Forest Stocks Research Articles

Carbonated tiger-high above-ground biomass carbon stock in protected areas and corridors and its observed negative relationship with tiger population density and occupancy in the Terai Arc Landscape, Nepal.

Healthy natural forests maintain and/or enhances carbon stock while also providing potential habitat and an array of services to wildlife including large carnivores such as the tiger. This study is the first of its kind in assessing relationships between above-ground biomass carbon stock, tiger density and occupancy probability and its status in protected areas, corridors, and forest connectivity blocks. The dataset used to assess the relationship were: (1) Converged posterior tiger density estimates from camera trap data derived from Bayesian- Spatially Explicit Capture-Recapture model from Chitwan National Park; (2) Site wise probability of tiger occupancy estimated across the Terai Arc Landscape and (3) Habitat wise above-ground biomass carbon stock estimated across the Terai Arc Landscape. Carbon stock maps were derived based on eight habitat classes and conservation units linking satellite (Landsat 7 ETM+) images and field collected sampling data. A significant negative relationship (r = -0.20, p<0.01) was observed between above-ground biomass carbon stock and tiger density in Chitwan National Park and with tiger occupancy (r = -0.24, p = 0.023) in the landscape. Within protected areas, we found highest mean above-ground biomass carbon stock in high density mixed forest (~223 tC/ha) and low in degraded scrubland (~73.2 tC/ha). Similarly, we found: (1) highest tiger density ~ 0.06 individuals per 0.33 km2 in the riverine forest and lowest estimates (~0.00) in degraded scrubland; and (2) predictive tiger density of 0.0135 individuals per 0.33 km2 is equivalent to mean total of 43.7 tC/ha in Chitwan National Park. Comparatively, we found similar above-ground biomass carbon stock among corridors, large forest connectivity blocks (~117 tC/ha), and within in tiger bearing protected areas (~119 tC/ha). Carbon conservation through forest restoration particularly in riverine habitats (forest and grassland) and low transitional state forests (degraded scrubland) provides immense opportunities to generate win-win solutions, sequester more carbon and maintain habitat integrity for tigers and other large predators.

Carbon stock at several types of mangrove ecosystems in Bregasmalang, Central Java, Indonesia

Abstract. Sugiatmo, Poedjirahajoe E, Pudyatmoko S, Purwanto RH. 2023. Carbon stock at several types of mangrove ecosystems in Bregasmalang, Central Java, Indonesia. Biodiversitas 24: 182-191. Mangrove ecosystems have an important role but are also faced with the conversion of use and impacts from climate change. Therefore, this research aims to determine the carbon stock above-ground, below-ground, and the soil at several types of mangrove ecosystems in Bregasmalang, Central Java. A total of 8 transect lines, each having a length of 125 m and consisting of six plots, were placed in four types of mangrove ecosystems to obtain data on the diameter of the vegetation and soil at five different depths. Allometric equations were used to analyze diameter data, while the soil compositions were analyzed in the laboratory. The results showed that the total carbon stock in Bregasmalang was 713.13 Mg ha-1 with the details as follows; above-ground 30.27 Mg ha-1 (4%), below-ground 10.99 Mg ha-1 (2%), and soil carbon 671.87 Mg ha-1 (94%). Meanwhile, the total carbon stock in conservation mangrove forests was 763.75 Mg ha-1, rehabilitation mangrove 719.25 Mg ha-1, silvofishery 680.71 Mg ha-1, and ponds 688.81 Mg ha-1. Based on the results, the high soil and total carbon stock in conservation mangroves showed the importance of protecting the ecosystems to mitigate climate change.

