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Background: Under the growing pressure to implement mitigation actions, the focus of forest management is shifting from a traditional resource centric view to incorporate more forest ecosystem services objectives such as carbon sequestration. Estimating the above-ground biomass in forests using airborne laser scanning (ALS) is now an operational practice in Northern Europe and is being adopted in many parts of the world. In the boreal forests, however, most of the carbon (85%) is stored in the soil organic (SO) matter. While this very important carbon pool is "invisible" to ALS, it is closely connected and feeds from the growing forest stocks. We propose an integrated methodology to estimate the changes in forest carbon pools at the level of forest stands by combining field measurements and ALS data. Results: ALS-based models of dominant height, mean diameter, and biomass were fitted using the field observations and were used to predict mean tree biophysical properties across the entire study area (50 km2) which was in turn used to estimate the biomass carbon stocks and the litter production that feeds into the soil. For the soil carbon pool estimation, we used the Yasso15 model. The methodology was based on (1) approximating the initial soil carbon stocks using simulations; (2) predicting the annual litter input based on the predicted growing stocks in each cell; (3) predicting the soil carbon dynamics of the annual litter using the Yasso15 soil carbon model. The estimated total carbon change (standard errors in parenthesis) for the entire area was 0.741 (0.14) Mg ha−1 yr−1. The biomass carbon change was 0.405 (0.13) Mg ha−1 yr−1, the litter carbon change (e.g., deadwood and leaves) was 0.346 (0.027) Mg ha−1 yr−1, and the change in SO carbon was − 0.01 (0.003) Mg ha−1 yr−1. Conclusions: Our results show that ALS data can be used indirectly through a chain of models to estimate soil carbon changes in addition to changes in biomass at the primary level of forest management, namely the forest stands. Having control of the errors contributed by each model, the stand-level uncertainty can be estimated under a model-based inferential approach. [ABSTRACT FROM AUTHOR]

Climate change mitigation requires, besides reductions in greenhouse gas emissions, actions to increase carbon sinks in terrestrial ecosystems. A key measurement method for quantifying such sinks and calibrating models is the eddy covariance technique, but it requires imputation, or gap-filling, of missing data for determination of annual carbon balances of ecosystems. Previous comparisons of gap-filling methods have concluded that commonly used methods, such as marginal distribution sampling (MDS), do not have a significant impact on the carbon balance estimate. By analyzing an extensive, global data set, we show that MDS causes significant carbon balance errors for northern (latitude > 60 ∘ ) sites. MDS systematically overestimates the carbon dioxide (CO 2 ) emissions of carbon sources and underestimates the CO 2 sequestration of carbon sinks. We also reveal reasons for these biases and show how a machine learning method called extreme gradient boosting or a modified implementation of MDS can be used to substantially reduce the northern site bias. [ABSTRACT FROM AUTHOR]

The chemical quality of soil carbon (C) inputs is a major factor controlling litter decomposition and soil C dynamics. Mycorrhizal fungi constitute one of the dominant pools of soil microbial C, while their litter quality (chemical proxies of litter decomposability) is understood poorly, leading to major uncertainties in estimating soil C dynamics. We examined litter decomposability of arbuscular mycorrhizal (AM) and ectomycorrhizal (EM) fungal species using samples obtained from in vitro cultivation. We showed that the chemical composition of AM and EM fungal mycelium differs significantly: EM fungi have higher concentrations of labile (water-soluble, ethanol-soluble) and recalcitrant (non-extractable) chemical components, while AM fungi have higher concentrations of acid-hydrolysable components. Our results imply that differences in decomposability traits among mycorrhizal fungal guilds represent a critically important driver of the soil C cycle, which could be as vital as is recognized for differences among aboveground plant litter. Chemical profiles of arbuscular (AM) and ectomycorrhizal (EM) fungi reveal that differences in decomposability-relevant chemistry are larger between AM and EM fungi than across plant functional groups. [ABSTRACT FROM AUTHOR]

