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The carbon budget concept states that the global mean temperature (GMT) increase is roughly linearly dependent on cumulative emissions of CO 2. The proportionality is measured as the transient climate response to cumulative emissions of carbon dioxide (TCRE). In this paper, the deviations of the carbon budget from the strict linear relationship implied by the TCRE are examined through the lens of a temperature response to an emission pulse (i.e., pulse response) and its relationship with a nonlinear TCRE. Hereby, two sources of deviation are distinguished: emission scenario and climate state dependence. The former stems from the scenario choice, i.e., the specific emission pathway for a given level of cumulative emissions and the latter from the change in TCRE with changing climatic conditions. Previous literature argues for scenario independence using a stylized set of emission scenarios, and offers a way to fit a nonlinear carbon budget equation. This paper shows how the pulse response, viewed as a Green's function, gives a unifying perspective on both scenario and state dependence. Moreover, it provides an optimization program that tests the scenario independence under the full range of emission pathways for a given set of constraints. In a setup chosen in this paper, the deviations stemming from emission pathway choices are less than 10 % of the overall temperature increase and gradually diminish. Moreover, using the pulse response as a Green's function, the scenario-dependent effects of a reduced-complexity climate model were replicated to a high degree, confirming that the behavior of scenario-dependent deviations can be explained and predicted by the shape of the pulse response. Additionally, it is shown that the pulse response changes with climatic conditions, through which the carbon budget state dependency is explained. Using a pulse response as an approximation for a state-dependent TCRE, an alternative method to derive a nonlinear carbon budget equation is provided. Finally, it is shown how different calibrations of a model can lead to different degrees of carbon budget nonlinearities. The analysis is done using FaIRv2.0.0, a simple climate emulator model that includes climate feedback modifying the carbon cycle, along with a one-box model used for comparison purposes. The Green's function approach can be used to diagnose both models' carbon budget scenario dependency, paving the way for future investigations and applications with other and more complex models. [ABSTRACT FROM AUTHOR]

Blue Carbon is increasingly popular worldwide, and it also belongs to circular economy field which would last a long period in academy. To further understand the development and characteristics of Blue Carbon, this study uses CiteSpace software to perform quantitative analysis on literature published on Web of Science and Chinese CNKI database with the main topic of "Blue Carbon." The results show that: (1) Since 2009, increasing attention has been paid to Blue Carbon research, among which the United States, Australia and China are the leading countries. (2) Keywords such as "Blue Carbon," "mangrove," "carbon sequestration" and "carbon neutrality" are the high-frequency keywords appearing both in China and the World in recent years. (3) Spartina alterniflora, soil organic carbon, livestock, trophic cascade, biodiversity and seagrass ecosystem clustering are hot topics related to international Blue Carbon research, while organic carbon, seagrass-conservation, methodology, sustainable development, climate change, carbon neutralization, coastal zone and carbon storage are hot topics related to Chinese Blue Carbon research. In addition, based on the research trends of Blue Carbon, this paper attempts to sort out the research framework from three levels: core characteristics, theoretical basis and research methods, respectively. Facing a series of challenges brought by climate change, Blue Carbon research should strengthen the accurate estimations of Blue Carbon sink and its market potential, and explore the reasonable market mechanism and protection mechanism, to respond to realistic demands, solve major concerns and promote new progress in Blue Carbon theory and practice. [ABSTRACT FROM AUTHOR]

The land-use, land-use change and forestry (LULUCF) sector is receiving increasing attention in climate change mitigation and greenhouse gas (GHG) emission offsetting. The sector itself and measures applied to mobilize this sector in order to tackle climate change are dominant in nationally determined contributions under the Paris Agreement as well as in national strategies, as in the case of Lithuania. Lithuania has set the goal of becoming a carbon-neutral country in 2050, reducing GHGs by 80% compared to 1990 and offsetting the remaining 20% through the LULUCF sector. Therefore, this paper aims at analyzing historical land-use changes in 1990–2021, as reported for the United Nations Framework Convention on Climate Change (UNFCCC) secretariat, and LULUCF's potential to achieve climate change mitigation goals, taking into account different land-use change scenarios (business as usual, forest development, forest development + additional measures and forest land 40% + additional measures) for 2030 and 2050 in Lithuania. The scenarios are based on historical and potential future policy-based land-use changes. Projections of GHG emissions/removals for different scenarios are prepared according to the Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories (2006) by the Intergovernmental Panel on Climate Change (IPCC). The results indicate that land-use changes over the period 1990–2021 remained rather stable, with some increases in forest area and grassland at the expense of cropland. The whole LULUCF sector acted as a carbon sink in most cases, forests being a key category for removal. However, reaching climate neutrality in 2050 might be challenging, as the goal to offset 20% of remaining GHG emission compared to 1990 through LULUCF would not be met in any of the scenarios analyzed, even the scenario of maximal forest-area development and additional measures. Considering the high historical GHG-removal fluctuations and the uncertainties of the sector itself, caution should be taken when relying on LULUCF's potential to reach the set goals. [ABSTRACT FROM AUTHOR]

The "Dual Carbon" initiative is a two-stage carbon reduction goal proposed by China, with significant implications for global climate change mitigation. This article examines the impact of the "Dual Carbon" strategy on China's forestry development and explores how to leverage this strategy to facilitate the transformation and advancement of the forestry sector. Current review indicated that forestry has the advantage of achieving higher emission reduction targets at a low cost. Starting with an overview of the "Dual Carbon" strategy, this paper analyzes the carbon sequestration potential of plants and soil, and the challenges and opportunities faced by forestry development under this framework. Furthermore, we outline implementation pathways for forestry development, aiming to provide insights for the progress of China's forestry sector. Overall, it should be noted that the priority is to vigorously develop timber resources, and we also need to vigorously develop and protect forestry talent with the support of China's policies. By trapping into the carbon storage capabilities and leveraging carbon trading mechanisms of forests, a favorable ecological environment can be created, thus achieving the goal of carbon neutrality. Highlights: • Forest development and its carbon sinks, attributed to plant and soil have the potential in carbon sequestration process, thus helping China achieve carbon neutrality. • The supply of forest products and the balance of economic growth and environmental protection are the key difficulties under the "Dual Carbon" strategy. • Trading forest carbon sinks can boost China's sequestration. [ABSTRACT FROM AUTHOR]

Land cover and its changes over time are significant for better understanding the Earth's fundamental characteristics and processes, such as global climate change, hydrology, and the carbon cycle. A number of land cover-geoprocessing models have been proposed for land cover-data production with different spatial and temporal resolutions. With the massive growth in land cover data and the increasing demand for efficient model utilization, developing efficient and convenient land cover-geoprocessing models has become a formidable challenge. Although some model-migration methods have been proposed for handling the massive data, the intricacy of land cover-data and -heterogeneity models frequently prevent current strategies from directly meeting demand. In this paper, we propose the PAMC-LC-containerization approach to overcome the difficulties associated with moving existing land cover models in the open web environment. Based on the idea of model migration, we design a standardized model description and hierarchical encapsulation strategy for land cover models, and develop migration and deployment methods. Furthermore, we assess the viability and efficacy of the proposed approach by using coupled workflows for model migration and the introduction of visualization on the Mts-WH dataset and the Google dataset. The experimental results show that the PAMC-LC approach can simplify and streamline the model migration process, with important ramifications for increasing productivity, reusing models, and lowering additional data-transmission costs. [ABSTRACT FROM AUTHOR]

Simple Summary: In this paper, the differences in carbon sequestration microbial communities in different wetland types and their main influencing factors were investigated. It was found that the alpha diversity of cbbM carbon-sequestering microorganisms was consistent with the change trend in the total carbon content. Acidithiobacillus was used as a biomarker in lakeside wetlands, and Thiothrix and Thiodictyon were used as biomarkers in marsh wetlands. The diversity of cbbM carbon-fixing microorganisms was primarily influenced by the total nitrogen content, while the community structure was significantly affected by the soil total carbon content. The increase in soil temperature and humidity was conducive to the carbon-sequestering process of Thiomicrospira, Thiomonas, Polaromonas and Acidithiobacillus. The changes in wetland types seriously affected the characteristics of cbbM carbon sequestration in microbial communities, and a warm and humid climate may be conducive to wetland carbon sequestration. Carbon-sequestering microorganisms play an important role in the carbon cycle of wetland ecosystems. However, the response mechanism of carbon-sequestering microbial communities to wetland type changes and their relationship with soil carbon remain unclear. To explore these differences and identify the main influencing factors, this study selected marsh wetlands, river wetlands and lakeside wetlands around Qinghai Lake as research subjects. High-throughput sequencing was employed to analyze the functional gene cbbM of carbon-sequestering microorganisms. The results revealed that the alpha diversity of cbbM carbon-sequestering microorganisms mirrored the trend in total carbon content, with the highest diversity observed in marsh wetlands and the lowest in lakeside wetlands. The dominant bacterial phylum was Proteobacteria, with prevalent genera including Thiothrix, Acidithiobacillus, and Thiodictyon. Acidithiobacillus served as a biomarker in lakeside wetlands, while two other genera were indicative of marsh wetlands. The hierarchical partitioning analysis indicated that the diversity of cbbM carbon-fixing microorganisms was primarily influenced by the total nitrogen content, while the community structure was significantly affected by the soil total carbon content. Moreover, an increased soil temperature and humidity were found to favor the carbon fixation processes of Thiomicrospira, Thiomonas, Polaromonas, and Acidithiobacillus. In summary, changes in wetland types seriously affected the characteristics of cbbM carbon sequestration in microbial communities, and a warm and humid climate may be conducive to wetland carbon sequestration. [ABSTRACT FROM AUTHOR]