Assessing the Correlation between Aboveground Carbon Stock, NDVI and Tree Species Diversity (A Study of Kailali and Kanchanpur District)

There is limited research to show the correlation between biophysical character and reflectance value of satellite imageries. Thus, this research was conducted to show the relation between the reflectance value (Normalized Differences Vegetation Index: NDVI) and biophysical characteristics (carbon stock and biodiversity) of forest. Kanchanpur and Kailali districts of Nepal were selected as the study sites. Total 184 plots were established to measure the height and diameter at breast height (DBH). The Landsat 8 image of 2022 was downloaded from USGS.gov. Above ground tree biomass was calculated which was further converted into carbon stock. Tree species diversity was assessed using Shannon-Weiner index (H’). Furthermore, Pearson’ correlation was performed to show the relation between aboveground carbon stock vs NDVI and biodiversity vs NDVI. The descriptive statistics showed that mean value of above ground carbon with standard deviation was 109.70±64.52 and 96.76±53.79 ton/ha in Kanchanpur and Kailali districts respectively. The mean value with standard deviation of H’ index was 1.163 ±0.512 and 1.247 ±0.56 in Kanchanpur and Kailali districts respectively. The mean value with standard deviation of NDVI of the sampled plots was 0.491±0.268 and 0.367±0.192 of Kanchanpur and Kailali districts respectively. The R value of Carbon stock vs NDVI was 0.54 and 0.382 of study sites in Kanchanpur and Kailali districts respectively. Similar results were of Carbon stock vs H’ index and H’ index vs NDVI of the study sites of these districts. t-test showed that, these equations were significant at 5% since p value was less than 0.05. This study will be useful to understand the application of NDVI to correlate with biophysical characteristics of the forest.

The Vegetation Composition and Carbon Stock of Old Shrub Typology to Support the Rehabilitation Program in Sumatra and Kalimantan Islands, Indonesia

The typology of certain old shrubs assists with the selection of suitable plant species for rehabilitation. The carbon stock dynamic in old shrubs is fundamental due to their high uptake during the growth process phase. A plot of 100 m × 100 m (1 hectare) was created in each location, referring to the work of Mueller-Dombois and Ellenberg. The plot was further divided into subsquares measuring 20 m × 20 m; in each plot, there were 25 subplots. Research results showed that the diversity index of old shrubs at the tree, pole, and seedling stage is 2.50–2.66, 1.23–1.50, and 0.67–1.11, respectively. For Kalimantan, the diversity index is lower than that on Sumatra Island, which is 1.64–1.80, 1.00–1.02, and 0.52–0.81, respectively. The carbon stock of the old shrub forest in Sumatra has an average of 36.61 Mg C per ha (standard deviation 14.54 Mg C per ha) to 72.50 Mg C per ha (standard deviation 25.61 Mg C per ha), while Kalimantan has an average of 47.94 Mg C per ha (standard deviation 13.30 Mg C per ha) to 144.07 Mg C per ha (standard deviation 54.64 Mg C per ha). The dynamics of the vegetation composition and carbon stock in each old shrub’s typology are considered when choosing a suitable model, including high carbon stock content, to provide optimal results for rehabilitation activities.

Holm oak (Quercus ilex L.) cover: A key soil-forming force in controlling C and nutrient stocks in long-time coppice-managed forests

In forest ecosystems, soil-plant interactions drive the physical, chemical, and biological soil properties and, through soil organic matter cycling, control the dynamics of nutrient cycles. Parent material also plays a fundamental role in determining soil's chemical properties and nutrient availability. In this study, eight long-time coppice-managed Holm oak forests under conversion to high forest, located under similar climatic conditions in Tuscany and Sardinia Regions (Italy), and grown on soils developed from three different lithologies (limestone, biotite granite, and granite with quartz veins) were evaluated. The research aimed to a) estimate the amount of C and nutrients (total N and potentially available P, Ca, Mg, and K) stored both in the organic, organo-mineral, and mineral horizons and at fixed depth intervals (0–0.3 and 0.3–0.5 m), and b) assess the dominant pedological variables driving elemental accumulation. The soils were described and sampled by genetic horizons and each sample was analyzed for its C and nutrient concentration in both the fine earth and skeleton fractions. Despite the different parent materials from which the soils had evolved, the physicochemical properties and the C and nutrient stocks for the 0–0.3 and 0.3–0.5 m layers did not show substantial differences among the eight soils. Conversely, some differences were observed in the stocks of potentially available P and Ca per 0.01 m of mineral horizons. The findings show that over time, plant-induced pedogenic processes (acidification, mineral weathering, organic matter addition, and nutrient cycling) almost obliterated the influence of parent materials on soil properties. This resulted in the upper soil horizons that showed similar characteristics, even though derived from different lithologies. However, among the study sites, some differences occurred due to lithology, as in the case of the soils derived from calcareous parent materials that had high concentrations of exchangeable Ca in the mineral horizons and, likely, to environmental variables (e.g., exposure), which possibly influenced litter degradation and the release of nutrients such as N and available P.

