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Introduction: Existing studies on ecosystem service relationships are mainly qualitative or semi-quantitative assessments, but lack of quantitative exploration of aggregated ecosystem services and their influencing factors. We mapped the distributions of 12 ecosystem services of Zhejiang Province in 2000 and 2015 at the district and county level, a...
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... Over the past decade, several research efforts that present novel approaches to address this issue have been conducted. These include an ESs landscape index to compare the multifunctionality of landscapes in different communities (Rodríguez-Loinaz et al. 2015), a Multiple ESs Landscape Index (MESLI) calculated as the sum of normalized values of selected ES indicators (Shen et al. 2020), and an Ecosystem Service Bundle Index (ESBI) using structural equation modeling (Hong et al. 2020). Shaad et al. (2022) developed an indicator framework and a Fresh-Water Health Index to assess both the supply of and the demand for water ES. ...
One of the paramount challenges in natural resource management revolves around the delicate equilibrium between the demand for and the supply of diverse Ecosystem Services (ESs) within a cultural landscape. Recognizing the centrality of cultural landscapes to human well-being, the sustainability of these landscapes hinges upon the health and stability of ecosystems that can effectively provide the required ESs. Over the long term, the sustainable supply of ESs is constrained by the potential supply of ESs. Understanding the potential supply of ESs is crucial for averting compromises to the ecosystems within a landscape. This article introduces a novel perspective on evaluating the ESs of a landscape by means of efficiency analysis. Instead of presenting the potential supply of ESs in absolute terms, we offer a comparative analysis of ESs' relative supply to associated management costs. In principle, the efficiency of Landscape Units (LUs) is defined as the ratio of the potential supply of multiple ESs to the costs associated with land use and land cover management. The resultant efficiency maps serve as hot and cold spot maps, revealing efficient ecosystem compositions that yield multiple ESs. This composition reflects management efforts, incorporating various management costs. Forests emerge as pivotal ecosystems in landscapes, delivering the most ESs at the lowest costs. These efficiency maps offer valuable insights for regional planners, enabling them to enhance the supply of ES in inefficient LUs by studying the ecosystem structure and associated costs of the most efficient LUs.
... At present, an important research method in the field of ecology is to judge the trade-offs and synergies of ESs through correlation analysis, which can be used to measure the interactions between different services (Plieninger et al. 2019). Pearson or Spearman coefficients are generally in correlation analysis of ESs (Hong et al. 2020), with positive values of these correlation coefficients representing synergies and negative values representing tradeoffs. Bai et al. (2011) used correlation analysis to assess the correlation between biodiversity and ESs at the watershed scale; Liu et al. (2023) used correlation analysis to assess the trade-off synergies between biodiversity and ESs at the provincial scale. ...
Biodiversity and ecosystem services (ESs) are closely linked. Human activities have caused critical damage to the habitat and ecosystem function of organisms, leading to decline in global biodiversity and ecosystem services. To ensure sustainable development of local ecological environments, it is critical to analyze the spatial matching degree of biodiversity and ESs and identify ecologically vulnerable areas. Taking Xishuangbanna, southern China, as an example, we constructed a pixel-scale matching degree index to analyze the spatial matching degree of endangered plant diversity (EPD) and four ESs and classified the matching degree into low-low, low-high, high-low, and high-high four types. The results revealed a mismatch relationship of EPD and ESs in more than 70% of areas. Under the influence of altitude and land use/land cover (LULC) type, the matching degree of EPD and ESs showed obvious spatial heterogeneity. In low-altitude areas in the south of Xishuangbanna, EPD and ESs mainly showed mismatch, while high-altitude areas in the west had a better match. Natural forest was the main land cover in which EPD and ESs showed high-high match and its areal proportion was much larger than that of rubber plantation, tea plantation, and cropland. Our findings also stress the need to concentrate conservation efforts on areas exhibiting a low-low match relationship, indicative of potential ecological vulnerability. The pixel-scale spatial matching degree analysis framework developed in this study for EPD and ESs provides high-resolution maps with 30 m × 30 m pixel size, which can support the implementation of ecological protection measures and policy formulation, and has a wide range of applicability. This study provides valuable insights for the sustainable management of biodiversity and ESs, contributing to the strengthening of local ecological environment protection.
