Carbon Sink Research Articles

Geological Net Zero and the need for disaggregated accounting for carbon sinks

Geological Net Zero and the need for disaggregated accounting for carbon sinks

The key role of forest disturbance in reconciling estimates of the northern carbon sink

AbstractNorthern forests are an important carbon sink, but our understanding of the driving factors is limited due to discrepancies between dynamic global vegetation models (DGVMs) and atmospheric inversions. We show that DGVMs simulate a 50% lower sink (1.1 ± 0.5 PgC yr−1 over 2001–2021) across North America, Europe, Russia, and China compared to atmospheric inversions (2.2 ± 0.6 PgC yr−1). We explain why DGVMs underestimate the carbon sink by considering how they represent disturbance processes, specifically the overestimation of fire emissions, and the lack of robust forest demography resulting in lower forest regrowth rates than observed. We reconcile net sink estimates by using alternative disturbance-related fluxes. We estimate carbon uptake through forest regrowth by combining satellite-derived forest age and biomass maps. We calculate a regrowth flux of 1.1 ± 0.1 PgC yr−1, and combine this with satellite-derived estimates of fire emissions (0.4 ± 0.1 PgC yr−1), land-use change emissions from bookkeeping models (0.9 ± 0.2 PgC yr−1), and the DGVM-estimated sink from CO2 fertilisation, nitrogen deposition, and climate change (2.2 ± 0.9 PgC yr−1). The resulting ‘bottom-up’ net flux of 2.1 ± 0.9 PgC yr−1 agrees with atmospheric inversions. The reconciliation holds at regional scales, increasing confidence in our results.

Carbon Sequestration Potential of Rhizophora mucronata in Tongke-Tongke Mangrove Forest, Sinjai Regency, Indonesia

Mangroves play a crucial role in coastal ecosystems, offering significant ecological benefits and acting as important carbon sinks. This study focuses on the carbon sequestration potential of Rhizophora mucronata in the Tongke-Tongke mangrove forest, Sinjai Regency, Indonesia. By measuring the carbon content in leaves, roots, and sediments, the study found carbon content ranges from 0.09 to 0.11 tons/ha in leaves with a carbon absorption capacity ranging from 0.33–0.42 tonnes/ha and 0.44 to 0.72 tons/ha in roots with absorption capacity reaching 1.60–2.64 tonnes/ha, with sediment carbon content varying significantly ranges from 8.66–156.83 tons/ha with an absorption capacity of 31.79–575.55 tons/ha. The carbon content in mangrove stands reaches 109.23–180.87 tonnes/ha, with carbon uptake reaching 400.89–663.80 tonnes/ha. Results indicate that R. mucronata has a substantial carbon absorption capacity, underscoring the importance of these ecosystems in climate change mitigation. The findings aim to inform conservation strategies and potential carbon trading initiatives, contributing to global climate resilience.

A Multi Source Data-Based Method for Assessing Carbon Sequestration of Urban Parks from a Spatial–Temporal Perspective: A Case Study of Shanghai Century Park

As urbanization accelerates globally, urban areas have become major sources of greenhouse gas emissions. In this context, urban parks are crucial as significant components of carbon sinks. Using Shanghai Century Park as a case study, this study aims to develop an applicable and reliable workflow to accurately assess the carbon sequestration capacity of urban parks from a spatial–temporal perspective. Firstly, the random forest model is employed for biotope classification and mapping in the park based on multi-source data, including raw spectral bands, vegetation indices, and texture features. Subsequently, the Net Primary Productivity and biomass of different biotope types are calculated, enabling dynamic monitoring of the park’s carbon sequestration capacity from 2018 to 2023. Moreover, the study explores the main factors influencing changes in carbon sequestration capacity from the management perspective. The findings reveal: (1) The application of multi-source imagery data enhances the accuracy of biotope mapping, with winter imagery proving more precise in classification. (2) From 2018 to 2023, Century Park’s carbon sequestration capacity showed a fluctuating upward trend, with significant variations in the carbon sequestration abilities of different biotope types within the park. (3) Renovation and construction work related to biotope types significantly impacted the park’s carbon sequestration capacity. Finally, the study proposes optimization strategies focused on species selection and layout, planting density, and park management.

