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This study examines the impact of silvicultural and land-use management practices on carbon sequestration in peri-urban forest ecosystems, with a particular focus on human-induced carbon dynamics. The study area's complex profile spans from a compact native forest to varying degrees of fragmentation. This included areas undergoing secondary succession forest without silvicultural interventions (No-SI) alongside sites subjected to high-intensity (High-SI) and low-intensity silvicultural interventions (Low-SI). The research assessed carbon stocks and sequestration in different carbon pools (living biomass, dead organic matter and soil) using field data, allometric equations and laboratory analysis. Findings reveal a significant correlation between the intensity of anthropogenic interventions and variations in carbon stocks. The CASMOFOR model facilitated the reconstruction of carbon stock and carbon-stock change dynamics over four decades (1980–2022), showing disparities in carbon storage capabilities linked to the structural characteristics of the sites. The Low-SI site had the highest carbon stock in all carbon pools (378 tonnes C ha−1), which is more than double compared to High-SI (161 tonnes C ha−1) or No-SI sites (134 tonnes C ha−1). However, the secondary succession forest (No-SI) demonstrated the highest annual carbon stock change (4.4 tonnes C ha−1 year−1), two times higher than the Low-SI mature stand (2.2 tonnes C ha−1 year−1), emphasising the resilience of forest ecosystems to recover and sustain carbon sequestration capacities after harvesting if forest land use remains unchanged. The study underscores the significant importance of anthropogenic interventions on carbon dynamics, especially for living tree biomass, which has consequences in enhancing carbon sequestration and contributing to emission reduction targets. [ABSTRACT FROM AUTHOR]

The fate of soil organic carbon (SOC) under warming is poorly understood, particularly across large extents and in the whole‐soil profile. Using a data‐model integration approach applied across the globe, we find that downward movement of SOC along the soil profile reduces SOC loss under warming. We predict that global SOC stocks (down to 2 m) will decline by 4% (~80 Pg) on average when SOC reaches the steady state under 2°C warming, assuming no changes in net primary productivity (NPP). To compensate such decline (i.e. maintain current SOC stocks), a 3% increase of NPP is required. Without the downward SOC movement, global SOC declines by 15%, while a 20% increase in NPP is needed to compensate that loss. This vital role of downward SOC movement in controlling whole‐soil profile SOC dynamics in response to warming is due to the protection afforded to downward‐moving SOC by depth, indicated by much longer residence times of SOC in deeper layers. Additionally, we find that this protection could not be counteracted by promoted decomposition due to the priming of downward‐moving new SOC from upper layers on native old SOC in deeper layers. This study provides the first estimation of whole‐soil SOC changes under warming and additional NPP required to compensate such changes across the globe, and reveals the vital role of downward movement of SOC in reducing SOC loss under global warming. [ABSTRACT FROM AUTHOR]

Labile carbon (C) is a major source of C loss because of its high vulnerability to environmental change. Yet its potential role in regulating soil organic carbon (SOC) dynamics remains unclear. In this study, we tested the effect of physical disturbance on SOC decomposition using soils from two abandoned farmlands free of management practice for more than 28 years. The soil respiration rate was measured in undisturbed and disturbed soil columns and was inversely modeled using the two-compartment model. We found that the C loss was 16.8~74.1% higher in disturbed than in undisturbed soil columns. Physical disturbance increased the total amount of labile C (C1) loss by 136~241%, while had no effect on the kinetic decomposition rate constants of both labile (k1) and stable (k2) SOC decomposition. Physical disturbance fragmented the large macroaggregates into small macroaggregates, microaggregates, and free silt and clay-sized fractions. This indicates that C loss was derived from the initially protected labile C, and there was no change of SOC fraction being decomposed. Our results give insights into the understanding of the extent of labile C loss to physical disruption and demonstrate the potential effect of physical disturbance on SOC dynamics. [ABSTRACT FROM AUTHOR]

Color sensor technologies offer opportunities for affordable and rapid assessment of soil organic carbon (SOC) and total nitrogen (TN) in the field, but the applicability of these technologies may vary by soil type. The objective of this study was to use an inexpensive color sensor to develop SOC and TN prediction models for the Russian Chernozem (Haplic Chernozem) in the Kursk region of Russia. Twenty-one dried soil samples were analyzed using a Nix ProTM color sensor that is controlled through a mobile application and Bluetooth to collect CIEL*a*b* (darkness to lightness, green to red, and blue to yellow) color data. Eleven samples were randomly selected to be used to construct prediction models and the remaining ten samples were set aside for cross validation. The root mean squared error (RMSE) was calculated to determine each model's prediction error. The data from the eleven soil samples were used to develop the natural log of SOC (lnSOC) and TN (lnTN) prediction models using depth, L*, a*, and b* for each sample as predictor variables in regression analyses. Resulting residual plots, root mean square errors (RMSE), mean squared prediction error (MSPE) and coefficients of determination (R², adjusted R²) were used to assess model fit for each of the SOC and total N prediction models. Final models were fit using all soil samples, which included depth and color variables, for lnSOC (R² = 0.987, Adj. R² = 0.981, RMSE = 0.003, p-value < 0.001, MSPE = 0.182) and lnTN (R² = 0.980 Adj. R² = 0.972, RMSE = 0.004, p-value < 0.001, MSPE = 0.001). Additionally, final models were fit for all soil samples, which included only color variables, for lnSOC (R² = 0.959 Adj. R² = 0.949, RMSE = 0.007, p-value < 0.001, MSPE = 0.536) and lnTN (R² = 0.912 Adj. R² = 0.890, RMSE = 0.015, p-value < 0.001, MSPE = 0.001). The results suggest that soil color may be used for rapid assessment of SOC and TN in these agriculturally important soils. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Forest Research is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The boreal forest plays a key role in the global carbon (C) cycle, and black spruce ( Picea mariana (Mill.) BSP) forests are the dominant coniferous forest type in the Canadian boreal forest. National-scale forest C models currently do not account for the contribution of moss-derived organic matter that we hypothesize to be significant in the C budget of black spruce ecosystems. One such model, the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3), is designed to meet Canada's forest-related greenhouse gas reporting requirements. In this study our goal was to determine if black spruce forest soil C stocks are significantly underestimated by the CBM-CFS3, and if so, to determine if estimates could be improved by adding moss-derived C. We conclude that in black spruce sites, organic layer C is significantly underestimated by CBM-CFS3 compared to sites with all other leading tree species analyzed. We compiled and used published moss net primary productivity rates for upland forest systems, with decomposition rates, in mass-balance calculations to estimate mean moss-derived C in black spruce forests for feather mosses at 64 Mg C ha, and for sphagnum mosses at 103 Mg C ha. These C pools are similar to the CBM-CFS3 mean underestimation of black spruce soil organic layers (63 Mg C ha). We conclude that the contribution of mosses is sufficiently large that a moss C pool should be added to national-scale models including the CBM-CFS3, to reduce uncertainties in boreal forest C budget estimation. Feather and sphagnum mosses should be parameterized separately. [ABSTRACT FROM AUTHOR]

