Aboveground Carbon Stocks Research Articles

Carbon Stock Potential of Gara Gola Natural Vegetation in East Hararghe Zone, Eastern Ethiopia

This study was conducted at Gara Gola, in the Oromia regional state of Ethiopia, to examine the carbon sequestration potentials under three altitudinal gradients [i.e., Lower altitude (LA: 1500–1800 m.a.s.l.); Middle altitude (MA: 1801–2000 m.a.s.l.) and upper altitude (UA: 2001–2300 m.a.s.l.)]. A total of 60 quadrats of 20m x 20m, 5m x 5m, and 1m x 1m with six horizontal transect lines were employed to gather data on the tree, shrub, herbaceous, and soil, respectively. To estimate organic carbon percentage, soil parameters were collected from three soil profiles (i.e., 0 to 10 cm, 10 to 20 cm, and 20 to 30 cm). The mean total carbon stock of the study area was 641.18 Mg ha-1. MA had relatively higher TC than the other gradients. But the LA had the lowest TC stock, due to a high amount of human and animal interference. The results showed that the UA had significantly higher above-ground (AGC) and below-ground carbon (BGC) stocks with 147.3±39.4 Mg ha-1 and 18.37±7.8 Mg ha-1, respectively, compared to other gradients. However, LA had the lowest AGC (66.8±8.7 Mg ha-1) and BGC (12.06±2.6 Mg ha-1). Lower altitude exhibited a significantly higher SOC value than the other two altitudinal gradients followed by MA. The UA had the lowest SOC value. SOC across the three soil profiles follows a reduction trend from topsoil depth to lower soil depth with significant variation. In conclusion, LA should embrace better ecological, policy, and socioeconomic considerations than the other gradients.

Stand structure and carbon storage of a young mangrove plantation forest in coastal area of Bangladesh: The promise of a natural solution

Globally, with the growing importance of mangroves for providing ecosystem services and mitigating climate change, it is still uncertain whether planted mangroves can be the counterpart of natural mangroves, and thus the role of planted mangroves is still less understood. Therefore, this study aimed to assess the stand structure and carbon storage of a young mangrove plantation in Satkhira District, Bangladesh and to compare it with the natural mangrove forest (i.e., Sundarbans) to understand the potential of this young mangrove plantation as a nature-based solution to climate change. In addition, to better understand the spatial dynamics of afforested mangrove forests, we investigated and compared both above and below-ground carbon stocks between the landward and riverward sites. We collected both above (height and diameter at breast height, DBH) and belowground (i.e., coarse and fine root) data from 16 plots with a total area of 1600 m2 in two paired transects, eight plots each in landward and riverward sites. Aboveground carbon stocks were estimated using the species-specific allometric models from the biophysical tree parameters (i.e., height and DBH). Besides, belowground root (≥ 20 mm) carbon was measured by direct weighting after collecting soil samples through coring. Stand structural attributes (i.e., density, basal area, and DBH) showed a significant difference between the two sites, whereas Sonneratia apetala was found as the dominant species (IV = 188.7∼207.1) in both forest sites. The mean carbon stock of this plantation was 49.1 Mg C ha−1, while the mean aboveground carbon (AGC) was 37.3 Mg C ha−1. The landward site contributed significantly more AGC (40.1 Mg C ha−1) than the riverward (34.4 Mg C ha−1) site (p<0.05). Besides, the mean belowground roots carbon (BGRC) of this plantation was 11.8 ± 1.4 Mg C ha−1, where the riverward site contributed significantly more root carbon (14.3 Mg C ha−1) than the landward site (9.4 Mg C ha−1) (p<0.05). Tree density and basal area showed a significant positive relationship with BGRC. Although only two species were planted, after 15 years, we observed the total number of species reached nine. The carbon stock, progressive species richness in this plantation reflects the significance of young mangrove plantations in sequestering carbon to mitigate climate change and biodiversity conservation as nature-based solutions which may be useful for future coastal afforestation and restoration programs.

