Estimating soil carbon fluxes following land-cover change: a test of some critical assumptions for a region in Costa Rica

Changes in soil carbon storage that accompany land‐cover change may have significant effects on the global carbon cycle. The objective of this work was to examine how assumptions about preconversion soil C storage and the effects of land‐cover change influence estimates of regional soil C storage. We applied three models of land‐cover change effects to two maps of preconversion soil C in a 140 000 ha area of northeastern Costa Rica. One preconversion soil C map was generated using values assigned to tropical wet forest from the literature, the second used values obtained from extensive field sampling. The first model of land‐cover change effects used values that are typically applied in global assessments, the second and third models used field data but differed in how the data were aggregated (one was based on land‐cover transitions and one was based on terrain attributes). Changes in regional soil C storage were estimated for each combination of model and preconversion soil C for three time periods defined by geo‐referenced land‐cover maps. The estimated regional soil C under forest vegetation (to 0.3 m) was higher in the map based on field data (10.03 Tg C) than in the map based on literature data (8.90 Tg C), although the range of values derived from propagating estimation errors was large (7.67–12.40 Tg C). Regional soil C storage declined through time due to forest clearing for pasture and crops. Estimated CO₂ fluxes depended more on the model of land‐cover change effects than on preconversion soil C. Cumulative soil C losses (1950–1996) under the literature model of land‐cover effects exceeded estimates based on field data by factors of 3.8–8.0. In order to better constrain regional and global‐scale assessments of carbon fluxes from soils in the tropics, future research should focus on methods for extrapolating regional‐scale constraints on soil C dynamics to larger spatial and temporal scales.     

Soil carbon stocks and changes after oil palm introduction in the Brazilian Amazon

As oil palm has been considered one of the most favorable oilseeds for biodiesel production in Brazil, it is important to understand how cultivation of this perennial crop will affect the dynamics of soil organic carbon (SOC) in the long term. The aim of this study was to evaluate the changes in soil C stocks after the conversion of forest and pasture into oil palm production in the Amazon Region. Soil samples were collected in March 2008 and September 2009 in five areas: native forest (NARF), pasture cultivated for 55 years (PAST), and oil palm cultivated for 4 (OP‐4), 8 (OP‐8) and 25 years (OP‐25), respectively. Soils were sampled in March 2008 to evaluate the spatial variability of SOC and nitrogen (N) contents in relation to the spacing between trees. In September 2009, soils were sampled to evaluate the soil C stocks in the avenues (inter rows) and frond piles, and to compare the total C stocks with natural forest and pasture system. Soil C contents were 22–38% higher in the area nearest the oil palm base (0.6 m) than the average across the inter row (0–4.5 m from the tree), indicating that the increment in soil organic matter (SOM) must have been largely derived from root material. The soil C stocks under palm frond piles were 9–26% higher than in the inter rows, due to inputs of SOM by pruned palm fronds. The soil carbon stocks in oil palm areas, after adjustments for differences in bulk density and clay content across treatments, were 35–46% lower than pasture soil C stocks, but were 0–18% higher than the native forest soil C content. The results found here may be used to improve the life cycle assessment of biodiesel derived from palm oil.     

Widespread decreases in topsoil inorganic carbon stocks across China's grasslands during 1980s–2000s

Soil carbon (C) stocks consist of inorganic and organic components, ~1.7 times larger than the total of the C stored in vegetation and the atmosphere together. Significant soil C losses could thus offset any C sink in vegetation, creating a positive feedback to climate change. However, compared with the susceptible sensitivity of organic matter decay to climate warming, soil inorganic carbon (SIC) stocks are often assumed to be relatively stable. Here, we evaluated SIC changes across China's grasslands over the last two decades using data from a recent regional soil survey during 2001–2005 and historical national soil inventory during the 1980s. Our results showed that SIC stocks in the top 10 cm decreased significantly between the two sampling periods, with a mean rate of 26.8 (95% confidence interval: 15.8–41.7) g C m^?2 yr^?1. The larger decreases in SIC stocks were observed in those regions with stronger soil acidification and richer soil carbonates. The lost SIC could be released to the atmosphere as carbon dioxide, redistributed to the deeper soil layer, and transferred to the nearby regions. The fraction of soil carbonates entering into the atmosphere may diminish the strength of terrestrial C sequestration and amplify the positive C‐climate feedback.     

