Mangrove ecosystems support biodiversity, protect coastal areas, and provide sustainable livelihoods. However, they face significant threats from deforestation and unsustainable land use practices. This study examines the viability of the payments for ecosystem services (PES) programs in promoting sustainable mangrove tourism in Tongke-Tongke Village, Sinjai District, South Sulawesi Province, Indonesia. We collected data through household surveys, semi-structured stakeholder interviews, and tourist questionnaires to evaluate the economic value of mangrove tourism and tourists’ willingness to pay (WTP) for conservation. Analytical methods included quantitative descriptive analysis, thematic analysis, travel cost analysis, and contingent valuation method. The results indicated strong community support, with 70.00% of respondents acknowledging sustainable mangrove tourism’s economic, environmental, and cultural benefits. Economic estimates revealed that mangrove tourism generated 943.00 USD/(hm²•a), while tourists’ WTP for conservation ranged from 0.21 to 0.56 USD/(person•month), contributing approximately 11.39 USD/(hm²•a). Despite challenges such as inadequate infrastructure, socioeconomic disparities, and land privatization, this study advocates for integrating the PES programs, enhancing governance frameworks, and fostering local community engagement to ensure equitable benefit distribution and maximize the potential of mangrove tourism. These strategies aim to bolster conservation efforts, improve local livelihoods, and strengthen the resilience of mangrove ecosystems.

Motivated by a significant impact of price volatility on food security and economic stability in Cameroon, this study aims to understand the factors influencing agricultural product price volatility (APPV) and formulate effective policies for mitigating its negative impact and promoting sustainable economic growth. Specifically, this research used the autoregressive distributed lag-error correction model (ARDL-ECM) to analyse the impact of agricultural productivity, agricultural product imports, population, temperature variation, gross domestic product (GDP) per capita, and government expenditure on APPV based on the annual data from 2000 to 2021. The ARDL-ECM estimation results revealed that agricultural productivity (β=4.901), agricultural product imports (β=1.012), population (β=13.635), and GDP per capita (β=2.794) were positively related to APPV, while temperature variation (β= -0.990) and government expenditure (β= -8.585) were negatively related to APPV in the long term. However, temperature variation had a positive relationship with APPV in the short term. Moreover, the Granger causality test showed that there were bidirectional causality of APPV with agricultural productivity and agricultural product imports, and unidirectional causality of APPV with population, temperature variation, GDP per capita, and government expenditure. The findings highlight the importance of public policies in stabilizing agricultural product prices by investing in agricultural research, improving access to agricultural inputs, strengthening farmer capacities, implementing climate adaptation measures, and enhancing rural infrastructure. These policies can reduce APPV, improve food security, and promote inclusive economic growth in Cameroon.

As the world grapples with increasing environmental challenges, innovative technologies are essential for promoting sustainability and accountability. This study examined the impact of environmental performance indices (EPIs) on the growth and investment trends of blockchain-based sustainability-focused companies in 15 countries (Belgium, Czechia, Denmark, Estonia, Finland, France, Germany, Italy, Norway, Poland, Sweden, Spain, Switzerland, the United Kingdom, and the United States) from Europe and America during 2010-2022. This study used the negative binomial regression model to assess the relationship between EPIs and blockchain-based sustainability-focused companies based on the data from the CrunchBase and EarthData. Results indicated that in ecosystem vitality, national terrestrial biome protection efforts were negatively correlated the formation of blockchain-based sustainability-focused companies, while global terrestrial biome protection efforts and marine protected areas had a positive impact on the formation of these companies and the number of funding rounds. In environmental health, PM_2.5 exposure had a positive impact on the number of funding rounds. Conversely, pollutants such as sulfur dioxide (SO₂) and ocean plastics deterred the formation of blockchain-based sustainability-focused companies and reduced the number of funding rounds. In climate change performance, adjusted emission growth rate for carbon dioxide (CO₂), adjusted emission growth rate for F-gases, and adjusted emission growth rate for black carbon had a significantly positive impact on the formation of blockchain-based sustainability-focused companies. Conversely, adjusted emission growth rate for Nitrous Oxide (N₂O) and projected greenhouse gas emissions in 2050 negatively affected the formation of these companies. These findings highlight the dual role of EPIs as driving factors and barriers in the development and investment of blockchain-based sustainability-focused companies in countries from Europe and America.

As urbanization accelerates, rural regions in China are experiencing transformative changes. This study examines the transformation mechanism of modern agricultural villages in the loess hilly and gully regions, using Zhaojiawa Village in Shannxi Province of China as a case study. In this study, we explored the village’s evolution amid China’s rural revitalization efforts, highlighting the transition from a traditional agricultural village to a modern agricultural village in the context of rapid urbanization. This study employed actor-network theory (ANT) to investigate the complex interactions among diverse actors that drive rural transformation. ANT interlinks spatial relationships with intricate social networks. We utilized Google Earth remote sensing images in 2015 and 2021 and interview data to construct ANT. Three key dimensions of rural transformation are identified: economic structure transformation, social relationship reorganization, and spatial layout reconstruction. The transformation mechanism in Zhaojiawa Village is underpinned by a network of diverse actors, both human and non-human, aligned around two pivotal stages of agricultural village development (i.e., construction stage and development stage). In the initial construction stage, the Suide County government led a complex actor network to enhance rural living and production spaces. In the development stage, the village committee emerged as a central actor, with increased participation from villagers and external enterprises, facilitating the creation of a multifunctional space. The evolving goals and roles of these key actors contributed to the reconfiguration of the actor network, promoting rural transformation. These insights are applicable to other ecologically vulnerable and economically challenged rural areas in the loess hilly and gully regions, suggesting that collaboration among stakeholders can effectively facilitate the transition to specialized and integrated industries, thereby fostering rural revitalization.

Poverty remains one of the most pressing global challenges of this era, affecting millions of people across both developing and developed countries. The poverty alleviation resettlement (PAR) is a policy with Chinese characteristics for eradicating poverty. By integrating the Maslow’s Hierarchy of Needs and Amartya Sen’s Capability Approach, this study developed a theoretical framework to analyze the factors influencing the well-being of poverty alleviation migrants (PAMs). A telephone survey conducted between July and August 2022 in Hubei Province, Guizhou Province, Shaanxi Province, and Chongqing Municipality of China yielded 259 valid questionnaires. Using the partial least squares-structural equation modeling (PLS-SEM), this study revealed that financial accessibility, health level, living conditions, and social networks significantly enhanced the well-being of PAMs, with living conditions having the strongest impact on the well-being of PAMs. Furthermore, the factors affecting well-being varied across age groups. Social networks played a more significant role in the elderly group, whereas health level had a greater impact on the young and middle-aged group. These findings deepen the understanding of the PAR and its effects on the well-being of PAMs, offering valuable insights for policy-makers and practitioners to refine poverty alleviation strategies and enhance social welfare.

