Nature-based solutions (NbSs) of biodiversity conservation and ecosystem restoration have been paid increasing attention as an essential approach to slow down climate change. However, to what degree an NbS approach will contribute to the combined effects of human intervention and climate change has not been well studied. From a habitat quality perspective, we set four NbS scenarios to analyze whether the NbS—mangrove restoration in particular—will be enough for climate change in Xiamen Bay of Fujian Province, China. The habitat quality module of the InVEST model (InVEST-HQ) and the Sea Level Affecting Marshes Model (SLAMM) were used to simulate the spatial-temporal changes in habitat types and habitat quality. Results show that (1) rising sea levels will cause coastal squeeze effects, impacting habitat quality due to erosion and inundation in the study area; (2) mangrove restoration is an effective way to mitigate climate change effects and to increase habitat quality; and (3) further analysis of the effectiveness of mangrove restoration shows that the consideration of mangrove fragmentation effects and sea-use impacts are necessary. The findings in this study will enrich the international discussion of NbSs to climate change in coastal areas.

Non-point source pollution (NSP) and runoff intensities and distribution are primarily affected by landscape structure and composition. Multiple causalities hinder our ability to determine significant variables that influence NSP. Therefore, we developed an approach that integrates the Soil and Water Assessment Tool (SWAT), random forest regression model, redundancy analysis, and correlation coefficient to assess the role of landscape structure on runoff and NSP in the Dongsheng basin. We used R to calculate landscape metrics and the SWAT to simulate NSP loads from 1990 to 2019. redundancy analysis (RDA), random forest, and Pearson correlation were used to analyze the relationships among landscape metrics and NSP variables. The largest patch index (LPI) shows a significant negative correlation with NSP, with an R2 of −0.58 for TP and TN and −0.62 for sediment load. The findings indicate that landscapes with larger patch sizes, a high number of patches, and aggregation of patches largely influence pollution distribution. Overall, the results suggest that the role of landscape patterns on NSP outweighs that of runoff. Moreover, the findings infer that the aggregation and connectivity of forest patches contribute to the decline in NSP load and vice versa for cropland cover. Thus, for sustainable watershed management, it is crucial to encourage unfragmented landscapes, especially pollutant-intercepting landcovers such as forests.