A greater negative impact of future climate change on vegetation in Central Asia: Evidence from trajectory/pattern analysis.

In the context of global warming, vegetation changes exhibit various patterns, yet previous studies have focused primarily on monotonic changes, often overlooking the complexity and diversity of multiple change processes. Therefore, it is crucial to further explore vegetation dynamics and diverse change trajectories in this region under future climate scenarios to obtain a more comprehensive understanding of local ecosystem evolution. In this study, we established an integrated machine learning prediction framework and a vegetation change trajectory recognition framework to predict the dynamics of vegetation in Central Asia under future climate change scenarios and identify its change trajectories, thus revealing the potential impacts of future climate change on vegetation in the region. The findings suggest that various future climate scenarios will negatively affect most vegetation in Central Asia, with vegetation change intensity increasing with increasing emission trajectories. Analyses of different time scales and trend variations consistently revealed more pronounced downward trends. Vegetation change trajectory analysis revealed that most vegetation has undergone nonlinear and dramatic changes, with negative changes outnumbering positive changes and curve changes outnumbering abrupt changes. Under the highest emission scenario (SSP5-8.5), the abrupt vegetation changes and curve changes are 1.7 times and 1.3 times greater, respectively, than those under the SSP1-2.6 scenario. When transitioning from lower emission pathways (SSP1-2.6, SSP2-4.5) to higher emission pathways (SSP3-7.0, SSP5-8.5), the vegetation change trajectories shift from neutral and negative curve changes to abrupt negative changes. Across climate scenarios, the key climate factors influencing vegetation changes are mostly evapotranspiration and soil moisture, with temperature and relative humidity exerting relatively minor effects. Our study reveals the negative response of vegetation in Central Asia to climate change from the perspective of vegetation dynamics and change trajectories, providing a scientific basis for the development of effective ecological protection and climate adaptation strategies.

Strong positive direct impact of soil moisture on the growth of central asian grasslands.

As the issue of global climate change becomes increasingly prominent, the grassland ecosystems in Central Asia are facing severe challenges posed by the impacts of climate change. However, the dominant factors, impact pathways, and cumulative and time-lagged effects of climate factors on various grassland indices remain to be explored. This study selected data from 1988 to 2019, including Fractional Vegetation Cover (FVC), Leaf Area Index (LAI), Net Primary Productivity (NPP), and Vegetation Optical Depth (VOD), to characterize grassland coverage, greenness, biomass accumulation, and water content features. Utilizing multiple linear regression, path analysis, and correlation analysis, this study investigated the dominant effects, direct impacts, indirect influences, and cumulative and time-lagged effects of climate factors on various grassland indices from spatial and climatic zone perspectives. The research findings indicate that over time, the grassland FVC and NPP exhibited increasing trends, while the LAI and VOD showed decreasing trends. Grassland indices are primarily influenced by precipitation and soil moisture (SM). The direct impact of SM on grassland indices was higher than precipitation. Vapour pressure deficit (VPD) has a direct negative impact on grassland indices. Grassland indices are subject to positive indirect effects from precipitation via SM and negative indirect effects from VPD via SM. Precipitation and SM mainly exhibited no cumulative and time-lagged effects on the impact of grassland VOD. VPD primarily demonstrated cumulative and time-lagged effects on grassland indices. The research findings offer valuable insights for conserving grassland ecosystems in Central Asia, as well as for shaping socioeconomic strategies and formulating climate policies.

Probabilistic assessment of drought stress vulnerability in grasslands of Xinjiang, China.

In the process of climate warming, drought has increased the vulnerability of ecosystems. Due to the extreme sensitivity of grasslands to drought, grassland drought stress vulnerability assessment has become a current issue to be addressed. First, correlation analysis was used to determine the characteristics of the normalized precipitation evapotranspiration index (SPEI) response of the grassland normalized difference vegetation index (NDVI) to multiscale drought stress (SPEI-1 ~ SPEI-24) in the study area. Then, the response of grassland vegetation to drought stress at different growth periods was modeled using conjugate function analysis. Conditional probabilities were used to explore the probability of NDVI decline to the lower percentile in grasslands under different levels of drought stress (moderate, severe and extreme drought) and to further analyze the differences in drought vulnerability across climate zones and grassland types. Finally, the main influencing factors of drought stress in grassland at different periods were identified. The results of the study showed that the spatial pattern of drought response time of grassland in Xinjiang had obvious seasonality, with an increasing trend from January to March and November to December in the nongrowing season and a decreasing trend from June to October in the growing season. August was the most vulnerable period for grassland drought stress, with the highest probability of grassland loss. When the grasslands experience a certain degree of loss, they develop strategies to mitigate the effects of drought stress, thereby decreasing the probability of falling into the lower percentile. Among them, the highest probability of drought vulnerability was found in semiarid grasslands, as well as in plains grasslands and alpine subalpine grasslands. In addition, the primary drivers of April and August were temperature, whereas for September, the most significant influencing factor was evapotranspiration. The results of the study will not only deepen our understanding of the dynamics of drought stress in grasslands under climate change but also provide a scientific basis for the management of grassland ecosystems in response to drought and the allocation of water in the future.

Floral characteristics and pollination ecology of Manglietia ventii (Magnoliaceae), a plant species with extremely small populations (PSESP) endemic to South Yunnan of China.

Manglietia ventii is a highly endangered plant species endemic to Yunnan province in China, where there are only five known small populations. Despite abundant flowering there is very low fruit and seed set, and very few seedlings in natural populations, indicating problems with reproduction. The causes of low fecundity in M. ventii are not known, largely because of insufficient knowledge of the species pollination ecology and breeding system. We conducted observations and pollination experiments, and analyzed floral scents to understand the pollinator-plant interactions and the role of floral scent in this relationship, as well as the species breeding system. Like the majority of Magnoliaceae, M. ventii has protogynous and nocturnal flowers that emit a strong fragrance over two consecutive evenings. There is a closing period (the pre-staminate stage) during the process of anthesis of a flower, and we characterize the key flowering process as an "open-close-reopen" flowering rhythm with five distinct floral stages observed throughout the floral period of this species: pre-pistillate, pistillate, pre-staminate, staminate, and post-staminate. Flowers are in the pistillate stage during the first night of anthesis and enter the staminate stage the next night. During anthesis, floral scent emission occurs in the pistillate and staminate stages. The effective pollinators were weevils (Sitophilus sp.) and beetles (Anomala sp.), while the role of Rove beetles (Aleochara sp.) and thrips (Thrips sp.) in pollination of M. ventii appears to be minor or absent. The major chemical compounds of the floral scents were Limonene, ß-Pinene, α-Pinene, 1,8-Cineole, Methyl-2-methylbutyrate, p-Cymene, Methyl-3-methyl-2-butenoate and 2-Methoxy-2-methyl-3-buten, and the relative proportions of these compounds varied between the pistillate and staminate stages. Production of these chemicals coincided with flower visitation by weevils and beetles. The results of pollination experiments suggest that M. ventii is pollinator-dependent, and low seed set in natural populations is a result of insufficient pollen deposition. Thus, conservation of the species should focus on improving pollination service through the introduction of genetically variable individuals and increase in density of reproducing trees.