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Abstract Background Implementing large-scale carbon sink afforestation may contribute to carbon neutrality targets and increase the economic benefits of forests in rural areas. However, how to manage planted forests in China to maximize the joint benefits of timber production and carbon sequestration is still unclear. Therefore, the present study quantified the effects of different rotation lengths, thinning treatments, site quality (SCI), stand density (SDI), and management costs on the joint benefits of carbon sequestration and timber production based on a stand-level model system developed for larch plantations in northeast China. Results The performances of the different scenarios on carbon stocks were satisfactory, where the variations in the outcomes of final carbon stocks could be explained by up to 90%. The joint benefits increased significantly with the increases of SDIs and SCIs, regardless of which rotation length and thinning treatments were evaluated. Early thinning treatments decreased the joint benefits significantly by approximately 131.53% and 32.16% of middle- and higher-SDIs, however longer rotations (60 years) could enlarge it by approximately 71.39% and 80.27% in scenarios with and without thinning when compared with a shorter rotation length (40 years). Discount rates and timber prices were the two most important variables affecting joint benefits, while the effects of carbon prices were not as significant as expected in the current trading market in China. Conclusions The management plans that promote longer rotations, higher stand densities, and no thinning treatments can maximize the joint benefits of carbon sequestration afforestation and timber production from larch plantations located in northeast China. Graphical Abstract

Abstract Background Carbon (C) sink and stock are among the most important ecosystem services provided by forests in climate change mitigation policies. In this context, old-growth forests constitute an essential reference point for the development of close-to-nature silviculture, including C management techniques. Despite their small extent in Europe, temperate old-growth forests are assumed to be among the most prominent in terms of biomass and C stored. However, monitoring and reporting of C stocks is still poorly understood. To better understand the C stock amount and distribution in temperate old-growth forests, we estimated the C stock of two old-growth stands in the Dinaric Alps applying different assessment methods, including direct and indirect approaches (e.g., field measurements and allometric equations vs. IPCC standard methods). This paper presents the quantification and the distribution of C across the five main forest C pools (i.e., aboveground, belowground, deadwood, litter and soil) in the study areas and the differences between the applied methods. Results We report a very prominent C stock in both study areas (507 Mg C ha− 1), concentrated in a few large trees (36% of C in 5% of trees). Moreover, we found significant differences in C stock estimation between direct and indirect methods. Indeed, the latter tended to underestimate or overestimate depending on the pool considered. Conclusions Comparison of our results with previous studies and data collected in European forests highlights the prominence of temperate forests, among which the Dinaric Alps old-growth forests are the largest. These findings provide an important benchmark for the development of future approaches to the management of the European temperate forests. However, further and deeper research on C stock and fluxes in old-growth stands is of prime importance to understand the potential and limits of the climate mitigation role of forests.

Abstract Backgorund Forest plays an important role in the global carbon cycle by sequestering carbon dioxide and thereby mitigating climate change. In this study, an attempt was made to investigate the effects of land use/land cover (LULC) change (1989–2017) on carbon stock and its economic values in tropical moist Afromontane forests of the Majang Forest Biosphere Reserve (MFBR), south-west Ethiopia. Systematic sampling was conducted to collect biomass and soil data from 140 plots in MFBR. The soil data were collected from grassland and farmland. InVEST modelling was employed to investigate the spatial and temporal distribution of carbon stocks. Global Voluntary Market Price (GVMP) and Tropical Economics of Ecosystems and Biodiversity (TEEB) analysis was performed to estimate economic values (EV) of carbon stock dynamics. Correlation and regression analyses were also employed to identify the relationship between environmental and anthropogenic impacts on carbon stocks. Results The results indicated that the above-ground carbon and soil organic carbon stocks were higher than the other remaining carbon pools in MFBR. The mean carbon stock (32.59 M tonne) in 2017 was lower than in 1989 (34.76 Mt) of MFBR. Similarly, the EV of carbon stock in 2017 was lower than in 1989. Elevation, slope, and harvesting index are important environmental and disturbance factors resulting in major differences in carbon stock among study sites in MFBR. Conclusions Therefore, the gradual reduction of carbon stocks in connection with LULC change calls for urgent attention to implement successful conservation and sustainable use of forest resources in biosphere reserves.

