Storage Patterns Research Articles

Emergence of the North Pacific heat storage pattern delayed by decadal wind-driven redistribution

Storage of anthropogenic heat in the oceans is spatially inhomogeneous, impacting regional climates and human societies. Climate models project enhanced heat storage in the mid-latitude North Pacific (MNP) and much weaker storage in the tropical Pacific. However, the observed heat storage during the past half-century shows a more complex pattern, with limited warming in the MNP and enhanced warming in the northwest tropical Pacific. Here, based on observational datasets, ocean model experiments, and climate models, we show that the emergence of human-induced heat storage is likely postponed in the North Pacific by natural variability until the late-21st century. Specifically, phase shifts of the Pacific Decadal Oscillation have vitally contributed to trends in the North Pacific winds during recent decades. Changes in surface winds drove meridional heat redistribution via Rossby wave dynamics, leading to regional warming and cooling structures and a more complex historical heat storage than models predict. Despite this, enhanced anthropogenic warming has already been emerging in marginal seas along the North Pacific basin rim, for which we shall prepare for the pressing consequences such as increasing marine heatwaves.

Spatiotemporal Nonlinear Characteristics and Threshold Effects of China's Water Resources

China faces shortage of water resources, particularly in the context of rapid population growth and accelerating urbanization, making the changes in its water resources among the most pronounced on Earth. Additionally, the complex interplay between climate change and human activities leads to nonlinear and non-stationary patterns in China's water resources. This study utilizes high-resolution water storage monitoring data to comprehensively analyze the nonlinear changes in water storage and its relationships with human footprint, precipitation, and temperature, revealing the complex dynamics of water storage changes across China. We used advanced data analysis techniques to identify critical points where water storage patterns shifted significantly, with categories of nonlinear changes that first decrease then increase and those that first increase then decrease together accounting for 55.62% of the observations. The northeastern and western border areas of China are hotspots for these nonlinear changes, and the analysis identifies 2019 as a year with a high frequency of turning points. The piecewise linear regression analysis found that when the human footprint exceeds a specific threshold, its negative impact on water storage significantly intensifies; when precipitation and temperature exceed certain thresholds, their impact on water storage shifts from negative to positive. These findings not only reveal the complex spatiotemporal distribution characteristics of water storage change turning points across China but also emphasize that water resource management strategies in China and globally need to adopt more comprehensive and dynamic approaches in the context of global climate change. To meet future challenges, it is essential to integrate multiple variables and develop flexible, adaptive management strategies to ensure the sustainable use and effective management of water resources.

Temporal and Spatial Characteristics and Influencing Factors of Carbon Storage in Black Soil Area Under Topographic Gradient

Exploring the characteristics and driving factors of carbon storage change in different terrain gradient variations can provide important insights for formulating the agricultural ecological protection policy for regional development. Previous studies have used the fixed value of carbon density to evaluate the change characteristics of carbon storage but ignored the spatio-temporal heterogeneity of carbon storage at the block scale and the impact of policy factors. Thus, this paper takes Sanjiang Plain, Heilongjiang Province, China, as a study area, and the spatio-temporal variation of carbon storage at different topographic gradients was revealed using hot and cold spot analysis and zonal statistics. Through the geographic detector and estimation of the soil carbon density model, the driving factors and intensity of carbon storage spatial distribution are revealed from 1990 to 2020. We conducted analyses on aboveground biomass, underground biomass, and soil carbon storage across three elevation levels (0–200 m, 200–500 m, 500–999 m) to reveal the quantitative distribution features of carbon storage. The study analysis finds that carbon storage indicates a sawtooth evolution during the study period. Carbon storage was dominant at elevation I (range is 0–200 m), slope I (range is 0–2°), and relief amplitude I (range is 0–30 m). Additionally, the carbon storage losses were severe at elevation II (range is 200–500 m), slope II (2–6°), and relief amplitude II (30–70 m). In contrast, the carbon storage losses at elevation III (500–999 m), slope III (6–15°), and relief amplitude III (70–186 m) were insignificant. The spatial pattern of carbon storage varies significantly under different topographic gradients from 1990 to 2020. The most critical driving factors influencing the spatial distribution pattern of carbon storage were land use and annual average temperature. Distance to urban centers and soil texture also moderately influence the distribution of carbon storage. As the topographic gradient increases, the dominant factors of carbon storage gradually change from annual mean temperature and the extent of land use to policy factors and other socio-economic factors. Therefore, this study emphasizes the importance of implementing policies that convert farmland to forests and wetlands and promote the green transformation of agriculture.