The importance of climate and soils for estimates of net primary production: a sensitivity analysis with the terrestrial ecosystem model

We used the Terrestrial Ecosystem Model (TEM) to investigate how alternative input data sets of climate (temperature/precipitation), solar radiation, and soil texture affect estimates of net primary productivity (NPP) for the conterminous United States. At the continental resolution, the climates of Cramer and Leemans (C&L) and of the Vegetation/ Ecosystem Modelling and Analysis Project (VEMAP) represent cooler and drier conditions for the United States in comparison to the Legates and Willmott (L&W) climate, and cause 5.2% and 2.3% lower estimates of NPP. Solar radiation derived from C&L and given in VEMAP is 32% and 60% higher than the solar radiation data derived from Hahn cloudiness. These differences cause ～ 8% and 10% lower NPP because of radiation-induced water stress. In comparison to the FAO/CSRC soil texture, which represents most biomes with loam soils, the soil textures are finer (more silt and clay) in the Zobler and VEMAP data sets. The use of VEMAP soil textures instead of FAO/CSRC soil textures causes ～ 3% higher NPP because enhanced volumetric soil moisture causes higher rates of nitrogen cycling, but use of the Zobler soil textures has little effect. In general, NPP estimates of TEM are more sensitive to alternative data sets at the biome and grid cell resolutions than at the continental resolution. At all spatial resolutions, the sensitivity of NPP estimates represents the impact of uncertainty among the alternative data sets we used in this study. The reduction of uncertainty in input data sets is required to improve the spatial resolution of NPP estimates by process-based ecosystem models, and is especially important for improving assessments of the regional impacts of global change.     

Soil carbon stocks and land use change: a meta analysis

The effects of land use change on soil carbon stocks are of concern in the context of international policy agendas on greenhouse gas emissions mitigation. This paper reviews the literature for the influence of land use changes on soil C stocks and reports the results of a meta analysis of these data from 74 publications. The meta analysis indicates that soil C stocks decline after land use changes from pasture to plantation (?10%), native forest to plantation (?13%), native forest to crop (?42%), and pasture to crop (?59%). Soil C stocks increase after land use changes from native forest to pasture (+ 8%), crop to pasture (+ 19%), crop to plantation (+ 18%), and crop to secondary forest (+ 53%). Wherever one of the land use changes decreased soil C, the reverse process usually increased soil carbon and vice versa. As the quantity of available data is not large and the methodologies used are diverse, the conclusions drawn must be regarded as working hypotheses from which to design future targeted investigations that broaden the database. Within some land use changes there were, however, sufficient examples to explore the role of other factors contributing to the above conclusions. One outcome of the meta analysis, especially worthy of further investigation in the context of carbon sink strategies for greenhouse gas mitigation, is that broadleaf tree plantations placed onto prior native forest or pastures did not affect soil C stocks whereas pine plantations reduced soil C stocks by 12–15%.     

Determination of Spatial Distribution Patterns of Clay and Plant Available Potassium Contents in Surface Soils at the Farm Scale using High Resolution Gamma Ray Spectrometry

Variation in dryland crop yield is often related to underlying soil properties such as water availability and soil fertility. There are often significant difficulties in adequately defining the spatial distribution of such properties at the farm scale. Gamma ray spectrometry (radiometrics) is a relatively new soil sensing technique that can potentially address this by improving the mapping of soil texture and plant available potassium (bic-K). Three sites North Nolba, South Nolba and Summerset were investigated using exploratory linear correlation analysis. Mapping analysis was focused on the Summerset site. In contrast to the two Nolba sites, the soils from Summerset had sufficient soil texture range and parent material conditions that allowed for calibrations to be developed. Soil properties were mapped at Summerset using multivariate linear regression and tree-based models with radiometric, topographic and location data as the inputs. A multivariate linear regression analysis using radiometric data was associated with greater than 70% of the variance in bic-K and soil texture at Summerset. Field checked maps indicated that up to 66% and 60% of the variation in clay and bic-K contents respectively, could be predicted. The overall lowest map errors in root mean square error (RMSE) were 2.4 dag/kg clay and 103 mg/kg bic-K contents. This study concludes that for a site with weathered soils of sufficient soil texture range, radiometrics can reliably predict clay and plant available potassium contents. Radiometrics has practical farm scale applications at a precision that is useful for understanding potential yield variation across a farm.     