Dynamics of CO2 fluxes and environmental responses in a Poplar plantation

Forest plantations cover a large percentage of global forest landscapes contributing significantly to carbon sequestration. By using continuous eddy covariance technique, we observed net ecosystem CO2 exchange (NEE), gross primary production (GPP), ecosystem respiration (ER), and meteorological variables from August 2018 to December 2019 in a Poplar plantation. The Poplar plantation ecosystem was a carbon sink overall, with high carbon uptake in growing season and limited uptake/emission in non-growing season. The annual cumulative NEE, GEP, and ER were −763.61, 1542.19, and 778.58 g C m−2 yr−1, respectively. Photosynthetically active radiation (PAR) significantly influenced NEE both at half-hourly and daily scale (P < 0.01 for both), while relative humidity (RH) and vapor pressure deficit (VPD) only significantly affected NEE at half-hourly scale (P < 0.01). The prevailing wind direction throughout 2019 was southeast and it varied between seasons. Southeast wind was the prevailing wind direction in summer and winter, while southwest and northeast wind were the dominant wind direction in spring and autumn, respectively. Our results highlight that polar plantations play an important role in storing carbon, and that understanding meteorological conditions is crucial in investigating ecosystem-atmosphere interactions and their impacts on carbon cycling.

Land-use competition in 1.5°C climate stabilization: is there enough land for all potential needs?

Achieving a low-carbon future requires a comprehensive approach that combines emission mitigation options from economic activities with the sustainable use of land for numerous needs: food production, energy production, carbon sequestration, nature preservation and broad ecosystem services. Using the MIT Integrated Global System (IGSM) framework we analyze land-use competition in a 1.5°C climate stabilization scenario, in which demand for bioenergy and natural sinks increase along with the need for sustainable farming and food production. We find that to address the numerous trade-offs, effective approaches to nature-based solutions (NBS) and agriculture practices are essential. With proper regulatory policies and radical changes in current practices, global land is sufficient to provide increased consumption of food per capita (without large diet changes) over the century while also utilizing 2.5–3.5 billion hectares (Gha) of land for NBS practices that provide a carbon sink of 3–6 gigatonnes (Gt) of CO2 per year as well as 0.4–0.6 Gha of land for energy production—0.2–0.3 Gha for 50–65 exajoules (EJ) per year of bioenergy and 0.2–0.35 Gha for 300–600 EJ/year of wind and solar power generation. We list the competing uses of land to reflect the trade-offs involved in land use decisions, and note that while there is sufficient land in our scenario, attaining this outcome, capable of delivering a 1.5°C future, requires effective policies and measures at national and global levels that promote efficient land use for food, energy and nature (including carbon sequestration) and ensure long-term commitments by decision makers from governments and industry in order to realize the benefits of climate change mitigation.

DRONES4BLUECARBONSEAGRASS: A Capacity-Building Program for Mapping Seagrasses using Unmanned Aerial System (UAS) Technology in the Philippines

Abstract. Coastal blue carbon ecosystems, such as mangrove forests and seagrass meadows, are important for various environmental functions, serving as habitats, food sources, and carbon sinks. Despite their importance, seagrass ecosystems are experiencing global decline due to numerous stressors, including anthropogenic activities. To address this, effective monitoring and management strategies are crucial. Traditional in situ surveys for seagrass monitoring are labor-intensive and time-consuming. Alternatively, remote sensing technologies, particularly satellite imagery, offer a more efficient means of mapping seagrass distribution over large areas. However, accurately assessing seagrass cover at a local scale remains challenging with satellite data alone. Recently, unmanned aerial system (UAS) technology has emerged as a promising approach for seagrass mapping. With its fine resolution and flexibility for image acquisition, UAS can provide more precise estimates of seagrass cover, complementing satellite data. This integration enhances accuracy assessments and expands data availability for training and validation purposes. Under the BlueCARES Project, a drone training program was developed to equip stakeholders with the skills needed for cost-effective UAS-based seagrass mapping. The drone training program encompasses lectures on UAS basics, flight planning, and image processing. Beyond training, collected data are used to create seagrass maps and assess seagrass density. This initiative not only advances seagrass conservation but also fosters collaboration between government agencies, academia, and local communities to achieve sustainable management of blue carbon ecosystems.