A study on identifying representative trips for mobility service design

AbstractRecently, with growing interest in urban mobility patterns, the demand for collecting and analysing origin‐destination (OD) data is increasing. Due to the large scale and dimensionality of OD data, there are two issues in analysing the data: big‐data storage and major pattern extraction. To deal with two issues at the same time, this study suggests a principal control analysis‐based major demand identification method to improve the usability of microscopic OD data. Especially, this study focuses on finding principal components that preserve major patterns from OD data with small random noise so that the data can be effectively used for mobility service design. The proposed method is applied to smart card data of Seoul and Sejong and extracted major demand patterns from peak‐ and non‐peak hour data of these cities. The degree of daily regularity, reconstruction accuracy, and compression rate of the reconstructed data is analysed varying sets of principal components. The obtained results show that the major demands contain a low volume and a large volume of demand and with lower‐order principal components, major demands can be efficiently extracted by removing randomly appearing small‐volume demand. In addition, the trade‐off behaviour is observed between the degree of daily regularity and reconstruction accuracy depending on the compression rate. Based on the observations, it can be found that the loss of major demand patterns could be prevented when targeting a reconstruction accuracy of 90–95% and the proposed method can reduce the data size while preserving major mobility patterns.

Firearm possession among emergency department youth and young adults: A latent class analysis

IntroductionFirearm injuries are a leading cause of death for youth/young-adults. We utilized latent class analysis to identify distinct motivational/behavioral patterns of firearm possession in a youth/young-adult emergency department sample to inform prevention strategies. MethodsCross-sectional data were obtained from surveys conducted among youth/young-adults (age = 16–29; n = 1311) seeking emergency department treatment (7/10/2017–6/25/2018). Latent class analysis was performed for individuals reporting firearm possession (n = 223) using five variables: carriage frequency, social carriage, risky firearm behaviors, ownership/carriage for protection, and recreational ownership/carriage. Descriptive statistics were examined. ResultsIn this sample, 17.0 % reported having firearms (age-22.7; 48.0 %-male; 49.3 %-Black; 52.5 %-public assistance). Latent class analysis identified four classes: 1-recreational possession (n = 51); 2-possession for protection with low carriage (n = 60); 3-carriage for protection with low risky firearm behaviors (n = 76); and 4-carriage for protection with high risky firearm behaviors (n = 36). Class-1 (recreational possession) had low firearm victimization, violence exposure, and community violence. This class primarily kept long-guns with secure storage patterns. Class-2 (protection with low carriage) were mostly female youth/young-adults with children and reported moderately high rates of violence exposure. Nearly 20 % stored their firearm unlocked. Class-3 and -4 endorsed firearm carriage for protection, with Class-4 also engaging in risky firearm behaviors. Both classes had high violence exposure; however, Class-4 had higher risk profiles including higher marijuana misuse, mental health symptoms, and firearm victimization. ConclusionsAmong an emergency department sample, four distinct firearm possession classes emerged with different risk levels. Understanding firearm behaviors and risk/protective factors is critical to tailoring healthcare-focused interventions to address individual needs and reduce injury risk.

RanSMAP: Open dataset of Ransomware Storage and Memory Access Patterns for creating deep learning based ransomware detectors

Ransomware attacks have become significant cyber threats to enterprises and public sectors. Our previous RanSAP dataset, which contained only low-level storage access patterns collected using a thin hypervisor, was used to create behavioral-based ransomware detectors; it provides an additional protection layer when the OS-level ransomware detection systems are compromised. The previous ransomware detector, which used only low-level storage access patterns, could not detect ransomware when Office applications and web browsers were executed simultaneously. This paper presents a new open dataset named RanSMAP, which stands for Ransomware Storage and Memory Access Patterns. It contains low-level storage and memory access patterns collected using a thin hypervisor. We provide an overview of the open RanSMAP dataset, including directory structure and file formats, to guide researchers in using the dataset. We then present our data preprocessing method and deep-learning-based ransomware detector. The RanSMAP datasets consist of storage and memory access patterns of six ransomware samples and six benign applications, seven Conti ransomware variants, and simultaneous execution of ransomware with benign applications collected on the machines with various CPUs, RAM generations, RAM frequencies, and RAM capacities. The experimental results show that low-level memory access patterns improved ransomware detection performance by 2.3% compared to detectors using only storage access patterns. We confirmed that ransomware detectors trained using the RanSMAP dataset can detect ransomware when Office and web browser programs are executed simultaneously. We presented the survey on state-of-the-art ransomware detection research and the availability of open behavioral-feature datasets to discuss the advantages and limitations of our RanSMAP dataset.