Baseline map of organic carbon in Australian soil to support national carbon accounting and monitoring under climate change

We can effectively monitor soil condition—and develop sound policies to offset the emissions of greenhouse gases—only with accurate data from which to define baselines. Currently, estimates of soil organic C for countries or continents are either unavailable or largely uncertain because they are derived from sparse data, with large gaps over many areas of the Earth. Here, we derive spatially explicit estimates, and their uncertainty, of the distribution and stock of organic C in the soil of Australia. We assembled and harmonized data from several sources to produce the most comprehensive set of data on the current stock of organic C in soil of the continent. Using them, we have produced a fine spatial resolution baseline map of organic C at the continental scale. We describe how we made it by combining the bootstrap, a decision tree with piecewise regression on environmental variables and geostatistical modelling of residuals. Values of stock were predicted at the nodes of a 3‐arc‐sec (approximately 90 m) grid and mapped together with their uncertainties. We then calculated baselines of soil organic C storage over the whole of Australia, its states and territories, and regions that define bioclimatic zones, vegetation classes and land use. The average amount of organic C in Australian topsoil is estimated to be 29.7 t ha^?1 with 95% confidence limits of 22.6 and 37.9 t ha^?1. The total stock of organic C in the 0–30 cm layer of soil for the continent is 24.97 Gt with 95% confidence limits of 19.04 and 31.83 Gt. This represents approximately 3.5% of the total stock in the upper 30 cm of soil worldwide. Australia occupies 5.2% of the global land area, so the total organic C stock of Australian soil makes an important contribution to the global carbon cycle, and it provides a significant potential for sequestration. As the most reliable approximation of the stock of organic C in Australian soil in 2010, our estimates have important applications. They could support Australia's National Carbon Accounting System, help guide the formulation of policy around carbon offset schemes, improve Australia's carbon balances, serve to direct future sampling for inventory, guide the design of monitoring networks and provide a benchmark against which to assess the impact of changes in land cover, land management and climate on the stock of C in Australia. In this way, these estimates would help us to develop strategies to adapt and mitigate the effects of climate change.     

Peat carbon stocks in the southern Mackenzie River Basin: uncertainties revealed in a high-resolution case study

The organic carbon (C) stocks contained in peat were estimated for a wetland‐rich boreal region of the Mackenzie River Basin, Canada, using high‐resolution wetland map data, available peat C characteristic and peat depth datasets, and geostatistics. Peatlands cover 32% of the 25 119 km² study area, and consist mainly of surface‐ and/or groundwater‐fed treed peatlands. The thickness of peat deposits measured at 203 sites was 2.5 m on average but as deep as 6 m, and highly variable between sites. Peat depths showed little relationship with terrain data within 1 and 5 km, but were spatially autocorrelated, and were generalized using ordinary kriging. Polygon‐scale calculations and Monte Carlo simulations yielded a total peat C stock of 982–1025 × 10¹² g C that varied in C mass per unit area between 53 and 165 kg m^?2. This geostatistical approach showed as much as 10% more peat C than calculations using mean depths. We compared this estimate with an overlapping 7868 km² portion of an independent peat C stock estimate for western Canada, which revealed similar values for total peatland area, total C stock, and total peat C mass per unit area. However, agreement was poor within ～875 km² grids owing to inconsistencies in peatland cover and little relationship in peat depth between estimates. The greatest disagreement in mean peat C mass per unit area occurred in grids with the largest peatland cover, owing to the spatial coincidence of large cover and deep peat in our high‐resolution assessment. We conclude that total peat C stock estimates in the southern Mackenzie Basin and perhaps in boreal western Canada are likely of reasonable accuracy. However, owing to uncertainties particularly in peat depth, the quality of information regarding the location of these large stocks at scales as wide as several hundreds of square kilometers is presently much more limited.     

