Responses of spatial relationships between ecosystem services and the Sustainable Development Goals to urbanization

Revealing the contribution of mountain ecosystem services research to sustainable development goals: A systematic and grounded theory driven review

Ecosystem services are the bridge between people and nature, especially for mountains, which cover more than two thirds of the world's territory, and are able to provide a diversity of ecosystem services and are significant for the enhancement of human well-being. Understanding how mountain ecosystem services (MES) support The United Nations (UN) Sustainable Development Goals (SDGs) is critical to realizing effective benefits from mountain resources, yet the extent to which MES support the SDGs is currently unclear and needs to be further explored. This study systematically reviewed the current research works by using grounded theory. We searched the Web of Science platform for papers closely related to mountain ecosystem services (2008-2022) and obtained 2010 papers, and further streamlined the most representative 114 papers based on the direct correlation between typical mountains, ecosystem service, and SDGs in the literature. We then explored the relationship between MES and specific SDGs and focused on the most strongly linked goals. The study indicated: (1) 66 targets (39%) and 12 SDGs (71%) were found, and we categorized the linkages into three categories, benefit, synergize, benefit & synergize. SDG3, 11, 13, 15 are goals that most strongly link to the MES, Subclasses storage and soil conservation services of ES are the most studied; (2) There is a gap between research and specific SDGs, and we need to focus on specific goals with relevant MES that are poorly researched but emphasized in SDGs; (3) The extent and emphasis of attention to mountain ecosystem services varied globally across continental regions. Therefore, we summarized a sustainable management model for mountain features. Policy makers are advocated to use our recommendations as a reference based on the specific features of the local mountains in combination with the development aims.

Optimizing the ecological network of resource-based cities to enhance the resilience of regional ecological networks

Mineral extraction in resource-based cities has caused serious damage to the original ecology, resulting in poor regional vegetation growth, reduced carbon sequestration capacity, and reduced ecosystem resilience. Especially in resource-based cities with fragile ecology, the overall anti-interference ability of the environment is relatively worse. Seeking ecological network optimization solutions that can improve vegetation growth conditions on a large scale is an effective way to enhance the resilience of regional ecosystems. This paper introduces carbon sequestration indicators and designs a differential ecological networks (ENs) optimization model (FTCC model) to achieve the goal of improving ecosystem resilience. The model identifies the patches that need to be optimized and their optimization directions based on the differences in ecological function-topology-connectivity-carbon sequestration of the patches. Finally, the resilience of the ecological network before and after optimization was compared, proving that the model is effective. The results show that the sources in the Yulin ENs form three main clusters, with connectivity between clusters relying on only a few patches. The patches in the northeastern and southwest clusters are large but their ecological functions need to be improved. After optimization, 16 new stepping stones were added, 38 new corridors were added, and the ecological function of 39 patches was enhanced. The optimized ecological network resilience was improved in terms of structure, function, and carbon sinks, and carbon sinks increased by 6364.5 tons. This study provides a reference for measures to optimize landscape space and manage ecosystem resilience enhancement in resource-based cities.

Exploring the interrelations and driving factors among typical ecosystem services in the Yangtze river economic Belt, China

Exploring the spatiotemporal characteristics of ecosystem services (ESs) and their drivers is crucial for managers to develop significant scientific policies that further sustainable development. We used the Yangtze River Economic Belt (YREB) to explore the trends, hotspots, and drivers of water yield (WY), soil conservation (SC), carbon sequestration (CS), and food supply (FS) between 2000 and 2020. Similarly, we analyzed relationships among ESs and drivers of the multiple ecosystem services landscape index (MESLI). We used the self-organizing map method to obtain the types and distribution of the ES bundles, revealing the bundles, trade-offs, and synergies among ESs. The four ESs had an increasing trend, with CS having the highest increase; ES hotspot analysis showed differences among upper, middle, and lower reaches. Constraint lines among ESs and drivers were diverse; the corresponding SC and WY reached thresholds when CS values were 1477.81 and 460.5 t km-2, respectively. When FS values were 67.34 and 86.17 × 104 Yuan·km-2, CS and WY reached their thresholds. All critical drivers of the four ESs were natural factors. The thresholds that the MESLI reached with driver status were 1000 mm (evapotranspiration), 2121 mm (precipitation), 2.42° (slope), 1.46% (soil organic matter), 36.08% (sand), 30.75% (proportion of non-agricultural population), 18.57% (cropland proportion), 1.05 × 104 persons·km-2 (population density), and 84.84% (proportion of non-agricultural industries in total gross domestic product), respectively. FS, water supply, and ecological conservation bundles changed over the 20 years, and trade-offs and synergies among ESs within bundles differed. We revealed the complexity of ESs from multiple perspectives, which will enable the development of ecosystem management and conservation recommendations for the YREB and large-scale economic zones worldwide.