Weak edge effects on trees in Bornean rainforest remnants bordering oil palm

AbstractMany tropical forests are dominated by edge habitat, with consequences for forest structure, carbon stocks, and biodiversity. However, edge effects are highly variable and context‐dependent, and are poorly quantified in oil palm landscapes. We studied edge effects in 10 lowland rainforest remnants bordering mature oil palm plantations on Borneo, by surveying 0.2 ha plots along transects running perpendicular to the forest edge (ten 1.6 km transects, 5‐6 plots per transect; 57 plots in total). We examined how edge proximity affected plot‐level forest structure (canopy cover, number and size of stems ≥10 cm diameter), aboveground carbon stocks, microclimate (air temperature and light intensity), and tree community composition and richness. The largest trees were significantly smaller (up to 21% reduced diameter) in plots near edges, and plot‐level carbon was up to 30% lower (model‐fitted average = 64.7 Mg ha−1 at 50 m from the edge, versus 92.3 Mg ha−1 at 1600 m), with the strongest effects within 300m of edges. However, these significant effects of edge proximity were relatively small in the context of existing variation, with distance‐from‐edge explaining &lt;13% of the total variability in maximum tree size or carbon. In addition, there were generally no effects of edge proximity on any other component of forest structure, composition or diversity, and only a weak effect on microclimate. We conclude that limited edge effects in this system may reflect low structural contrast between forest and mature oil palm, and limited invasion of pioneer trees from plantations, which diminished edge influence in highly heterogeneous forest remnants.Abstract in Malay is available with online material.

Aboveground Carbon Stock Estimation Model Using Sentinel-2A Imagery in Mbeliling Lanscape in Nusa Tenggara Timur, Indonesia

To determine emission levels, information on carbon stocks and changes in each carbon pool is required. Aboveground biomass, particularly on dry land, is one carbon pool that contributes significantly to carbon storage. The goal of this study was to develop a model for estimating aboveground carbon stocks in the Mbeliling landscape, in Nusa Tenggara Timur, using a vegetation index that was correlated with field carbon stocks. The best model was then used to create a map of the distribution of carbon stocks as the final result. Simple linear regression analysis and multiple linear regression analysis were used in the study. Google Earth Engine was used to process the images on a cloud system. When comparing the RGI index for measuring field carbon stocks to other indexes, the correlation test revealed a perfect correlation. The linear regression model for aboveground biomass = 14.046 + 272.496 RGI (R-sq = 0.86) was found to be the best model for aboveground biomass. In the multiple linear regression model, there were signs of multicollinearity. With an overall accuracy of 68% and a cappa accuracy of 54.23%, the best model was able to be used to create a carbon stock map in Mbeliling landscape.&#x0D; Keywords: Carbon stock estimation model, Above Ground Biomass, Sentinel 2A

Assessing intraspecific wood density variations of Syzgium sp. in tropical forest of Southwest Sabah

Wood density (WD) is a critical determinant of estimating forest above-ground biomass (AGB) and carbon stock. Thus, heterogeneity in WD on individuals within species trees needs to be scrutinized, and acquisition of fixed WD value is essential to estimate carbon stock with confidence. This study investigated intraspecific variation in WD of Syzgium sp., also known as “Jambu” or “Kelat”. It is the most occurring species in study areas, and is regarded as an economically important species. Firstly, one half-diameter drilling from bark-to-pith measurement was taken per tree using Rinntech Resistograph R650-ED at breast height. Meanwhile, 5.15 mm-diameter core was sampled at 1.30 m above-ground, with DeWalt DCF899HP2 20V impact wrench 950 Nm and Haglöf increment borer. WD was estimated for each core sample using a dimensional method. Drilling resistance (DR) profiles were processed using DECOM 2.38m1 Scientific (c), and several independent variables were extracted from the resistogram. All resistogram-derived variables were positively correlated with field WD (R: 0.2 – 0.70). In addition, variability on WD in Syzgium sp. population is predominantly explained by the Resistograph amplitude, expressed as mean raw scale of adjusted DR (DR adj.RawSC) in a regression model. Given that intraspecific variation in WD is a crucial conjecture in forest AGB estimation, it is recommended to analyze with larger samples, and in-depth exploration on Resistograph-based variables is deemed to improve the accuracy of WD prediction models.