Peatlands are major natural carbon pool in terrestrial ecosystems globally and are essential to a variety of fields, including global ecology, hydrology, and ecosystem services. Under the context of climate change, the management and conservation of peatlands has become a topic of international concern. Nevertheless, few studies have yet systematized the overall international dynamics of existing peatland research. In this study, based on an approach integrating bibliometrics and a literature review, we systematically analyzed peatland research from a literature perspective. Alongside traditional bibliometric analyses (e.g., number of publications, research impact, and hot areas), recent top keywords in peatland research were found, including 'oil palm', 'tropical peatland', 'permafrost', and so on. Furthermore, six hot topics of peatland research were identified: (1) peatland development and the impacts and degradations, (2) the history of peatland development and factors of formation, (3) chemical element contaminants in peatlands, (4) tropical peatlands, (5) peat adsorption and its humic acids, and (6) the influence of peatland conservation on the ecosystem. In addition, this review found that the adverse consequences of peatland degradation in the context of climate change merit greater attention, that peatland-mapping techniques suitable for all regions are lacking, that a unified global assessment of carbon stocks in peatlands urgently needs to be established, spanning all countries, and that a reliable system for assessing peatland-ecosystem services needs to be implemented expeditiously. In this study, we argued that enhanced integration in research will bridge knowledge gaps and facilitate the systematic synthesis of peatlands as complex systems, which is an imperative need. [ABSTRACT FROM AUTHOR]

Wetlands provide numerous ecological and economic services to mankind. The soils of wetlands are one of the largest sinks of carbon (C) among the terrestrial ecosystems and can play an important role in offsetting the emission of C as a greenhouse gas (GHG) to the atmosphere. India is bestowed with enriched wetland ecosystems that support diverse and unique habitats. The potential of the wetlands in terms of C capture and sequestration has not been quantified. Therefore, in the present paper, an assessment of C capture from different sources and its ultimate deposition in soils leading to sequestration has been done in three different types of wetlands, one created sewage-fed and two natural floodplain oxbow lakes, in the West Bengal state of India. Multiple seasonal sampling of water, macrophytes, and soil was done to assess the primary productivity, dissolved C, and deposition of C in soils of the wetlands in comparison to reference upland sites. All these wetlands are productive ecosystems as indicated by the physicochemical parameters of water and soil. The quantity of C accumulated up to 0.3 m depth in the oxbow lakes was to the tune of 144–166 Mg/ha, which was 3.43–4.78 times higher than that in the corresponding reference upland sites. In the sewage-fed wetland, the C accumulation estimated as 50 Mg/ha was 1.27 times higher than its corresponding upland site. So, the wetland ecosystems, particularly the floodplains, are highly efficient in accumulating C in their soils and thus can somewhat negate the GHG emission. [ABSTRACT FROM AUTHOR]

The soil respiration (Rs) of forests is a major component of global Rs, yet few studies have focused on it. This study aimed to estimate global forest Rs and its changes at a resolution of 30 m via an artificial neural network (ANN) model. Five input candidates representing forest type, climatic, soil, and geographical information, as well as 1472 satisfactory forest Rs records, were used to build the ANN model and evaluate the model performance via a 10‐fold cross‐validation scheme. Global forest change data sets were used to accurately define the extent of forests and their changes, which was achievable because of the dynamic information and high resolution (30 m) of the data sets. The results indicate that the average annual global forest Rs from 2000 to 2020, as estimated by the optimal ANN model with an r2 value of 0.67 and a root‐mean‐square error of 252.6 g C m−2 yr−1, was 46.24 ± 5.86 Pg C yr−1. From 2001 to 2019, the average theoretical annual global forest Rs loss was 0.22 ± 0.06 Pg C yr−1 due to an average forest loss area of 23.4 million ha yr−1. In addition, the annual Rs theoretically increased by 0.75 Pg C in 2012 due to a global forest gain area of 80.5 million from 2001 to 2012. The presented data sets of global forest Rs and its changes can provide an accurate benchmark for discussing the carbon cycle and climate change at global to regional scales, even when operating over a small forest area (i.e., dozens of ha), which is a scale that has been ignored in other global Rs studies. Plain Language Summary: This paper discusses the soil respiration (written as Rs) of global forests, which has rarely been the focus of other Rs studies. Soil respiration is defined as the amount of Carbon Dioxide released from the soil surface into the atmosphere. The goal of this study was to estimate global forest Rs and its changes at a resolution of 30 m using the artificial intelligence model. The model had five input candidates representing forest type, climatic, soil, and geographical information. Additionally, 1472 satisfactory forest Rs records were used to build the model and evaluate its performance via a cross‐validation scheme. Global forest change data sets have a high 30 m‐resolution and provide dynamic information, and were thus chosen to accurately define the extent of forests and their changes in this research. This results show that the estimated average annual global forest Rs from 2000 to 2020 was 46.24 ± 5.86 quadrillion gram of carbon. The data sets produced by this study is able to act as an accurate benchmark used to discuss the carbon cycle and climate change at global to regional scales, and they can even make it possible to operate over a smaller forest area, such as dozens of ha. Key Points: 30‐m resolution global data sets of forest soil respiration and its changes from 2000 to 2020 are providedThe average annual global forest soil respiration from 2000 to 2020 was 46.24 ± 5.86 Pg C yr−1An accurate benchmark is provided for discussing the carbon cycle and climate change at global to regional scales, even over a small forest area (i.e., dozens of ha) [ABSTRACT FROM AUTHOR]

Globally, forest ecosystems, especially subtropical forests, play a central role in biogeochemical cycles and climate regulation, demonstrating their irreplaceable function. The subtropical region of China, characterized by its unique forest ecosystem, complex terrain, climate heterogeneity, diverse vegetation types, and frequent human activities, underscores the importance of the in-depth study of its net primary productivity (NPP). This paper employs the eddy covariance–light use efficiency (EC-LUE) model to quantitatively estimate the gross primary productivity (GPP) of this region from 2001 to 2018, followed by an estimation of the actual net primary productivity (ANPP) using the carbon use efficiency (CUE). The results showed that over these 18 years, the annual average ANPP was 677.17 gC m−2 a−1, exhibiting an overall increasing trend, particularly in mountainous areas, reserves, and the cultivated lands of the northeastern plains, whereas a significant decrease was observed around the urban agglomerations on the southeast coast. Furthermore, the Thornthwaite memorial model was applied to calculate the potential net primary productivity (PNPP), and diverse scenarios were set to quantitatively evaluate the impact of climate change and human activities on the vegetation productivity in the study area. It was found that in areas where the ANPP increased, both human activities and climate change jointly influenced ANPP dynamics; in areas with a decreased ANPP, the impact of human activities was particularly significant. Additionally, the heterogeneous distribution of ANPP across different altitudinal gradients and the driving effects of various climatic factors were analyzed. Finally, a partial correlation analysis was used to examine the relationships between the temperature, precipitation, and ANPP. This study indicated that temperature and precipitation have a substantial impact on the growth and distribution of vegetation in the region, yet the extent of this influence shows considerable variation among different areas. This provides a robust scientific basis for further research and understanding of the carbon dynamics of subtropical forest ecosystems and their role in the global carbon cycle. [ABSTRACT FROM AUTHOR]

This document is an editorial published in Frontiers in Plant Science titled "Carbon-water-nitrogen processes and mechanisms of agricultural and forest ecosystems under future climate change." The editorial emphasizes the importance of understanding the processes and mechanisms of carbon, water, and nitrogen cycles in agricultural and forest ecosystems in response to climate change. It highlights 10 papers that provide insights into the interactions between carbon, water, and nitrogen in these ecosystems. The papers cover topics such as litter decomposition, carbon sequestration, evapotranspiration, water use efficiency, root distribution, leaf photosynthesis, and the mitigating effects of elevated CO2 concentrations on environmental stressors. The editorial concludes by emphasizing the need to fully explore the potential mechanisms and processes of agriculture and forests in order to project the potential risks of climate change on global grain yield and forest carbon sequestration. [Extracted from the article]

Nature-based Solutions (NbS) are integral to efforts to keep global warming below 2°C in accordance with the United Nations' 2015 Paris Agreement on Climate Change. Yet the transboundary governance dimensions of NbS remain unclear and largely undocumented. In Southeast Asia, NbS have emphasised the conservation and/ or sustainable commodification of carbon sinks found in terrestrial and mangrove forests, seagrass meadows, peatlands and agricultural soils. Mostly project-driven and fixed-term, these "solutions" have often failed to meet their social and ecological objectives. Increasingly, they have added to cross-border problems of: (1) displaced carbon emissions; and (2) economic migration and societal dispossession. This perspective paper delineates a transboundary governance research agenda to mitigate these trade-offs and enhance the co-benefits of NbS in carbon sinks. Building on NbS literature, it identifies cross-sector, multi-scalar and interdisciplinary pathways to improve transboundary cooperation, inclusion and equity in carbon sink governance in varying Southeast Asian contexts. [ABSTRACT FROM AUTHOR]

The Earth's oceans serve as vast heat storage reservoirs and the ocean currents, forming a heat transfer zone, act as a buffer for climate change. The oceans play a crucial role in the water cycle, carbon cycle, and nitrogen cycle, interacting with the atmosphere. However, the increasing occurrence of heatwaves in recent years has disrupted the stability of the oceans and affected their function as a global thermostat. This paper examines relevant literature from the Web of Science database spanning from 1996 to 2023. Our analysis reveals the evolving research hotspots regarding the impact of heatwaves on ocean carbon sinks, progressing from "carbon dioxide - carbon emissions - ocean - seawater - organic matter - marine sediment" over the past decades. Keyword frequency and centrality analysis indicate a deepening focus in this field of study. The research areas primarily revolve around climate change, carbon dioxide, ocean variability, the influence of high temperatures on the carbon cycle, the weakening of the ocean carbon sink function, and ocean temperature. This study summarizes research findings on the mechanisms by which high temperature heatwaves affect ocean carbon sinks, alterations in ocean carbon cycle patterns, their impacts on marine ecosystems, and factors influencing seawater temperature and heatwave occurrence. Finally, the paper discusses novel findings in this field and proposes countermeasures to enhance ocean sink capacity amidst the warming trend. • The research hotspots have shifted from "carbon dioxide-carbon emissions-ocean-seawater-organic matter-marine sediment". • The study analyzes mechanisms by which high-temperature heat waves affect ocean carbon sinks and identifies influencing factors. • The research presents novel findings in this area and proposes strategies to enhance the capacity of ocean sinks. [ABSTRACT FROM AUTHOR]