Growing climate change concerns have intensified the focus on agribusiness sustainability, driving an urgent energy transition to improve production efficiency and mitigate environmental harm. The complex interplay between energy efficiency and energy consumption highlights the essential role of strategic energy policies in ensuring sustainable development. This study used the Double-Log regression model with bootstrap resampling to examine the rebound effect in the energy transition of agribusiness focusing on five Latin American countries including Brazil, Argentina, Uruguay, Colombia, and Mexico based on the agricultural sector data during 2010-2022. The findings revealed that the rebound effect significantly influences energy transition, with varying degrees of impact across agricultural sectors. This study identified partial rebound effect across all five countries, with elasticity coefficient varying from 9.63% (Colombia’s coffee sector) to 89.12% (Brazil’s livestock sector). In Brazil’s sugarcane sector, non-renewable energy, agricultural employment, and irrigation efficiency were identified as key factors influencing energy consumption, while in livestock sector, energy consumption was affected by CH₄ emissions, income and well-being of farmers, water consumption, and water conservation practices. In Mexico’s livestock sector, CH₄ emissions, non-renewable energy, and water conservation practices were the key factors affecting energy consumption. In Argentina’s sugarcane sector, pesticides, NO₂ emissions, renewable energy, and agricultural employment were the key factors affecting energy consumption, while renewable energy, income and well-being of farmers, and water consumption were the key factors affecting energy consumption in livestock sector. In Uruguay’s livestock sector, non-renewable energy, income and well-being of farmers, and irrigation efficiency were the key factors affecting energy consumption. In Colombia’ coffee sector, NO₂ emissions and irrigation efficiency were identified as key factors influencing energy consumption. Finally, this study reinforces the importance of aligning energy transition with Sustainable Development Goals (SDGs), ensuring that energy efficiency gains do not inadvertently increase energy consumption or environmental degradation.

The use of renewable energy is an important way to achieve sustainable agricultural and economic development. However, there are differences in access to renewable energy between the Global North and Global South. This study utilised an autoregressive distributed lag-error correction model and the data spanning from 1991 to 2021 to comparatively analyse the dynamic relationship among renewable energy consumption, the value of agricultural production, gross domestic product (GDP), economic diversification index, urban population, the total water extraction for agricultural withdrawal, and trade balance in the Netherlands and South Africa. In the short run, renewable energy consumption was increased by the value of agricultural production but decreased by GDP in South Africa. In the long run, renewable energy consumption and GDP increased the value of agricultural production, while the value of agricultural production also increased GDP in South Africa. However, in the Netherlands, there was no short- and long-run relationship between renewable energy consumption and agricultural and economic development. The results revealed that there was a short- and long-run relationship in South Africa. Moreover, in the Netherlands, the adjustment speed was -1.46 for renewable energy consumption with an error correction of 0.68 a (8.22 months). In South Africa, the adjustment speed was -1.28 for renewable energy consumption with an error correction of 0.78 a (9.38 months). Therefore, compared to South Africa, renewable energy consumption in the Netherlands takes less time to return to balance after a shock. These findings signify different trajectories on sectoral and economic transition initiatives spurred using renewable energy between the Netherlands and South Africa. Policy relating to initiatives such as “agro-energy communities” in Global South countries such as South Africa should be emphasised to promote the use of renewable energy in the agricultural sector.

Road transport plays a crucial role in facilitating mobility and the movement of goods, particularly in the Extended Bangkok Metropolitan Region (EBMR), Thailand. This area is undergoing rapid industrialization and urbanization, resulting in significant energy consumption and greenhouse gas (GHG) emissions. This study examined the relationships among individual socioeconomic factors, travel characteristics, and energy consumption characteristics and their impacts on GHG emissions from road transport. The path analysis technique was applied to identify the key driving factors and their causal relationships. The data were collected through 1600 questionnaire surveys with road drivers in representative areas of the EBMR from December 2022 to May 2023. The results revealed that individual socioeconomic factors significantly influenced GHG emissions from road transport. Among the drivers, factors such as income, age, education, and driving experience indirectly influenced travel characteristics and energy consumption characteristics, impacting GHG emissions. Similarly, individual socioeconomic factors affected the travel characteristics of tourists and personal travelers. Driving experience was a crucial factor for public road transport and freight vehicle drivers, influencing travel characteristics and contributing to GHG emissions. These findings highlight the importance of key policy recommendations, such as promoting the adoption of electric vehicles, optimizing public transport, incentivizing low-emission tourism, and modernizing freight transport with clean technologies, to enhance efficiency, reduce emissions, and support regional sustainability. This study provides policy-makers with insights into the key factors influencing GHG emissions across different driving factors, revealing how individual socioeconomic factors impact travel characteristics and energy consumption characteristics. The findings will inform the development of targeted emission reduction strategies and sustainable transport policies.

The intersection of economic development, energy dynamics, environmental policy, and environmental sustainability presents complex challenges for European Union (EU) countries. This study investigated the impact of environmental taxes, hydroelectricity consumption, economic globalization, and gross domestic product (GDP) on the load capacity factor (LCF) in the 10 EU member countries (including Austria, Finland, France, Germany, Italy, Poland, Portugal, Slovakia, Spain, and Sweden) using data from 1995 to 2020. To ensure the reliability and validity of the data, this study applied several advanced econometric tests, including the Pesaran and Yamagata slope heterogeneity test, Pesaran cross-sectional dependence (CSD) test, second-generation unit root test, and Westerlund cointegration test. The data showed important statistical issues such as slope heterogeneity across panels, CSD, mixed-order unit root structures, and long-run associations between variables. To address these issues, we applied an augmented mean group (AMG) model as the main regression approach, and used the pooled mean group-autoregressive distributed lag (PMG-ARDL) method to check the robustness. Specifically, the AMG results indicate that a 1.000% rise in hydroelectricity consumption results in a 0.048% rise in the LCF, while a 1.000% increase in environmental taxes leads to a 0.175% increase in the LCF. Contrary to this, a 1.000% increase in economic globalization results in a 0.370% decrease in the LCF, and a 1.000% increase in GDP leads to a 0.850% decrease in the LCF. Environmental taxes have a more beneficial impact on the environment, and GDP has the most detrimental effect. The findings provide empirical evidence on the role of environmental taxes, hydroelectricity consumption, economic globalization, and GDP in driving the LCF. Additionally, the findings provide valuable information to policy-makers, academicians, and stakeholders shaping energy and environmental policies in the 10 EU member countries.

As the impact of climate change intensifies, climate migration (climate change-induced migration) has become a pressing global issue that requires effective adaptation strategies to lessen its effects. Therefore, this study delved into the complex relationship between climate change adaptation strategies and climate migration with food insecurity serving as a mediating factor. We collected sample data through face-to-face interviews in Khorramabad City, Iran from February to May in 2023. Using the Structural Equation Modeling (SEM), we explored how food insecurity influences the relationship between climate change adaptation strategies and climate migration. The findings showed that while climate change adaptation strategies can boost community resilience, their success is closely tied to levels of food insecurity. About 78.72% of the surveyed households experienced certain levels of food insecurity, increasing the risk of displacement due to climate-related disasters. Climate change adaptation strategies including economic strategies, irrigation management strategies, organic-oriented strategies, sustainable development-oriented strategies, and crop variety management strategies played a significant role in reducing climate migration. Moreover, we found that climate change adaptation strategies not only impact food security, but also shape migration decisions. This research underscores the importance of an integrated approach that links climate change adaptation strategies, climate migration, and food insecurity. This study emphasizes the importance of food security for formulating sustainable adaptation strategies.

Urbanization in small- and medium-sized cities has often been overlooked in urban studies. Research on urbanization has predominantly focused on large metropolitan cities; however, urbanization in small- and medium-sized cities also contributes to the acceleration of urban sprawl. Urban growth boundary (UGB) is an ecological approach designed to limit urban development. This study aimed to analyze environmental protection priority zones by combining ecological quality and sensitivity indices to identify the areas suitable for UGB implementation. Tegal City and its surrounding areas (including Tegal and Brebes regencies) of Indonesia were selected as the study area. The ecological quality index was calculated using the normalized difference vegetation index, humidity index, land surface temperature, and normalized difference bare soil index. These indices were subsequently subjected to principal component analysis (PCA) to extract orthogonal factors, which were summed to derive the final index value. In parallel, we mapped and evaluated ecological sensitivity based on spatial planning policies and regulations. The results revealed that ecological quality in Tegal and Brebes regencies was predominantly categorized as good and very good ecological quality, whereas Tegal City exhibited moderate and poor ecological quality. Additionally, over 45.00% of the area in Tegal and Brebes regencies demonstrated very high ecological sensitivity. Consequently, more than 50.00% of the area in Tegal and Brebes regencies, along with 27.00% of Tegal City, were classified as ecological constraint zone, making them potential regions for UGB development. The UGB is expected to curtail urban expansion, promote compact city planning, and preserve ecosystem services to achieve urban sustainability. This study implies that planning small- and medium-sized cities is important to prevent urban sprawl and maintain environmental health. Designing UGB to limit urban expansion should be enhanced by better knowledge about its ecological functions in supporting urban sustainability.

