Soil Organic Carbon Stocks In Forests Research Articles

Simulation of Soil Organic Carbon Dynamics in Postfire Boreal Forests of China by Incorporating High-Resolution Remote Sensing Data and Field Measurement

Soil organic carbon (SOC) is an important component of the ecosystem carbon pool, and fire is one of the important disturbances in forest ecosystems. With global warming, there has been a gradual increase in boreal forest fires, which has a nonnegligible impact on the SOC dynamics in forests. The CENTURY model was employed in our study to simulate the changes in SOC stocks in boreal forests of the Great Xing’an Mountains, China under different fire severity conditions. Fire severity was represented by the metric of difference normalized burn ratio (dNBR) derived from 30-m Landsat-8 imageries. Changes in forest SOC stocks following fire disturbance were predicted under four future Representative Concentration Pathway (RCP) scenarios (RCP2.6, RCP4.5, RCP6.0, and RCP8.5). We found that the CENTURY model had good results in simulating the SOC stocks in the postfire of China’s boreal forests. Forest SOC dynamics responded differently to fire severities and the larger SOC loss was associated with increasing fire severity. Importantly, a feedback mechanism was found between climate change and SOC stocks, which reduces SOC stocks with increasing temperatures. High-severity forest fires tended to cause serious damage to the SOC pool and delay forest SOC recovery time; after such events, forest SOC stocks cannot be fully recovered to the prefire levels (6.74% loss). In addition, higher CO2 emissions and warmer temperatures significantly affected the recovery of SOC stocks after fire disturbance, resulting in larger SOC losses. Overall, we projected losses of 10.14%, 12.06%, 12.41%, and 15.70% of SOC stocks after high-severity fires in four RCP scenarios, respectively. Our findings emphasize the importance of fire disturbance and climate change on future dynamics of SOC stocks in China’s boreal forests, providing a scientific basis for future boreal forest management and fire management.

A global synthesis and conceptualization of the magnitude and duration of soil carbon losses in response to forest disturbances.

Forest disturbances are increasing around the globe due to changes in climate and management, deteriorating forests' carbon sink strength. Estimates of global forest carbon budgets account for losses of plant biomass but often neglect the effects of disturbances on soil organic carbon (SOC). Here, we aimed to quantify and conceptualize SOC losses in response to different disturbance agents on a global scale. Global. 1983-2022. Forest soils. We conducted a comprehensive global analysis of the effects of harvesting, wildfires, windstorms and insect infestations on forest SOC stocks in the surface organic layer and top mineral soil, synthesizing 927 paired observations from 151 existing field studies worldwide. We further used global mapping to assess potential SOC losses upon disturbance. We found that both natural and anthropogenic forest disturbances can cause large SOC losses up to 60 Mg ha-1. On average, the largest SOC losses were found after wildfires, followed by disturbances from windstorms, harvests and insects. However, initial carbon stock size, rather than disturbance agent, had the strongest influence on the magnitude of SOC losses. SOC losses were greatest in cold-climate forests (boreal and mountainous regions) with large accumulations of organic matter on or near the soil surface. Negative effects are present for at least four decades post-disturbance. In contrast, forests with small initial SOC stocks experienced quantitatively lower carbon losses, and their stocks returned to pre-disturbance levels more quickly. Our results indicate that the more carbon is stored in the forest's organic layers and top mineral soils, the more carbon will be lost after disturbance. Robust estimates of forest carbon budgets must therefore consider disturbance-induced SOC losses, which strongly depend on site-specific stocks. Particularly in cold-climate forests, these disturbance-related losses may challenge forest management efforts to sequester CO2.

Effects of Understory Vegetation Heterogeneity on Soil Organic Carbon Components in Cunninghamia lanceolata Plantation