Evaluation of Effectiveness and Multi-Scenario Analysis of Land Use Development Strategies and Ecological Protection Redlines on Carbon Storage in the Great Bay Area of China Using the PLUS-InVEST-PSM Model

Land use change is a key factor affecting the carbon storage of terrestrial ecosystems. Most studies focus on formulating different land development strategies to mitigate the adverse impacts of land development, while fewer discuss the effectiveness of these strategies. In the context of varying socio-economic development and limited budgets for ecological conservation, evaluating effectiveness is essential for selecting the most suitable land development strategy. This research proposed a Patch-Generating Land Use Simulation-Integrated Valuation of Ecosystem Services and Tradeoffs–Propensity Score Matching (PLUS-InVEST-PSM) model to evaluate the effectiveness of different land use development strategies in the Greater Bay Area of China as a case study. Specifically, this study analyzed the historical land use changes from 2000 to 2020 and mapped the multi-scenario patterns of land use and carbon storage with the PLUS and the InVEST models from 2030 to 2050. Then, this study employed the PSM model, along with a series of criteria (i.e., similar ecological backgrounds and parallel historical trends), to evaluate the effectiveness of the ecological development strategy and ecological protection redlines on carbon storage compared with the natural development strategy. The results indicate that the ecological development strategy and the ecological protection redline can prevent the decline in carbon storage. However, in the ecological development strategy, implementing the ecological redline policy may hinder the growth of carbon storage within the ecological redline area. Compared with the PLUS-InVEST-PSM model, the comparison between the subregions could underestimate the efficiencies of evaluation, partly due to underestimating the negative impact of urban development on carbon storage. These findings will help governments develop comprehensive and systematic land use policies to achieve carbon peaking and carbon neutrality goals. Also, the approach would help to further explore the broader impacts of land use development strategies on the overall regional ecological environment, such as biodiversity and ecosystem services.

Stability‐Enhanced Variable Stiffness Metamaterial with Controllable Force‐Transferring Path

AbstractSelf‐contact variable stiffness (SVS) metamaterial offers specific patterns of elastic strain energy storage by changing its force‐transferring path. The change of the elastic strain energy storage patterns further influences the stiffness variation of the SVS metamaterials. However, challenges still arise because typically fabricated SVS metamaterials inevitably contain structural irregularities, eccentricities, and defects. These microstructural imperfections impede the stable generation of designed strain energy storage patterns in the metamaterial, implying that the SVS metamaterials cannot achieve expected stiffness variations. To address this burning question, an SVS metamaterial/meta‐structure design paradigm with eccentric unit designs is proposed, which can realize both stable stiffness variations and high load‐bearing. The theoretical, simulation, and experimental results demonstrate that the SVS chain meta‐structure achieves ≈110 times stiffness variation between the low and high loading conditions. Its load‐bearing can reach more than 1500 N when the meta‐structure falls into the high stiffness stage. Furthermore, some typical functions are demonstrated using the stability‐enhanced SVS metamaterial, including customized mechanical protections for human joints and information transformation regulated by remote mechanical input signals. The results can provide a useful solution for generating a more feasible stability‐enhanced SVS metamaterial/meta‐structure and promote their potential applications in aerospace, medical devices, and robotics.

Construction of Cross-basin Ecological Security Patterns Based on Carbon Sinks and Landscape Connectivity

