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Record number 496591
Title The decadal state of the terrestrial carbon cycle : Global retrievals of terrestrial carbon allocation, pools, and residence times
Author(s) Velde, I.R. van der; Bloom, J.; Exbrayat, J.; Feng, L.; Williams, M.
Source Proceedings of the National Academy of Sciences of the United States of America 113 (2016)5. - ISSN 0027-8424 - p. 1285 - 1290.
DOI http://dx.doi.org/10.1073/pnas.1515160113
Department(s) Meteorology and Air Quality
Publication type Refereed Article in a scientific journal
Publication year 2016
Abstract The terrestrial carbon cycle is currently the least constrained component of the global carbon budget. Large uncertainties stem from a poor understanding of plant carbon allocation, stocks, residence times, and carbon use efficiency. Imposing observational constraints on the terrestrial carbon cycle and its processes is, therefore, necessary to better understand its current state and predict its future state. We combine a diagnostic ecosystem carbon model with satellite observations of leaf area and biomass (where and when available) and soil carbon data to retrieve the first global estimates, to our knowledge, of carbon cycle state and process variables at a 1° × 1° resolution; retrieved variables are independent from the plant functional type and steady-state paradigms. Our results reveal global emergent relationships in the spatial distribution of key carbon cycle states and processes. Live biomass and dead organic carbon residence times exhibit contrasting spatial features (r = 0.3). Allocation to structural carbon is highest in the wet tropics (85–88%) in contrast to higher latitudes (73–82%), where allocation shifts toward photosynthetic carbon. Carbon use efficiency is lowest (0.42–0.44) in the wet tropics. We find an emergent global correlation between retrievals of leaf mass per leaf area and leaf lifespan (r = 0.64–0.80) that matches independent trait studies. We show that conventional land cover types cannot adequately describe the spatial variability of key carbon states and processes (multiple correlation median = 0.41). This mismatch has strong implications for the prediction of terrestrial carbon dynamics, which are currently based on globally applied parameters linked to land cover or plant functional types.
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