Regional Sustainable Development Research Articles

Evaluating net primary productivity dynamics and their response to land-use change in the loess plateau after the 'Grain for Green' program

Assessing net primary productivity (NPP) dynamics and the contribution of land-use change (LUC) to NPP can help guide scientific policy to better restore and control the ecological environment. Since 1999, the “Green for Grain” Program (GGP) has strongly affected the spatial and temporal pattern of NPP on the Loess Plateau (LP); however, the multifaceted impact of phased vegetation engineering measures on NPP dynamics remains unclear. In this study, the Carnegie-Ames-Stanford Approach (CASA) model was used to simulate NPP dynamics and quantify the relative contributions of LUC and climate change (CC) to NPP under two different scenarios. The results showed that the average NPP on the LP increased from 240.7 gC·m−2 to 422.5 gC·m−2 from 2001 to 2020, with 67.43% of the areas showing a significant increasing trend. LUC was the main contributor to NPP increases during the study period, and precipitation was the most important climatic factor affecting NPP dynamics. The cumulative amount of NPP change caused by LUC (ΔNPPLUC) showed a fluctuating growth trend (from 46.23 gC·m−2 to 127.25 gC·m−2), with a higher growth rate in period ΙΙ (2010–2020) than in period Ι (2001–2010), which may be related to the accumulation of vegetation biomass and the delayed effect of the GGP on NPP. The contribution rate of LUC to increased NPP in periods Ι and ΙΙ was 101.2% and 51.2%, respectively. Regarding the transformation mode, the transformation of grassland to forest had the greatest influence on ΔNPPLUC. Regarding land-use type, the increased efficiency of NPP was improved in cropland, grassland, and forest. This study provides a scientific basis for the scientific management and development of vegetation engineering measures and regional sustainable development.

Groundwater recharge estimation using WetSpass-M and MTBS leveraging from HydroOffice and WHAT tools for baseflow in Weyib watershed, Ethiopia.

WetSpass-M model and multi-technique baseflow separation (MTBS) were applied to estimate spatio-temporal groundwater recharge (GWR) to be used to comprehend and enhance sustainable water resource development in the data-scarce region. Identification of unit Hydrographs And Component flows from Rainfall, Evaporation, and Streamflow (IHACRES) techniques outperform the existing 13 MTBS techniques to separate baseflow depending on the correlation matrix; mean baseflow was 5.128 m3/s. The WetSpass-M model performance evaluated by Nash-Sutcliff Efficiency (NSE) was 0.95 and 0.89; R2 was 0.90 and 0.85 in comparison to observed and simulated mean monthly baseflow and runoff (m3/s), respectively. The estimated mean annual water balance was 608.2 mm for actual evapotranspiration, 221.42 mm for the surface runoff, 87.42 mm for interception rate, and 177.66 mm for GWR, with an error of - 3.29 mm/year. The highest annual actual evapotranspiration was depicted in areas covered by vegetation, whereas lower in the settlement. The peak annual interception rates have been noticed in areas covered with forests and shrublands, whereas the lowest in settlement and bare land. The maximum annual runoff was depicted in settlement and bare land, while the lowest was in forest-covered areas. The annual recharge rates were low in bare land due to high runoff and maximum in forest-covered areas due to low surface runoff. The watershed's downstream areas receive scanty annual rainfall, which causes low recharge and drought. The findings point the way ahead in terms of selecting the best approach across multi-technique baseflow separations.