The social progress index (SPI) measures social and environmental performance beyond traditional economic indicators, providing transparent and actionable insights into the true condition of societies. This study investigates the interdependencies among SPI components and their impact on country-level sustainability performance. Using a Bayesian Belief Network (BBN) approach, the analysis explores the interdependencies among 12 SPI components (including advanced education, basic education, environmental quality, freedom and choice, health, housing, inclusive society, information and communications, nutrition and medical care, rights and voice, safety, and water and sanitation) and their collective influence on sustainability performance. Data from the Sustainable Development Report and SPI datasets, covering 162 countries (including Australia, China, United Arab Emirates, United Kingdom, United States, and so on), were used to assess the relative importance of each SPI component. The key findings indicate that advanced education, inclusive society, and freedom and choice make substantial contributions to high sustainability performance, whereas deficiencies in nutrition and medical care, water and sanitation, and freedom and choice are associated with poor sustainability performance. The results reveal that sustainability performance is shaped by a network of interlinked SPI components, with education and inclusion emerging as key levers for progress. The study emphasizes that targeted improvements in specific SPI components can significantly enhance a country’s overall sustainability performance. Rather than visualizing countries’ progress through composite indicator-based heat maps, this study explores the interdependencies among SPI components and their role in sustainability performance at the global level. The study underscores the importance of a multidimensional policy approach that addresses social and environmental factors to enhance sustainability. The findings contribute to a deeper understanding of how SPI components interact and shape sustainable development.

The rapid acceleration of global warming and intensifying human activities have exacerbated the fragility and climate sensitivity of ecosystems worldwide, particularly in arid regions. Vegetation, a key component of ecosystems, is critical in enhancing the ecological environment. The Ertix River Basin (ERB) is a transboundary watershed that spans multiple countries, mostly in arid regions. However, research on the fractional vegetation coverage (FVC) and its driving factors in the ERB remains limited. Investigating the spatiotemporal changes in the FVC and its relationship with various factors in the ERB can offer scientific support for optimizing regional vegetation restoration policies and promoting the coordinated development of human-environment interactions. The Moderate-resolution Imaging Spectroradiometer (MODIS) MYD13Q1 V6 data were obtained via the Google Earth Engine platform, and methods including the pixel dichotomy method, Theil-Sen median trend analysis, and Mann‒Kendall test were employed to examine the spatiotemporal dynamics of the FVC in the ERB from 2003 to 2023, with future trend forecast using the Hurst index. The impacts of natural and socioeconomic factors on the FVC were evaluated through the partial least squares-structural equation model (PLS-SEM). The results indicated that the FVC in the ERB showed a slight degradation trend with an average annual decrease of 0.046% during 2003-2023, with significant changes occurring in 2004, 2010, and 2019. Spatially, 53.380% of the study area was degraded, and the change in the FVC increased gradually from southeast to northwest. The FVC in 63.000% of the study area was highly stable and displayed long-term persistence; and the direct impact of natural factors (path coefficient of 0.617) on the FVC was significantly higher than that of socioeconomic factors (0.167). Among the natural factors, precipitation (0.999) was the most significant. This study reveals the significant impacts of natural and socioeconomic factors on vegetation dynamics in arid regions, and provides a scientific basis for transnational ecological conservation.

Desertification poses a significant ecological threat to global sustainability, notably within arid regions such as the Tarim Basin surrounding the extensive Taklimakan Desert in Northwest China. This study used the Google Earth Engine (GEE) platform and Random Forest (RF) to analyze multi-temporal Landsat images to reveal desertification dynamics in the Tarim Basin spanning from 1990 to 2020. The results showed that land use types of the Tarim Basin were classified into three types: artificial oases, natural oases, and desertified land. To robustly quantify the spatiotemporal dynamics of land use, we introduced the Desertification Change Index (DCI), a novel metric specifically designed to measure the transformation sensitivity of land use types. Our analysis demonstrated that from 1990 to 2020, artificial oases showed a continuous increasing trend, while desertified land decreased significantly. Natural oases decreased during 1990-2000, then continued to grow, and showed a decreasing trend again after 2015. Moreover, natural oases have mainly been converted into desertified land and artificial oases. Artificial oases were mainly converted into natural oases, and most of desertified land was converted into natural oases. Regions with significant oasis expansion (DCI=2) were mostly concentrated within the influence radius of artificial oases. In contrast, regions with significant oasis degradation (DCI= -2) were generally farther from artificial oases. Finally, this study found that the changes in land use types of the Tarim Basin are mainly driven by human activities, which play a dual role—mitigating desertification by controlling oasis expansion and exacerbating desertification through unsustainable resource utilization. Ultimately, this research provides essential insights for policy-makers and land managers aiming to devise adaptive and sustainable desertification control measures in the Tarim Basin and similarly arid regions globally.

Digital transformation, as a recent trend in socioeconomic development, is considered as a critical pathway for urban carbon reduction because of its potential to increase productivity and energy efficiency. However, few studies have explored the relationship between urban digitalization and carbon emissions (CE). Therefore, this study systematically analyzed the spatiotemporal distribution and interaction mechanism between digitalization and CE in the Yangtze River Delta (YRD) urban agglomerations of China during 2006-2020 based on a multidimensional indicator system, including digitalization industry level, digitalization application level, and urban green digitalization willingness. The findings revealed that both digitalization and CE in the YRD exhibit a significant and synchronously evolving “core-periphery” spatial pattern. Core cities generated substantial positive spillover effect on periphery cities through technology diffusion and policy demonstration, advancing both regional digitalization and the collaborative governance of CE. However, digitalization had dual impact on CE. On the one hand, it promoted the reduction of CE by enhancing energy efficiency, optimizing industrial structures, and promoting the application of green technologies. On the other hand, the expansion of digital infrastructure introduced a potential risk of increased energy consumption. Therefore, targeted policy recommendations are proposed to facilitate the coordination of environmental sustainability and digitalization in the YRD. This study provides empirical support and policy insights for advancing the coordinated development of regional digital transformation and green low-carbon initiatives.

