Improving ecosystem services supply provides insights for sustainable landscape planning: A case study in Beijing, China

Evolution and driving mechanism of multiple ecosystem services in resource-based region of Northern China

Understanding the spatiotemporal characteristics and comprehensive service capabilities of various ecosystem services is crucial for maintaining regional ecosystem security, and clarifying the driving mechanisms of ecosystem services plays a guarantee for achieving regional sustainable development. Based on the ecological issues of Shanxi Province (SXP) in China, an assessment system covering eight targeted ecosystem services were constructed to quantitatively analyze the spatio-temporal patterns and contribution rates of driving factors. The water conservation, sand fixation, environment purification and habitat quality in the Loess Hills of western SXP have improved, with significant increase in hotspots. The comprehensive service capacity of ecosystem services in the Fenwei Basin (central SXP) has deteriorated, and the coldspots have expanded. The water conservation, carbon storage, habitat quality and recreation culture in the Yanshan-Taihang Mountains (eastern SXP) were enhanced, while product supply, carbon storage and environment purification were deteriorated. Land use is the dominant influencing factor on product supply. Water and soil conservation, sand fixation, and environment purification are dominated by climate factors. Carbon storage, habitat quality and recreation culture are influenced by underlying surface conditions. The current study provided a research paradigm, which will help the government with appropriate management policies to ensure the effectiveness of ecological protection and restoration, and offers insights for facilitating ecological sustainability and economic transformation in resource-based regions worldwide.

Climate and land use changes impact the trajectories of ecosystem service bundles in an urban agglomeration: Intricate interaction trends and driver identification under SSP-RCP scenarios

The delivery of ecosystem services (ESs), particularly in urban agglomerations, faces substantial threats from impending future climate change and human activity. Assessing ES bundles (ESBs) is critical to understanding the spatial allocation and interactions between multiple ESs. However, dynamic projections of ESBs under various future scenarios are still lacking, and their underlying driving mechanisms have received insufficient attention. This study examined the Beijing-Tianjin-Hebei urban agglomeration and proposed a framework that integrates patch-generating land use simulation into three shared socioeconomic pathway (SSP) scenarios and clustering analysis to assess spatiotemporal variations in seven ESs and ESBs from 1990 to 2050. The spatial trajectories of ESBs were analyzed to identify fluctuating regions susceptible to SSP scenarios. The results indicated that (1) different scenarios exhibited different loss rates of regulating and supporting services, where the mitigation of degradation was most significant under SSP126. The comprehensive ES value was highest under SSP245. (2) Bundles 1 and 2 (dominated by regulating and supporting services) had the largest total proportion under SSP126 (51.92 %). The largest total proportion of Bundles 4 and 5 occurred under SSP585 (48.96 %), with the highest provisioning services. The SSP126 scenario was projected to have the least ESB fluctuation at the grid scale, while the most occurred under SSP585. (3) Notably, synergies between regulating/supporting services were weaker under SSP126 than under either SSP245 or SSP585, while trade-offs between water yield and non-provisioning services were strongest. (4) Forestland and grassland proportions significantly affected carbon sequestration and habitat quality. Climatic factors (precipitation and temperature) acted as the dominant drivers of provisioning services, particularly water yield. Our findings advocate spatial strategies for future regional ES management to address upcoming risks.

An improved approach for evaluating landscape ecological risks and exploring its coupling coordination with ecosystem services

The rapid urbanization has accelerated the destruction of regional ecosystems, triggering ecological risks and threatening sustainable development. Landscape ecological risk (LER) evaluation is an effective tool to mitigate such negative impacts. However, the existing evaluation systems exhibit certain subjectivity. Therefore, an improved LER evaluation method was proposed, which incorporates ecosystem services (ESs) to characterize landscape vulnerability. The method was validated using the Pearl River Delta urban agglomeration (PRDUA) as the study area. The results showed that the optimal grain size and extent for landscape pattern analysis in the PRDUA were determined to be 150 m and 6km × 6 km, respectively. The comparison results with the traditional LER evaluation method demonstrated the improved method's superior rationality and reliability. The hotspot analysis based on the Getis-Ord Gi* method revealed that the hotspots of LER were mainly concentrated in the densely populated areas of the south-central region of the PRDUA. The coupling coordination degree (CCD) between LERs and ESs showed four different levels of development in both temporal and spatial dimensions, generally dominated by moderately balanced development and lagging ESs, reflecting the unbalanced ecological environment and socio-economic development of the PRDUA. It is recommended that the ecosystems in the PRDUA be managed and protected separately according to the delineated Ecological Protection Area (EPA), Urban Built-up Area (UBA), and Urban Ecological Boundary Area (UEBA). This study can provide an important reference for regional ecosystem conservation and management.

