Regional Management Strategies Research Articles

A Composite Approach for Evaluating Operational Cloud Seeding Effect in Stratus Clouds

Robust water management is in intense demand in many water scarcity areas, such as arid and semi-arid regions in the world. As part of the regional water management strategy, rain enhancement is vital to replenish groundwater reservoirs, and the key challenge is how to assess its effectiveness. Some recent weather modification experiments attained cloud seeding effect through advanced in situ measurement coupled with accurate numerical simulation. However, there is still a lack of an objective and scientific approach to quantitatively evaluate the rain enhancement effect, especially for many non-randomized operational cloud seeding activities in China. In this study, we proposed a composite evaluation approach by analyzing two operational aircraft cloud seeding cases in stratus clouds in Shaanxi, China. By calculating the aircraft cloud seeding agent plumes, the target areas (as well as the control areas) of cloud seeding were dynamically and roughly determined. Physical properties, such as radar reflectivity and precipitation, were individually quantified in these areas. The cloud seeding effect was then evaluated by calculating the difference in parameter variation between target and control areas. This approach can be applied to qualitative analysis in a single aircraft cloud seeding operation and can also provide quantitative statistical results from multiple cloud seeding cases. We found that the average precipitation enhancement percentage of 18 operational aircraft cloud seeding cases is ~4.84%. Note that the homogeneity hypothesis of the seeding cloud, the error in the calculation of the target area, and the selection of control areas are the major uncertainties likely in the evaluation of the cloud seeding effect by this approach.

Customized Statistically Downscaled CMIP5 and CMIP6 Projections: Application in the Edwards Aquifer Region in South‐Central Texas

AbstractClimate projections are being used for decision‐making related to climate mitigation and adaptation and as inputs for impacts modeling related to climate change. The plethora of available projections presents end users with the challenge of how to select climate projections, known as the “practitioner's dilemma.” In addition, if an end‐user determines that existing projections cannot be used, then they face the additional challenge of producing climate projections for their region that are useful for their needs. We present a methodology with novel features to address the “practitioner's dilemma” for generating downscaled climate projections for specific applications. We use the Edwards Aquifer region (EAR) in south‐central Texas to demonstrate a process to select a subset of global climate models from both the CMIP5 and CMIP6 ensembles, followed by downscaling and verification of the accuracy of downscaled data against historical data. The results show that average precipitation changes range from a decrease of 10.4 mm to an increase of 25.6 mm, average temperature increases from 2.0°C to 4.3°C, and the number of days exceeding 37.8°C (100°F) increase by 35–70 days annually by the end of century. The findings enhance our understanding of the potential impacts of climate change on the EAR, essential for developing effective regional management strategies. Additionally, the results provide valuable scenario‐based projected data to be used for groundwater and spring flow modeling and present a clearly documented example addressing the “practitioner's dilemma” in the EAR.

Identification of High-Quality Vegetation Areas in Hubei Province Based on an Optimized Vegetation Health Index

This research proposes an optimized method for identifying high-quality vegetation areas, with a focus on forest ecosystems, using an improved Vegetation Health Index (VHI). The study introduces the Land Cover Vegetation Health Index (LCVHI), which integrates the Vegetation Condition Index (VCI) and the Temperature Condition Index (TCI) with land cover data. Utilizing MODIS (Moderate Resolution Imaging Spectroradiometer) satellite imagery and Google Earth Engine (GEE), the study assesses the impact of land cover changes on vegetation health, with particular attention to forested areas. The application of the LCVHI demonstrates that forests exhibit a VHI approximately 25% higher than that of croplands, and wetlands show an 18% higher index compared to grasslands. Analysis of data from 2012 to 2022 in Hubei Province, China, reveals an overall upward trend in vegetation health, highlighting the effectiveness of environmental protection and forest management measures. Different land cover types, including forests, wetlands, and grasslands, significantly impact vegetation health, with forests and wetlands contributing most positively. These findings provide important scientific evidence for regional and global ecological management strategies, supporting the development of forest conservation policies and sustainable land use practices. The research results offer valuable insights into the effective management of regional ecological dynamics.