Abstract Background In Ethiopia, highland bamboo has been cultivated in various niches: farmlands, riverbanks, woodlot boundaries, and homesteads, and agroforestry systems. However, the biomass and carbon storage of potential of bamboo forests across niches is not well characterized in Ethiopia. Therefore, this study was conducted to estimate the biomass and carbon storage potential of highland bamboo plantations in northwestern Ethiopia. To this end, a total of 60 circular plots measuring 100 m2 with a radius of 5.64 m were randomly established on the homestead, woodlot, and riverbank plantation niches to conduct the inventory. The biomass storage of bamboo was calculated based on previously published allometric equations. Biomass and carbon stock variations among age-classes and niches of bamboo forests were analyzed using analysis of variance (ANOVA) and subsequent pairwise means comparisons of carbon stocks among niches were performed via post hoc Tukey test at p

Abstract Background Allometric equations are used to estimate biomass and carbon stock of forests. In Ethiopia, despite the presence of large floral diversity, only a few site-specific allometric equations have been developed so far. This study was conducted in the Omo-Gibe woodland of south-western Ethiopia to develop an allometric equation to estimate the Above-ground Biomass (AGB) of the four Acacia species (Senegalia polyacantha, Vachellia seyal, Vachellia etbaica and Vachellia tortilis). Fifty-four (54) Acacia trees were sampled and measured within 35 temporarily established square plots. In each plot, dendrometric variables were measured to derive the models based on combinations of Diameter at Breast Height (DBH), height, and wood density as predictor variables. Model performance was evaluated using goodness-of-fit statistics. The biomass was compared using four allometric biomass models that have been widely used in the tropics. Results The model containing DBH alone was more accurate to estimate AGB compared to the use of multiple predictor variables. This study, therefore, substantiated the importance of site-specific allometric equations in estimating the AGB of Acacia woodlands. This is because a site-specific allometric equation recognizes the environmental factors, vegetation types and management practices. Conclusions The results of this study contribute to a better understanding of allometric equations and an accurate estimate of AGB of Acacia woodlands in Ethiopia and similar ecosystems elsewhere.

Abstract Background The homestead forests of Bangladesh occupy 0.27 million hectares (10% of the total forested area) and have potential to store carbon (C) and conserve biodiversity. Small scale forestry practices, however, are lacking reliable estimation of C stocks and tree species diversity. This may hinder successful implementation of REDD + and similar mechanisms as they concentrate on large-scale forests. This study aimed to estimate the above- and below-ground carbon stocks in homestead forests of Maheshkhali Island in Bangladesh and how tree species diversity and stand structural variation affect these C stocks. We randomly surveyed a total of 239 homestead forests in the hillside, beachside, and inland in 2019. Results Tree biomass C stocks were 48–67% greater in the inland and hillside forests than in the beachside due to significantly greater stand density, basal area, tree diameter. In total we found 52 tree species, but most abundant species in the inland and hillside forests, Mangifera indica, Samanea saman, and Artocarpus heterophyllus stored the most C in tree biomass. Greater tree species richness and diversity index in the inland and hillside forests indicated greater above- and below-ground tree biomass C stocks. An increase in tree species richness and diversity index by one unit was found to increase the tree biomass C stock by 22 and 30 Mg C ha−1, respectively. The total soil C stock was also affected by tree species diversity, stand density, and their interaction with soil properties. Total soil C stocks were greatest (51 Mg ha−1) in the inland forests, having also the greatest stand density and tree species richness. C stock in soil surface was greatest in the hillside forests due to the greatest litterfall, but the average share of litterfall from the total biomass C was only 0.1%. Conclusions Homestead forest ecosystems could store 96 Mg C ha−1 in total, which can contribute to climate change mitigation by generating C credits for small-scale homestead forests owners. Above- and below-ground tree biomass C stocks were found to correlate with tree species diversity, which may also contribute to biodiversity conservation in the REDD + in Bangladesh and countries alike.