... These inconsistencies can be attributed to the diverse interpretation of ''nature's contribution" in indicator quantification [4,48,49]. With a sacrifice in terms of quantifying the physical amounts of NCPs, an advantage of using our rapid assessment indicator framework is the ability to spatiotemporally identify the relationships among all NCPs, which can prevent landscape managers from focusing on only easily evaluated landscape functions and lead to biased ecological governance decisions [50,51]. Moreover, using the nested multiple basin levels as assessment units, the production observation, benefit assignment, and management of NCPs are simplified across different spatial scales [52][53][54], and the NCP demands of local stakeholders are positioned in an enveloped geographical unit [55][56][57]. ...
Synergistically maintain or enhance the numerous beneficial contributions of nature to the quality of human life is an important but challenging question for achieving Sustainable Development Goals. However, the spatiotemporal distributions of global nature's contributions to people (NCPs) and their interactions remain unclear. We built a rapid assessment indicator framework and produced the first spatially explicit assessment of all 18 NCPs at a global scale. The 18 global NCPs in 1990 and 2018 were globally assessed in 15,204 subbasins based on two spatial indicator dimensions, including nature's potential contribution and the actual contribution to people. The results show that most of the high NCP values are highly localized. From 1992 to 2018, 6 regulating NCPs, 3 material NCPs, and 2 nonmaterial NCPs declined; 29 regulating-material NCP combinations (54 in total) dominated 76% of the terrestrial area, and the area with few NCPs accounted for 22%; and synergistic relationships were more common than tradeoff relationships, while the relationships among regulating and material NCPs generally traded-off with each other. Transitional climate areas contained few NCPs and have strong tradeoff relationships. However, the high synergistic relationship among NCPs in low latitudes could be threatened by future climate change. These findings provide a general spatiotemporal understanding of global NCP distributions and can be used to interpret the biogeographic information in a functional way to support regional coordination and achieve landscape multifunctionality for the enhancement of human well-being.
... the watershed. In fact, as an important supply service, FP is often associated with watershed economic development, which more likely to generate trade-offs with other services, especially regulatory services (Hong et al. 2020;Yang et al. 2021;Lu et al. 2021). Therefore, for the DJLB, government should scientifically plan agricultural production, vigorously develop ecological agriculture, and transform cultivated land into multi-functional landscape types to maximize the comprehensive ecological-economic benefits. ...
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.
... We selected a total of eight natural and six anthropogenic drivers, which theoretically and empirically influence ecosystem services (Hong et al., 2020;Shen et al., 2021). Natural drivers include elevation, slope, temperature, precipitation, NDVI, soil organic matter, distance from water systems, and distance from coastal zones. ...
Ecosystem services (ESs) have been widely used for ecological protection and land spatial planning. Natural and anthropogenic drivers exhibit a strong dynamic coupling relationship with ESs. However, current ESs-related research focused on mapping the ESs spatially or investing the trade-offs and synergies relationship between ES, ignoring the nonlinear response of ESs to natural and anthropogenic drivers. Here we aimed to investigate the nonlinear effect of 14 potential drivers (8 natural and 6 anthropogenic) on the total value of six typical ESs (ESV). Taking Beijing-Tianjin-Hebei urban agglomeration (BTH) in China as an example, we established 14 constrain lines and identified critical thresholds through the restricted cubic splines (RCS) regression. We found strong non-linear impacts of natural and anthropogenic drivers on ESV and critical thresholds existed among all the 14 constrain lines. The RCS plots showed that the overall ESV was kept at a high level before or after certain thresholds (e.g., altitude >687 m, slope >13.4°, NDVI >0.7, distance from water <31.2 km, etc.). We categorized these threshold combinations and found the potentially high ES delivery areas were mainly distributed in the Yanshan Mountian, accounting for approximately 5% of the total BTH region. These critical thresholds offer a new method to delineate conservation and restoration priority areas.
... Currently, the application of ES bundles is mainly focused on ES trade-offs and synergies [24], regionally dominant ESs, ecological-function zoning [25], landscape planning and management [10], etc. Previous studies have promoted our understanding of ES bundles, but have not considered their dynamic evolution due to the significant temporal-spatial heterogeneity of ESs [9,26]. The identification and analysis of multiyear ES bundle evaluations can be used to reveal the ES spatial pattern more effectively [14,16]. ...