Differences in the seasonal development of perithecia by Neonectria ditissima on apple trees across Northern Europe

AbstractAscospores discharged at rainfall and dispersed by wind can provide long-distance spread of the European canker fungus, Neonectria ditissima. Ascospores are produced by perithecia which are the sexual reproductive stage. Diffuse knowledge exists on the seasonal pattern of perithecium formation under different climatic conditions. Therefore, the development of perithecia was observed for several successive seasons at five sites in three Northern European countries. In Norway and Finland, ripe perithecia were commonly recorded throughout the year, and on individual cankers continuously for up to 28 months. In contrast, asexual reproductive structures (sporodochia) were confined to the growing season in both countries. In Northern Germany an average of 51% of cankers developed ripe perithecia by late winter, and perithecial senescence ensued in late spring. On average, ripe perithecia were present on cankers for 22 weeks. In contrast, sporodochia were observed all year round. The timing of perithecium maturation correlated with the number of days with > 2 mm rainfall in July–September. The presence of mature perithecia and sporodochia for different lengths of time in different countries has implications for regional disease management strategies.

Trend Analysis and Spatial Source Attribution of Surface Ozone in Chaozhou, China

Surface ozone (O3), a critical air pollutant, poses significant challenges in urban environments, as exemplified by the city of Chaozhou in southeastern China. This study employs a novel combination of trend analysis and spatial source attribution techniques to evaluate the long-term dynamics of surface ozone and identify its sources. Utilizing the Kolmogorov–Zurbenko (KZ) filter and percentile regression, we analyzed the temporal trends of daily maximum 8 h moving average ozone (MDA8 O3) concentrations from 2014 to 2023. Our analysis revealed a general long-term downward trend in MDA8 O3 values alongside notable monthly fluctuations, with peak concentrations typically occurring in October and April. Additionally, the percentile regression analysis demonstrated a significant downward trend in MDA8 O3 concentrations across nearly all percentiles, with larger decline rates at higher percentiles, highlighting the effectiveness of local and regional O3 management strategies in Chaozhou. The changes in MDA8 O3 concentrations were mainly influenced by the short-term component, contributing 62.2%, while the contribution of the long-term fraction is relatively small. This suggests a significant influence of immediate meteorological conditions and transient pollution events on local O3 levels. To further elucidate the origins of high O3 concentrations, trajectory cluster analysis, trajectory sector analysis (TSA), and potential source contribution function (PSCF) analysis were conducted. The trajectory cluster analysis revealed that the northeast air mass was the main transport air mass in Chaozhou during the study period, accounting for 39.1% of occurrences. The northeast cluster C with medium-distance trajectories corresponds to higher concentration of O3, which may be the main transport pathway of O3 pollution in Chaozhou. TSA corroborates these findings, with northeast sectors 1, 2, and 3 accounting for 50.3% of trajectory residence time and contributing 52.2% to O₃ levels in Chaozhou. PSCF results further indicate potential high O₃ sources from the northeast, especially in autumn. This comprehensive analysis suggests that Chaozhou’s elevated O3 levels are influenced by both regional transport from the northeast and local emissions. These findings offer crucial insights into the temporal dynamics of surface O3 in Chaozhou, paving the way for more effective and targeted air quality management strategies.

Temporal variation in river ice phenology of the Heilongjiang River in response to climate change

Study regionUpstream of the Heilongjiang River, located in Northeast Asia, is the transboundary river between China and Russia. Study focusUsing long-term hydrological records provided by the Mohe station in combination with multiple statistical approaches, we investigate how river ice phenology of the Heilongjiang River has varied during the period 1957–2016, and quantitatively assess the individual contribution of changes in different climatic factors to such variation in river ice phenology. New insights for the regionWe show the later occurrence for newly formed ice date, ice-on date, and freeze-up date and the earlier occurrence for beak-up date and ice-off date, ultimately leading to a decrease in persistence of river ice in the Heilongjiang River. River ice phenology exhibits a general lag response to climate change, with ranging from 1 to 5 months. Further attribution analysis that explicitly considers time-lag effect suggests that climate change plays a dominant role in regulating river ice phenology. More specifically, compared to other climatic factors, air pressure and maximum and minimum temperature changes have larger contributions to variation in river ice phenology, particularly for the delay of formation time. These findings provide technical basis and beneficial reference to the development of regional river management strategies involved in climate change adaptation framework.

