Aboveground Biomass Stocks Research Articles

Estimation of carbon stocks of woody plant species in church forests of West Gojjam zone, Northwestern Ethiopia: Implications for climate change mitigation

Forests, particularly church forests, play a crucial role in mitigating climate change by absorbing and storing CO2, preserving biodiversity, and acting as carbon sinks. This study aimed to estimate the biomass and carbon stocks of various woody species in church forests in the West Gojjam zone. Twenty-six church forests were selected based on agroecology, elevation, size, and proximity to population centers. Vegetation data were collected using a systematic sampling technique, with 20 m x 20 m (400 m2) plots established along transect lines oriented at 120° intervals at 60°, 180°, and 300° within each church forest. Measurements of diameter at breast height (DBH) and height were taken for all matured woody plants with a DBH ≥ 2.5 cm. Data analysis was performed using one-way ANOVA to evaluate the effects of altitude, forest size, and human disturbance on aboveground biomass (AGB) and carbon stocks. Additionally, linear regression was applied to investigate the relationship between vegetation structure (species richness, density, and diversity) and biomass accumulation. The results revealed a total of 111 woody species, dominated by indigenous species particularly from the Fabaceae family. The study church forests had Shannon diversity index and richness ranging from 1.73 to 3.47 and 7 to 45, respectively. The results showed that the 26 church forests had an average aboveground biomass (AGB) of 31.97 ± 3.31 tons ha-1 and a CO2 equivalence of 97.15 ± 10.47 tons ha-1. The AGB and aboveground carbon (AGC) values varied among the church forests, of which Debre Mihret Mesk Kidanemihret had the highest AGB with 99.00 tons ha-1 and 49.50 tons ha-1 AGC, indicating their substantial capacity for carbon storage. Conversely, Korch Silassie church forest displayed the lowest AGB, suggesting ecological challenges that necessitate targeted conservation efforts. These findings underscore the critical role of church forests as carbon sinks, capable of sequestering atmospheric CO2 and contributing to the mitigation of climate change. The findings of the present study suggest the integration of church forests into national and international climate policies, such as REDD+ to leverage their potential in reducing emissions from deforestation and forest degradation.

Potential environmental implications of sandbar afforestation: Insights from ecosystem restoration initiatives in a sandbar of Brahmaputra River Assam, India

Plantation in riverine sandbars offers an excellent opportunity for restoration of ecosystem with a vast potential for enhancing carbon stock. Afforestation on barren islands is challenging task; however, Padmashree Jadav Payeng has single-handedly transformed a sandbar of the river Brahmaputra into a forested landscape in India’s northeastern state of Assam. Such inspiring initiative needs more attention in terms of scientific assessment to quantify ecosystem value and services that can be enriched through such activities. This study uses remote sensing data viz., Landsat4–5TM and Sentinel 2 A data to provide a detailed information on spatio-temporal variability of land use land cover of study region from 1990 to 2021. It aims to conduct a scientific and systematic assessment of biophysical changes that have occurred in the sandbars, understand the status of afforestation, and evaluate the current levels of aboveground biomass (AGB), belowground biomass (BGB), and carbon stock in the selected sandbars. The spatial distribution of AGB, BGB and carbon stock is derived using linear regression model between SAR backscatter and field-based AGB. The results demonstrate that forest cover increased by 31.92 % and sandbar area is reduced by 26.87 % from 1990 to 2021. Spatially derived AGB ranges from 9 to 1295.89 Mg per ha, BGB from 2.35 to 290.50 Mg per ha and carbon stock from 6.18 to 763.34 Mg per ha. Ficus religiosa exhibits a high biomass, ranging from 564.7 Mg per ha to 994.7 Mg per ha, and a high carbon stock, ranging from 8 to 557.30 Mg per ha, attributed to its larger diameter at breast height (DBH). Moreover, phytosociological assessment was conducted for the studied forest, which reveal a total tree species richness of 79. The forest exhibits a total tree density of 395 individuals per hectare. Different biodiversity indices provide a comprehensive understanding of species composition; where results show a Shannon diversity index of 2.81, a Simpson's index of 0.08, a Menhinick's richness index of 2.7, and a Margalef's richness index of 5.26. The article provides detailed information on change in forest cover and present status of AGB, BGB and Carbon stock, providing evidence-based narratives on ecosystem restoration. The initiative by a single person has created a forested landscape and habitat for a large number of wild animals, contributing to better carbon stock and a healthier ecosystem. With regard to the current debate of carbon market, the study suggests the need of instrumentalization of carbon credits for such restoration activities to encourage increase in carbon stock. It also concludes that in-depth research should be taken up on long-term effectiveness of such plantation activities and the potential for scaling up these initiatives for ecosystem restoration in view of climate change mitigation and sustainable forest development.

