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  1. Gustafsson M, Gustafsson L, Alloysius D, Falck J, Yap S, Karlsson A, et al.
    Data Brief, 2016 Mar;6:466-70.
    PMID: 26900591 DOI: 10.1016/j.dib.2015.12.048
    The data presented in this paper is supporting the research article "Life history traits predict the response to increased light among 33 tropical rainforest tree species" [3]. We show basic growth and survival data collected over the 6 years duration of the experiment, as well as data from traits inventories covering 12 tree traits collected prior to and after a canopy reduction treatment in 2013. Further, we also include canopy closure and forest light environment data from measurements with hemispherical photographs before and after the treatment.
  2. Schepaschenko D, Chave J, Phillips OL, Lewis SL, Davies SJ, Réjou-Méchain M, et al.
    Sci Data, 2019 10 10;6(1):198.
    PMID: 31601817 DOI: 10.1038/s41597-019-0196-1
    Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world's forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.
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