Carbon potential of climate projects in forests: methodical approach and investment decisions

This article is devoted to the description of the main methodical aspects of calculating the carbon potential of the implementation of climate projects in forests, including the initial data and formulas for such calculations. The study analyzes the basic methodical principles for calculating carbon stocks in forests (including the assessment of changes in carbon stocks in forests, assessment of carbon pools (above-ground and below-ground biomass, litter, soil, dead wood), the possibility of using conversion coefficients to assess carbon stocks for the main forest-forming species, potential approaches to assessment carbon absorption by forest lands not covered by forest vegetation), attention is focused on the basic requirements for the assessment of scenarios of climate projects in forests (baseline, project scenario), as well as on the institutional framework for assessing carbon stocks in forests (including state regulation of the implementation of climate projects in forests). On the basis of the analysis, preliminary estimates of the carbon potential of the implementation of climate projects in forests are given, their prospects are determined, the rationale for the need to assess the carbon potential based on the classification of climate projects in forests is given.

FLORISTICS, CARBON STOCK QUANTIFICATION AND SEQUESTRATION ABILITY OF AN ENCROACHED FOREST IN AKWA IBOM STATE UNIVERSITY, IKOT AKPADEN, SOUTHERN NIGERIA

This study assessed the floristics, carbon stock and sequestration ability of an encroached forest in Akwa Ibom State, Southern Nigeria. Ten plots within the forest were chosen and ten belt transects were established. Trees species were identified in each plot. Litter boxes were placed in each plot at 10 m for litter collection. Soils were collected from the plots at different depths. AGB (aboveground biomass), BGB (belowground biomass), AGC (aboveground carbon) and BGC (belowground carbon) were calculated using appropriate allometric equations. Twenty-two woody species were present in the forest. The values for AGB, AGC, BGM and BGC were 119.31 Mg ha-1, 59.65 Mg C.ha-1, 24.46 Mg ha-1 and 12.23 Mg C.ha-1, each. The total carbon stock (TCS) and biomass in the litter were 9.37 MgCha-1 and 20 Mg ha-1, respectively. The carbon stock in the litter followed this order: leaf (4.10±0.08 Mg C.ha-1) &gt; twigs (3.02±0.04 Mg C.ha-1) &gt; fine root (2.25±0.01 Mg C.ha-1). The TCS in the soil was 33.73 MgCha-1 and followed this decreasing trend: 0-15 cm (23.80±2.65 MgCha-1) &gt; 0 – 30 cm (9.93±1.02 MgCha-1). The TCS and carbon sequestration ability (CSA) of this forest were 125.61 Mg C.ha-1 and 458.31 Mg CO2ha-1. The CSA of this forest followed this decreasing order: AGC pool (218.92 Mg CO2ha-1) &gt; soil (121.11 Mg CO2ha-1) &gt; litter (73.40 Mg CO2ha-1) &gt; BGC pool (44.88 Mg CO2ha-1). These results validate this forest as having a considerable carbon sequestration ability, though, this ability is threatened by human disturbances.

Stand Diversity and Carbon Stock of a Tropical Forest in the Deng Deng National Park, Cameroon

Stand Diversity and Carbon Stock of a Tropical Forest in the Deng Deng National Park, Cameroon

Spatial-temporal variations and driving factors of soil organic carbon in forest ecosystems of Northeast China