An alternative approach to reduce algorithm‐derived biases in monitoring soil organic carbon changes

Quantifying soil organic carbon (SOC) changes is a fundamental issue in ecology and sustainable agriculture. However, the algorithm‐derived biases in comparing SOC status have not been fully addressed. Although the methods based on equivalent soil mass (ESM) and mineral‐matter mass (EMMM) reduced biases of the conventional methods based on equivalent soil volume (ESV), they face challenges in ensuring both data comparability and accuracy of SOC estimation due to unequal basis for comparison and using unconserved reference systems. We introduce the basal mineral‐matter reference systems (soils at time zero with natural porosity but no organic matter) and develop an approach based on equivalent mineral‐matter volume (EMMV). To show the temporal bias, SOC change rates were recalculated with the ESV method and modified methods that referenced to soils at time t1 (ESM, EMMM, and EMMV‐t1) or referenced to soils at time zero (EMMV‐t0) using two datasets with contrasting SOC status. To show the spatial bias, the ESV‐ and EMMV‐t0‐derived SOC stocks were compared using datasets from six sites across biomes. We found that, in the relatively C‐rich forests, SOC accumulation rates derived from the modified methods that referenced to t1 soils and from the EMMV‐t0 method were 5.7%–13.6% and 20.6% higher than that calculated by the ESV method, respectively. Nevertheless, in the C‐poor lands, no significant algorithmic biases of SOC estimation were observed. Finally, both the SOC stock discrepancies (ESV vs. EMMV‐t0) and the proportions of this unaccounted SOC were large and site‐dependent. These results suggest that although the modified methods that referenced to t1 soils could reduce the biases derived from soil volume changes, they may not properly quantify SOC changes due to using unconserved reference systems. The EMMV‐t0 method provides an approach to address the two problems and is potentially useful since it enables SOC comparability and integrating SOC datasets.     

Soil carbon stocks,deforestation and land‐cover changes in the Western Ghats biodiversity hotspot (India)

Habitat loss and soil organic carbon (SOC) stock variations linked to land‐cover change were estimated over two decades in the most densely populated biodiversity hotspot in the world, in order to assess the possible influence of conservation practices on the protection of SOC. For a study area of 88 484 km², 70% of which lie inside the Western Ghats Biodiversity Hotspot (WGBH), land‐cover maps for two dates (1977, 1999) were built from various data sources including remote sensing images and ecological forest maps. SOC stocks were calculated from climatic parameters, altitude, physiography, rock type, soil type and land‐cover, with a modelling approach used in predictive learning and based on Multiple Additive Regression Tree. The model was trained on 361 soil profiles data, and applied to estimate SOC stocks from predictor variables using a Geographical Information System (GIS). Comparison of 1977 and 1999 land‐cover maps showed 628 km² of dense forests habitat loss (6%), corresponding to an annual deforestation rate of 0.44%. This was found consistent with other studies carried out in other parts of the WGBH, but not with FAO figures showing an increase in forest area. This could be explained by the different forest definitions used, based on ecological classification in the former, and on percentage tree cover in the latter. Unexpectedly, our results showed that despite ongoing deforestation, overall SOC stock was maintained (～0.43 Pg). But a closer examination of spatial differences showed that soil carbon losses in deforested areas were compensated by sequestration elsewhere, mainly in recent plantations and newly irrigated croplands. This suggests that more carbon sequestration in soils could be achieved in the future through appropriate wasteland management. It is also expected that increasing concerns about biodiversity loss will favour more conservation and reinforce the already prevailing protective measures, thus further maintaining C stocks.     

