Detecting small-scale spatial heterogeneity and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

Abstract. Carbon (C) sequestration in soils plays a key role in the global C cycle. It is therefore crucial to adequately monitor dynamics in soil organic carbon (∆SOC) stocks when aiming to reveal underlying processes and potential drivers. However, small-scale spatial and temporal changes in SOC stocks, particularly pronounced on arable lands, are hard to assess. The main reasons for this are limitations of the well-established methods. On the one hand, repeated soil inventories, often used in long-term field trials, reveal spatial patterns and trends in ∆SOC but require a longer observation period and a sufficient number of repetitions. On the other hand, eddy covariance measurements of C fluxes towards a complete C budget of the soil-plant-atmosphere system may help to obtain temporal ∆SOC patterns but lack small-scale spatial resolution. To overcome these limitations, this study presents a reliable method to detect both short-term temporal as well as small-scale spatial dynamics of ΔSOC. Therefore, a combination of automatic chamber (AC) measurements of CO2 exchange and empirically modeled aboveground biomass development (NPPshoot) was used. To verify our method, results were compared with ΔSOC observed by soil resampling. AC measurements were performed from 2010 to 2014 under a silage maize/winter fodder rye/sorghum-Sudan grass hybrid/alfalfa crop rotation at a colluvial depression located in the hummocky ground moraine landscape of NE Germany. Widespread in large areas of the formerly glaciated Northern Hemisphere, this depression type is characterized by a variable groundwater level (GWL) and pronounced small-scale spatial heterogeneity in soil properties, such as SOC and nitrogen (Nt). After monitoring the initial stage during 2010, soil erosion was experimentally simulated by incorporating topsoil material from an eroded midslope soil into the plough layer of the colluvial depression. SOC stocks were quantified before and after soil manipulation and at the end of the study period. AC-based ∆SOC values corresponded well with the tendencies and magnitude of the results observed in the repeated soil inventory. The period of maximum plant growth was identified as being most important for the development of spatial differences in annual ΔSOC. Hence, we were able to confirm that AC-based C budgets are able to reveal small-scale spatial and short-term temporal dynamics of ∆SOC.

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Detecting small-scale spatial heterogeneity and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

Biogeosciences ◽

10.5194/bg-14-1003-2017 ◽

2017 ◽

Vol 14 (4) ◽

pp. 1003-1019 ◽

Cited By ~ 13

Author(s):

Mathias Hoffmann ◽

Nicole Jurisch ◽

Juana Garcia Alba ◽

Elisa Albiac Borraz ◽

Marten Schmidt ◽

...

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Spatial Heterogeneity ◽

Temporal Dynamics ◽

Small Scale ◽

Short Term ◽

C Cycle ◽

Spatial Differences ◽

Northeastern Germany ◽

Soc Stocks

Abstract. Carbon (C) sequestration in soils plays a key role in the global C cycle. It is therefore crucial to adequately monitor dynamics in soil organic carbon (ΔSOC) stocks when aiming to reveal underlying processes and potential drivers. However, small-scale spatial (10–30 m) and temporal changes in SOC stocks, particularly pronounced in arable lands, are hard to assess. The main reasons for this are limitations of the well-established methods. On the one hand, repeated soil inventories, often used in long-term field trials, reveal spatial patterns and trends in ΔSOC but require a longer observation period and a sufficient number of repetitions. On the other hand, eddy covariance measurements of C fluxes towards a complete C budget of the soil–plant–atmosphere system may help to obtain temporal ΔSOC patterns but lack small-scale spatial resolution. To overcome these limitations, this study presents a reliable method to detect both short-term temporal dynamics as well as small-scale spatial differences of ΔSOC using measurements of the net ecosystem carbon balance (NECB) as a proxy. To estimate the NECB, a combination of automatic chamber (AC) measurements of CO2 exchange and empirically modeled aboveground biomass development (NPPshoot) were used. To verify our method, results were compared with ΔSOC observed by soil resampling. Soil resampling and AC measurements were performed from 2010 to 2014 at a colluvial depression located in the hummocky ground moraine landscape of northeastern Germany. The measurement site is characterized by a variable groundwater level (GWL) and pronounced small-scale spatial heterogeneity regarding SOC and nitrogen (Nt) stocks. Tendencies and magnitude of ΔSOC values derived by AC measurements and repeated soil inventories corresponded well. The period of maximum plant growth was identified as being most important for the development of spatial differences in annual ΔSOC. Hence, we were able to confirm that AC-based C budgets are able to reveal small-scale spatial differences and short-term temporal dynamics of ΔSOC.

