Zhaofei Wen

Monitoring species-level vegetation dynamics within mountainous riparian zones presents significant challenges due to pronounced hydrological variability, intricate terrain, and the presence of narrow, fragmented vegetation corridors. These spatial configurations intensify mixed-pixel effects, giving rise to the common view that species-level monitoring in such complex riparian environments necessitates the use of sub-meter or ultra-high-resolution remote sensing imagery. However, the high costs and limited routine availability of such data constrain their application for temporally continuous monitoring under dynamic hydrological conditions. This study investigates the feasibility of using meter-scale optical satellite imagery for species-level vegetation monitoring in narrow and hydrologically dynamic mountainous riparian zones. By employing PlanetScope imagery as a representative source of meter-scale, high-temporal-resolution data, we investigate the feasibility of mapping dominant species coverage (CDS) through the integration of multiple machine learning models. To address the pronounced temporal variability characteristic of riparian environments, this study further investigates the efficacy of a multi-temporal integration (MTI) strategy in stabilizing species-level vegetation signals under fluctuating hydrological conditions. The findings indicate that CDS estimation based on single-date imagery is highly susceptible to the timing of image acquisition, with prediction performance showing considerable variation across acquisition dates (R² ranging from approximately 0.53 to 0.90). This variability reflects the combined effects of meteorological conditions, water-level fluctuations, and vegetation phenology on image quality and background interference. By integrating predictions from multiple acquisition dates, the MTI strategy markedly enhanced both prediction accuracy and temporal consistency. For the best-performing model, MTI increased the R² to approximately 0.91 and reduced the RMSE to about 0.09, while models with initially lower performance demonstrated greater relative improvements following integration. Overall, the results demonstrate that meter-scale satellite imagery, when integrated with frequent temporal sampling, can yield reliable species-level data in narrow and heterogeneous riparian environments, which have traditionally been thought to necessitate sub-meter resolution. This underscores the practical applicability of meter-scale data for ecological monitoring in complex riparian systems.

As an important geographical position in China, the middle and lower reaches of the Yangtze River play an important role in the construction and development of the Yangtze River Economic Belt. The evolution of mid-channel bar (MCB) has a good reference value for wetland protection and waterway safety, and the dynamic changes of vegetation on the continent are also crucial for river ecosystem functions and related ecosystem services. In this paper, based on the Landsat image data from 1987 to 2020, we used the ArcGIS software to synthesize the bands and improved the normalized differential water index method and the object-oriented classification method, so as to obtain the forms of MCB and some vegetation classification vectors on the continents in the middle and lower reaches of the Yangtze River in the past 30 years. In addition, we compared the data with high spatial resolution images to verify the accuracy and reliability of the data. This dataset can be used for analysis of the evolution of MCB in the middle and lower reaches of the Yangtze River, analysis of the impact of environmental factors, and research on landscape pattern changes.

Vegetation dynamics on mid-channel bars (MCBs) is essential for supporting ecosystem functions and associated services in river systems, especially in dammed large rivers. Generally, there are two possible changing patterns that vegetation of MCBs downstream a dam would experience. On one hand, the vegetation area may shrink because of a decrease in the MCB area in the post-dam period, which has been observed in many rivers around the world. On the other hand, the MCB vegetation area may expand because flood disturbances would be weakened by dam operation. However, little evidence has been reported to clarify such confusion. Therefore, vegetation dynamics of MCBs in the mid-lower Yangtze River downstream the Three Gorges Dam (TGD; the world’s largest dam) is selected as a case study to address the issue. Using long-term (1987–2017) Landsat archive images, this study reveals the spatiotemporal variations of vegetation area change intensities (VACIs; indicated by dynamic trends) on MCBs in the mid-lower Yangtze River. Results show that an overall VACI in the post-dam period (2003–2017) is about three times faster than that in the pre-dam period (1987–2002). In other words, the rate of vegetation colonization accelerated after the TGD operation began in 2003. Moreover, the VACIs in the post-dam period are size dependent, where large size MCBs are likely to gain higher VACIs: Small-sized MCBs (0.33 km²/yr), medium-sized MCBs (1.23 km²/yr), large-sized MCBs (1.49 km²/yr). In addition, VACIs of individual MCBs in the post-dam period are distance dependent, where the further a MCB was from the TGD, the higher the VACI. It is also suggested that the weakened flood disturbances in the post-dam could explain the rapid vegetation growth and colonization. This work is not only beneficial for managing and protecting MCBs downstream the TGD after its operation, but is also helpful in understanding vegetation dynamics of MCBs in other dammed river systems around the world.

Forest ecosystem plays a vital role in the global carbon cycle and maintaining climate stability. However, how net primary productivity (NPP) dynamics of different stand ages of forest respond to climatic change and residual (being other climate factors or human activities) still remain unclear. In this study, firstly, forests are divided into two categories based on their stand age: forests appeared before appeared before the research period (F_old), and forests appeared during the research period (F_new). Secondly, we improved a quantitative method of basic partial derivatives to disentangle the relative contributions of climatic factors, other climate factors, and human activities to the NPP of F_old and F_new. Then, different scenarios were simulated to identify the dominant drivers for forest restoration and degradation. In this study, we hypothesized the residual of F_old was other climate factors rather than human activities. Our results revealed that from 2000 to 2019, F_old and F_new of NPP in Yangtze River Basin showed a significant increment trend and precipitation was the major positive contributor among all of the climatic factors. We found that, in F_old, climate change and other climate factors contributed 9.77% and 28.33%, respectively, in explaining NPP. This finding unsupported our initial hypothesis and implied that residuals should be human activities for F_old. Furthermore, we found that human activities dominate either restoration or degradation of F_new. This result may be due to the attenuated human disturbances and strengthened forest management, such as ecological policies, forest tending, closing the land for reforestation, etc. Therefore, based on disentangling the two types of factors, we concluded that human activities govern the forest change, and imply that the environment-friendly forest managements may favorite to improving the forest NPP against the impacts of climate change. Thus, effective measures and policies are suggested implement in controlling forest degradation in facing climate change.

The downstream reach of the Three Gorges Dam (TGD) along the Yangtze River (1560 km) hosts numerous mid-channel bars (MCBs). MCBs dynamics are crucial to the river’s hydrological processes and local ecological function. However, a systematic understanding of such dynamics and their linkage to TGD remains largely unknown. Using Landsat-image-extracted MCBs and several spatial-temporal analysis methods, this study presents a comprehensive understanding of MCB dynamics in terms of number, area, and shape, over downstream of TGD during the period 1985–2018. On average, a total of 140 MCBs were detected and grouped into four types representing small (33 km²) MCBs, respectively. MCBs number decreased after TGD closure but most of these happened in the lower reach. The area of total MCBs experienced an increasing trend (2.77 km²/yr, p-value < 0.01) over the last three decades. The extra-large MCBs gained the largest area increasing rate than the other sizes of MCBs. Small MCBs tended to become relatively round, whereas the others became elongate in shape after TGD operation. Impacts of TGD operation generally diminished in the longitudinal direction from TGD to Hankou and from TGD to Jiujiang for shape and area dynamics, respectively. The quantified longitudinal and temporal dynamics of MCBs across the entire Yangtze River downstream of TGD provides a crucial monitoring basis for continuous investigation of the changing mechanisms affecting the morphology of the Yangtze River system.