Forest soil carbon is a major carbon pool of terrestrial ecosystems, and accurate estimation of soil organic carbon (SOC) stocks in forest ecosystems is rather challenging. This study compared the prediction performance of three empirical model approaches namely, regression kriging (RK), multiple stepwise regression (MSR), random forest (RF), and boosted regression trees (BRT) to predict SOC stocks in Northeast China for 1990 and 2015. Furthermore, the spatial variation of SOC stocks and the main controlling environmental factors during the past 25 years were identified. A total of 82 (in 1990) and 157 (in 2015) topsoil (0–20 ​cm) samples with 12 environmental factors (soil property, climate, topography and biology) were selected for model construction. Randomly selected 80% of the soil sample data were used to train the models and the other 20% data for model verification using mean absolute error, root mean square error, coefficient of determination and Lin's consistency correlation coefficient indices. We found BRT model as the best prediction model and it could explain 67% and 60% spatial variation of SOC stocks, in 1990, and 2015, respectively. Predicted maps of all models in both periods showed similar spatial distribution characteristics, with the lower SOC in northeast and higher SOC in southwest. Mean annual temperature and elevation were the key environmental factors influencing the spatial variation of SOC stock in both periods. SOC stocks were mainly stored under Cambosols, Gleyosols and Isohumosols, accounting for 95.6% (1990) and 95.9% (2015). Overall, SOC stocks increased by 471 ​Tg ​C during the past 25 years. Our study found that the BRT model employing common environmental factors was the most robust method for forest topsoil SOC stocks inventories. The spatial resolution of BRT model enabled us to pinpoint in which areas of Northeast China that new forest tree planting would be most effective for enhancing forest C stocks. Overall, our approach is likely to be useful in forestry management and ecological restoration at and beyond the regional scale.

Carbon stock and dynamic in the middle Xingu forests at eastern Amazonia

ABSTRACT Studies on the quantification and spatial distribution of stored carbon, as well as the potential for carbon uptake by forests, are of great importance. We assessed the spatial distribution and dynamic of carbon in forest plots in the Middle Xingu. These plots are part of the vegetation monitoring area of the Belo Monte Dam. We estimated the biomass of trees with diameter at breast height (DBH) ≥10 cm using an allometric equation with forest inventory data in the eastern Amazonian region in the Xingu River area. We evaluated the vegetation structure and carbon stock dynamic in 2012, 2014, and 2016, and temporal effects on carbon uptake. The periodic annual increase in carbon was significantly higher between 2012 and 2014 (2.5 Mg ha−1) than between 2014 and 2016 (1.84 Mg ha−1). Plant biomass was highly influenced by the abundance of species with low diameters (between 10 cm and 50 cm DBH). Despite the mortality rate being higher than the recruitment in the second period (2014–2016), we found that the forest did function as a carbon sink but showing increases in carbon emissions.

Tree Species Diversity and Carbon Stock in Community and Religious Forests of Rupandehi, Nepal

Forest is one of the most important natural resources of the ecosystem which contributes in biodiversity conservation as well as plays a significant role in maintaining the earth’s climate by sequestrating atmospheric carbon. Tropical forests are rich in biodiversity and store large amounts of carbon. The studied Bolbum Community Forest (BCF) and Brahmakumari Global Religious Forest (BGRF) lie in tropical region between the altitudes 120 and 300 m asl in Rupandehi District of Nepal. The main objective of this research was to assess and compare tree diversities and carbon stocks in two different management regimes, namely, community forest and religious forest. Stratified random sampling technique was used for data collection. The allometric equation biomass-diameter regression (Model II) was used for estimation of carbon stock of tree species while Simpson and Shannon-Wiener indices were used to measure tree species diversity. The results showed that the carbon stock value was 27.15 t.ha-1 in BCF and 40.94 t.ha-1 in BGRF. The community forest had lower value of tree carbon stock than that of the religious forest. However, tree diversity was higher in BCF (25) than in BGRF (20). Shorea robusta was found to be the single dominant species in BGRF with higher basal area (102.24 m².ha-1) and contributed 56% of the carbon stock. The contribution of carbon stock of two co-dominant tree species in BCF were 32% for Shorea robusta and 26% for Terminalia anogeissiana. There was significant (p=0.05) positive relationship of carbon stock with basal area and DBH in both forest types.