In the global context, countries must reduce carbon dioxide emissions to "net zero" by 2050 to limit global warming to 1.5 °C above pre-industrial levels. China's Nationally Determined Contributions (NDCs) are to peak carbon dioxide emissions by 2030 and achieve the carbon neutrality target by 2060. To monitor the achievements of the NDCs, establishing an annual-based accounting mechanism is necessary to record the carbon stocks in China, especially for Blue Carbon. The paper aims to present China's first national-scale systematic Blue Carbon accounting for mangroves, salt marshes, and seagrasses, covering the accounting subjects of physical and monetary assets, as well as relevant indicators for investors. It focuses on the design of the accounting method and system, the selection of data categories applied to this system, and the application of China's Blue Carbon accounting based on this accounting system. Taking Blue Carbon accounting as a starting point, this paper analyses the restoration prospects of these ecosystems and their application potential for NDCs in China compared with the terrestrial ecosystems. The results indicate that mangroves are the most cost-effective type of ecosystem, even compared to terrestrial forests. Thus, the paper provides policymakers with a new perspective on the decision-making of carbon sequestration relevant decisions, aiming to promote the monitoring, restoration, and expansion of China's coastal blue carbon ecosystem through the establishment of a sound Blue Carbon accounting system, and to help achieve the carbon neutrality goal in China's NDCs through regular and systematic monitoring of its national Blue Carbon inventories. • China's coastal blue carbon ecosystems are carbon sources rather than carbon sinks. • Mangroves are the most cost-effective coastal blue carbon ecosystem compared to salt marshes and seagrass beds. • The Blue Carbon of mangroves is more cost-effective than the Green Carbon of terrestrial forests when meeting China's Nationally Determined Contributions target of increasing forest stocks. • Establishing guidelines for Blue Carbon data requirements will lay a scientific foundation for formulating strategies and policies to cope with global climate change. [ABSTRACT FROM AUTHOR]

A three-dimensional (3-D) physical-biogeochemical-carbon cycle coupled model is used to investigate the interannual variability of the air-sea carbon dioxide (CO2) flux (FCO2) in the Northern Yellow Sea (NYS) from 2009 to 2018. The verification of the model indicate that the simulation results for multiple variables exhibit consistency and fit well with the observed data. The study show that although the multi-year average FCO2 in the NYS is close to the source-sink balance, there are obvious interannual differences between different years. In particular, a relatively strong source of atmospheric CO2 (1.0 mmol m-2 d-1) is exhibited in 2014, while a relatively strong sink of atmospheric CO2 (-0.7 mmol m-2 d-1) emerges in 2016. Mechanism analysis indicates that the abnormally high temperature is the main controlling factor for the relatively high CO2 efflux rate in the NYS in 2014, while the abnormally low dissolved inorganic carbon (DIC) concentration is the main factor contributing to the relatively high CO2 influx rate in 2016. Further analysis reveals that the primary reason for the low DIC concentration since the onset of winter in 2016 is the high net decrease rate of DIC in the NYS in 2015, influenced by net community production in the summer and advection processes during the autumn. The abnormally high primary production during the summer of 2015 results in the excessive reduction of DIC concentration through biological processes. In addition, due to the strong northeasterly wind event in November 2015, low-concentration-DIC water from the Yellow Sea (YS) extends into the Bohai Sea (BS). This further leads to higher DIC flux from the NYS into the BS in the upper mixed layer and increases the inflow of low-concentration-DIC water from the Southern Yellow Sea (SYS) into the NYS. These ultimately result in the abnormal reduction of DIC concentration in the upper mixed layer of the NYS during the autumn of 2015. This study enriches our understanding of interannual variability of FCO2 in the NYS, which will not only help to further reveal the variations of FCO2 under human activities and climate change, but also provide useful information for guiding the comprehensive assessment of the carbon budget. [ABSTRACT FROM AUTHOR]

Thermophilization is the directional change in species community composition towards greater relative abundances of species associated with warmer environments. This process is well-documented in temperate and Neotropical plant communities, but it is uncertain whether this phenomenon occurs elsewhere in the tropics. Here we extend the search for thermophilization to equatorial Africa, where lower tree diversity compared to other tropical forest regions and different biogeographic history could affect community responses to climate change. Using re-census data from 17 forest plots in three mountain regions of Africa, we find a consistent pattern of thermophilization in tree communities. Mean rates of thermophilization were +0.0086 °C·y−1 in the Kigezi Highlands (Uganda), +0.0032 °C·y−1 in the Virunga Mountains (Rwanda-Uganda-Democratic Republic of the Congo) and +0.0023 °C·y−1 in the Udzungwa Mountains (Tanzania). Distinct from other forests, both recruitment and mortality were important drivers of thermophilzation in the African plots. The forests studied currently act as a carbon sink, but the consequences of further thermophilization are unclear. Thermophilization is a change in species community composition towards greater abundances of species associated with warmer environments. This study provides evidence of thermophilization in understudied Afromontane forests, but with drivers that are distinct from other forest types. [ABSTRACT FROM AUTHOR]

Surface, aircraft, and satellite measurements indicate pervasive early cold season (Augut–September) CO2 emissions across Arctic regions, consistent with increased ecosystem metabolism in plants and soils. A key remaining question is whether cold season sources will become large enough to permanently shift the Arctic into a net carbon source. Polar orbiting GHG satellites provide robust estimation of regional carbon budgets but lack sufficient spatial coverage and repeat frequency to track sink‐to‐source transitions in the early cold season. Mission concepts such as the Arctic Observing Mission (AOM) advocate for flying imaging spectrometers in highly elliptical orbits (HEO) over the Arctic to address sampling limitations. We perform retrieval and flux inversion simulation experiments using the AURORA mission concept, leveraging a Panchromatic imaging Fourier Transform Spectrometer (PanFTS) in HEO. Our simulations demonstrate the potential benefits of increased CO2 sampling for detecting emissions during the early cold season. Plain Language Summary: The Arctic is warming rapidly, leading to an acceleration of carbon exchange across tundra and boreal ecosystems. These changing flows of carbon can be difficult to detect using traditional observing systems. We propose that measurement systems which observe Arctic ecosystems continuously from a quasi‐GEO orbit can more accurately detect these important changes, such that unexpected and dangerous feedbacks to climate warming can be monitored and accounted for. Key Points: The Arctic Fourier Transform Spectrometer Investigation (AURORA) mission concept addresses GHG sampling limitations in the ArcticAURORA uses a highly elliptical orbit (HEO) to increase repeat frequency, and a panchromatic iFTS for SWIR O2 and CO2 bands (0.7–2.5 μm)Simulation experiments show potential benefits of increased sampling frequency for grid scale detection of early cold season CO2 emissions [ABSTRACT FROM AUTHOR]

Lakes are a crucial source of drinking water, provide ecological services from fisheries and aquaculture to tourism and are also a critical part of the global carbon cycle. Therefore, it is important to understand how lakes are changing over time. The ESA Ocean Colour Climate Change Initiative (OC-CCI) database allows to study changes in the largest lakes over 1997–2023 period. The Caspian Sea and ten next largest lakes were under investigation. Changes in the phytoplankton biomass (Chl-a), the concentration of particulate matter (bbp(555)), the colored dissolved organic matter, CDOM (adg(412)), and the light diffuse attenuation coefficient in water (Kd(490)) were analyzed. Both increasing and decreasing trends (or no significant trend at all) of studied parameters were observed in these lakes over the study period. In some of the Laurentian Great Lakes the changes in CDOM over the study period were found to be in accordance with the lake water level changes i.e. with the inflow from the catchment. There was difference between the trends of Chl-a and bbp(555) in lakes Michigan and Huron indicating that there may have been shift in phytoplankton community that took place around 2005. The study demonstrated that remote sensing products, like the ones created by ESA OC-CCI, are valuable tools to study behavior of large lakes ecosystems over time. [ABSTRACT FROM AUTHOR]

Hector is an open-source reduced-complexity climate–carbon cycle model that models critical Earth system processes on a global and annual basis. Here, we present an updated version of the model, Hector V3.2.0 (hereafter Hector V3), and document its new features, implementation of new science, and performance. Significant new features include permafrost thaw, a reworked energy balance submodel, and updated parameterizations throughout. Hector V3 results are in good general agreement with historical observations of atmospheric CO 2 concentrations and global mean surface temperature, and the future temperature projections from Hector V3 are consistent with more complex Earth system model output data from the sixth phase of the Coupled Model Intercomparison Project. We show that Hector V3 is a flexible, performant, robust, and fully open-source simulator of global climate changes. We also note its limitations and discuss future areas for improvement and research with respect to the model's scientific, stakeholder, and educational priorities. [ABSTRACT FROM AUTHOR]

