Forest Carbon Storage Research Articles

Unsupervised Semantic Segmenting TLS Data of Individual Tree Based on Smoothness Constraint Using Open-Source Datasets

Unsupervised segmentation of Terrestrial Laser Scanning (TLS) data into wood and leaf is the key for studying forest carbon storage, photosynthesis, canopy radiation. Further segmentation of wood data into trunk and larger branch (TLB), remaining branch (RB) is of great significance and challenge for dust retention, soil heavy metal enrichment. We proposed an unsupervised, automatic semantic segmentation method based on TLS data of individual tree. The method firstly performs initial segmentation based on plane fitting residuals and neighborhood normal angle, which can extract smooth and connected regions in point cloud. Then, the geometric features of segmented clusters are quantified to approximate RB or leaf features. Finally, the segmentation of TLB, RB, and leaf is realized by combining different clusters from bottom to top with geometric features and neighborhood relations. The segmentation performance of our method was evaluated with 104 tree samples from 23 tree species in two open-source datasets from Indonesia, Peru, Guyana and from Canada and Finland. The micro-average precision of our method is 93.61%. The micro-average recalls of TLB, RB, and leaf are 97.08%, 86.44%, and 89.62%. Compared with the well-known method of separating wood and leaf, our method has 33.56% higher sensitivity, 1.82% higher specificity, 20.52% higher precision, and 0.217 higher F1-score. Besides, we estimated the surface area and volume of TLB, the surface area and volume of RB based on the segmented data. The above parameters have good consistency compared to those calculated based on manually separated point clouds (Pearson correlation coefficient (PCC) of 0.55-0.93).

Application of a Panel Data Quantile-Regression Model to the Dynamics of Carbon Sequestration in Pinus kesiya var. langbianensis Natural Forests

Even though studies on forest carbon storage are relatively mature, dynamic changes in carbon sequestration have been insufficiently researched. Therefore, we used panel data from 81 Pinus kesiya var. langbianensis forest sample plots measured on three occasions to build an ordinary regression model and a quantile-regression model to estimate carbon sequestration over time. In the models, the average carbon reserve of the natural forests was taken as the dependent variable and the average diameter at breast height (DBH), crown density, and altitude as independent variables. The effects of the DBH and crown density on the average carbon storage differed considerably among different age groups and with time, while the effect of altitude had a relatively insignificant influence. Compared with the ordinary model, the quantile-regression model was more accurate in residual and predictive analyses and removed large errors generated by the ordinary model in fitting for young-aged and over-mature forests. We are the first to introduce panel-data-based modeling to forestry research, and it appears to provide a new solution to better grasp change laws for forest carbon sequestration.

Author Correction: Estimating carbon storage in urban forests of New York City

Author Correction: Estimating carbon storage in urban forests of New York City

Root Growth Was Enhanced in China Fir (Cunninghamia lanceolata) after Mechanical Disturbance by Ice Storm

Accurate estimation of forest biomass and its growth potential could be important in assessing the mitigation potential of forest for climate change. However, severe mechanical disturbance such as stem breakage imposed significant changes to tree individuals in biomass structure, which could bring new inaccuracy to biomass estimation. In order to investigate the influence of severe mechanical disturbance on tree biomass accumulation and to construct accurate models for biomass and carbon storage estimation, this paper analyzed the relationship between tree size and biomass for China fir (Cunninghamia lanceolata (Lamb.) Hook) which suffered stem breakage from, and survived, an ice storm. The performance of independent variables diameter (D) and height (H) of China fir, were also compared in biomass estimation. The results showed that D as an independent variable was adequate in biomass estimation for China fir, and tree height was not necessary in this case. Root growth was faster in China fir which had suffered breakage in the main stem by the ice storm, than China fir which were undamaged for at least 7 years after the mechanical disturbance, which, in addition to biomass loss in stem, caused changes in the allocation pattern of the damaged trees. This suggests biomass models constructed before severe mechanical disturbance would be less suitable in application for a subsequent period, and accurate estimations of biomass and forest carbon storage would take more effort.

