Spatial Variability of Soil Carbon in Floodplain Soils of Southeastern Nigeria

2007 ◽  
Vol 2 (6) ◽  
pp. 552-558 ◽  
Author(s):  
E.U. Onweremadu .
Keyword(s):  
Spatial Variability ◽  
Soil Carbon ◽  
Southeastern Nigeria ◽  
Floodplain Soils

scholarly journals Spatially Related Sampling Uncertainty in the Assessment of Labile Soil Carbon and Nitrogen in an Irish Forest Plantation

2021 ◽  
Vol 11 (5) ◽  
pp. 2139
Author(s):  
Junliang Zou ◽  
Bruce Osborne
Keyword(s):  
Spatial Variability ◽  
Soil Carbon ◽  
Sampling Effort ◽  
Limited Information ◽  
Sampling Area ◽  
Soil C ◽  
Distribution Maps ◽  
Soil C And N ◽  
C And N ◽  
Highly Correlated

The importance of labile soil carbon (C) and nitrogen (N) in soil biogeochemical processes is now well recognized. However, the quantification of labile soil C and N in soils and the assessment of their contribution to ecosystem C and N budgets is often constrained by limited information on spatial variability. To address this, we examined spatial variability in dissolved organic carbon (DOC) and dissolved total nitrogen (DTN) in a Sitka spruce forest in central Ireland. The results showed moderate variations in the concentrations of DOC and DTN based on the mean, minimum, and maximum, as well as the coefficients of variation. Residual values of DOC and DTN were shown to have moderate spatial autocorrelations, and the nugget sill ratios were 0.09% and 0.10%, respectively. Distribution maps revealed that both DOC and DTN concentrations in the study area decreased from the southeast. The variability of both DOC and DTN increased as the sampling area expanded and could be well parameterized as a power function of the sampling area. The cokriging technique performed better than the ordinary kriging for predictions of DOC and DTN, which are highly correlated. This study provides a statistically based assessment of spatial variations in DOC and DTN and identifies the sampling effort required for their accurate quantification, leading to improved assessments of forest ecosystem C and N budgets.

Spatial variability of topsoil δ13C across Qinghai-Tibet Plateau

2021 ◽  
Author(s):  
Yunsen Lai ◽  
Shaoda Li ◽  
Xiaolu Tang ◽  
Xinrui Luo ◽  
Liang Liu ◽  
...  
Keyword(s):  
Climate Change ◽  
Machine Learning ◽  
Spatial Variability ◽  
Soil Carbon ◽  
Tibet Plateau ◽  
Learning Approach ◽  
Carbon Turnover ◽  
Machine Learning Approach ◽  
Qinghai Tibet Plateau ◽  
Soil Carbon Turnover

<p>Soil carbon isotopes (δ<sup>13</sup>C) provide reliable insights at the long-term scale for the study of soil carbon turnover and topsoil δ<sup>13</sup>C could well reflect organic matter input from the current vegetation. Qinghai-Tibet Plateau (QTP) is called “the third pole of the earth” because of its high elevation, and it is one of the most sensitive and critical regions to global climate change worldwide. Previous studies focused on variability of soil δ<sup>13</sup>C at in-site scale. However, a knowledge gap still exists in the spatial pattern of topsoil δ<sup>13</sup>C in QTP. In this study, we first established a database of topsoil δ<sup>13</sup>C with 396 observations from published literature and applied a Random Forest (RF) algorithm (a machine learning approach) to predict the spatial pattern of topsoil δ<sup>13</sup>C using environmental variables. Results showed that topsoil δ<sup>13</sup>C significantly varied across different ecosystem types (p < 0.05).  Topsoil δ<sup>13</sup>C was -26.3 ± 1.60 ‰ for forest, 24.3 ± 2.00 ‰ for shrubland, -23.9 ± 1.84 ‰ for grassland, -18.9 ± 2.37 ‰ for desert, respectively. RF could well predict the spatial variability of topsoil δ<sup>13</sup>C with a model efficiency (pseudo R<sup>2</sup>) of 0.65 and root mean square error of 1.42. The gridded product of topsoil δ<sup>13</sup>C and topsoil β (indicating the decomposition rate of soil organic carbon, calculated by δ<sup>13</sup>C divided by logarithmically converted SOC) with a spatial resolution of 1000 m were developed. Strong spatial variability of topsoil δ<sup>13</sup>C was observed, which increased gradually from the southeast to the northwest in QTP. Furthermore, a large variation was found in β, ranging from -7.87 to -81.8, with a decreasing trend from southeast to northwest, indicating that carbon turnover rate was faster in northwest QTP compared to that of southeast. This study was the first attempt to develop a fine resolution product of topsoil δ<sup>13</sup>C for QTP using a machine learning approach, which could provide an independent benchmark for biogeochemical models to study soil carbon turnover and terrestrial carbon-climate feedbacks under ongoing climate change.</p>

Using Information about Spatial Variability to Improve Estimates of Total Soil Carbon

2006 ◽  
Vol 98 (3) ◽  
pp. 823-829 ◽  
Author(s):  
A. N. Kravchenko ◽  
G. P. Robertson ◽  
S. S. Snap ◽  
A. J. M. Smucker
Keyword(s):  
Spatial Variability ◽  
Soil Carbon ◽  
Total Soil

scholarly journals Alaskan soil carbon stocks: spatial variability and dependence on environmental factors

2012 ◽  
Vol 9 (5) ◽  
pp. 5695-5718 ◽  
Author(s):  
U. Mishra ◽  
W. J. Riley
Keyword(s):  
Climate Change ◽  
Spatial Variability ◽  
Soil Carbon ◽  
Active Layer ◽  
High Latitude ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Intergovernmental Panel ◽  
Soil Wetness ◽  
Soc Stocks