Identifying the impacts of land use landscape pattern and climate changes on streamflow from past to future

Identifying the individual and combined hydrological response of land use landscape pattern and climate changes is key to effectively managing the ecohydrological balance of regions. However, their nonlinearity, effect size, and multiple causalities limit causal investigations. Therefore, this study aimed to establish a comprehensive methodological framework to quantify changes in the landscape pattern and climate, evaluate trends in streamflow response, and analyze the attribution of streamflow events in five basins in Beijing from the past to the future. Future climate projections were based on three general circulation models (GCMs) under two shared socioeconomic pathways (SSPs). Additionally, the landscape pattern in 2035 under a natural development scenario was simulated by the patch-generating land use simulation (PLUS). The Soil and Water Assessment Tool (SWAT) was applied to evaluate the streamflow spatial and temporal dynamics over the period 2005-2035 with multiple scenarios. A bootstrapping nonlinear regression analysis and boosted regression tree (BRT) model were used to analyze the individual and combined attribution of landscape pattern and climate changes on streamflow, respectively. The results indicated that in the future, the overall streamflow in the Beijing basin would decrease, with a slightly reduced peak streamflow in most basins in the summer and a significant increase in the autumn and winter. The nonlinear quadratic regression more effectively explained the impact of landscape pattern and climate changes on streamflow. The trends in the streamflow change depended on where the relationship curve was in relation to the threshold. In addition, the impacts of landscape pattern and climate changes on streamflow were not isolated but were joint. They presented a nonlinear, non-uniform, and coupled relationship. Except for the YongDing River Basin, the annual streamflow change was influenced more by the landscape pattern. The dominant factors and the critical pair interactions varied from basin to basin. Our findings have implications for city planners and managers for optimizing ecohydrological functions and promoting sustainable development.

Coupling strength of human-natural systems mediates the response of ecosystem services to land use change

Addressing the dynamics of human-natural systems (HNS) driven by land use change (LC) is a key challenge for the sustainable development of ecosystem services (ES). However, how changes to the HNS coupling relationships affect ES is rarely reported. We used network analysis methods to construct an HNS correlation network in the Loess Plateau based on the correlation between the main components of HNS, such as ES, human factors, landscape pattern, vegetation cover, climate change and geomorphic characteristics, and quantitatively described the HNS coupling relationships through key network attributes. We analyzed the variation in HNS network attributes and their relationships with ES along an LC intensity gradient. The results show that carbon storage and soil conservation in the Loess Plateau increased by 0.56% and 0.26%, respectively, during the study period, while the habitat quality and water yield decreased by 0.11% and 0.18%, respectively. An increase in LC intensity reduces connectivity and density in the HNS network, which results in looser connections among HNS components. Importantly, we found that HNS network attributes explained 85% of ES variation across different LC intensity gradients and that connectivity and density had the strongest explanatory power. This means that LC mainly affects ES dynamics by changing the coupling strength of HNS. Our research offers a new perspective for linking LC-HNS-ES, which will help guide practitioners toward establishing and maintaining the sustainability of human well-being amidst changing HNS.