Commercial forest carbon protocol over-credit bias delimited by zero-threshold carbon accounting

The validity of forest carbon offsets is increasingly called into question. However, despite the use of commercial forest carbon protocols (CFCPs) for more than two decades, claiming ∼566 MMtCO2e and a market value of ∼USD $15.7 billion, comparative analysis and quality assurance of CFCP methodology and offset results are limited. In this study, five widely used biometric-based CFCPs are characterized and compared with results of directly measured CO2 by eddy covariance, a meteorological method integrating vertical fluxes of forest and soil carbon and the only alternative non-biometric source of net forest carbon sequestration data available. We show that CFCPs share a structural feature delimiting forest carbon values by zero-threshold carbon accounting (gC m−2 y−1 or d−1 ≤ 0), confirming reported forest carbon uncertainty, elucidating the data gap across CFCPs, and emphasizing the need for urgent improvement. The CFCP pattern of values is in contrast to known natural emissions of global forest CO2 exchange that is based on direct measurement, obviating a fundamental biological constraint on net forest carbon storage (i.e., soil efflux, ecosystem respiration). Exclusion of forest CO2 sources to the atmosphere precludes net carbon accounting, resulting in unavoidable over-credit of CFCP project offsets. CFCP carbon results are significantly different from global forest CO2 net ecosystem exchange population results (FLUXNET2015 gC m−2) at the 95 to 99.99% confidence levels, inferring an annual median error of ∼247% (gC m−2), consistent with over-crediting. Given the urgency of reliably reducing CO2 emissions and achievement of net-zero and carbon neutral goals, direct CO2 measurement provides a quality-assured alternative method for commercial forest carbon products with the potential to harmonize global markets, catalyzing the role of forests in managing climate change through nature-based solutions.

Neural network guided interpolation for mapping canopy height of China's forests by integrating GEDI and ICESat-2 data

Spatially continuous estimates of forest canopy height at national to global scales are critical for quantifying forest carbon storage, understanding forest ecosystem processes, and developing forest management and restoration policies to mitigate global climate change. Spaceborne light detection and ranging (lidar) platforms, especially the Global Ecosystem Dynamics Investigation (GEDI) and Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) Advanced Topographic Laser Altimeter System (ATLAS), can measure forest canopy height in discrete footprints globally. Their coverage provides a promising data source for national to global-scale forest canopy height estimates. However, previous studies usually used a regression-based approach to develop spatially continuous forest canopy height distribution through the aid of optical images, which cannot take full advantage of the dense spaceborne lidar footprints and may still suffer from the saturation effect of optical images. In this study, we developed a novel neural network guided interpolation (NNGI) method to map forest canopy height by fusing GEDI, ICESat-2 ATLAS, and Sentinel-2 images. To evaluate the performance of the proposed NNGI method, we generated a 30-m forest canopy height product of China for the year 2019. More than 140 km2 drone-lidar data were collected across the country to train and validate the NNGI method. The results showed that the average forest canopy height of China is 15.90 m with a standard deviation of 5.77 m. We evaluated the interpolated forest canopy height product of China by over 1,100,000 GEDI validation footprints (R2 = 0.55, RMSE = 5.32 m), about 33 km2 drone-lidar validation data (R2 = 0.58, RMSE = 4.93 m), and over 59,000 field plot measurements (R2 = 0.60, RMSE = 4.88 m). Benefiting from the interpolation-based mapping strategy, the resulting product had almost no saturation effect in areas with tall forest canopies. The high mapping accuracy demonstrates the feasibility of the proposed NNGI method for monitoring spatially continuous forest canopy height at national to global scales by integrating multi-platform spaceborne lidar data and optical images, enabling opportunities to provide more accurate quantification of terrestrial carbon storage and better understanding of forest ecosystem processes.

Adding Tree Rings to North America's National Forest Inventories: An Essential Tool to Guide Drawdown of Atmospheric CO2.

Tree-ring time series provide long-term, annually resolved information on the growth of trees. When sampled in a systematic context, tree-ring data can be scaled to estimate the forest carbon capture and storage of landscapes, biomes, and—ultimately—the globe. A systematic effort to sample tree rings in national forest inventories would yield unprecedented temporal and spatial resolution of forest carbon dynamics and help resolve key scientific uncertainties, which we highlight in terms of evidence for forest greening (enhanced growth) versus browning (reduced growth, increased mortality). We describe jump-starting a tree-ring collection across the continent of North America, given the commitments of Canada, the United States, and Mexico to visit forest inventory plots, along with existing legacy collections. Failing to do so would be a missed opportunity to help chart an evidence-based path toward meeting national commitments to reduce net greenhouse gas emissions, urgently needed for climate stabilization and repair.