Atmospheric tracers are often used to interpret the local CO 2 budget, where measurements at a single height are assumed to represent local flux signatures. Alternatively, these signatures can be derived from direct flux measurements or by using fluxes derived from measurements at multiple heights. In this study, we contrast interpretation of surface CO 2 exchange from tracer measurements at a single height to measurements at multiple heights. Specifically, we analyse the ratio between atmospheric O 2 and CO 2 (exchange ratio, ER) above a forest. We consider the following two alternative approaches: the exchange ratio of the forest (ER forest) obtained from the ratio of the surface fluxes of O 2 and CO 2 derived from measurements at multiple heights, and the exchange ratio of the atmosphere (ER atmos) obtained from changes in the O 2 and CO 2 mole fractions over time measured at a single height. We investigate the diurnal cycle of both ER signals to better understand the biophysical meaning of the ER atmos signal. We have combined CO 2 and O 2 measurements from Hyytiälä, Finland, during spring and summer of 2018 and 2019 with a conceptual land–atmosphere model to investigate the behaviour of ER atmos and ER forest. We show that the CO 2 and O 2 signals as well as their resulting ERs are influenced by climate conditions such as variations in soil moisture and temperature, for example during the 2018 heatwave. We furthermore show that the ER atmos signal obtained from single-height measurements rarely represents the forest exchange directly, mainly because it is influenced by entrainment of air from the free troposphere into the atmospheric boundary layer. The influence of these larger-scale processes can lead to very high ER atmos values (even larger than 2), especially in the early morning. These high values do not directly represent carbon cycle processes, but are rather a mixture of different signals. We conclude that the ER atmos signal provides only a weak constraint on local-scale surface CO 2 exchange, and that ER forest above the canopy should be used instead. Single-height measurements always require careful selection of the time of day and should be combined with atmospheric modelling to yield a meaningful representation of forest carbon exchange. More generally, we recommend always measuring at multiple heights when using multi-tracer measurements to study surface CO 2 exchange. [ABSTRACT FROM AUTHOR]

The Eocene–Oligocene transition (EOT, ca. 40–33 Ma) marks a transformation from a largely ice-free to an icehouse climate mode that is well recorded by oxygen-stable isotopes and sea surface temperature proxies. Opening of the Southern Ocean gateways and decline in atmospheric carbon dioxide levels have been considered as factors in this global environmental transformation and the growth of ice sheets in Antarctica during the Cenozoic. A more comprehensive understanding is still needed of the interplay between forcing versus response, the correlation among environmental changes, and the involved feedback mechanisms. In this study, we investigate the spatio-temporal variation in export productivity using biogenic Ba (bio- Ba) from Ocean Drilling Program (ODP) sites in the Southern Ocean, focusing on possible mechanisms that controlled them as well as the correlation of export productivity changes to changes in the global carbon cycle. We document two high export productivity events in the Southern Ocean during the late Eocene (ca. 37 and 33.5 Ma) that correlate to proposed gateway-driven changes in regional circulation and to changes in global atmospheric pCO2 levels. Our findings suggest that paleoceanographic changes following Southern Ocean gateway openings, along with more variable increases in circulation driven by episodic Antarctic ice sheet expansion, enhanced export production in the Southern Ocean from the late Eocene through early Oligocene. These factors may have played a role in episodic atmospheric carbon dioxide reduction, contributing to Antarctic glaciation during the Eocene–Oligocene transition. [ABSTRACT FROM AUTHOR]

Simple Summary: Climate warming has caused the active layer of permafrost to thicken, leading to permafrost melting and surface collapse, forming thermokarst landforms. These changes significantly affect regional vegetation, soil properties, and water processes, thereby impacting regional carbon cycling. This study examined the relationships between soil respiration rate (Rs), soil temperature (T), and volumetric water content (VWC) in the thermokarst depression zones of Qinghai Lake's headwater wetlands. The results showed a significant positive correlation between soil temperature and Rs, and a significant negative correlation between VWC and Rs. The inhibitory effect of VWC on Rs was stronger in thermokarst areas compared to natural conditions. Temperature had a greater influence on Rs, especially during the day, while VWC inhibited Rs more at night. The study highlights the combined impact of temperature and humidity on soil respiration, revealing that Rs in thermokarst areas is more sensitive to temperature changes at night. These findings improve our understanding of carbon cycling in wetland ecosystems and help predict wetland carbon emissions under climate change. As the climate warms, the thickening of the active layer of permafrost has led to permafrost melting and surface collapse, forming thermokarst landforms. These changes significantly impact regional vegetation, soil physicochemical properties, and hydrological processes, thereby exacerbating regional carbon cycling. This study analyzed the relationship between soil respiration rate (Rs), soil temperature (T), and volumetric water content (VWC) in the thermokarst depression zone of the headwater wetlands of Qinghai Lake, revealing their influence on these soil parameters. Results showed a significant positive correlation between soil temperature and Rs (p < 0.001), and a significant negative correlation between VWC and Rs (p < 0.001). The inhibitory effect of VWC on Rs in the thermokarst depression zone was stronger than under natural conditions (p < 0.05). Single-factor models indicated that the temperature-driven model had higher explanatory power for Rs variation in both the thermokarst depression zone (R2 = 0.509) and under natural conditions (R2 = 0.414), while the humidity-driven model had lower explanatory power. Dual-factor models further improved explanatory power, slightly more so in the thermokarst depression zone. This indicates that temperature and humidity jointly drive Rs. Additionally, during the daytime, temperature had a more significant impact on Rs under natural conditions, while increased VWC inhibited Rs. At night, the positive correlation between Rs and temperature in the thermokarst depression zone increased significantly. The temperature sensitivity (Q10) values of Rs were 3.32 and 1.80 for the thermokarst depression zone and natural conditions, respectively, indicating higher sensitivity to temperature changes at night in the thermokarst depression zone. This study highlights the complexity of soil respiration responses to temperature and humidity in the thermokarst depression zone of Qinghai Lake's headwater wetlands, contributing to understanding carbon cycling in wetland ecosystems and predicting wetland carbon emissions under climate change. [ABSTRACT FROM AUTHOR]

The ocean is responsible for taking up approximately 25% of anthropogenic CO2 emissions and stores >50 times more carbon than the atmosphere. Biological processes in the ocean play a key role, maintaining atmospheric CO2 levels approximately 200 ppm lower than they would otherwise be. The ocean's ability to take up and store CO2 is sensitive to climate change, however the key biological processes that contribute to ocean carbon storage are uncertain, as are how those processes will respond to, and feedback on, climate change. As a result, biogeochemical models vary widely in their representation of relevant processes, driving large uncertainties in the projections of future ocean carbon storage. This review identifies key biological processes that affect how ocean carbon storage may change in the future in three thematic areas: biological contributions to alkalinity, net primary production, and interior respiration. We undertook a review of the existing literature to identify processes with high importance in influencing the future biologically‐mediated storage of carbon in the ocean, and prioritized processes on the basis of both an expert assessment and a community survey. Highly ranked processes in both the expert assessment and survey were: for alkalinity—high level understanding of calcium carbonate production; for primary production—resource limitation of growth, zooplankton processes and phytoplankton loss processes; for respiration—microbial solubilization, particle characteristics and particle type. The analysis presented here is designed to support future field or laboratory experiments targeting new process understanding, and modeling efforts aimed at undertaking biogeochemical model development. Plain Language Summary: The storage of carbon in the ocean forms an essential component of the Earth's carbon cycle. The contribution of ocean biology to carbon storage is not well constrained by observations and as a result has large uncertainties in the future model projections. There are a multitude of processes involved in the uptake, remineralization and storage of carbon, many of which have high uncertainty. Here we assess significant processes in determining net primary production, the biological contribution to alkalinity, and interior respiration. Using an extensive literature review, expert assessment and community survey, we rank processes as having high, moderate or low importance to the future biologically‐mediated storage of carbon in the ocean. This analysis is intended to support future observational studies and biogeochemical model development. Key Points: Key processes needed to improve projections of the response of ocean carbon storage to climate change identifiedThree themes are addressed: net primary production, interior respiration, and biological contributions to alkalinityAn expert assessment and community survey used to rank processes according to importance and uncertainty levels [ABSTRACT FROM AUTHOR]

Ocean biogeochemical models have become critical tools for interpreting trace element and isotope (TEI) distributions observed during the GEOTRACES program and understanding their driving processes. Models stimulate new research questions that cannot be addressed with observations alone, for instance, concerning processes that occur over vast spatial scales and linkages between TEIs and other elemental cycles. A spectrum of modeling approaches has been applied to date, including (1) fully prognostic models that couple TEIs to broader biogeochemical frameworks, (2) simpler element-specific mechanistic models that allow for assimilation of observations, and (3) machine learning models that have no mechanistic underpinning but allow for skillful extrapolation of sparse data. Here, we evaluate the strengths and weaknesses of these approaches and review three sets of novel insights they have facilitated. First, models have advanced our understanding of global-scale micronutrient distributions, and their deviations from macronutrients, in terms of a "ventilation-regeneration-scavenging" balance. Second, models have yielded global-scale estimates of TEI inputs to and losses from the ocean, revealing, for instance, a rapid iron (Fe) cycle with an oceanic residence time on the order of decades. Third, models have identified novel links among various TEI cycling processes and the global ocean carbon cycle, such as tracing the supply of hydrothermally sourced Fe to iron-starved microbial communities in the Southern Ocean. We foresee additional important roles for modeling work in the next stages of trace element research, including synthesizing understanding from the GEOTRACES program in the form of TEI state estimates, and projecting the responses of TEI cycles to global climate change. [ABSTRACT FROM AUTHOR]

Modeling terrestrial gross primary productivity (GPP) is central to predicting the global carbon cycle. Much interest has been focused on the environmentally induced dynamics of photosystem energy partitioning and how improvements in the description of such dynamics assist the prediction of light reactions of photosynthesis and therefore GPP. The maximum quantum yield of photosystem II (ΦPSIImax) is a key parameter of the light reactions that influence the electron transport rate needed for supporting the biochemical reactions of photosynthesis. ΦPSIImax is generally treated as a constant in biochemical photosynthetic models even though a constant ΦPSIImax is expected only for non-stressed plants. We synthesized reported ΦPSIImax values from pulse-amplitude-modulated fluorometry measurements in response to variable temperatures across the globe. We found that ΦPSIImax is strongly affected by prevailing temperature regimes with declined values in both hot and cold conditions. To understand the spatiotemporal variability in ΦPSIImax , we analyzed the temperature effect on ΦPSIImax across plant functional type (PFT) and habitat climatology. The analysis showed that temperature's impact on ΦPSIImax is shaped more by climate than by PFT for plants with broad latitudinal distributions or in regions with extreme temperature variability. There is a trade-off between the temperature range within which ΦPSIImax remains maximal and the overall rate of decline of ΦPSIImax outside the temperature range such that species cannot be simultaneously tolerant and resilient to extreme temperatures. Our study points to a quantitative approach for improving electron transport and photosynthetic productivity modeling under changing climates at regional and global scales. [ABSTRACT FROM AUTHOR]

