Search Results (98)

Large-scale tree planting programs that store carbon provided by wood and non-wood products are being promoted to mitigate climate change. Assessing the biomass pool of plantations is thus an essential task in forest ecology. This study investigated biomass allocation and allometric equations for above- and belowground components along an age-sequence of Pinus tabuliformis plantations (8, 18, 32, and 46 years old) in northern Hebei Province, China. The biomass of each tree component (root, stem, branch, foliage) was quantified by destructive harvesting. Allometric equations and biomass conversion and expansion factors (BCEFs) were subsequently developed for each tree component. The mean above- and belowground biomass was 5.86, 20.05, 41.26, and 135.28 kg tree⁻¹ and 1.73, 3.42, 11.39, and 27.30 kg tree⁻¹ in the 8-, 18-, 32-, and 46-year-old stands, respectively. The proportion of stem biomass to total tree biomass increased from 28.7% for the 8-year-old stand to 55.8% for 46-year-old stand. In contrast, the contributions of foliage and branch decreased along the chronosequence. The root contribution to total tree biomass also showed a declining trend with stand age. Allometric models based on diameter at breast height showed a good fit (p < 0.001) and incorporating stand age as an additional variable improved the fit of allometric equations (higher R² and lower ACI) for branch, aboveground, root, and total tree biomass. BCEFs decreased for all tree components as stand age increased. These findings indicate that changes in tree biomass allocation and allometry across stand development must be considered to improve estimates of plantation biomass and carbon stocks at regional and national scales. Full article

Peatlands, as globally important carbon sinks, are highly sensitive to human disturbances. The direct discharge or use of domestic sewage with different treatment gradients as peatland replenishment water affects plant communities, but how the plant community structure and biomass change and what drives these changes remain unclear. This study simulated domestic sewage input to a sedge-dominated peatland in the Changbai Mountain region of Northeast China, explored changes in plant community structure and aboveground biomass and revealed the key factors influencing these plant characteristics. The results revealed the following: (1) Reclaimed water treatment (Z) had little effect on the plant community structure; treatments with 50% tap water and 50% domestic sewage (H) and domestic sewage (W) caused rapid expansion of Poaceae plants, with Echinochloa crus-galli (L.) P. Beauv. occupying dominance. (2) Domestic sewage input increases plant diversity, which is driven jointly by soil nutrients and aboveground plant nutrients. (3) The H and W treatments significantly altered aboveground biomass, which was positively correlated with soil nutrients, aboveground plant nutrients, and diversity, whereas the Z treatment had little effect. This research provides scientific support for the control of domestic sewage discharge and whether reclaimed water can be used for ecological water replenishment in peatlands. It holds significant practical value for the scientific management of peatlands, the maintenance of carbon sink functions, and the mitigation of climate change. Full article

The rapid expansion of global aquaculture has led to wastewater enriched with nitrogen, phosphorus, organic matter, antibiotics, and heavy metals, posing serious risks such as eutrophication, ecological imbalance, and public health threats. Conventional physical, chemical, and biological treatments face limitations including high cost, secondary pollution, and insufficient efficiency, limiting sustainable wastewater management. Algal–bacterial symbiotic systems (ABSS) provide a sustainable alternative, coupling the metabolic complementarity of microalgae and bacteria for effective pollutant mitigation and concurrent biomass valorization. Immobilizing microbial consortia within carrier materials enhances system stability, tolerance to environmental changes, and scalability. This review systematically summarizes the pollution characteristics and ecological risks of aquaculture effluents, highlighting the limitations of conventional treatment methods. It focuses on the metabolic cooperation within ABSS, including nutrient cycling and pollutant degradation, the impact of environmental factors, and the role of immobilization carriers in enhancing system performance and biomass resource valorization. Despite their potential, ABSS still face challenges related to mass transfer limitations, complex microbial interactions, and difficulties in scale-up. Future research should focus on improving environmental adaptability, regulating microbial dynamics, designing intelligent and cost-effective carriers, and developing modular engineering systems to enable robust and scalable solutions for sustainable aquaculture wastewater treatment. Full article