Tajikistan represents a core region of the biodiversity hotspot in Central Asian mountains and has exceptional vascular plant diversity. However, the species diversity of the country faces urgent conservation challenges. There has been a lack of a comprehensive and multidimensional assessment to inform strategic conservation planning. Therefore, this study integrated 4 key biodiversity indices including species richness (SR), phylogenetic diversity (PD), threatened species richness (TSR), and endemic species richness (ESR) to map species diversity distribution patterns, identify conservation gaps, and elucidate their effects of climatic factors. This study revealed that species diversity shows a clear trend of decreasing from the western region to the eastern region of Tajikistan. The central-western mountains (specifically the Gissar-Darvasian and Zeravshanian regions) emerge as irreplaceable biodiversity hotspots. However, we found a severe spatial mismatch between these priority areas and the existing protected areas (PAs). Protection coverage for all hotspots was alarmingly low, ranging from 31.00% to 38.00%. Consequently, a critical 64.80% of integrated priority areas fall outside of the current PAs, representing a major conservation gap. This study identified precipitation seasonality and isothermality as the principal drivers, collectively explaining over 50.00% of the diversity variation and suggesting high vulnerability to hydrological shifts. Furthermore, we detected significant geographic sampling bias in the public biodiversity databases, with the most critical hotspot being systematically under-sampled. This study provides a robust scientific basis for conservation action, highlighting the urgent need to strategically expand PAs in the under-protected southwestern region and to mitigate critical sampling gaps through targeted data digitization and field surveys. These measures are indispensable for securing Tajikistan’s unique biodiversity and achieving the Kunming-Montreal Global Biodiversity Framework Target 3 (“30×30 Protection”).

Tajikistan, a mountainous country and a vital water tower for Central Asia, is becoming increasingly vulnerable to snow drought under climate change, threatening its snow- and glacier-fed streamflow. Yet, the impacts of snow drought on the regional hydrology remain insufficiently understood. In this study, we integrated multisource data, including the Fifth Generation European Centre for Medium-Range Weather Forecasts Atmospheric Reanalysis for Land Applications (ERA5-Land) data and hydrological station data, to systematically assess the snow drought patterns and their impacts on streamflow during 1950-2023. We identified snow drought events based on precipitation and snow fraction anomalies relative to climatological means and classified them into warm snow drought, dry snow drought, and warm&dry snow drought. The results revealed that snow drought was a recurrent phenomenon, occurring in 51.70% of the years during the study period, with warm&dry snow drought accounting for 21.90% of the total events. Both the frequency and severity exhibited pronounced spatial variability, largely governed by the elevation and snowfall fraction. Specifically, the frequency of warm snow drought was negatively correlated with the snowfall fraction, decreasing on average by 0.20 per unit increase in snowfall fraction, whereas the frequency of dry snow drought was positively correlated, increasing by 0.07 per unit increase. The streamflow analysis results demonstrated that snow drought typically reduced the warm-season discharge by 5.00%-18.00% in certain rivers, thereby exacerbating the water stress during the dry season. The results of this study advance our understanding by explicitly linking the types of snow drought to hydrological responses in Central Asia’s high mountains, providing a scientific basis for climate adaptation and sustainable water resource management in Tajikistan.

Households in western Ethiopia are experiencing food insecurity driven by the effects of climate change. Hence, there is an opportunity to lessen the consequences of climate change by adopting climate-smart agriculture (CSA). The study involved 385 households from western Ethiopia during the 2023-2024 production period. Specifically, we examined the variables that affect adoption decisions and investigated how the combined adoption of CSA practices affects maize yield. The multinomial endogenous switching regression (MESR) model was used to analyze these factors. The results showed that the adoption of CSA practices is positively impacted by age, gender, farm size, and education, but the distances from the household residence to market and plot have a negative impact. Adopters of CSA practices achieved a greater average yield per hectare than the non-adopters. Specifically, agroforestry, crop diversification, and adjusted planting dates all considerably increased maize yield, with gains of 0.21, 0.70, and 0.52 t/hm², respectively, compared to non-adoption. The implementation of combined CSA practices, rather than a single CSA practice, is a great way to mitigate the negative impacts of climate change. Therefore, we recommend ensuring adequate funding, providing incentives, facilitating technical assistance, and fostering community involvement when implementing combined CSA practices. This information is essential for reducing the negative consequences of climate change and developing successful adaptation strategies.

The hydrological system in Central Asia is highly sensitive to global climate change, significantly affecting water supply and energy production. In Tajikistan, the Vakhsh River—one of the main tributaries of the Amu Darya—plays a key role in the region’s hydropower and irrigation. However, research on long-term hydrological changes in its two top large basins—the Surkhob and Khingov river basins—remains limited. Therefore, this study analyzed long-term climate and hydrological changes in the Vakhsh River, including its main tributaries—the Surkhob and Khingov rivers—which are vital for the water resource management in Tajikistan and even in Central Asia. Using long-term hydrometeorological observations, the change trends of temperature (1933-2020), precipitation (1970-2020), and runoff (1940-2018) were examined to assess the impact of climate change on the regional water resources. The analysis revealed the occurrence of significant warming and a spatially uneven increase in precipitation. The temperature changes across three climatic periods (1933-1960, 1960-1990, and 1990-2020) indicated that there was a transition from baseline level to accelerated warming. The precipitation showed a 2.99 mm/a increase in the Khingov River Basin and a 2.80 mm/a increase in the Surkhob River Basin during 1970-2020. Moreover, there was a gradual shift toward wetter conditions in recent decades. Despite the relatively stable annual mean runoff, seasonal redistribution occurred, with increased runoff in spring and reduced runoff in summer, due to the compensation of glacier melting. Moreover, this study forecasted runoff change during 2019-2040 using the exponential triple smoothing (ETS) method and revealed the occurrence of alternating wet and dry phases, emphasizing the sensitivity of the Vakhsh River Basin’s hydrological system to climate change and the necessity of adaptive water resource management in mountainous regions of Central Asia. Therefore, this study can provide evidence-based insights that are critical for future water resources planning, climate-resilient hydropower development, and regional adaptation strategies in climate-vulnerable basins in Central Asia.

The Kulpawn River Basin (KRB) plays a critical role in supporting rural livelihoods through agriculture, water supply, and biodiversity conservation. However, between 1995 and 2023, significant land use and land cover (LULC) changes have been observed, affecting ecosystem services (ESs). This study evaluated the ecosystem service values (ESVs) associated with LULC changes. The random forest algorithm was applied to extract LULC information from Landsat images for 1995, 2005, 2015, and 2023. The benefit transfer method was employed to estimate the ESVs over the study period. Questionnaires were also used to assess the views of respondents on the drivers of the ES changes in the basin. The results showed that agricultural lands expanded by 14.14%, built-up areas by 15.17%, and light savannah forest by 8.73%, while dense savannah forest and water bodies declined by 25.71% and 20.00%, respectively. The total estimated ESV was 410.09×10⁸, 362.92×10⁸, 335.30×10⁸, and 319.28×10⁸ USD/(hm²·a) in 1995, 2005, 2015, and 2023, respectively, indicating that the total ESV declined from 410.09×10⁸ USD/(hm²·a) in 1995 to 319.28×10⁸ USD/(hm²·a) in 2023. The study concludes that the reduction in ESVs is due to the LULC changes resulting from agricultural activities, expansion of built-up areas, population sprawl, and artisanal mining activities. Hence, there is an urgent need to develop programs and strategies to mitigate and curtail the degradation of LULC and ESVs in the basin. These findings reveal a growing ecological vulnerability, threatening water security and rural livelihoods. The study offers valuable insights to guide sustainable land use planning and ecosystem conservation strategies.