Remote sensing of depth-induced variations in soil organic carbon stocks distribution within different vegetated landscapes

The preservation and augmentation of soil organic carbon (SOC) stocks is critical to designing climate change mitigation strategies and alleviating global warming. However, due to the susceptibility of SOC stocks to environmental and topo-climatic variability and changes, it is essential to obtain a comprehensive understanding of the state of current SOC stocks both spatially and vertically. Consequently, to effectively assess SOC storage and sequestration capacity, precise evaluations at multiple soil depths are required. Hence, this study implemented an advanced Deep Neural Network (DNN) model incorporating Sentinel-1 Synthetic Aperture Radar (SAR) data, topo-climatic features, and soil physical properties to predict SOC stocks at multiple depths (0–30 cm, 30–60 cm, 60–100 cm, and 100–200 cm) across diverse land-use categories in the KwaZulu-Natal province, South Africa. There was a general decline in the accuracy of the DNN model’s prediction with increasing soil depth, with the root mean square error (RMSE) ranging from 8.34 t/h to 11.97 t/h for the four depths. These findings imply that the link between environmental covariates and SOC stocks weakens with soil depth. Additionally, distinct factors driving SOC stocks were discovered in both topsoil and deep-soil, with vegetation having the strongest effect in topsoil, and topo-climate factors and soil physical properties becoming more important as depth increases. This underscores the importance of incorporating depth-related soil properties in SOC modelling. Grasslands had the largest SOC stocks, while commercial forests have the highest SOC sequestration rates per unit area. This study offers valuable insights to policymakers and provides a basis for devising regional management strategies that can be used to effectively mitigate climate change.

A Global Probability‐Of‐Fire (PoF) Forecast

AbstractAccurate wildfire forecasting can inform regional management and mitigation strategies in advance of fire occurrence. Existing systems typically use fire danger indices to predict landscape flammability, based on meteorological forecasts alone, often using little or no direct information on land surface or vegetation state. Here, we use a vegetation characteristic model, weather forecasts and a data‐driven machine learning approach to construct a global daily ∼9 km resolution Probability of Fire (PoF) model operating at multiple lead times. The PoF model outperforms existing indices, providing accurate forecasts of fire activity up to 10 days in advance, and in some cases up to 30 days. The model can also be used to investigate historical shifts in regional fire patterns. Furthermore, the underlying data driven approach allows PoF to be used for fire attribution, isolating key variables for specific fire events or for looking at the relationships between variables and fire occurrence.

Addressing uncertainty in Participatory Integrated Assessment: qualitative modeling approach for risk estimation

Participatory Integrated Assessment (PIA) has become a vital tool for decision-making for sustainable development, but it faces significant challenges due to the inherent uncertainty of socio-ecological systems. Uncertainty arises from multiple sources, such as incomplete data, knowledge gaps, and unpredictable events, which can lead to inadequate risk estimations and potentially undermine the effectiveness of environmental planning efforts. To address these challenges, this study proposes a qualitative modeling approach for risk estimation in PIA. The approach employs Decision Making under Deep Uncertainty (DMDU) to combine qualitative insights and information from stakeholders with available quantitative data. It allows for the exploration of alternative future states of the world and the identification of robust scenarios that promote sustainable development. The effectiveness of the proposed approach is demonstrated through the Ecological Ordinance of Yucatán, Mexico, a policy-making tool for multi-sectoral environmental planning. The study shows how qualitative DMDU can identify critical uncertainties and provide insights into regional management strategies. It also emphasizes the importance of stakeholder engagement and transparency in the decision-making process. Overall, this study presents a promising approach for addressing multiple forms of uncertainty in PIA and improving ecological risk estimation for decision-making in complex socio-ecological systems.