As one of the important factors affecting forest soil organic carbon stocks, the effect of understory vegetation types on soil organic carbon and its components was explored to provide a theoretical basis for understory vegetation management and sustainable management in plantation forests. In order to determine the characteristics of soil organic carbon and its components under different understory vegetation types in Subtropical Cunninghamia lanceolata plantation, Indocalamus tessellatus, Diplazium donianum and Oreocnide frutescenssp were taken as research objects. The mass fractions of total organic carbon, recalcitrant organic carbon, readily oxidizable organic carbon, microbial biomass carbon and dissolved organic carbon in each soil layer at 0–10, 10–20, 20–40 and 40–60 cm were measured, and the change characteristics of soil organic carbon components were also studied and compared. The results showed that: (1) The mass fractions of total organic carbon, recalcitrant organic carbon, readily oxidizable organic carbon and microbial biomass carbon in the soils of the three understory vegetation types showed significant decreasing trends along the profile, while the mass fraction of dissolved organic carbon in 0–40 cm soil layer was significantly higher than those in 40–60 cm soil layer. (2) The mass fraction of total organic carbon (5.98–20.66 g·kg−1) had no significant difference among understory vegetation types. The mass fraction and proportion of microbial biomass carbon were higher in the 0–60 cm soil layer under cover of Indocalamus tessellatus, and the mass fractions of recalcitrant organic carbon in the 20–40 cm soil layer under Indocalamus tessellatus cover (8.57 g·kg−1) was significantly higher than that of Oreocnide frutescenssp (5.73 g·kg−1). The soil layer of 0–20 cm under the Diplazium donianum community has a higher mass fraction and proportion of readily oxidizable organic carbon. (3) Correlation analysis showed that soil organic carbon and its components were positively correlated with total nitrogen, dissolved total nitrogen, dissolved organic nitrogen and microbial biomass nitrogen. There is a significant positive correlation among the components of soil organic carbon. (4) Redundancy analysis showed that soil bulk density (41.6%), microbial biomass nitrogen (41.2%), dissolved total nitrogen (43.7%), total nitrogen (9.9%), dissolved organic nitrogen (43.6%) and pH (6.6%) were the most significant environmental factors affecting organic carbon components in four soil layers. Understory vegetation type can influence the distribution characteristics of soil organic carbon components in Cunninghamia lanceolata plantation, and soil active organic carbon components are more susceptible to the influence of understory vegetation type than total organic carbon and recalcitrant organic carbon.

Disturbance and management effects on forest soil organic carbon stocks in the Pacific Northwest.

Carbon (C)-informed forest management requires understanding how disturbance and management influence soil organic carbon (SOC) stocks at scales relevant to landowners and forest policy and management professionals. The continued growth of data sets and publications allows powerful synthesis approaches to be applied to such questions at increasingly fine scales. Here, we report results from a synthesis that used meta-analysis of published studies and two large observational databases to quantify disturbance and management impacts on SOC stocks. We conducted this, the third in a series of ecoregional SOC assessments, for the Pacific Northwest, which comprises ~8% of the land area but ~12% of the U.S. forest sector C sink. At the ecoregional level, our analysis indicated that fundamental patterns of vegetation, climate, and topography are far more important controls on SOC stocks than land use history, disturbance, or management. However, the same patterns suggested that increased warming, drying, wildland fire, and forest regeneration failure pose significant risks to SOC stocks across the region. Detailed meta-analysis results indicated that wildfires diminished SOC stocks throughout the soil profile, while prescribed fire only influenced surface organic materials and harvesting had no significant overall impact on SOC. Independent observational data corroborated the negative influence of fire on SOC derived from meta-analysis, suggested that harvest impacts may vary subregionally with climate or vegetation, and revealed that forests with agricultural uses (e.g., grazing) or legacies (e.g., cultivation) had smaller SOC stocks. We also quantified effects of a range of common forest management practices having either positive (organic amendments, nitrogen [N]-fixing vegetation establishment, inorganic N fertilization) or no overall effects on SOC (other inorganic fertilizers, urea fertilization, competition suppression through herbicides). In order to maximize the management applications of our results, we qualified them with ratings of confidence based on degree of support across approaches. Last, similar to earlier published assessments from other ecoregions, we supplemented our quantitative synthesis results with a literature review to arrive at a concise set of tactics for adapting management operations to site-specific criteria.

Predictors for digital mapping of forest soil organic carbon stocks in different types of landscape

Forest soils have a high potential to store carbon and thus mitigate climate change. The information on spatial distribution of soil organic carbon (SOC) stocks is thus very important. This study aims to analyse the importance of environmental predictors for forest SOC stock prediction at the regional and national scale in the Czech Republic. A big database of forest soil data for more than 7 000 sites was compiled from several surveys. SOC stocks were calculated from SOC content and bulk density for the topsoil mineral layer 0–30 cm. Spatial prediction models were developed separately for individual natural forest areas and for four subsets with different altitude range, using random forest method. The importance of environmental predictors in the models strongly differs between regions and altitudes. At lower altitudes, forest edaphic series and soil classes are strong predictors, while at higher altitudes the predictors related to topography become more important. The importance of soil classes depends on the pedodiversity level and on the difference in SOC stock between the classes. The contribution of forest types as predictors is limited when one (mostly coniferous) type dominates. Better prediction results can be obtained in smaller, but consistent regions, like some natural forest areas.