Understanding supply-demand mismatches in ecosystem services and interactive effects of drivers to support spatial planning in Tianjin metropolis, China

Metropolitan areas are being challenged by the disparity between growing societal needs and dwindling natural resource provision. Understanding the supply-demand mismatches of ecosystem services (ES) and their drivers is essential for landscape planning and decision-making. However, integrating such information into spatial planning remains challenging due to the complex nature of urban ecosystems and their intrinsic interactions. In this study, we first assessed and mapped the supply, demand, and mismatches of six typical ES in Tianjin, China. We then clustered numerous townships based on their corresponding spatial characteristic of ES supply-demand mismatches. We also used Random Forest regression to examine the relative importance of drivers and applied Partial Least Squares structural equation modelling to decouple their interactions. The results showed that, the distribution of ES supply and demand showed obvious spatial heterogeneity, with a common surplus of ES supply in highly natural mountainous region and an excess of demand in urban centre. Additionally, all towns were classified into four spatial clusters with homogeneous states of supply-demand mismatches, serving as basic units for spatial optimization. Moreover, the interactions between drivers affected ES supply-demand mismatches in a coupled manner, including the direct effects of the socioeconomic factor (-0.821) and landscape composition (0.234), as well as the indirect effects of the biophysical factor (0.151) and landscape configuration (0.082). Finally, we discussed the utility of analysing the spatial mismatches between ES supply and demand for integrated territorial planning and coordinated decision-making.

Spatiotemporal assessment of ecosystem services supply-demand relationships to identify ecological management zoning in coastal city Dalian, China

Integrating ecosystem services supply-demand relationships into ecological management zoning is a hot topic. Most studies have focused on the matching relationship between the supply and demand of ecosystem services. However, the extent to which both are coordinated at different matching levels is ignored, that is, whether ecosystem services supply and demand tend to reinforce each other at high levels or constrain each other at low levels. Therefore, taking Dalian as an example, this study constructed a research framework for ecological management zoning by integrating the matching and coupling coordination relationship of ecosystem services supply-demand. We found that the supply of ecosystem services in Dalian decreased by 23.70% and the demand increased by 22.54% from 2005 to 2019. There was an obvious mismatch and disharmony in the supply and demand of ecosystem services, and the matching and coordination often did not exist simultaneously. Overlay analysis was used to divide Dalian into four ecological management zones: eco-conservation, eco-development, eco-improvement, and eco-restoration zones. This study helped in integrating the matching and coupling coordination relationship of ecosystem services supply-demand into the environmental management system, which has practical significance for the sustainable development of ecosystem services.

Assessment of Multiple Ecosystem Services and Ecological Security Pattern in Shanxi Province, China

The ecological security pattern construction could effectively regulate ecological processes and ensure ecological functions, then rationally allocate natural resources and green infrastructure, and, finally, realize ecological security. In view of serious soil erosion, accelerated land desertification, soil pollution and habitat degradation in Shanxi Province, the spatial distribution of six key ecosystem services, including water conservation (WC), soil conservation (SC), sand fixation (SF), carbon storage (CS), net primary productivity (NPP) and habitat quality (HQ), was analyzed by using multiple models. The comprehensive ability of multiple ecosystem services in different regions was quantified by calculating multiple ecosystem services landscape index (MESLI). Combined with ecosystem services hotspots, the ecological security pattern of Shanxi Province was constructed by using the minimum cumulative resistance model. The results showed that the spatial differences in ecosystem services in Shanxi Province were obvious, which was low in the seven major basins and Fen River valley, and high in the mountains (especially Taihang and Lvliang Mountains) for WC, SC, CS, NPP and HQ, while high SF was only distributed in the northern Shanxi. The MESLI showed that the ability to provide multiple ecosystem services simultaneously was low in Shanxi Province, with the medium and low grade MESLI regions accounting for 58.61%, and only 18.07% for the high grade MESLI regions. The important protected areas and ecological sources of the ecological security pattern were concentrated in the Lvliang and Taihang Mountains, which were consistent with the key areas of ecosystem services. The ecological corridors illustrated network distribution with ecological sources as the center, the low-, medium- and high-level buffers accounted for 26.34%, 17.03% and 16.35%, respectively. The results will provide important implications for economic transformation, high-quality development and ecological sustainable development in resource-based regions worldwide.