Exploring the coupling and decoupling relationship of urbanization and carbon emissions in China

Burgeoning urbanization is a defining challenge for global carbon emissions mitigation in the coming decades. In this context, achieving low-carbon urbanization remains an urgent issue that demands prompt solutions. The coupling and decoupling relationships between urbanization and carbon emissions play an important role in the coordination of urbanization development and carbon emissions reduction, which has rarely been explored in existing studies, especially in China at the county level. To address this gap, the coupling and decoupling relationship between the urbanization level (UL) and carbon emissions density (CED) was explored using an improved coupling degree model and the Tapio decoupling method in China at the county level from 2000 to 2020. The results showed that the UL and CED of China both exhibited increasing trends, and the spatial distribution was quite similar, with the UL increasing from 0.018 in 2000 to 0.028 in 2020 and the CED increasing from 95.163 ton/km2 in 2000 to 295.746 ton/km2 in 2020. The spatial distribution of hotspots in the UL change differed with time, whereas that in the CED change was relatively stable. However, both of them were concentrated in eastern China. The coupling degrees of the UL and CED in China were 0.348, 0.355, 0.369, 0.370, and 0.338 in 2000, 2005, 2010, 2015, and 2020, respectively, with the moderately unbalanced type (>35%) being dominant at the county level and mainly scattered in eastern China. The changes in the spatial distribution patterns of the 10 subcategories were quite limited, with the systematically balanced type being dominant (89%). The decoupling types of the UL and CED during 2000-2005, 2005-2010, and 2010-2015 were weak decoupling, while those in 2015-2020 were expansive negative decoupling. At the county level, the most significant transition occurred between expansive negative decoupling, strong decoupling, and strong negative decoupling. The proportion of strong decoupling type counties peaked in 2015-2020 (70.86%), whereas that of the strong negative decoupling type counties remained high (17.55%), scattering the country. These findings can advance policy enlightenment of low-carbon urbanization and green development for China against the backdrop of "30·60 dual carbon" goal.

Landscape pattern and ecosystem services are critical for protected areas' contributions to sustainable development goals at regional scale

Protected areas are essential for the conservation of biodiversity, natural and cultural resources, and contribute to regional and global sustainable development. However, since authorities and stakeholders concern more on the conservation targets of protected areas, how to better evaluate the protected areas' contributions to sustainable development goals (SDGs) remains generally understudied. To fill this knowledge gap, we chose the Qinghai-Tibet Plateau (QTP) as the study area, mapped the SDGs in 2010, 2015 and 2020, detecting the interactive relationships among SDGs. Then we used the landscape pattern indices and ecosystem service (ES) proxies to describe the characteristics of national nature reserves (NNRs), and explore the contributions of protected areas to SDGs using panel data models. The results showed that from 2010 to 2020, most cities of QTP improved their SDG scores to >60. The three cities with the best SDG performance improved their average scores by nearly 20 %. Among the 69 pairs correlations of SDG indicators, 13 synergies and 6 trade-offs were observed. About 65 % of the SDG indicators were significantly correlated with landscape pattern or ESs of NNRs. Carbon sequestration had a significant positive effect on 30 % of the SDG indicators, while habitat quality had a negative effect on 18 % of the SDG indicators. For the landscape pattern indices, the largest patch index had a significant positive effect on 18 % of the SDG indicators. This study highlighted that the ESs and landscape pattern could well quantify the contribution of protected areas to SDGs, which can provide essential implications for protected area management and regional sustainable development.

Spatially Non-Stationary Response of Carbon Emissions to Urbanization in Han River Ecological Economic Belt, China

Within the context of the "30·60 dual carbon" goal, China's low-carbon sustainable development is affected by a series of environmental problems caused by rapid urbanization. Revealing the impacts of urbanization on carbon emissions (CEs) is conducive to low-carbon city construction and green transformation, attracting the attention of scholars worldwide. The research is rich concerning the impacts of urbanization on CEs but lacking in studies on their spatial dependence and heterogeneity at multiple different scales, especially in areas with important ecological statuses, such as the Han River Ecological Economic Belt (HREEB) in China. To address these gaps, this study first constructed an urbanization level (UL) measurement method. Then, using a bivariate spatial autocorrelation analysis and geographically weighted regression model, the spatial relationships between UL and CEs from 2000 to 2020 were investigated from a multiscale perspective. The results were shown as follows. The total CEs in the HREEB witnessed an upsurge in the past two decades, which was mainly dispersed in the central urban areas of the HREEB. The ULs in different regions of the HREEB varied evidently, with high levels in the east and low levels in the central and western regions, while the overall UL in 2020 was higher than that in 2000, regardless of the research scale. During the study period, there was a significant, positive spatial autocorrelation between UL and CEs, and similar spatial distribution characteristics of the bivariate spatial autocorrelation between CEs and UL at different times, and different scales were observed. UL impacted CEs positively, but the impacts varied at different grid scales during the study period. The regression coefficients in 2020 were higher than those in 2000, but the spatial distribution was more scattered, and more detailed information was provided at the 5 km grid scale than at the 10 km grid scale. The findings of this research can advance policy enlightenment for low-carbon city construction and green transformation in HREEB and provide a reference for CE reduction in other similar regions of the world.