Aboveground carbon stocks and sequestration rates of forests under different management regimes in Churia region of Nepal

The impact of forest management activities on the ability of forest ecosystems to sequester and store atmospheric carbon is of increasing scientific and social concern. This research estimated the aboveground carbon stocks and carbon sequestration rates of forests under various management regimes in the Churia region of Nepal. We used tree data from 469 permanent sample plots distributed across the region from the data archive of Forest Research and Training Centre for the study. The data from 2012 and 2017 were used. The volumes of individual trees were calculated using species–specific allometric equations, which were then converted to biomasses using their respective wood densities. The carbon content was calculated by multiplying the biomass by 0.47 and was converted to the amount of sequestrated CO2 by multiplying by 3.67. We found that the average estimated aboveground carbon stock increased from 78.43 t ha–1 in 2012 to 89.20 t ha–1 in 2017, resulting in an average annual carbon sequestration rate of 5.34 t ha–1 yr–1 (i.e. 7.90 t CO2 ha–1 yr–1). The results showed significant differences in aboveground carbon stocks and annual carbon sequestration rates among different forest management regimes in the region. Generally, aboveground carbon stock was found to be the highest in protected areas in both years whereas, the annual carbon sequestration rate was found to be the highest in government–managed forests. It can be concluded that the Churia region has great potential in terms of carbon sequestration. The evidence of the strong association of carbon stock and sequestration rate with management regimes provides valuable information for policymakers to maintain and further enhance carbon storage in a geographically vulnerable region like Churia.

Aboveground carbon stocks, woody and litter productivity along an elevational gradient in the Rwenzori Mountains, Uganda

AbstractMontane forests are characterized by high biodiversity, endemism, and strong elevational environmental gradients. The latter attribute makes them also suitable as a “natural laboratory” for studying the effects of environmental parameters on ecosystem functions. To provide better insight into the carbon cycle of Afromontane ecosystems, we used an elevational gradient approach to quantify carbon stocks, woody and litter productivity, and their constraining factors. Twenty plots were established, covering five elevations from Kibale Forest at 1250 m to 3000 m in the Rwenzori Mountains. Results revealed aboveground carbon stocks of between 185.4 ± 48.9 and 70.8 ± 18.6 Mg C ha−1 at 1250–1300 and 2700–3000 m, respectively. Aboveground carbon tended to decrease with elevation, but this trend was not significant. This was due to similarities in stem diameter combined with different effects of tree height and stem density. Similarly, woody productivity did not change with elevation, ranging from 8.3 ± 4.1 to 3.4 ± 1.5 Mg C ha−1 year−1 at 2500–2600 and 2700–3000 m, respectively. However, litter productivity decreased linearly by 0.14 ± 0.04 Mg C ha−1 year−1 per 100 m of elevation increase, ranging from 4.0 ± 0.7 Mg C ha−1 year−1 at 1750–1850 m to 1.2 Mg C ha−1 year−1 at 2700–3000 m. Topsoil physicochemical properties varied with elevation, but showed no significant relationship with carbon stocks and woody productivity. However, litter productivity increased with mean soil temperature, whereas it decreased with soil total nitrogen.

Decoupled abiotic and biotic drivers of aboveground and topsoil organic carbon stocks in temperate forests

AbstractForests are major components of global carbon (C) cycling, and hence, it is crucial to explore the drivers of forest functions related to C sequestration. Here, using the multiple linear regression models (MLMs) and structural equation models (SEMs), we evaluated how abiotic (i.e., soil nutrients and topography) and biotic [i.e., functional trait diversity (FTD) and functional trait identity (FTI)] factors regulate aboveground C (AGC) and topsoil (0–30 cm) organic C (SOC) stocks across 104 plots in temperate forests of Northern Iran. The optimal MLMs showed that the community‐weighted mean (CWM) of wood density and functional divergence increased, but functional evenness decreased AGC stock, where FTI values contributed much (i.e., 74.40%) to the explained variance in AGC stock as compared to FTD indices (12.86%) and abiotic factors (12.74%). On contrary, SOC stock was mainly promoted by soil‐available phosphorus, where abiotic factors contributed much (92.62%) to the explained variance as compared to FTD indices (6.73%) and FTI values (0.65%). The final best‐fitted SEMs showed that AGC stock was strongly controlled (β = 0.64) by FTI values (i.e., a latent variable of CWM of wood density and plant maximum height), whereas SOC stock was strongly controlled (β = 0.74) by abiotic factors (i.e., a latent variable of soil‐available phosphorus and total nitrogen). We argue that suitable functional strategies in combination with soil nutrients should be taken into priority during the forestland management and policy plans for the improvement of C stocks in above‐ and belowground compartments of forest ecosystems.