Multicriteria spatial model to prioritize degraded areas for landscape restoration through agroforestry

Reconciling the restoration of ecosystem services within agricultural landscapes is an effort that has been advancing within degraded areas restoration through agroforestry systems. However, to contribute to the effectiveness of these initiatives, it is essential to integrate landscape vulnerability and local demands to better highlight in which areas the implementation of agroforestry systems should be prioritized. Thus, we developed a spatial hierarchization methodology as a decision support tool as an active strategy for agroecosystem restoration. The proposed method constitutes a spatial indicator of priority areas to guide agroforestry interventions, including resource allocation and public policies for payment for environmental services. The methodology consists of Multicriteria Decision Analysis implemented in GIS software by combining input datasets based on biophysical conditions, environmental and socioeconomic aspects, that integrated promotes an assessment of the environment fragility, the pressures and responses to land use dynamic; a strategy for landscape restoration and conservation of the natural habitats, and multiple specific scenarios for decision making regarding the agricultural and the local actors demands. The output of the model provides the spatial distribution of areas suitable for the implementation of agroforestry systems, sorted into four priority levels (Low, Medium, High, and Extreme priority). The method is a promising tool proposal for territorial management and governance and subsidizes future research on the flows of ecosystem services.•Assessment of the environment fragility and the pressures and responses to land use dynamic.•Strategy for landscape restoration and conservation of remaining natural habitats.•Multiple specific scenarios for decision making regarding the agricultural and the local actors demands.

Multi-Scenario Simulation of Land Use Changes with Ecosystem Service Value in the Yellow River Basin

Land use change plays a crucial role in global environmental change. Understanding the mode and land use change procedure is conducive to improving the quality of the global eco-environment and promoting the harmonized development of human–land relationships. Large river basins play an important role in areal socioeconomic development. The Yellow River Basin (YRB) is an important ecological protective screen, economic zone, and major grain producing area in China, which faces challenges with respect to ecological degradation and water and sediment management. Simulating the alterations in ecosystem service value (ESV) owing to land use change in the YRB under multiple scenarios is of great importance to guaranteeing the ecological security of the basin and improve the regional ESV. According to the land use data of 1990, 2000, 2010, and 2018, the alterations in the land use and ESV in the YRB over the past 30 years were calculated and analyzed on the basis of six land use types: cultivated land, forestland, grassland, water area, built-up land, and unused land. The patch-generating land use simulation (PLUS) model was used to simulate the land use change in the study area under three scenarios (natural development, cultivated land protection, and ecological protection in 2026); estimate the ESV under each scenario; and conduct a comparative analysis. We found that the land use area in the YRB changed significantly during the study period. The ESV of the YRB has slowly increased by ~USD 15 billion over the past 30 years. The ESV obtained under the ecological protection scenario is the highest. The simulation of the YRB’s future land use change, and comparison and analysis of the ESV under different scenarios, provide guidance and a scientific basis for promoting ecological conservation and high-quality development of river basins worldwide.

Can ecological landscape pattern influence dry-wet dynamics? A national scale assessment in China from 1980 to 2018

Land cover has been demonstrated to have substantial impacts on climate and dry-wet environment, but potential influence of landscape pattern dynamics accompanying land cover change on drought remains unclear. In this study, response of dry-wet dynamics to landscape pattern in China was examined. Results suggest that landscape pattern in China's nine agricultural districts had transformed to varying extents and showed spatiotemporal heterogeneity from 1980 to 2018. For forest landscape, the highest annual average Percentage of Landscape (PLAND) was recorded in SC, reaching 62.26%; and the highest Largest Patch Index (LPI) was presented in YGP, followed by SC, with annual values of 53.79% and 46.26% respectively. The QTP has the most prominent forest connectivity in spite of its lower abundance. For grass landscape, the highest abundance and dominance were recorded in QTP, with annual PLAND fluctuation range of 49.66%-63.52% and annual LPI variation range of 34.10%-58.46%, which is associated with its climate and altitude. The most prominent crop landscape abundance and dominance were recorded in HHHP, with annual PLAND fluctuating interval of 56.53%-60.64%, indicating the highest agricultural development level in this district. At landscape level, dry-wet circumstance could be improved with enhancements in the largest patch percentage, patch density and spatial connectivity, while worsen with increases of landscape fragmentation and separated degree. At class level, increases in abundance and dominance of forest and crop landscapes would reduce drought risk, while it was opposite for grass landscape. Improved forest connectedness would optimize dry-wet environment and reduce drought risk. The PLAND of forest and crop landscapes contributed the most prominent effect to alleviate drought intensity. Compared with forestland and grassland, determining suitable crop landscape configuration to reduce drought risk is more complex because the balance between agricultural economic benefits and ecological landscape effects should be taken into account.