Peatland carbon stocks and accumulation rates in the Ecuadorian páramo

The páramo is a high altitude tropical Andean ecosystem that contains peatlands with thick horizons of carbon (C) dense soils. Soil C data are sparse for most of the páramo, especially in peatlands, which limits our ability to provide accurate regional and country wide estimates of C storage. Therefore, the objective of our research was to quantify belowground C stocks and accumulation rates in páramo peatland soils in two regions of northeastern Ecuador. Peatland soil cores were collected from Antisana Ecological Reserve and Cayambe-Coca National Park. We measured soil C densities and ¹⁴C dates to estimate soil accumulation rates. The mean peatland soil depth across both regions was 3.8 m and contained an estimated mean C storage of 1282 Mg ha^?1. Peatlands older than 3000 cal. year BP had a mean long-term C accumulation rate of 26 g m^?2 year^?1, with peatlands younger than 500 cal. year BP displaying mean recent rates of C accumulation of 134 g m^?2 year^?1. These peatlands also receive large inputs of mineral material, predominantly from volcanic deposition, that has created many interbedded non-peat mineral soil horizons that contained 48 % of the soil C. Because of large C stocks in Ecuadorian mountain peatlands and the potential disturbance from land use and climate change, additional studies are need to provide essential baseline assessments and estimates of C storage in the Andes.     

Organic carbon stocks and sequestration rates of forest soils in Germany

The National Forest Soil Inventory (NFSI) provides the Greenhouse Gas Reporting in Germany with a quantitative assessment of organic carbon (C) stocks and changes in forest soils. Carbon stocks of the organic layer and the mineral topsoil (30 cm) were estimated on the basis of ca. 1.800 plots sampled from 1987 to 1992 and resampled from 2006 to 2008 on a nationwide grid of 8 × 8 km. Organic layer C stock estimates were attributed to surveyed forest stands and CORINE land cover data. Mineral soil C stock estimates were linked with the distribution of dominant soil types according to the Soil Map of Germany (1 : 1 000 000) and subsequently related to the forest area. It appears that the C pool of the organic layer was largely depending on tree species and parent material, whereas the C pool of the mineral soil varied among soil groups. We identified the organic layer C pool as stable although C was significantly sequestered under coniferous forest at lowland sites. The mineral soils, however, sequestered 0.41 Mg C ha^?1 yr^?1. Carbon pool changes were supposed to depend on stand age and forest transformation as well as an enhanced biomass input. Carbon stock changes were clearly attributed to parent material and soil groups as sandy soils sequestered higher amounts of C, whereas clayey and calcareous soils showed small gains and in some cases even losses of soil C. We further showed that the largest part of the overall sample variance was not explained by fine‐earth stock variances, rather by the C concentrations variance. The applied uncertainty analyses in this study link the variability of strata with measurement errors. In accordance to other studies for Central Europe, the results showed that the applied method enabled a reliable nationwide quantification of the soil C pool development for a certain period.     

The impact of agricultural management on soil aggregation and carbon storage is regulated by climatic thresholds across a 3000 km European gradient

Organic carbon and aggregate stability are key features of soil quality and are important to consider when evaluating the potential of agricultural soils as carbon sinks. However, we lack a comprehensive understanding of how soil organic carbon (SOC) and aggregate stability respond to agricultural management across wide environmental gradients. Here, we assessed the impact of climatic factors, soil properties and agricultural management (including land use, crop cover, crop diversity, organic fertilization, and management intensity) on SOC and the mean weight diameter of soil aggregates, commonly used as an indicator for soil aggregate stability, across a 3000 km European gradient. Soil aggregate stability (−56%) and SOC stocks (−35%) in the topsoil (20 cm) were lower in croplands compared with neighboring grassland sites (uncropped sites with perennial vegetation and little or no external inputs). Land use and aridity were strong drivers of soil aggregation explaining 33% and 20% of the variation, respectively. SOC stocks were best explained by calcium content (20% of explained variation) followed by aridity (15%) and mean annual temperature (10%). We also found a threshold-like pattern for SOC stocks and aggregate stability in response to aridity, with lower values at sites with higher aridity. The impact of crop management on aggregate stability and SOC stocks appeared to be regulated by these thresholds, with more pronounced positive effects of crop diversity and more severe negative effects of crop management intensity in nondryland compared with dryland regions. We link the higher sensitivity of SOC stocks and aggregate stability in nondryland regions to a higher climatic potential for aggregate-mediated SOC stabilization. The presented findings are relevant for improving predictions of management effects on soil structure and C storage and highlight the need for site-specific agri-environmental policies to improve soil quality and C sequestration.     