The magnitude and causes of edge effects on soil organic carbon stocks within and across urban to rural forest patches

Landscape fragmentation has created large areas of forest edge. Understanding how soil organic carbon (SOC) stocks within forest edges respond to fragmentation is essential to assess carbon budgets; however, the causes and magnitude of edge effects on SOC stocks have been poorly characterized. Here, we quantify the edge effects on SOC stocks within and across urban to rural forest patches from three fragmented urban forests to a large patch of rural forest. The SOC stocks within 20 m of the rural forest edge (1.86kgCm−2) is on average 80% lower than the interiors of rural forest (10.47kgCm−2). We found that biotic factors, including annual litterfall mass (R2 > 0.94), peak leaf area index (R2 > 0.92), and fine-root mass density (R2 > 0.77), explained the spatial variation in SOC stocks within the rural forest. In urban forests, human activities at forest edges led to contrasting edge effects on SOC stocks, for instance, the SOC stocks at the east edges (4.74 kgC m−2) were 56% greater than at the west edges (3.03 kgC m−2) explained by the adjacent land uses (e.g., paved roads vs. non-paved soils) and in-situ litterfall management. We also found significant differences in summer soil temperature (ΔTS > 2.8 °C) and soil moisture (ΔVWC > 0.05 m3 m−3) between the east and west forest edges. Our results reveal that the factors responsible for the edge effects on SOC stocks in rural forests are biotic factors, while heterogeneous human activities at the local scale lead to complex edge effects on urban forest SOC stocks.

Factors controlling soil organic carbon stocks in hardwood floodplain forests of the lower middle Elbe River

We assessed key relationships of soil organic carbon (SOC) stocks to hydromorphic features, soil texture, C/N ratio, pH, and forest age in hardwood floodplain forests. Floodplain ecosystems play a significant role in the global carbon cycle, particularly due to their SOC storage potential. Interactions between heterogeneous micro-relief and anthropogenically affected vegetation and the hydrologic situation of floodplains make predicting SOC stocks difficult without field validation. Especially within hardwood floodplain forests, the controlling factors for SOC storage remain understudied, whereas these floodplain types can be the largest reservoir for carbon and have a substantial SOC sequestration potential. To determine the controlling factors for SOC storage, we selected 38 hardwood floodplain forest and 11 floodplain grasslands of the lower middle Elbe River and categorized them according to vegetation type (grassland, young forest, or old forest) and hydrologic situation (low-lying or high elevated and active or former floodplain). Profile SOC stocks were determined to a depth of 1 m, and topsoil SOC stocks were related to vegetation and soil characteristics, particularly pedological traits (e.g., hydromorphic features).Forest SOC stocks ranged between 99 and 149 t ha−1. SOC stocks decreased with depth throughout all categories and were unaffected by vegetation type within the same hydrologic situation. Vegetation parameters such as age, basal area, or leaf litter carbon stock had no direct effect on SOC stocks. An active connection to the river had the strongest effect on SOC stocks, with former floodplain sites storing 33% less SOC than the active sites. Within the active floodplains, low sites stored 50% more SOC than high sites. This effect was mainly controlled by relief-affected features such as flooding duration and fine texture, which also were the strongest univariate predictors for SOC stocks (R2 = 0.39 and 0.63). A multiple linear regression showed that fine texture, pH, C/N ratio and forest age can be used to explain 86% of variance in SOC stocks.We conclude that proxies for relief and sedimentation (i.e., hydromorphic features, flooding duration, soil texture, C/N ratio, and pH) are the strongest factors controlling SOC stocks in hardwood floodplain forests. Both can be related to allochthonous carbon inputs, increasing SOC stabilization through the accumulation of fine soil particles, and decreasing aerobic carbon mineralization potential through oxygen scarcity, while vegetation plays only a subordinate role.

TransparC2U–A two-pool, pedology oriented forest soil carbon simulation model aimed at user investigations of multiple uncertainties