Concept of Smart Specialization as a Strategy for Sustainable Regional Development

The subject of this paper is a review of previous research on smart specialization as a concept which is one of the strategies for sustainable development of regions. Innovations are considered as one of the key drivers of growth. Recognition of innovation which was central point of strategy ‘Europe 2020’ where ‘smart specialization’ needs to make possible for the regions and countries pursue those industries in which they hold a comparative advantage and which have basis for further innovations. The main purpose of this paper is defining smart specialization and its role on the regional development. Analysis and comparison of the scientific literature and applications of smart specialization were used as methods for this paper. The main findings of this paper show that the basis of smart specialization are innovation, knowledge and research which are pillars of smart, sustainable development. Smart specialization means identifying the unique characteristics and potential of each country and region, with the aim of achieving competitive advantages and excellence. It also includes strengthening regional innovation systems, increasing knowledge exchange and spillover the benefits of innovation throughout the regional economy. By comparison method of the scientific literature this paper will contribute to the development of theoretical background of smart specialization as a strategic concept formed by a group of European Union experts with the aim of reducing the gap in competitiveness between the European Union and the United States, which arises from the lower economic and technological specialization of European countries, especially at the regional level. Also it will promote smart specialization as a concept that can contribute to strengthening regional innovation policy and regional development.

Spatiotemporal Evolution of Land Cover and Landscape Ecological Risk in Wuyishan National Park and Surrounding Areas

Previous studies on national park conservation have focused mainly on their internal areas, and few studies have focused on national parks and their surrounding areas as unified entities. Therefore, the investigation of land cover and landscape ecological risks in national parks and surrounding areas is essential for overall ecosystem protection and regional sustainable development. This study examines the spatiotemporal evolution of land cover and its landscape ecological risk in Wuyishan National Park, China, and its surrounding areas (WNPSA) from 1990 to 2020. The results show that (1) the land cover of WNPSA from 1990 to 2020 predominantly exhibited a consistent decline in forested areas, paralleled by an augmentation in farmland and impervious surface areas. The center of standard deviation ellipse of impervious surfaces has been progressively moving further south in tandem with the expansion of these surfaces, primarily located within the county town of Fujian Province. (2) The Wuyishan National Park (WNP) areas were dominated by low values of landscape index, and the high value areas in the park were mainly located at the provincial boundary area, with a gradual narrowing during 1990–2020, suggesting a decrease in landscape heterogeneity within the park. High value areas in the surrounding areas mainly occurred in areas with clustered impervious surfaces (e.g., the county town), where part of them located in Wuyishan City have spread to the edge area southeast of WNP. (3) From 1990 to 2020, the lowest-risk areas continue to expand. However, as the medium-risk zone of the adjacent region extends into the edge of the national park, the low risk zone within the national park exhibits a trend from continuous to separate with the neighboring low risk zone. This led to an escalating stress effect on the ecological security of both the adjacent regions and the national park’s boundary areas due to land cover changes.

Predicting regional sustainable development to enhance decision-making in brownfield redevelopment using machine learning algorithms

Brownfield redevelopment and land sustainable management have many interconnected aspects, which could be evaluated by regional development. Most contaminated sites in Taiwan often lack comprehensive consideration during remediation for land reuse planning; therefore, they are operated independently from regional development. Regional development is a dynamic process; however, there is a research gap in understanding how regional development can serve as an incentive for brownfield redevelopment. This study established a model for assessing regional sustainability using machine learning (ML-RSD), that model used principal component analysis (PCA) and support vector machine (SVM) to predict the comprehensive evaluation rating of regional development at the township level and to explore the trends of regional governance sustainability. The results of ML-RSD that are compared to commonly used methods (driver-pressure-state-impact-response and entropy weight method) were consistent. Indicators such as the protection of vulnerable groups (SDG1), food security (SDG2), good health and well-being (SDG3), inclusive and equitable quality education (SDG4), environmental protection (SDG6), accessible and reliable energy (SDG7), and sustainable economic growth (SDG8) were identified as the main factors affecting regional development. Additionally, the model achieved an accuracy value exceeding 80%. Additionally, the results showed that there was no significant correlation between the delisted site (completed remediation) and regional development in southern Taiwan. The model underscored the overall lower comprehensive sustainable values for regions affected by inadequate land rehabilitation governance (SDG15). The results present that brownfield redevelopment strategies should enhance their effectiveness in land adaptation and integrating brownfield redevelopment with regional sustainable development is essential for it to become a win–win solution.