Evaluation of GEDI footprint level biomass models in Southern African Savannas using airborne LiDAR and field measurements

Savannas cover more than 20% of the Earth and account for the third largest stock of global aboveground biomass yet estimates of their above ground biomass density (AGBD) are very inaccurate. The Global Ecosystem Dynamic Investigation (GEDI) sensor provides near-global full-waveform LiDAR data with 25 m footprints, from which various structural metrics are derived that are used to predict footprint level AGBD. The current GEDI L4A AGBD product uses a comprehensive Forest Structure and Biomass Database (FSBD) to develop models for specific plant functional types and geographic regions, but southern African savannas have been underrepresented in the reference data. The objectives of this study were to (i) validate GEDI L4A AGBD in South African savannas using field measurements and ALS datasets and (ii) develop and evaluate local GEDI footprint-level AGBD estimates from multiple L2A and L2B metrics. The local GEDI AGBD models outperformed GEDI L4A AGBD (R2 = 0.42, RMSE = 12 Mg/ha, %RMSE = 79.5%) with higher R2 and smaller error measures. The local GEDI AGBD using a random forest model (RF) had the highest R2 of 0.71 and lowest %RMSE of 53.3%, while the generalized linear model (GLM) results provided the lowest Relative Mean Systematic Deviation (RMSD) of 9.2%, which was half that of RF model. L4A significantly underestimated AGBD with an RMSD up to −37%. This highlights the importance and benefits of local calibration of biomass models to unlock the full potential of GEDI metrics for estimating AGBD. The field and ALS data have subsequently been contributed to the GEDI FSBD and should be used in calibration of future versions of GEDI L4A AGBD product. This research paves the way for the integration of the local GEDI AGBD estimates with other sensors, notable the eminent NISAR mission, to derive regional to global gridded AGBD products that will enable the monitoring of savanna carbon stocks.

Short Communication: Estimation of aboveground biomass and carbon sequestration in KGPAA Mangkunagoro I Grand Forest Park, Central Java, Indonesia

Abstract. Indriyani S, Sari SP, Negari SIT, Prambudi SA, Nur AAI, Kusumaningrum L, Indrawan M, Sunarto, Sugiyarto, Budiharta S, Setyawan AD. 2024. Short Communication: Estimation of aboveground biomass and carbon sequestration in KGPAA Mangkunagoro I Grand Forest Park, Central Java, Indonesia. Biodiversitas 25: 2257-2263. Forests play an important role in climate change mitigation by absorbing carbon dioxide in the atmosphere and store it in the form of biomass. Valuation of carbon storage potential of a forest will provide insight on the importance of preserving it. This study aims to assess plant diversity and estimate aboveground biomass, carbon stocks, carbon dioxide sequestration potential, and the economic value of ecosystem services from carbon sequestration in KGPAA Mangkunagoro I Grand Forest Park, Central Java, Indonesia. We used a non-destructive method (i.e. allometric equation) in estimating aboveground biomass and carbon stock. We established 50 sampling plots to identify and measure trees (DBH >20 cm) and poles (10<DBH<20 cm). The results showed that there were 30 species from 20 families found in the observation plots. The potential aboveground biomass at the tree and pole level was 297.92 tons/ha and 57.22 tons/ha, respectively, while the total carbon stock for tree and pole was 140.02 tons/ha and 26.89 tons/ha, respectively. This was equivalent to carbon dioxide sequestration of 513.88 tons/ha and 98.70 tons/ha for trees and poles. The economic value of environmental services from carbon stock in the whole area of KGPAA Mangkunagoro I Grand Forest Park was estimated at IDR 21,289,040,253. The results of this research show that apart from playing a role in mitigating climate change by absorbing carbon, KGPAA Mangkunagoro I Grand Forest Park also has valuable economic value.