Millennial-Scale Carbon Storage in Natural Pine Forests of the North Carolina Lower Coastal Plain: Effects of Artificial Drainage in a Time of Rapid Sea Level Rise

Coastal forested wetlands provide important ecosystem services along the southeastern region of the United States, but are threatened by anthropogenic and natural disturbances. Here, we examined the species composition, mortality, aboveground biomass, and carbon content of vegetation and soils in natural pine forests of the lower coastal plain in eastern North Carolina, USA. We compared a forest clearly in decline (termed “ghost forest”) adjacent to a roadside canal that had been installed as drainage for a road next to an adjacent forest subject to “natural” hydrology, unaltered by human modification (termed “healthy forest”). We also assessed how soil organic carbon (SOC) accumulation changed over time using 14C radiocarbon dating of wood sampled at different depths within the peat profile. Our results showed that the ghost forest had a higher tree density at 687 trees ha−1, and was dominated by swamp bays (Persea palustric), compared to the healthy forest, which had 265 trees ha−1 dominated by pond pine (Pinus serotina Michx). Overstory tree mortality of the ghost forest was nearly ten times greater than the healthy forest (p < 0.05), which actually contributed to higher total aboveground biomass (55.9 ± 12.6 Mg C ha−1 vs. 27.9 ± 8.7 Mg ha−1 in healthy forest), as the dead standing tree biomass (snags) added to that of an encroaching woody shrub layer during ecosystem transition. Therefore, the total aboveground C content of the ghost forest, 33.98 ± 14.8 Mg C ha−1, was higher than the healthy forest, 24.7 ± 5.2 Mg C ha−1 (p < 0.05). The total SOC stock down to a 2.3 m depth in the ghost forest was 824.1 ± 46.2 Mg C ha−1, while that of the healthy forest was 749.0 ± 170.5 Mg C ha−1 (p > 0.05). Carbon dating of organic sediments indicated that, as the sample age approaches modern times (surface layer year 2015), the organic soil accumulation rate (1.11 to 1.13 mm year−1) is unable to keep pace with the estimated rate of recent sea level rise (2.1 to 2.4 mm year−1), suggesting a causative relationship with the ecosystem transition occurring at the site. Increasing hydrologic stress over recent decades appears to have been a major driver of ecosystem transition, that is, ghost forest formation and woody shrub encroachment, as indicated by the far higher overstory tree mortality adjacent to the drainage ditch, which allows the inland propagation of hydrologic/salinity forcing due to SLR and extreme storms. Our study documents C accumulation in a coastal wetland over the past two millennia, which is now threatened due to the recent increase in the rate of SLR exceeding the natural peat accumulation rate, causing an ecosystem transition with unknown consequences for the stored C; however, much of it will eventually be returned to the atmosphere. More studies are needed to determine the causes and consequences of coastal ecosystem transition to inform the modeling of future coastal wetland responses to environmental change and the estimation of regional terrestrial C stocks and flux.

Allodb: An R package for biomass estimation at globally distributed extratropical forest plots

Abstract Allometric equations for calculation of tree above‐ground biomass (AGB) form the basis for estimates of forest carbon storage and exchange with the atmosphere. While standard models exist to calculate forest biomass across the tropics, we lack a standardized tool for computing AGB across boreal and temperate regions that comprise the global extratropics. Here we present an integrated R package, allodb, containing systematically selected published allometric equations and proposed functions to compute AGB. The data component of the package is based on 701 woody species identified at 24 large Forest Global Earth Observatory (ForestGEO) forest dynamics plots representing a wide diversity of extratropical forests. A total of 570 parsed allometric equations to estimate individual tree biomass were retrieved, checked and combined using a weighting function designed to ensure optimal equation selection over the full tree size range with smooth transitions across equations. The equation dataset can be customized with built‐in functions that subset the original dataset and add new equations. Although equations were curated based on a limited set of forest communities and number of species, this resource is appropriate for large portions of the global extratropics and can easily be expanded to cover novel forest types.