Carbon Footprint Accounting and Verification of Seven Major Urban Agglomerations in China Based on Dynamic Emission Factor Model

Amidst the prevailing trends in environmental conservation and the imperatives of energy conservation and emission reduction, the precision in assessing and forecasting carbon emissions has acquired heightened significance. The conventional emission factors, typically derived from historical data and empirical knowledge, often remain unchanged and fail to swiftly account for the reductions in emissions that are a consequence of technological advancements and green innovations. (1) This paper establishes a dynamic emission factor model, then uses city data and provincial data to verify the model, and compares the research results of other relevant researchers. The research results show that this method not only considers the different characteristics of energy types, but also considers regional differences and industry characteristics, making the emission factor more suitable for the actual situation. The results show that the method takes into account not only the different characteristics of energy types, but also regional differences and industry characteristics, making the emission factor more suitable for the actual situation. (2) This paper systematically compares the diverse methods for calculating the carbon footprints of Chinese provinces and cities. It encompasses a spectrum of methods, including carbon footprint accounting based on emission factors, accounting based on dynamically adjusted emission factors, and accounting from the perspective of carbon sinks. Each of these methods possesses its own set of applicable scenarios and inherent limitations. The emission factor method is apt for basic carbon emission accounting, while the adjusted emission factor method is tailored for scenarios where the evolution of technology and shifts in energy paradigms are pivotal. Concurrently, the carbon sink accounting framework is optimally suited for the evaluation of the carbon footprint within the realm of natural ecosystems.

Simulating Ips typographus L. outbreak dynamics and their influence on carbon balance estimates with ORCHIDEE r8627

Abstract. New (a)biotic conditions resulting from climate change are expected to change disturbance dynamics, such as windthrow, forest fires, droughts, and insect outbreaks, and their interactions. These unprecedented natural disturbance dynamics might alter the capability of forest ecosystems to buffer atmospheric CO2 increases, potentially leading forests to transform from sinks into sources of CO2. This study aims to enhance the ORCHIDEE land surface model to study the impacts of climate change on the dynamics of the bark beetle, Ips typographus, and subsequent effects on forest functioning. The Ips typographus outbreak model is inspired by previous work from Temperli et al. (2013) for the LandClim landscape model. The new implementation of this model in ORCHIDEE r8627 accounts for key differences between ORCHIDEE and LandClim: (1) the coarser spatial resolution of ORCHIDEE; (2) the higher temporal resolution of ORCHIDEE; and (3) the pre-existing process representation of windthrow, drought, and forest structure in ORCHIDEE. Simulation experiments demonstrated the capability of ORCHIDEE to simulate a variety of post-disturbance forest dynamics observed in empirical studies. Through an array of simulation experiments across various climatic conditions and windthrow intensities, the model was tested for its sensitivity to climate, initial disturbance, and selected parameter values. The results of these tests indicated that with a single set of parameters, ORCHIDEE outputs spanned the range of observed dynamics. Additional tests highlighted the substantial impact of incorporating Ips typographus outbreaks on carbon dynamics. Notably, the study revealed that modeling abrupt mortality events as opposed to a continuous mortality framework provides new insights into the short-term carbon sequestration potential of forests under disturbance regimes by showing that the continuous mortality framework tends to overestimate the carbon sink capacity of forests in the 20- to 50-year range in ecosystems under high disturbance pressure compared to scenarios with abrupt mortality events. This model enhancement underscores the critical need to include disturbance dynamics in land surface models to refine predictions of forest carbon dynamics in a changing climate.