Synergy between Carbon and Biodiversity in Restored Forests: A case from leasehold forestry of Nepal

Studies on forest carbon stock have increased in Nepal, especially in community forests, as a result of worldwide recognition of the role of sustainable forest management in climate change mitigation. Leasehold forests, which contribute greatly to reviving degraded forests and livelihoods of pro-poor communities, however, have been sidelined from such studies. This study assessed the biomass carbon stock of leasehold forests and its relationship with tree diversity in the Nawalpur district in Nepal. The concentric sample plots with subplots were laid, measuring trees (8.92m radius), saplings (5.64m radius), and regeneration (1m radius), in eleven leasehold forests. Plant diversity was calculated using the Shannon–Wiener diversity index (H’) to assess forest conditions. The average carbon stock was found to be 11.40 t/ha, where the stock varied by nature of intervention. The average carbon stock in non-tree-based restoration sites was estimated to be 3.81 t/ha, which was significantly lower than in tree-based restoration sites (14.49 t/ha). A total of 37 species of trees were recorded from 45 sample plots distributed across eleven LFUGs. Spearman’s rank-order correlation coefficient between forest carbon stock and diversity index was 0.613, which shows a strong positive correlation and was significant at a 99% confidence interval. There was a synergy between biomass carbon stock and tree diversity because communities were protecting the existing tree species and planting multipurpose trees to meet their need for forest products. The study concludes that leasehold forestry contributes positively to the enhancement of carbon stock and tree diversity.

Contrasting plant-soil-microbial feedbacks stabilize vegetation types and uncouple topsoil C and N stocks across a subarctic-alpine landscape.

Global vegetation regimes vary in belowground carbon (C) and nitrogen (N) dynamics. However, disentangling large-scale climatic controls from the effects of intrinsic plant-soil-microbial feedbacks on belowground processes is challenging. In local gradients with similar pedo-climatic conditions, effects of plant-microbial feedbacks may be isolated from large-scale drivers. Across a subarctic-alpine mosaic of historic grazing fields and surrounding heath and birch forest, we evaluated whether vegetation-specific plant-microbial feedbacks involved contrasting N cycling characteristics and C and N stocks in the organic topsoil. We sequenced soil fungi, quantified functional genes within the inorganic N cycle, and measured 15 N natural abundance. In grassland soils, large N stocks and low C:N ratios associated with fungal saprotrophs, archaeal ammonia oxidizers, and bacteria capable of respiratory ammonification, indicating maintained inorganic N cycling a century after abandoned reindeer grazing. Toward forest and heath, increasing abundance of mycorrhizal fungi co-occurred with transition to organic N cycling. However, ectomycorrhizal fungal decomposers correlated with small soil N and C stocks in forest, while root-associated ascomycetes associated with small N but large C stocks in heath, uncoupling C and N storage across vegetation types. We propose that contrasting, positive plant-microbial feedbacks stabilize vegetation trajectories, resulting in diverging soil C:N ratios at the landscape scale.

Assessing the impact of ecological security and forest fire susceptibility on carbon stocks in Bo Trach district, Quang Binh province, Vietnam

An assessment index of landscape ecological security (LES), different from other ecological models namely Pressure-State-Response (PSR), will be more accurate to capture temporal and geographic changes in landscape as well as ecosystem resilience and resistance to interference. In the present study, the impact of ecological security and forest fires on the carbon stock of forests in Bo Trach district, Quang Binh province, central Vietnam was evaluated and analyzed based on remote sensing data and a hybrid model of ant colony optimization (ACO) and neuro-fuzzy system (NFS). The present study indicated that forest fires are generally high throughout the study area, concentrating on areas exposed to and affected by human reclamation and production activities. The artificial neural network (ANN) model based on principal component analysis (PCA) combined Sentinel-1A data performed a higher prediction accuracy (R2 = 0.74), being much greater than biomass estimation using optical data. It reveals that there is a reliability in estimating the aboveground carbon stocks (AGCs) from the aboveground biomass (AGB). The calculated data suggest the AGCs in the study area is high, but these parameters will loss severely in the coming years due to the nature and humans impacts. These results show that utilizing remote sensing combined with PCA-ANN model would have increased the accuracy of forest fire susceptibility, and detected assessment of the LES and forest fires on the AGCs. The above obtainings supply helpful information for managers and forest rangers to guard the forests in the study area better, and to limit human encroachment, thereby offering actions that contribute to sustainable development.

