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Human activities have significantly altered flow regimes, but the effects of shifting flow regimes on riparian species interactions and the ecosystem network remain unclear. This study applied a modified community-wide population model, integrated with network theory, to simulate the responses of the riparian ecosystem to potential future flow regimes in a desert oasis in northwestern China. Results indicate that the riparian ecosystem network in the desert oasis is inherently unstable under the Heihe River’s current hydrological conditions, characterized by considerable intra-annual and inter-annual runoff variability, as even minor changes in flow regimes could alter the network. Specifically, increased frequency of drought year simplifies the network, while heightened flood year frequencies (not exceeding 85%) create a more intricate network. Additionally, longer flood duration (more extended overlap with seed dispersal periods) significantly improves network connectivity and redundancy. Notably, the keystone status of species within the flow regime influences the network structure. With reduced flooding and more homogeneous flow, the keystone roles shift from trees and shrubs to herbs. This underscores the essential role of flooding events in sustaining riparian ecological networks. Thus, flood frequency, timing, and duration, alongside water quantity, should be considered in ecological restoration efforts for desert oasis environments. The study’s methodology and findings provide a scientific foundation for developing comprehensive management guidelines to regulate riparian areas under global change.

Coastlines have experienced profound alterations due to human disturbances and ocean dynamics against the backdrop of climate change and intensified anthropogenic activities. Significant modifications have occurred within the muddy coastal ecosystem, rendering it extremely susceptible to heightened levels of vulnerability. However, existing studies on coastal eco-environmental vulnerability have often overlooked crucial factors such as coastline erosion and siltation, particularly concerning coastline change. In this study, we assess coastline stability utilizing Landsat remote sensing imagery to investigate the vulnerability of coastal ecology alongside 24 economic and natural parameters, serving as indices for the Coastal Vulnerability Index (CVI) of the coastal eco-environment. Subsequently, we analyze the impact factors to vulnerability and predict trends in coastline change over the next 20 years to propose recommendations for sustainable development to safeguard the coastal eco-environment. Our findings reveal a trend towards coastline stabilization in Jiangsu, with significantly higher stability observed during 2010–2020 compared to 1985–2010. The overall CVI along the Jiangsu coast shows an downward trajectory over the past 15 years, primarily influenced by tidal action and coastal topography and geomorphology. Predictive modeling suggests Jiangsu coastline is bounded by the Sheyang estuary, with the coastline to the north dominated by stabilization and to the south dominated by siltation. Climate change, coupled with intensified human activities and future coastline alterations, may exacerbate vulnerability. Effective protection strategies for coastal ecosystems necessitate a comprehensive understanding of local natural conditions, resource availability, and socioeconomic dynamics. Governmental interventions should focus on reinforcing regulatory frameworks for coastal organism management, implementing coastal protection infrastructure, and enhancing supervision and management protocols for beachfront development, thereby fostering the sustainable management of muddy coastlines.

Global climate change has led to an increasing frequency and intensity of extreme climates (e.g., extreme temperature and precipitation), and its impact on land surface phenology (LSP) has attracted increasing attention. This study evaluated the effects of extreme climates on land surface phenology in Central Asia (CA) based on 13 extreme climate indices (ECIs). The results showed that the start of the season (SOS) of the LSP was gradually delayed, the end of the season (EOS) advanced, and the length of the growing season (LOS) shortened. Most ECIs showed varying degrees of an increasing trend, except the cold indices of the cool days (TX10p) and the cool nights (TN10p) and the precipitation indices of the max one-day precipitation amount (RX1day) and the max five-day precipitation amount (RX5day). The LSP was influenced by extreme climates, and 13 ECIs were mainly negatively correlated with the SOS and positively correlated with the EOS and LOS. Increased extreme temperature and decreased extreme precipitation contributed to the change in the LSP. The most important impact on the SOS was from the max Tmin (TNx), the mean Tmax (TXmean), while the mean Tmin (TNmean) and warm days (TX90p) also had noticeable effects. The most important impact on the EOS and LOS was from TX90p, followed by TX10p and TXmean. Based on climate model projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6), future extreme climates are projected to intensify under Shared Socioeconomic Pathways (SSPs) and will likely continue to affect the LSP. This study helps provide a basis for formulating scientific and reasonable vegetation restoration strategies and disaster warnings in Central Asia.

Spartina alterniflora (S. alterniflora) was introduced into China in the 1980s to control coastal erosion. However, it has significant negative impacts on coastal wetlands by encroaching on the habitat of native plant communities, which has seriously threatened coastal wetland function and biodiversity maintenance. The core area of the Migratory Bird Sanctuaries along the Coast of Yellow Sea-Bohai Gulf of China was taken as the study area and GF-2 remote sensing images from 2017, 2019 and 2020 were selected in this study. By using U-Net, this study extracted habitat information, identified the variation in habitat pattern, investigated interspecific competition and the characteristics of habitat type shifts. The results indicated that the U-Net model showed excellent classification performance, with the highest F1-score and MIoU. The habitat of S. alterniflora expanded and increased from 3,920 to 4,350 hm2 between 2017 and 2020. The habitat of Suaeda salsa (S. salsa) continuously fragmented and had been reduced to 1,414 hm2 by 2020. The degree of habitat fragmentation in the core area was strengthened and heterogeneity was enhanced. Moreover, while the competition between S. alterniflora and Phragmites australis (P. australis) was intensifying, both encroached on the habitat of S. salsa, which aggravated the reduction and fragmentation of the habitat of S. salsa, causing the loss of food and habitat of red-crowned cranes and further threatening biodiversity maintenance and ecosystem stability. These results can offer new insights on the habitat competitive mechanism among native plant communities and alien invasive species in the coastal wetland under global warming and anthropogenic influences.

Litter decomposition plays an important role in the nutrient cycle of terrestrial ecosystems. The alpine wetland has a high litter accumulation rate and a slow degradation rate, which is extremely sensitive to changeable freeze–thaw patterns against the background of global climate change. Freeze-thaw process is a common natural phenomenon in middle-high latitudes and high altitudes. Hydrothermal changes caused by freezing and thawing process affect the survival and physiological characteristics of microorganisms, and then affect the decomposition process of litters. The alpine wetland could be an ideal example for wetland in high altitude to study the mechanism of microbial community structure and function during litter composition during freeze–thaw process. Moreover, seldom has research in the whole process in the fields. The bacterial and fungal communities were analyzed in three different Carex litter decomposition stages—fresh, four-, and six-month—during the freeze–thaw period using 16/18S rDNA pyrosequencing. Phyllosphere microflora had identified rapid changes in the structure and function. Bacteria were mainly influenced by environmental factors (air temperature, soil moisture), and were significantly related to the degradation of litter lignin and the change of C/N ratio. Fungi were affected by both litter quality and environmental factors, and were significantly related to the degradation of cellulose and the change of C/N ratio. Moreover, phyllosphere organisms, including bacteria (Cryobacterium and Paracoccus members) and fungi (Mrakia, Mrakiella, and Naganishia), were replaced by communities with specific metabolic capabilities to adapt to each particular decomposition stage. Ilumatobacter and the fungal genera, Mycosphaerella and Athelia were characteristic of four-month-old litter samples, whereas Brevundimonas, Paracoccus and Nigrospora were characteristic of six-month-old litter samples. Our results suggest that the bacterial community structures of Carex and forest litter during initial decomposition stages may be similar but that their fungal community structures may differ substantially.