Land use/cover change has an important impact on global climate change and carbon cycle, and it has become another major source of carbon emission after energy consumption. Therefore, this study focuses on the main line of "land use carbon emissions-spatial and temporal patterns-influencing factors," and selects 13 cities in Jiangsu Province as the research object. Based on the data of land use and energy consumption, combined with the method of land use carbon emissions and ArcGIS technology, this study conducted a quantitative analysis of the spatio-temporal distribution of carbon emissions in Jiangsu Province. The factors affecting the spatial distribution of carbon emissions from land use in Jiangsu Province were discussed by using Geographic detector. The results show that: 1) Carbon emissions in Jiangsu Province showed an overall growth trend, from 16215.44 × 104tC in 2010-23597.68 × 104tC in 2020, with an average annual growth rate of 4.55%, of which the construction land and watersheds had a greater impact on carbon sources and sinks, respectively. 2) During the period, there were significant differences in carbon emission levels among different cities in Jiangsu Province, and the land use carbon emission in Jiangsu Province showed a stable spatial pattern of "northwest--southeast." The southern part of Jiangsu is always the hot area of carbon emission, while the cold spot area is mainly distributed in the northern and central parts of Jiangsu. 3) The interaction of factors such as economic development, industrial structure, energy intensity, land use and human activities is an important reason for the spatio-temporal differences of land use carbon emissions in Jiangsu Province. Among them, the level of urbanization, population size and economic aggregate have significant effects on carbon emissions. [ABSTRACT FROM AUTHOR]

Natural ecosystems store large amounts of carbon globally, as organisms absorb carbon from the atmosphere to build large, long-lasting, or slow-decaying structures such as tree bark or root systems. An ecosystem's carbon sequestration potential is tightly linked to its biological diversity. Yet when considering future projections, many carbon sequestration models fail to account for the role biodiversity plays in carbon storage. Here, we assess the consequences of plant biodiversity loss for carbon storage under multiple climate and land-use change scenarios. We link a macroecological model projecting changes in vascular plant richness under different scenarios with empirical data on relationships between biodiversity and biomass. We find that biodiversity declines from climate and land use change could lead to a global loss of between 7.44-103.14 PgC (global sustainability scenario) and 10.87-145.95 PgC (fossil-fueled development scenario). This indicates a self-reinforcing feedback loop, where higher levels of climate change lead to greater biodiversity loss, which in turn leads to greater carbon emissions and ultimately more climate change. Conversely, biodiversity conservation and restoration can help achieve climate change mitigation goals. Loss of vegetation carbon from biodiversity loss could rival emissions from other sources such as land-use change. This creates a feedback where climate change increases biodiversity loss, leading to greater emissions and more climate change. [ABSTRACT FROM AUTHOR]

We describe the baseline model configuration and simulation characteristics of the Geophysical Fluid Dynamics Laboratory (GFDL)'s Land Model version 4.1 (LM4.1), which builds on component and coupled model developments over 2013–2019 for the coupled carbon‐chemistry‐climate Earth System Model Version 4.1 (ESM4.1) simulation as part of the sixth phase of the Coupled Model Intercomparison Project. Analysis of ESM4.1/LM4.1 is focused on biophysical and biogeochemical processes and interactions with climate. Key features include advanced vegetation dynamics and multi‐layer canopy energy and moisture exchanges, daily fire, land use representation, and dynamic atmospheric dust coupling. We compare LM4.1 performance in the GFDL Earth System Model (ESM) configuration ESM4.1 to the previous generation component LM3.0 in the ESM2G configuration. ESM4.1/LM4.1 provides significant improvement in the treatment of ecological processes from GFDL's previous generation models. However, ESM4.1/LM4.1 likely overestimates the influence of land use and land cover change on vegetation characteristics, particularly on pasturelands, as it overestimates the competitiveness of grasses versus trees in the tropics, and as a result, underestimates present‐day biomass and carbon uptake in comparison to observations. Plain Language Summary: The Geophysical Fluid Dynamics Laboratory (GFDL) has developed a new Land Model (LM4.1) as part of its 4th generation coupled model development. This model includes advances from the previous generation and introduces a new vegetation demography model, multi‐layer canopy, plant hydraulics, fire, and land use representation as well as dynamic atmospheric dust coupling. Coupled within an Earth System Model (ESM4.1), LM4.1 features an improved representation of many ecological processes from the previous generation of GFDL ESMs. Key Points: A new land model LM4.1 is developed at the Geophysical Fluid Dynamics Laboratory (GFDL) for the next‐generation Earth System Model (ESM) ESM4.1LM4.1 integrates age‐height structured vegetation dynamics, multi‐layer canopy‐soil‐snow energy exchanges, and prognostic fires and mineral dustESM4.1/LM4.1 improves patterns of land surface climate and carbon cycle compared to the previous generation GFDL model ESM2G/LM3.0 [ABSTRACT FROM AUTHOR]

Land use change (LUC) alters the global carbon (C) stock, but our estimation of the alteration remains uncertain and is a major impediment to predicting the global C cycle. The uncertainty is partly due to the limited number and geographical bias of observations, and limited exploration of its predictors. Here we generated a comprehensive global database of 5,980 observations from 790 articles. The number of sites evaluated is at least seven times larger than in previous meta‐analyses. Our constrained estimates of different LUC's effects on soil organic C (SOC) and their variations across global climates reveal underestimation/overestimation in previous estimates. Converting forests and grasslands to croplands reduced SOC by 24.5% ± 1.53% (−11.03 ± 1.06 Mg ha−1) and 22.7% ± 1.22% (−8.09 ± 0.67 Mg ha−1), while 28.0% ± 1.56% (4.46 ± 0.42 Mg ha−1) and 33.5% ± 1.68% (5.8 ± 0.38 Mg ha−1) increases, respectively, were obtained in the reverse processes. Converting forests to grasslands decreased SOC by 2.1% ± 1.22% (−1.13 ± 0.44 Mg ha−1), while the reverse process increased SOC by 18.6% ± 1.73% (3.31 ± 0.51 Mg ha−1). Modeled relative importance of 10 drivers of LUC's impact on SOC revealed that higher initial SOC (iSOC) does not solely determine SOC loss in SOC‐negative LUC scenarios as previously proposed. Across four decades, reconverting croplands to forests and grasslands recovered only 49.5% (6.1 ± 0.51 Mg ha−1) and 75.3% (7.0 ± 0.38 Mg ha−1) of the iSOC, respectively, indicating the need for protecting C‐rich ecosystems. Our global data set advances information on LUC's effect on SOC and can be valuable to constrain Earth system models to reliably estimate global SOC stocks and plan climate change mitigation strategies. Plain Language Summary: Land use change (LUC) could increase or decrease the global soil organic carbon (SOC) stock and affect carbon cycling and climate change, but estimating its effect size is the most uncertain aspect of the global carbon cycle. Available estimates vary among studies, most of which often use few observations that do not cover most global regions. To provide more accurate estimates of different LUC types' effects on SOC, we compiled a comprehensive database that contains 5,980 observations across all global regions; and revealed that previous studies have underestimated/overestimated these effects. We modeled the predictors of SOC change and found that previous conclusions that higher initial SOC is the main reason for higher organic carbon loss under negative LUC scenarios were inexact. We show that land use practices aimed at restoring SOC could only recover part of the amount lost during similar time frames; hence, it is important to protect carbon‐rich ecosystems. Our study provides robust estimates of LUC's effect on SOC and provides data sets that can reliably assess and model the global carbon cycle and plan strategies for controlling global climate change. Key Points: Comprehensive global database advances robust estimates of land use change's (LUCs) effect on soil organic carbon (SOC) vital for Earth system modelingHigher initial SOC does not solely control rapid SOC loss in carbon‐negative LUC as often proposedDespite SOC buildup in the past four decades, the amount lost cannot be regained by restoration during similar time frames [ABSTRACT FROM AUTHOR]

In the pursuit of carbon neutrality, state-owned forests are prime candidates for carbon offset projects due to their unique tenure and management characteristics. Employing methodologies endorsed by the International Panel on Climate Change and logistic growth curves, this study assesses the carbon stocks and sequestration potential of established state-owned plantation forests across 31 Chinese provinces from 2023 to 2060, encompassing seven forestry industry groups. This study projects that by 2060, these forests will amass a carbon stock of 558.25 MtC, with the highest stock in Northeast China (122.09 MtC) and the lowest in Northwest China (32.27 MtC), notably showing the highest growth rate at 91.15%. Over the forecast period, they are expected to accumulate a carbon sink of 637.07 MtCO2e, translating to an average annual carbon sink of 17.22 MtCO2e and an average annual carbon sink per unit of 1.41 tons of CO2 per hectare per year. Additionally, state-owned forests have the potential to offset approximately 0.15%–0.17% of annual carbon emissions, aligning with international climate goals. However, it is essential to note that the conversion of these carbon sinks into tradable carbon credits is subject to specific methodology requirements. Therefore, the future development of carbon offset projects in China's state-owned forests should consider the advancement of carbon market mechanisms, including the Chinese Certified Emission Reduction and the introduction of a carbon inclusion mechanism and natural forest methodology, to fully realize their potential contributions to carbon neutrality. In summary, these findings offer valuable insights for shaping the future of carbon offset initiatives within China's state-owned forests. [ABSTRACT FROM AUTHOR]