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Spatial heterogeneity and environmental predictors of permafrost region soil organic carbon stocks

Science Advances ◽

10.1126/sciadv.aaz5236 ◽

2021 ◽

Vol 7 (9) ◽

pp. eaaz5236 ◽

Cited By ~ 1

Author(s):

Umakant Mishra ◽

Gustaf Hugelius ◽

Eitan Shelef ◽

Yuanhe Yang ◽

Jens Strauss ◽

...

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Spatial Heterogeneity ◽

Surface Air Temperature ◽

Spatially Explicit ◽

Soil Profiles ◽

Permafrost Region ◽

Environmental Predictors ◽

Soil Organic Carbon Stocks ◽

Soc Stocks

Large stocks of soil organic carbon (SOC) have accumulated in the Northern Hemisphere permafrost region, but their current amounts and future fate remain uncertain. By analyzing dataset combining >2700 soil profiles with environmental variables in a geospatial framework, we generated spatially explicit estimates of permafrost-region SOC stocks, quantified spatial heterogeneity, and identified key environmental predictors. We estimated that 1014−175+194 Pg C are stored in the top 3 m of permafrost region soils. The greatest uncertainties occurred in circumpolar toe-slope positions and in flat areas of the Tibetan region. We found that soil wetness index and elevation are the dominant topographic controllers and surface air temperature (circumpolar region) and precipitation (Tibetan region) are significant climatic controllers of SOC stocks. Our results provide first high-resolution geospatial assessment of permafrost region SOC stocks and their relationships with environmental factors, which are crucial for modeling the response of permafrost affected soils to changing climate.

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Spatial heterogeneity and environmental controllers of soil organic carbon stocks in a boreal forest

10.5194/egusphere-egu2020-9359 ◽

2020 ◽

Author(s):

Udaya Vitharana ◽

Nora Casson ◽

Darshani Kumaragamage ◽

Geoff Gunn ◽

Scott Higgins ◽

...

