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The ecosystem service concept is recognized as a useful tool to support sustainability in decision-making. In this study, we collaborated with actors in the Helge å catchment, southern Sweden, in an iterative participatory ecosystem service assessment. Through workshops and interviews, we jointly decided which ecosystem services to assess and indicators to use in order to achieve a sense of ownership and a higher legitimacy of the assessment. Subsequently, we explored the landscape-level interactions between the 15 assessed services, and found that the area can be described using three distinct ecosystem service bundles. The iterative, participatory process strengthened our analysis and created a shared understanding and overview of the multifunctional landscape around Helge å among participants. Importantly, this allowed for the generated knowledge to impact local strategic sustainability planning. With this study, we illustrate how similar processes can support local decision-making for a more sustainable future.

Although the research framework of ecological function zoning is complex and diverse, there are not many spatially continuous zoning results, which can be effectively applied to watershed management practices. Ecosystem service bundles and trade-offs can identify interactions among multiple ecosystem services, and achieve better social-ecosystem management when applying to ecological function zoning. Taking the Dongjiang Lake Basin, China, as research area, the study used the InVEST model to investigate the trade-offs and synergies of ecosystem services at township and grid scales, respectively. Then, the study conducted ecological function zoning based on the bundles and trade-off intensity among ecosystem services. The results showed that food production showed extremely significant trade-offs with other services in the two scales, in which the trade-off intensity between food production and water purification was the largest, and the water areas were the hotspots of trade-off intensity. Based on the ecosystem service bundles at the township, combined with the trade-off intensity, the watershed was finally divided into four ecological functional zones, namely, agricultural product supply area (southern part in the study area), economic forestry area (northeast regions in the study area), water supply area (western areas of the study area), and forest conservation area (northern areas in the study area), accounting for 29.27%, 14.63%, 17.07%, and 39.03%, respectively. The study contributed to the ecological function maintenance and sustainable development in Dongjiang Lake Basin and provided an important reference in ecological zoning.

ContextLandscape structure is thought to affect the provision of ecosystem service bundles. However, studies of the influence of landscape configuration on ecosystem service trade-offs and synergies in urban areas are limited. This study used Bayesian Belief Networks to predict ecosystem service trade-offs and synergies in the urban area comprising the towns of Milton Keynes, Bedford and Luton, UK.ObjectivesThe objectives of this study were to test (1) a Bayesian Belief Network approach for predicting ecosystem service trade-offs and synergies in urban areas and (2) assess whether landscape configuration characteristics affect ecosystem service trade-offs and synergies.MethodsBayesian Belief Network models were used to test the influence of landscape configuration on ecosystem service interactions. The outputs of a Principal Component Analysis (PCA) on six ecosystem services and landscape configuration metrics were used as response and explanatory variables, respectively. We employed Spearman’s rank correlation and principal component analysis to identify redundancies between landscape metrics.ResultsWe found that landscape configuration affects ecosystem service trade-offs and synergies. A sensitivity analysis conducted on the principal components showed that landscape configuration metrics core area (CORE) and effective mesh size (MESH) are strong influential determinants of ecosystem service trade-offs and synergies.ConclusionsThis study demonstrates that landscape configuration characteristics affect ecosystem service trade-offs and synergies and that a core set of metrics could be used to assess ecosystem service (ES) trade-offs and synergies. The findings may be relevant to planning and urban design and improved ecosystem management.

Ecological function zoning is an essential means of scientific management of ecosystems. According to the characteristics of ecological function zoning, implementing zoning control is conducive to the governance and protection of the ecological environment and the maintenance of ecological sustainability. This study was conducted with the Nansi Lake Basin as the cross-section for 2018. The Integrated Valuation of Ecosystem Services and Trade-offs model was adopted to assess and measure five ecosystem services, including water yield, crop production, soil conservation, carbon storage and carbon sequestration, and habitat quality. The Self-Organizing Feature Maps neural network was applied to obtain the ecosystem service bundles, and then, the ecological function zones were divided. The results indicated that the overall spatial pattern of ecosystem services in the study zone showed a decreasing schema from east to west; There was a trade-off between supply services and support services and a synergy between supply services and regulatory services; according to the bundling results, the Nansi Lake Basin was divided into four ecological functional zones: the eastern ecological surplus zone, the central crop supply zone, the western ecological balance zone, and the lake habitat protection zone. The results showed that (1) the spatial distribution of various ecosystem services in the Nansi Lake Basin showed spatial heterogeneity and specific regional laws, showing a decreasing pattern from the east to the west as a whole, especially in soil conservation, carbon sequestration, and habitat quality. (2) According to the supply and spatial distribution of each ecosystem service, the Nansi Lake Basin was divided into four ecological functional zones: the eastern ecological surplus zone, the central crop supply zone, the western ecological balance zone, and the lake habitat protection zone. (3) For zone I, provisioning services and regulation services were in synergy. For zone II and zone III, the provisioning service had a trade-off relationship with the regulation service and the supporting service. For zone IV, supporting services were trade-offs not only with provisioning services but also with regulating services. In general, the trade-offs between ecosystem service in the Nansi Lake Basin were stronger than the synergies, and the overall benefits of ecosystem services were smaller. Relying on the perspective of the ecosystem service bundles, at the county level, this study provided an analysis of the trade-offs and synergies among ecosystem services in the Nansi Lake Basin, which helped formulate the management plan for the corresponding region and provided the appropriate recommendations for regional habitat conservation and restoration. Graphical Abstract