Since the United Nations launched the Sustainable Development Goals (SDGs) in 2015, global implementation has steadily advanced, yet prominent challenges persist. Progress has been uneven across regions and countries, with Tajikistan representing a typical example of such disparities. Based on 81 SDG indicators for Tajikistan from 2001 to 2023, this study applied a three-level coupling network framework: at the microscale, it identified synergies and trade-offs between indicators; at the mesoscale, it examined the strength and direction of linkages within four SDG-related components (society, finance, governance, and environment); and at the global level, it focused on the overall SDG interlinkages. Spearman’s rank correlation, sliding window method, and topological properties were employed to analyze the coupling dynamics of SDGs. Results showed that over 70.00% of associations in the global SDG network were of medium-to-low intensity, alongside extremely strong ones (|r| value approached 1.00, where r is the correlation coefficient). SDG interactions were generally limited, with stable local synergy clusters in core livelihood sectors. Network modularity fluctuated, reflecting a cycle of differentiation, integration, and fragmentation, while coupling efficiency varied with the external environment. Each component exhibited distinct functional characteristics. The social component maintained high connectivity through the “poverty alleviation-education-healthcare” loop. The environmental component shifted toward coordinated eco-economic governance. The governance-related component broke interdepartmental barriers, while the financial component showed weak links between resource-based indicators and consumption/employment indicators. Tajikistan’s SDG coupling evolved through three phases: survival-oriented (2001-2012), policy integration (2013-2018), and shock adaptation (2019-2023). These phases were driven by policy changes, resource industries, governance optimization, and external factors. This study enriches the analytical framework for understanding the dynamic coupling of SDGs in mountainous resource-dependent countries and provides empirical evidence to support similar countries in formulating phase-specific SDG promotion strategies.

Agriculture extension and advisory services (AEAS) are integral to smart agricultural systems and play a pivotal role in supporting sustainable agricultural development. The study aimed to assess the role of AEAS in strengthening climate-smart coastal farming system to enhance coastal agricultural sustainability. A mixed-methods study was conducted in the southwestern coastal region of Bangladesh in 2023, which involved administering a structured questionnaire and conducing face-to-face interviews with 390 farmers. Perceived role index (PRI) was employed to assess the potential role of AEAS. To forecast the perceived role outcomes, the machine learning model was undertaken by utilizing suitable algorithms. Additionally, feature importance was calculated to underpin the significant factors of perceived role outcomes. The findings showed that coastal farming communities held a comprehensive understanding of the role of AEAS. Key roles included diffusion of agricultural innovations, acting as a bridge between farmers and research organizations, using demonstration techniques to educate farmers, training farmers on food storage, processing, and utilization, and promoting awareness and adoption of best practices. The machine learning model exposed a significant relationship between farmers’ socio-economic characteristics and their perception behavior. The results identified that factors like innovativeness, awareness, training exposure, access to AEAS, and access to information significantly influenced how farmers perceived the efficacy of AEAS in promoting a smart coastal farming system. However, farmers confronted multiple constraints in receiving demand-driven services and maintaining coastal farm sustainability. These insights can guide concerned authorities and policy-makers in providing AEAS for the purpose of strengthening climate-smart coastal farming system, particularly with a special focus on capacity building programs and machine learning application. Moreover, the outcomes of this study can assist the authorities of similar coastal systems throughout the world to initiate potential strategies for enhancing region-specific agricultural sustainability.

Climate change has emerged as an important global issue, primarily driven by human activities, affecting ecosystems, societies, and economies worldwide. This review employed a comprehensive narrative analysis that incorporates expertise from policy studies, environmental science, and economics. Targeted keywords are used to systematically search major academic databases. This article explores various aspects of climate change, economic consequences, and the evolving discourse on climate risk. It addresses the association between climate change and several economic variables, such as gross domestic product (GDP), foreign direct investment (FDI), and financial markets. The review highlights the complex relationship among physical risks, transition risks, and approaches to cope with climate change. It examines global climate policies such as the Kyoto Protocol and Paris Agreement. This study also investigates climate risk assessment models like Integrated Assessment Models (IAMs) and how they help understand the economic effect of climate change. Moreover, it explores ways to adapt to and reduce climate change, such as carbon taxes and subsidies. This review focuses on the critical importance of instruments like the Climate Action Tracker in evaluating national and global climate change responses, which serve as a framework for assessing policy effectiveness and progress toward emission targets. By integrating different viewpoints from economics, environmental science, and governance, this review underscores the value of coordinated global action to address the challenges posed by climate change.

Based on monthly runoff and climate datasets spanning 2000-2024, this study employed the Theil-Sen’s slope estimation, Mann-Kendall (M-K) trend test, as well as Pearson correlation and Spearman rank correlation analyses to systematically examine the spatiotemporal patterns of runoff and its climatic driving mechanisms across Tajikistan, providing a scientific basis for sustainable water resource utilization and management in the study area. Results indicated that during 2000-2024, the annual runoff in Tajikistan exhibited statistically non-significant long-term trend (P=0.76), while displaying pronounced seasonal variability and strong spatial heterogeneity. Spring and summer average runoff primarily exhibited slight declining tendencies, while winter average runoff exhibited pronounced reduction in localized regions, such as the Syr Darya Basin, the Vakhsh River Basin, and the lower reaches of the Zeravshan River Basin. Precipitation emerged as the dominant positive driver of runoff, exhibiting moderate to strong positive correlations across over 78.00% of the country, whereas potential evapotranspiration consistently functioned as a negative driver. Rising temperatures exerted a dual competitive effect on runoff: in high-elevation, glacier-covered regions, rising temperatures temporarily increased runoff by accelerating glacier melt; however, at the national scale, the negative impact of rising temperature on runoff has played a slightly dominant role to a certain extent by enhancing evapotranspiration. Collectively, these results indicated that the present stability of runoff in Tajikistan is strongly dependent on the short-term compensatory effects of glacier melt and the risk of future runoff decline is likely to intensify as glacier reserves continue to diminish. This study provides a critical scientific evidence to inform sustainable water resource management in Tajikistan and underscores the need for glacier conservation and integrated water resource management strategies.

Rapid growth in nature-based and super-premium tourism has increased environmental pressures on protected destinations such as Labuan Bajo and Komodo National Park (KNP) in Indonesia, raising concerns about biodiversity conservation and responsible visitor behavior. Understanding how visitors value and support green tourism initiatives is therefore essential for designing effective and acceptable sustainability policies. This study explores visitor preferences and willingness to pay (WTP) for green tourism initiatives in Labuan Bajo and KNP, a renowned super-premium tourism destination in Indonesia. A choice experiment was employed to ascertain which green tourism options visitors prioritize. A total of 600 visitors completed surveys presenting different tourism scenarios. The data were then analyzed using statistical models to estimate to what extent visitors are willing to pay for each option. The study’s primary focus was on five key aspects: green hotels, sustainable transportation, locally sourced products, environmental footprint reduction, and communication with locals. Three hypothetical scenarios were developed: Scenario 1 with a focus on eco-friendly accommodations; Scenario 2 with an emphasis on sustainable transportation and local engagement; and Scenario 3 with comprehensive green tourism initiatives. The findings showed robust support from visitors and clear WTP for programs such as green hotels, public transport, local food, and improved waste management. The findings also highlighted the significance of enhancing awareness regarding the protection of Komodo dragons and marine ecosystems as part of sustainable tourism. This study significantly contributes to the literature by quantifying visitor preferences within a United Nations Educational, Scientific and Cultural Organization (UNESCO) world heritage site and shows the potential for policies that support environmentally and socially responsible tourism in biodiversity-rich areas.