The dynamic character of forest soil organic carbon (SOC) stocks is demonstrated in the simulation model TransparC2U. The model has up to 10 layers, each with two pools with first order kinetics running for 40 years. The model is aimed at teaching soil science to a broad audience in academia, extension services, secondary schools and public life. The learning objective of the model is to bring about an understanding of SOC dynamics over time, uncertainty, and the complexity of the soil profile with its pedogenesis represented by soil horizons. The user works in an illustrated spreadsheet calculator with options for instant and interactive exploration of the multiple uncertainties and constraints on forest SOC stocks. The user divides the initial SOC stock in each horizon into two pools, Cnew with faster mineralization, and Cold with very slow mineralization, based on their knowledge of horizon designations and stabilization mechanisms.Data from 23 soil Nordic and Baltic forest soil profiles with horizons characterized by chemical and physical properties are available. Site information to the user intended for reflections on choosing parameter values includes soil classification, tree species, climate, stand age, soil nutrient status and properties that govern physical or chemical protection of soil C (extractable phosphorus (P), total nitrogen (N), subsoil clay content and extractable iron (Fe)). Other changeable inputs are the average annual aboveground litter fall, root litter allocation to individual soil horizons as a fraction (%) of aboveground input, and decomposition rates of each pool. The game played aims for preservation of the initial C stock by manual calibration by the user. The sensitivity of the potential C change (dC ±) is tested by changing the parameter values and watching the effects on model results, i.e. C stocks in each horizon over time. The sensitivity analysis can involve the uncertainty of the input, the initial C content in each horizon, the fraction of Cold and the turnover rates that represent heterotrophic respiration.The processes representing C input to deeper horizons (roots and exudates), bioturbation by macrofauna, as well as podzolisation provide optional transfer of C between the forest floor and mineral soil layers when judged appropriate by the user based on the site and stand information.The user may interpret results of the simulation by examining the outputs of total C stock change over 40 years by inspecting total N and P requirements for new litter inputs against potentially available current and future N and P stocks in the soil and the capacity of C binding by subsoil clay and Fe-oxides. It highlights the physical and chemical soil properties required to justify the simulated fate of new and old SOC and the sensitivity of controlling parameters on a decadal timescale to the user.

Impact of European Beech Forest Diversification on Soil Organic Carbon and Total Nitrogen Stocks–A Meta-Analysis

Drought-sensitive European beech forests are increasingly challenged by climate change. Admixing other, preferably more deep-rooting, tree species has been proposed to increase the resilience of beech forests to drought. This diversification of beech forests might also affect soil organic carbon (SOC) and total nitrogen (TN) stocks that are relevant for a wide range of soil functions and ecosystem services, such as water and nutrient retention, filter functions and erosion control. Since information of these effects is scattered, our aim was to synthesize results from studies that compared SOC/TN stocks of beech monocultures with those of beech stands mixed with other tree species as well as monocultures of other tree species. We conducted a meta-analysis including 38 studies with 203, 220, and 160 observations for forest floor (i.e., the organic surface layer), mineral soil (0.5 m depth) and the total soil profile, respectively. Monoculture conifer stands had higher SOC stocks compared to monoculture beech in general, especially in the forest floor (up to 200% in larch forests). In contrast, other broadleaved tree species (oak, ash, lime, maple, hornbeam) showed lower SOC stocks in the forest floor compared to beech, with little impact on total SOC stocks. Comparing mixed beech-conifer stands (average mixing ratio with regard to number of trees 50:50) with beech monocultures revealed significantly higher total SOC stocks of around 9% and a smaller increase in TN stocks of around 4%. This equaled a SOC accrual of 0.1 Mg ha−1 yr−1. In contrast, mixed beech-broadleaved stands did not show significant differences in total SOC stocks. Conifer admixture effects on beech forest SOC were of additive nature. Admixing other tree species to beech monoculture stands was most effective to increase SOC stocks on low carbon soils with a sandy texture and nitrogen limitation (i.e., a high C/N ratio and low nitrogen deposition). We conclude that, with targeted admixture measures of coniferous species, an increase in SOC stocks in beech forests can be achieved as part of the necessary adaptation of beech forests to climate change.

Forest Soil Organic Carbon Stocks of Tessala Mount in North-West Algeria-Preliminary Estimates

Mountainous forests in Algeria are severely affected by climate change. The degradation is exacerbated by overgrazing, deforestation, and poor land management linked to the harsh topographical conditions of the mountain agrosystem. These conditions have influenced the turnover of the soil organic matter and thus the SOC stocks storage. This study aims to investigate the average of organic carbon stored in forest soils of Tessala Mount in Algeria and to examine the influence of different plant formations alongside with geographical characteristics and soil physicochemical properties on the amount of carbon stored in the soil. We estimated the critical threshold, the saturation point, and the organic carbon deficit of soils. The correlation between geographical characteristics and soil physicochemical properties and soil organic carbon stocks was determined using principal component analysis and other statistical tools. The results of the study show that the organic carbon stock in soils of Tessala Mount area has an average value of 77.4 t ha−1. The maximum average of SOC stocks (121 t ha−1) of 0–30 cm depth was noted under dense matorral of green and kermes oak followed by sparse garrigue with a value of 112 t ha−1. The soil organic carbon stock in Tessala region was positively correlated with coarse silt, elevation, and northern exposure, but negatively with calcium carbonates contents. The current carbon contents of Tessala topsoil are 22 g C kg−1 which is very low and closer to the critical threshold (11 g C kg−1) whose estimate was based on their clay and silt content. The estimated maximum storage capacity is 160 g C kg−1. The preliminary estimate of the forest soils organic carbon stock of Tessala Mount under current natural conditions indicates an alarming situation with a low rate close to the critical threshold, thus exposing this area to further and stronger degradation.