Background: Global climate change is one of the major challenges facing the world today, and forests play a crucial role as significant carbon sinks and providers of ecosystem services in mitigating climate change and protecting the environment. China, as one of the largest developing countries globally, owns 60% of its forest resources collectively. Evaluating the carbon sequestration cost of collective forests not only helps assess the contribution of China's forest resources to global climate change mitigation but also provides important evidence for formulating relevant policies and measures. Results: Over the past 30 years, the carbon sequestration cost of collective forests in China has shown an overall upward trend. Except for coastal provinces, southern collective forest areas, as well as some southwestern and northeastern regions, have the advantage of lower carbon sequestration costs. Furthermore, LSTM network predictions indicate that the carbon sequestration cost of collective forests in China will continue to rise. By 2030, the average carbon sequestration cost of collective forests is projected to reach 125 CNY per ton(= 16.06 Euros/t). Additionally, there is spatial correlation in the carbon sequestration cost of collective forests. Timber production, labor costs, and labor prices have negative spatial spillover effects on carbon sequestration costs, while land opportunity costs, forest accumulation, and rural resident consumption have positive spatial spillover effects. Conclusion: The results of this study indicate regional disparities in the spatial distribution of carbon sequestration costs of collective forests, with an undeniable upward trend in future cost growth. It is essential to focus on areas with lower carbon sequestration costs and formulate targeted carbon sink economic policies and management measures to maximize the carbon sequestration potential of collective forests and promote the sustainable development of forestry. [ABSTRACT FROM AUTHOR]

The slowdown of the Atlantic Meridional Overturning Circulation (AMOC) and associated consequences on ocean carbon uptake could have large implications for the Earth's climate system and its global carbon cycle. This study analyzes ten Earth System Models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and reveals that the regional carbon uptake in the subpolar North Atlantic under a high CO2 emission scenario moderately correlates with the decline in AMOC at 40°N. AMOC transports warm and salty subtropical waters to the subpolar regions. Models with stronger AMOC slowdown generally exhibit weaker surface warming and larger decline of surface salinity and alkalinity. We consider two plausible mechanisms linking the AMOC slowdown to the decline of regional CO2 uptake: the reduction in surface alkalinity and diminished subduction. The decline of surface salinity and alkalinity reduces the ocean's capacity to buffer acids leading to a reduced CO2 uptake. This important contribution is unique to the North Atlantic. Diminished convective mixing and subduction of surface water can further decrease the downward transport of anthropogenic carbon, as also shown in previous research. The centennial trends of pCO2 are decomposed into four components driven by temperature, salinity, alkalinity and dissolved inorganic carbon, revealing that alkalinity and dissolved inorganic carbon are both significant contributors. The alkalinity-driven pCO2 essentially follows surface salinity, establishing the linkage between AMOC slowdown and alkalinity decline. Our results indicate that alkalinity changes are important for the interplay between AMOC and the regional carbon sequestration ability across the late 20th and the entirety of the 21st century in the subpolar North Atlantic. [ABSTRACT FROM AUTHOR]

The Eastern Indian Ocean (EIO) is an ideal region to explore the variability and controlling mechanisms of the seawater carbonate system and their potential influence on global climate change due to the distinctive environmental features, while studies in the EIO is far from sufficient. The spatiotemporal distributions of pH, dissolved inorganic carbon (DIC), alkalinity (Alk), and partial pressure of carbon dioxide (pCO2) were investigated in the EIO during autumn 2020 and spring 2021. The respective quantitative contributions of different controlling processes to DIC were further delineated. Significant seasonal variations were observed in the study area. Overall, the surface pH was lower and DIC, Alk, and pCO2 were higher during spring 2021 than during autumn 2020. The pH generally decreased from east to west during autumn 2020, whereas it decreased from north to south during spring 2021. The low values of DIC and Alk that were detected in the Bay of Bengal in these two seasons were mainly attributed to the influence of river inputs. Coastal upwelling during monsoon periods led to higher pCO2 and DIC values near Sumatra and Sri Lanka during spring 2021. The relationships of carbonate system parameters with different types of nutrients and different sized chlorophyll-a in the two seasons indicated the shifts of nutrients utilized by the phytoplankton, and phytoplankton species dominated the carbonate system variabilities. In vertical profiles, carbonate system parameters showed strong correlations with other physical and biogeochemical parameters, and these correlations were more robust during spring 2021 than during autumn 2020. The average sea-air flux of CO2 was 10.00 mmolm-2 d-1 during autumn 2020 andwas 16.00 mmolm-2 d-1 during spring 2021, which revealed that the EIO served as a CO2 source during the study period. In addition, the separation of different controlling processes of DIC indicated stronger mixing processes, less CaCO3 precipitation, more intensive sea-air exchange, and weaker photosynthesis during spring 2021 than during autumn 2020. [ABSTRACT FROM AUTHOR]

Gross primary productivity (GPP) is a reliable measure of the carbon sink potential of terrestrial ecosystems and is an essential element of terrestrial carbon cycle research. This study employs the diffuse fraction-based two-leaf light-use efficiency (DTEC) model to imitate China's monthly GPP from 2001 to 2020. We studied the trend of GPP, investigated its relationship with climatic factors, and separated the contributions of climate change and human activities. The findings showed that the DTEC model was widely applicable in China. During the study period, China's average GPP increased significantly, by 9.77 g C m−2 yr−1 (p < 0.001). The detrimental effect of aerosol optical depth (AOD) on GPP was more widespread than that of total precipitation, temperature, and solar radiation. Areas that benefited from AOD, such as Northwest China, experienced significant increases in GPP. Climate change and human activities had a primary and positive influence on GPP during the study period, accounting for 28% and 72% of the increase, respectively. Human activities, particularly ecological restoration projects and the adoption of advanced agricultural technologies, played a significant role in China's GPP growth. China's afforestation plan was particularly notable, with the GPP increasing in afforestation areas at a rate greater than 10 g C m−2 yr−1. This research provides a theoretical foundation for the long-term management of China's terrestrial ecosystems and helps develop adaptive ecological restoration tactics. [ABSTRACT FROM AUTHOR]

Introduction: Carbon neutrality has become a key strategy to combat global climate change. However, current methods for predicting carbon emissions are limited and require the development of more effective strategies to meet this challenge. This is especially true in the field of sports and competitions, where the energy intensity of major events and activities means that time series data is crucial for predicting related carbon emissions, as it can detail the emission patterns over a period of time. Method: In this study, we introduce an artificial intelligence-based method aimed at improving the accuracy and reliability of carbon emission predictions. Specifically, our model integrates an Improved Mahjong Search Algorithm (ISSA) and GRU-Transformer technology, designed to efficiently process and analyze the complex time series data generated by sporting events. These technological components help to capture and parse carbon emission data more accurately. Results: Experimental results have demonstrated the efficiency of our model, which underwent a comprehensive evaluation involving multiple datasets and was benchmarked against competing models. Our model outperformed others across various performance metrics, including lower RMSE and MAE values and higher R2 scores. This underscores the significant potential of our model in enhancing the accuracy of carbon emission predictions. Discussion: By introducing this new AI-based method for predicting carbon emissions, this study not only provides more accurate data support for optimizing and implementing carbon neutrality measures in the sports fi eld but also improves the accuracy of time series data predictions. This enables a deeper understanding of carbon emission trends associated with sports activities. It contributes to the development of more effective mitigation strategies, making a significant contribution to global efforts to reduce carbon emissions. [ABSTRACT FROM AUTHOR]

There is a cross‐sectoral push among conservationists to simultaneously mitigate biodiversity loss and climate change, especially as the latter increasingly threatens the former. Growing evidence demonstrates that animals can have substantial impacts on carbon cycling. As such, there are increasing calls to use animal conservation and rewilding to dually overcome biodiversity loss and mitigate climate change.Specifically, trophic rewilding—which involves restoring intact animal communities, functional roles and trophic structure within food webs, and natural ecosystem processes—utilizes a rewilding framework to simultaneously support biodiversity conservation and carbon capture and storage. Trophic rewilding is a complex conservation approach to mitigating climate change, involving accurate estimations of baseline conditions and continuous monitoring of carbon cycling and species impacts within a system. It is also predicated on garnering social support for both the reintroduction and monitoring of a species, and obtaining the animals themselves.We are excited by the growing interest in this potential, but emphasize that a species' net impact on ecosystem carbon dynamics is context‐dependent. Caution is required whenever biodiversity conservation (including rewilding), climate change mitigation, and human welfare do not readily align. Hence—similar to other nature‐based solutions—these burgeoning efforts must avoid sweeping generalizations.To bolster successful trophic rewilding, we highlight a range of social and ecological context dependencies that can vary outcomes in a rewilded carbon cycle and provide ethical considerations for successful implementation.We conclude with an overview of the available technology to predict and monitor progress toward both biodiversity and climate mitigation goals. Read the free Plain Language Summary for this article on the Journal blog. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Desertification is a transnational, cross-regional, and global eco-environmental problem that seriously restricts sustainable socioeconomic development. As Mongolia is a typical arid and semi-arid region, the evolution of desertification in the country is closely related to major global issues such as climate change, global carbon cycling, and biodiversity. In this article, we analyze the background, development process, limitations, and other aspects of Mongolia's desertification prevention and control policies and regulations and conclude that Mongolia needs to formulate a "Desertification Prevention and Control Law." In particular, it needs to clarify the responsibility subjects, beneficiaries, interest compensation subjects, and illegal punishment subjects for prevention and control, as well as the responsibilities and obligations of relevant legal subjects. The research results show that it is important to form a solution mechanism in legal research on the joint prevention and control of desertification between Mongolia and China. We propose a concept of best future practice, highlighting the urgent need to establish a framework for the joint prevention and control of desertification via a cooperative mechanism between Mongolia and China and for the two countries to jointly promote global cooperation in combating this important environmental issue. [ABSTRACT FROM AUTHOR]