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Spatial Variability ◽

Boreal Forest ◽

Spatial Heterogeneity ◽

Surface Soil ◽

Local Scale ◽

Gravel Content ◽

Soc Stock ◽

Soc Stocks

The knowledge of spatial heterogeneity and environmental controllers of soil organic carbon (SOC) stocks is essential for upscaling and predicting SOC dynamics under changing land use and climatic conditions. &#160;This study investigated the spatial variability and intrinsic and extrinsic controllers of SOC stocks in a boreal forest catchment (320 ha) at the International Institute for Sustainable Development Experimental Lakes Area in Ontario, Canada. Forty-seven surface soil (0-30 cm) samples, representative of the spatial variability of topography, surface water flow patterns and vegetation distribution, were obtained within the catchment. Air dried soil samples were sieved to separate gravel (>2 mm) and fine-earth (<2 mm) fractions and were analyzed for SOC concentration using the loss-on-ignition method. Core sample method was used to determine the soil bulk density. SOC concentrations in surface soils showed a large spatial variability (1.2% to 50.4%, CV= 111.3%). Thick organic soil layers in the wetlands of the sub-catchment showed the highest SOC concentrations. The surface soil SOC stocks ranged between 14.5 to 240.5 Mg ha-1 with an average stock of 101.5 Mg ha-1. Spatial autocorrelations of SOC stocks were modelled by calculating relevant variograms. The variability of SOC stocks (sill = 834) was dominated by the random variability (nugget=275) whereas the variability of SOC concentration (sill = 2.5) was dominated by the spatially structured variability (nugget = 0). We found a strong spatial autocorrelation of the SOC concentrations within the catchment, but the SOC stocks were less spatially correlated. This was largely due to the heterogeneity in the thickness of the surface soil layer (10 cm - 30 cm) and in the gravel content (0-28.9%). We found that a large over-estimation of SOC stocks (52.5%) could result if these intrinsic factors are not considered. Extrinsic controllers were generally not significantly related to the SOC stock; Spearman&#8217;s rank correlation analysis on the entire dataset showed non-significant relationships between the SOC stock and extrinsic controllers, namely NDVI (r = 0.04) elevation (r = 0.2), slope (r = -0.1) and topographic indices, stream power index (r = -0.1), relative position index (r=-0.2) and plan curvature (r = -0.1). However, regression tree analysis revealed local-scale effects of aspect, NDVI, elevation, and distance to ridge on the SOC stocks. Many forest soil databases lack information of gravel content and soil depth. Thus, upscaling boreal forest SOC stocks without these two key intrinsic controllers can lead to higher uncertainties in &#160;SOC stock estimates. Further, the impacts of extrinsic controllers may vary across heterogenous landscapes. Machine learning-based digital soil mapping techniques such as Random Forest models are more appropriate for incorporating local-scale impacts of extrinsic controllers when upscaling SOC stocks of boreal forest soils.&#160;

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Short-Term Effect of Sugarcane Straw on Soil Organic Carbon Pools

Journal of Agricultural Science ◽

10.5539/jas.v10n8p405 ◽

2018 ◽

Vol 10 (8) ◽

pp. 405 ◽

Cited By ~ 2

Author(s):

Luiz Fernando C. Leite ◽

Edvaldo Sagrilo ◽

Ademir Sergio F. de Araújo ◽

Henrique Antunes de Souza

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Soil Surface ◽

Tropical Soils ◽

C Sequestration ◽

Term Effect ◽

Short Term ◽

Short Term Effect ◽

Sugarcane Straw ◽

Soc Stocks

This study aimed to evaluate the short-term effect of sugarcane straw on soil organic carbon (SOC) stocks in tropical soils. The treatments simulated the maintenance of different rates of sugarcane straw (0, 2.2, 5.1, 7.8 and 12 t ha-1) applied on the soil surface, with four replication, and evaluated chemical and biological attributes in four depths (0-0.05; 0.05-0.10; 0.10-0.20; 0.20-0.40 m). Results from soil samples collected in the rainy and dry seasons showed evidence of positive short-term effects of green harvest either on labile and humified soil organic matter (SOM) pools. For the total SOC stocks, we observed linear responses with straw rates in both sampling seasons. A decreased humification index in the topsoil suggests more labile C pools available in the soil, resulting in a significant increase in microbial activity. Microbial indicators point towards a steady equilibrium in SOC turnover, which can lead to future lower increases in SOC stocks if high straw amounts are maintained on the soil surface. Therefore, long-term studies under low-latitude areas are necessary to model the potential of C sequestration in sugarcane green harvest systems.

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Detecting small scale spatial heterogeneity and short-term temporal variability of CO2 flux dynamics in agricultural used landscapes using a robotic chamber system

10.5194/egusphere-egu2020-955 ◽

2020 ◽

Author(s):

Shrijana Vaidya ◽

Juergen Augustin ◽

Michael Sommer ◽

Marten Schmidt ◽

Peter Rakowski ◽

...