The impact of biochar addition on morpho-physiological characteristics, yield and water use efficiency of tomato plants under drought and salinity stress

The use of saline water under drought conditions is critical for sustainable agricultural development in arid regions. Biochar is used as a soil amendment to enhance soil properties such as water-holding capacity and the source of nutrition elements of plants. Thus, the research was carried out to assess the impact of biochar treatment on the morphological and physiological characteristics and production of Solanum lycopersicum in greenhouses exposed to drought and saline stresses. The study was structured as a three-factorial in split-split-plot design. There were 16 treatments across three variables: (i) water quality, with freshwater and saline water, with electrical conductivities of 0.9 and 2.4 dS m− 1, respectively; (ii) irrigation level, with 40%, 60%, 80%, and 100% of total evapotranspiration (ETC); (iii) and biochar application, with the addition of biochar at a 3% dosage by (w/w) (BC3%), and a control (BC0%). The findings demonstrated that salt and water deficiency hurt physiological, morphological, and yield characteristics. Conversely, the biochar addition enhanced all characteristics. Growth-related parameters, such as plant height, stem diameter, leaf area, and dry and wet weight, and leaf gas exchange attributes, such rate of transpiration and photosynthesis, conductivity, as well as leaf relative water content were decreased by drought and salt stresses, especially when the irrigation was 60% ETc or 40% ETc. The biochar addition resulted in a substantial enhancement in vegetative growth-related parameters, physiological characteristics, efficiency of water use, yield, as well as reduced proline levels. Tomato yield enhanced by 4%, 16%, 8%, and 3% when irrigation with freshwater at different levels of water deficit (100% ETc, 80% ETc, 60% ETc, and 40% ETc) than control (BC0%). Overall, the use of biochar (3%) combined with freshwater shows the potential to enhance morpho-physiological characteristics, support the development of tomato plants, and improve yield with higher WUE in semi-arid and arid areas.

Decoupling the multi-drivers of urban extreme heat environment in urban agglomerations using ensemble learning

Urban extreme heat (UEH) has been imparting a formidable menace to various facets of sustainable urban and regional development. While increasing studies have examined the urban thermal environment, a gap exists in decoupling the nonlinear multi-drivers of UEH environment in intra-urban regions, especially across the urban agglomerations. In this study, we estimated UEH through the land surface temperature (LST) in the extended summer season exceeding a specific threshold computed through cross-regional statistics. Furthermore, an additive interpretable ensemble learning model enhanced via the Bayesian Optimization algorithm (BO) and Monte Carlo Simulation framework (MCS) was employed to dissect the intricate nonlinear interplay between UEH and intra-urban morphology, green-blue composition, and atmospheric determinants. Our results highlight the indispensably suppressive effect of green and blue factors on UEH, whereas urban morphological variables generally exhibit an opposite trend. Interestingly, we reveal heterogeneity responses of building heights, elevated urban structures mitigate UEH in temperate monsoon and subtropical monsoon zones and exhibit diminished marginal utility in temperate continental zones. Furthermore, the arid climatic characteristics are expected to exert an unexpectedly enhancing effect on water bodies' cooling capacity. These findings provide heterogeneous local guidance for landscape and urban planning towards the severe challenges of climate change.