This study presents an integrated framework for spatiotemporal mapping of carbon stocks in rubber plantations in Rayong Province, Eastern Thailand—an area undergoing rapid agricultural transformation and rubber expansion. Unlike most existing assessments that rely on Tier 1 IPCC defaults or coarse plantation age classes, our framework combines annual plantation age derived from Landsat time series, age-specific allometric growth models, and Tier 2 soil organic carbon (SOC) accounting. This enables fine-scale, age- and site-sensitive estimation of both tree and soil carbon. Results show that tree biomass dominates the carbon pool, with mean tree carbon stocks of 66.94 ± 13.1% t C ha⁻¹, broadly consistent with national field studies. SOC stocks averaged 45.20 ± 0.043% t C ha⁻¹, but were overwhelmingly inherited from pre-conversion land use (43.7 ± 0.042% t C ha⁻¹). Modeled SOC changes ($\mathsf{\Delta }\mathrm{SOC}$) were modest, with small gains (2.06 t C ha⁻¹) and localized losses (−9.96 t C ha⁻¹), producing a net mean increase of only 1.44 t C ha⁻¹. These values are substantially lower than field-based estimates (5–15 t C ha⁻¹), reflecting structural limitations of the global empirical ΔSOC model and reliance on generalized default parameters. Uncertainties also arise from allometric assumptions, generalized soil factors, and Landsat resolution constraints in smallholder landscapes. Beyond carbon, ecological trade-offs of rubber expansion—including biodiversity loss, soil fertility decline, and hydrological impacts—must be considered. By integrating methodological innovation with explicit acknowledgment of uncertainties, this framework provides a conservative but policy-relevant basis for carbon accounting, subnational GHG reporting, and sustainable land-use planning in tropical agroecosystems. Full article

Background: While forests are pivotal for climate change mitigation, robust CO₂ accounting is required to quantify their climate benefits. However, varying current methodologies complicate this process for practitioners. This study addresses the need for a low-threshold, IPCC-compliant CO₂ estimation method of tree biomass in forest stands. Methods: We developed CO₂ yield tables by integrating segmented allometric biomass functions into fourth-generation yield tables, combining empirical data and simulations for Northwest Germany. Above- and belowground biomass was calculated, converted into CO₂, and compared with estimates from traditional expansion factors. An interactive R Shiny dashboard was designed to visualise results. Results: The main results of this article are the carbon yield tables, covering beech (Fagus sylvatica), oak (Quercus spp.), spruce (Picea abies), pine (Pinus sylvestris) and Douglas fir (Pseudotsuga menziesii), each across various yield classes and starting at age 1, thereby also encompassing the juvenile phase of forest stands. Our comparison with estimates from traditional expansion factors shows that the latter can substantially overestimate carbon content in forest stands compared to our results, ranging from 20% to 35%, with higher estimates for mature stands and improved representation of early growth. The interactive dashboard also allows readers to experiment with their own figures. Conclusions: The choice of CO₂ methodology profoundly affects results. Our yield tables and a calculation tool (dashboard) deliver a transparent, accessible tool for quantifying forest CO₂ stock, supporting sustainable management and carbon market participation. Full article