Aboveground biomass and carbon stocks in a Seasonally Dry Tropical Forest-remnant in Sergipe State, Brazil

Na Caatinga, poucos estudos contabilizam os estoques aéreos de biomassa e carbono, apesar da importância destas informações para a mitigação das mudanças climáticas. Neste estudo, foram avaliados estes estoques após o intervalo de quatro anos (2011-2015) em um remanescente em Poço Verde, SE, Brasil. Adicionalmente, foi analisada a relação desses estoques com parâmetros fitossociológicos. A biomassa foi estimada por meio de equações alométricas e o carbono como a fração de 0,47 da biomassa. A comparação dos estoques e dos dados climáticos entre os períodos foi feita pelo teste t pareado; dados climáticos ainda foram comparados aos valores históricos pelo teste de Friedman. A relação da biomassa com abundância e riqueza foi avaliada por regressões lineares. Foi observado um equilíbrio temporal dos estoques aéreos de biomassa e carbono no período avaliado, provavelmente em função de condições climáticas desfavoráveis e do grau de antropização observado, que podem ter impedido crescimento desses estoques. A biomassa não apresentou relação com abundância e/ou riqueza. Os valores totais observados dos estoques de biomassa e carbono (52,8 Mg ha-1 e 24,8 Mg ha-1, respectivamente) estão dentro da amplitude esperada para a Caatinga. A conservação do fragmento de Caatinga estudado pode contribuir localmente para o armazenamento de carbono.

Growth dynamics of an Amazonian forest: Effects of reduced impact logging and recurring atypical climate events during a 20-year study

Although forest management with reduced impact logging (RIL) practices is regarded as a way to generate income from tropical forests without losing their overall conservation values, the behavior of forests following logging is a topic that has been little studied in the southwestern Brazilian Amazon (SWA), where the predominant forest type is open with low density of commercial timber species. This study examined the growth dynamics of a logged forest in the SWA through monitoring of permanent sample plots (PSP) over twenty years post logging. Following logging, the forest fully recovered its original tree density (439. ha−1) and aboveground biomass (AGB) stocks (188.4 Mg. ha−1) but did not recover extracted timber volume in the commercial size class (DBH > 50 cm, 28 m3. ha−1 before logging and 22.6 m3. ha−1 in 2022). Tree growth, recruitment and mortality rates presented a high fluctuation during the monitoring period, increasing immediately after logging (0.43 cm. yr.−1, 4.1 % and 4.7 % respectively), declining five years after, (0.25 cm. yr.−1, 0.7 % and 1.5 % respectively) and presenting a new peak sixteen years after logging (0.35 cm. yr.−1, 3.9 % and 7.4 % respectively) which persisted to the end of the study period. Consequently, forest turnover was very high, with stand half-life and doubling life of 29.6 and 27.2 years, respectively. The results show that in terms of forest dynamics and production, the behavior of logged forests was also affected by atypical climate events, such as recurring droughts across Amazonia. Consequently, in the forest type studied, and under the prescribed logging cycle of 25 years, RIL alone was not sufficient to guarantee the sustainability of long-term production of the main timber species harvested. Following the current growth trend (0.46 m3. ha−1. yr.−1 for trees above 10 cm DBH and 0.22 m3. ha−1. yr.−1 for trees above 50 cm DBH) the time to recover the total commercial volume and commercial volume for trees above 10 cm DBH and above 50 cm DBH would be 34 and 45 years respectively. Our findings suggest the need for adoption of silvicultural treatments to increase forest productivity in areas under RIL in SWA.

Species diversity, aboveground biomass, and carbon stock of mangrove species in coastal area of Mahaba Island, Placer, Surigao Del Norte

Species diversity, aboveground biomass, and carbon stock of mangrove species in coastal area of Mahaba Island, Placer, Surigao Del Norte

Aboveground biomass stocks of species-rich natural forests in southern China are influenced by stand structural attributes, species richness and precipitation

