Mapping global forest age from forest inventories, biomass and climate data
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Published:2021-10-26
Issue:10
Volume:13
Page:4881-4896
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ISSN:1866-3516
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Container-title:Earth System Science Data
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language:en
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Short-container-title:Earth Syst. Sci. Data
Author:
Besnard SimonORCID, Koirala SujanORCID, Santoro MaurizioORCID, Weber UlrichORCID, Nelson JacobORCID, Gütter Jonas, Herault Bruno, Kassi Justin, N'Guessan Anny, Neigh Christopher, Poulter BenjaminORCID, Zhang TaoORCID, Carvalhais NunoORCID
Abstract
Abstract. Forest age can determine the capacity of a forest to uptake carbon from the atmosphere. However, a lack of global diagnostics that reflect the
forest stage and associated disturbance regimes hampers the quantification of age-related differences in forest carbon dynamics. This study provides
a new global distribution of forest age circa 2010, estimated using a machine learning approach trained with more than 40 000 plots using forest
inventory, biomass and climate data. First, an evaluation against the plot-level measurements of forest age reveals that the data-driven method has
a relatively good predictive capacity of classifying old-growth vs. non-old-growth (precision = 0.81 and 0.99 for old-growth and non-old-growth,
respectively) forests and estimating corresponding forest age estimates (NSE = 0.6 – Nash–Sutcliffe efficiency – and RMSE = 50 years – root-mean-square error). However, there are systematic
biases of overestimation in young- and underestimation in old-forest stands, respectively. Globally, we find a large variability in forest age with
the old-growth forests in the tropical regions of Amazon and Congo, young forests in China, and intermediate stands in Europe. Furthermore, we find
that the regions with high rates of deforestation or forest degradation (e.g. the arc of deforestation in the Amazon) are composed mainly of
younger stands. Assessment of forest age in the climate space shows that the old forests are either in cold and dry regions or warm and wet regions,
while young–intermediate forests span a large climatic gradient. Finally, comparing the presented forest age estimates with a series of regional
products reveals differences rooted in different approaches and different in situ observations and global-scale products. Despite showing
robustness in cross-validation results, additional methodological insights on further developments should as much as possible harmonize data across
the different approaches. The forest age dataset presented here provides additional insights into the global distribution of forest age to better
understand the global dynamics in the forest water and carbon cycles. The forest age datasets are openly available at
https://doi.org/10.17871/ForestAgeBGI.2021 (Besnard et al., 2021).
Funder
European Commission
Publisher
Copernicus GmbH
Subject
General Earth and Planetary Sciences
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