The response of the global climate–carbon-cycle system to anthropogenic perturbations happens differently at different timescales. The unravelling of the memory structure underlying this timescale dependence is a major challenge in climate research. Recently the widely applied α – β – γ framework proposed by to quantify climate–carbon-cycle feedbacks has been generalized to account also for such internal memory. By means of this generalized framework, we investigate the timescale dependence of the airborne fraction for a set of Earth system models that participated in CMIP5 (Coupled Model Intercomparison Project Phase 5). The analysis is based on published simulation data from C 4 MIP-type (Coupled Climate–Carbon Cycle Model Intercomparison) experiments with these models. Independently of the considered scenario, the proposed generalization describes at global scale the reaction of the climate–carbon system to sufficiently weak perturbations. One prediction from this theory is how the timescale-resolved airborne fraction depends on the underlying feedbacks between climate and the carbon cycle. These feedbacks are expressed as timescale-resolved functions depending solely on analogues of the α , β , and γ sensitivities, introduced in the generalized framework as linear response functions. In this way a feedback-dependent quantity (airborne fraction) is predicted from feedback-independent quantities (the sensitivities). This is the key relation underlying our study. As a preparatory step, we demonstrate the predictive power of the generalized framework exemplarily for simulations with the Max Planck Institute (MPI) Earth System Model. The whole approach turns out to be valid for perturbations of up to an about 100 ppm CO 2 rise above the pre-industrial level; beyond this value the response becomes non-linear. By means of the generalized framework we then derive the timescale dependence of the airborne fraction from the underlying climate–carbon-cycle feedbacks for an ensemble of CMIP5 models. Our analysis reveals that for all studied CMIP5 models (1) the total climate–carbon-cycle feedback is negative at all investigated timescales, (2) the airborne fraction generally decreases for increasing timescales, and (3) the land biogeochemical feedback dominates the model spread in the airborne fraction at all these timescales. Qualitatively similar results were previously found by employing the original α – β – γ framework to particular perturbation scenarios, but our study demonstrates that, although obtained from particular scenario simulations, they are characteristics of the coupled climate–carbon-cycle system as such, valid at all considered timescales. These more general conclusions are obtained by accounting for the internal memory of the system as encoded in the generalized sensitivities, which in contrast to the original α , β , and γ are scenario-independent. [ABSTRACT FROM AUTHOR]

As one of the most widespread components in marine sediments, calcium carbonate (CaCO3) plays a crucial role in the global carbon cycle and climate changes. To efficiently semi‐quantify the CaCO3 concentration, a more effective, non‐destructive, economic, and accurate technique is required. Diffuse reflectance spectroscopy (DRS) has been widely used for the detection and quantification of minerals but has been less studied for CaCO3. This study synthesized a series of samples with well‐determined content of CaCO3 to analyze the visible and near‐infrared DRS characteristics. Results show that the intensity of the second derivative of Kubelka‐Munk (K‐M) remission functions of the DRS spectra at 2,340 nm (I2340) is linearly correlated with the CaCO3 content. Then, the new proxy I2340 was applied for marine sediments from the Pacific Ocean with known CaCO3 concentrations determined previously by chemical methods, and the robustness of the I2340 as the proxy for CaCO3 concentration was attested. Plain Language Summary: Calcium carbonate (CaCO3) is one of the most common components in marine sediments, and its content variations (precipitation and dissolution) play an important role in global environmental change and paleoclimate evolution. However, previous quantitative methods such as chemistry and X‐ray diffraction cannot simultaneously achieve efficiency, accuracy, and environmental protection. To solve the above problems, this study established a new proxy using visible and near‐infrared diffuse reflectance spectroscopy (DRS) technology that can detect calcium carbonate content in a fast, non‐destructive, economic, and eco‐friendly way. The verification results from synthetic standard samples and natural marine sediment samples indicate that the new DRS proxy can well reflect the variations in calcium carbonate content, which is more targeted for calcium carbonate with less interference compared with the traditional brightness proxy. Overall, this study provides a promising method for precisely quantifying calcium carbonate in marine sediments. Key Points: CaCO3 exhibits a significant absorption in the near‐infrared band between 2,300 and 2,400 nmA new spectral proxy I2340 is proposed to quantify marine sedimentary CaCO3 contentI2340 is more accurate in quantifying marine sedimentary CaCO3 than traditional brightness proxy [ABSTRACT FROM AUTHOR]

Mangrove forest is a critical primary producer, biological habitat, and carbon sink in the subtropical-tropical coast zone, and the natural variation of mangrove coverage deserves study for a better understanding of the dynamics of mangrove coastal evolution. In this study, multispectral Landsat images from 1985 to 2018 are used to reconstruct the change in the coverage of mangrove (dominant species is Aegiceras corniculatum) and salt marsh (dominant species is Cyperus malaccensis) in the Nanliu River estuary. Tidal flat elevation measuring and 210Pb dating is used to study the substrate elevation when mangroves first colonize salt marsh. Historical temperature records, river discharge records, and the time series N/P concentration in sediment are analyzed. It is found that the mangrove forests have expanded rapidly in salt marsh since the mid-1980s. The change in factors such as accommodation space, cold event frequency, and nutrient supply cannot explain the origin of mangrove expansion. A low river discharge episode lasting for 8 years since 1986 is considered to have triggered the mangrove expansion in this area, as previously established salt marsh plants died due to germination restriction caused by high salinity and mangroves colonized the salt marsh habitat during this period. This case proves again that estuarine wetlands are very sensitive to salinity variation. [ABSTRACT FROM AUTHOR]

As the largest terrestrial organic carbon pool, soil organic carbon (SOC) plays an important role in the global carbon cycle, but it is easily affected by land use and climate change. The Huang-Huai-Hai Plain (HHHP) in China, which is dominated by dry farming, is experiencing rapid farmland loss and gain (farmland use transition), which may cause drastic changes in SOC storage. To clarify the effects of farmland use transition on SOC in dry farming areas, this study adopted a land use transition matrix and spatial analyst tool to explore the characteristics of farmland use transition and its effects on SOC content and stocks in the 200 cm soil layer in the HHHP from 2000 to 2020. The results showed that the farmland use transition in this area during that time period resulted in a net decrease of 16.06 × 103 km2 of farmland, of which urban built-up land and rural settlements led to a net reduction of farmland by 9.74 × 103 km2 and 6.43 × 103 km2, respectively, which was mainly affected by climate, topography, and economic factors. In addition, the farmland use transition resulted in a net increase in SOC storage of 6.13 Tg C, contributing 44.32% of the net increase. This is likely because the change in land use type led to a change in soil bulk density and soil gravel content while altering the SOC content, which in turn affected the SOC stock. This study has important implications for addressing global climate change and maintaining sustainable agricultural resources. [ABSTRACT FROM AUTHOR]

Paleoclimate reconstructions of the Early Eocene provide important data constraints on the climate and hydrologic cycle under extreme warm conditions. Available terrestrial water isotope records have been primarily interpreted to signal an enhanced hydrologic cycle in the Early Eocene associated with large-scale warming induced by high atmospheric CO2. However, orbital-scale variations in these isotope records have been difficult to quantify and largely overlooked, even though orbitally driven changes in solar irradiance can impact temperature and the hydrologic cycle. In this study, we fill this gap using water isotope–climate simulations to investigate the orbital sensitivity of Earth's hydrologic cycle under different CO2 background states. We analyze the relative difference between climatic changes resulting from CO2 and orbital changes and find that the seasonal climate responses to orbital changes are larger than CO2 -driven changes in several regions. Using terrestrial δ18O and δ2H records from the Paleocene–Eocene Thermal Maximum (PETM), we compare our modeled isotopic seasonal range to fossil evidence and find approximate agreement between empirical and simulated isotopic compositions. The limitations surrounding the equilibrated snapshot simulations of this transient event and empirical data include timing and time interval discrepancies between model and data, the preservation state of the proxy, analytical uncertainty, the relationship between δ18O or δ2H and environmental context, and vegetation uncertainties within the simulations. In spite of the limitations, this study illustrates the utility of fully coupled, isotope-enabled climate models when comparing climatic changes and interpreting proxy records in times of extreme warmth. [ABSTRACT FROM AUTHOR]

Background: Forests mitigate climate change by reducing atmospheric CO 2 -concentrations through the carbon sink in the forest and in wood products, and substitution effects when wood products replace carbon-intensive materials and fuels. Quantifying the carbon mitigation potential of forests is highly challenging due to the influence of multiple important factors such as forest age and type, climate change and associated natural disturbances, harvest intensities, wood usage patterns, salvage logging practices, and the carbon-intensity of substituted products. Here, we developed a framework to quantify the impact of these factors through factorial simulation experiments with an ecosystem model at the example of central European (Bavarian) forests. Results: Our simulations showed higher mitigation potentials of young forests compared to mature forests, and similar ones in broad-leaved and needle-leaved forests. Long-lived wood products significantly contributed to mitigation, particularly in needle-leaved forests due to their wood product portfolio, and increased material usage of wood showed considerable climate benefits. Consequently, the ongoing conversion of needle-leaved to more broad-leaved forests should be accompanied by the promotion of long-lived products from broad-leaved species to maintain the product sink. Climate change (especially increasing disturbances) and decarbonization were among the most critical factors influencing mitigation potentials and introduced substantial uncertainty. Nevertheless, until 2050 this uncertainty was narrow enough to derive robust findings. For instance, reducing harvest intensities enhanced the carbon sink in our simulations, but diminished substitution effects, leading to a decreased total mitigation potential until 2050. However, when considering longer time horizons (i.e. until 2100), substitution effects became low enough in our simulations due to expected decarbonization such that decreasing harvests often seemed the more favorable solution. Conclusion: Our results underscore the need to tailor mitigation strategies to the specific conditions of different forest sites. Furthermore, considering substitution effects, and thoroughly assessing the amount of avoided emissions by using wood products, is critical to determine mitigation potentials. While short-term recommendations are possible, we suggest risk diversification and methodologies like robust optimization to address increasing uncertainties from climate change and decarbonization paces past 2050. Finally, curbing emissions reduces the threat of climate change on forests, safeguarding their carbon sink and ecosystem services. [ABSTRACT FROM AUTHOR]