Forests, the largest terrestrial carbon sinks, play an important role in carbon sequestration and climate change mitigation. Although forest attributes and environmental factors have been shown to impact aboveground biomass, their influence on biomass stocks in species-rich forests in southern China, a biodiversity hotspot, has rarely been investigated. In this study, we characterized the effects of environmental factors, forest structure, and species diversity on aboveground biomass stocks of 30 plots (1 ha each) in natural forests located within seven nature reserves distributed across subtropical and marginal tropical zones in Guangxi, China. Our results indicate that forest aboveground biomass stocks in this region are lower than those in mature tropical and subtropical forests in other regions. Furthermore, we found that aboveground biomass was positively correlated with stand age, mean annual precipitation, elevation, structural attributes and species richness, although not with species evenness. When we compared stands with the same basal area, we found that aboveground biomass stock was higher in communities with a higher coefficient of variation of diameter at breast height. These findings highlight the importance of maintaining forest structural diversity and species richness to promote aboveground biomass accumulation and reveal the potential impacts of precipitation changes resulting from climate warming on the ecosystem services of subtropical and northern tropical forests in China. Notably, many natural forests in southern China are not fully stocked. Therefore, their continued growth will increase their carbon storage over time.

Exploring Carbon Sequestration Potential Across Various Clones in Teak Plantation

A study conducted during August, 2019- February, 2020 forty year old clonal teak plantation in Manchikere, Karnataka, showed substantial carbon sequestration potential across eight distinct clones, emphasizing the promising role of genetic diversity in enhancing carbon capture. The clone studied were MyHaD1, MyHaD4, MyHaV1, MyHaV3, MyHaK2, MySA1, MyHuT1and MyMK3.The recognition and propagation of superior clones are crucial for enhancing carbon sequestration, aiding in the absorption and storage of atmospheric carbon dioxide.The diverse performance observed among the eight clones in the clonal teak plantation underscores the critical role of genetic diversity in shaping key parameters such as girth at breast height, volume, and biomass accumulation. Measurements of volume, aboveground biomass (AGB), belowground biomass (BGB), and soil carbon stock, along with nitrogen (N), phosphorus (P), and potassium (K) levels, were conducted. Carbon sequestration potential per tree varied, with all individuals contributing 395.56 t ha-1. MySA1 showed the highest potential (3.85 t), followed by MyHaD4 (3.08 t), and MyHaV1 recorded the least (1.46 t). Soil analysis revealed available N, P, and K concentrations, and the total carbon sequestration rate was 69.55 tha-1. The organic carbon (OC) content was 1.98% and 1.61%. This emphasizes the importance of factoring in both genetic diversity and soil nutrient dynamics to optimize carbon management in teak plantations effectively.

Estimating Sugarcane Aboveground Biomass and Carbon Stock Using the Combined Time Series of Sentinel Data with Machine Learning Algorithms

Accurately mapping crop aboveground biomass (AGB) in a timely manner is crucial for promoting sustainable agricultural practices and effective climate change mitigation actions. To address this challenge, the integration of satellite-based Earth Observation (EO) data with advanced machine learning algorithms offers promising prospects to monitor land and crop phenology over time. However, achieving accurate AGB maps in small crop fields and complex landscapes is still an ongoing challenge. In this study, the AGB was estimated for small sugarcane fields (<1 ha) located in the Kumphawapi district of Udon Thani province, Thailand. Specifically, in order to explore, estimate, and map sugarcane AGB and carbon stock for the 2018 and 2021 years, ground measurements and time series of Sentinel-1 (S1) and Sentinel-2 (S2) data were used and random forest regression (RFR) and support vector regression (SVR) applied. Subsequently, optimized predictive models used to generate large-scale maps were adapted. The RFR models demonstrated high efficiency and consistency when compared to the SVR models for the two years considered. Specifically, the resulting AGB maps displayed noteworthy accuracy, with the coefficient of determination (R2) as 0.85 and 0.86 with a root mean square error (RMSE) of 8.84 and 9.61 t/ha for the years 2018 and 2021, respectively. In addition, mapping sugarcane AGB and carbon stock across a large scale showed high spatial variability within fields for both base years. These results exhibited a high potential for effectively depicting the spatial distribution of AGB densities. Finally, it was shown how these highly accurate maps can support, as valuable tools, sustainable agricultural practices, government policy, and decision-making processes.