Frequent channel migrations of the Yellow River, coupled with increasing human disturbances, have driven significant land cover changes in the Yellow River Delta (YRD) over time. Accurate estimation of aboveground biomass (AGB) and clarification of the impact of land cover changes on AGB are crucial for monitoring vegetation dynamics and supporting ecological management. However, field-based biomass samples are often time-consuming and labor-intensive, and the quantity and quality of such samples greatly affect the accuracy of AGB estimation. This study developed a robust AGB estimation framework for the YRD by synthesizing 4717 field-measured samples from the published scientific literature and integrating two critical ecological indicators: leaf area index (LAI) and length of growing season (LGS). A random forest (RF) model was employed to estimate AGB for the YRD from 2001 to 2022, achieving high accuracy (R² = 0.74). The results revealed a continuous spatial expansion of AGB over the past two decades, with higher biomass consistently observed in western cropland and along the Yellow River, whereas lower biomass levels were concentrated in areas south of the Yellow River. AGB followed a fluctuating upward trend, reaching a minimum of 204.07 g/m² in 2007, peaking at 230.79 g/m² in 2016, and stabilizing thereafter. Spatially, western areas showed positive trends, with an average annual increase of approximately 10 g/m², whereas central and coastal zones exhibited localized declines of around 5 g/m². Among the changes in land cover, cropland and wetland changes were the main contributors to AGB increases, accounting for 54.2% and 52.67%, respectively. In contrast, grassland change exhibited limited or even suppressive effects, contributing −6.87% to the AGB change. Wetland showed the greatest volatility in the interaction between area change and biomass density change, which is the most uncertain factor in the dynamic change in AGB. Full article

The rapid expansion of photovoltaic installations in arid and semi-arid regions has altered regional water–heat regimes, triggering complex responses in vegetation recovery and soil processes. However, systematic assessments of ecological restoration under varying operational durations and microenvironmental interactions remain insufficient. Therefore, this study examines photovoltaic power stations operating for 1, 7, and 13 years within China’s temperate desert regions, alongside undeveloped control areas, to compare differences across four microenvironments: the front eave of photovoltaic panels (FP), underneath photovoltaic panels (UP), back eave of photovoltaic panels (BP), and interval between photovoltaic panels (IP). Combining analysis of variance, correlation analysis, variance partitioning analysis (VPA), and generalised additive models (GAMs), the study evaluates the coupling mechanisms between vegetation and soil. The results indicate that operational duration significantly enhances vegetation cover, biomass, and species diversity, with the 13 year operational zone demonstrating optimal restoration outcomes. Microenvironmental variations were pronounced, with vegetation and soil quality in the front eave zone surpassing other areas, while the inter-panel zone exhibited the weakest recovery. Key soil factors shifted with recovery stages: early-stage vegetation showed heightened sensitivity to soil water content (SWC), whereas later stages relied more heavily on soil organic matter (SOM) and nutrient supply. Variation Partial Analysis (VPA) revealed that soil factors in the 13 year operational zone accounted for 71.9% of the variation in vegetation cover. The operational lifespan of photovoltaic power stations, microenvironmental variations, and key soil factors collectively drive the restoration of thermophilic desert vegetation. This research reveals phased regulatory mechanisms during the restoration process, providing scientific grounds for optimising photovoltaic layouts and enhancing desert ecosystem stability. Full article

Teak (Tectona grandis L.f.) is a leading tropical plantation species valued for high-quality timber and carbon (C) storage. This study assessed stand growth across ages and sites, quantified biomass and C by tree component and stand, and developed DBH-based allometric equations for biomass and C estimation. Six stand ages (5, 6, 9, 11, 14, and 17 years) were assessed in three municipalities of Nayarit, Mexico. Dendrometric inventories in permanent plots and destructive sampling of 35 trees provided calibration data for leaves, branches, stem, and roots. C concentration was determined with an elemental analyzer, and nonlinear regression models were adjusted and validated. Stand biomass and C increased with age, peaking at ages 11–14 (>130 Mg ha⁻¹; >60 Mg C ha⁻¹), with lower values at age 17. San Blas and Rosamorada accumulated significantly more than Tuxpan, reflecting site quality. C concentration was stable across sites and ages, with stem and roots consistently ranging between 48% and 50%, and leaves and branches averaging 45%–46%. Allometric equations were most accurate for stem and total biomass/C (R² = 0.73–0.79), while foliage showed higher variability. On average, 60%–70% of biomass was allocated to the stem and 15%–20% to roots. Indicators were stable, with an aboveground-to-belowground ratio (A:B) ≈ 4.9 and a biomass expansion factor (BEF) ≈ 1.5. The current annual increment (CAI) presented two main peaks: ~20 Mg ha⁻¹ yr⁻¹ at ages 5–6 and ~11 Mg ha⁻¹ yr⁻¹ at ages 9–11, followed by a decline after age 14. Teak in western Mexico reaches peak productivity at ages 6–11, with belowground biomass essential for accurate C accounting. Full article

