Spatiotemporal trends in ecosystem carbon stock evolution and quantitative attribution in a karst watershed in southwest China

Spatiotemporal Variation and Quantitative Attribution of Carbon Storage Based on Multiple Satellite Data and a Coupled Model for Jinan City, China

“…The nighttime light index was treated as discrete data in order to more scientifically and accurately analyze the driving mechanisms of geographic changes in carbon storage. The results show that B6 (nighttime light index), B1 (GDP), A1 (elevation), B2 (population density), A6 (NDVI), and A2 (slope) were always the main drivers affecting the spatial distribution of carbon storage, while A5 (temperature), B3 (density of commercial service facilities), and C1 (distance from major roads) were secondary drivers, as confirmed by this study at this point [32]. After the two-factor inter-detection effect, all factors exhibited a non-linear enhancement, which is consistent with what others have found in the Yellow River Basin [63] and the Southwest Karst Basin [32].…”

“…The results show that B6 (nighttime light index), B1 (GDP), A1 (elevation), B2 (population density), A6 (NDVI), and A2 (slope) were always the main drivers affecting the spatial distribution of carbon storage, while A5 (temperature), B3 (density of commercial service facilities), and C1 (distance from major roads) were secondary drivers, as confirmed by this study at this point [32]. After the two-factor inter-detection effect, all factors exhibited a non-linear enhancement, which is consistent with what others have found in the Yellow River Basin [63] and the Southwest Karst Basin [32]. The distribution of the nighttime lighting index plays a major role in carbon storage changes, indicating that the expansion of building sites reduces carbon storage [16].…”

“…The detection of spatial dispersion is one of the critical features of geo-detectors for identifying regional variability and explaining its driving factors [46,47]. It has been widely used in recent years in areas such as ecosystem services [32]. However, the critical aspect of using a geo-detector is determining the appropriate hierarchical spatial heterogeneity level through spatial data discretization.…”

“…In addition, there are relatively few studies on the spatiotemporal changes in carbon storage based on carbon density correction in Jinan City. While the carbon density of biomass and soil carbon has a significant relationship with the precipitation factor [32], many studies have been conducted based on factors such as the precipitation density, which is corrected to improve accuracy [32,33]. Thirdly, although the current research methods on carbon storage drivers and the selection of driver indicators can provide scientific guidance for subsequent related studies, the research objects tend to focus on regions such as urban clusters, provinces, and ecologically fragile areas [34][35][36].…”

Ecosystem-based management approaches for watershed conservation and geosustainability

“…It is essential to acknowledge that although the present study examines explicitly feeding fish, equation (1) can be universally given to any species within an ecosystem model. Consequently, this equation would produce comparable outcomes to a gatekeeper examination, which assesses the overall influence of alterations in the numbers of particular species [ 34 ]. Under the assumption of stable endeavor to fish, the annual landed value (LV) for any species subgroup and nation is computed by considering the baseline claimed value for every country.…”