Background: Increasing the use of forest harvest residues for bioenergy production reduces greenhouse emissions from the use of fossil fuels. However, it may also reduce carbon stocks and habitats for deadwood dependent species. Consequently, simple tools for assessing the trade-offs of alternative management practices on forest dynamics and their services to people are needed. The objectives of this study were to combine mapping and simulation modelling to investigate the effects of forest management on ecosystem services related to carbon cycle in the case of bioenergy production; and to evaluate the suitability of this approach for assessing ecosystem services at the landscape level. Stand level simulations of forest growth and carbon budget were combined with extensive multi-source forest inventory data across a southern boreal landscape in Finland. Stochastic changes in the stand age class distribution over the study region were simulated to mimic variation in management regimes. Results: The mapping framework produced reasonable estimates of the effects of forest management on a set of key ecosystem service indicators: the annual carbon stocks and fluxes of forest biomass and soil, timber and energy-wood production and the coarse woody litter production over a simulation period 2012–2100. Regular harvesting, affecting the stand age class distribution, was a key driver of the carbon stock changes at a landscape level. Extracting forest harvest residues in the final felling caused carbon loss from litter and soil, particularly with combined aboveground residue and stump harvesting. It also reduced the annual coarse woody litter production, demonstrating negative impacts on deadwood abundance and, consequently, forest biodiversity. Conclusions: The refined mapping framework was suitable for assessing ecosystem services at the landscape level. The procedure contributes to bridging the gap between ecosystem service mapping and detailed simulation modelling in boreal forests. It allows for visualizing ecosystem services as fine resolution maps to support sustainable land use planning. In the future, more detailed models and a wider variety of ecosystem service indicators could be added to develop the method. [ABSTRACT FROM AUTHOR]

We report on preparatory work to develop a virtual laboratory for ecosystem services, ESLab, and demonstrate its pilot application in southern Finland. The themes included in the pilot are related to biodiversity conservation, climate mitigation and eutrophication mitigation. ESLab is a research environment for ecosystem services (ES), which considers ES indicators at different landscape scales: habitats, catchments and municipalities and shares the results by a service that utilizes machine readable interfaces. The study area of the pilot application is situated in the boreal region of southern Finland and covers 14 municipalities and ten catchments including forested, agricultural and nature conservation areas. We present case studies including: present carbon budgets of natural ecosystems; future carbon budgets with and without the removal of harvest residues for bioenergy production; and total phosphorus and nitrogen future loads under climate and agricultural yield and price scenarios. The ESLab allows researchers to present and share the results as visual maps, statistics and graphs. Our further aim is to provide a toolbox of easily accessible virtual services for ES researchers, to illustrate the comprehensive societal consequences of multiple decisions (e.g. concerning land use, fertilisation or harvesting) in a changing environment (climate, deposition). [ABSTRACT FROM AUTHOR]

Land use changes are known to significantly affect the soil C balance by altering both C inputs and losses. Since the late 1990s, a large area of the Loess Plateau has undergone intensive land use changes during several ecological restoration projects to control soil erosion and combat land degradation, especially in the Grain for Green project. By using remote sensing techniques and the Yasso07 model, we simulated the dynamics of soil organic carbon (SOC) stocks in the Yangjuangou catchment of the Loess Plateau. The performance of the model was evaluated by comparing the simulated results with the intensive field measurements in 2006 and 2011 throughout the catchment. SOC stocks and NPP values of all land use types had generally increased during our study period. The average SOC sequestration rate in the upper 30 cm soil from 2006 to 2011 in the Yangjuangou catchment was approximately 44 g C m yr, which was comparable to other studies in the Loess Plateau. Forest and grassland showed a more effective accumulation of SOC than the other land use types in our study area. The Yasso07 model performed reasonably well in predicting the overall dynamics of SOC stock for different land use change types at both the site and catchment scales. The assessment of the model performance indicated that the combination of Yasso07 model and remote sensing data could be used for simulating the effect of land use changes on SOC stock at catchment scale in the Loess Plateau. [ABSTRACT FROM AUTHOR]

