RESUMO
Ecological vulnerability and poverty are interrelated and must be addressed together. The resolution of this issue will help us to meet the challenges during the process of implementing concrete actions for realizing the 2030 UN sustainable development goals (SDGs). Ecological restoration projects (ERPs) can enhance ecosystem services (ESs) while providing policy support for improving people's livelihoods. However, processes and mechanisms of ERPs on the ecological environment and socioeconomic development in poverty-stricken and ecologically fragile areas have rarely been studied. To address these issues, we conducted a comparative analysis on the changes of land use and land cover (LULC), ecosystem services (ESs), and socioeconomic development in Bijie City, a karst rocky desertification area in southwest China, before and after the implementation of ERPs in 2000, as well as the complex relationship between these factors. ERPs have affected LULCs, ESs, socioeconomics, and poverty reduction significantly since 2000. Specifically, the total ecosystem service value (ESV) in the study area has increased by more than 3 times in the past 30 years, with the ESV of tourism services and carbon storage increasing the most, from CNY 0.001 and 337.07 billion in 1990 to CNY 11.07 and 108.97 billion in 2019, respectively. The correlation between ESs is mainly synergistic, while the tradeoff between carbon storage and water yield is in a fluctuating upward trend. LULC conversion of cropland to green, and cropland to water, wetland and shrubs has positive effects on carbon storage and water yield, respectively. During study period, GDP, urbanization increased by over 70 times, 5 times, respectively, whereas poverty population, poverty incidence, and employment rate of various sectors (i.e., agriculture, forest, animal, and fishery, or AFAF) decreased by 96.4%, 97.7%, and 18.24%, respectively. Our findings emphasized that ERPs can effectively help poor and ecologically fragile areas to get out of the poverty trap and achieve the "win-win" goals of ecological and socio-economic sustainable development. These results have profound environmental management references to China and other developing countries around the world in realizing ecological restoration, poverty reduction, and the SDGs.
Assuntos
Conservação dos Recursos Naturais , Ecossistema , Pobreza , China , Desenvolvimento Sustentável , Ecologia , HumanosRESUMO
Monitoring ecological resource change in mountainous and hilly areas (MHAs) is vital for theoretical and practical advancements of ecological resource utilization and management in complex ecosystems. The factors driving structural and functional changes in green eco-spaces (GES) in these areas are complex and uncertain, with notable spatial scale effects. However, analyzing the multi-scale driving mechanisms of ecological and socioeconomic factors at a fine spatiotemporal scale presents significant challenges. To address these challenges, we analyzed dynamic changes in GES and eco-socio-economic development in Shanghang County, a typical mountainous region in southern China. We used multiple linear regression and multi-scale geographically weighted regression model to identify key factors driving GES changes and their multi-scale effects at both global and local levels. Over the past two decades, the GES area in the study area has exhibited a consistent pattern of decline, characterized by phases of gradual decline (2000-2005), sharp decline (2005-2009), slow decline (2009-2019). Key global factors driving GES changes included elevation (ELE), slope (SLOPE), population density (PD), distance to settlements (SETTLE), and distance to administrative centers (ADMIN). These factors exhibited significant spatial heterogeneity and multi-scale effects on GES changes. Specifically, SETTLE, PD, SLOPE, and ELE consistently drove GES changes at the local level, while ADMIN only showed significant localized effects during 2005-2009. The synergy between SETTLE and SLOPE had a considerable impact on GES changes, increasing over time, whereas ELE and PD demonstrated a consistent trade-off effect. These findings provide detailed spatiotemporal insights into the driving mechanisms of natural ecological resources, offering crucial guidance for environmental management, land source management, regional economic development, and biodiversity conservation in Shanghang and analogous subtropical hilly regions worldwide.
RESUMO
Firmiana danxiaensis is an endemic species of Danxia landform in China. Identifying the main driving factors of its distribution can provide scientific basis for the conservation of F. danxiaensis and related habitats. With GeoDetector, we analyzed the correlation (measured by q value) between the spatial distribution of F. danxiaens and its habitat factors in F. danxiaens Nature Reserve in Nanxiong City and the Guangdong Danxia Mountain Tourism Scenic Area (core scenic area). Factors measured in this study included geographical elements (geomorphological type, soil subtype, elevation, slope, aspect) and climatic elements (annual precipitation and annual sunshine hours, mean annual relative humidity and mean annual wind speed). Our results showed that the main habitat factors affecting the spatial distribution of F. danxiaensis were soil subtype, annual sunshine hours, and geomorphologic genesis type. The q values of those three factors were higher than the mean values of all factors. In the pairwise combination of habitat factors, the interaction between geomorphologic genesis types â© annual sunshine hours and soil subtypes â© annual sunshine hours was enhanced by two factors and the q value was greater than the mean value of all combinations, with a strong correlation. Compared with other factors, the q value of soil subtypes, annual sunshine hours and geomorphologic genesis types were significantly different in the ecological detection of spatial distribution correlation of F. danxiaensis. The spatial distribution of F. danxiaensis was significantly correlated with soil subtypes, geomorphologic genesis types and annual sunshine hours, indicating that the GeoDetector is a useful method for vegetation habitat factor analysis and species distribution prediction.