Climate change may have detrimental effects on different sectoral growth in global economy and according to the Intergovernmental Panel on Climate Change, the impacts of climate change will be more vigorous in the coming years. The climatic and non-climatic driving forces behind the economic sectoral performances involve short- and long-run interconnections among variables. This study attempts to investigate the effect of climatic factors (temperature and precipitation) along with non-climatic factors, including foreign direct investment (FDI), human capital index (HCI), natural capital (NC), and information and communication technology (ICT) on three major sectors of the economy (agricultural sector, industrial sector, and service sector) through non-linear model framework by employing cross-sectionally augmented autoregressive distributed lag (CS-ARDL) estimation technique. It considers a panel of 56 selected countries from different income groups, including high-income countries, upper-middle-income countries, lower-middle-income countries, and low-income countries, covering the period 1985-2022. The confirmation of slope heterogeneity, cross-sectional dependence, stationarity, and cointegration among variables lends support to the robustness of results. The augmented mean group (AMG) robustness test was applied to check robustness and the results were found mostly consistent with estimation method. The results revealed that upper-middle-income countries are more vulnerable to extreme temperatures compared to high-income countries. The results also confirmed an inverted U-shaped relationship between each sector’s output and precipitation in upper-middle-income countries. In contrast, for upper-middle-income, lower-middle-income, and low-income countries, this relation exists in industrial sector only in long run. This indicates that precipitation is initially beneficial for production activities. However, beyond a certain threshold of precipitation, this trend reverses, i.e., the output of the economic sectors tends to decline. Furthermore, there is no supporting evidence that confirms a short-run non-linear relation between precipitation and agricultural yields. In upper-middle-income countries, the results confirmed that FDI is a driving factor behind both agricultural sector and service sector in long run while short-run results indicated a negative association but insignificant. This study also showed that in long run, an increase in HCI contributes to improving the output of the three sectors for high-income countries. The empirical findings provide valuable insights for policy-makers and governments to formulate coherent adaptation and mitigation strategies, thereby accelerating the transition of sectoral productivity from low to high levels in the sample countries.

This study examined the role of green energy development in mitigating climate change and fostering sustainable development in Central Asia including Kazakhstan, Uzbekistan, Kyrgyzstan, Tajikistan, and Turkmenistan. The region has substantial untapped potential in solar energy, wind energy, hydropower energy, as well as biomass and bioenergy, positioning it strategically for renewable energy deployment. The result demonstrated that integrating renewable energy can reduce greenhouse gas emissions, improve air quality, enhance energy security, and support rural development. Case studies from Kazakhstan, Uzbekistan, Kyrgyzstan, and Tajikistan showed measurable environmental and economic benefits. However, the large-scale use of renewable energy still faces numerous barriers, including outdated infrastructure, fragmented regulatory frameworks, limited investment, and shortages of technical expertise. Overcoming these obstacles requires institutional reform, stronger regional cooperation, and increasing engagement from international financial institutions and private investors. Modernizing grids, deploying storage systems, and investing in education, research, and innovation are critical for building human capacity in renewable energy sector. Accelerating the renewable energy transition is essential for Central Asia to meet climate goals, enhance environmental resilience, and ensure long-term socioeconomic development through innovation, investment, and regional collaboration.

Livestock farming is a critical pillar of Tajikistan’s national economy and livelihood security. However, significant economic challenges in the country have led to the degradation of grassland ecosystems. This degradation has not only reduced the productivity of grassland ecosystems but also severely impacted their ecological functions. A particularly concerning consequence is the threat to biodiversity, as the survival and persistence of endemic, rare, and endangered plant species are at serious risk, thereby diminishing the value of species’ genetic resources. Based on the data from multiple sources such as literature reviews, field observations, and national statistics, this study employed a systematic literature review and meta-analysis to investigate the current status, causes of degradation, and restoration measures for grassland ecosystems in Tajikistan. The results revealed that Tajikistan’s grassland ecosystems support exceptionally high plant species diversity, comprising over 4500 vascular plant species, including nearly 1500 endemic and sub-endemic taxa that constitute a unique genetic reservoir. These ecosystems are experiencing severe degradation, characterized by significantly reduced vegetation cover and declining species richness. Palatable forage species are increasingly being displaced by unpalatable, thorny, and poisonous species. The primary drivers of degradation include excessive grazing pressure, which disrupts plant reproductive cycles and regeneration capacity, habitat fragmentation due to urbanization and infrastructure development, and uncontrolled exploitation of medicinal and edible plants. Climate change, particularly rising temperatures and altered precipitation patterns, further exacerbates these anthropogenic pressures. Ecological restoration experiments suggested that both ecosystem productivity and plant species diversity are significantly enhanced by systematic reseeding trials using altitude-adapted native species. These findings underscore the necessity of establishing scientifically grounded approaches for ecological restoration.

Waste management strategies employed by emerging economies worldwide are often insufficient to address the new-age sustainability challenges. Especially in chemical-intensive manufacturing industries, increasing levels of waste production are a significant environmental threat. Adopting a circular supply chain (CSC) can be a viable solution to this problem since it incorporates the components of the circular economy into an organization’s supply chain, bringing an engaging viewpoint to the supply chain sustainability field. Nevertheless, the adoption of CSC in chemical-intensive manufacturing industries faces various intricate challenges in emerging economies. This study, therefore, aims to explore and evaluate the challenges associated with adopting CSC in the chemical-intensive manufacturing industries, using the empirical case of an emerging economy, Bangladesh. After a thorough literature review and expert validation, 26 challenges were analyzed using a probabilistic group decision-making approach, i.e., the Bayesian best-worst method (BWM). The result showed that the most significant challenge is the chemical composition-related complexity (global weight=0.0801), followed by strong emphasis on the take-make-dispose policy (0.0705), and insufficient investment and financial resources (0.0697). On the contrary, the least important challenge is the resistance toward the transition from conventional supply chain to CSC (0.0078). The outcomes of this study are expected to enrich existing knowledge and comprehension of the challenges linked to implementing CSC practices in Bangladesh and contribute to achieving Sustainable Development Goals (SDGs), such as SDG 3 (good health and well-being), SDG 11 (sustainable cities and communities), SDG 12 (responsible consumption and production), SDG 13 (climate action), and so on.

Coastal Bangladesh is highly vulnerable to various impacts of climate change, including rising temperatures, unpredictable precipitation, cyclones, droughts, and saltwater intrusion. These factors collectively threaten agricultural productivity and food security. This study examines the relationship between farmers’ perceptions and observable climatic trends, with a focus on the sustainability of food systems and the promotion of adaptable farming techniques in Bagerhat District, Bangladesh. A mixed-methods strategy was employed, incorporating household surveys (a total of 110 purposively selected farmers), focus group discussions, key informant interviews, and climatic data analysis. The Mann-Kendall test, Sen’s slope estimator, precipitation concentration index (PCI), and standardized rainfall anomaly index (SRAI) were employed to analyze climate trends from 1991 to 2020. The findings showed that more than 70.00% of respondents indicated that summers were becoming warmer, over 50.00% reported that winters were becoming colder, and 63.00% stated that yearly precipitation was decreasing. Farmers reported an increase in flood occurrences and a decline in the predictability of precipitation. Between 2011 and 2019, the output of most rice varieties decreased, with the exception of high-yielding Aman rice and hybrid Boro rice. The results also showed that 60.00% of respondents reported experiencing salinity intrusion, and 57.00% attributed significant yield losses to salinity. Planting salt-tolerant rice varieties (such as BRRI Dhan 67 and Binadhan-10), practicing homestead vegetable cultivation, and moderately integrating shrimp aquaculture were also common adaptive measures. To improve long-term food security in coastal Bangladesh, we suggest growing more salt-tolerant crop varieties, promoting vertical and homestead gardening, enhancing seed systems that are resilient to climate change, and educating farmers on the use of climate-smart farming methods. This study highlights the importance of aligning farmers’ perceptions with observed climatic data to design effective adaptation strategies. The findings of this study can guide policy-makers and development practitioners in strengthening climate-resilient agriculture and ensuring long-term food security in coastal Bangladesh.

