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[Display omitted] • SIF and NDVI datasets had large differences on Yun-Gui Plateau and northwestern China. • Drought propagation time based on NDVI is larger than that based on SIF. • Drought had a similar impact degree in SIF and NDVI. • Both SIF and NDVI showed similar performance when monitoring crop yield. An increase in global warming has resulted in a global increase in meteorological droughts. As droughts play a key factor regulating vegetation growth, they inevitably have social and economic effects. Understanding vegetation dynamics and its response to climate change is therefor highly important to reveal the behavior mechanism of terrestrial ecosystems and to guide environmental management. In this investigation, Solar-induced Chlorophyll Fluorescence (SIF) and the Normalized Difference Vegetation Index (NDVI) were applied as vegetation indicators to describe vegetation dynamics and meteorological drought was described using the standardized precipitation evapotranspiration index (SPEI). Bias correction of precipitation and crop yield data of major crop producing areas was also used. By employing correlation coefficient of the maximum absolute value, a drought impact degree and propagation time to vegetation were defined. Dimensions of SIF and NDVI were unified by normalization. Results indicated that: (1) SIF and NDVI generally had a high level of consistency over China, and NDVI had a higher normalized value distribution level than SIF for different vegetation types. (2) Drought generally had a negative impact on vegetation in northern China and a positive impact in southern China. (3) Drought propagation time based on NDVI was larger than that based on SIF. (4) SIF had some advantages when monitoring crop yields among different crop producing areas. Results from this investigation will enable a greater understanding of SIF and NDVI for their application to monitor droughts and crop yield. [ABSTRACT FROM AUTHOR]

[Display omitted] • NDVI shows an overall increasing trend from 2000 to 2020. • The Hexi region shows a warming and wetting trend. • Extreme precipitation is more important for NDVI. • The lag effect of NDVI on climate extremes varies by indicators and spaces. Climate extremes significantly affects vegetation dynamics, and understanding the relationship between dryland vegetation and climate extremes is crucial for regional ecological security and disaster warning. According to meteorological and satellite remote sensing data, the paper analyses the dynamics of normalized difference vegetation index (NDVI) and climate extremes in the Hexi region from 2000 to 2020 using Theil-Sen Median, Mann-Kendall and linear regression methods; the relationship between climate extremes and vegetation dynamics is revealed using Pearson correlation and boosted regression trees (BRT) models. On this basis, the time-lag effect of NDVI in response to climate extremes was further investigated. The results show that the NDVI in the Hexi region increased from 2000 to 2020, with significant greening (67.72 %) and a small amount of degradation concentrated in the desert in the northwest and the oasis in the southeast. The correlation between climate extremes indicators and NDVI shows a large spatial heterogeneity, with extreme precipitation showing a high importance for all regions except oasis. NDVI has no lag or 1 month lag for extreme temperature, no lag for max 1-day precipitation amount (Rx1day) for areas other than mountainous areas, and a 3-month lag for max 5-day precipitation amount (Rx5day) for extensive areas. The results of this study could serve as a reference for the study of the relationship between vegetation dynamics and climate extremes in arid and semi-arid regions, and provide a theoretical basis for the establishment of scientific and reasonable strategies for regional vegetation restoration and conservation. [ABSTRACT FROM AUTHOR]

• Limited phosphorus availability hampers grassland productivity in Banni; PAC and PSM play key roles. • Livestock movement introduces organic matter and PSM, enhancing phosphorus accessibility for plants. • Effective phosphorus management considering livestock and organic contributions can boost grassland productivity. The Banni grasslands, located in the Kachchh district of India, have experienced significant degradation and a decrease in grassland productivity. Phosphorus is a crucial nutrient for grassland productivity, and its availability is often limited in these ecosystems. The study is a maiden attempt to understand the link between phosphorus availability, measured by the phosphorus activation coefficient (PAC), phosphate solubilizing microorganisms (PSM), vegetation patterns, indicated by normalized difference vegetation index (NDVI) and its relationship with livestock movement. Soil samples were collected from 45 locations spread across the three divisions of Banni grassland, and various soil parameters including phosphorus content, organic carbon, and microbial activity were analyzed. The results showed that the concentration of available phosphorus (AP) varied significantly among different divisions of the grassland, with division 1 having the highest AP concentration. The phosphorus activation coefficient (PAC) was also highest in division 2. Additionally, PSM diversity was significantly different among divisions, with division 2 exhibiting the highest PSM values. The NDVI values, representing vegetation density, varied across divisions, with division 1 having the highest overall NDVI. Statistical analysis revealed significant positive correlations between PAC, PSM, and NDVI. The research emphasizes the significance of PSM driven phosphorus availability in influencing vegetation dynamics within the Banni grassland ecosystem. The movement of livestock emerges as a key factor in introducing organic matter and phosphate solubilizing microorganisms, thereby facilitating the conversion of total phosphorus (TP) into forms accessible to plants. The study indicates that implementing effective phosphorus management practices, taking into account livestock movement and organic contributions, could enhance grassland productivity and ensure the long-term sustainability of the ecosystem. These findings offer valuable insights for more holistic and nuanced understanding of the complex relationships between phosphorus availability, phosphate solubilizing microorganisms, vegetation patterns, and sustainable management in the Banni grasslands and potentially in other ecosystems facing similar challenges. [ABSTRACT FROM AUTHOR]