Structural attributes estimation in a natural tropical forest fragment using very high-resolution imagery from unmanned aircraft systems

Structural attributes are fundamental biophysical parameters of forest, useful for ecological and environmental monitoring and planning. Canopy height is an important input for the estimation of several biophysical parameters as aboveground biomass and carbon stock, and can be related with forest degradation, deforestation, and emission reduction. Thus, an accurate canopy height estimation is a crucial issue in climate change studies and REDD+ initiatives. VHR imagery from unmanned aircraft systems has been studied as a low cost mean for canopy height estimation at local scales, but the accuracy in the estimation is a factor that determines its utility. We evaluated the ability of VHR imagery from unmanned aircraft systems to derive structural attributes, specifically tree-crown area and height, in a natural tropical forest fragment located in the foothills of the Andes Mountains, in the humid tropical forests of the region known as Biogeographic Chocó, South America. The region is one of the most biodiverse areas of the world and has a high level of endemism, but it is also at higher risk of natural-resource loss. We used a structure from motion approach to derive canopy height models of the forest fragment, and we applied mean-shift algorithms to identify single tree crowns. The accuracy assessment was performed using reference data derived from field campaigns and visually interpretation of VHR imagery. The estimated root-mean-square error of the population of vertical errors for the canopy height model was 3.6 m. The total accuracy for delineating tree crowns was 73.9%. We found that using VHR imagery, specific trees and canopy gaps can be identified and easily monitored, which is an important step in conservation programs. We also discuss the usefulness of these findings in the context of fragmented forests and the tradeoffs between the price of a LIDAR system and the accuracy of this approach.

Functional composition enhances aboveground carbon stock during tropical late-secondary forest succession

The ‘mass ratio’ hypothesis states that ecosystem functioning is driven by the functional traits of the most dominant species in communities. Thus, we aimed to evaluate (i) How topographical conditions and stand age determine changes in tree community composition, richness, abundance and carbon dominant (CD) species, and (ii) Assess whether community-weighted mean of functional trait values of CD species explain aboveground carbon (AGC) stock. We used community-weighted mean of wood density and maximum stem diameter to evaluate the effect of functional dominance in AGC stock. We found that different topographic conditions and stand age change community composition, richness, abundance and CD species along the late-secondary stage. Our results showed that functional trait values of CD species determine AGC stock. Thus, the proportion of CD species was shaped by topography and stand age, whereas carbon stock by the dominant species’ functional traits (wood density and diameter). This study advances our understanding of the mechanisms that drive carbon stock in tropical forests and supports the ‘mass ratio’ hypothesis. We emphasize the relevance of the trait-based approach to understand forest functioning and trait functional composition and taxonomic identity for carbon storage, recovery and increase in secondary Atlantic Forests.

Species-specific and generalized biomass models for estimating carbon stocks of young reforestations

Biomass models are key to the correct quantification of aboveground biomass and carbon stocks. Most of the current available sets of biomass models were developed for adult trees although very few have been employed to accurately estimate biomass during the first years of reforestations, despite the increasing number of reforestations over recent years.In this study, species-specific and generalized models for aboveground biomass of single trees have been developed for the main 14 species used in reforestations in Spain. A comparison with the existing biomass models at individual tree level for larger trees of these species was also conducted to confirm the hypothesis that specific models are required for the first years of the reforestation.A new set of biomass models was fitted simultaneously per species, based on three different independent variables – root-collar-diameter, total height and crown projection area- and their combinations. The fitted models provide more accurate and unbiased predictions of aboveground biomass in the first years after reforestation when compared with previously existing models for adult trees. The generalized models can be applied to reforestations when the main species is unknown or for mixed plantations where species are not individualized.The set of models provided can be used in a wide variety of surveys and monitoring conditions depending on the available data, from classical field inventories to more novel approaches such as airborne LiDAR data or aerial photographs.