Ecosystem services (ESs) play an important role in sustainable landscape management. People value ESs in diverse ways encompassing social and ecological domains and we need to bring these different values together. We used social-cultural and biophysical methods to map a diverse set of ESs at two spatial scales in a UNESCO Biosphere Reserve in Norway. The ESs bundled into three distinct social–ecological system archetypes which were similar in their distribution and relative ES values at both spatial scales. The bundles were also well matched to relative ESs values of the Biosphere Reserve zones (core, buffer, and transition) indicating that the bundles capture the social–ecological systems of the zones. We argue that it is important to consider the social–ecological context of the zones to provide sufficient knowledge to inform management. Our work has the capacity to contribute to sustainable land management that takes biocultural values into consideration.

In the context of carbon peak and energy structure transformation, ecosystem service bundle(ESB) have obvious changes. As a typical ecologically fragile area in China, the study of ESB in Shanxi Province plays a significant effect in regional sustainable development and ecological governance. This paper employs the PLUS model to simulate land use patterns, which utilizes land use data about Shanxi Province for the years 1980, 2000, and 2020. By integrating this with the dynamic ecosystem service value (ESV) model to assess the ESV, the evolutionary trajectory of the ESB is systematically revealed. Additionally, the driving factors behind the changes in ESB are analyzed using geographic detectors. The results indicated that: (1)From 1980 to 2020, the area of cultivated land consistently decreased, while the area of construction land expanded rapidly. By 2040, the area of cultivated land under the NDS is projected to decrease by 4.21%, whereas under the FPS, it is expected to increase by 4.35% due to policy intervention. (2)The total value of ESV exhibited fluctuations in an ‘N-type’ pattern. From 1980 to 2020, there was an overall decline of 2.05%, but the ESV is projected to rebound by 0.84% in 2040(FPS). (3)The synergistic relationship among ecosystem services was dominant, accounting for 88.79%, yet the trade-off coefficient between FP-CR increased by 23.5% over the past decade, which is underscoring the significant conflict between food production and ecological protection.(4)Three types of ESBs were identified: the agricultural production-leading bundle (ESB1), the ecological regulation-strengthening bundle (ESB2), and the water conservation-sensitive bundle (ESB3).The proportion of stable types reached its peak at 82.91% under the AEDS, highlighting the reinforcing effect of market mechanisms on ecological function lock-in. The research findings can provide valuable decision support for land space optimization in ecologically fragile areas and the value transformation of ecological product.

The degradation of ecosystem structure and function on the Qinghai-Tibet Plateau is the result of a combination of natural and anthropogenic factors, with landscape change driven by global change and human activities being one of the major ecological challenges facing the region. This study analyzed the spatiotemporal characteristics of ecosystem services (ESs) and landscape patterns in eastern Qinghai province (EQHP) from 2000 to 2018 using multisource datasets and landscape indices. Three ecosystem service bundles (ESBs) were identified using the self-organizing map (SOM), and changes in ecosystem structure and function were analyzed through bundle-landscaped spatial combinations. The study also explored the interactions between ESs and natural and human factors using redundancy analysis (RDA). We revealed an increase in total ecosystem service in the EQHP from 1.59 in 2000 to 1.69 in 2018, with a significant change in landscape patterns driven by the conversion of unused land to grassland in the southwest. Forestland, grassland, and unused land were identified as important to the supply of ESs. In comparison to human activities, natural environmental factors were found to have a stronger impact on changes in ESs, with vegetation, meteorology, soil texture, and landscape composition being the main driving factors. However, the role of driving factors within different ESBs varied significantly. Exploring the response of ecosystem services to changes in landscape patterns can provide valuable insights for achieving sustainable ecological management and contribute to ecological restoration efforts.