Toward dual carbon targets: Spatial correlation on comprehensive carbon emission index in urban agglomerations based on a new evaluation model

China is confronted with substantial pressure to mitigate its carbon emissions. Urban agglomerations assume a pivotal role in the attainment of carbon peaking and carbon neutrality. This study constructed a carbon emission evaluation model from the perspectives of total quantity, intensity, efficiency, population, and land. A modified gravity model and social network analysis method was used to analyze the spatial correlation characteristics of six urban agglomerations, clarified their carbon emission spillover effects, and explored their influencing factors using the quadratic assignment procedure method. The results are as follows. (1) The carbon emission correlations in the Yangtze River Delta, Pearl River Delta, and Chengdu-Chongqing urban agglomerations increased, while Beijing-Tianjin-Hebei, Central Plains, and Middle Reaches of Yangtze River urban agglomerations decreased. (2) From a macro perspective, the Yangtze River Delta and Pearl River Delta urban agglomerations were at the core of the network, and the “bridging” role of the Middle Reaches of Yangtze River urban agglomeration was evident. From a micro perspective, the cities in the middle of urban agglomerations were more likely to become network cores. (3) Spillover effects between plates were present in the correlation network, with a gradual balance between the reception and spillover relationships. Most urban agglomerations exhibited an uneven distribution of community correlation capacity. (4) Geographic adjacency and urbanization level significantly promoted carbon emission correlation, although the direction and magnitude of other factors’ influence varied. The findings contribute to the implementation of low-carbon planning, carbon reduction strategies and regional sustainable development.

Creating Low‐Carbon Economies: Probing Transition Dynamics through the Lens of Field Theory

AbstractWe employ field theory as an approach to analysing sustainable regional development by reconciling funding needs and funding procurement. Initial expectations that private capital would bridge the financial gap to decarbonize our economies and societies have not materialized. Instead, state‐led coalitions increasingly introduce spatialized decarbonization strategies in which public development banks are pivotal, yet underappreciated, actors. Field theory provides a fresh perspective for mapping the particular context in which regional industrial policies intersect with broader national and supra‐national investment programmes and funding needs for these long‐term initiatives. Transitions are typically directed but open‐ended social processes, necessitating agency to both alter context and institutions and stabilize the emerging new structures. Field theory can surpass limitations in approaches like transition studies and integrate change mechanisms across scales.

Study on the Spatiotemporal Evolution and Driving Factors of Ecological Security in Stages Based on the DPSIRM-SBM Model: A Case Study of the Yangtze River Economic Belt.

Scientific assessment of urban ecological security (ES) is an important prerequisite to realize regional sustainable development. Previous studies lack the consideration of quality and poor systematic correlation, which could not reflect the internal dynamic relationship. On the basis of considering the time lag, this study divided the research process into the natural operation stage and the management feedback stage based on the driving forces, pressures, state, impacts, responses, management (DPSIRM) framework model and DEA theory, so as to effectively overcome the above shortcomings. Finally, we analyzed the spatio-temporal characteristics and influencing factors of the ES level of 108 cities in the Yangtze River Economic Belt (YREB) during 2005-2019. The results showed that: (a) both two stages showed a slow and fluctuating upward trend in time series, and the level of urban ES in the management feedback stage was significantly higher than that in the natural operation stage; (b) with the passage of time, the spatial distribution of ES in the natural operation stage gradually developed towards the middle and downstream of the YREB, while the management feedback stage mainly evolved from the midstream to the edge area; (c) the level of urban ES presented a different degree of spatial agglomeration phenomenon, and showed an increasing trend over time; and (d) the key influencing factors gradually changed from pressure to response during 2005-2019. This research aims to provide an innovative perspective for the measurement of urban ES, and provide scientific reference for improving urban ecological sustainable development.

Sustainable Water Management and Indigenous Socio-Technical Heritage in Marrakech, Morocco

Sustainable Water Management and Indigenous Socio-Technical Heritage in Marrakech, Morocco

Human Capital at the Regional Level: Population Forecast Insights into Latvia from a Long-Term Perspective