Analysis of spatial and temporal characteristics and evolution of green total factor productivity in agriculture in the lower Yellow River basin

The construction of ecological barriers in the Yellow River Basin represents a significant step toward reducing agricultural carbon emissions, achieving carbon neutrality, and reaching carbon peaking in China. The diverse agrarian development objectives of various regions within the basin have resulted in a heterogeneous approach to greening agriculture. Therefore, this paper will evaluate the development of carbon sink agriculture across 34 cities and municipalities in the lower Yellow River basin from 2008 to 2021 based on the EBM-GML model, and analyze the spatial-temporal evolution of agricultural green total factor productivity (AGTFP) in each region through the application of the Moran index, kernel density estimation, and spatial Markov chain analysis. The results demonstrate that agricultural carbon emissions in the Lower Yellow River Basin gradually decreased throughout the study period. Furthermore, overall carbon emission efficiency improved, indicating significant potential for further emission reduction. In addition, Agricultural Green Technology Progress (AGTC) has become a primary driver of AGTFP growth, while Agricultural Green Technology Efficiency (AGEC) has demonstrated a gradual upward trend. Locally, most areas are weakly connected and display an isolated development trend. The results of the kernel density analysis demonstrate a notable degree of mobility in the distributional dynamics of AGTFP growth, characterized by a gradual narrowing of the gap between locations. The transfer of (AGTFP) types in the lower reaches of the Yellow River Basin is stable, with a noticeable “club convergence” phenomenon, while geographical conditions significantly influence the transfer of AGTFP types in this region. Based on long-term trend predictions, the future trajectory of AGTFP in the lower Yellow River Basin appears optimistic and is expected to improve progressively, with the overall distribution tending toward equilibrium.

Internal physiological drivers of leaf development in trees: Understanding the relationship between non‐structural carbohydrates and leaf phenology

Abstract Plant phenology is crucial for understanding plant growth and climate feedback. It affects canopy structure, surface albedo, and carbon and water fluxes. While the influence of environmental factors on phenology is well‐documented, the role of plant intrinsic factors, particularly internal physiological processes and their interaction with external conditions, has received less attention. Non‐structural carbohydrates (NSC), which include sugars and starch essential for growth, metabolism and osmotic regulation, serve as indicators of carbon availability in plants. NSC levels reflect the carbon balance between photosynthesis (source activity) and the demands of growth and respiration (sink activity), making them key physiological traits that potentially influence phenology during critical periods such as spring leaf‐out and autumn leaf senescence. However, the connections between NSC concentrations in various organs and phenological events are poorly understood. This review synthesizes current research on the relationship between leaf phenology and NSC dynamics. We qualitatively delineate seasonal NSC variations in deciduous and evergreen trees and propose testable hypotheses about how NSC may interact with phenological stages such as bud break and leaf senescence. We also discuss how seasonal variations in NSC levels, align with existing conceptual models of carbon allocation. Accurate characterization and simulation of NSC dynamics are crucial and should be incorporated into carbon allocation models. By comparing and reviewing the development of carbon allocation models, we highlight the shortcomings in current methodologies and recommend directions to address these gaps in future research. Understanding the relationship between NSC, source–sink relationships, and leaf phenology poses challenges due to the difficulty of characterizing NSC dynamics with high temporal resolution. We advocate for a multi‐scale approach that combines various methods, which include deepening our mechanistic understanding through manipulative experiments, integrating carbon sink and source data from multiple observational networks with carbon allocation models to better characterize the NSC dynamics, and quantifying the spatial pattern and temporal trends of the NSC‐phenology relationship using remote sensing and modelling. This will enhance our comprehension of how NSC dynamics impact leaf phenology across different scales and environments. Read the free Plain Language Summary for this article on the Journal blog.

