot size varies widely, but with most less than one hectare in size. A wide range of minimum sizes is used to define a 'tree'. The database helps to identify gaps that need filling by further data collection and collation. The data can be publicly accessed through a web application at http://portal.biotreenet.com. Researchers are invited and encouraged to contribute data to BIOTREE-NET.

BIOTREE-NET development has been supported primarily by Fundación BBVA (project BIOCON08_044).

Long Database Report.-- et al.

Peer Reviewed