Despite the Yangtze River Basin (YRB)’s abundant land and forestry resources, there is still a dearth of research on forecasting habitat quality changes resulting from various geographic and environmental factors that drive landscape transformations. Hence, this study concentrates on the YRB as the focal area, with the aim of utilizing the Patch Landscape Upscaling Simulation model (PLUS) and the habitat quality model to scrutinize the spatial distribution of landscape patterns and the evolution of HQ under four scenarios: the natural development scenario (NDS), farmland protection scenario (CPS), urban development scenario (UDS), and ecological protection scenario (EPS), spanning from the past to 2030. Our results show that (1) from 2000 to 2020, the construction land in the YRB expanded at a high dynamic rate of 47.86% per year, leading to a decrease of 32,776 km2 in the cultivated land area; (2) the UDS had the most significant expansion of construction land, followed by the NDS, CPS, and EPS, which had higher proportions of ecologically used land such as forests and grasslands; (3) from 2000 to 2020, the HQ index ranged from 0.211 to 0.215 (low level), showing a slight upward trend, with the most drastic changes occurring in the low-level areas (−0.49%); (4) the EPS had the highest HQ (0.231), followed by the CPS (0.215), with the CPS increasing the HQ proportion of the lower-level areas by 2.64%; (5) and in addition to government policies, NDVI, DEM, GDP, and population were also significant factors affecting landscape pattern and changes in habitat quality.

River heat flux (HF) regime has been significantly affected by anthropogenic activities and climate variation, and it is of great significance to deeply explore intrinsic driving mechanisms and ecological effects. This study uses the middle reaches of the Yangtze River as its research area and, by constructing the wavelet model and the IHA-RVA model, quantifies the evolution mechanism and internal law of "flow- water temperature (WT) - HF" over the past four decades and investigates the effects of Three Gorges Dam on the ecological reproduction of "Four Major Chinese Carp". The results show that, (1) Flow and WT have three change cycle scales; The overall hydrologic variations of flow and WT were 64% and 62%, respectively, close to high variation. (2) The overall HF shows a decreasing trend from 1983 to 2019, with significant changes in HF in spring and winter regulated by the Three Gorges Reservoir; The basin flow-WT-HF relationships exhibit a hysteretic pattern, with the maximum WT occurring one month after the peak HF and flow. (3) The "Four Major Chinese Carp" natural breeding season is closely related to the time when the WT reaches 18°C; HF is a vital habitat factor that influences fish spawning and reproduction.

River heat flux (HF) regime has been significantly affected by anthropogenic activities and climate variation, and it is of great significance to deeply explore intrinsic driving mechanisms and ecological effects. This study uses the middle reaches of the Yangtze River as its research area and, by constructing the wavelet model and the IHA-RVA model, quantifies the evolution mechanism and internal law of ‘flow- water temperature (WT) – HF’ over the past four decades and investigates the effects of Three Gorges Dam on the ecological reproduction of ‘Four Major Chinese Carp’. The results show that, (1) Flow and WT have three change cycle scales; The overall hydrologic variations of flow and WT were 64 and 62%, respectively, close to high variation. (2) The overall HF shows a decreasing trend from 1983 to 2019, with significant changes in HF in spring and winter regulated by the Three Gorges Reservoir; The basin flow-WT-HF relationships exhibit a hysteretic pattern, with the maximum WT occurring one month after the peak HF and flow. (3) The ‘Four Major Chinese Carp’ natural breeding season is closely related to the time when the WT reaches 18 °C; HF is a vital habitat factor that influences fish spawning and reproduction.

Quantitatively separating the influence of climate change and human activities on runoff is crucial to achieving sustainable water resource management in watersheds. This study presents a framework for quantitative assessment by integrating the indicators of hydrologic alteration, the whale optimization algorithm and random forest (WOA-RF), and the water erosion prediction (WEP-L) model. This framework aims to reconstruct natural runoff and quantify the differences in hydrological conditions and their driving forces at multi-timescales (annual, season, and month). The results indicate that the runoff of the Wu River has decreased since 2005, with a change degree of 46%. Climate factors were found to influence the interannual variation of runoff mainly. Meanwhile, human activities had a more significant impact in autumn, with a relative contribution rate of 59.0% (WOA-RF model) and 70.8% (WEP-L model). Monthly, the picture is more complex, with the results of the WOA-RF model indicating that climate change has a significant impact in July, August, and September (88.8, 92.7, and 79.3%, respectively). However, the WEP-L model results showed that the relative contribution of land use was significant in April, May, June, October, and November (51.24, 64.23, 63.63, 53.16, and 50.63%, respectively). The results of the study can be helpful for regional water allocation.