CO2 Footprint of Kiwi Fruits Deduced from Field Measurements and Cultivation Energy Data

The unequivocal understanding of the planetary-global climate change has rendered the apportionment of sources and sinks of greenhouse gases in the terrestrial domain, an urgent priority. In the present study, the micrometeorological method of “dynamic gradient fluxes” coupled with the Monin–Obukhov similarity theory, was utilised for the determination of net ecosystem exchange of carbon dioxide (CO2) from a kiwi plantation. This annual net exchange, in conjunction with the energy and fertiliser equivalent CO2 used, established the CO2 footprint of the produce. For the year 2023, the CO2 Net Ecosystem Exchange (NEE) is −16.20 tonnes per hectare per year (CO2 uptake by the plantation). The cultivation processes used throughout the year consumed +2.96 tonnes per hectare per year, and after deduction of this value from the NEE, the result is in a net CO2 sink for the kiwi plantation of −13.24 tonnes per hectare per year. It is hence obvious that, under these conditions, the kiwi plantations in Greece can be net CO2 sinks. This result is of increasing importance since the country is the fourth largest producer of kiwi globally, with production increasing in later years.

Analysis of the Wangping Brownfield Using a Two-Step Urban Brownfield Redevelopment Model

With societal progress, urban brownfields have become restrictive, and redevelopment studies have become an important part of urban renewal. In this work, we developed a two-step model for urban brownfield redevelopment, while considering the Wangping brownfield as the study area. Site suitability evaluation models for brownfield parks, agricultural picking gardens, and creative industrial centers were developed based on the elevation, slope, and surface runoff, and the evaluation results were categorized into five levels. The redevelopment plan was formulated based on these evaluation results. To study the effect of the plan, a transition matrix of land use was assessed using satellite images and the cellular automata (CA)–Markov model; based on the analysis, we predicted the land use situation of the Wangping brownfield, with respect to natural development, for 2030. A comparison of the redevelopment planning with the forecasted results revealed that the proportions of grassland, construction, and unused land decreased by 25.68, 3.12, and 2.38% and those of plowland and forest land increased by 6.61 and 24.57%. This confirms the advantages of redevelopment planning for restoring plowland and increasing biological carbon sinks. Notably, our two-step urban brownfield redevelopment model can enrich the current research on urban brownfields and guide similar urban renewal projects.

Mapping the Sustainability of Waste-to-Energy Processes for Food Loss and Waste in Mexico—Part 2: Environmental and Economic Analysis

Mexico generated 8.9 million tons of food loss and waste (FLW) in the year 2022, which was primarily managed through linear economy schemes where final disposal sites are predominant, leading to significant contributions to climate change and economic losses. This study, as a continuation of a prior work (Part 1), aims to evaluate the economic and environmental feasibility of implementing waste-to-energy anaerobic digestion (WtE-AD) plants for FLW management across Mexico, identifying the key factors that influence the competitiveness of these systems compared to conventional waste management practices. Using the outcomes of an energy feasibility analysis (Part 1), alongside life cycle assessment (LCA), geographic information systems, and cost engineering, this research analyzes the eco-efficiency and viability of WtE-AD for FLW valorization throughout the Mexican territory. The results indicate that, with a conventional waste management fee of USD 35.4 t−1, only the largest WtE-AD plant in the State of Mexico (treatment capacity of 2536.8 t FLW d−1) achieved a positive net present value (NPV) of USD 70.1 million, while all the other plants remained economically unviable. Conversely, under an optimistic scenario with a fee of USD 139 t−1, plants processing over 50 t FLW d−1 achieved profitability, with the largest plant reaching an NPV of USD 1.15 billion. The environmental assessment showed that larger plants effectively act as carbon sinks, with the largest plant reducing emissions by up to −89.8 kg CO₂ eq t−1 of FLW. These findings emphasize the need for appropriate waste management fees and governmental incentives to ensure the economic viability of WtE-AD plants. This study provides valuable insights for policymakers, highlighting the potential of WtE-AD technologies to contribute to Mexico’s energy transition and the shift toward a circular economy.