Contex: Soil carbon sequestration is an ecosystem process that can provide important ecosystem services such as climate regulation and mitigation of global warming. Spatiotemporal variation in the soil organic carbon (SOC) stock is the basic information needed for landscape management and determination of regional carbon budgets. Objectives: The objective of this study was to evaluate the effect of ecological restoration on SOC stocks and determine the influences of multiple factors in the Yanhe watershed of the Loess Plateau. Methods: We coupled the Yasso07 soil carbon model with remote sensing indices as model input. The model performance was evaluated by uncertainty and sensitivity analyses as well as validation against field measurement. Results: The modeling captured the spatial pattern of SOC variability across the landscape generally well. Net primary productivity (NPP) was the foremost factor that affecting the spatiotemporal variation of SOC density. Converting cropland to grassland was the most efficient restoration type in soil carbon sequestration in the study period. Land use change influenced the spatial correlation between NPP and SOC density by altering both litter quantity and quality. The changes in land use area tended to have higher contributions to the changes in SOC stock than did the changes in SOC density for different land use types. Conclusions: The overall effect of ecological restoration on soil carbon sequestration was dependent on the main vegetation restoration type and the time of recovery. Human-derived land use changes could have more substantial effects on soil carbon budgets compared to natural factors in a short period of time. [ABSTRACT FROM AUTHOR]

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A total of 30 coniferous forest sites representing two productivity classes, forest types, were investigated on a temperature gradient (effective temperature sum using +5 deg.C threshold 800--1300 degree-days and annual mean temperature -0.6--+3.9 deg.C) in Finland for studying the effect of thermoclimate on the soil C storage. Other soil forming factors were standardized within the forest types so that the variation in the soil C density could be related to temperature. According to the applied regression model, the C density of the 0--1 m mineral soil layer increased 0.266 kg m{sup}-2{end} for every 100 degree-day increase in the temperature sum, and the layer contained 57% and 28% more C under the warmest conditions of the gradient compared to the coolest in the less and more productive forest type, respectively.Accordingly, this soil layer was estimated to contain 23% more C in a new equilibrium with a 4 deg.C higher annual mean temperature in Finland. The C density of the organic layer was not associated with temperature. Both soil layers contained more C at the sites of the more productive forest type, and the forest type explained 36% and 70% of the variation in the C density of the organic and 0--1 m layers, respectively. Within the forest types, the temperature sum accounted for 33-41% of the variation in the 0--1 m layer. These results suggest that site productivity is a cause for the large variation in the soil Cdensity within the boreal zone, and relating the soil C density to site productivity and temperature would help to estimate the soil C reserves more accurately in the boreal zone. [ABSTRACT FROM AUTHOR]

For confidently estimating the amount of carbon stored in boreal forest soil, better knowledge of smaller regions is needed. In order to estimate the amount of soil C in forests on mineral soil in Finland, i.e. excluding peatland forests, and illustrate the regional patternsof the storage, statistical models were first made for the C densities of the organic and 0--1 m mineral soil layers. A forest type, which indicated site productivity, and the effective temperature sum wereused as explanatory variables of the models. In addition, a constantC density was applied for the soil layer below the depth of 1 m on sorted sediments. Using these models the C densities were calculated for a total of 46673 sites of the National Forest Inventory (NFI). Theamount of the soil C was then calculated in two ways: 1) weighting the C densities of the NFI sites by the land area represented by thesesites and 2) interpolating the C densities of the NFI sites for 4 hablocks to cover the whole land area of Finland and summing up the blocks on forested mineral soil. The soil C storage totalled 1109 Tg and 1315 Tg, when calculated by the areal weighting and the interpolated blocks, respectively. Of that storage, 28% was in the organic layer, 68% in the 0--1 m mineral soil layer and 4% in the layer below 1 m.The total soil C equals more than two times the amount of C in tree biomass and 20% of the amount of C in peat in Finland. Soil C maps made using the interpolated blocks indicated that the largest soil C reserves are located in central parts of southern Finland. The C storage of the organic layer was assessed to be overestimated at largest by13% and that of the 0--1 m mineral soil layer by 29%. The largest error in the organic layer estimate is associated with the effects of forest harvesting and in the mineral soil estimate with the stone content of the soil. [ABSTRACT FROM AUTHOR]