Spatial variation analysis of urban forest vegetation carbon storage and sequestration in built-up areas of Beijing based on i-Tree Eco and Kriging

To explore available methods for assessing the orientation, magnitude, and role of urban forests in abating climate change, i-Tree Eco and Kriging interpolation were employed to quantify and map the carbon storage and sequestration capability of trees in urban forests. Specifically, urban tree field data were collected from 981 sample plots throughout five types of urban forests in the built-up area of Beijing, China, and used to estimate carbon storage and sequestration within each individual plot and the area as a whole. These data were subsequently subjected to Kriging interpolation to map carbon storage and sequestration within the study area. The results showed that the carbon storage and sequestration patterns in the urban forests in Beijing exhibit noticeable spatial heterogeneity, and that there is a clear, statistically significant distribution of high and low value areas. Furthermore, urban planning, the degree of urbanization, and the urban forest structure effect the carbon spatial distribution. This work provides a reference for prudent planning and construction of urban forests and will aid decision-makers in designing eco-friendly urban environments.

Spatial distribution characteristics of carbon storage density in typical mixed fir and broadleaf forests

In order to further improve the vegetation utilization rate of typical Chinese fir and broad-leaved mixed forest, increase the carbon storage in the ecological environment, protect and improve the ecological environment, the spatial distribution characteristics of carbon storage in typical Chinese fir broad-leaved mixed forest were analyzed. The weight set of subjective estimation of carbon storage density of vegetation carbon storage factor was modified, and the fuzzy evaluation matrix of vegetation carbon storage was obtained. The evaluation vector of the matrix was calculated to evaluate the carbon storage density, and the spatial distribution characteristics of carbon storage density of typical mixed fir and broad-leaved forest were obtained. The carbon content in tree layer, shrub layer, herb layer and litter layer was detected through the sample investigation in Ganzhou City, Ji’an City, Jiujiang City, Yichun City and Shangrao City of Jiangxi Province under the same climate environment. At the same time, the soil samples of each layer were collected for analysis. The results showed that under the same age, density and site conditions, there were significant differences in the carbon storage of vegetation layer and litter layer between Chinese fir mixed forest and Chinese fir pure forest, and the carbon fixation capacity of Chinese fir mixed forest was greater than that of Chinese fir pure forest. In order to enhance the carbon storage in the ecological environment, we can consider a variety of Chinese fir mixed forest, which is of great significance to the maintenance of the ecosystem environment.

Multi-scale estimation of carbon storage for moso bamboo (Phyllostachys edulis) based on the mixed weibull density function

Due to its strong carbon sequestration function, the accurate estimation method for Moso bamboo carbon storage is the basis of quantitative description for Moso bamboo ecological function and carbon trade in the region. Since common methods for estimating forest carbon storage are unsuitable for Moso bamboo with the empty culm which is no concept of volume and accumulation, this study provided an approach to estimating Moso bamboo carbon storage in the region. Based on the biomass of Moso bamboo permanent sample plots, Moso bamboo biomass probability density was calculated through the mixed Weibull density function, where parameters were fitted with the measured probability by the Kernel Density Method. Then the total carbon storage was estimated by the formula M = ω A ∫ b c m f ( m ) d m with the regional area of Moso bamboo forests. Comparisons for this method, the Mean Biomass Method (MBM) and the method on the lowest scale are as follows: 1) The new method takes the area of Moso bamboo as the scale conversion factor to carry out the scale conversion of carbon storage in the region uninvolved in the concept of volume and accumulation. 2) The estimation result of this is more reliable than MBM and simpler than the method on the lowest scale.

