Rapid urbanization exerts profound pressure on urban biodiversity, yet long-term assessments integrating multi-source remote sensing data remain scarce. Objective: Focusing on the Hangzhou Bay Urban Agglomeration, a rapidly developing region in China’s Yangtze River Delta, this study aims to construct a remote sensing-based Biodiversity Index (BI) and analyze its spatiotemporal evolution and underlying drivers. Six Essential Biodiversity Variables derived from satellite observations (2000–2024) were integrated using Principal Component Analysis. Spatial autocorrelation and Geodetector models were then applied to examine BI dynamics and driving factors. The regional BI declined gradually from 0.80 in 2000 to 0.72 in 2024, with the rate of decline slowing after 2020 and a partial recovery observed in Zhoushan. Marked inter-city heterogeneity exists: Huzhou retains the highest and most stable BI due to extensive forest cover, whereas Jiaxing exhibits the lowest BI and the most pronounced decline, driven by rapid expansion of construction land. Land use/cover (LULC) and fractional vegetation cover (FVC) emerge as the dominant drivers (average q-values of 0.196 and 0.208, respectively), and their interaction explains over 46% of the spatial variance in BI. Road density shows a consistently increasing influence over time. This study demonstrates the utility of remote sensing-based frameworks for monitoring urban biodiversity dynamics and provides actionable insights for evidence-based land use planning and ecological restoration.

Natural wetland loss constitutes a primary threat to waterbirds worldwide, increasingly forcing them to rely on expanding artificial wetlands. Extensive underground coal mining across the North China Plain has created numerous subsidence wetlands, which could serve as important alternative habitats for migratory and wintering waterbirds. However, the effects of different management regimes on waterbirds in these novel artificial wetlands remain poorly understood, hindering effective strategies for reconciling human development with waterbird conservation. Here, we conducted a long-term field survey (2017–2025) of wintering waterbirds across 15 subsidence wetlands under four distinct human management regimes in the Huaibei coal mining area. We recorded 22,712 waterbirds of 45 species. We found that high-intensity aquaculture and floating photovoltaic systems were associated with reduced waterbird diversity, increased community dissimilarity, altered species composition, and the loss of multiple threatened species from survey records. We also found that ecological aquaculture and unutilized wetlands may serve as favorable habitats as alternatives to natural wetlands. Our findings demonstrate that subsidence wetlands can provide vital wintering habitats when managed sustainably, but intensive development severely compromises their conservation value. Future research should integrate habitat variables and year-round surveys to optimize management strategies for these expanding artificial ecosystems.

During crop growth, leaf photosynthetic capacity changes continuously, and the vertical distribution of leaf nitrogen (Na) and chlorophyll (Chla) affects photosynthesis in different canopy layers. Understanding stratified photosynthesis is vital for accurate prediction of crop photosynthetic capacity. We conducted a two-year field study on winter wheat and paddy rice in Eastern China, measuring leaf maximum carboxylation rate (Vc_max25), maximum electron transport rate (J_max25), Na, and Chla every 7–10 days from greening to maturity. We analyzed vertical variations of these parameters in upper (T-1), middle (T-2), and lower (T-3) canopy layers and explored relationships between Na/Chla and Vc_max25. Results showed significant vertical variations: Vc_max25 and J_max25 in T-1 were higher than T-2, and T-2 higher than T-3. The vertical distribution of Na and Vc_max25 was more pronounced than Chla. Correlation between Na and Vc_max25 increased from T-1 to lower layers, while Vc_max25-Chla correlation decreased. A single Vc_max25 estimation model based on Na performed well across layers (R²=0.619, RMSE=15.751 µmol m⁻² s⁻¹). Differentiating T-1 from T-2/T-3 improved Chla-based models. Na was better than Chla for characterizing Vc_max25 vertical variation, with Chla-based models requiring separation of T-1 from T-2/T-3. This study provides key insights for remote sensing of photosynthetic parameters and improves understanding of crop canopy photosynthesis.

During crop growth, leaf photosynthetic capacity changes continuously, and the vertical distribution of leaf nitrogen (N_a, in g m⁻²) and chlorophyll (Chl_a, in μg cm⁻²) affects photosynthesis in different canopy layers. Understanding stratified photosynthesis is vital for the accurate prediction of crop photosynthetic capacity. We conducted a two-year field study on winter wheat and paddy rice in Eastern China, measuring the leaf maximum carboxylation rate (V_cmax25), maximum electron transport rate (J_max25), N_a, and Chl_a every 7–10 days from greening to maturity. We analyzed vertical variations in these parameters in the upper (T-1), middle (T-2), and lower (T-3) canopy layers and explored relationships between N_a/Chl_a and V_cmax25. The results showed significant vertical variations: V_cmax25 and J_max25 in T-1 were higher than in T-2, and T-2 was higher than T-3. The vertical distribution of N_a and V_cmax25 was more pronounced than that of Chl_a. The correlation between N_a and V_cmax25 increased from T-1 to the lower layers, while the V_cmax25-Chl_a correlation decreased. A single V_cmax25 estimation model based on N_a performed well across layers (R² = 0.619, RMSE = 15.751 µmol m⁻² s⁻¹). Differentiating T-1 from T-2/T-3 improved the Chl_a-based models. N_a was better than Chl_a for characterizing the V_cmax25 vertical variation, with the Chl_a-based models requiring separation of T-1 from T-2/T-3. This study provides key insights for remote sensing of photosynthetic parameters and improves the understanding of crop canopy photosynthesis.