[Display omitted] • Vegetation changes in Gannan Prefecture were in a stable increasing trend during 2000–2018. • The LISA cluster maps of NDVI were mainly characterized by "High-High" and "Low-Low" types. • Annual mean temperature, soil type and elevation were the dominant factors affecting NDVI changes. • The interaction between any two factors was higher than that of any single factor. Vegetation is essential in maintaining terrestrial ecosystem functions, and understanding why and how vegetation evolves is necessary for regional ecological management. On the Tibetan Plateau, the effects of various factors and their interactions in directing vegetation change remain unclear. Supported by the Google Earth Engine (GEE) platform, we quantified spatiotemporal vegetation variation in Gannan Prefecture on the northeastern Tibetan Plateau for 2000–2018 using trend analysis and spatial autocorrelation and explored its driving factors with a geographic detector method. The normalized difference vegetation index (NDVI) illustrated fluctuating growth from 2000 to 2018, and the overall growth rate was 0.002/year. The spatial distributions of NDVI were variable, and areas with NDVI greater than 0.8 accounted for more than 69% of Gannan Prefecture area. From 2000 to 2018, the global Moran's index of vegetation NDVI was greater than 0.52 and showed a fluctuating upward trend, indicating that the vegetation NDVI tended to be distributed with a high spatial concentration. The local Moran's index of NDVI was mainly characterized by "High-High" and "Low-Low" clustering types, and the former increased significantly, but the latter decreased. The annual mean temperature, soil type, and elevation were the dominant factors driving vegetation NDVI change in Gannan Prefecture, explaining more than 15% of the variability. Furthermore, the influence of the interaction between any two factors on NDVI was an almost nonlinear enhancement. These results could help us improve our understanding of the underlying mechanism of NDVI changes and provide a scientific basis for ecological protection in alpine regions. [ABSTRACT FROM AUTHOR]

• A system for vegetation change mechanisms in cold-arid mountainous was developed. • Climate factors dominate vegetation greening and exist nonlinear thresholds. • Topographic factors coupled with multi-factors influence vegetation degradation. • Reasonable sustainable planning can avoid further degradation of vegetation. Understanding vegetation evolution trends and their driving mechanisms are essential to uncover changes in ecosystem structure and function. Under the interaction of natural and human factors in cold-arid mountainous region, the main controlling factors and degree of nonlinear influence are not yet clear. This study utilized trend analysis, along with modeling techniques such as boosted regression trees (BRT) and structural equation model (SEM), to identify and quantify the contributions and nonlinear response thresholds of natural and human factors to normalized difference vegetation index (NDVI) in the Qilian Mountains from 2000 to 2020. The results showed that the implementation of ecological projects made the overall vegetation into greening trend (91.06%), while irrational human activities led to degradation in the central-eastern regions. The BRT showed that climatic factors dominated for overall vegetation changes, greening and significant greening. Thresholds exist for different drivers to influence both greening and degradation of vegetation. Regarding degradation/significant vegetation degradation, the importance of climate factors decreased, and topography ranked first, followed by population density and LUCC. The expansion of building and unused land will inhibit vegetation greening. SEM revealed that climate factors continued to maintain positive effect with the warm-humid change. The destruction of forestlands and grasslands led to significant degradation of vegetation in the central-eastern regions with the largest total negative effect. Topographic factors coupled with multi-factors inhibited vegetation growth in the central-eastern regions. This study provided a new framework for accurately assessing the dynamic evolution of vegetation, and better reveal the multi-factor driving mechanism vegetation changes in cold-arid mountainous regions. Future research should consider combining more accurate AI algorithms with field surveys to quantify the coupling mechanisms between factors and vegetation dynamic. It is expected to provide scientific guidance for vegetation ecosystem planning in other mountainous regions globally and support the achievement of sustainable development. [ABSTRACT FROM AUTHOR]