Rapid urbanization is profoundly impacting the ecological environment and landscape patterns, leading to a decline in ecosystem services (ES) and posing threats to both ecological security and human well-being. This study aimed to identify the spatial and temporal patterns of ecosystem service bundles (ESB) in the Beibu Gulf urban agglomeration from 2000 to 2030, analyze the trajectory of ESB evolution, and elucidate the drivers behind ESB formation and evolution. We utilized the Patch-generating Land Use Simulation (PLUS) model to establish baseline (BLS), carbon sequestration priority (CPS), and urbanization priority (UPS) scenarios for simulating land use patterns in 2030. Following the assessment of ecosystem service values (ESV) through the equivalent factor method, we identified the spatiotemporal distribution patterns of ESB using the K-means clustering algorithm. By employing stability mapping and landscape indices, we identified and analyzed various types of ESB evolutionary trajectories. Redundancy analysis (RDA) was employed to pinpoint the drivers of ESB formation and evolution. The results revealed that from 2000 to 2030, land use changes were primarily observed in cropland, forestland, and construction land. Between 2000 and 2020, 92.88% of the region did not experience shifts in ESB types. In UPS, the ESB pattern in the study area underwent significant changes, with only 76.68% of the region exhibiting stabilized trajectories, while the other two scenarios recorded percentages higher than 80%. Key drivers of ESB-type shifts included initial food provision services, elevation, slope, changes in the proportion of construction land, and population change. This multi-scenario simulation of ESB evolution due to land use changes aids in comprehending potential future development directions from diverse perspectives and serves as a valuable reference for formulating and changing ecological management policies and strategies.

The Yellow River Basin (YRB) is recognized as an essential ecological safeguard in China, significantly contributing to ecological stability and environmental protection. However, rapid socioeconomic development poses significant threats to the ecological security of the region. To address this issue, this study used normalized difference vegetation index data to identify ecological source areas. Using optimal parameters-based geographical detector model processed a multi-source data set to develop an ecological spatial network. Methods for topological and pattern analysis were utilized to examine the network. Additionally, various ecosystem services (ESs) within the ecological source areas and their interrelationships were calculated to analyze their associations with network characteristics, climate, and human factors under different network patterns. Finally, based on the importance of the structure and function of regional vegetation, a series of strategies has been proposed to optimize and protect the stability of its spatial distribution. The research findings show that: (1) areas with high ES indicator values are mainly found in the upper reaches of the YRB and the adjacent regions of the Taihang Mountains (2) the ecological spatial network of the YRB is denser in the mid-upper reaches and sparser in the lower reaches. (3) There is a significant synergy between water supply and water conservation within the ecological source areas, while landscape aesthetics and carbon storage, as well as water supply and carbon storage, exhibit significant trade-off effects. (4) Five network patterns and six ES bundles were identified. The correlation between ESs, network topological metrics, and climate-human factors varies across different patterns, with more structurally complete network patterns generally providing better ESs.

Understanding ecosystem services(ESs)and their interactions will help to formulate effective and sustainable land use management plans, and clarifying the balance and synergy between watershed ecosystem services can provide a basis for the regulation of the ecological environment in different regions of the watershed and the maximization of overall ecological benefits. This paper takes the Yellow River Basin as the research object and uses the Ecosystem Services and Trade Offs (InVEST)model to evaluate the water yield (WY), soil conservation (SC), carbon storage (CS) and habitat quality (HQ) of the Yellow River Basin. The paper adopts the Carnegie-Ames-Stanford Approach (CASA)model to evaluate the net primary productivity (NPP), draws the spatial distribution map of the five ecosystems, analyzes the trade-off and synergy between the five ecosystems using correlation and binary spatial correlation, and expresses it in space. In addition, it adopts self-organizing mapping (SOM) method to identify ecosystem service clusters. The results show that: (1) ES is generally higher in the upper reaches of the Yellow River, and lower in the middle reaches. (2) WY and NPP, HQ, CS and WY are trade-off relationships, and other ecosystem services are synergistic relationships. Trade-offs and synergy show obvious spatial heterogeneity. (3) The ecosystem services of the Yellow River Basin, driven by different factors, can be divided into three areas, namely WY and SC service leading functional areas, HQ and CS service leading functional areas, and NPP service leading functional areas. Finally, it discusses the driving factors of the spatial heterogeneity of the balance of the ecosystem service functions of the Yellow River Basin and the suggestions of land use management in the basin.