Spatiotemporal pattern of NPP and its response to climatic factors in the Yangtze River Economic Belt

Net primary productivity (NPP) of terrestrial ecosystems serves as a crucial carbon sink, playing a significant role in mitigating climate change. This study, focusing on the Yangtze River Economic Belt (YREB), a key area for both economic development and ecological conservation in China, evaluates the temporal and spatial changes in regional NPP and its responses to climatic factors against the backdrop of global change. Utilizing long-term NPP and meteorological grid data from 1981 to 2017, we analyzed the annual change patterns of NPP and its linear and nonlinear responses to climatic factors using copula functions. Our findings indicate that 57.00 % of the YREB has experienced a significant increase in NPP, with the most substantial decreases observed in Shanghai and its surrounding areas (P < 0.05). Temperature emerged as the primary climatic driver, positively correlating with NPP changes in over half of the study area (P < 0.05). Moreover, the nonlinear response of NPP to temperature and precipitation underscores the complex interactions between these factors, revealing a sensitivity to temperature variations that surpasses that to precipitation. The study also highlights the influence of solar radiation and topographic factors, with a significant positive correlation between NPP and solar radiation observed in 15.85 % of the area (P < 0.05). The practical significance of these findings lies in their implications for regional ecological management and climate resilience strategies. The positive correlation between temperature and NPP underscores the potential for targeted temperature management to optimize carbon sequestration across the YREB. Furthermore, the identified nonlinear responses and the role of solar radiation and topography in influencing NPP offer valuable insights for the formulation of adaptive strategies that enhance ecosystem productivity and contribute to achieving carbon neutrality goals. By elucidating the dynamics of NPP in response to a range of environmental factors, this study provides a foundation for informed decision-making in ecological conservation and climate change mitigation efforts within the YREB and similar regions globally.

Strategi Pengelolaan Lanskap Wisata di Perkampungan Budaya Betawi Setu Babakan Jakarta

Setu Babakan Betawi Cultural Village (PBBSB) is a built landscape to save and maintain Betawi cultural traditions, including religion, culture, and Betawi arts with a community. It is fostered by the culture which includes all the results of ideas and works, both physical and non-physical, such as art, customs, folklore, literature, culinary, clothing, and architecture that are characterized by Betawi. PBBSB is an area designated by the government as a sustainable Betawi cultural preservation area with diverse tourism potential. This research aimed to map the existing conditions, inventory the potential tourist attractions, to calculate the carrying capacity, and to develop a management strategy for the PBBSB area. The research method used descriptive quantitative and qualitative analysis, carrying capacity assessment, and SWOT analysis. Based on the results of the study, the existing condition of the PBBSB area still remained to facilitate the activities that take place in this area, obtained several types of tourism that can attract the attention of visitors to the PBBSB area to realize and learn more about Betawi culture, the value obtained the carrying capacity of PCC &gt; RCC &gt; ECC = 22,923 &gt; 4,031 &gt; 3,084. This value indicates that the current carrying capacity of the PBBSB allows the area to move towards the sustainability of the Betawi cultural preservation area. More over several regional management strategies can be used to preserve the area of Setu Babakan Betawi Cultural Village.

A combined methodological approach to characterize pig farming and its influence on the occurrence of interactions between wild boars and domestic pigs in Corsican micro-regions.

The pig sector in Corsica is based by a wide range of farming systems, mainly characterized on traditional extensive practices, which favor contacts between domestic and wild individuals. These contacts are suspected to influence the maintenance and the transmission of shared infectious diseases between both populations. Therefore, it is important to develop methods that allow to understand and anticipate their occurrence. Modeling these interactions requires accurate data on the presence, location and use of land on pig farms and farming practices, but such data are often unavailable, incomplete or outdated. In this study, we suggest a method to collect and analyze pig farming information that combines approaches from social sciences and epidemiology and enables a spatial representation of an index of potential interaction (IPI) between wild and domestic pigs at municipality level in the Corsican territory. As a first step of the process, interviews were conducted to gather information from 103 pig farms. Then, using hierarchical clustering, we identified five different clusters of pig farming practices which were evaluated and validated by local experts using participatory tools. The five pig farming clusters with their respective estimated levels of direct and indirect interactions with wild boars were combined in a linear equation with pig density to estimate a hypothetical index of potential interaction (IPI) in 155 municipalities. Our results revealed the diversity of pig farming practices across the island of Corsica and pointed out potential hotspots of interaction. Our method proved to be an effective way to collect and update information on the presence and typology of pig farms which has the potential to update official livestock production statistics. The spatial representation of an IPI between wild boars and domestic pigs in the Corsican territory could help design regional disease management strategies and policies to improve the control of certain shared pig pathogens in pig farms from Corsica.

