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MODIS Based Estimation of Forest Aboveground Biomass in China.

Yin G, Zhang Y, Sun Y, Wang T, Zeng Z, Piao S - PLoS ONE (2015)

Bottom Line: The mean forest aboveground biomass density is 56.1 Mg C ha-1, with high values observed in temperate humid regions.The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y-1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y-1.During the 2000s, the forests in China sequestered C by 61.9 Tg C y-1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests.

View Article: PubMed Central - PubMed

Affiliation: College of Urban and Environmental Sciences, Peking University, Beijing, China.

ABSTRACT
Accurate estimation of forest biomass C stock is essential to understand carbon cycles. However, current estimates of Chinese forest biomass are mostly based on inventory-based timber volumes and empirical conversion factors at the provincial scale, which could introduce large uncertainties in forest biomass estimation. Here we provide a data-driven estimate of Chinese forest aboveground biomass from 2001 to 2013 at a spatial resolution of 1 km by integrating a recently reviewed plot-level ground-measured forest aboveground biomass database with geospatial information from 1-km Moderate-Resolution Imaging Spectroradiometer (MODIS) dataset in a machine learning algorithm (the model tree ensemble, MTE). We show that Chinese forest aboveground biomass is 8.56 Pg C, which is mainly contributed by evergreen needle-leaf forests and deciduous broadleaf forests. The mean forest aboveground biomass density is 56.1 Mg C ha-1, with high values observed in temperate humid regions. The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y-1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y-1. During the 2000s, the forests in China sequestered C by 61.9 Tg C y-1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests.

No MeSH data available.


(A) Distribution of forest AGBD in a two-dimensional space with (MAT) and (MAP) binned into intervals of 1°C MAT and 100 mm MAP.(B) The sensitivity of AGBD on temperature (ST) along precipitation gradient. (C) The sensitivity of AGBD on precipitation (Sp) along temperature gradient. The shaded area in (B) and (C) indicates 95% significance intervals of ST and Sp. Sensitivities were only calculated in bins having more than 100 grid pixels.
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pone.0130143.g004: (A) Distribution of forest AGBD in a two-dimensional space with (MAT) and (MAP) binned into intervals of 1°C MAT and 100 mm MAP.(B) The sensitivity of AGBD on temperature (ST) along precipitation gradient. (C) The sensitivity of AGBD on precipitation (Sp) along temperature gradient. The shaded area in (B) and (C) indicates 95% significance intervals of ST and Sp. Sensitivities were only calculated in bins having more than 100 grid pixels.

Mentions: As shown in Fig 4, forests in China are distributed in regions with MAT ranging from -10 to 26°C and MAP ranging from 0 to 5200 mm y-1. The highest AGBD levels (> 100 Mg ha-2) are mostly found in temperate (5–22°C) and moist climate regions (MAP > 1000 mm y-1), while the relatively low AGBD levels (< 40 Mg ha-2) mainly occur in regions with MAP < 500 mm y-1 and MAT > 5°C.


MODIS Based Estimation of Forest Aboveground Biomass in China.

Yin G, Zhang Y, Sun Y, Wang T, Zeng Z, Piao S - PLoS ONE (2015)

(A) Distribution of forest AGBD in a two-dimensional space with (MAT) and (MAP) binned into intervals of 1°C MAT and 100 mm MAP.(B) The sensitivity of AGBD on temperature (ST) along precipitation gradient. (C) The sensitivity of AGBD on precipitation (Sp) along temperature gradient. The shaded area in (B) and (C) indicates 95% significance intervals of ST and Sp. Sensitivities were only calculated in bins having more than 100 grid pixels.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4482713&req=5

pone.0130143.g004: (A) Distribution of forest AGBD in a two-dimensional space with (MAT) and (MAP) binned into intervals of 1°C MAT and 100 mm MAP.(B) The sensitivity of AGBD on temperature (ST) along precipitation gradient. (C) The sensitivity of AGBD on precipitation (Sp) along temperature gradient. The shaded area in (B) and (C) indicates 95% significance intervals of ST and Sp. Sensitivities were only calculated in bins having more than 100 grid pixels.
Mentions: As shown in Fig 4, forests in China are distributed in regions with MAT ranging from -10 to 26°C and MAP ranging from 0 to 5200 mm y-1. The highest AGBD levels (> 100 Mg ha-2) are mostly found in temperate (5–22°C) and moist climate regions (MAP > 1000 mm y-1), while the relatively low AGBD levels (< 40 Mg ha-2) mainly occur in regions with MAP < 500 mm y-1 and MAT > 5°C.

Bottom Line: The mean forest aboveground biomass density is 56.1 Mg C ha-1, with high values observed in temperate humid regions.The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y-1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y-1.During the 2000s, the forests in China sequestered C by 61.9 Tg C y-1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests.

View Article: PubMed Central - PubMed

Affiliation: College of Urban and Environmental Sciences, Peking University, Beijing, China.

ABSTRACT
Accurate estimation of forest biomass C stock is essential to understand carbon cycles. However, current estimates of Chinese forest biomass are mostly based on inventory-based timber volumes and empirical conversion factors at the provincial scale, which could introduce large uncertainties in forest biomass estimation. Here we provide a data-driven estimate of Chinese forest aboveground biomass from 2001 to 2013 at a spatial resolution of 1 km by integrating a recently reviewed plot-level ground-measured forest aboveground biomass database with geospatial information from 1-km Moderate-Resolution Imaging Spectroradiometer (MODIS) dataset in a machine learning algorithm (the model tree ensemble, MTE). We show that Chinese forest aboveground biomass is 8.56 Pg C, which is mainly contributed by evergreen needle-leaf forests and deciduous broadleaf forests. The mean forest aboveground biomass density is 56.1 Mg C ha-1, with high values observed in temperate humid regions. The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y-1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y-1. During the 2000s, the forests in China sequestered C by 61.9 Tg C y-1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests.

No MeSH data available.