Each year, the biological carbon pump (BCP) transports large quantities of carbon from the ocean surface to the interior. The efficiency of this transfer varies geographically, and is a key determinant of the atmosphere‐ocean carbon dioxide balance. Traditionally, the attention has been focused on explaining perceived geographical variations in this transfer efficiency (TE) in an attempt to understand it, an approach that has led to conflicting results. Here we combine observations and modeling to show that the spatial variability in TE can instead be explained by the seasonal variability in carbon flux attenuation. We also show that seasonality can explain the contrast between known global estimates of TE, due to differences in the date and duration of sampling. Our results suggest caution in the mechanistic interpretation of annual‐mean patterns in TE and demonstrates that seasonally and spatially resolved data sets and models might be required to generate accurate evaluations of the BCP. Plain Language Summary: Each year, marine phytoplankton convert carbon dioxide into millions of tonnes of organic carbon with a fraction of it reaching the deep ocean, where it can remain for hundreds of years. The efficiency of this surface‐to‐depth carbon transfer is therefore a key determinant of the atmosphere‐ocean carbon dioxide balance. However, the variability of this transfer efficiency (TE) and its underlying causes are poorly understood, to the extent that different studies report contradicting results. We show that the existence of seasonal variability in the attenuation of sinking carbon particles can explain the observed spatial variability in annual TE and reconcile with the literature. Our findings suggest caution in interpreting results from sparse but time‐varying data sets, highlighting that seasonal variability should be considered when studying the oceanic carbon cycle. Key Points: Spatial variability in carbon transfer efficiency (TE) can be generated solely by the seasonality of flux attenuation informed by observationsSeasonality in flux attenuation can reconcile contrasting TE maps reported in the literatureResolving and understanding seasonality are key for an accurate evaluation of the biological carbon pump under climate change [ABSTRACT FROM AUTHOR]

Accurately representing the ocean carbon cycle in Earth System Models (ESMs) is essential to understanding the oceanic CO2 sink evolution under CO2 emissions and global warming. A key uncertainty arises from the ESM's inability to explicitly represent mesoscale eddies. To address this limitation, we conduct eddy‐resolving experiments of CO2 uptake under global warming in an idealized mid‐latitude ocean model. In comparison with similar experiments at coarser resolution, we show that the CO2 sink is 34% larger in the eddy‐resolving experiments. 80% of the increase stems from a more efficient anthropogenic CO2 uptake due to a stronger Meridional Overturning circulation (MOC). The remainder results from a weaker reduction in CO2 uptake associated to a weaker MOC decline under global warming. Although being only a fraction of the overall response to climate change, these results emphasize the importance of an accurate representation of small‐scale ocean processes to better constrain the CO2 sink. Plain Language Summary: Today, the ocean absorbs ∼25% of the CO2 emissions caused by human activities. This CO2 sink is primarily driven by the increase of CO2 in the atmosphere, but it is also influenced by physical changes in the ocean's properties. Earth System Models are used to project the future of the ocean CO2 sink. Due to limited computational capacity, ESMs need to parameterize flows occurring at scales smaller than ∼100 km, their typical horizontal grid resolution. To overcome the computational limitations, we use an ocean biogeochemical model representing an idealized North Atlantic ocean of reduced dimensions. We conduct simulations of global warming using increasingly finer horizontal resolutions (from ∼100 km to ∼4 km). Our findings demonstrate that the ocean CO2 uptake is highly influenced by resolution. This sensitivity primarily stems from how the overturning circulation's mean state depends on resolution, as well as how it responds to global warming. Although our results capture only a fraction of the overall oceanic response to climate change, they emphasize the significance of accurately representing the role of small‐scale ocean processes to better constrain the future evolution of ocean carbon uptake. Key Points: We conducted idealized ocean simulations under global warming and rising atmospheric CO2 at coarse and eddy‐resolving resolutionsCO2 sink is larger by 34% at eddy resolution, due to larger anthropogenic CO2 uptake combined with weaker climate feedbackThis ensues from the model's overturning circulation sensitivity to resolution in both historical and future state [ABSTRACT FROM AUTHOR]

After many years with little change in community views on equilibrium climate sensitivity (ECS), in 2021 the Intergovernmental Panel on Climate Change (IPCC) concluded that it was much better known than previously. This development underpinned increased confidence in long-term climate changes in that report. Here, we place this development in historical context, briefly assess progress since then, and discuss the challenges and opportunities for further improving our knowledge of this iconic concept. We argue that the probability distributions published in those assessments are still approximately valid; while various subsequent studies have claimed further narrowing, they have omitted important structural uncertainties associated with missing processes, imperfect relationships, or other factors that should be included. The distributions could nonetheless be narrowed in the future, particularly through better understanding of certain climate processes and paleoclimate proxies. Not all touted strategies are truly helpful, however. We also note that ECS does not address risks from the carbon cycle or possible tipping points, and as increasingly strong mitigation (i.e., "net-zero") scenarios are considered, ECS becomes less informative about future climate change compared to other factors such as aerosol radiative forcing and influences on regional change such as ocean dynamics. [ABSTRACT FROM AUTHOR]

Mass timber construction is widely considered a promising alternative construction method to reduce buildings' total life-cycle carbon emissions because wood is a carbon sink. Cross-laminated timber (CLT) panels, manufactured by gluing lumber layers with grains at right angles, are potential low-carbon alternatives to carbon-intensive concrete and steel construction. However, most environmental impact assessment studies do not consider variation in transportation impacts within the CLT supply chain when calculating life-cycle impacts. This study investigates the embodied primary energy and the global warming potential (GWP) of CLT supply chain decisions regarding the type of timber species used, the U.S. region it is sourced from, and the location of the CLT mill. Longer transport distances in the supply chain for timber and CLT panels can contribute as much as 923MJ/m2 (20%) of the embodied primary energy of a CLT building, and the use of a higher-density timber species increases this contribution to 1246 MJ/m2 (24%), with most of that energy derived from fossil energy sources. For perspective, the GWP of a building whose CLT panels and timber have been transported by truck over 6,000 km (252-270 kgCO2/m2) is greater than the GWP of an equivalent reinforced concrete (RC) building (245 kgCO2/m2). Thus, factors like the location of CLT processing facilities and the type of timber species can significantly impact the overall life-cycle assessment and, if chosen appropriately, can mitigate the environmental impacts of CLT construction. [ABSTRACT FROM AUTHOR]

Land surface models are an important tool in the study of climate change and its impacts, but their use can be hampered by uncertainties in input parameter settings and by errors in the models. We apply uncertainty quantification (UQ) techniques to constrain the input parameter space and corresponding historical simulations of JULES-ES-1.0 (Joint UK Land Environment Simulator Earth System), the land surface component of the UK Earth System Model, UKESM1.0. We use an ensemble of historical simulations of the land surface model to rule out ensemble members and corresponding input parameter settings that do not match modern observations of the land surface and carbon cycle. As JULES-ES-1.0 is computationally expensive, we use a cheap statistical proxy termed an emulator, trained on the ensemble of model runs, to rule out parts of the parameter space where the simulator has not yet been run. We use history matching, an iterated approach to constraining JULES-ES-1.0, running an initial ensemble and training the emulator, before choosing a second wave of ensemble members consistent with historical land surface observations. We successfully rule out 88 % of the initial input parameter space as being statistically inconsistent with observed land surface behaviour. The result is a set of historical simulations and a constrained input space that are statistically consistent with observations. Furthermore, we use sensitivity analysis to identify the most (and least) important input parameters for controlling the global output of JULES-ES-1.0 and provide information on how parameters might be varied to improve the performance of the model and eliminate model biases. [ABSTRACT FROM AUTHOR]

Grassland, as a key component of the carbon cycle in terrestrial ecosystems, is vital in confronting global climate change. Characterising the carbon density of grassland ecosystems in the Longzhong Loess Plateau is important for accurately assessing the contribution of grasslands to global climate change and achieving the goal of "peak carbon" and "carbon neutral". In this study, the Longzhong Loess Plateau was used as the research object to explore changes in the plant–soil system carbon density in two grassland types by analysing the aboveground vegetation biomass carbon density, belowground vegetation biomass carbon density, 0–100 cm soil carbon density, and ecosystem carbon density of temperate steppe and temperate desert. The results showed that the vegetation biomass (standing and living, litter, and belowground biomass), soil, and ecosystem carbon densities of the temperate steppe were significantly higher than those of the temperate desert (p < 0.05). Their carbon densities were 700.51, 7612.95, and 8313.45 g·m−2, respectively. The vertical distribution of belowground biomass and soil carbon density in the temperate steppe was significantly higher than that in the temperate desert. The overall trend of belowground biomass carbon density in the temperate steppe and temperate desert showed a gradual decrease, whereas soil carbon density showed a steady increase. More than 91% and 96% of the carbon was stored in soil in the temperate steppe and temperate desert, respectively, and the belowground biomass carbon stock accounted for more than 84% of the total biomass carbon pools in both temperate steppe and temperate desert. Temperate steppe has a significant effect in improving the carbon stock of grassland ecosystems, so ecological protection and restoration of grassland should be strengthened in the future to enhance the capacity of grassland to sequester carbon and increase sinks. [ABSTRACT FROM AUTHOR]

Trawling the seafloor can disturb carbon that took millennia to accumulate, but the fate of that carbon and its impact on climate and ecosystems remains unknown. Using satellite-inferred fishing events and carbon cycle models, we find that 55-60% of trawling-induced aqueous CO2 is released to the atmosphere over 7-9 years. Using recent estimates of bottom trawling's impact on sedimentary carbon, we found that between 1996-2020 trawling could have released, at the global scale, up to 0.34-0.37 Pg CO2 yr-1 to the atmosphere, and locally altered water pH in some semi-enclosed and heavy trawled seas. Our results suggest that the management of bottom-trawling efforts could be an important climate solution. [ABSTRACT FROM AUTHOR]