In permafrost regions, vegetation growth is influenced by both climate conditions and the effects of permafrost degradation. Climate factors affect multiple aspects of the environment, while permafrost degradation has a significant impact on soil moisture and nutrient availability, both of which are crucial for ecosystem health and vegetation growth. However, the quantitative analysis of climate and permafrost remains largely unknown, hindering our ability to predict future vegetation changes in permafrost regions. Here, we used statistical methods to analyze the NDVI change in the permafrost region from 1982 to 2022. We employed correlation analysis, multiple regression residual analysis and partial least squares structural equation modeling (PLS-SEM) methods to examine the impacts of different environmental factors on NDVI changes. The results show that the average NDVI in the study area from 1982 to 2022 is 0.39, with NDVI values in 80% of the area remaining stable or exhibiting an increasing trend. NDVI had the highest correlation with air temperature, averaging 0.32, with active layer thickness coming in second at 0.25. Climate change plays a dominant role in NDVI variations, with a relative contribution rate of 89.6%. The changes in NDVI are positively influenced by air temperature, with correlation coefficients of 0.92. Although the active layer thickness accounted for only 7% of the NDVI changes, its influence demonstrated an increasing trend from 1982 to 2022. Overall, our results suggest that temperature is the primary factor influencing NDVI variations in this region.

Dust storms are natural events that remove and relocate surface soil, damage vegetation crops, and disrupt many other aspects of the earth 's terrestrial ecosystem. Despite the importance of the risk assessment of dust hazards, vulnerability modeling of them is very limited. For this reason, this study provides a conceptual model based on Structural Equation Modeling and the Finite Mixture Partial Least Squares (FIMIX-PLS) approach using interviews and questions for vulnerability modeling of dust in Ahvaz County, Khuzestan province, Iran. Key model drivers included Resilience Actions, Natural-Physical effects, Economic Influence, and Social Influence. The Aerosol Optical Depth (AOD) product of MODIS/Terra was used to develop a dust hazard map. MODIS/Terra performance was evaluated using observed PM10 data from Ahvaz County air pollution monitoring stations. Land use mapping was used for spatial detection of agricultural land affected by the intensity of the AOD map in the previous step. The vulnerability model fitting results showed that the model had acceptable validity (SRMR = 0.013). Results showed that approximately 25 % of agricultural lands are at high and very high dust hazard risk. Based on modeling results, natural-physical variables affect about 89 % and 97 % of social and economic drivers, respectively. Conversely, social influences significantly negatively affect dust storm resilience resulting in agricultural vulnerability. Based on results from the integrated model, strengthening farmers ' resilience strategies against dust hazards requires additional research and attention.

Legumes play a crucial role in the restoration and utilization of salinized grassland. To explore the physiological response mechanism of Astragalus membranaceus and Medicago sativa seedlings to salt stress, salt stress culture experiments with five NaCl concentration treatments (0 mmol/L, 50 mmol/L, 100 mmol/L, 200 mmol/L, and 300 mmol/L) were conducted on these two legume seedlings. Morphological characteristics, physiological features, biomass, and the protective enzyme system were measured for both seedlings. Correlation analysis, principal component analysis (PCA), and membership function analysis (MFA) were conducted for each index. Structural equation modeling (SEM) was employed to analyze the salt stress pathways of plants. The results indicated that number of primary branches (PBN), ascorbate peroxidase (APX) activity in stems and leaves, catalase (CAT) activity in roots, etc. were identified as the primary indicators for evaluating the salt tolerance of A. membranaceus during its seedling growth period. And CAT and peroxidase (POD) activity in roots, POD and superoxide dismutase (SOD) activity in stems and leaves, etc. were identified as the primary indicators for evaluating the salt tolerance of M. sativa during its growth period. Plant morphological characteristics, physiological indexes, and underground biomass (UGB) were directly affected by salinity, while physiological indexes indirectly affected the degree of leaf succulence (LSD). Regarding the response of the protective enzyme system to salt stress, the activity of POD and APX increased in A. membranaceus, while the activity of CAT increased in M. sativa. Our findings suggest that salt stress directly affects the growth strategies of legumes. Furthermore, the response of the protective enzyme system and potential cell membrane damage to salinity were very different in the two legumes.