Land cover impacts on aboveground and soil carbon stocks in Malagasy rainforest

Andriamananjara, Andry; Hewson, Jenny; Razakamanarivo, Herintsitohaina; Andrisoa, Riana H.; Ranaivoson, Ntsoa; Ramboatiana, Nantenaina; Razafindrakoto, Mieja; Razafimanantsoa, Marie-Paule; Rabeharisoa, Lilia; Ramananantoandro, Tahiana; Rasolohery, Andriambolantsoa; Rabetokotany, Nantenaina; Razafimbelo, Tantely

doi:10.1016/j.agee.2016.08.030

Cited by 44 publications

(38 citation statements)

References 49 publications

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“…Globally, the distribution of SOC stocks down to 200 cm was based on the distribution of the soil profile type in the watershed and could not be predicted from the SOC stocks at the surface. For halloysitic soil profiles, we observed a linear relationship between SOC stock in 0-20 cm and SOC stock in 0-200 cm as already reported for soils with different texture but without SRO minerals (Andriamananjara et al, 2016). However, this relationship did not hold in allophanic and allophanic-halloysitic soil profiles (Fig.…”

Section: Variation Of Soc Stocks In the Aquiares Watershedsupporting

confidence: 86%

“…This coexistence of allophane and halloysite marked a transition from the allophanic soils to the halloysitic soils. This transition could be explained by formation of halloysite at microsites within an allophane matrix (Aomine andWada, 1962, quoted in Parfitt, 2009), when periods of leaching alternate with periods of desiccation (Churchman et al, 2016). The resulting fluctuations in activity of Si in soil solutions could cause differential formation of amorphous and crystalline weathering products.…”

Section: Three Types Of Soil Profiles In the Watershedmentioning

confidence: 99%

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Short-range-order minerals as powerful factors explaining deep soil organic carbon stock distribution: the case of a coffee agroforestry plantation on Andosols in Costa Rica

Chevallier

Fujisaki

Roupsard

et al. 2019

SOIL

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Abstract. Soil organic carbon (SOC) constitutes the largest terrestrial C stock, particularly in the Andosols of volcanic areas. Quantitative information on distribution of SOC stocks is needed to construct a baseline for studying temporal changes in SOC. The spatial variation of soil short-range-order minerals such as allophane usually explains the variability of topsoil SOC contents, but SOC data for deeper soil layers are needed. We found that within a 1 km2 Costa Rican basin covered by coffee agroforestry, SOC stocks in the upper 200 cm of soil were highly variable (24 to 72 kg C m−2). Topsoil SOC stocks were not correlated with SOC stocks present in deeper layers. Diffuse-reflectance mid-infrared (MIR) spectroscopy made possible the analysis of a large number of samples (69 soil profiles, i.e. 598 soil samples) for ammonium-oxalate and sodium-pyrophosphate-extractable forms of Al, Fe, and Si, as well as SOC content and bulk density. Using the MIR spectra, we identified two different soil materials, which were identified as allophanic and halloysitic soil material. Allophanic soil occurred on top of the halloysitic soil. The thickness of the allophanic soil material, rich in SRO minerals and related to a young andic A horizon, explained the variability of SOC. This study illustrates that knowledge of topography and pedogenesis is needed to understand and extrapolate the distribution of SOC stocks at landscape scales.

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Section: Variation Of Soc Stocks In the Aquiares Watershedsupporting

confidence: 86%

Section: Three Types Of Soil Profiles In the Watershedmentioning

confidence: 99%

Short-range-order minerals as powerful factors explaining deep soil organic carbon stock distribution: the case of a coffee agroforestry plantation on Andosols in Costa Rica

Chevallier

Fujisaki

Roupsard

et al. 2019

SOIL

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“…Climate, geology, and soil formation are affecting SOC in the long term, while vegetation disturbance and land cover change are the main factors affecting on soil C storage in the short period [62]. Changes in C stock were found to be potentially related to altitude, precipitation, temperature, soil texture, and root biomass [7]. In our studied area rotation is wheat -corn, and this cropping system isn't suitable.…”

Section: Fig 5 Spatial Distribution Map Of Soil Oc (Right) and Soilmentioning

confidence: 80%

“…Soil properties can also have effect on soil organic carbon. In this regard, Andriamananjara et al [7] also showed that the SOC was positively correlated with the clay content in topsoil. In studied area soil organic matter was low and variable, applying different sources and amounts of organic matter, proportional with different part of field, improved soil properties consistent with the findings of [65].…”