Effects of Stand Structure and Topography on Forest Vegetation Carbon Density in Jiangxi Province

Stand structure and topography are important factors affecting forest vegetation carbon density (FVCD). Revealing the interaction mechanisms between stand structure and topography on FVCD is of great significance for enhancing forest vegetation carbon storage and achieving regional carbon neutrality. Based on stratified sampling, systematic distribution and forest continuous inventory sample plots in Jiangxi province, the variation characteristics of FVCD and its correlations with stand structure and topographic factors were studied. The results are as follows: (1) The average FVCD in Jiangxi province was 44.23 Mg/ha, which was dominated by the carbon density of the arbor layer, accounting for about 81.39% of the total forest—far lower than the average level of global FVCD, which proved that the forest in Jiangxi province was dominated by middle-age and young forests with low carbon density, and also showed that the potential for forest vegetation carbon storage in Jiangxi province was huge. (2) Except for vegetation carbon densities of shrub and herb layers, the vegetation carbon densities of other forest layers in Jiangxi province were significantly different among different forest types. Volume per unit area was the most important factor affecting the vegetation carbon densities of arbor and total forest, and vegetation carbon density–volume models of the main forests were built for vegetation carbon density calculation in Jiangxi province. (3) The vegetation carbon densities of arbor layer, snag and log layer, and total forest increased significantly with increases in elevation and slope. Except for the shrub layer and herb layer, the vegetation carbon densities of the other layers and the total forest had extremely significant or significant differences between slope position gradients—indicating that the effect of topography on FVCD in Jiangxi province was significant, mainly through influencing of forest distribution and human disturbance intensity.

Dynamics of Carbon Storage and Its Drivers in Guangdong Province from 1979 to 2012

Accurately estimating the carbon storage of forest ecosystems and deriving the driving factors affecting forest carbon storage are the prerequisites and foundations for promoting the development of global carbon sinks. In order to explore an effective approach for monitoring the carbon sink of forests in developed coastal areas on a large scale, in this paper, Guangdong Province was taken as the case study region; eight periods plots of data of national forest resources continuous inventory were used to estimate the forest carbon storage and carbon density in Guangdong Province from 1979 to 2012; unary linear regression and standard deviation ellipse were used to analyze the dynamic change of carbon storage; and the structural equation model was used to study the driving factors of forest carbon storage. The results showed that: (1) From 1979 to 2012, the forest carbon storage in Guangdong Province increased by 15,087.93 × 104 t, and the forest carbon density increased by 17.66 t/ha. (2) After 2007, the main body of forest carbon storage changed from coniferous species to broadleaf species. (3) From 1979 to 2012, the proportion of young and middle-aged forest carbon storage continued to decline, but it still occupied the dominant component. (4) The forest carbon storage and carbon density in the northern region of Guangdong Province are higher than those in the southern region. (5) Stand factors and environmental factors have a positive effect on forest carbon storage, and understory factors have a negative effect. In conclusion, although forest carbon storage has fluctuated under the influence of forestry policies and human activities, the overall carbon storage and carbon density of Guangdong Province have been increasing. Tree species have become more abundant and the proportion of coniferous forest to broadleaf forest became more rationalized. The forest age group structure is continuously optimized. We also compared our results with that of other provinces in China and other countries with approximate latitude and climatic conditions. The carbon sink potential of Guangdong Province is huge in the future.

Estimating carbon storage in urban forests of New York City

Forests play an important role in mitigating many of the negative effects of climate change. One of the ways trees mitigate impacts of climate change is by absorbing carbon dioxide and storing carbon in their wood, leaves, roots, and soil. Field assessments are used to quantify the carbon storage across different forested landscapes. The number of trees, their size, and total area inform estimates of how much carbon they store. Urban forested natural areas often have greater tree density compared to trees planted in designed cityscapes suggesting that natural area forests could be an important carbon stock for cities. We report a carbon budget for urban forested natural area using field-collected data across an entire city and model carbon stock and annual stock change in multiple forest pools. We find that natural area forests in New York City store a mean of 263.04 (95% CI 256.61, 270.40) Mg C ha-1 and we estimate that 1.86 Tg C (95% CI 1.60, 2.13 Tg C) is stored in the city’s forested natural areas. We provide an upper estimate that these forests sequester carbon at a mean rate of 7.42 (95% CI 7.13, 7.71) Mg C ha-1 y-1 totaling 0.044 Tg (95% CI 0.028, 0.055) of carbon annually, with the majority being stored in trees and soil. Urban forested natural areas store carbon at similar and in some cases higher rates compared to rural forests. Native oak-dominated forests with large mature trees store the most carbon. When compared to previous estimates of urban-canopy carbon storage, we find that trees in natural area forests in New York City account for the majority of carbon stored despite being a minority of the tree canopy. Our results show that urban forested natural areas play an important role in localized, natural climate solutions and should be at the center of urban greening policies looking to mitigate the climate footprint of cities.