Artificial water system creation and land use changes have great effects on ecosystems. The construction of cross-basin ecological security patterns based on carbon sinks and landscape connectivity plays a key role in regional ecological environment protection. The linkage area between the Xiang River and the Li River was selected as the research object. Based on the land use data from 2000 to 2020, this study examined the ecological security network of the Xiang-Li connected region using the InVEST model combined with morphological spatial pattern analysis （MSPA） and evaluated the temporal and spatial evolution of carbon storage and ecological security patterns. The results showed that： ① From 2000 to 2020, the land cover types of the Xiang-Li linkage area were mainly forest land and arable land. The changes of land use types were characterized by decreases in arable land, forest land, and grassland and by increases in watersheds and construction land. ② The carbon storage in the Xiang-Li linkage area was characterized by a blocky distribution, and the high and medium areas were dominant. The carbon stock increased slowly from 2000 to 2010 and decreased dramatically from 2010 to 2020, with a cumulative decrease of 18.32×103 t due to the influence of land use changes. ③ The area of ecological sources （five in total） decreased firstly and then increased, whereas the length of ecological corridors （ten in total） increased firstly and then decreased in the Xiang-Li linkage area. Overall, in the process of urbanization, the distribution of the high ecological resistance value in the Xiang-Li linkage area gradually shifted to the northeast with an expansion, whereas the barycenter of the ecological safety pattern shifted to the southwest. Determining the dynamic distribution and stability of ecological sources by coupling carbon storage patches and landscape patterns can provide a new way to construct ecological security patterns in cross-basin ecosystems.

An x-ray computed tomography gas hydrate in situ formation and seepage simulation device.

Nano-CT (computed tomography) technology enables high-resolution imaging and scanning of hydrate dissociation processes in porous media at submicron-scale resolution. However, due to the inability of nano-CT to withstand large torque, the traditional semiconductor cooling method cannot be used for in situ hydrate formation, resulting in the hindering of the effective operation of seepage simulators. Therefore, in this paper, a nano-CT-based in situ hydrate formation and seepage simulator are specially designed, and the torque and entanglement problems existing in traditional experimental devices can be solved by using a pipeline placed above the device and a built-in seepage line. The device is able to offer an improved depiction of hydrates in porous media and the effect of the seepage process on the three-dimensional distribution of hydrates. The future applications of this device are expected to provide novel insights into the effects of gas-water transport and hydrate storage patterns during gas hydrate exploitation.

원삼국~백제 한성기 취락의 저장 양상 변화

In the process of state formation, storage methods can change according to political, economic, and social transformations. This study aims to identify such changes in storage methods, storage amounts, and stored crops by comparing and analyzing various types of archaeological evidence, such as crop remains, pottery, storage pits, and above-ground structures from sites of the central region of the Korean Peninsula dating the Proto-Three Kingdoms to Baekje’s Hanseong period. The results of the analysis revealed that, in the Gyeonggi region, the tendency to store crops indoors was weakened by the Hanseong period. However, in major settlements, this tendency persisted, and the use of external storage facilities increased, with rice becom-ing a significant crop for external storage. In the Yeongseo region, the change in indoor storage methods was not as distinct as in the Gyeonggi region, but there was a noticeable change in external storage patterns. Overall, the use of deep storage pits increased, new storage crops were added, and the use of external storage facilities increased somewhat in the Namhan River basin. Analyzing the reasons for these changes based on contemporary contexts, it was found that both the Gyeonggi and Yeongseo regions were influenced by changes in agricultural production methods. In the case of the Gyeonggi region, the in-creased complexity of society, such as the intensification of social stratification and the dif-ferentiation of site functions, also influenced storage strategies.

Application of pressure small signals extraction and amplification technology in abandoned well pattern for geothermal energy extraction and H2 storage: Numerical modeling and economic analysis

Using abandoned reservoirs for geothermal energy development and H2 storage is economical. The impact of complex fractures from long-term oil and gas extraction on geothermal energy and H2 storage is not yet clearly understood. Here, a pressure small signals extraction and amplification (PSEA) technology is developed to improve reservoir monitoring accuracy. This technology is capable of coupling many pressure transient analysis models to invert parameters for multiple scenarios. This work establishes numerical models to simulate the effects of geothermal energy extraction and H2 storage over 5000 days. Results show that this technology improves the accuracy of inverted parameters by 4–14 times. This technology adjusts the production temperature differences in a single injection-production system from 1.4K to 6.5K and the net heat power from 0.25 MW to 1.1 MW, and it can also identify an early low-rate H2 storage phase. The Non-Sorting Genetic Algorithm II calculates that the PSEA technology brings economic benefits of $704,000 and $352,000 for geothermal energy extraction and H2 storage in a single injection-production system. In conclusion, the developed monitoring technology and models improve accuracy in assessing geothermal energy development and H2 storage, preventing failures in residential heating or H2 storage projects.