To remain prosperous and competitive, modern regions must meet the challenge of becoming smart and sustainable, and human capital has a key role in this context. Depopulation increases risks of human capital availability and emigration is a primary reason. Regions that are experiencing a decreased population must develop strategic sustainable regional development policies that consider scientifically based population forecasts. The youth population characterises regional potential for long-term human capital availability. First, children represent a region’s future employees and entrepreneurs. Second, children require availability of educational services at regional level, which promotes regional vitality. Third, the youth population indirectly demonstrates a region’s socio-economic attractiveness for living and working. This study employs the system dynamic method to forecast different population change scenarios at the regional level in Latvia. The results reveal a declining, long-term population tendency for working age and youth populations in Latvian regions. Overall, Latvian regions will remain extremely homogeneous in the long term, with minor differences in the short term. In conclusion, despite regional disparities in terms of quality of life with some leading examples, all regions will experience high emigration loss. Regional social, economic and environmental characteristics demonstrate a need to assess population change trends in a complex manner. This study provides data for understanding short- and long-term perspectives that must be addressed through sustainable regional development policies.   Received: 27 October 2023 / Accepted: 24 March 2024 / Published: 5 May 2024

The State of Agricultural Development and Industrial Prosperity Pathway and Strategy Design in the Context of Data-Driven and Rural Revitalization

Current advances in materials science are providing a huge variety of novel adsorbents that could be used for the transformation and storage of low-temperature heat, such as the heat generated by renewable energy sources.Achieving industrial prosperity is a key step in building an all-round well-off society and realizing agricultural modernization. In the process of industrial prosperity, there are also many problems: firstly, the long-term traditional farming in China has led to the information blockage and ideological constraint of most farmers in China, so that they are slow to accept new things and new ideas; secondly, due to the "one long and one short" characteristic of long growth cycle and short storage cycle of agricultural products, it is difficult for rural transportation and deep processing of agricultural products. Secondly, because of the "long and short" nature of the long growth cycle and short storage cycle of agricultural products, the demand for rural transportation and deep processing of agricultural products is high. This study is based on the problems related to sustainable agricultural development in traditional agricultural areas. The main purpose of this study is to clarify the sustainable development status of agricultural systems under different agricultural development paths in traditional agricultural areas, to establish a methodological system for studying regional agricultural development paths, to explore the optimal path for sustainable regional agricultural development, and orderly management of sustainable agricultural development in traditional agricultural areas, so as to promote the sustainable development of traditional agricultural areas with economic prosperity, social stability and ecological health. The experimental results prove that the optimized SGA algorithm has carried out good system dynamics modeling for the typical traditional agricultural area - the problem of choosing the agricultural development path, and the comprehensive evaluation of the simulation results.

Urbanization intensifies the imbalance between human development and biodiversity conservation: Insights from the coupling analysis of human activities and habitat quality

AbstractIntensified human activities have been seriously threatening the structure and ecological processes of ecosystems, resulting in habitat degradation. Therefore, coordinating the coupling between human activities and habitat quality (HQ) is crucial for high‐quality sustainable regional development and human well‐being. This study evaluated the human activities and HQ in the Pearl River Delta (PRD) urban agglomeration in China from 2000 to 2020 using the human footprint index (HFI) and the integrated valuation of ecosystem services and tradeoffs model. Then, we employed bivariate spatial autocorrelation and a coupling coordination degree (CCD) model to explore the synergistic relationship between human activities and HQ. The results show that spatial changes in HQ were predominantly driven by human activities. The gradual outward urban expansion resulted in significant HQ degradation. Slight HQ improvement by ecological restoration in urban outskirts cannot offset HQ losses caused by urbanization. During the study period, high‐HQ low‐HFI clusters decreased by 1.02%, while low‐HQ high‐HFI clusters increased by 4.67%, the two main clustering types in the PRD. Despite the CCD between HFI and HQ increased after 2010, the continuous changes of CCD characteristics from the HFI significantly lagged type to the HQ lagged. HFI showed an inverted U‐shaped relationship with CCD. The CCD peaks during 2000–2020 corresponded to HFI decreasing from 0.711 to 0.566. This indicates that the risk of decoupling between human activities and HQ gradually increased. Furthermore, CCD levels and characteristics in different bivariate clusters exhibited varying changes over time. These results reveal that the spatiotemporal dislocation between urbanization and ecological restoration induced the spatial nonstationarity of the coupling relationship between human activities and HQ. Urbanization exacerbates the imbalance between human development and biodiversity conservation. Therefore, we suggest reasonably delimiting urban boundaries, controlling the scale of urban sprawl, and strengthening biodiversity protection in areas undergoing rapid urbanization. In addition, we advocate for the division of ecological barrier zones, urban development buffer zones, and urban built‐up areas, each with tailored management and protection measures. Our findings can provide an important reference for the ecological restoration of urban agglomerations.