An Ecological-Economic Approach to Assess Impacts of the Expansion of Eucalyptus Plantations in Agroforest Landscapes of Northern Ethiopia

The conversion of fertile croplands to Eucalyptus woodlots in Ethiopian highlands, due to its business attractiveness to smallholders, raises concerns related to food production, water resources, carbon and other ecosystem services. This study was therefore designed to examine land allocation and plantation management decisions. Our emphasis was on the analysis of tradeoffs between the economic gains obtained from harvesting Eucalyptus timber and food production, carbon and water use. For that purpose, we considered a 1987 ha agroforest landscape in the Amhara region, Northern Ethiopia. With a planning horizon covering nine one-year periods, we developed and used nine Model I single objective linear programming (LP) models, and analyzed tradeoffs between objectives (e.g., land expectation value (LEV), Carbon, volume of ending inventory (VolEI), crop production and water use) using an LP-based Pareto frontier approach. The study revealed that the objective of maximizing the total economic gain from the sale of Eucalyptus wood poles favored a complete conversion of the available cropland into Eucalyptus woodlots. To meet the minimum annual crop production/consumption/requirements of households in the study area, the land under Eucalyptus should be limited to 1772 ha, with a sequestration potential of 1.5 to 1.57 × 107 kg yr−1 of carbon in the aboveground biomass. However, this land cover limit should be decreased to 921 ha so as to limit the total annual water use (for biomass production) below the amount available from rainfall (11,000 m3 ha−1 yr−1). Moreover, the study highlighted that maximizing the harvested wood volume or LEV would come at the cost of a decreased aboveground carbon stock and volume of ending inventory and higher total water use. It also provided alternative optimal Pareto-front points, among which decision makers will be able to select their preferred targets. The current study also showed the potential for the application of Pareto frontier approaches to support the development of effective ecological/economic management strategies and the design of land use policies in an Ethiopian context.

Assessment of WorldView-2 images for aboveground seagrass carbon stock mapping in patchy and continuous seagrass meadows

ABSTRACT Spatially explicit information on aboveground seagrass carbon stock (AGCseagrass) is required to understand the role of seagrass as a nature-based solution to mitigating and adapting to climate change. Remote sensing provides the most effective and efficient means to map AGCseagrass. This research aimed to assess the accuracy of multispectral images to map AGC in seagrass meadows with different characteristics. Kemujan Island in Indonesia was selected to represent patchy beds with relatively low seagrass percent cover and low water clarity, whereas Labuan Bajo of Indonesia served an example of continuous beds with a relatively high percent cover and water clarity. WorldView-2 is a high-spatial-resolution multispectral image with six visible bands, by which water can be penetrated. Several image processing techniques, including sunglint and water column correction, principal component analysis, and co-occurrence texture analysis, were applied to the atmospherically corrected WorldView-2 images. These datasets were used as inputs in the AGC empirical model using seven regression algorithms, namely, single-band linear regression, band-ratio linear regression, stepwise regression, random forest regression, support vector regression, extreme gradient boosting, and multivariate adaptive regression spline. Seagrass field data collected using photo quadrat technique were used to train the regression model and assess the accuracy of the resulting AGCseagrass maps. The results indicated that WorldView-2 can be used to map AGC in different seagrass meadows with a consistent accuracy. The most accurate AGCseagrass map for Kemujan Island had a root mean square error (RMSE) of 4.11 g C m−2 for the aboveground stock in the range of 0–28.70 g C m−2, and for Labuan Bajo, the RMSE of the map was 9.73 g C m−2, with aboveground stock range of 0.31–64.38 g C m−2. Model cross-validation revealed that the mapping model can be site-specific or robust depending on the characteristics of the field-derived AGCseagrass data used to train the regression algorithm. For example, the model developed for Labuan Bajo seagrasses, which had a higher AGC variance, can be successfully applied to Kemujan Island with its lower AGC variance, but not vice versa. This finding is a key factor in the future development of a robust AGCseagrass mapping model that is applicable to various seagrass meadows as a stepping stone to accelerating the filling of gaps in the global seagrass dataset.