Ecosystem service (ES) bundles can be defined as the temporal and spatial co-occurrence of ESs. ES bundles are jointly driven by socio-ecological factors and form at different scales. However, in recent research, a few studies have analyzed the dynamic evolution and driving mechanisms of ES bundles at different scales. Therefore, this study explored the spatial patterns of six ESs supplied in Dalian (China) from 2005 to 2015 at three spatial scales, determining the distribution and evolution patterns of ES bundles and their responses to socio-ecological driving factors. Our results are as follows: (1) We identified four ES bundles representing ecological conservation, water conservation, ecological depletion, and food supply. The developmental trajectory of each ES bundle could be attributed to the combined effects of environmental conditions and urban expansion. In particular, the water conservation bundle and food supply bundle were changed to the ecological depletion bundle. Given the ongoing urbanization, the conflict between ESs has intensified. (2) The impact of socio-ecological driving factors on ES bundles vary with scale. At three spatial scales, the digital elevation model (DEM) and normalized difference vegetation index (NDVI) had a great impact on ES bundles. Urbanization indicators also strongly explain the spatial distribution of ES bundles at the county and grid scales. The interaction factor detector shows that there is no combination of mutual weakening, indicating that the formation of ES bundles is driven by multiple factors in Dalian. Overall, this study used a more holistic approach to manage the ecosystem by studying the temporal-spatial dynamics of the multiple ESs.
... Although researchers have extensively studied ESs at a global or national scale (China), research on Zhejiang Province is fragmented. Hong et al. (2020) mapped the distributions of 12 ESs of Zhejiang Province in 2000 and 2015 at the district and county scale and explored factors associated with aggregated ES variations. However, the mechanisms of factors driving the relationships between ESs and the formation of ESB in Zhejiang Province are still unknown. ...
... The ES models (Text S1) were used to calculate the ESs of Zhejiang Province in each grid (Fig. 3) The spatial distribution of ESs in Zhejiang showed that they had obvious heterogeneity, which was also proved by the Moran index (Moran's I > 0.32, p < 0.01), an index representing spatial agglomeration. NP was lower in northeastern Zhejiang, while NE, PE, and GP were the highest on the plains of northern Zhejiang; further, WY decreased gradually from west to east and from south to north, which is consistent with the results of a previous study (Hong et al. 2020). ...
A systematic understanding of the driving mechanisms of ecosystem services (ESs) and the relationships among them is critical for successful ecosystem management. However, the impact of driving factors on the relationships between ESs and the formation of ecosystem service bundles (ESBs) remains unclear. To address this gap, we developed a modeling process that used random forest (RF) to model the ESs and ESBs of Zhejiang Province, China, in regression and classification mode, respectively, and the Shapley Additive Explanations (SHAP) method to interpret the underlying driving forces. We first mapped the spatial distribution of seven ESs in Zhejiang Province at a 1 × 1 km spatial resolution and then used the K-means clustering algorithm to obtain four ESBs. Combining the RF models with SHAP analysis, the results showed that each ES had key driving factors, and the relationships of synergy and trade-off between ESs were determined by the driving direction and intensity of the key factors. The driving factors affect the relationships of ESs and consequently affect the formation of ESBs. Thus, managing the dominant drivers is key to improving the supply capacity of ESs.
... This research assessed the sustainable use of water resources from the perspective of ecosystem services. As ecosystem services were broad topics, the trade-off and synergy among service functions could be further discussed to better reflect the integrity of the ecosystems (Hong et al., 2020). With a better understanding of ecosystem services, research hot spots continued to emerge, including ecosystem service evaluations, ecosystem service flows, and ecological compensation (Yu and Bi, 2011). ...
Water shortage is one bottleneck that limits economic and social developments in arid and semi-arid areas. As the impacts of climate change and human disturbance intensify across time, uncertainties in both water resource supplies and demands increase in arid and semi-arid areas. Taking a typical arid region in China, Xinjiang Uygur Autonomous Region, as an example, water yield depth (WYD) and water utilization depth (WUD) from 2002 to 2018 were simulated using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and socioeconomic data. The supply-demand relationships of water resources were analyzed using the ecosystem service indices including water supply-demand difference (WSDD) and water supply rate (WSR). The internal factors in changes of WYD and WUD were explored using the controlled variable method. The results show that the supply-demand relationships of water resources in Xinjiang were in a slight deficit, but the deficit was alleviated due to increased precipitation and decreased WUD of irrigation. WYD generally experienced an increasing trend, and significant increase mainly occurred in the oasis areas surrounding both the Junggar Basin and Tarim Basin. WUD had a downward trend with a decline of 20.70%, especially in oasis areas. Water resources in most areas of Xinjiang were fully utilized and the utilization efficiency of water resources increased. The water yield module in the InVEST model was calibrated and validated using gauging station data in Xinjiang, and the result shows that the use of satellite-based water storage data helped to decrease the bias error of the InVEST model by 0.69×108 m3. This study analyzed water resource supplies and demands from a perspective of ecosystem services, which expanded the scope of the application of ecosystem services and increased the research perspective of water resource evaluation. The results could provide guidance for water resource management such as spatial allocation and structural optimization of water resources in arid and semi-arid areas.