Spatio-Temporal Evolution, Prediction and Optimization of LUCC Based on CA-Markov and InVEST Models: A Case Study of Mentougou District, Beijing

With the rapid advancement of urbanization and industrialization, the contradiction between the social economy and resources and the environment has become increasingly prominent. On the basis of limited land resources, the way to promote multi-objective comprehensive development such as economic, social development and ecological and environmental protection through structure and layout regulation, so as to maximize regional comprehensive benefits, is an important task of current land spatial planning. Our aim is to obtain land-use-change data in the study area using remote-sensing data inversion and multiple-model simulation. Based on land suitability evaluation, we predict and optimize the land use structure of the study area in 2030 and evaluate and compare ecosystem services. Based on remote-sensing images and eco-environmental data from 1985 to 2014 in the study area, land use/land cover change (LUCC) and future simulation data were obtained by using supervised classification, landscape metrics and the CA-Markov model. The ecosystem services were evaluated by the InVEST model. The analytic hierarchy process (AHP) method was used to evaluate the land suitability for LUCC. Finally, the LUCC in 2030 under two different scenarios, Scenario_1 (prediction) and Scenario_2 (optimization), were evaluated, and the ecosystem service functions were compared. In the last 30 years, the landscape in the study area has gradually fragmented, and the built-up land has expanded rapidly, increased by one-third, mainly at the cost of cropland, orchards and wasteland. According to the suitability evaluation, giving priority to the land use types with higher environmental requirements will ensure the study area has a higher ecosystem service value. The rapid development of urbanization has a far-reaching impact on regional LUCC. Intensive land resources need reasonable and scientific land use planning, and land use planning should be based on the suitability evaluation of land resources, which can improve the regional ecosystem service function.

Integrating Landscape Pattern into Characterising and Optimising Ecosystem Services for Regional Sustainable Development

Humans benefit from ecosystem services (ES) and profoundly influence the ecosystem in rapid urbanisation and large-scale urban sprawl contexts, especially at the landscape level. However, the impacts of landscape pattern, the driving mechanism of sub-ES and the spatially explicit regional optimisation, have been largely ignored. In response, to the present paper explores two primary aspects: the relationship among ES, landscape pattern, urban income and agricultural output, and the regional governance of optimised ES values (ESV), using the Wuhan urban agglomeration as a case study area. The survey method is employed in obtaining the adjusted magnitude matrix of land use and ecosystem services. Spatial regression analyses are conducted on each ES, including food provision, climate regulation and soil maintenance, with socio-economic indicators and landscape pattern index as explanatory variables. Finally, geographically weighted regression and scenario analyses are conducted on each sub-ESV to generate adjusted coefficients in each county for ESV regulation. The results show that urban per capita disposable income and agricultural output significantly contribute to ESV change, with the former being negative and the latter being positive. A highly aggregated landscape also produces reduced ESV, particularly in soil maintenance and gas and climate regulation. We summarise the ESV in 2020 and in the period after adjustment in different administrative counties. Provision, regulation and culture ecosystem benefits substantially increase when attempts are made to lower the landscape aggregation pattern by 1%. In general, counties and county-level cities have the largest ESV, with food provision as the optimum ecosystem benefit. Districts in the capital city show an immense growth in provision and regulation, and county-level cities show the highest growth rate in cultural service. Integrating the landscape pattern into characterising and optimising ES, provides references for regional governance on land-use planning and socio-economic development, which is vital to sustainable regional development.