Storage of firearms in vehicles: findings from a sample of firearm owners in nine U.S. states

BackgroundIn recent years, there has been a growing number of thefts of firearms stored in vehicles. Despite this trend, there is limited research on firearm storage patterns in vehicles in the United States. This study investigates these storage patterns and evaluates the relationship between the surge in firearm purchases after March 2020 and the practice of storing firearms in vehicles.MethodsFirearm storage practices were classified into four categories: (a) no vehicle storage, (b) locked vehicle storage only, (c) unlocked vehicle storage only, and (d) both locked and unlocked vehicle storage. Multinomial logistic regression analyses were conducted to determine the association between vehicle firearm storage practices and the main independent variable (firearm purchases since March 2020), adjusting for covariates.ResultsThose who purchased a firearm since March 2020 were significantly more likely to store at least one firearm in a vehicle unlocked only (RRR = 2.41, 95% CI 1.45–3.99) or both locked and unlocked (RRR = 2.57, 95% CI .180–3.67) compared to the reference category of no vehicle storage.ConclusionIndividuals who purchased a firearm after March 2020 were more likely to report storing a firearm in a vehicle. Given the limited research on patterns of firearm storage in vehicles, these findings provide novel evidence suggesting that firearm purchases following the March 2020 firearm purchasing surge may have fomented behaviors that increased the likelihood of firearm storage in automobiles. Moving forward, there is a need for additional quantitative and qualitative research that can better understand patterns and motivations of firearm storage in vehicles.

Machine learning downscaling of GRACE/GRACE-FO data to capture spatial-temporal drought effects on groundwater storage at a local scale under data-scarcity

The continued threat from climate change and human impacts on water resources demands high-resolution and continuous hydrological data accessibility for predicting trends and availability. This study proposes a novel threefold downscaling method based on machine learning (ML) which integrates: data normalization; interaction of hydrometeorological variables; and the application of a time series split for cross-validation that produces a high spatial resolution groundwater storage anomaly (GWSA) dataset from the Gravity Recovery and Climate Experiment (GRACE) and its successor mission, GRACE Follow-On (GRACE-FO). In the study, the relationship between the terrestrial water storage anomaly (TWSA) from GRACE and other land surface and hydrometeorological variables (e.g., vegetation coverage, land surface temperature, precipitation, and in situ groundwater level data) is leveraged to downscale the GWSA. The predicted downscaled GWSA datasets were tested using monthly in situ groundwater level observations, and the results showed that the model satisfactorily reproduced the spatial and temporal variations in the GWSA in the study area, with Nash-Sutcliffe efficiency (NSE) correlation coefficient values of 0.8674 (random forest) and 0.7909 (XGBoost), respectively. Evapotranspiration was the most influential predictor variable in the random forest model, whereas it was rainfall in the XGBoost model. In particular, the random forest model excelled in aligning closely with the observed groundwater storage patterns, as evidenced by its high positive correlations and lower error metrics (Mean Absolute Error (MAE) of 54.78 mm; R-squared (R²) of 0.8674). The downscaled 5 km GWSA data (based on random forest) showed a decreasing trend in storage associated with variability in the rainfall pattern. An increase in drought severity during El Niño lengthened the full recovery time of groundwater based on historical storage trends. Furthermore, the time lag between the occurrence of precipitation and recharge was likely controlled by the drought intensity and the spatial recharge characteristics of the aquifer. Projected increases in drought severity could further increase groundwater recovery times in response to droughts in a changing climate, resetting storage to a new tipping condition. Therefore, climate change adaptation strategies must recognise that less groundwater will be available to supplement the surface water supply during droughts.