Contrasting drivers of aboveground woody biomass and aboveground woody productivity in lowland forests of Colombia

The relative importance of abiotic and biotic factors in shaping forest biomass stocks and fluxes remains a controversial issue. Here, using data gathered from 39 1 ha plots located in flooded and terra firme mature tropical lowland forests of the Amazon and Orinoquia regions of Colombia, we evaluated the importance of climate, soil fertility, and flooding, as well as tree taxonomic/phylogenetic diversity and forest structural properties, in determining the aboveground biomass stocks (AGB; Mg ha−1) and aboveground woody productivity (AWP; Mg ha−1 year−1). Using information‐theoretic multimodel inference and variance partitioning we found that forest structural features such as the number of trees with diameter at breast height ≥ 70 cm, and wood density, are the main drivers of variation in AGB. However, taxonomic diversity also contributes to AGB because it is associated with more large trees in these forests. In contrast, the key drivers of AWP in these forests were soil P and Mg concentrations, with no significant effects of diversity indices. These findings emphasize the need to include major soil cations other than N and P (e.g. Mg) in experimental studies to improve our understanding about the extent to which soil fertility can modulate increases in forest AWP due to climate change. Terra firme forests had higher AGB stocks than flooded forests, but both had similar AWP; and we found similar results for the drivers of AGB and AWP between flooded and terra firme forests. Our results provide limited evidence for strong effects of plant diversity on AGB or AWP. Therefore, we call for caution on generalizations of nature‐based initiatives aiming to preserve diversity based on maximizing carbon stocks and productivity, due to the complex nature of the processes controlling carbon accumulation and carbon fluxes in tropical forests.

Decadal forest mensuration cycle significantly underestimates net primary production in dense young beech stands

The early development of naturally regenerated forest stands is highly dynamic and includes rapid shifts in productivity and mortality. To characterise the growth dynamics in the initial decades, we assessed aboveground biomass stocks (Sab),aboveground biomass productivity (DPab), and aboveground biomass mortality (DMab) in five naturally regenerated European beech stands located in the Inner Western Carpathians. We developed allometric models for aboveground biomass compartments based on a sample of 262 trees. We also established five circular sampling plots within each stand and, for 15 years, carried out annual measurements of stem diameter at the base and height for all trees within the sampling plots. We then utilised the allometric models to calculate annual biomass accumulation in aboveground biomass compartments on an area basis. Our findings show that, despite the declining contribution of foliage to the total aboveground stock, about a quarter of annual net primary production in young beech stands enters the dead biomass pool due to leaf fall and tree mortality. The growth dynamics and biomass allocation patterns of young beech forests necessitate the development of specific allometric models to describe their growth and carbon capture processes.

Biomass recovery along a tropical forest succession: Trends on tree diversity, wood traits and stand structure

Secondary forests recovering after disturbances currently comprise about half of the world′s tropical forests. A better understanding of the recovery of species composition, stand structure, and biomass stocks of these secondary forests is critical for the sustainable management of these ecosystems. The main objective of this research was to develop the successional trends in forest biomass, tree diversity, and species composition recovery. We monitored the changes in tree species composition, stand structural characteristics, and biomass growth in a chronosequence of tropical secondary forests in the Yucatan Peninsula of Southeastern Mexico. We used both linear and non-linear regressions to develop biomass growth models during forest succession. We calculated tree species diversity and similitude indices between forest successional groups (young, medium-aged, and old-growth forests). The aboveground biomass stocks ranged from 5.2 to 121 Mg C ha-1, which increased gradually with forest age. We observed a divergent trend of biomass accumulation between soft- and densewood species during succession. The contribution of densewood species on tree biomass stock increased (from 32 % to 81 %) with the increasing forest ages. However, the tree diversity indices did not change significantly with forest age and were a poor predictor of aboveground biomass growth during succession. Secondary forests (SFs) of advanced age were more similar to old-growth forests (OF) in their species composition compared to young ones, as evidenced by the Chao-Jaccard index. However, it may take more than a century for these secondary forests to recover to OF-level species composition. Furthermore, the structural equation model allowed us to infer the relative importance of forest age, tree diversity, soil properties, and stand structural attributes, including wood density on biomass growth along the forest chronosequence. Forest age-mediated effect of species composition shift and stand structural changes was a better predictor of biomass accumulation than the changes in tree diversity or soil properties during succession. However, the soil properties as a construct (latent variable), had a significant positive covariance with stand structure, indirectly influencing biomass growth. These biomass and species composition recovery models could be useful in forest management for biodiversity conservation, landscape restoration, and ecosystem services, including carbon sequestration.

