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Under the context of global climate change, vegetation on the Tibetan Plateau (TP) has experienced significant changes during the past three decades. In this study, the spatiotemporal changes of growing season vegetation index (GSVI) on the TP were analyzed using various methods from pixel level to ecoregion level. In addition, a relative importance approach was employed to investigate the regulating effect of temperature and precipitation on vegetation. During the period of 1982-2012, vegetation on the TP was generally experiencing a greening trend, but with pronounced fluctuations. The interannual variation of the long-term GSVI was most significant in the Qaidam Basin and southern forest. At ecoregion scale, vegetation in the arid and frigid arid zones showed a browning tendency, with other ecoregions presenting greener trends. Over a large proportion of the TP, there exist change points in the GSVI time series, which were mainly concentered around the year 1996 and 2000. The Hurst exponent identified that a majority (88%) of the vegetation on the plateau would maintain a persistent trend in the future, which would mainly consist of undetermined development and greening trends. TP vegetation during the 1990s experienced more greening than in the 1980s or 2000s according to the interdecadal analysis. The long-term change in growing season vegetation was most positively correlated with the temperature during the same period, followed by the temperature in the preseason and postseason periods. There were more negative relationships of vegetation change with precipitation than with temperature. The relative contribution of the temperature to the vegetation changes exhibited an opposite spatial pattern to that of precipitation. Overall, the findings in this work provide an essential archive of decade-scale vegetation dynamics that may be helpful for projecting the future ecosystem dynamics on the Tibetan Plateau, such as the consistent greening., Competing Interests: The authors have declared that no competing interests exist.

Projecting the distribution of malaria vectors under climate change is essential for planning integrated vector control activities for sustaining elimination and preventing reintroduction of malaria. In China, however, little knowledge exists on the possible effects of climate change on malaria vectors. Here we assess the potential impact of climate change on four dominant malaria vectors (An. dirus, An. minimus, An. lesteri and An. sinensis) using species distribution models for two future decades: the 2030 s and the 2050 s. Simulation-based estimates suggest that the environmentally suitable area (ESA) for An. dirus and An. minimus would increase by an average of 49% and 16%, respectively, under all three scenarios for the 2030 s, but decrease by 11% and 16%, respectively in the 2050 s. By contrast, an increase of 36% and 11%, respectively, in ESA of An. lesteri and An. sinensis, was estimated under medium stabilizing (RCP4.5) and very heavy (RCP8.5) emission scenarios. in the 2050 s. In total, we predict a substantial net increase in the population exposed to the four dominant malaria vectors in the decades of the 2030 s and 2050 s, considering land use changes and urbanization simultaneously. Strategies to achieve and sustain malaria elimination in China will need to account for these potential changes in vector distributions and receptivity.

• A novel salinization monitoring model based on 3-D feature space had been proposed with the overall accuracy of 93%. • The relative actions of climate change and human activities have been quantitatively distinguished from a new perspective of "' soil solute transport-vegetation response '". • The NDVI ∩ other factors were the dominant factors in the salinization process. • Human activities gradually became the dominant factor in salinization improvement or intensification area. Within the context of global change, the evolution of salinization in the Yellow River Delta has undergone dramatic changes. However, it is not clear how it responds to the combined processes of climate change and human activity（reclamation projects, changes in land-use types, and increases in fertilizer use）Based on the optimal soil salinization monitoring index model, this study retrieved the annual time series data set for salinization from 1984 to 2022 and then analyzed the spatial and temporal evolution patterns of salinization in the modern Yellow River Delta. The mechanism of the response of salinization evolution to climate change and human activities was investigated using Geodetector. The main conclusions were as follows: (1) From 1984 to 2022, the salinization intensity in the northeastern coastal zone of the Yellow River Delta showed an increasing trend, while that in the southwestern inland area showed an improving trend. (2) The high-frequency salinization zones were mainly concentrated near the mainstream and tributaries of the Yellow River, while zones with desalinization, re-salinization, and new salinization zones were mainly distributed in the main stream of the Yellow River. (3) There were obvious differences in the dominant factors in the evolution of salinization in different historical periods. In 1984, soil component factors and vegetation coverage were the dominant factors in the evolution of salinization. In 2022, vegetation coverage and land-use types had the strongest explanatory power for the salinization process. (4) The influence of natural and human activity factors on the salinization process was not independent, but a mutually reinforcing process. The interaction between NDVI and other factors has dominated the evolution of salinization in the Yellow River Delta. From 1984 to 2022, human activities were the dominant factors that promoted the improvement or intensification of salinization in the region. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel remote sensing ecological vulnerability index (RSEVI) was proposed. • The RSEVI had better applicability with the precision of 89.75%. • The increment and increasing rate of ecological vulnerability in the northeastern parts were larger. • The precipitation had negative relationships with ecological vulnerability. • The dominant factor and dominant interactive factors differed greatly in different sub-regions. There were dramatic changes in the ecological vulnerability (EV) of the China-Pakistan Economic Corridor (CPEC) region due to the effects of climate change and human activity. Obtaining field observation and statistical data for the evaluation of the EV of the CPEC region is difficult due to its transnational status. This study proposes a novel remote sensing ecological vulnerability index (RSEVI) based on the Moderate Resolution Imaging Spectroradiometer (MODIS), STRM3, DMSP-OLS, and NPP-VIIRS products. The RSEVI index was applied to the CPEC region to investigate the spatiotemporal changes in EV and the influencing factors during 2000–2019. The results showed that: (1) the large-scale application of the RSEVI index showed good applicability to the CPEC region, with a precision of 89.75%; (2) the average RSEVI value for the CPEC region was 0.83, thereby falling into a category of "intensive vulnerability"; (3) a stable trend in RSEVI was observed for the entire CPEC region during the study period, except for the Indus Basin where there was a significant change; (4) the increasing rate of the RSEVI in the northeastern parts exceeded that of other parts during 2000–2019; (5) precipitation, temperature, and vegetation coverage showed negative relationships with RSEVI, whereas RSEVI showed a positive relationship with slope. The RSEVI results indicated that ice and bare land were the most vulnerable, whereas cropland was the least vulnerable; (6) there were differences in the dominant factor and dominant interactive factor among different sub-regions. The results of this study could provide important decision support for the protection of the ecological environment and for economic development. [ABSTRACT FROM AUTHOR]