Multispectral Remote Sensing Data Are Effective and Robust in Mapping Regional Forest Soil Organic Carbon Stocks in a Northeast Forest Region in China

Accurately mapping the spatial distribution information of soil organic carbon (SOC) stocks is a key premise for soil resource management and environment protection. Rapid development of satellite remote sensing provides a great opportunity for monitoring SOC stocks at a large scale. In this study, based on 12 environmental variables of multispectral remote sensing, topography and climate and 236 soil sampling data, three different boosted regression tree (BRT) models were compared to obtain the most accurate map of SOC stocks covering the forest area of Lvshun District in the Northeast China. Four validation indexes, including mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2), and Lin’s concordance correlation coefficient (LCCC) were calculated to evaluate the performance of the three models. The results showed that the full variable model performed the best, except the model using multispectral remote sensing variables. In the full variable model, the regional SOC stocks are primarily determined by multispectral remote sensing variables, followed by topographic and climatic variables, with the relative importance of variables in the model being 63%, 28%, and 9%, respectively. The average prediction results of full variables model and only multispectral remote sensing variables model were 8.99 and 9.32 kg m−2, respectively. Our results indicated that there is a strong dependence of SOC stocks on multispectral remote sensing data when forest ecosystems have dense natural vegetation. Our study suggests that the multispectral remote sensing variables should be used to map SOC stocks of forest ecosystems in our study region.

Temporal and Spatial Changes of Soil Organic Carbon Stocks in the Forest Area of Northeastern China

Forest soil organic carbon (SOC) accounts for a large portion of global soil carbon stocks. Accurately mapping forest SOC stocks is a necessity for quantifying forest carbon cycling and forest soil sustainable management. In this study, we used a boosted regression trees (BRT) model to predict the spatial distribution of SOC stocks during two time periods (1990 and 2015) and calculated their spatiotemporal changes during 25 years in Liaoning Province, China. A total of 367 (1990) and 539 (2015) sampling sites and 9 environmental variables (climate, topography, remote sensing) were used in the BRT model. The ten-fold cross-validation technique was used to evaluate the prediction performance and uncertainty of the BRT model in two periods. It was found that the BRT model could account for 65% and 59% of SOC stocks, respectively for the two periods. MAP and NDVI were the main environmental variables controlling the spatial variability of SOC stocks. Over the 25-year period, the average SOC stocks increased from 5.66 to 6.61 kg m−2. In the whole study area, the SOC stocks were the highest in the northeast, followed by the southwest, and the lowest in the middle of the spatial distribution pattern in the two periods. Our accurate mapping of SOC stocks, their spatial distribution characteristics, influencing factors, and main controlling factors in forest areas will assist soil management and help assess environmental changes in the region.

Estimation of plot-level soil carbon stocks in China's forests using intensive soil sampling

Forest soil is a large carbon (C) pool and plays a pivotal role in the global C cycle. The accurate estimation of soil organic carbon (SOC) stocks in forests is the cornerstone of studying the C budget; however, current assessments of forest SOC stocks are highly uncertain. One of the key reasons for this uncertainty is that most previous studies only used a few soil profiles for their estimation, whereas SOC stocks are highly spatially heterogeneous. To accurately evaluate the plot-level SOC stocks of China's forests, we conducted intensive soil sampling (100 soil cores within a plot) in 33 plots across 11 forest sites from south to north China. The average SOC density (SOCD) of these forest sites was 137.4 ± 12.1 Mg C ha−1 (0–100 cm), with significant geographic variations. The highest SOCD (306.8 ± 7.6 Mg C ha−1) was observed in deciduous needleleaf forest (boreal forest) in northeast China, while the lowest one (64.8 ± 0.9 Mg C ha−1) was found in subtropical evergreen broadleaf forest in south China. We also showed that the error of the SOCD estimates obtained from the intensive soil sampling was significantly smaller than that of estimates obtained from the traditional sampling method (5.3 ± 1.3% vs. 24.2 ± 5.6%, with a confidence level of 0.95). Our results suggest that intensive sampling can significantly reduce the uncertainty in forest SOC stock estimation by guarding against the effects of spatial heterogeneity, and provide an important methodological reference for accurately evaluating forest SOC stocks and C budgets in other regions.