Assessment and Dynamic Prediction of Green Space Ecological Service Value in Guangzhou City, China

As an important part of the urban ecosystem, urban green space provides a variety of ecosystem services, including climate regulation, soil conservation, carbon sink and oxygen release, and biodiversity protection. However, existing remote sensing evaluation methods for ecological service value lack the evaluation indicators of ecosystem service value for Guangzhou, China, and the evaluation method depends on the land cover type. Based on remote sensing technology and random forest algorithm, this study addresses these gaps by integrating remote sensing technology with a random forest algorithm to enhance the accuracy and rationality of ESV assessments. Focusing on Guangzhou, China, we improved the ecological service value evaluation system and conducted dynamic predictions based on land-use change scenarios. Our results indicate that the total ESV of Guangzhou’s green space was USD 7.323 billion in 2020, with a projected decline to USD 6.496 billion by 2030, representing a 12.37% reduction due to urbanization-driven land-use changes. This research highlights the noticeable role of green spaces in urban sustainability and provides robust, data-driven insights for policymakers to design more effective green space protection and management strategies. The improved assessment framework offers a novel approach for accurately quantifying urban ecosystem services and predicting future trends.

Beyond MRV: Combining remote sensing and ecosystem modeling for geospatial monitoring and attribution of forest carbon fluxes over Maryland, USA

Abstract Members of the U.S. Climate Alliance, a coalition of 24 states committed to achieving the emissions reductions outlined in the 2015 Paris Agreement, are considering policy options for inclusion of forest carbon in climate mitigation plans. These initiatives are generally limited by a lack of relevant data on forest carbon stocks and fluxes past-to-future. Previously, we developed a new forest carbon modeling system that combines high-resolution remote sensing, field data, and ecological modeling to estimate contemporary above-ground forest carbon stocks, and projected future forest carbon sequestration potential for the state of Maryland. Here we extended this work to provide a consistent geospatial approach for monitoring changes in forest carbon stocks over time. Utilizing the same data and modeling system developed previously for planning, we integrated historical input data on weather and disturbance to reconstruct the history of vegetation dynamics and forest above-ground carbon stocks annually over the period 1984-2016 at 30 m resolution and provided an extension to 2023. Statewide, forested land had an average annual net above ground carbon sink of 1.37 TgC yr-1, comparable to prior estimates. However, unlike the prior estimates, there was considerable variation around this mean. The statewide net above ground flux ranged interannually from -0.65 - 2.77 Tg C yr-1. At the county scale, the average annual net above ground flux ranged spatially from 0.01 - 0.13 Tg C yr-1 and spatiotemporally from -0.43 - 0.24 Tg C yr -1. Attribution analyses indicate the primary importance of persistent and regrowing forests, vegetation structure, local disturbance, and rising CO2 to the mean flux, and the primary importance of weather to the large-scale interannual variability. These results have important implications for state climate mitigation planning, reporting and assessment. With this approach, it is now possible to monitor changes in forest carbon stocks spatiotemporally over policy relevant domains with a consistent framework that is also enabled for future planning.

Construction and Application of an Evaluation System for Ocean Carbon Sink Trading

Construction and Application of an Evaluation System for Ocean Carbon Sink Trading

Great ape abundance and per capita carbon storage in their habitats

The ecological importance of great apes is widely recognised, yet few studies have highlighted the role of protecting great apes’ habitats in mitigating climate change, particularly through carbon sequestration. This study used GIS tools to extract data from various sources, including the International Union for Conservation of Nature database, to examine carbon quantity and great ape abundance in African great ape habitats. Subsequently, we employed a generalised linear model to assess the relationship between locally measured great ape populations abundance and carbon storage across areas with different levels of protection. Our findings showed a positive relationship between the abundance of great apes in their habitats and carbon storage, likely since conservation efforts in great apes habitats may be strengthened with higher great ape populations. The results reveal that gorilla habitats exhibited higher carbon storage than chimpanzee habitats. Specifically, the areas inhabited by gorillas are associated with a mean increase of 27.47 t/ha in carbon storage. Additionally, we observed a positive association between highly protected areas and carbon storage within great ape habitats. Our model indicates that highly protected areas increase the mean carbon stored by 1.13 t/ha compared to medium protected areas, which show a reduction of 15.49 t/ha. This highlights the critical role that protected areas play in both species conservation and carbon sequestration, contributing significantly to climate mitigation efforts. Furthermore, our study underscores the significant contribution of great ape habitats, extending beyond protected areas, to carbon storage, highlighting the potential for synergistic conservation strategies targeting both great apes and carbon sequestration. Protecting great apes is vital for reducing carbon emissions from deforestation and boosting tropical forest carbon sinks. Since nearly 90% of great apes live outside protected areas, targeted conservation in these low-protected areas is also crucial.