Global challenges, including resource inefficiency, rising food demand, sustainability concerns, and climate change, necessitate more efficient and resilient agricultural systems. Conservation agriculture (CA), which is based on the principles of the minimum mechanical soil disturbance, permanent soil organic cover, and species diversification, provides a promising solution. This study examined the principles and mechanisms of CA, assessed its benefits and constraints, and identified key research gaps. This study focused on CA outcomes related to soil health, biodiversity, productivity, and ecosystem services, considering factors such as climate, soil type, and management practices. CA has demonstrated the potential to improve soil health, enhance biodiversity, and boost productivity across diverse regions. However, its effectiveness has been found to vary across studies, emphasizing the need for a more critical understanding of its benefits and limitations. Moreover, variations in outcomes are evident due to differences in experimental methodologies, environmental conditions, and socioeconomic factors. For the widespread adoption of CA practices, it is necessary to make personalized adjustments to it, integrating the corresponding technologies, thereby meeting the needs of farmers. Interdisciplinary research is crucial to refining CA practices and addressing existing knowledge gaps. This study is practiced to enhance the understanding of the potential of CA to promote a sustainable global food production system.

The tropical timber trade faces significant sustainability challenges, including deforestation, illegal logging, and inadequate traceability. Inaccurate species identification further complicates these issues, leading to unreliable trade statistics and enforcement challenges. The Lacey Act Amendment (LAA) of 2008 mandated declaring scientific names for timber shipments entering the United States. Therefore, this study assessed the implementation of the LAA using data obtained through a Freedom of Information Act request to the United States Department of Agriculture-Animal and Plant Health Inspection Service for 4 tropical timber species including Keruing, Meranti, Acajou d’Afrique, and Mahogany from Indonesia, Malaysia, Brazil, Philippines, Cameroon, Ghana, Congo, Cote d’Ivoire, and Bolivia, with high rates of illegal logging. This study showed that the United States imported 49 species of Keruing species group, 126 species of Meranti species group, 6 species of Acajou d’Afrique species group, and 2 species of Mahogany species group during 2017-2023. Despite mandatory declarations, approximately 14.60% of timber import records lacked species-specific names. Conservation assessments identified 37 species of Keruing species group and 68 species of Meranti species group listed as threatened by the International Union for Conservation of Nature (IUCN) but absent from the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). Moreover, the principal component analysis (PCA) indicated that the first principal component was primarily driven by import value and import volume, reflecting the overall trade prominence, while the second principal component captured temporal pattern through import year. Further, this study developed a Trade-Adjusted Conservation Priority Index (TACPI) that integrated conservation status with trade prominence to prioritize species at risk. Species with high TACPI scores, such as Dipterocarpus coriaceus and Shorea balangeran, were identified as urgently needing regulatory focus. To strengthen sustainable trade and conservation, it is recommended to enforce the LAA more strictly, expand timber identification technologies, and mandate key supplier countries, who are the CITES’ signatories, to list high-risk species in the CITES appendices.

Tajikistan contains the majority of Central Asia’s glaciers, which cover about 6.00% of the national territory; their rapid shrinkage poses a significant threat to regional water resource security. However, glacier monitoring in Tajikistan was interrupted after 1991, creating a substantial gap in understanding the current state and temporal evolution of these glaciers. Based on glacier inventory data, in situ measurements, and published literature, this study examined the present status and recent variations of glaciers in Tajikistan through data integration and validation, literature collation and comparative analysis, and the application of Geographic Information System (GIS) spatial analysis techniques. As of 2023, Tajikistan possesses a total of 11,528 glaciers, encompassing an area of 7624.48 (±305.58) km². Small glaciers dominate in number, whereas large glaciers account for the majority of the total area. Over the past two decades, the glacier count has decreased by 2014, and the total area has decreased by 628.98 km², corresponding to an average annual reduction rate of 0.33%. Regional shrinkage rates range from 4.10% to 22.28%. Glaciers have undergone accelerated mass loss during the past 20 a; only those on the northeastern Pamir Plateau exhibit a weak positive mass balance. Observations of typical monitored glaciers also reveal intensified melting and retreat, consistent with regional trends. In light of the recent acceleration of glacier shrinkage in Tajikistan, focused measures should be implemented to strengthen glacier monitoring, enhance public awareness of glacier preservation, and promote the sustainable development and utilization of glacier tourism. These findings bridge the knowledge gap regarding the spatiotemporal dynamics of Tajikistan’s glaciers over recent decades and provide essential data support for regional water resource management.

The Jabodetabek Metropolitan Area (JMA), Indonesia’s largest urban agglomeration, faces severe challenges due to rapid population growth and environmental degradation. Expanding urban areas has led to a reduction in green spaces, damaging ecosystem services, and exacerbating urban heat island effect, soil erosion, and flood risk. Therefore, this study identified key ecosystem service indicators, including Urban Heat Mitigation (UHM), Sediment Retention (SR), and Flood Risk Mitigation (FRM), and defined the spatial pattern of ecosystem services and its management zones in the JMA in 2024. Spatial data and ecosystem service indicators were analyzed using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) and spatial clustering analysis tool (e.g., Rustiadi’s Quantitative Zoning Method(RQZM) II), and the results served as the basis for formulating strategic recommendations. This study highlighted significant regional disparities. Jakarta, Tangerang Regency, Bekasi Regency, Depok City, Tangerang City, South Tangerang City, and Bekasi City experienced the increase of urban heat effect and flood risk due to dense infrastructure and limited green spaces. Conversely, southern peri-urban areas of Bogor Regency demonstrated higher ecological capacities, particularly in water infiltration and temperature regulation, but remained vulnerable to soil erosion due to urban expansion. The results underscored the critical imbalance between growing urban demands and the diminishing capacity of peri-urban areas to supply ecosystem services, which is driven by the transformation of green spaces into built-up areas. To address these challenges, this study proposed the Nature-Based Solutions (NBS) by emphasizing forested area conservation in the southern region of the JMA, natural landscape restoration and rehabilitation in the central region, and a hybrid of natural and artificial ecosystem creation in the northern region.

The present review critically examines the role of neglected and underutilized crops (NUCs) in enhancing the resilience of South Asian cropping systems and diets in the context of climate change and nutritional challenges. This analysis reveals that integrating NUCs, such as millets, sorghums, amaranth, and indigenous legumes, into existing cropping systems can significantly improve the climate resilience, dietary diversity, and ecological sustainability of the food systems. These crops exhibit superior tolerance to abiotic stress and offer higher nutritional density compared to staple cereals, such as rice and wheat. However, their adoption faces challenges, including limited research investment, fragmented value chains, etc. We further identify that complementary cropping strategies and climate-smart agriculture (CSA) practices can optimize resource use while boosting smallholder farmers’ income. NUCs are pivotal for the transformation of exist cropping systems towards nutrition-sensitive and climate-resilient agricultural and food systems. Strategic integration of NUCs can simultaneously address food insecurity, biodiversity loss, and rural poverty. Yet, unlocking their potential requires coordinated efforts in genetic improvement, market development, and policy frameworks tailored to regional contexts. This synthesis provides a comprehensive roadmap for policy-makers, researchers, and farmers to leverage NUCs as “Future Smart Food”. By bridging agronomic, nutritional, and socioeconomic perspectives, this study highlights the transformative potential of NUCs in achieving Sustainable Development Goals (SDGs) across South Asian countries.