Abstract Background Developing countries participating in the mitigation mechanism of reducing emissions from deforestation and forest degradation (REDD+), are required to establish a forest reference emission level (FREL), if they wish to seek financial support to reduce carbon emissions from deforestation and forest degradation. However, establishment of FREL relies heavily on the accurate estimates of carbon stock as one of the input variable for computation of the emission factors (EFs). The product of an EF and activity data, such as the area of deforestation, results in the total emissions needed for establishment of FREL. This study presents the carbon stock estimates for different land cover classes based on an analysis of Tanzania’s national forest inventory data generated through the National Forest Resources Monitoring and Assessment (NAFORMA). Results Carbon stocks were estimated in three carbon pools, namely aboveground, belowground, and deadwood for each of the three land cover classes (i.e. Forest, non-forest, and wetland). The weighted average carbon stock was 33.35 t C ha−1 for forest land, 4.28 t ha−1 for wetland and 5.81 t ha−1 for non-forest land. The uncertainty values were 0.9% for forest land, 11.3% for wetland and 1.8% for non-forest land. Average carbon stocks for land cover sub-classes, which make up the above mentioned major land cover classes, are also presented in our study. Conclusions The values presented in this paper correspond to IPCC tier 3 and can be used for carbon estimation at the national scale for the respective major primary vegetation type for various purposes including REDD+. However, if local based estimates values are needed, the use of auxiliary data to enhance the precision of the area of interest is recommended.

Abstract Background Worldwide, forests are an important carbon sink and thus are key to mitigate the effects of climate change. Mountain moist evergreen forests in Mozambique are threatened by agricultural expansion, uncontrolled logging, and firewood collection, thus compromising their role in carbon sequestration. There is lack of local tools for above-ground biomass (AGB) estimation of mountain moist evergreen forest, hence carbon emissions from deforestation and forest degradation are not adequately known. This study aimed to develop biomass allometric equations (BAE) and biomass expansion factor (BEF) for the estimation of total above-ground carbon stock in mountain moist evergreen forest. Methods The destructive method was used, whereby 39 trees were felled and measured for diameter at breast height (DBH), total height and the commercial height. We determined the wood basic density, the total dry weight and merchantable timber volume by Smalian’s formula. Six biomass allometric models were fitted using non-linear least square regression. The BEF was determined based on the relationship between bole stem dry weight and total dry weight of the tree. To estimate the mean AGB of the forest, a forest inventory was conducted using 27 temporary square plots. The applicability of Marzoli’s volume equation was compared with Smalian’s volume equation in order to check whether Marzoli’s volume from national forest inventory can be used to predict AGB using BEF. Results The best model was the power model with only DBH as predictor variable, which provided an estimated mean AGB of 291 ± 141 Mg ha−1 (mean ± 95% confidence level). The mean wood basic density of sampled trees was 0.715 ± 0.182 g cm−3. The average BEF was of 2.05 ± 0.15 and the estimated mean AGB of 387 ± 126 Mg ha−1. The BAE from miombo woodland within the vicinity of the study area underestimates the AGB for all sampled trees. Chave et al.’s pantropical equation of moist forest did not fit to the Moribane Forest Reserve, while Brown’s equation of moist forest had a good fit to the Moribane Forest Reserve, having generated 1.2% of bias, very close to that generated by the selected model of this study. BEF showed to be reliable when combined with stand mean volume from Marzoli’s National Forestry Inventory equation. Conclusion The BAE and the BEF function developed in this study can be used to estimate the AGB of the mountain moist evergreen forests at Moribane Forest Reserve in Mozambique. However, the use of the biomass allometric model should be preferable when DBH information is available.

Abstract Background The degradation of forests in developing countries, particularly those within tropical and subtropical latitudes, is perceived to be an important contributor to global greenhouse gas emissions. However, the impacts of forest degradation are understudied and poorly understood, largely because international emission reduction programs have focused on deforestation, which is easier to detect and thus more readily monitored. To better understand and seize opportunities for addressing climate change it will be essential to improve knowledge of greenhouse gas emissions from forest degradation. Results Here we provide a consistent estimation of forest degradation emissions between 2005 and 2010 across 74 developing countries covering 2.2 billion hectares of forests. We estimated annual emissions of 2.1 billion tons of carbon dioxide, of which 53% were derived from timber harvest, 30% from woodfuel harvest and 17% from forest fire. These percentages differed by region: timber harvest was as high as 69% in South and Central America and just 31% in Africa; woodfuel harvest was 35% in Asia, and just 10% in South and Central America; and fire ranged from 33% in Africa to only 5% in Asia. Of the total emissions from deforestation and forest degradation, forest degradation accounted for 25%. In 28 of the 74 countries, emissions from forest degradation exceeded those from deforestation. Conclusions The results of this study clearly demonstrate the importance of accounting greenhouse gases from forest degradation by human activities. The scale of emissions presented indicates that the exclusion of forest degradation from national and international GHG accounting is distorting. This work helps identify where emissions are likely significant, but policy developments are needed to guide when and how accounting should be undertaken. Furthermore, ongoing research is needed to create and enhance cost-effective accounting approaches.