Keyword(s):

Spatial Heterogeneity ◽

Eddy Covariance ◽

Temporal Variability ◽

Agricultural Practices ◽

Agricultural Landscapes ◽

Small Scale ◽

Chamber System ◽

Short Term ◽

Flux Dynamics ◽

Ne Germany

&#173;&#173;&#173;Improved agricultural practices sequestering additional atmospheric C within the soil are considered as one of the potential solution for mitigating global climate change. However, agricultural used landscapes are complex and their capacity to sequester additional atmospheric C might differ substantially in time and space. Hence, accurate and precise information on the complex spatio-temporal CO2 flux pattern is needed to evaluate the effects/benefits of new agricultural practices aiming towards increasing soil organic carbon.To date, different approaches are used to measure and quantify CO2 flux dynamics of agricultural landscapes, such as e.g. eddy covariance, as well as manual and automatic chamber systems. However, all these methods fail to some extend in either accounting for small scale spatial heterogeneity (eddy covariance and automatic chambers) or short-term temporal variability (manual chambers). Although, automatic chambers are in principle capable to detect small-scale spatial differences of CO2 flux dynamics in a sufficient temporal resolution, these systems are usually limited to only a few spatial repetitions which is not sufficient to represent small scale soil heterogeneity such as present within the widespread hummocky ground moraine landscape of NE-Germany.To overcome these challenges, we developed a novel robotic chamber system allowing to detect small-scale spatial heterogeneity and short-term temporal variability of CO2 (as well as CH4 and N2O) flux dynamics for a range of different fertilization and tillage management practices. The system is equipped with two canopy chambers, CR6 data logger, CDM-A116 analog multiplexer and multiple sensors to measure plant activity/biomass development in parallel. The measurements of the gaseous C exchange is performed by moving the system along the tracks with each chamber along one half of the gantry crane. Thus, each chamber measures 18 plots, out of 36 plots (2x3m; 12 per soil type) established in the study area.Here, we present first CO2 flux measurement results (spring barley; 3 different soil types) using this novel system, to prove its overall accuracy and precision. Our results show clear small-scale/within field spatial pattern and short-term temporal dynamics regarding measured ecosystem respiration, net ecosystem exchange as well as derived gross primary productivity.

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Spatial heterogeneity of soil organic carbon and total nitrogen at small scale in subalpine meadow andPicea meyeriforest in Luya Mountain

Acta Ecologica Sinica ◽

10.5846/stxb201210231466 ◽

2013 ◽

Vol 33 (24) ◽

Author(s):

武小钢 WU Xiaogang ◽

郭晋平 GUO Jinping ◽

田旭平 TIAN Xuping ◽

杨秀云 YANG Xiuyun

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Spatial Heterogeneity ◽

Total Nitrogen ◽

Small Scale ◽

Subalpine Meadow

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Stover management modifies soil organic carbon dynamics in the short-term under semiarid continuous maize

Soil and Tillage Research ◽

10.1016/j.still.2021.105143 ◽

2021 ◽

Vol 213 ◽

pp. 105143

Author(s):

Jorge Álvaro-Fuentes ◽

Samuel Franco-Luesma ◽

Victoria Lafuente ◽

Pablo Sen ◽

Asun Usón ◽

...

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Carbon Dynamics ◽

Short Term ◽

Continuous Maize ◽

Soil Organic Carbon Dynamics

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Effects of Management and Hillside Position on Soil Organic Carbon Stratification in Mediterranean Centenary Olive Grove

Agronomy ◽

10.3390/agronomy11040650 ◽

2021 ◽

Vol 11 (4) ◽

pp. 650

Author(s):