Impact of land use conversion on soil organic carbon stocks in an agro-pastoral ecotone of Inner Mongolia

Soil organic carbon (SOC) stocks in terrestrial ecosystems vary considerably with land use types. Grassland, forest, and cropland coexist in the agro-pastoral ecotone of Inner Mongolia, China. Using SOC data compiled from literature and field investigations, this study compared SOC stocks and their vertical distributions among three types of ecosystems. The results indicate that grassland had the largest SOC stock, which was 1.5- and 1.8-folds more than stocks in forest and cropland, respectively. Relative to the stock in 0–100 cm depth, grassland held more than 40% of its SOC stock in the upper 20 cm soil layer; forest and cropland both held over 30% of their respective SOC stocks in the upper 20 cm soil layer. SOC stocks in grazed grasslands were remarkably promoted after ≥20 years of grazing exclusion. Conservational cultivation substantially increased the SOC stocks in cropland, especially in the 0–40 cm depth. Stand ages, tree species, and forest types did not have obvious impacts on forest SOC stocks in the study area likely due to the younger stand ages. Our study implies that soil carbon loss should be taken into account during the implementation of ecological projects, such as reclamation and afforestation, in the arid and semi-arid regions of China.

Conventional intensive logging promotes loss of organic carbon from the mineral soil.

There are few data, but diametrically opposed opinions, about the impacts of forest logging on soil organic carbon (SOC). Reviews and research articles conclude either that there is no effect, or show contradictory effects. Given that SOC is a substantial store of potential greenhouse gasses and forest logging and harvesting is routine, resolution is important. We review forest logging SOC studies and provide an overarching conceptual explanation for their findings. The literature can be separated intoshort-term empirical studies,longer-term empirical studies and long-term modelling. All modelling that includes major aboveground and belowground biomass pools shows a long-term (i.e. ≥300years) decrease in SOC when a primary forest is logged and then subjected to harvesting cycles. The empirical longer-term studies indicate likewise. With successive harvests the net emission accumulates but is only statistically perceptible after centuries. Short-term SOC flux varies around zero. The long-term drop in SOC in the mineral soil is driven by the biomass drop from the primary forest level but takes time to adjust to the new temporal average biomass. We show agreement between secondary forest SOC stocks derived purely from biomass information and stocks derived from complex forest harvest modelling. Thus, conclusions that conventional harvests do not deplete SOC in the mineral soil have been a function of their short time frames. Forest managers, climate change modellers and environmental policymakers need to assume a long-term net transfer of SOC from the mineral soil to the atmosphere when primary forests are logged and then undergo harvest cycles. However, from a greenhouse accounting perspective, forest SOC is not the entire story. Forest wood products that ultimately reach landfill, and some portion of which produces some soil-like material there rather than in the forest, could possibly help attenuate the forest SOC emission by adding to a carbon pool in landfill.

Improving forest soil carbon models using spatial data and geostatistical approaches

Forest soils store large amounts of carbon (C), and stock changes in this C pool may significantly increase the CO2 concentration in the atmosphere. However, estimation of soil organic carbon (SOC) stocks and stock changes following land use transition to forestry is subject to large uncertainty. Many currently used geochemical modelling approaches, such as YASSO, are used to estimate regional changes in forest SOC stocks, but these are difficult to calibrate to reflect regional conditions because of limited availability of sufficient SOC data. In addition, most model frameworks give little consideration regarding the appropriate use of geospatial climatic and topographical data, as dependent variables in the model. As a result, many regional models may exhibit spatial autocorrelation (SAC) of residuals, which contributes to overall model error. In this paper, we develop a method for assessing SOC stock changes in Irish forests by compiling a spatial SOC database and using these data to calibrate and improve on an existing YASSO model. Careful consideration was given to the use of available climatic and digital elevation GIS data in YASSO with the aim of reducing SAC of model residuals and to more precisely predict soil- and site-specific variations in SOC stock changes following transition to forestry.Analysis of the complied national SOC database shows that stock changes in afforested mineral soils may increase or decrease depending on previous land use and soil type. During refinement of the YASSO model, conventional statistical approaches confirmed that model performance can be improved by using climatic GIS data at the appropriate scale (resolution), together with additional use of novel topographical spatial data. The current YASSO model does not use these topographical factors as dependent variables, nor is there any consideration given to the spatial or temporal resolution of GIS datasets used. Use of GIS geo-statistical approaches to determine if SAC was reduced, as the YASSO model accuracy was improved on, produced conflicting results. We suggest that the use of Anselin Local Moran's I outlier analysis may not be suitable for this purpose because it may falsely detect spatial outliers due to the presence of neighbouring points with very high or low residual values. In contrast, semi-variogram analysis appeared to be the most useful geo-statistical measure of the spatial dependency, distribution and scale at which residual SAC occurs. Use of fine resolution (50m) slope and topographical position index (TPI) raster datasets to predict forest SOC stocks significantly improved the final YASSO model accuracy and precision. In addition, semi-variogram analysis confirmed that the final YASSO model residuals exhibited no spatial dependency and residual error was uniformly distributed over the entire sample area, from which the SOC database was derived. However, the final YASSO model we describe requires considerable refinement using more intensive sampling studies and independent validation before it can be applied at a national level. In the future, particular emphasis should be directed to sampling forest brown earth soils, which are suggested to result in a net emission of C following transition from grassland to forest land.

