Changes in soil carbon stock after deforestation and subsequent establishment of “Imperata” grassland in the Asian humid tropics

Yonekura, Yusuke; Ohta, Seiichi; Kiyono, Yoshiyuki; Aksa, Darul; Morisada, Kazuhito; Tanaka, Nagaharu; Kanzaki, Mamoru

doi:10.1007/s11104-009-0175-y

Cited by 33 publications

(33 citation statements)

References 29 publications

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“…2). Possible explanations for the high total SOC s in grasslands, which were similar to SOC s in mature forest, are higher belowground net primary production (NPP) and charcoal inputs compared to forests (van der Kamp et al, 2009;Yonekura et al, 2010). Higher belowground NPP in Imperata grasslands compared to forests may result in greater inputs of organic matter to the soil.…”

Section: Effects Of Land-use Type On Soil Organic Carbon Concentratiomentioning

confidence: 98%

“…However, results from field measurements on impacts of fire and charcoal additions on SOC quantities are contradictory, ranging from SOC losses (Bird et al, 2000;Fynn et al, 2003) to no change or increases in the SOC pool (Eckmeier et al, 2007;Ojima et al, 1994). Studies conducted in Kalimantan, Indonesia (van der Kamp et al, 2009;Yonekura et al, 2010), reported even higher SOC s in Imperata grasslands compared to primary forests. Similarly, a meta-study of tropical landuse conversions (Powers et al, 2011) reported an increase in SOC s of 26 % following forest-to-grassland conversions on soils with low activity clays and annual precipitation of 1501-2500 mm, which are similar to the biophysical conditions in our study area.…”

Section: Effects Of Land-use Type On Soil Organic Carbon Concentratiomentioning

confidence: 99%

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Spatial variability in soil organic carbon in a tropical montane landscape: associations between soil organic carbon and land use, soil properties, vegetation, and topography vary across plot to landscape scales

Blécourt¹,

Corre²,

Paudel

et al. 2017

SOIL

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Abstract. Presently, the lack of data on soil organic carbon (SOC) stocks in relation to land-use types and biophysical characteristics prevents reliable estimates of ecosystem carbon stocks in montane landscapes of mainland SE Asia. Our study, conducted in a 10 000 ha landscape in Xishuangbanna, SW China, aimed at assessing the spatial variability in SOC concentrations and stocks, as well as the relationships of SOC with land-use types, soil properties, vegetation characteristics and topographical attributes at three spatial scales: (1) land-use types within a landscape (10 000 ha), (2) sampling plots (1 ha) nested within land-use types (plot distances ranging between 0.5 and 12 km), and (3) subplots (10 m radius) nested within sampling plots. We sampled 27 one-hectare plots -10 plots in mature forests, 11 plots in regenerating or highly disturbed forests, and 6 plots in open land including tea plantations and grasslands. We used a sampling design with a hierarchical structure. The landscape was first classified according to land-use types. Within each land-use type, sampling plots were randomly selected, and within each plot we sampled within nine subplots. SOC concentrations and stocks did not differ significantly across the four land-use types. However, within the open-land category, SOC concentrations and stocks in grasslands were higher than in tea plantations (P < 0.01 for 0-0.15 m, P = 0.05 for 0.15-0.30 m, P = 0.06 for 0-0.9 m depth). The SOC stocks to a depth of 0.9 m were 177.6 ± 19.6 (SE) Mg C ha −1 in tea plantations, 199.5 ± 14.8 Mg C ha −1 in regenerating or highly disturbed forests, 228.6 ± 19.7 Mg C ha −1 in mature forests, and 236.2 ± 13.7 Mg C ha −1 in grasslands. In this montane landscape, variability within plots accounted for more than 50 % of the overall variance in SOC stocks to a depth of 0.9 m and the topsoil SOC concentrations. The relationships of SOC concentrations and stocks with land-use types, soil properties, vegetation characteristics, and topographical attributes varied across spatial scales. Variability in SOC within plots was determined by litter layer carbon stocks (P < 0.01 for 0-0.15 m and P = 0.03 for 0.15-0.30 and 0-0.9 m depth) and slope (P ≤ 0.01 for 0-0.15, 0.15-0.30, and 0-0.9 m depth) in open land, and by litter layer carbon stocks (P < 0.001 for 0-0.15, 0.15-0.30 and 0-0.9 m depth) and tree basal area (P < 0.001 for 0-0.15 m and P = 0.01 for 0-0.9 m depth) in forests. Variability in SOC among plots in open land was related to the differences in SOC concentrations and stocks between grasslands and tea plantations. In forests, the variability in SOC among plots was associated with elevation (P < 0.01 for 0-0.15 m and P = 0.09 for 0-0.9 m depth). The scale-dependent relationships between SOC and its controlling factors demonstrate that studies that aim to investigate the land-use effects on SOC Published by Copernicus Publications on behalf of the European Geosciences Union. 124 M. de Blécourt et al.: Spatial variability of soil organic carbon need an appropriate samp...

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Section: Effects Of Land-use Type On Soil Organic Carbon Concentratiomentioning

confidence: 98%

Section: Effects Of Land-use Type On Soil Organic Carbon Concentratiomentioning

confidence: 99%

Spatial variability in soil organic carbon in a tropical montane landscape: associations between soil organic carbon and land use, soil properties, vegetation, and topography vary across plot to landscape scales

Blécourt¹,

Corre²,

Paudel

et al. 2017

SOIL

View full text Add to dashboard Cite

show abstract

Section: Soil C Stock In Tropical Monsoon Forestsmentioning

confidence: 91%

“…The estimated soil C stocks for the 0-to 30-cm depth range were 26.8 Mg C ha -1 in Southern Thailand 22 and 29.9 Mg C ha -1 in East Kalimantan 28 . Within the 0-to 100-cm depth range, estimates were 55.0 Mg C ha -1 in East Kalimantan 28 and 70.0 Mg C ha -1 in peninsular Malaysia 27 . The studies mentioned above did not report C stocks in the 0-to 100-cm depth range of Andosols and Andisols 12,26 , although these are the largest stocks (>200 Mg C ha -1 ) in the humid tropics.…”

Section: Soil C Stock In Tropical Monsoon Forestsmentioning

confidence: 91%