ABERG wood density dataset
收藏NIAID Data Ecosystem2026-05-01 收录
下载链接:
https://zenodo.org/record/10864739
下载链接
链接失效反馈官方服务:
资源简介:
The Andes Biodiversity and Ecosystem Research Group (ABERG) is a team of 38 researchers from 12 universities dedicated to understanding biodiversity distribution and ecosystem function in the Peruvian Andes. ABERG is committed to data exchange within the scientific community and promoting collaboration among other tropical ecosystem scientists.The ABERG wood density dataset includes 892 arborescent individuals representing 311 species. It was collected in 51 sites along the Andes to Amazon elevational gradient, spanning from 346 to 3650 m of elevation in the Kosñipata Valley, Cusco, Peru (-13.1969°, -71.6199°). The dataset includes wood density values (in g/cm3) for trees, palms, and tree ferns with a diameter ≥10 cm, and it is available as a comma-separated values file. Wood density was calculated using the water displacement method with all samples oven-dried to constant mass and weighted to the nearest 0.001 g (Chave et al., 2006). Values of wood density were first calculated at an oven-dry temperature of ~80 oC. Because of the possible presence of bond water in the wood samples (Williamson and Wiemann, 2010), we used a sub-sample (n = 145) to calculate wood density at 105 oC. We developed a correction equation (105 oC WD = - 0.0113 + 0.9969 x 80 oC WD) that was applied to calibrate the wood density values of the rest of the wood samples. For more information regarding the ABERG projects, please visit the website (https://www.andesconservation.org/).
The ABERG wood density dataset has been supported by generous grants from the Gordon and Betty Moore Foundation’s Andes to Amazon initiative, the US National Science Foundation (NSF) DEB 0743666, and the NSF Long-Term Research in Environmental Biology (LTREB) 1754647. The research was also supported by the National Aeronautics and Space Administration (NASA) Terrestrial Ecology Program grant # NNH08ZDA001N-TE/ 08-TE08-0037.
创建时间:
2024-03-25