Application of machine learning in the assessment of landslide susceptibility: A case study of mountainous eastern Mediterranean region, Syria

Landslide is a considerable geomorphological risk in terrain systems worldwide. Advanced techniques present a unique tool for predicting landslide susceptibility with unbiased and precise outputs. However, the application of this tool to analyze landslide susceptibility in the eastern Mediterranean landscape is still not sufficiently understood. This study aimed to assess the implementation of three machine learning (ML) algorithms, i.e., support vector machine (SVM), random forest (RF) and extreme gradient boost (XGBoost), in landslide susceptibility mapping in the mountainous area of western Syria. In this regard, 200 landslide events were inventoried from historical data, aerial images and conducted fieldworks. Sixteen triggering factors were selected according to the literature and geographical features (Monsoon period). The receiver operating characteristic (ROC) outcomes revealed that the RF achieved better performance with an area under curve (AUC) of 0.96, pursued by XGBoost and SVM with AUC of 0.94 and 0.90, respectively. This assessment presents an essential understanding of the effective implementation of ML in landslide assessment in the mountainous region of the eastern Mediterranean. We emphasized, hence, that the RF algorithm has the most robust performance of landslide susceptibility prediction in the western Syria. Moreover, the outputs of this study will provide local decision-makers with insights to produce regional management strategies for the landslide, especially after the Syrian war phase.

Carbapenem-resistant Enterobacterales among hospitalized patients in Cape Town, South Africa: clinical and microbiological epidemiology.

Carbapenem-resistant Enterobacterales (CRE) are a substantial problem in Cape Town. CRE epidemiology is largely unknown and mortality remains high. To describe and characterize the clinical and microbiological epidemiology of CRE within Cape Town hospitals to better inform therapy with regard to current and novel antibiotics, as well as improve antimicrobial stewardship (AMS), and infection prevention and control (IPC). This prospective, multicentre study performed between 1 November 2020 and 30 November 2022, across three public and three private hospitals included hospitalized participants with CRE from clinical cultures. Participant demographics, clinical information and microbiology results were collected and analysed. Ninety percent of participants were from public hospitals. The age distribution ranged from 7 days to 88 years. Notable risk factors for CRE infection included recent exposure to antibiotics, medical devices and surgery. The most prevalent species was Klebsiella pneumoniae. However, a higher proportion of Serratia marcescens compared with previous reports was identified. The detected carbapenemases were blaOXA-48-like (80%) and blaNDM (11%). With the exception of amikacin (63%), tigecycline (65%), colistin (95%) and ceftazidime/avibactam (87%), susceptibility to antibiotics was low. This study identified common risk factors for CRE infection and generated a description of carbapenemase enzymes, species distribution and antibiograms, enabling a better understanding of CRE epidemiology. This provides insights into transmission patterns and resistance determinants of CREs, beneficial to informing data-driven regional patient management, AMS and IPC strategies.

REALISASI PENANGANAN PERUBAHAN IKLIM DI INDONESIA MELALUI IMPLEMENTASI SUSTAINABLE DEVELOPMENT GOALS (SDGs): TUJUAN-13.1.3

This article aims to know the realization of handling climate change in Indonesia through the implementation of Sustainable Development Goals (SDGs): Goals-13.1.3 which focuses on implementing regional disaster management strategies in Indonesia in the 2017-2019 period. The method used in this research is a qualitative method and a literature review of various literature discussing handling climate change in Indonesia. The green theory perspective is used in analyzing the realization of Goals-13.1.3 in Indonesia. The research results show that the realization of handling climate change through the implementation of SDGs Goals-13.1.3 falls into the category of anthropocentric understanding and shallow environmental understanding; as well as placing greater emphasis on environmental sustainability by aligning people's consumption levels without excessive consumption; Regular environmental preservation and implementation of regional disaster management strategies will shape sustainable development in Indonesia