Soil carbon stocks and their variability across the forests, shrublands and grasslands of peninsular Spain

Abstract. Accurate estimates of C stocks and fluxes of soil organic carbon (SOC) are needed to assess the impact of climate and land use change on soil C uptake and soil C emissions to the atmosphere. Here, we present an assessment of SOC stocks in forests, shrublands and grasslands of peninsular Spain based on field measurements in more than 900 soil profiles. SOC to a depth of 1 m was modelled as a function of vegetation cover, mean annual temperature, total annual precipitation, elevation and the interaction between temperature and elevation, while latitude and longitude were used to model the correlation structure of the errors. The resulting statistical model was used to estimate SOC in the ∼8 million pixels of the Spanish Forest Map (29.3 × 106 ha). We present what we believe is the most reliable estimation of current SOC in forests, shrublands and grasslands of peninsular Spain thus far, based on the use of spatial modelling, the high number of profiles and the validity and refinement of the data layers employed. Mean concentration of SOC was 8.7 kg m−2, ranging from 2.3 kg m−2 in dry Mediterranean areas to 20.4 kg m−2 in wetter northern locations. This value corresponds to a total stock of 2.544 Tg SOC, which is four times the amount of C estimated to be stored in the biomass of Spanish forests. Climate and vegetation cover were the main variables influencing SOC, with important ecological implications for peninsular Spanish ecosystems in the face of global change. The fact that SOC was positively related to annual precipitation and negatively related to mean annual temperature suggests that future climate change predictions of increased temperature and reduced precipitation may strongly reduce the potential of Spanish soils as C sinks. However, this may be mediated by changes in vegetation cover (e.g. by favouring the development of forests associated to higher SOC values) and exacerbated by perturbations such as fire. The estimations presented here provide a baseline to estimate future changes in soil C stocks and to assess their vulnerability to key global change drivers, and should inform future actions aimed at the conservation and management of C stocks.

The influence of changes in forest management over the past 200 years on present soil organic carbon stocks

Forest ecosystems in Europe have been affected by human activities for many centuries. Here we investigate, if current forest soil organic carbon stocks are influenced not only by present ecological conditions and land use, but also by land management in the past. Based on the forest management history of the Hainich-Dün region a total of 130 inventory plots were selected in age-class forest and selectively cut forests under present management practice. The age-class forest originated from (1) former coppice-with-standards, (2) former selectively cut forests and (3) afforestation. The selectively cut forest contains “early regulated” forest where selective cutting has been practised for centuries, and forest, which was managed as coppice-with-standards through the 18th and the 19th centuries. We hypothesise that past management influences present soil organic carbon stocks. Density fractionation of soils in three physical fractions (HF: heavy fraction, o-LF: occluded light fraction, f-LF: free light fraction) was carried out to increase the probability of detecting long-lasting effects of management history. No detectable differences in soil organic carbon (SOC) stocks, as measured in kgm−2 ground area, of the mineral soil and the heavy fractions, were found between present and historical forest management types (average total organic carbon (OC) stocks of mineral soil: 9.7±2.3kgm−2; average OC stocks of the organic layer: 0.5±0.3kgm−2; average total inorganic carbon (IC) stocks of mineral soil: 5.0±3.7kgm−2). The variation of samples was overlapping. There was no consistent trend with management history. The upper mineral soil (0–30cm) contained about 74% of total SOC, with f-LF contributing 24% in 0–10cm and 20% in 10–30cm, and o-LF 9% in 0–10cm and 6% in 10–30cm. The HF contained 85% (0–10cm) and 86% (10–30cm) of SOC stocks in the bulk soil. There was a significant decrease of total SOC stocks in the 0–10 and 10–30cm depth increment with increasing abundance of beech. Mean 14C concentrations in the HF were 102.0 pMC in 0–10cm, and 93.4 pMC in 10–30cm, corresponding to a mean 14C age of around 100years and 550years, respectively. Modelling C-dynamics based on the present measurements reveals that disturbances depleting 50% of soil C-stocks would equilibrate after 80years. Thus, there is no memory effect of 19th century forest management. We conclude that past and present management has no detectable effect on present SOC.