A New Strategy to Modify Hopfield by Using XOR Operation

تعد شبكة هوبفيلد واحدة من أسهل الأنواع الشبكات العصبية، تركيب الشبكة يكون كل خلية عصبية في الشبكة تتصل بالخلية الأخرى، وبالتالي تسمى الشبكة العصبية المتصلة بالكامل. بالإضافة إلى ذلك، يعتبر هذا النوع ذاكرة ارتباطية تلقائية، نظرًا لأن الشبكة تقوم بإرجاع النمط فور التعرف عليه، فإن هذه الشبكة بها العديد من القيود، بما في ذلك سعة الذاكرة، والتباين، والمتعامد بين الأنماط، والاوزان المتماثلة، والحد الأدنى. هذا البحث يقترح استراتيجية جديدة لتصميم شبكة الهوبفيلد باستخدام عملية XOR ؛ حيث تم اقتراح إستراتيجية جديدة لحل هذه القيود من خلال اقتراح خوارزمية جديدة، باستخدام هذه الاستراتيجية سيزيد من تحسين أداء شبكة الهوبفيلد من خلال تعديل بنية الشبكة، ومراحل التدريب والتقارب ، وان الاستراتيجية المقترحة تعتمد على حجم النمط. و تتجنب تعلم نمط مشابه عدة مرات، و تظهر قابليتها في التعرف على أنماط مشوهة بالضوضاء، وسعة تخزينها غير محدودة وحل مشكلة النمط المعكوس. أظهرت التجارب أن الطريقة المقترحة لها نتائج جيدة من خلال تجنب غالبية قيود شبكة هوبفيلد. بالإضافة إلى ذلك ، يتعلم التعرف على عدد لا حصر له من الأنماط بأحجام مختلفة مع الحفاظ على نسبة ضوضاء مناسبة.

Logjams in a mountain stream network: Patterns, biogeomorphic associations, and anthropogenic impacts

AbstractLogjams, in‐channel accumulations of downed wood, play important roles governing biophysical processes in river ecosystems. In this study conducted in the mountainous inland Pacific Northwest, we leveraged a basin‐scale inventory to carry out a comprehensive analysis of logjam frequency, volume, and their associations with a suite of biophysical landscape characteristics and anthropogenic influences. We complemented this analysis with one that relies on the concept of process domains. We found that logjam frequency increased with drainage area up to ~10–30 km2 and declined thereafter, while the mean jam volume steadily increased downstream up to the area of >300 km2. Combined, these variables yielded a nonlinear downstream pattern of large wood storage in jams, peaking at drainage areas of ~10–100 km2. Logjam characteristics were associated with multiple predictors, used as proxies for biogeomorphic processes relevant for large wood supply and redistribution: bank erosion, landslides, avulsions, wood availability in riparian forest, and wood transport. Additionally, anthropogenic disturbances were inferred to strongly influence logjam‐forming processes in the study basin. A riprapped forest road disrupted a process chain responsible for large wood supply, wherein erosion undercuts slope toe, ultimately triggering landslides. Timber harvest influenced large wood supply by reducing forest biomass. Overall, these findings contribute to improved understanding of logjams: they provide insight into the complex suite of interacting natural and anthropogenic factors which, by regulating large wood inputs and redistribution, generate a basin‐scale pattern in jam frequency and volume. We believe that our study will be useful in informing river management and restoration practices.

Modeling sex-specific whole-body metabolic responses to feeding and fasting

Men generally favor carbohydrate metabolism, while women lean towards lipid metabolism, resulting in significant sex-based differences in energy oxidation across various metabolic states such as fasting and feeding. These differences are influenced by body composition and inherent metabolic fluxes, including increased lipolysis rates in women. However, understanding how sex influences organ-specific metabolism and systemic manifestations remains incomplete. To address these gaps, we developed a sex-specific, whole-body metabolic model for feeding and fasting scenarios in healthy young adults. Our model integrates organ metabolism with whole-body responses to mixed meals, particularly high-carbohydrate and high-fat meals. Our predictions suggest that differences in liver and adipose tissue nutrient storage and oxidation patterns drive systemic metabolic disparities. We propose that sex differences in fasting hepatic glucose output may result from the different handling of free fatty acids, glycerol, and glycogen. We identified a metabolic pathway, possibly more prevalent in female livers, redirecting lipids towards carbohydrate metabolism to support hepatic glucose production. This mechanism is facilitated by the TG-FFA cycle between adipose tissue and the liver. Incorporating sex-specific data into multi-scale frameworks offers insights into how sex modulates human metabolism.

