Research on the spatiotemporal evolution and trade-offs of ecosystem services (ESs) is important for optimizing the ecological security barrier system and promoting coordinated socio-economic development. Natural factors, e.g., climate change, and human factors, e.g., unreasonable land use, have impacted and damaged ecosystem structure and function, leading to challenges with ES trade-offs and the spatial identification of priority protected areas. Here, the spatiotemporal evolution characteristics of five ESs (water yield, nitrogen export, soil retention, carbon storage, and habitat quality) in Anhui Province, China, from 2000–2020 were analyzed based on the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model. The trade-offs and spatial patterns among different ESs were explored using Pearson correlation and hotspot analyses; the dynamics of natural growth, cultivated land protection, and ecological protection scenarios for ESs in 2030 were simulated and analyzed by coupling InVEST with the patch-generating land use simulation (PLUS) model. The results reveal the following. (1) From 2000–2020, increases in water yield and soil retention occurred, with concurrent declines in the other services; the total nitrogen high-value area was mainly concentrated in the plain, with the other services’ high-value areas mainly concentrated in the Dabieshan and Southern Anhui Mountains, with each ES showing similar spatial distributions across years. (2) The ESs were mainly synergistic, with trade-offs mainly between nitrogen export and other services. (3) Hotspot overlap between water yield and the other ESs was relatively low; no more than 6.53% of ecosystems per unit area provided five ESs simultaneously. (4) Other than water yield, the ecological protection scenario was more conducive to improving ecosystem functions. This study’s results indicate inadequate synergy among ESs in Anhui Province; competition among land types must be further balanced in the future. This study provides a basic reference for implementing ecological projects and constructing ecological security patterns.

River islands are sandbars formed by scouring and silting. Their evolution is affected by several factors, among which are runoff and sediment discharge. The spatial-temporal evolution of seven river islands in the Nanjing Section of the Yangtze River of China was examined using TM (Thematic Mapper) and ETM (Enhanced Thematic Mapper)+ images from 1985 to 2015 at five year intervals. The following approaches were applied in this study: the threshold value method, binarization model, image registration, image cropping, convolution and cluster analysis. Annual runoff and sediment discharge data as measured at the Datong hydrological station upstream of Nanjing section were also used to determine the roles and impacts of various factors. The results indicated that: (1) TM/ETM+ images met the criteria of information extraction of river islands; (2) generally, the total area of these islands in this section and their changing rate decreased over time; (3) sediment and river discharge were the most significant factors in island evolution. They directly affect river islands through silting or erosion. Additionally, anthropocentric influences could play increasingly important roles.

As one of the most developed regions in China, the plain of East China is undergoing gradually increased flooding under the obvious urbanization process. This paper mainly analyses the trend of water level time series in the region during the past decades, and assesses the temporal and spatial variation of water level and indicators of hydrological alteration. The results show that there is a trend of increasing water level. Bigger slope and higher significant level can be observed in monthly minimum than in monthly maximum water level, in peri-urban than in urban areas. Meanwhile, it is observed that the mean monthly minimum and maximum water level increased in both urban and peri-urban regions, while decreased coefficients of variation (Cv) in urban and increased Cv in peri-urban regions were calculated. Most indicators of hydrologic alteration in urban stations are concentrated to the range of variability approach target, while most indicators are discrete in peri-urban stations. And the degree of hydrologic alteration is higher in peri-urban than in urban regions.

Rivers and streams are recognized as potential greenhouse gas (GHGs: CO₂, CH₄, and N₂O) sources, contributing to global warming. However, GHG emissions from rivers and streams have received insufficient attention compared to other ecosystems (forests, grasslands, wetlands, etc.). In this study, dissolved GHG concentrations were measured in the Qingyijiang River, the longest tributary in the lower reaches of the Yangtze River, during two campaigns in September 2020 and April 2021. Our results showed that the Qingyijiang River was oversaturated with dissolved GHGs. The dissolved GHG concentration in the surface river water ranged from 8.70 to 67.38 μM CO₂, 0.03 to 2.06 μM CH₄, and 12.30 to 32.22 nM N₂O. The average diffusive GHG emission rates were 31.89 ± 22.23 mmol CO₂ m⁻² d⁻¹, 697.22 ± 939.82 μmol CH₄ m⁻² d⁻¹, and 18.12 ± 7.73 μmol N₂O m⁻² d⁻¹. The total emissions (CO₂-e) were CO₂ (58%) dominated, while CH₄ (38%) played a moderate role in total emissions. Temporally, average GHG concentrations and fluxes from the studied river in April were higher than those in September. The concentration and flux of CH₄ exhibited high spatial variability, similar to those in most rivers. In contrast, we found that there was no obvious spatial variability in CO₂ and N₂O concentrations but a significant difference among reaches in N₂O fluxes. We found that water temperature and flow velocity were the potential drivers for the regulating spatial variability in GHGs. However, no other observed limnological parameters were found in governing the spatial patterns of GHGs, suggesting a complex combination of factors governing GHG fluxes; thus, these inconspicuous mechanisms underscore the need for further research. Overall, our study suggests that this river acts as a minor source of GHGs relative to other rivers, and CH₄ cannot be ignored when considering aquatic carbon emissions.