Sustainable Regional Straw Utilization: Collaborative Approaches and Network Optimization

The SDGS repeatedly emphasizes the importance of reducing greenhouse gas emissions such as carbon dioxide. The strategic utilization of straw resources to curtail open-air burning not only epitomizes optimal resource deployment but also constitutes a significant stride in environmental preservation and sustainable development. Globally, the imperative of this challenge is increasingly recognized, prompting nations to enhance straw resource utilization technologies, devise regional management strategies, and extend requisite policy support. Regional straw utilization encapsulates a comprehensive concept involving an array of stakeholders including governments, farmers, corporations, brokers, and rural cooperatives, with each one of these uniquely contributing to a multifaceted network that is influenced by their respective resource utilization intentions. This heterogeneity, coupled with the diverse roles of these stakeholders, renders the identification of the pivotal participants and their specific functions within the intricate network. To navigate this complexity, this study employed text analysis and social network analysis, uncovering 30 robust associative rules within this domain. Our findings elucidate that the stakeholder network in regional straw resource utilization exhibits characteristics akin to the NW small-world network model. The key network entities identified include farmers, corporations, governments, and rural cooperatives. Furthermore, the study systematically categorizes the principal entities and elucidates the dynamics of this multi-stakeholder network. This research delineates four developmental models that are pertinent to regional straw resource utilization, which is a framework that is instrumental in pinpointing the accountable parties and optimizing the overarching benefits derived from these resources. The significance of this research lies not only in showcasing the potential of straw resources for environmental conservation but also in underscoring the importance of collaborative strategies and network optimization in order to achieve sustainable development goals.

Recognition of the Specialties of the Kingdom of Yogyakarta and the Practice of Asymmetric Decentralization in Indonesia

Objective: Yogyakarta Palace is a kingdom that existed before Indonesia became independent. Generally, a country can adopt a monarchy as a system of government that applies nationally. However, uniqueness emerged in recognizing the privileges of the Kingdom of Yogyakarta in Indonesia, which still has the authority to regulate its territory but is also under the auspices of the Republic of Indonesia. In response to this phenomenon, this article was created to answer questions regarding (1) a comparison of monarchical systems in the world, (2) the Validity of the Yogyakarta Palace area as a Special Region in Indonesia, and (3) DIY Government Policy Strategy in maintaining and managing the unique features of Yogyakarta. From the results of this analysis, this study aims to provide alternative recommendations for recognizing the kingdom's authority based on practices that occur in Indonesia.&#x0D; &#x0D; Method: The study uses normative juridical research methods with a conceptual and statutory approach. The theory of asymmetric decentralization is the analytical tool used to see the chain of validity of the privileges of the Yogyakarta Palace.&#x0D; &#x0D; Result: The results of the analysis show that the authority of the King of the Yogyakarta Palace to lead the Yogyakarta Special Region Province is a form of asymmetric decentralization practice that is different from the implementation of other monarchical systems in the world.&#x0D; &#x0D; Conclusion: Based on these findings, it can be concluded that a King's authority to regulate his territory does not have to be within the realm of a monarchical system of government. Recognition of the unique features of the Yogyakarta Palace in Indonesia has proven that a kingdom can exist within the territory of a Republic that practices an asymmetric decentralized system. For this reason, further research is needed that can examine unique regional management strategies to strengthen regional autonomy and fiscal independence.