Aboveground carbon stock in phytophysiognomies of the Southeast Pantanal, Brazil

Aboveground carbon stock in phytophysiognomies of the Southeast Pantanal, Brazil

Estimating the aboveground biomass and carbon stocks of tall shrubs in a prerestoration degraded salt marsh

Wetlands play a vital role in Earth's carbon cycle and provide important ecosystem services. Their ability to perform their roles can be compromised by human activities that destroy or impair their functioning. The restoration of degraded wetlands may allow carbon cycle functioning, as well as other services, to be recovered. Predicting the potential outcomes from any restoration project requires upfront consideration, including via modeling possible changes in carbon stocks. In this study, we quantified the carbon stocks in tall shrub vegetation proliferating in a degraded salt marsh that is currently the subject of an extensive restoration project. We produced allometric models to estimate biomass and carbon stocks for three tall shrub species, which, along with other freshwater and upland species in the area, will die with continued restoration. Therefore, estimating the potential for carbon losses in biomass is important. We also developed a means of estimating carbon stocks in other nontree plants in the estuary area. Useful equations for estimating the biomass of tall shrubs are limited in general and lacking for degraded systems. Our study adds to the literature on carbon stocks in shrub species and fills a data gap for degraded ecosystems. It also contributes to the broader carbon feasibility study of the aforementioned restoration project that was designed to predict the overall net impact of the project on greenhouse gas emissions in the ecosystem.

Estimation of above-ground biomass and carbon stock of tree species in public parks of Bhubaneswar, Odisha

ABSTRACT Cities play important roles in the conservation of global biodiversity and climate change mitigation, particularly through the planning and management of urban green spaces. Bhubaneswar is a rapidly urbanising city and is witnessing a decline in its green status. This study aims to understand the current species composition and structure in selected urban parks. These urban parks are also reservoirs of carbon stock; and the study estimates park biomass and biomass carbon stocks. We documented 48 species belonging to 44 genera and 22 families in this study. The population structure in the parks revealed that most of the parks lacks trees in the sapling category and hence the regeneration potential is lacking. This may be because of the plantation of various tree species in different planting years. We found the carbon stock ranging from 13.48 Mg in an area of 0.22 ha in SV Park, to 479.49 Mg in an area of 8.91 ha in BP Park. On average, we estimated the biomass per ha to be 32.85 Mg. The difference in carbon stock among the considered parks result from difference in park size, species composition, and structure. Local authorities can use the current assessment of species composition and carbon stock to safeguard the existing trees and prioritise the planting effort in these urban parks.

Estimation of aboveground mangrove carbon stocks from WorldView-2 imagery based on generic and species-specific allometric equations

The aboveground mangrove carbon stock can be estimated and mapped from remote-sensing data using allometric equations. However, the distinct effects of applying the generic or species-specific allometric equations remain unclear in the mangrove environment. The aims of this study are to (1) describe the relationship between field biomass and image pixels using generic and species-specific allometric equations, (2) estimate and map the mangrove carbon stock at the generic and species-specific levels, and (3) compare the accuracy and distribution of the resulting mangrove carbon stock maps. We tested the performance of these allometric equations using a resampled WorldView-2 image (6 m pixel size). The study site was in Clungup Mangrove Conservation (CMC), Malang, East Java and included natural mangrove forests and well-planted mangroves. We used the simple ratio (SR) vegetation index to estimate and map the aboveground carbon stock (AGC) of the mangroves based on the WorldView-2 image. Overall, the results indicate that the use of a generic allometric equation estimates mangrove AGC more accurately than the species-specific equations. However, we found a low coefficient of determination (R2) for both models: 0.2175 for the generic model and 0.1801 for the species-specific one. This may be due to the mangrove objects’ high variation in internal spectral reflectance at the tested image pixel size. The total estimated mangrove AGC obtained was 3,834.15 tons with a standard error of 0.12 for the generic model and 4,927.90 tons with a standard error of 0.17 for the species-specific model. Our findings substantiate the importance of the selection of allometric equations for mangrove AGC studies based on remote-sensing images.

Biomass stocks in California’s fire-prone forests: mismatch in ecology and policy

Restoration of fire-prone forests can promote resiliency to disturbances, yet such activities may reduce biomass stocks to levels that conflict with climate mitigation goals. Using a set of large-scale historical inventories across the Sierra Nevada/southern Cascade region, we identified underlying climatic and biophysical drivers of historical forest characteristics and projected how restoration of these characteristics manifest under future climate. Historical forest conditions varied with climate and site moisture availability but were generally characterized by low tree density (∼53 trees ha−1), low live basal area (∼22 m2 ha−1), low biomass (∼34 Mg ha−1), and high pine dominance. Our predictions reflected broad convergence in forest structure, frequent fire is the most likely explanation for this convergence. Under projected climate (2040–2069), hotter sites become more prevalent, nearly ubiquitously favoring low tree densities, low biomass, and high pine dominance. Based on these projections, this region may be unable to support aboveground biomass >40 Mg ha−1 by 2069, a value approximately 25% of current average biomass stocks. Ultimately, restoring resilient forests will require adjusting carbon policy to match limited future aboveground carbon stocks in this region.