Sustainable management of land use patterns and water allocation for coordinated multidimensional development

The sustainable and integrated management of resources is a crucial approach to achieving sustainable regional development in the face of limited land and increasingly scarce water resources. This paper proposes a multidimensional optimization model to jointly optimize land use patterns and water resource allocation under the conditions of maximizing economic benefits and minimizing social differences, ecological loads, environmental pollution, and carbon emissions. The optimization model is solved using the affiliation function method and then combined with random forest (RF) and cellular automata (CA) models to further obtain the optimal spatial layout of land use. This paper takes the Mid-Yangtze River City Cluster as an example and optimizes the land use pattern and water allocation in the region in 2020 and 2030. The results of the study show that the optimized water and land resource allocation scheme performs better than the status quo in all dimensions. The optimized economic benefits, social effects, ecological effects, environmental effects, and overall sustainability in 2020 are increased by 45.97%, 22.89%, 10.07%, 24.65%, and 42.73%, respectively. By 2030, overall sustainability reaches 0.69. The developed modeling framework helps to elucidate the internal linkages between land use and water allocation, and it provides decision-makers with diversified approaches to land and water resource management and adjustment for different cities in different periods, which promotes the sustainable development of urban agglomerations.

Modelling and assessing new SME digital business status for visualising virtual economics and sustainability economic indicators: Empirical evidence from poultry business

SMEs are generally recognised as financial contributors to regional economic development. Despite the enormous contributions of digital SMEs to sustainable economic growth and regional development have not yet been reported. This paper assesses and models SME businesses to gain a digital business status and model. These days, visualising economic growth is challenging and powerful to identify business performance and realise sustainable regional development. This research analyses empirical data obtained from a poultry business to form a standard model for implementing a new SME digital business model and status. This standard model is a guideline to measure the other SME businesses and productions. Localisation of the SDGs was analysed using thematic analysis. Mathematical computation is used to visualise virtual economic growth geographically. Hence, our digital business model and status demonstrated business performance, management, and economic growth.

Impacts of climate change and land cover factor on runoff in the Coastal Chinese Mainland region

The increasingly frequent storms pose a significant threat to the sustainable development of coastal regions, particularly in densely populated and economically vibrant areas. Comprehending the intricate mechanisms and dynamics underlying runoff generation is curial, especially in the context of climate change and anthropogenic interference. This study aims to investigate the runoff production and its variation in the Coastal Chinese Mainland (CCM) by analyzing hydro-meteorological and land-use data from 1982 to 2020. Based on hydro-meteorological and land-use data from 1982 to 2020, this study investigates the runoff production and its variation in the Coastal Chinese Mainland (CCM), to reveal the temporal and spatial trends of runoff yielding and its driving factors, and to clarify the sensitivity of runoff in coastal cities to the integrated and individual parameters of climate change and anthropogenic interference, including precipitation (P), potential evapotranspiration (E0), and land cover factor (n). The results show that: (1) runoff has generally increased over the period, particularly in regions such as the Yangtze River Delta, Shandong, and Guangxi, while it has decreased in Beijing and eastern Guangdong; (2) in the northern CCM with larger aridity index, the land cover factor plays a dominant role in runoff production, while in the wetter southern CCM, precipitation is more influential, and potential evapotranspiration mainly hinders runoff generation all over CCM; (3) urban expansion tends to negatively impact n, while the loss of forests and shrinkage of croplands tend to enhance the value range of n. Other land use types have minimal impact. To ensure the achievement of sustainable development goals in the CCM, it is imperative to introduce a more comprehensive and theoretical framework that encompasses the natural, technical, and social dimensions of human-water systems into traditional flood regulation and water resource management. This framework should promote interdisciplinary collaboration and a watershed perspective, bridging administrative and watershed boundaries, to effectively address the complex challenges posed by climate change and anthropogenic activities on runoff and water resources in coastal regions.