Grassland degradation poses a serious threat to ecosystem stability and the sustainable development of human societies. In this study, we propose a framework for grassland degradation risk assessments and early warning based on key ecological factors (KEFs) in Xilingol. The NDVI, NPP, and grass yield were selected as KEFs to represent vegetation coverage, ecosystem productivity, and actual biomass, respectively. By constructing a grassland degradation index (GDI) and integrating K-means clustering, the average curvature, and a gravity center shift analysis, we quantified the degradation risk levels and identified the threshold values for different grassland types. The results showed the following: (1) the grass yield was the most sensitive indicator of grassland degradation in Xilingol, with high-risk thresholds decreasing from 115.67 g·m⁻² in the temperate meadow steppes (TMSs) to 73.27 g·m⁻² in the temperate typical steppes (TTSs), and further to 32.30 g·m⁻² in the temperate desert steppes (TDSs); (2) the TDSs exhibited the highest curvature value (2.81 × 10⁻⁴) in the initial stage, indicating a higher likelihood of rapid early-stage degradation, whereas the TMSs and TTSs reached peak curvature in the latest stages; and (3) the TTSs had the largest proportion of high-risk areas (33.02%), with a northeast–southwest distribution and a probable westward expansion trend. This study provides a practical framework for grassland degradation risk assessments and early warning, offering valuable guidance for ecosystem management and sustainable land use. Full article

Improving the precision of forest vegetation carbon stock estimation is essential for scientifically evaluating its economic value and ecological benefits. This study aims to investigate the impact of different estimation methods on carbon stock and its economic value. Taking the forest vegetation of the Zixi Mountain Nature Reserve as the research object, the carbon stock of the arbor layer was estimated using four approaches: the variable biomass expansion factor method, the biomass expansion factor method, the volume conversion method, and the continuous function method of the biomass conversion factor. The carbon stocks of economic forests and shrublands were estimated using the average biomass method. The economic value of forest carbon storage was then evaluated through the market value method and the optimal pricing approach for forest carbon sinks. The results revealed no significant differences among the four estimation methods. The estimated arbor forest carbon stocks were 692,548.39 tC, 672,599.83 tC, 673,161.07 tC, and 400,369.17 tC, respectively, with an overall average of 609,669.62 tC. The biomass expansion factor method and the volume conversion method produce the most consistent results. The corresponding relative errors were 13.59%, 10.32%, 10.41%, and −34.33%, respectively. The continuous function method of the biomass conversion factor exhibited the greatest variability, mainly due to the influence of Pinus yunnanensis parameters. Among all methods, the biomass expansion factor method yielded the smallest relative error, making it the most suitable for estimating arbor carbon stocks in the study area. The total average economic value of forest carbon storage in the region was estimated at CNY 58.09 million. Among all forest types, Pinus yunnanensis contributed the highest carbon value, totaling CNY 50.48 million. In terms of economic value per unit area, Pinus armandii ranked first, with CNY 11,418.92 per hectare. Among different age groups of arbor forests, middle-aged stands had the highest carbon sequestration value, reaching CNY 36.87 million. Across all functional zones, the core zone showed the greatest economic value at CNY 29.34 million. Enhancing forest resource protection to maximize both carbon sink capacity and economic returns, as well as promoting forest carbon trading, can bring additional economic benefits to Southwest China while contributing to the achievement of the national “dual carbon” goals. Full article