Debris flow events are frequent in Tajikistan, yet comprehensive investigations at the regional scale are limited. This study integrates remote sensing, Geographic Information System, and machine learning techniques to evaluate debris flow susceptibility and associated hazards across Tajikistan. A dataset comprising 405 documented debris flow points and 14 influencing factors, encompassing geological, climatic-hydrological, and anthropogenic variables, was established. Three machine learning algorithms—Random Forest, Support Vector Machine (SVM), and Multi-layer Perceptron—were applied to generate susceptibility maps and delineate debris flow risk zones. The results indicate that the areas of higher and high susceptibility accounted for 20.43% and 4.41% of the national area, respectively, and were predominantly concentrated along the Zeravshan and Vakhsh river basins. Among the evaluated models, SVM model demonstrated the highest predictive performance. Beyond conventional topographic and environmental controls, drought conditions were identified as a critical factor influencing debris flow occurrence within the arid and semi-arid mountainous regions of Tajikistan. These findings provide a scientific basis for regional debris flow risk management and disaster mitigation planning, and offer practical guidance for selecting conditioning factors in machine-learning-based susceptibility assessments in other dry mountainous environments.

Shrimp farming is a major global aquaculture activity; however, its social and ecological impacts raise sustainability concerns. While previous research has focused on isolated social or environmental aspects of sustainability in shrimp farming, integrated assessments of these factors using a social-ecological systems (SES) approach are rare. A framework for assessing the sustainability of shrimp farming—comprising a set of social and ecological indicators—is developed and conceptualized in this study for the first time, using an integrated, interdisciplinary, and empirical SES approach. We first identified key social and ecological indicators and developed a conceptual framework based on SES approach, then surveyed 90 shrimp farms across 3 coastal regions (including Satkhira, Bagerhat, and Cox’s Bazar districts) in Bangladesh. Nearly all farmers in Satkhira (97%) and all in Bagerhat (100%) expressed dissatisfaction with the decreasing pattern of shrimp production and profitability over the last decade. In contrast, nearly all respondents in Cox’s Bazar (97%) reported satisfaction with increasing shrimp production. Except in Cox’s Bazar, equity in labor payment remained a concern for the social sustainability of the shrimp farming system. The changing pattern of shrimp production and profitability, which does not ensure equity, poses a threat to the sustainability of shrimp farming. Most of the surveyed farmers recognized the mutual benefits of mangrove forests and shrimp farming (97% in Satkhira and 77% in Cox’s Bazar), which suggests potential for the development of policy on integrated mangrove-shrimp farming with community-based management. This research could help assess the sustainability of the shrimp farming system and contribute to achieving Sustainable Development Goals 2 (zero hunger) and 8 (decent work and economic growth). By examining existing practices and developing a novel framework, this study highlights informed decision-making and guides methodological discussion on assessing the sustainability of shrimp farming using the SES approach in coastal regions and different aquaculture systems worldwide.

As a major source of freshwater in Central Asia, Tajikistan is endowed with abundant glaciers and water resources. However, the country faces multiple challenges, including accelerated glacier retreat, complex inter-government water resource management, and inefficient water use. Existing research has predominantly focused on individual hydrological processes, such as glacier retreat, snow cover change, or transboundary water issues, but it has yet to fully capture the overall complexity of water system. Tajikistan’s water system functions as an integrated whole from mountain runoff to downstream supply, but a comprehensive study of its water resource has yet to be conducted. To address this research gap, this study systematically examined the status, challenges, and sustainable management strategies of Tajikistan’s water resources based on a literature review, remote sensing data analysis, and case studies. Despite Tajikistan’s relative abundance of water resources, global warming is accelerating glacier melting and altering the hydrological cycles, which have resulted in unstable runoff patterns and heightened risks of extreme events. In Tajikistan, outdated infrastructure and poor management are primary causes of low water-use efficiency in the agricultural sector, which accounts for 85.00% of the total water withdrawals. At the governance level, Tajikistan faces challenges in balancing the water-energy-food nexus and transboundary water resource issues. To address these issues, this study proposes core paths for Tajikistan to achieve sustainable water resource management, such as accelerating technological innovation, promoting water-saving agricultural technologies, improving water resource utilization efficiency, and establishing a community participation-based comprehensive management framework. Additionally, strengthening cross-border cooperation and improving real-time monitoring systems have been identified as critical steps to advance sustainable water resource utilization and evidence-based decision-making in Tajikistan and across Central Asia.

Quantifying material use in infrastructure development and analyzing its relationship with economic growth is essential for enhancing resource efficiency and steering regional resource management toward sustainable development. This study systematically assessed infrastructure related material use in 30 provinces, autonomous regions, and municipalities in China during 1978-2022. The result indicated that material stock has experienced significant growth, increasing from 16.91×10⁹ t in 1978 to 103.60×10⁹ t in 2022, with an average annual growth rate of 4.20%. However, from 1978 to 2015, material input followed a strong upward trend but saturated after 2015. At the national level, material input peaked in 2015, after which it began to decline. The central region reached its peak earlier in 2013, while the eastern and western regions peaked in 2015. Using a decoupling analysis framework, this study revealed that nationally, the elasticity value between material stock and gross domestic product (GDP) remained near or above 1.0, reflecting continued reliance on stock accumulation. Regionally, the elasticity value between material stock and GDP has increased in the central and western regions during 1978-2022, whereas elasticity value between material stock and GDP in the eastern region showed a slower growth rate but still struggled to achieve absolute decoupling. Moreover, the elasticity value between material input and GDP has declined at the national level, presenting a relative decoupling, with some regions already achieving absolute decoupling. The eastern region was closer to absolute decoupling, while the central and western regions, though still intensive in material input, exhibited faster declines in elasticity. Accelerating the transition from linear to circular economy is an essential step for China to achieve absolute decoupling and long-term sustainability. Finally, this research recommends promoting the adoption of renewable energy, driving industrial upgrading, implementing compact urban design, and extending the lifespan of infrastructure to reduce material dependency and achieve sustainable infrastructure transformation at the national level.

Desertification poses severe threats to socio-ecological resilience in arid regions, yet systematic quantification of desertification control efficiency remains limited. This study addressed this gap by developing an integrated Data Envelopment Analysis (DEA) Malmquist index to assess the spatiotemporal dynamics of desertification control efficiency in Hotan Prefecture (a hyper-arid region) of China from 2005 to 2023. To achieve this goal, we analyzed 5 indices spanning the total factor productivity, technical change, efficiency change, pure efficiency change, and scale efficiency change across 7 counties and 1 city in Hotan Prefecture. Results revealed that the growth rate of the total factor productivity is 12.0%, which is driven primarily by technical change and management optimization. However, significant spatiotemporal heterogeneity emerged. Temporally, rapid early gains during 2005-2010, with the total factor productivity value of 1.372, were dominated by technological progress, where technical change reached 1.291, while scale efficiency change helped sustain progress between 2010 and 2015. A recent decline in the total factor productivity to 0.987 during 2015-2023 underscored the risks associated with technological stagnation. Spatially, Qira County achieved the highest growth rate of the total factor productivity at 33.7% through dual advances in technology and management, which stands in sharp contrast to Moyu County’s stagnation, where the total factor productivity reached only 1.029, reflecting the minimal growth rate of 2.9%. Furthermore, scale expansion change proved beneficial in Pishan County but counterproductive in Qira County. Based on these findings, this study proposes targeted policy recommendations to enhance desertification control efficiency in hyper-arid regions like Hotan Prefecture. It emphasizes the importance of continuous technological innovation, particularly water-saving and adaptive techniques to counteract declining productivity. Differentiated spatial strategies are essential, with tailored interventions for high-risk northern areas and scaling successful models from higher-efficiency southern zones. Optimizing project scale based on ecological carrying capacity rather than uncontrolled expansion is urged, along with strengthening cross-regional water resource coordination. Finally, establishing a data-driven monitoring and decision-support system could enable dynamic efficiency evaluations and evidence-based policy planning. This study provides a critical methodological framework for systematically quantifying desertification control efficiency in hyper-arid regions, establishing an empirical foundation for targeted ecological governance.