Simulated sensitivity of the Amazon rainforest to extreme drought

Abstract The Amazon rainforest is highly biodiverse and the largest intact, tropical forest in the world. Undisturbed tropical forests act as a carbon sink by taking up about 15% of anthropogenic carbon emissions per year. In the past decades, a declining trend in the carbon sink capacity in the Amazon rainforest has been observed due to increased carbon losses and tree mortality. The causes are disputed, but increasing temperatures and more frequent severe droughts are potentially major drivers. We employ a novel modelling framework and hypothesize that previously rare, extreme droughts in the Amazon, such as the ones in 2005 and 2010, constitute the main cause behind the decline of the net carbon sink in aboveground biomass. Our dynamic vegetation model simulates process-based plant hydraulics and drought-induced mortality, and accounts for the diversity of strategies in plant responses to drought based on observed hydraulic vulnerability curves. The simulated impact of the 2005 drought event temporarily turned the annual Amazon net carbon sink to a carbon source of about 0.25 MgC ha-1. In contrast to other dynamic vegetation models our model simulated an increasing trend in carbon losses and a declining trend in the Amazon carbon sink over the past 25 years (net sink rate of -0.018 Mg C ha-1 year-1 or -0.22 Mg C ha-1 per decade) which corresponds well with long-term forest monitoring data (net sink rate of -0.016 Mg C ha-1 year-1). We show that this trend is entirely attributable to drought-induced forest mortality during extreme years. The simulations show a threshold-like behaviour between drought intensity and biomass loss, which is due to xylem vulnerability, indicating the potentially high sensitivity of Amazon forests to extreme drought. Further increases in the severity and frequency of droughts might thus lead to greater carbon release and tree mortality than previously assumed.

Characteristics of Carbon Fluxes and Their Environmental Control in Chenhu Wetland, China

Carbon dioxide (CO2) flux measurements were conducted throughout the year 2022 utilizing the eddy covariance technique in this study to investigate the characteristics of carbon fluxes and their influencing factors in the Chenhu wetland, a representative subtropical lake-marsh wetland located in the middle reaches of the Yangtze River in China. The results revealed that the mean daily variation of CO2 flux during the growing season exhibited a U-shaped pattern, with measurements ranging from −12.42 to 4.28 μmolCO2·m−2·s−1. The Chenhu wetland ecosystem functions as a carbon sink throughout the growing season, subsequently transitioning to a carbon source during the non-growing season, as evidenced by observations made in 2022. The annual CO2 absorption was quantified at 21.20 molCO2·m−2, a figure that is lower than those documented for specific subtropical lake wetlands, such as Dongting Lake and Poyang Lake. However, this measurement aligns closely with the average net ecosystem exchange (NEE) reported for wetlands across Asia. The correlation between daytime CO2 flux and photosynthetically active radiation (PAR) can be accurately represented through rectangular hyperbola equations throughout the growing season. Vapor pressure deficit (VPD) acts as a constraining factor for daytime NEE, with an optimal range established between 0.5 and 1.5 kPa. Furthermore, air temperature (Ta), relative humidity (RH), and vapor pressure difference (VPD) are recognized as the principal determinants affecting NEE during the nocturnal period. The association between Ta and NEE during the non-growing season conforms to the van’t Hoff model, suggesting that NEE increases in response to elevated Ta during this timeframe.