Does human intervention modulate the above-ground carbon biomass of agroforestry systems? A study of homegardens in Jaffna peninsula, Sri Lanka

CONTEXTAccumulating above-ground biomass (AGB) and conservation of biodiversity are two major services provided by any ecosystem and homegardens are no exceptions. The permanent structure of a homegarden is owing to its perennial tree-community which steadily builds up and maintains the tree diversity and AGB accumulation. Being a manmade agroforestry system, humans play a vital role in mediating each component of homegarden ecosystem including its carbon stock and biodiversity through management of the tree community. OBJECTIVEThe objectives of this study were to compute the tree diversity and AGB and human interventions in homegarden ecosystem in Jaffna peninsula and to identify the most prominent factors affecting the AGB. METHODSA primary survey was conducted capturing 135 homegardens from two agro-ecological regions (DL3 and DL4) in Jaffna peninsula (Northern province, Sri Lanka), where homegardens are observed as the primary tree-based vegetation. Data on floral composition, livestock and, household-interventions in homegardens were gathered through a structured questionnaire. Tree diversity and AGB were computed using Shannon-Wiener index (SWI) and carbon stock respectively. A multiple linear regression model was estimated to determine the effects of pre-defined interventions on AGB of homegardens. RESULTS AND CONCLUSIONSThe study sample consisted of 122 small-scale (<0.2 ha), 11 medium-scale (0.2–0.8 ha) and 02 large-scale (>0.8 ha) homegardens. The mean tree diversity as estimated by SWI was 1.1 ± 0.6 with 38 perennial species and 1286 trees; 32 genera and 17 families. An average homegarden is estimated to store 23.8 ± 20.9 Mg C/ha as AGB. Homegardens which reared livestock animals, had a significantly lower SWI value, yet, a higher AGB stock, compared to the opposed group (p < 0.05). The SWI, time allocation (hours) for homegarden/week/ha, technical knowledge on farming and non-timber usage within homegarden have significantly (p < 0.05) contributed to the AGB of homegardens, with regression-coefficients of 6.12, 0.02, 1.38 and 7.91, respectively. The results indicate that up-keeping the commitment of households in managing their homegardens contribute to environmental sustainability. SIGNIFICANCEThe results revealed a significant contribution of human interactions on the size of the AGB of homegardens in Jaffna peninsula. This contribution was not adequately discussed in previously literature and the findings suggest the need to manage human interactions in homegarden agroforestry systems to optimize carbon stock in traditional homegardens.

Deep point cloud regression for above-ground forest biomass estimation from airborne LiDAR

Quantifying forest biomass stocks and their dynamics is important for implementing effective climate change mitigation measures by aiding local forest management, studying processes driving af-, re-, and deforestation, and improving the accuracy of carbon accounting. Owing to the 3-dimensional nature of forest structure, remote sensing using airborne LiDAR can be used to perform these measurements of vegetation structure at large scale. Harnessing the full dimensionality of the data, we present deep learning systems predicting wood volume and above ground biomass (AGB) directly from the full LiDAR point cloud and compare results to state-of-the-art approaches operating on basic statistics of the point clouds. For this purpose, we devise different neural network architectures for point cloud regression and evaluate them on remote sensing data of areas for which AGB estimates have been obtained from field measurements in the Danish national forest inventory. Our adaptation of Minkowski convolutional neural networks for regression give the best results. The deep neural networks produce significantly more accurate wood volume, AGB, and carbon stock estimates compared to state-of-the-art approaches. In contrast to other methods, the proposed deep learning approach does not require a digital terrain model and is robust to artifacts along the boundaries of the evaluated areas, which we demonstrate for the case where trees protrude into the area from the outside. We expect this finding to have a strong impact on LiDAR-based analyses of biomass dynamics.

Impact of community-based forest restoration on stand structural attributes, aboveground biomass and carbon stock compared to state-managed forests in tropical ecosystems of Sri Lanka.