Novel coupled permafrost–forest model (LAVESI–CryoGrid v1.0) revealing the interplay between permafrost, vegetation, and climate across eastern Siberia

Abstract. Boreal forests of Siberia play a relevant role in the global carbon cycle. However, global warming threatens the existence of summergreen larch-dominated ecosystems, likely enabling a transition to evergreen tree taxa with deeper active layers. Complex permafrost–vegetation interactions make it uncertain whether these ecosystems could develop into a carbon source rather than continuing atmospheric carbon sequestration under global warming. Consequently, shedding light on the role of current and future active layer dynamics and the feedbacks with the apparent tree species is crucial to predict boreal forest transition dynamics and thus for aboveground forest biomass and carbon stock developments. Hence, we established a coupled model version amalgamating a one-dimensional permafrost multilayer forest land-surface model (CryoGrid) with LAVESI, an individual-based and spatially explicit forest model for larch species (Larix Mill.), extended for this study by including other relevant Siberian forest species and explicit terrain. Following parameterization, we ran simulations with the coupled version to the near future to 2030 with a mild climate-warming scenario. We focus on three regions covering a gradient of summergreen forests in the east at Spasskaya Pad, mixed summergreen–evergreen forests close to Nyurba, and the warmest area at Lake Khamra in the southeast of Yakutia, Russia. Coupled simulations were run with the newly implemented boreal forest species and compared to runs allowing only one species at a time, as well as to simulations using just LAVESI. Results reveal that the coupled version corrects for overestimation of active layer thickness (ALT) and soil moisture, and large differences in established forests are simulated. We conclude that the coupled version can simulate the complex environment of eastern Siberia by reproducing vegetation patterns, making it an excellent tool to disentangle processes driving boreal forest dynamics.

Community Managed Protected Areas Conserve Aboveground Carbon Stocks: Implications for REDD+

Protected Areas (PAs) represent a broad spectrum of outcomes and governance systems. Among PAs, Community Managed PAs have emerged from communities that are not exclusively indigenous and have developed social organizations to acquire land rights, participate in forest governance, and in some cases, engage in REDD+. However, regardless of the scale or counterfactual, there is no clear consensus about Community Managed PAs’ effectiveness in forest conservation and climate change mitigation. Furthermore, previous studies have been devoted to estimating PAs’ effects on deforestation before REDD+ projects began to operate. Based on Community Concessions in Petén (Guatemala) and Extractive Reserves in Acre (Brazil), we analyzed Community Managed PAs’ temporal and spatial effects on carbon stocks and avoided emissions relative to unprotected lands, other Sustainable Use PAs (IUCN V-VI), and Strict PAs (I-IV). We used carbon density maps, matching methods, geographic discontinuity designs, and sensitivity analysis between 2003 and 2015. After controlling for the influence of market access and agriculture suitability, our analysis shows that Community Managed PAs were more effective than Other Lands (i.e., unprotected) and Sustainable Use PAs, and at least as effective as Strict PAs, in preserving carbon stocks and avoiding emissions. For instance, relative to Other Lands between 2011 and 2015, Community Managed PAs resulted in net avoided emissions of 4.6 tCO2-eq/ha in Petén (Guatemala) and 2.15 tCO2-eq/ha in Acre (Brazil). While these net avoided emissions were lower than in previous years, they seem to be driven by a reduction in carbon emissions outside Community Managed PAs. Spatially, the boundaries of Community Managed PAs varied across jurisdictions. For example, the boundaries of Acre’s Community Managed PAs’ have become less effective in avoiding emissions, which translates into reduced effects on conserving carbon stocks. Our results highlight the need to assess temporal effects to exhibit jurisdiction-wide land-use dynamics and spatial effects to identify local land-use pressures emerging inside or around the boundaries of PAs. Our analysis also shows that decentralized governance in Community Managed PAs may contribute to climate change mitigation through REDD+ and forest conservation targets.