Estimate Forest Aboveground Biomass of Mountain by ICESat-2/ATLAS Data Interacting Cokriging

Compared with the previous full-waveform data, the new generation of ICESat-2/ATLAS (Advanced Terrain Laser Altimeter System) has a larger footprint overlap density and a smaller footprint area. This study used ATLAS data to estimate forest aboveground biomass (AGB) in a high-altitude, ecologically fragile area. The paper used ATLAS data as the main information source and a typical mountainous area in Shangri-La, northwestern Yunnan Province, China, as the study area. Then, we combined biomass data from 54 ground samples to obtain the estimated AGB of 74,873 footprints using a hyperparametric optimized random forest (RF) model. The total AGB was estimated by combining the best variance function model in geostatistics with the slope that is the covariates. The results showed that among the 50 index parameters and three topographic variables extracted based on ATLAS, six variables showed a significant correlation with AGB. They were, in order, number of canopy photons, Landsat percentage canopy, canopy photon rate, slope, number of photons, and apparent surface reflectance. The optimized random forest model was used to estimate the AGB within the footprints. The model accuracy was the coefficient of determination (R2) = 0.93, the root mean square error (RMSE) = 10.13 t/hm2, and the population estimation accuracy was 83.3%. The optimized model has a good estimation effect and can be used for footprint AGB estimation. The spatial structure analysis of the variance function of footprint AGB showed that the spherical model had the largest fitting accuracy (R2 = 0.65, the residual sum of squares (RSS) = 2.65 × 10−4), the nugget (C0) was 0.21, and the spatial structure ratio was 94.0%. It showed that the AGB of footprints had strong spatial correlation and could be interpolated by kriging. Finally, the slope in the topographic variables was selected as the co-interpolation variable, and cokriging spatial interpolation was performed. Furthermore, a continuous map of AGB spatial distribution was obtained, and the total AGB was 6.07 × 107 t. The spatial distribution of AGB showed the same trend as the distribution of forest stock. The absolute accuracy of the estimation was 82.6%, using the statistical value of the forest resource planning and design survey as a reference. The ATLAS data can improve the accuracy of AGB estimation in mountain forests.

Effect of Prescribed Burning on Tree Diversity, Biomass Stocks and Soil Organic Carbon Storage in Tropical Highland Forests

Fire has been an integral part of ecosystem functioning in many biomes for a long time, but the increased intensity and frequency of wildfires often affect plant diversity and carbon storage. Prescribed burning is one of the alternatives to forest fuel management where the fire is controlled and carried out under a determined set of weather conditions and objectives. The effect of prescribed burning on plant diversity and carbon (C) storage has not been studied widely. The objective of this study was to evaluate the effect of prescribed burning on plant diversity indices, biomass stocks, and soil C storage in the tropical highland forests of Southern Mexico. We assessed plant diversity and carbon stocks at 21 sampling sites: seven with prescribed burning, seven non-burning, and seven with wildfires. We calculated tree biodiversity indices, stand structural properties, and species composition among burning treatments. We quantified C stocks in vegetation biomass by using an allometric equation and forest litter by direct sampling. We analyzed 252 soil samples for soil organic C content and other properties. The results showed that the biodiversity index was higher in sites with prescribed burning (Shannon index, H = 1.26) and non-burning (H = 1.14) than in wildfire sites (H = 0.36). There was a greater similarity in plant species composition between non-burning and prescribed burning sites compared to wildfire sites. Prescribed burning showed a positive effect on soil carbon storage (183.9 Mg C ha−1) when compared to wildfire (144.3 Mg C ha−1), but the difference was not statistically significant (p &gt; 0.05) in biomass stocks. Prescribed burning in this study conserved plant diversity as well as soil carbon stocks compared to non-burning, the opposite of what we found in wildfires.