Section: Fig 5 Spatial Distribution Map Of Soil Oc (Right) and Soilmentioning

confidence: 92%

“…Climate and topography conditions combined with soil properties could explain the soil organic carbon (SOC) variations across the tropical region; also high SOC is related to high clay content and high root development [7]. Global warming and climate change is an important challenge; therefore, the high potential of topsoil to sequester C is an indicator of soil health and soil potential to mitigate climate change [8].…”

Section: Introductionmentioning

confidence: 99%

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Relationship between Spatial Variability Pattern of Wheat Yield and Soil Properties

Karami

Afzalinia

2018

ASRJ

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Aims: Determining effects of spatial variation of some soil properties on wheat quantity and quality variation in order that proper soil and inputs management can be applied for sustainable wheat production. Study Design: Analyzing data of a field with center pivot irrigation system and uniform management using the geostatistical method. Place and Duration Methodology: Wheat yield data harvested by class lexion 510 combine from 25 m 2 plots (11340 locations) with the corresponding geographical location were used. Besides, soil properties and wheat yield were measured at 36 randomly selected points on the field. Interpolation of parameters was predicted with the best semi-variogram model using kriging, inverse distance weighted (IDW), and cokriging methods. Results:Results showed that wheat yield varied from 2 to 10.08 tons per hectare. Cokriging with cofactor of kernel weight interpolator had more accuracy compared to the combine default interpolator (kriging). A logical, linear correlation was found between different parameters. The best variogram model for pH, OC, and ρb was exponential, for EC, TNV, SP, soil silt and clay percentage was spherical, and for soil, percentage sand was Gaussian model. Data of soil sand, silt, and clay percentage, EC, TNV, and SP had strong spatial structure, and soil pH, OC, and ρb had moderate spatial structure. The best interpolation method for soil pH, EC, sand and silt percentage was kriging method; while, for TNV, SP, OC, ρb, and clay percentage was IDW. Conclusion: There was a close relationship between wheat yield variation and changes in the soil properties. Soil properties and wheat yield distribution maps provided valuable information which could be used for wheat yield improvement in precision agriculture.

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Rainfall‐runoff responses and hillslope moisture thresholds for an upland tropical catchment in Eastern Madagascar subject to long‐term slash‐and‐burn practices

Zwartendijk,

van Meerveld,

Teuling

et al. 2023

Hydrological Processes

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Slash‐and‐burn agriculture is an important driver of tropical forest loss and typically results in a mosaic of land uses. However, there is little quantitative information about the hydrological effects of long‐term slash‐and‐burn agriculture and how such mosaics affect the rainfall‐runoff response at the catchment scale. We monitored streamflow responses at two points along a perennial stream in a 31.7 ha catchment in eastern Madagascar that was monitored previously between 1963 and 1972. Land cover in 2015 consisted of degraded grasslands, shrub and tree fallows at various stages of regrowth (64%), eucalypt stands for charcoal production (30%), and rice paddies and wetlands in the valley‐bottom (3%). For the majority (60%) of the events during the study period, the ratio between the total amount of stormflow and rainfall was <3%, suggesting that for these events runoff was generated in the valley‐bottom only. Events for which an antecedent soil moisture storage plus rainfall (ASI + P) threshold was exceeded had much higher stormflow ratios (up to 50%), indicating that a certain wetness was required for the hillslopes to contribute to stormflow. Stable isotope sampling for four small to moderate events indicated that stormflow was dominated by pre‐event water. Total stormflow and annual water yield in 2015 were higher than in the 1960s, despite much lower rainfall in 2015. We attribute these differences to changes in soil physical properties caused by the repeated burning and loss of top‐soil, which has resulted in a reduction in the depth to the impeding layer. The changed runoff‐processes (less infiltration, more saturation‐excess overland flow) thus affect local water resources.

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Land cover impacts on aboveground and soil carbon stocks in Malagasy rainforest

Cited by 44 publications

References 49 publications

Short-range-order minerals as powerful factors explaining deep soil organic carbon stock distribution: the case of a coffee agroforestry plantation on Andosols in Costa Rica

Short-range-order minerals as powerful factors explaining deep soil organic carbon stock distribution: the case of a coffee agroforestry plantation on Andosols in Costa Rica

Relationship between Spatial Variability Pattern of Wheat Yield and Soil Properties

Rainfall‐runoff responses and hillslope moisture thresholds for an upland tropical catchment in Eastern Madagascar subject to long‐term slash‐and‐burn practices

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