Abstract. The direction and magnitude of soil organic carbon (SOC) changes in response to climate change depend on the spatial and vertical distributions of SOC. We estimated spatially-resolved SOC stocks from surface to C horizon, distinguishing active-layer and permafrost-layer stocks, based on geospatial analysis of 472 soil profiles and spatially referenced environmental variables for Alaska. Total Alaska state-wide SOC stock was estimated to be 77 Pg, with 61% in the active-layer, 27% in permafrost, and 12% in non-permafrost soils. Prediction accuracy was highest for the active-layer as demonstrated by highest ratio of performance to deviation (1.5). Large spatial variability was predicted, with whole-profile, active-layer, and permafrost-layer stocks ranging from 1–296 kg C m−2, 2–166 kg m−2, and 0–232 kg m−2, respectively. Temperature and soil wetness were found to be primary controllers of whole-profile, active-layer, and permafrost-layer SOC stocks. Secondary controllers, in order of importance, were: land cover type, topographic attributes, and bedrock geology. The observed importance of soil wetness rather than precipitation on SOC stocks implies that the poor representation of high-latitude soil wetness in Earth System Models may lead to large uncertainty in predicted SOC stocks under future climate change scenarios. Under strict caveats described in the text and assuming temperature changes from the A1B Intergovernmental Panel on Climate Change emissions scenario, our geospatial model indicates that the equilibrium average 2100 Alaska active-layer depth could deepen by 11 cm, resulting in a thawing of 13 Pg C currently in permafrost. The equilibrium SOC loss associated with this warming would be highest under continuous permafrost (31%), followed by discontinuous (28%), isolated (24.3%), and sporadic (23.6%) permafrost areas. Our high resolution mapping of soil carbon stock reveals the potential vulnerability of high-latitude soil carbon and can be used as a basis for future studies of anthropogenic and climatic perturbations.

scholarly journals Quantity and Spatial Variability of Soil Carbon in the Conterminous United States

2006 ◽  
Vol 70 (2) ◽  
pp. 590-600 ◽  
Author(s):  
Yinyan Guo ◽  
Ronald Amundson ◽  
Peng Gong ◽  
Qian Yu
Keyword(s):  
United States ◽  
Spatial Variability ◽  
Soil Carbon

Spatial Variability of Soil Carbon in Forested and Cultivated Sites

2003 ◽  
Vol 32 (1) ◽  
pp. 278 ◽  
Author(s):  
Richard T. Conant ◽  
Gordon R. Smith ◽  
Keith Paustian
Keyword(s):  
Spatial Variability ◽  
Soil Carbon

scholarly journals Impact of 40 years poplar cultivation on soil carbon stocks and greenhouse gas fluxes

2005 ◽  
Vol 2 (4) ◽  
pp. 897-931 ◽  
Author(s):  
C. Ferré ◽  
A. Leip ◽  
G. Matteucci ◽  
F. Previtali ◽  
G. Seufert
Keyword(s):  
Spatial Variability ◽  
Soil Carbon ◽  
Greenhouse Gas ◽  
Carbon Stocks ◽  
Natural Forest ◽  
Small Scale ◽  
Forest Site ◽  
Poplar Plantation ◽  
Alluvial Deposits ◽  
Soil Carbon Stocks

Abstract. Within the JRC Kyoto Experiment in the Regional Park and UN-Biosphere Reserve "Parco Ticino" (North-Italy, near Pavia), the soil carbon stocks and fluxes of CO2, N2O, and CH4 were measured in a poplar plantation in comparison with a natural mesohygrophilous deciduous forest nearby, which represents the pristine land cover of the area. Soil fluxes were measured using the static and dynamic closed chamber techniques for CH4 N2O, and CO2, respectively. We made further a pedological study to relate the spatial variability found with soil parameters. Annual emission fluxes of N2O and CO2 and deposition fluxes of CH4 were calculated for the year 2003 for the poplar plantation and compared to those measured at the natural forest site. N2O emissions at the poplar plantation were 0.15$plusmn;0.1 g N2O m-2 y-1 and the difference to the emissions at the natural forest of 0.07±0.06 g N2O m-2 y-1 are partly due to a period of high emissions after the flooding of the site at the end of 2002. CH4 consumption at the natural forest was twice as large as at the poplar plantation. In comparison to the relict forest, carbon stocks in the soil under the poplar plantation were depleted by 61% of surface (10 cm) carbon and by 25% down the profile under tillage (45 cm). Soil respiration rates were not significant different at both sites with 1608±1053 and 2200±791 g CO2 m-2 y-1 at the poplar plantation and natural forest, respectively, indicating that soil organic carbon is much more stable in the natural forest. In terms of the greenhouse gas budget, the non-CO2 gases contributed minor to the overall soil balance with only 0.9% (N2O) and -0.3% (CH4 of CO2-eq emissions in the natural forest, and 2.7% (N2O) and -0.2% of CO2-eq. emissions in the poplar plantation. The very high spatial variability of soil fluxes within the two sites was related to the morphology of the floodplain area, which was formed by the historic course of the Ticino river and led to a small-scale (tenth of meters) variability in soil texture and to small-scale differences in elevation. Differences of site conditions are reflected by differences of inundation patterns, ecosystem productivity, CO2 and N2O emission rates, and soil contents of carbon and nitrogen. Additional variability was observed during a flooding event and after fertilisation at the poplar site. Despite of this variability, the two sites are comparable as both originate from alluvial deposits. The study shows that changes in soil carbon stocks and related fertility are the most visible phenomena after 40 years of land use change from a pristine forest to a fast growing poplar plantation. Therefore, the conservation and careful management of existing carbon stocks deserves highest priority in the context of the Kyoto Protocol.

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