Influence of Anthropogenic Activities on Forest Carbon Stocks—A Case Study from Gori Valley, Western Himalaya

Carbon stock assessment in various ecosystems is vital for monitoring the health of these ecosystems and national accounting for the United Nations convention on climate change. The influence of various anthropogenic drivers on carbon stock in different ecosystems has not been examined comprehensively. This study aims to determine the impact of anthropogenic pressures (lopping, cutting, grazing) on soil physico-chemical properties and carbon stock in four temperate broadleaf forests dominated by different species of oak, viz., Banj oak (Quercus leucotrichophora), Rianj oak (Quercus lanuginosa), Moru oak (Quercus floribunda) and Kharsu oak (Quercus semecarpifolia) along an elevation gradient from 1700–3000 m asl in Gori valley, western Himalaya. Biomass data were collected from 120 quadrats of 10 × 10 m size at three distinct altitudes (4 forest sites × 3 altitudes × 10 quadrats) and analysed for carbon stock, whereas soil samples were randomly collected in triplicate from three depths of each altitude of the forest site and further analysed for their physico-chemical properties. A total of 767 individual trees with a diameter of ≥31 cm were measured at twelve sites and standing biomass was estimated following the growing stock volume equations. Mean carbon stock was highest in Moru oak (396.6 ± 29.5 Mg C ha−1) and lowest in Banj oak forest (189.3 ± 48.6 Mg C ha−1). We also found soil to be the largest pool of forest carbon (43.0–59.7%) followed by aboveground biomass (31.5–45.0%), belowground biomass (8.4–11.7%) and litter (0.4–0.5%). The basal area showed significant effect on altitude and carbon stock, whereas disturbance showed significant (p &lt; 0.05) negative correlation with the total carbon stock. Soil nitrogen exhibited a significant positive correlation (R2 = 0.60) with the basal area, indicating that nitrogen enhances tree growth and forest carbon stock. However, anthropogenic disturbance showed a significant negative impact on the basal area, soil nutrients and carbon stock of oak forests. This concludes that forest structure, anthropogenic pressure and soil parameters contribute to the carbon stock of the area. Considering the significance of these overexploited oak forests, it is recommended to conserve the old-growth forest species in the study area, since they have the highest carbon accumulation potential.

Allometric relationships among tree-size variables under tropical forest stages in Gia Lai, Vietnam

Allometric models play an undeniable role for estimating hard-to-measure quantities such as volume, biomass and carbon stock in forests. However, so far there has been limited model development for native forests in Vietnam. Therefore, this study was conducted to build and analyze the effectiveness of nonlinear and mixed models for secondary and old-growth forests in Gia Lai, Vietnam. The study measured diameter at breast height, total height, commercial height and crown width of forest trees in 20 plots (10 plots for each forest stage). The results showed that diameter had the strongest relationship with height. In the secondary forest, the Power, Korf and Ratskowky models were the best for pairs of variables, while Prodan, Weibull and Power models were the best fit in the old-growth forest. The nonlinear mixed-effect models were better than classic nonlinear models in both forest stages. Fixed and mixed models developed in this study are very valuable for estimating difficult-to-measure quantities and contribute to effective forest management in the study region.

The role of forest status in households’ fuel choice in Uganda

In this study, we investigate how households' choice of energy source is influenced by the status of the local forest resource. We assume that households choose between clean fuels (e.g., kerosene, LPG, solar, and electricity), dirty biobased fuels (e.g., firewood, animal dung, crop residues, and charcoal), and mixed fuels. We integrate socioeconomic data with high-resolution satellite data on forest conditions from the Uganda National Panel Survey. The findings from a random-effects multinomial logit model indicate that households in vegetated areas are 6–7% less likely to rely solely on dirty biobased fuels, and 6–8% more likely to use mixed fuels, compared to those in non-vegetated areas. A larger forest stock is more strongly associated with lower use of firewood than charcoal. A possible explanation for the findings is the presence of policies for forest conservation and enhanced forest property rights, which improve forest conditions and limit opportunities to collect firewood. Given households' dependence on forest-based fuels, such policies could need to be modified to secure households’ access to these fuels.

Soil quality, carbon stock and climate change mitigation potential of Dipterocarp natural and planted forests of Tripura, Northeast India

Soil quality, carbon stock and climate change mitigation potential of Dipterocarp natural and planted forests of Tripura, Northeast India