Jesús Aguilera-Huertas ◽

Beatriz Lozano-García ◽

Manuel González-Rosado ◽

Luis Parras-Alcántara

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Soil Quality ◽

Management Practices ◽

Soil Management ◽

Olive Grove ◽

No Tillage ◽

Short Term ◽

Degradation Degree

The short- and medium—long-term effects of management and hillside position on soil organic carbon (SOC) changes were studied in a centenary Mediterranean rainfed olive grove. One way to measure these changes is to analyze the soil quality, as it assesses soil degradation degree and attempts to identify management practices for sustainable soil use. In this context, the SOC stratification index (SR-COS) is one of the best indicators of soil quality to assess the degradation degree from SOC content without analyzing other soil properties. The SR-SOC was calculated in soil profiles (horizon-by-horizon) to identify the best soil management practices for sustainable use. The following time periods and soil management combinations were tested: (i) in the medium‒long-term (17 years) from conventional tillage (CT) to no-tillage (NT), (ii) in the short-term (2 years) from CT to no-tillage with cover crops (NT-CC), and (iii) the effect in the short-term (from CT to NT-CC) of different topographic positions along a hillside. The results indicate that the SR-SOC increased with depth for all management practices. The SR-SOC ranged from 1.21 to 1.73 in CT0, from 1.48 to 3.01 in CT1, from 1.15 to 2.48 in CT2, from 1.22 to 2.39 in NT-CC and from 0.98 to 4.16 in NT; therefore, the soil quality from the SR-SOC index was not directly linked to the increase or loss of SOC along the soil profile. This demonstrates the time-variability of SR-SOC and that NT improves soil quality in the long-term.

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Influence of agricultural management on soil organic carbon: A compendium and assessment of Canadian studies

Canadian Journal of Soil Science ◽

10.4141/s03-009 ◽

2003 ◽

Vol 83 (4) ◽

pp. 363-380 ◽

Cited By ~ 194

Author(s):

A. J. VandenBygaart ◽

E. G. Gregorich ◽

D. A. Angers

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Management Practices ◽

Agricultural Management ◽

Organic Fertilizers ◽

Published Data ◽

Native Land ◽

Soc Stocks ◽

Long Term Studies

To fulfill commitments under the Kyoto Protocol, Canada is required to provide verifiable estimates and uncertainties for soil organic carbon (SOC) stocks, and for changes in those stocks over time. Estimates and uncertainties for agricultural soils can be derived from long-term studies that have measured differences in SOC between different management practices. We compiled published data from long-term studies in Canada to assess the effect of agricultural management on SOC. A total of 62 studies were compiled, in which the difference in SOC was determined for conversion from native land to cropland, and for different tillage, crop rotation and fertilizer management practices. There was a loss of 24 ± 6% of the SOC after native land was converted to agricultural land. No-till (NT) increased the storage of SOC in western Canada by 2.9 ± 1.3 Mg ha-1; however, in eastern Canada conversion to NT did not increase SOC. In general, the potential to store SOC when NT was adopted decreased with increasing background levels of SOC. Using no-tillage, reducing summer fallow, including hay in rotation with wheat (Triticum aestivum L.), plowing green manures into the soil, and applying N and organic fertilizers were the practices that tended to show the most consistent in creases in SOC storage. By relating treatment SOC levels to those in the control treatments, SOC stock change factors and their levels of uncertainty were derived for use in empirical models, such as the United Nations Intergovernmental Panel on Climate Change (IPCC). Guidelines model for C stock changes. However, we must be careful when attempting to extrapolate research plot data to farmers’ fields since the history of soil and crop management has a significant influence on existing and future SOC stocks. Key words: C sequestration, tillage, crop rotations, fertilizer, cropping intensity, Canada

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Factors Constraining the Adoption of Soil Organic Carbon Enhancing Technologies Among Small-Scale Farmers in Ethiopia

SSRN Electronic Journal ◽

10.2139/ssrn.3899297 ◽

2021 ◽

Author(s):

Wilson Nguru ◽

Charles KK Gachene ◽

Cecilia M. Onyango ◽

Stanley Karanja Ng’ang’a ◽

Evan H. Girvetz

Keyword(s):

Organic Carbon ◽

Soil Organic Carbon ◽

Small Scale ◽

Small Scale Farmers

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