... The influence of location factors on the ESV is also very significant. The change in economic benefits caused by distance, which affects the key geographical elements of economic development (such as transportation and water systems), has a profound impact on regional land use patterns and affects the ESV [54]. Based on the analysis above, 15 influencing factors of the ESV were preliminarily drafted, including the topography, climate, soil texture, the normalized difference vegetation index (NDVI), economic development, the population level, the urbanization level, land location, traffic location, and water system location ( Table 2). ...
Water conservation areas play an important role in regional ecological security patterns. The Funiu Mountain water conservation area is located in the densely populated central region of China, where human disturbance to the ecosystem is strong and ecosystem services are facing a very serious situation. Identifying and evaluating the factors leading to changes in the ecosystem service value (ESV) of the Funiu Mountain water conservation area can provide scientific guidance for ecological management and sustainable development. Using multi-source data and machine learning methods, our research reveals the characteristics of the spatio-temporal variation in the ESV, constructs a system of ESV influencing factors from the comprehensive perspectives of the natural environment and human activities, and discusses the comprehensive effects of the influencing factors on the Funiu Mountain area from 2000 to 2015. The results are as follows. (1) From 2000 to 2005, the ESV increased 375 million yuan, and from 2005 to 2015, it decreased 154 million yuan. (2) Hydrological regulation, biodiversity maintenance, soil conservation, gas regulation, and climate regulation were the main types of ecosystem services in the Funiu Mountain area. (3) The ESV was influenced by the comprehensive effects of the natural environment and human activities. Population was the most important influencing factor of the ESV; in addition, the normalized difference vegetation index (NDVI), precipitation, and economic factors had important influences on the ESV. (4) With the intensification of human activities, humanistic factors have surpassed the relatively stable natural factors, becoming the main factors of the ESV. With economic development, the effect of human activities on the ESV may be further intensified in the future.
... Several studies have analyzed and mapped the interactions of multiple ESs by overlaying the classification maps of those multiple ESs or integrating multiple maps of ES change (Liu et al., 2017a;Sun et al., 2020). Unfortunately, in many cases, the weight of different ESs is not equal and therefore simple spatial overlays could lead to inaccuracies in ES trade-off analysis (Bagstad et al., 2014;Hong et al., 2020). Moreover, the results of the overlay analysis are discrete, making it difficult to explore the influencing mechanism behind the trade-offs. ...
... Furthermore, combinations of different socioecological drivers could affect ESs in different ways and at different times. However, limited by data availability and data quality, only a few studies have emphasized the effects of historically different combinations of drivers on ES bundles (Hong et al., 2020). Moreover, consideration of only a few drivers, or lack of socio-economic factors, might not reflect the high heterogeneity of ES bundles (Lyu et al., 2019;Qiu et al., 2020), which may result in considerable uncertainty in predicting ES bundles and ES management policymaking. ...
A comprehensive understanding of ecosystem service (ES) bundles and their socioecological drivers is vital for ecological management and policymaking. However, the underlying mechanisms are still unclear due to less attention being paid to their historical dynamics. Taking the Three Gorges Reservoir Area as a case study, this study used Pearson parametric correlation analysis, k-means clustering analysis, and redundancy analysis to investigate how the ESs and their interactions have changed over time, and to identify historical spatial patterns of ES bundles and their associations with socioecological drivers. Results showed that: (1) most ESs improved over time but soil retention, water yield, and habitat provision showed slightly decreasing trends; (2) intensive agriculture and advances in technology diminished potential ES trade-offs related to food production, while the decrease in soil retention led to a decline in its synergistic relationships with water yield and nitrogen retention; (3) three ES bundles were identified at the watershed scale. The trajectory of each ES bundle could be attributed to the common effects of ecological projects and rapid urbanization. In particular, ecological projects have promoted the transformation of the ES bundle to the direction of high supply and low trade-off, yet trade-offs between ESs have not significantly improved because of constant urban expansion in a major city and its surrounding area; (4) the socioecological drivers determining ESs and ES bundles were also time-dependent, with the ratio of forest to land, slope, and population density being the major drivers. However, other random drivers (e.g., climate change) should also be highlighted as they generate great uncertainty for predicting future ES bundles and further ES management. Overall, our results advocate the historical assessment of the relationships between multiple ESs and socioecological drivers and emphasize the necessity of embracing a historical dynamic perspective in the sustainable management of ESs.