This study compared models for estimating carbon sequestered aboveground inCupressus lusitanicaplantation stands at Wondo Genet College of Forestry and Natural Resources, Ethiopia. Relationships of carbon storage with tree component and stand age were also investigated. Thirty trees of three different ages (5, 12 and 24 years), comprising 10 trees from each stand, were sampled in order to generate dry biomass and carbon data from tree components. Five linear and non-linear biomass and carbon models were compared and evaluated for estimation of overall aboveground carbon, carbon by age groups, and carbon by diameter at breast height (DBH) classes using performance indicator statistics. Among the models compared, a carbon model described byY=b0D2H+ ϵ (p-value < 0.001), whereD= DBH (in cm),H= total height of the tree (in m), ϵ = error, andb0is a parameter, was found to be the best model for estimation of carbon sequestered aboveground inC. lusitanicaplantation stands of the study area. The study also indicated the overall superiority of carbon models over biomass models in estimation of aboveground carbon ofC. lusitanica. It was concluded that, for the range of DBH utilised in the current study, the carbon model described can be a useful tool in estimation of carbon storage ofC. lusitanicaplantations in the study area and other related sites. [ABSTRACT FROM AUTHOR]

Background:Tropical forest biomass is not at steady state, being determined by a balance between deterministic growth and stochastic disturbances. Understanding tropical carbon sources and sinks therefore requires better characterisation of the incidence and intensity of disturbance at critical scales. Aims:We determine if information from remotely sensed biomass maps (ALOS-PALSAR) can constrain estimates of miombo woodland biomass dynamics and disturbance. Methods:We analyse biomass maps created over Mozambican woodlands undergoing varied disturbances. We use a simple ensemble model of biomass dynamics to test the hypothesis that biomass distributions can diagnose disturbance processes in specified areas, and use the model to explore the sensitivity of biomass to disturbance parameters. Results:Ensemble runs can reproduce qualitatively similar biomass patterns to those observed in miombo, through varying two parameters that determine frequency and intensity of biomass loss. Using sensitivity analyses, we show for a synthetic case that these two disturbance parameters can be retrieved from satellite observations. Conclusions:Biomass distributions provide enough information to constrain the two critical parameters of the disturbance model, the local probability of disturbance, and its intensity (fraction of biomass lost). These results provide a proof of concept for assimilating biomass maps into models of carbon cycling. [ABSTRACT FROM PUBLISHER]

Carbon (C) allocation and turnover in arctic bryophytes is largely unknown, but their response to climatic change has potentially significant impacts on arctic ecosystem C budgets. Using a combination of pulse-chase experiments and a newly developed model of C turnover in bryophytes, we show significant differences in C turnover between two contrasting arctic moss species ( Polytrichum piliferum and Sphagnum fuscum). C abundance in moss tissues (measured up to 1 year) and respired CO (traced over 5 days) were used to parameterise the bryophyte C model with four pools representing labile and structural C in photosynthetic and stem tissue. The model was optimised using an Ensemble Kalman Filter to ensure a focus on estimating the confidence intervals (CI) on model parameters and outputs. The ratio of aboveground NPP:GPP in Polytrichum piliferum was 23% (CI 9-35%), with an average turnover time of 1.7 days (CI 1.1-2.5 days). The aboveground NPP:GPP ratio in Sphagnum fuscum was 43% (CI 19-65%) with an average turnover time of 3.1 days (CI 1.6-6.1 days). These results are the first to show differences in C partitioning between arctic bryophyte species in situ and highlight the importance of modelling C dynamics of this group separately from vascular plants for a realistic representation of vegetation in arctic C models. [ABSTRACT FROM AUTHOR]

Copyright of Building Research & Information is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article discusses the empirical based model which estimates the net primary production (NPP) and depth-dependent decay rates of near-surface boreal and subarctic peatlands in Canada. It states that the application of the model in three boreal sites shows that the sites are net sinks for atmospheric carbon. It mentions that shifts from sinks to sources may happen within time frames.