Driving Analysis and Multi Scenario Simulation of Ecosystem Carbon Storage Changes Based on the InVEST-PLUS Coupling Model: A Case Study of Jianli City in the Jianghan Plain of China

The carbon storage capacity of terrestrial ecosystems serves as a crucial metric for assessing ecosystem health and their resilience to climate change. By evaluating the effects of land use alterations on this storage, carbon management strategies can be improved, thereby promoting carbon reduction and sequestration. While county-level cities are pivotal to ecological conservation and high-quality development, they often face developmental challenges. Striking a balance between economic growth and meeting peak carbon emissions and carbon neutrality objectives is particularly challenging. Consequently, there is an urgent need to bolster research into carbon storage management. The study focuses on Jianli City, employing the InVEST model and land use data to examine the response patterns of land use changes and terrestrial system carbon storage from 2000 to 2020. Using the PLUS model, the study simulated the land use and carbon storage in Jianli City for the year 2035 under three scenarios: Natural Development scenario, Urban Expansion scenario, and Ecology and food security scenario. Our findings indicate the following: (1) Between 2000 and 2020, significant shifts in land use were observed in Jianli City. These changes predominantly manifested as the interchange between Cropland and Water areas and the enlargement of impervious surfaces, leading to a decrease of 691,790.27 Mg in carbon storage. (2) Under the proposed scenarios—Natural Development scenario, Urban Expansion scenario, and Ecology and food security scenario—the estimated carbon storage capacities in Jianli City were 39.95 Tg, 39.90 Tg, and 40.14 Tg, respectively. When compared with the 2020 data, all these estimates showed an increase. In essence, our study offers insights into optimizing land use structures from a carbon storage standpoint to ensure stability in Jianli’s carbon storage levels while mitigating the risks associated with carbon fixation. This has profound implications for the harmonious evolution of regional eco-economies.

Assessment of Coastal Carbon Storage and Analysis of Its Driving Factors: A Case Study of Jiaozhou Bay, China

Global climate change and coastal urbanization have significantly impacted the health and carbon storage of coastal zone ecosystems. Investigating the spatial and temporal variations in coastal carbon storage is crucial for developing effective strategies for land management and ecological protection. Current methods for evaluating carbon storage are hindered by insufficient accuracy and data acquisition challenges, necessitating solutions to enhance both reliability and precision. This study aims to assess the variations in carbon storage and annual carbon sequestration in the Jiaozhou Bay coastal zone from 1990 to 2020 and to identify the driving factors by integrating the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) and Carnegie Ames Stanford Approach (CASA) models with remote sensing data and geographic detector methods. The findings suggest that Jiaozhou Bay has experienced a substantial decrease in carbon storage, declining by 17.4% from 1990 to 2020, and annual carbon sequestration, decreasing by 35.5% from 1990 to 2016, but has stabilized recently. Vegetation cover and water bodies play critical roles in regional carbon storage. Furthermore, the dynamics of carbon storage and land use patterns are significantly influenced by socioeconomic factors, including GDP and population density. A comparison of the InVEST and CASA models demonstrates consistency in their carbon storage and annual carbon sequestration assessments. Combining these models in future assessments can enhance the scientific rigor and accuracy of the research, providing more reliable evidence for ecosystem management and policy making.

Evolution and Projection of Carbon Storage in Important Ecological Functional Areas of the Minjiang River Basin, 1985–2050

The alteration of land use and cover (LULC) and the landscape ecological risk index (LERI) significantly impact carbon storage. Examining the carbon storage services in ecologically significant places is crucial for achieving a harmonious relationship between economic development in the region, conservation of terrestrial ecosystems, and mitigation of carbon sink depletion. This study aims to provide a complete framework that integrates the PLUS, Fragstats, and InVEST models. This framework will be utilized to optimize LULC and LERI, specifically maximizing carbon storage. The analysis will be carried out over an extended duration and from various viewpoints. The results indicate that the MJRB ecosystem experienced three clearly defined phases: enhancement (1985–1995), degradation (1995–2010), and subsequent enhancement (2010–2020). The LERI of high-level and carbon storage patterns showed similar trends. The degradation of local terrestrial ecosystems can primarily be due to the widespread use of ecological land caused by socio-economic development. The Ecological Preservation Scenario is projected to increase 41.97 Tg and 115.18 Tg in carbon storage. In contrast, the urban development scenario showed a substantial decrease in carbon storage rates, namely 0.89% and 1.34%, primarily evident in the Chengdu urban zone. An analysis of coupling coordination revealed a negative relationship between carbon storage and high LERI, while a positive connection was observed with low LERI. This study established a framework for rapidly assessing and forecasting the trajectory of carbon storage. It aids in optimizing land use patterns, conserving areas with high carbon sequestration, and ensuring the establishment of high-quality ecosystems. This study serves as a guide for achieving regional “dual carbon” objectives.