Mangroves play a pivotal role in carbon sequestration. To investigate the characteristics and driving factors of carbon sequestration in planted mangrove forests, we focused on planted mangrove forests in Wenzhou City, Zhejiang Province, China. Through a statistical analysis of soil physicochemical properties and plant morphological characteristics, we assessed carbon stock distribution patterns and identified key influencing factors, providing scientific support for the northward expansion of mangroves. The results demonstrated significant differences in soil properties and plant morphological characteristics among different stands (p < 0.05). The mean soil carbon stock of restored planted mangroves was 78.75 Mg C/ha (mature stands: 87.84 Mg C/ha; middle-aged stands: 74.09 Mg C/ha; young stands: 74.31 Mg C/ha), while the average plant carbon stock was 12.28 Mg C/ha, indicating that soil is the primary contributor to carbon sequestration in mangroves. Compared to natural mangroves, the restored planted mangroves still exhibited a lower carbon sequestration capacity. The variations in carbon sequestration levels among the planted mangrove forests were mainly attributed to differences in tree species and age composition, hydrothermal conditions, and biomass carbon quantification methods. Key drivers of soil carbon sequestration included total phosphorus content, bulk density, and clay content. Carbon storage in restored planted mangroves depends on short-term soil carbon accumulation and long-term biomass carbon accumulation. Ultimately, we recommend optimal species selection and planting design, improved soil carbon storage mechanisms, and integrated conservation monitoring systems to enhance carbon sequestration in mangrove plantations. Full article

The distribution of forest aboveground biomass density (AGBD) is a key indicator of carbon stock and ecosystem health in the Eastern Himalayas, which represents a global biodiversity hotspot that sustains diverse forest types across an elevation gradient from lowland rainforests to alpine meadows and contributes to the livelihoods of more than 200 distinct indigenous communities. This study aimed to identify the key factors influencing forest AGBD across this region by analyzing the underlying biophysical and anthropogenic drivers through machine learning (random forest). We processed AGBD data from the Global Ecosystem Dynamics Investigation (GEDI) spaceborne LiDAR and applied filtering to retain 30,257 high-quality footprints across ten ecoregions. We then analyzed the relationship between AGBD and 17 climatic, topographic, soil, and anthropogenic variables using random forest regression models. The results revealed significant spatial variability in AGBD (149.6 ± 79.5 Mg ha⁻¹) across the region. State-wise, Sikkim recorded the highest mean AGBD (218 Mg ha⁻¹) and Manipur the lowest (102.8 Mg ha⁻¹). Within individual ecoregions, the Himalayan subtropical pine forests exhibited the highest mean AGBD (245.5 Mg ha⁻¹). Topographic factors, particularly elevation and latitude, were strong determinants of biomass distribution, with AGBD increasing up to elevations of 2000 m before declining. Protected areas (PAs) consistently showed higher AGBD than unprotected forests for all ecoregions, while proximity to urban and agricultural areas resulted in lower AGBD, pointing towards negative anthropogenic impacts. Our full model explained 41% of AGBD variance across the Eastern Himalayas, with better performance in individual ecoregions like the Northeast India-Myanmar pine forests (R² = 0.59). While limited by the absence of regionally explicit stand-level forest structure data (age, stand density, species composition), our results provide valuable evidence for conservation policy development, including expansion of PAs, compensating avoided deforestation and modifications in shifting cultivation. Future research should integrate field measurements with remote sensing and use high-resolution LiDAR with locally derived allometric models to enhance biomass estimation and GEDI data validation. Full article