A rapid exploratory assessment of vegetation structure and carbon pools of the remaining tropical lowland forests of Southwestern Nigeria

Vegetation composition and structural diversity are important for biodiversity conservation and forest carbon storage.. Less attention has been paid to tropical forest vegetation characteristics and the carbon stock across different pools in Nigeria. This study presents the results of a rapid assessment and exploratory estimate of the woody species composition, biomass and carbon stock of six plots in order to gain quantitative insight into the carbon pools in the lowland forests across Southwest (SW) Nigeria. Using plot level quadrat (25 × 25 m) approach, this study explores the structural characteristic and carbon stock potential of the tropical natural forest. . Woody species composition, density, girth-size, height, basal area, and carbon stock from five major pools and their impact on total carbon storage were determined. A total of 89 woody species with mean density of 770.67/ha were enumerated and species structural composition, biomass and carbon stock differed among the investigated plots. Plots III and IV had the highest total number of species and woody density. The species diversity also varies across the plots, and ranged between 2.01 in Plot VI to 2.91 in Plot III. Although majority of the species present in Plots I, II, IV, and VI have lower species importance value index and smaller girth sizes, there were still few individuals with high girth-size. Above and below ground pools suggest that the study area has the capacity of storing between 145.17 to 745.57 Mg C ha−1 of carbon. Carbon stock estimate of the aboveground pool (1,593.89 MgC/ha) was higher than the belowground pool (595.19 MgC/ha) and carbon contribution from litter (0.0203 MgC/ha) and herb (0.0067 MgC/ha) was quite low. Overall, these findings have shown that despite the ongoing anthropogenic disturbance, SW Nigeria tropical forest has considerable potential carbon sequestration.

Natural disturbance impacts on trade-offs and co-benefits of forest biodiversity and carbon.

With accelerating environmental change, understanding forest disturbance impacts on trade-offs between biodiversity and carbon dynamics is of high socio-economic importance. Most studies, however, have assessed immediate or short-term effects of disturbance, while long-term impacts remain poorly understood. Using a tree-ring-based approach, we analysed the effect of 250 years of disturbances on present-day biodiversity indicators and carbon dynamics in primary forests. Disturbance legacies spanning centuries shaped contemporary forest co-benefits and trade-offs, with contrasting, local-scale effects. Disturbances enhanced carbon sequestration, reaching maximum rates within a comparatively narrow post-disturbance window (up to 50 years). Concurrently, disturbance diminished aboveground carbon storage, which gradually returned to peak levels over centuries. Temporal patterns in biodiversity potential were bimodal; the first maximum coincided with the short-term post-disturbance carbon sequestration peak, and the second occurred during periods of maximum carbon storage in complex old-growth forest. Despite fluctuating local-scale trade-offs, forest biodiversity and carbon storage remained stable across the broader study region, and our data support a positive relationship between carbon stocks and biodiversity potential. These findings underscore the interdependencies of forest processes, and highlight the necessity of large-scale conservation programmes to effectively promote both biodiversity and long-term carbon storage, particularly given the accelerating global biodiversity and climate crises.

Bright spots of carbon storage in temperate forests

Abstract Mitigating climate change is an urgent challenge for society. Increasing carbon storage in forests, which cover more than 30% of the global land surface, presents a key opportunity to meet this challenge. Although the biophysical and ecological factors that affect carbon storage have been well studied, the relative importance of social factors in privately owned forests, such as people's goals and management actions, is less well understood. We examine how well typical biophysical and ecological variables can explain differences in above‐ground carbon storage across 1,561 plots in temperate forests of southern Quebec, Canada. We then identify bright spots and dark spots of above‐ground carbon storage, where forests are performing much better or worse than predicted based on biophysical and ecological conditions alone. We conducted surveys with forest owners to assess whether their individual goals, values and management actions explain the differences in carbon storage between bright and dark spots. Biophysical and ecological variables collectively explained a substantial fraction of the variation in carbon storage between forest plots (R2 = 0.42). The ecological variables of stand age, species richness and functional diversity within the plots were the most important variables in explaining carbon storage. Surveys showed that bright spots (plots that stored more carbon than predicted) were often managed by forest owners who expressed a strong connection to, or dependence on, their forested property. Dark spots were often associated with forest harvesting and hunting. Synthesis and applications. Ecologically based policies that aim to increase the average forest age, species richness and functional diversity—and socially based policies that incentivise long‐term forest ownership, stronger connections between people and their properties, and maple syrup production—could help increase carbon storage over multidecadal time‐scales and thereby reduce the harmful effects of climate change.