Drivers of postfire soil organic carbon accumulation in the boreal forest

The accumulation of soil carbon (C) is regulated by a complex interplay between abiotic and biotic factors. Our study aimed to identify the main drivers of soil C accumulation in the boreal forest of eastern North America. Ecosystem C pools were measured in 72 sites of fire origin that burned 2–314 years ago over a vast region with a range of ? mean annual temperature of 3°C and one of ? 500 mm total precipitation. We used a set of multivariate a priori causal hypotheses to test the influence of time since fire (TSF), climate, soil physico‐chemistry and bryophyte dominance on forest soil organic C accumulation. Integrating the direct and indirect effects among abiotic and biotic variables explained as much as 50% of the full model variability. The main direct drivers of soil C stocks were: TSF >bryophyte dominance of the FH layer and metal oxide content >pH of the mineral soil. Only climate parameters related to water availability contributed significantly to explaining soil C stock variation. Importantly, climate was found to affect FH layer and mineral soil C stocks indirectly through its effects on bryophyte dominance and organo‐metal complexation, respectively. Soil texture had no influence on soil C stocks. Soil C stocks increased both in the FH layer and mineral soil with TSF and this effect was linked to a decrease in pH with TSF in mineral soil. TSF thus appears to be an important factor of soil development and of C sequestration in mineral soil through its influence on soil chemistry. Overall, this work highlights that integrating the complex interplay between the main drivers of soil C stocks into mechanistic models of C dynamics could improve our ability to assess C stocks and better anticipate the response of the boreal forest to global change.     

Smallholder farms have and can store more carbon than previously estimated

Increasing soil organic carbon (SOC) stocks is increasingly targeted as a key strategy in climate change mitigation and improved ecosystem resiliency. Agricultural land, a dominant global land use, provides substantial challenges and opportunities for global carbon sequestration. Despite this, global estimates of soil carbon sequestration potential often exclude agricultural land and estimates are coarse for regions in the Global South. To address these discrepancies and improve estimates, we develop a hybrid, data-augmented database approach to better estimate the magnitude of SOC sequestration potential of agricultural soils. With high-resolution (30 m) soil maps of Africa developed by the International Soils Database (iSDA) and Malawi as a case study, we create a national adjustment using site-specific soil data retrieved from 1160 agricultural fields. We use a benchmark approach to estimate the amount of SOC Malawian agricultural soils can sequester, accounting for edaphic and climatic conditions, and calculate the resulting carbon gap. Field measurements of SOC stocks and sequestration potentials were consistently larger than iSDA predictions, with an average carbon gap of 4.42 ± 0.23 Mg C ha⁻¹ to a depth of 20 cm, with some areas exceeding 10 Mg C ha⁻¹. Augmenting iSDA predictions with field data also improved sensitivity to identify areas with high SOC sequestration potential by 6%—areas that may benefit from improved management practices. Overall, we estimate that 6.8 million ha of surface soil suitable for agriculture in Malawi has the potential to store 274 ± 14 Tg SOC. Our approach illustrates how ground truthing efforts remain essential to reduce errors in continent-wide soil carbon predictions for local and regional use. This work begins efforts needed across regions to develop soil carbon benchmarks that inform policies and identify high-impact areas in the effort to increase SOC globally.     

排水对若尔盖高原泥炭地土壤有机碳储量的影响

泥炭地作为陆地上生态系统一个重要碳汇,存储了全球土壤有机碳储量的25%—43%。泥炭地排水与其他土地利用导致了大量的土壤有机碳损失。然而,有关排水对中国泥炭地土壤有机碳储量的影响研究报道较少,因此,为了获得更多可靠的泥炭地碳储量信息,以便减少它们估算的不确定性。选取了我国若尔盖高原未排水泥炭地和排水泥炭地进行土壤剖面取样,定量评价排水对泥炭地土壤有机碳储量的影响。研究表明:(1)未排水泥炭地土壤有机碳储量平均值为(923.71±107.18)t C/hm~2,为中国陆地和全球陆地土壤有机碳储量的8.1和9.4倍;而排水泥炭地土壤有机碳储量平均值为(574.01±66.86)t C/hm~2,为中国和全球陆地的5.1和5.8倍。(2)泥炭地排水后,导致表层(0—30 cm)土壤有机碳储量增加(59.11±9.31)t C/hm~2,可能源于土壤容重增加。(3)然而,完全考虑泥炭剖面深度后,排水泥炭地土壤有机碳储量较对照样地减少了349.7 t C/hm~2,这可能是由于泥炭地排水后,水位降低,加速了泥炭氧化,降低了泥炭厚度。     