Assessment of rock glaciers and their water storage in Guokalariju, Tibetan Plateau

Abstract. Rock glaciers are important hydrological reserves in arid and semi-arid regions. Their activity states can indicate the existence of permafrost. To help further explore the development mechanisms of rock glaciers in semi-arid and humid transition regions, this paper provides a detailed rock glacier inventory of the Guokalariju (also known as Goikarla Rigyu) area of the Tibetan Plateau (TP) using a manual visual interpretation of Google Earth Pro remote sensing imagery. We also estimated the water volume equivalent (WVEQ) in the study area for the first time. Approximately 5057 rock glaciers were identified, covering a total area of ∼404.69 km2. Rock glaciers are unevenly distributed within the three sub-regions from west to east, with 80 % of them concentrated in the central region, where climatic and topographic conditions are most favorable. Under the same ground temperature conditions, increases in precipitation are conducive to rock glaciers forming at lower altitudes. Indeed, the lower limit of rock glaciers' mean altitude decreased eastward with increasing precipitation. Estimates of the water storage capacity of rock glaciers obtained by applying different methods varied considerably, but all showed the potential hydrological value of rock glaciers. The possible water storage in the subsurface ice of rock glacier permafrost was 1.32–3.60 km3. The ratio between the amount of subsurface ice stored in rock glaciers and surface ice stored in local glaciers falls within the range of 1:2.32 to 1:1.26, with an average ratio of 1:1.69. In the west region, where the climate is the driest, the water storage capacity of rock glaciers was estimated to be up to twice as large as that of the sub-region's glaciers. Changes in water resources and permafrost stability in the area where rock glaciers occur will have implications for regional water resource management, disaster prevention, and sustainable development strategies.

Spatial-temporal heterogeneity in the influence of landscape patterns on trade-offs/synergies among ecosystem services: a case study of the Loess Plateau of northern Shaanxi.

Exploring the role of landscape patterns in the trade-offs/synergies among ecosystem services (ESs) is helpful for understanding ES generation and transmission processes and is of great significance for multiple ES management. However, few studies have addressed the potential spatial-temporal heterogeneity in the influence of landscape patterns on trade-offs/synergies among ESs. This study assessed the landscape patterns and five typical ESs (water retention (WR), food supply (FS), habitat quality (HQ), soil retention (SR), and landscape aesthetics (LA)) on the Loess Plateau of northern Shaanxi and used the revised trade-off/synergy degree indicator to measure trade-offs/synergies among ESs. The multiscale geographically weighted regression (MGWR) model was constructed to determine the spatial-temporal heterogeneity in the influence of landscape patterns on the trade-offs/synergies. The results showed that (1) from 2000 to 2010, the increase in cultivated land and the decrease in forestland and grassland increased landscape diversity and decreased landscape heterogeneity and fragmentation. During 2010-2020, the change range decreased, the spatial distribution was homogeneous, and the landscape diversity and fragmentation in the northwestern area increased significantly. (2) The supply of the five ESs continued to increase from 2000 to 2020. During 2000-2010, FS-SR, FS-LA and SR-LA were dominated by synergies. From 2010 to 2020, the proportion of trade-off units in all relationships increased, and HQ-FS, HQ-SR and HQ-LA were dominated by trade-offs. (3) Landscape patterns had complex impacts on trade-offs/synergies, and the same landscape variable could have the opposite impact on specific trade-offs/synergies in different periods and areas. The results of this study will inform managers in developing regional sustainable ecosystem management strategies and advocating for more research to address ecological issues from a spatial-temporal perspective.

Influence of fiscal decentralization, fintech, and mineral resources on green productivity of G5 countries

The study explores how regional financial autonomy, financial technologies, and resource management strategies intersect to influence sustainable practices and environmental efficiency in G5 economies. The yearly data from 1990 to 2021 has been taken for Canada, Japan, Germany, the United Kingdom, and the United States of America. Empirical analysis of the Cross-sectional Augmented Distributed Lag (CS-ARDL) modeling framework has been performed after a preliminary investigation regarding the variables' cross-sectional dependence, slope heterogeneity, and unit root properties. The outcomes of long-run estimation reveal the positive impact of fintech and revenue decentralization, while mineral resources and expenditure decentralization negatively influence green productivity. Similar results are observed in the short-run; however, their marginal effects are relatively lower. Moreover, the error correction term is negative and significant, indicating an 81.4% speed of adjustment annually to restore the obtained model's equilibrium system. These estimates are validated by the Augmented Mean Group (AMG) and Common Correlated Effect Mean Group (CCEMG) estimators. A bi-directional causality of fintech and revenue decentralization is observed, which offers valuable policy implications.