Estimation of plant community composition, aboveground biomass and carbon stock is crucial for understanding forest ecology, strengthening environmental management, and developing effective tools and policies for forest restoration. This study was conducted in nine different forest reserves in Sri Lanka from 2012 to 2018 to examine the impact of community-based forest restoration (CBFR) on stand structural attributes, aboveground biomass, and carbon stock compared to state-managed forests. In total, 180 plots (90 plots in community-managed restoration blocks (CMRBs) and 90 plots assigned to state-managed restoration blocks (SMRBs)) were sampled at the study site. To conduct an inventory of standing trees, circular plots with a radius of 12.6 m (equivalent to an area of 500 square meters) were established. The Shannon diversity index, Allometric equations and Difference in Differences (DID) estimation were used to assess the data. Our study provides evidence of the positive impact of the CBFR program on enriching trees diversity. Considering stand structural attributes of both blocks showed higher trees density in the smaller diameter at breast height (DBH) category, indicating growth in both CMRBs and SMRBs. The results showed that tree biomass and carbon density were disproportionally distributed across the nine different forest reserves. On average, tree biomass and carbon density were higher in SMRBs (79.97 Mg ha-1, 37.58 Mg C ha-1) compared to CMRBs (33.51 Mg ha-1, 15.74 Mg C ha-1). However, CMRBs in Madigala reserve represent the highest biomass (56.53 and 59.92 Mg ha-1) and carbon density (26.57 and 28.16 Mg C ha-1). The results of biomass and carbon estimates were higher in all SMRBs in the nine different forest reserves compared to CMRBs. The findings suggest that future forest restoration programs in Sri Lanka should enhance participatory approaches to optimize tree species diversity, density and carbon storage, particularly in community-controlled forests. Our findings could assist developing tropical nations in understanding how CBFR impacts forest restoration objectives and improves the provision of ecological services within forests.

Estimation of aboveground biomass and carbon stocks of Quercus ilex L. saplings using UAV-derived RGB imagery

Key messageCrown area, sapling height, and biovolume extracted from UAV-acquired RGB images provided accurate estimates of aboveground biomass and carbon stocks in a 5-year-old holm oak (Quercus ilex L.) plantation. Our models regressing UAV-derived sapling variables against ground-based measurements exhibited high R2 values (0.78–0.89), thereby reflecting that RGB data can be used as an effective tool for measuring young individuals.ContextThe monitoring of tree sapling performance from the early stages of reforestation is of particular importance in the context of the global efforts to restore forests. Yet, most models to estimate carbon sequestration are developed for adult trees. Thus, the few models specifically developed for young trees rely on ground-based field sampling of tree growth parameters, which is time-consuming and difficult to implement at large spatial scales.AimsOur objectives were as follows: (1) to study the potential of UAV-based RGB imagery to detect and extract sapling variables (e.g., crown area, height, and biovolume) by comparing ground-based sapling measurements with UAV-derived data and (2) to compare the accuracy of the data estimated from RGB imagery with existing traditional field-based allometric equations.MethodsWe used a 5-year-old holm oak (Quercus ilex L. subsp. ballota (Desf.) Samp.) plantation (N = 617 plants), and their crown area, height, and biovolume were estimated from RGB imagery. Subsequently, the plants were harvested and the UAV-derived data were compared with field-measured sapling height and aboveground biomass values. Carbon content in leaves and stems was measured in a subsample of the saplings to estimate carbon stocks.ResultsThe models fitted with UAV-derived variables displayed high performance, with R2 values from 0.78 to 0.89 for height, leaf and stem biomass, total aboveground biomass, and carbon stocks. Moreover, aboveground biomass outputs calculated with field height and UAV-derived height using allometric equations exhibited R2 values from 0.65 to 0.68.ConclusionsGiven the affordable cost of RGB cameras and the versatility of drones, we suggest that UAV-based models may be a cost-effective method to estimate the biomass and carbon stocks of young plantations. However, further studies conducting drone flights in different conditions are needed to make this approach more scalable.