Projected changes in mineral soil carbon of European forests, 1990–2100

Forests are a major land use in Europe, and European forest soils contain about the same amount of carbon as is found in tree biomass. Changes in the size of the forest soil carbon pool could have significant impacts on the European carbon budget. We present the first assessment of future changes in European forest soil organic carbon (SOC) stocks using a dedicated process-based SOC model and state-of-the-art databases of driving variables. Soil carbon change was calculated for Europe using the Rothamsted Carbon model using climate data from four climate models, forced by four Intergovernmental Panel on Climate Change (IPCC) emissions scenarios (SRES). Changes in litter input to the soil due to forest management, projected changes in net primary production (NPP), forest age-class structure, and changes in forest area were taken into account. Results are presented for mineral soil only. Under some climate scenarios carbon in forest soils will increase slightly (0.1 to 4.6 Pg) in Europe over the 21st Century, whilst for one scenario, forest SOC stocks are predicted to decrease by 0.3 Pg. Different trends are seen in different regions. Climate change will tend to speed decomposition, whereas increases in litter input due to increasing NPP and changing age-class structure will slow the loss of SOC. Increases in forest area could further enhance the total soil carbon stock of European forests. Whilst climate change will be a key driver of change in forest soil carbon, changes in ageclass structure and land-use change are estimated to have greater effects. Key words: Soil organic carbon, Europe, climate change, forest management, land-use change, Rothamsted Carbon model, EFISCEN model, LPJ model

Contemporary carbon stocks of mineral forest soils in the Swiss Alps.

Soil organic carbon (SOC) has been identified as the main globalterrestrial carbon reservoir, but considerable uncertainty remains as toregional SOC variability and the distribution of C between vegetationand soil. We used gridded forest soil data (8–km × 8–km)representative of Swiss forests in terms of climate and forest typedistribution to analyse spatial patterns of mineral SOC stocks alonggradients in the European Alps for the year 1993. At stand level, meanSOC stocks of 98 t C ha−1 (N = 168,coefficient of variation: 70%) were obtained for the entiremineral soil profile, 76 t C ha−1 (N =137, CV: 50%) in 0–30 cm topsoil, and 62 t Cha−1 (N = 156, CV: 46%) in0–20 cm topsoil. Extrapolating to national scale, we calculatedcontemporary SOC stocks of 110 Tg C (entire mineral soil, standarderror: 6 Tg C), 87 Tg C (0–30 cm topsoil, standarderror: 3.5 Tg C) and 70 Tg C (0–20 cm topsoil, standarderror: 2.5 Tg C) for mineral soils of accessible Swiss forests(1.1399 Mha). According to our estimate, the 0–20 cm layers ofmineral forest soils in Switzerland store about half of the Csequestered by forest trees (136 Tg C) and more than five times morethan organic horizons (13.2 Tg C). At stand level, regression analyses on the entire data set yielded nostrong climatic or topographic signature for forest SOC stocks in top(0–20 cm) and entire mineral soils across the Alps, despite thewide range of values of site parameters. Similarly, geostatisticalanalyses revealed no clear spatial trends for SOC in Switzerland at thescale of sampling. Using subsets, biotic, abiotic controls andcategorial variables (forest type, region) explained nearly 60%of the SOC variability in topsoil mineral layers (0–20 cm) forbroadleaf stands (N = 56), but only little of thevariability in needleleaf stands (N = 91,R 2 = 0.23 for topsoil layers). Considerable uncertainties remain in assessments of SOC stocks, due tounquantified errors in soil density and rock fraction, lack of data onwithin-site SOC variability and missing or poorly quantifiedenvironmental control parameters. Considering further spatial SOCvariability, replicate pointwise soil sampling at 8–km × 8–kmresolution without organic horizons will thus hardly allow to detectchanges in SOC stocks in strongly heterogeneous mountain landscapes.