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Soil and vegetation carbon turnover times from tropical to boreal forests
by
Wang, Jinsong
, Niu, Shuli
, Li, Meiling
, Sun, Jian
, He, Nianpeng
, Xia, Jianyang
in
Annual precipitation
/ Atmospheric models
/ atmospheric precipitation
/ Boreal forests
/ carbon
/ Carbon dioxide
/ carbon sinks
/ carbon turnover time
/ China
/ climate
/ Climate change
/ Climate models
/ Climate system
/ Environmental changes
/ forest age
/ Forest ecosystems
/ forest origin
/ forest type
/ forest types
/ Forests
/ Fossil fuels
/ Latitude
/ Precipitation
/ Prediction models
/ Rainfall
/ Soil investigations
/ Soil properties
/ soil property
/ Spatial variations
/ Taiga
/ temperature
/ Terrestrial ecosystems
/ Terrestrial environments
/ Tropical forests
/ Turnover time
/ Uncertainty
/ Variation
/ Vegetation
2018
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Soil and vegetation carbon turnover times from tropical to boreal forests
by
Wang, Jinsong
, Niu, Shuli
, Li, Meiling
, Sun, Jian
, He, Nianpeng
, Xia, Jianyang
in
Annual precipitation
/ Atmospheric models
/ atmospheric precipitation
/ Boreal forests
/ carbon
/ Carbon dioxide
/ carbon sinks
/ carbon turnover time
/ China
/ climate
/ Climate change
/ Climate models
/ Climate system
/ Environmental changes
/ forest age
/ Forest ecosystems
/ forest origin
/ forest type
/ forest types
/ Forests
/ Fossil fuels
/ Latitude
/ Precipitation
/ Prediction models
/ Rainfall
/ Soil investigations
/ Soil properties
/ soil property
/ Spatial variations
/ Taiga
/ temperature
/ Terrestrial ecosystems
/ Terrestrial environments
/ Tropical forests
/ Turnover time
/ Uncertainty
/ Variation
/ Vegetation
2018
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Soil and vegetation carbon turnover times from tropical to boreal forests
by
Wang, Jinsong
, Niu, Shuli
, Li, Meiling
, Sun, Jian
, He, Nianpeng
, Xia, Jianyang
in
Annual precipitation
/ Atmospheric models
/ atmospheric precipitation
/ Boreal forests
/ carbon
/ Carbon dioxide
/ carbon sinks
/ carbon turnover time
/ China
/ climate
/ Climate change
/ Climate models
/ Climate system
/ Environmental changes
/ forest age
/ Forest ecosystems
/ forest origin
/ forest type
/ forest types
/ Forests
/ Fossil fuels
/ Latitude
/ Precipitation
/ Prediction models
/ Rainfall
/ Soil investigations
/ Soil properties
/ soil property
/ Spatial variations
/ Taiga
/ temperature
/ Terrestrial ecosystems
/ Terrestrial environments
/ Tropical forests
/ Turnover time
/ Uncertainty
/ Variation
/ Vegetation
2018
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Soil and vegetation carbon turnover times from tropical to boreal forests
Journal Article
Soil and vegetation carbon turnover times from tropical to boreal forests
2018
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Overview
Terrestrial ecosystems currently function as a net carbon (C) sink for atmospheric C dioxide (CO2), but whether this C sink can persist with global climate change is still uncertain. Such uncertainty largely comes from C turnover time in an ecosystem, which is a critical parameter for modelling C cycle and evaluating C sink potential. Our current understanding of how long C can be stored in soils and vegetation and what controls spatial variations in C turnover time on a large scale is still very limited. We used data on C stocks and C influx from 2,753 plots in vegetation and 1,087 plots in soils and investigated the spatial patterns as well controlling factors of C turnover times across forest ecosystems in eastern China. Our results showed a clear latitudinal pattern of C turnover times, with the shortest turnover times in the low‐latitude zones and the longest turnover times in the high‐latitude zones. Mean annual temperature and mean annual precipitation were the most important controlling factors on soil C turnover times, while forest age accounted for the majority of variations in the vegetation C turnover times. Forest origin (planted or natural forest) was also responsible for the variations in vegetation C turnover times, while forest type and soil properties were not the dominant controlling factors. Our study highlights the different dominant controlling factors in soil and vegetation C turnover times and different mechanisms underlying above‐ and below‐ground C turnover. These findings are essential to better understand (and reduce uncertainty) in predictive models of coupled C–climate system. A plain language summary is available for this article. Plain Language Summary
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