Mungbean is grown as a summer crop in subtropical climates globally. The global demand for mungbean is increasing, and opportunities exist to expand production regions to more marginal environments, such as southern Australia, as an opportunistic summer crop to help meet the growing global demand. Mungbean has the potential to be an opportunistic summer crop when an appropriate sowing window coincides with sufficient soil water. This expansion from subtropical to temperate climates will pose challenges, including low temperatures, a longer day length and a low and variable water supply. To assess mungbean suitability to temperate, southern Australian summer rainfall patterns and soil water availability, we conducted field experiments applying a range of water treatments across four locations with contrasting rainfall patterns within the state of Victoria (in southern Australia) in 2020–2021 and 2021–2022. The water treatments were applied prior to sowing (60 mm), the vegetative stage (40 mm) and the reproductive stage (40 mm) in a factorial combination at each location. Two commercial cultivars, Celera II-AU and Jade-AU, were used. Water scarcity during flowering and the pod-filling stages were important factors constraining yield. Analysis of yield components showed that increasing water availability at critical growth stages, viz. the vegetative and reproductive stages, of mungbean was associated with increases in total biomass, HI and grain number in addition to increased water use and water use efficiency (WUE). Average WUEs ranged from 1.3 to 7.6 kg·ha⁻¹·mm⁻¹. The maximum potential WUE values were 6.4 and 5.1 kg·ha⁻¹·mm⁻¹ for Celera II-AU and Jade-AU across the sites, with the estimated soil evaporation values (x-intercept) of 83 and 74 mm, respectively. Nitrogen fixation was variable, with %Ndfa values ranging from 9.6 to 76.8%, and was significantly affected by soil water availability. This study emphasises the importance of water availability during the reproductive phase for mungbean yield. The high rainfall zones within Victoria have the potential to grow mungbean as an opportunistic summer crop. Full article

In the context of accelerating global climate change, the accurate quantification of forest carbon sequestration at the regional scale is of critical importance to estimate carbon budgets and formulate targeted ecological policies. This study systematically investigated the spatiotemporal dynamics and driving mechanisms of arbor forest carbon stocks between 2016 and 2020 in Yunnan Province, China. Based on the “One Map” forest resource inventory, the continuous biomass expansion factor (CBEF) method, standard deviational ellipse (SDE) analysis, and multiple linear regression (MLR) modeling, the results showed the following. (1) Arbor forest carbon stocks steadily increased from 832.13 Mt to 938.84 Mt, and carbon density increased from 41.92 to 42.32 t C·hm⁻². Carbon stocks displayed a dual high pattern in the northwest and southwest, with lower values in the central and eastern regions. (2) The spatial centroid of carbon stocks shifted 4.8 km eastward, driven primarily by afforestation efforts in central and eastern Yunnan. (3) The MLR results revealed that precipitation and economic development were significant positive drivers, whereas temperature, elevation, and anthropogenic disturbances were major limiting factors. A negative correlation to afforestation area indicated a diminished need for new plantations as forest quality and quantity improved. These results provided a theoretical foundation for spatially differentiated carbon sequestration strategies in Yunnan, providing key insights for reinforcing ecological security in Southwest China and enhancing national carbon neutrality objectives. Full article

Research was conducted in Gannan Prefecture, China, to better understand the characteristics of carbon emissions and sequestration in areas dominated by animal husbandry. The emission factor method was used to calculate and analyze changes in carbon emissions from 2009 to 2024. The region’s average annual carbon emissions from animal husbandry are 774,286 t C-eq (2,839,049 t CO₂eq), with enteric emissions from cattle being the biggest contributor. However, as the number of locally raised cattle and sheep has decreased, carbon emissions have gradually fallen at an average annual rate of −1.0%. The annual average total carbon sequestration of vegetation in the region is 6,861,535 t C-eq, and the carbon content in underground biomass is higher than that in aboveground biomass, making it the main contributor to grassland carbon sequestration. Carbon sequestration from grassland vegetation is greater than the carbon emissions from animal husbandry, which means that the entire production system is currently a carbon sink. Meanwhile, the analysis of land-use carbon sequestration found that the annual average total sequestration by forests and grasslands over the same time period was 752,327 t C-eq, and sequestration is increasing at an annual rate of 1.4%, primarily driven by the progressive expansion of forested areas. Although the regional carbon emissions from animal husbandry are lower than the carbon sequestration, developing a science-based animal husbandry plan aligned with regional ecological thresholds, continuing to implement grass–livestock balance management measures, and preventing livestock numbers from exceeding their ecological carrying capacity remain critical to promoting sustainable coordination between livestock economies and ecological conservation. Full article