STOCKS OF POTENTIALLY TOXIC ELEMENTS IN THE GROUND COVER OF NORTHERN TAIGA PINE FORESTS UNDER AEROTECHNOGENIC POLLUTION

The paper presents the results of studying the distribution of stocks of potentially toxic elements (Ni, Cu) in subcrown spaces and “windows” of stands in medium-aged pine forests in the background area of the Kola Peninsula and that under environmental pollution by atmospheric emissions of the Severonickel Combine (Monchegorsk, Murmansk Region). On the basis of previously obtained data on the stocks of aboveground biomass of the components of the ground cover, mortmass of plant debris and forest litter and data of chemical analysis by means of atomic absorption spectrometry of leaves of dominant shrub species, aboveground parts of the moss Pleurozium schreberi (Brid.) Mitt, and lichen Cladonia stellaris (Opiz) Pouzar et Vězda, as well as plant waste and organogenic horizon (forest litter) of Al-Fe-humus podzols, Ni and Cu stocks in different components of forest ecosystems were calculated. It was found that the sharp decrease in atmospheric emissions by the Severonickel Combine over the last 20 years has not affected the level of habitat contamination, and the stock of heavy metals in the upper organogenic horizon of Al-Fe-humus podzols remains very high, especially in the impact zone, which does not even allow to start the process of restoration of the ground cover in this area. The stock of heavy metals in the plant waste consistently increases with the increase in the level of forest litter contamination when approaching the source of pollution, but the scale of this increase is significantly smaller in the mortmass compared to the litter. The pattern of distribution of heavy metal stocks in components of ground cover, plant waste and forest litter over the phytocenosis area is fundamentally different in background conditions and under aerotechnogenic pollution, which is due to differences in the accumulation of organic matter in different types of microsites. The ratio of Ni : Cu concentrations and stocks also differs in the soil-vegetation cover in pine forests of the background area and under the influence of aerotechnogenic pollution.

Dendrometric Relationships and Biomass in Commercial Plantations of Dipteryx spp. in the Eastern Amazon

The objective of this study is to characterize and compare the relationships between dendrometric variables in Dipteryx spp. stands in the Western Amazon by fitting linear regression equations for total height (ht) and crown diameter (dc). Six forest stands were evaluated in three municipalities. The variables collected included diameter at 1.3 m height (dbh), ht, and dc. Simple and multiple linear regression equations were fitted to characterize the relationships between ht and dc. The aboveground biomass and carbon stock of the stands were estimated. Most dendrometric variables were positively correlated (97.5%). The general equations presented an R2adj. greater than 0.7, and all coefficients were significant. Equations with non-significant coefficients were common in settlement adjustments (45%). The error for these equations varied between 1.1 and 23.6 m. The trees averaged 22 t ha−1 of aboveground biomass in the stands. There was a variation in carbon sequestration potential among stands, ranging from 5.12 to 88.91 t CO2 ha−1. Single-input equations using dbh as an independent variable are recommended for estimating dc and ht for individual Dipteryx spp. stands. Stands in the Western Amazon play a significant role in carbon sequestration and accumulation. Trees can sequester an average of 4.8 tons of CO2 per year.

Plant Diversity, Aboveground Biomass and Carbon Stock in an Isolated Tropical Sub Montane Forest in Sri Lanka

This study was conducted at Rilagala conservation forest, Nawalapitiya to assess and compare the plant diversity, above ground biomass and carbon stock in the periphery and interior of an isolated sub montane forest in Sri Lanka. All trees above 5 cm Diameter at Breast Height (DBH) in eleven randomly demarcated 25 m × 25 m plots were recorded. Distance up to 100 m from the forest boundary considered as the periphery (8 plots) and over 200 m as the core (3 plots). A total of 1,583 trees belonging to 29 species were recorded and aboveground biomass (AGB) and carbon stocks were calculated using allometric equations. The tree diversity of each plot was calculated using the Shannon diversity index (H’). Results were statistically analysed using single factor ANOVA. The species richness and H’ were the highest at the periphery (n=23, H’= 2.55) while the lowest at forest interior (n=11, H’= 1.97). The highest tree density was recorded at periphery (2,992 trees ha-1) and it decreased to 1,408 trees ha-1 towards the core. The average DBH was 8.5 ± 3.33 cm and it increased towards the forest interior (9.7 ± 4.51 cm) from the periphery (7.2 ± 3.74 cm). Estimated aboveground biomass ranged from 63.99 - 108.13 Mg ha-1 with a mean of 82.53 ± 14.39 Mg ha-1. The above ground C stock was estimated from 31.99 - 54.07 Mg ha-1 with a mean of 41.26 ± 7.2 Mg ha-1. However, there was no significant difference between forest periphery and core in variables, except species richness (p&lt;0.05). The study revealed that the diversity and density of trees decreased towards the forest interior and vice versa was recorded for DBH, AGB and carbon stock. The study highlights the importance of conserving isolated tropical sub montane forest patches for carbon sequestration.