Abstract Background The German greenhouse gas inventory in the land use change sector strongly depends on national forest inventory data. As these data were collected periodically 1987, 2002, 2008 and 2012, the time series on emissions show several “jumps” due to biomass stock change, especially between 2001 and 2002 and between 2007 and 2008 while within the periods the emissions seem to be constant due to the application of periodical average emission factors. This does not reflect inter-annual variability in the time series, which would be assumed as the drivers for the carbon stock changes fluctuate between the years. Therefore additional data, which is available on annual basis, should be introduced into the calculations of the emissions inventories in order to get more plausible time series. Results This article explores the possibility of introducing an annual rather than periodical approach to calculating emission factors with the given data and thus smoothing the trajectory of time series for emissions from forest biomass. Two approaches are introduced to estimate annual changes derived from periodic data: the so-called logging factor method and the growth factor method. The logging factor method incorporates annual logging data to project annual values from periodic values. This is less complex to implement than the growth factor method, which additionally adds growth data into the calculations. Conclusion Calculation of the input variables is based on sound statistical methodologies and periodically collected data that cannot be altered. Thus a discontinuous trajectory of the emissions over time remains, even after the adjustments. It is intended to adopt this approach in the German greenhouse gas reporting in order to meet the request for annually adjusted values.

Abstract Background No consensus has been reached how to measure the effectiveness of climate change mitigation in the land-use sector and how to prioritize land use accordingly. We used the long-term cumulative and average sectorial C stocks in biomass, soil and products, C stock changes, the substitution of fossil energy and of energy-intensive products, and net present value (NPV) as evaluation criteria for the effectiveness of a hectare of productive land to mitigate climate change and produce economic returns. We evaluated land management options using real-life data of Thuringia, a region representative for central-western European conditions, and input from life cycle assessment, with a carbon-tracking model. We focused on solid biomass use for energy production. Results In forestry, the traditional timber production was most economically viable and most climate-friendly due to an assumed recycling rate of 80% of wood products for bioenergy. Intensification towards "pure bioenergy production" would reduce the average sectorial C stocks and the C substitution and would turn NPV negative. In the forest conservation (non-use) option, the sectorial C stocks increased by 52% against timber production, which was not compensated by foregone wood products and C substitution. Among the cropland options wheat for food with straw use for energy, whole cereals for energy, and short rotation coppice for bioenergy the latter was most climate-friendly. However, specific subsidies or incentives for perennials would be needed to favour this option. Conclusions When using the harvested products as materials prior to energy use there is no climate argument to support intensification by switching from sawn-wood timber production towards energy-wood in forestry systems. A legal framework would be needed to ensure that harvested products are first used for raw materials prior to energy use. Only an effective recycling of biomaterials frees land for long-term sustained C sequestration by conservation. Reuse cascades avoid additional emissions from shifting production or intensification.

Background: Developing countries participating in the mitigation mechanism of reducing emissions from deforestation and forest degradation (REDD+), are required to establish a forest reference emission level (FREL), if they wish to seek financial support to reduce carbon emissions from deforestation and forest degradation. However, establishment of FREL relies heavily on the accurate estimates of carbon stock as one of the input variable for computation of the emission factors (EFs). The product of an EF and activity data, such as the area of deforestation, results in the total emissions needed for establishment of FREL. This study presents the carbon stock estimates for different land cover classes based on an analysis of Tanzania's national forest inventory data generated through the National Forest Resources Monitoring and Assessment (NAFORMA)., Results: Carbon stocks were estimated in three carbon pools, namely aboveground, belowground, and deadwood for each of the three land cover classes (i.e. Forest, non-forest, and wetland). The weighted average carbon stock was 33.35 t C ha -1 for forest land, 4.28 t ha -1 for wetland and 5.81 t ha -1 for non-forest land. The uncertainty values were 0.9% for forest land, 11.3% for wetland and 1.8% for non-forest land. Average carbon stocks for land cover sub-classes, which make up the above mentioned major land cover classes, are also presented in our study., Conclusions: The values presented in this paper correspond to IPCC tier 3 and can be used for carbon estimation at the national scale for the respective major primary vegetation type for various purposes including REDD+. However, if local based estimates values are needed, the use of auxiliary data to enhance the precision of the area of interest is recommended.