Effects of biodiversity, stand factors and functional identity on biomass and productivity during the restoration of subtropical forests in Central China

AbstractBiodiversity is found to have a significant promotion effect on ecosystem functions in manipulation experiments on grassland communities. However, its relative role compared with stand factors or functional identity is still controversial in natural forests. Here, we examined their relative effects on biomass and productivity during forest restoration. We investigated stand biomass and productivity for 24 plots (600 m2) across restoration stages in the subtropical forests of Mt. Shennongjia, Central China. We measured five key functional traits and calculated functional diversity (functional richness, evenness and dispersion) and community-weighted mean of traits. We used general linear models, variation partitioning methods to test the relative importance of stand factors (density, stand age, maximum height, etc.), functional identity, species and functional diversity on biomass and productivity. Our results illustrated that stand biomass and productivity increased significantly as forest restoration, and that community species richness increased, while functional dispersion decreased significantly. Variation partitioning analyses showed that diversity had no significant pure effects on biomass and productivity. However, diversity may affect biomass and productivity through the joint effect with stand factors and functional identity. Overall, we found that stand factors had the strongest effect on biomass and productivity, while functional identity significantly affects productivity but not biomass, suggesting that modulating stand structure and species identity are effective ways to enhance forest carbon storage and sequestrations potential in forest management.

Impact of rehabilitation and status area change on land cover and carbon storage in Paliyan Wildlife Reserve, Gunung Kidul, Indonesia

Abstract. Puspanti A, Kusumandari A, Faida LRW, Sudaryatno. 2021. Impact of rehabilitation and status area change on land cover and carbon storage in Paliyan Wildlife Reserve, Gunung Kidul, Indonesia. Biodiversitas 22: 3964-3971. This study analyzed the land cover change and carbon storage after the rehabilitation of Paliyan forest. This study mainly focused on the forest status during 1999-2019, especially after establishing a wildlife reserve forest and after rehabilitation activity. We used a combination of canopy density model, carbon conversion, and changes of management-related data to analyze land cover classes in two decades of 1999-2009 and 2009-2019 representing the change in status of the area, rehabilitation, and management dynamics through the time. The result shows that at baseline (1999), the status was still production plantation forest dominated by non-forest/open land with the most carbon storage in plantation forest of 5463.04 tons of carbon. In the first decade, important events occurred such as continuing illegal logging until 2001; change of area status to wildlife reserve forest; and initiation of rehabilitation in 2003. There was an increase in non-forest areas during the first decade, and carbon storage decreased mostly in plantation forests with only 867.71 tons of carbon remaining. In the second decade, rehabilitation has shown a positive impact in increasing forested areas, and altered non-forest to the forested area dominated by open forest/mixed agriculture area, followed by plantation forest, and secondary forest. In this decade, the legality of the area status and rehabilitation activity underwent to be more advance. The carbon storage also shows the positive result with the most increase of storage in plantation forest of 4072.932 tons carbon, or almost 4.7 times higher than that in 2009. Total carbon storage in 2019 was 13257.50 tons, or almost three times higher than that in 2009. The rehabilitation required a longer period to achieve a more dense forest condition as in 2019 the area was still dominated by open forest or agriculture. The smallholder farmers and high dependency of the surrounding community manage the land to feed their livestock, impede the rehabilitation and restoration process, and de-escalate the transition from non-forest to forest resulted in the more vegetated area. This result is important for stakeholders for designing appropriate forest-related policies and supporting further rehabilitation strategies.