Modeling Soil Carbon Dynamics in Northern Forests: Effects of Spatial and Temporal Aggregation of Climatic Input Data

Boreal forests contain 30% of the global forest carbon with the majority residing in soils. While challenging to quantify, soil carbon changes comprise a significant, and potentially increasing, part of the terrestrial carbon cycle. Thus, their estimation is important when designing forest-based climate change mitigation strategies and soil carbon change estimates are required for the reporting of greenhouse gas emissions. Organic matter decomposition varies with climate in complex nonlinear ways, rendering data aggregation nontrivial. Here, we explored the effects of temporal and spatial aggregation of climatic and litter input data on regional estimates of soil organic carbon stocks and changes for upland forests. We used the soil carbon and decomposition model Yasso07 with input from the Norwegian National Forest Inventory (11275 plots, 1960–2012). Estimates were produced at three spatial and three temporal scales. Results showed that a national level average soil carbon stock estimate varied by 10% depending on the applied spatial and temporal scale of aggregation. Higher stocks were found when applying plot-level input compared to country-level input and when long-term climate was used as compared to annual or 5-year mean values. A national level estimate for soil carbon change was similar across spatial scales, but was considerably (60–70%) lower when applying annual or 5-year mean climate compared to long-term mean climate reflecting the recent climatic changes in Norway. This was particularly evident for the forest-dominated districts in the southeastern and central parts of Norway and in the far north. We concluded that the sensitivity of model estimates to spatial aggregation will depend on the region of interest. Further, that using long-term climate averages during periods with strong climatic trends results in large differences in soil carbon estimates. The largest differences in this study were observed in central and northern regions with strongly increasing temperatures.     

Soil organic carbon stocks in Laos: spatial variations and controlling factors

Surface soils, which contain the largest pool of terrestrial organic carbon (C), may be able to sequester atmospheric C and thus mitigate climate change. However, this remains controversial, largely due to insufficient data and knowledge gaps in respect of organic C contents and stocks in soils and the main factors of their control. Up to now and despite numerous evaluations of soil organic carbon (SOC) stocks worldwide, the sloping lands of southeast Asia, one of the most biogeochemically active regions of the world, remain uninvestigated. Our main objective was to quantify SOC stocks and to evaluate the impact of various environmental factors. We, therefore, selected Laos with 230 566 km² of mostly forested steep slopes, and where cultivation is still mainly traditional, i.e. a system of shifting cultivation without fertilization or mechanical tillage. Analytical data from 3471 soil profiles demonstrated that the top 1 m of soil depth holds an estimated 4.64 billion tons of SOC, 65% of which is in the first 0.3 m. SOC stocks to 0.3 m exhibit a high coefficient of variation (CV=62%) with values from 1.8 to 771 Mg C ha^?1 and a mean at 129 Mg C ha^?1. Furthermore, these stocks are significantly (at P<0.05 level) affected by land use as shown by principal components analysis and t‐tests with the largest amount being found under forest, less under shifting cultivation and the smallest under continuous cultivation. Moreover, SOC stocks correlated regionally to total annual rainfalls and latitude, and locally at the hill‐slope level to the distance to the stream network and the slope angle. It is hypothesized that this correlation is through actions on mineral weathering, soil clay content, soil fertility and SOC redistributions in landscapes. These relationships between SOC stocks and environmental factors may be of further use in (1) predicting the impact of global changes on future SOC stocks; and (2) identifying optimal strategies for land use planning so as to minimize soil C emissions to the atmosphere while maximizing carbon sequestration in soils.