Research on the economic agents' green co-evolution of China: framework, model, and application

Research on the economic agents' green co-evolution of China: framework, model, and application

Landscape ecological risk evaluation and prediction under a wetland conservation scenario in the Sanjiang Plain based on land use/cover change

Landscape ecological risk is the term used to describe potential negative effects of the relationship between environmental processes and landscape structure as a result of both natural and human interactions. The scientific assessment of past and prediction future ecological risks to landscapes is the basis for achieving sustainable regional development. In this study, we built an ecological risk measurement system characterized by variability in landscape composition to reflect the components of landscape ecological risk. In particular, the CA-Markov model was used to simulate the spatial pattern of land use in the Sanjiang Plain, China, under a wetland protection scenario. The evolution of the spatiotemporal land use trend in the study area was then analyzed for past (2011–2021) and future (2021–2036) periods. The results identified that construction land, farmland, water, and grassland areas exhibited an increasing trend from 2011 to 2021, while forest and wetland areas decreased each year. From 2021 to 2036, the grassland areas exhibited a downward trend, while the other land use types maintained the same previous trend, and all land use types experienced a slowdown in the degree of change. The major landscape ecological risk levels in the research region changed from medium-risk and low-risk levels (2011–2021) to low-risk and lower-risk levels (2021–2036). An evident decrease in risk is observed for farmland and construction land in the mid-region of the research district and forests in the south. In contrast, high-risk and higher-risk levels regions were smaller and distributed in the Songhua River basin in the northeast of the research region, wetland nature reserves, and the Xingkai Lake area, with an overall reduction of 59%. Based on the results, we propose several risk prevention and control management strategies. This research acts as a basis for determining Sanjiang Plain's future rational distribution of land resources and provides an example for the reduction of ecological risks in similar regions.

Enhancing sustainability: Exploring the evolution and dynamics of the grassland social-ecological system in Inner Mongolia over the past 260a

Understanding the intricate relationship between social-ecological systems (SES) coupling and long-term regional sustainable development is critical for effective management strategies. While recent research has predominantly focused on human-earth coupling, there is a dearth of knowledge concerning the transition of grassland SES from one regime to another and the underlying drivers. This study employs a comprehensive SES framework to identify and analyze interactions within typical pastoral areas of Inner Mongolia, aiming to shed light on the evolution of the grassland SES over the past centuries. Our research defines five distinct evolutionary phases in the grassland SES since the mid-Qing Dynasty. Each phase is characterized by unique social and ecological features, providing a nuanced understanding of the system's dynamics. We establish empirical links between the phases and their driving forces and impacts by assessing the main changes between these periods. Specifically, our findings reveal instances of negative cross-scale effects emerging during the evolution process. We observe that unreasonable resource utilization and an inability to curb ecological degradation may lead to unsustainable traps, posing challenges to long-term sustainability. To illustrate, during the transition from Phase 3 to Phase 4 in the late 19th century, a shift towards sedentary pastoralism led to increased land degradation due to intensified grazing practices. This unsustainable trajectory highlights the importance of adaptive management strategies to mitigate such negative consequences. This study contributes insights into the social and ecological management of grassland pastoral areas in China and for global analogous regions. By addressing the identified phases and their associated challenges, our research provides a foundation for crafting sustainable policies and practices to ensure the resilience of grassland SES in diverse geographical contexts.