The mid-high latitudes of the Northern Hemisphere are one of the major gathering areas of global vegetation, playing a key role in regulating the climate and carbon cycle. Studying the interactive effects of vegetation phenological dynamics and climate change will help predict future vegetation dynamics and ecological protection. However, the response of vegetation phenology to multi-dimensional climatic factors is still unclear, and the spatiotemporal heterogeneity of their contributions to phenological changes and the complex interactions between them are not yet determined. This study used the solar-induced chlorophyll fluorescence (SIF) to invert accurate spring phenological parameters, and combined ERA5-Land datasets to obtain "water-light-heat" multidimensional climatic factors. We quantified the responses of the start of the growing season (SOS) to climate factors and the contributions and spatiotemporal heterogeneity of climate impacts, and discovered the complex relationships and influences. The results show that SOS predominantly occurred between 140-160 days during 2001-2020. SOS was slowly delayed until 2009, and then advanced before that. The climate sensitivity of SOS has obvious spatial differences, and different gradient levels of climate factors significantly affect the sensitivity of SOS. Furthermore, temperature, precipitation, and solar radiation are the dominant factors affecting SOS. Their contributions to SOS changes show obvious latitude patterns, with relative contributions and dominant areas varying across different sub-periods, but temperature consistently controlled the most area of SOS changes. This study reveals the complex interactions and mechanisms between climate change and spring phenology of vegetation on a large scale, aiding in predicting and addressing potential future ecological changes.

Vegetation changes and human activities in both natural and urban environments have played a crucial role in carbon cycling and sustainable development globally. However, there is an insufficient comparison in national vegetation changes across regions with varying intensities of human activities to those natural areas. Based on urban boundary and night-time light datasets, we have identified and extracted rural, urban-low activity, and urban-high activity areas within China. Geodetector model was applied and conducted to assess the vegetation impacts of seven distinct natural and human factors on vegetation. Results show that overall vegetation change trend was characterized by Significant greening from 2000 to 2020. Areas with less than 1% Significant degradation are predominantly located in the southeastern China. Despite the dominance of forest growth, cropland in urban areas exhibits more stability under human control. Human involvement has significant restraint on vegetation growth from rural to urban, while there was little difference in vegetation growth between areas with strong human activity and areas with weak human activity. Moreover, human factors and land use/land cover have gradually become the dominant impact combinations in the eastern China over the past 20 years. The influence of temperature is increasing annually in southern China but decreasing in northern China. Meanwhile, factors related to water (e. g. precipitation and soil moisture) had more pronounced influences on western China. Our results provide a comprehensive insight in vegetation dynamic change in areas under different degrees of human activities, as well as the alterations in main driving factors on spatial heterogeneity of vegetation.

Phenology refers to the natural responses of vegetation to environmental factors and disturbances throughout its life cycle. Focusing on the mid-high latitudes vegetation in the Northern Hemisphere, this study reported the differences in phenology extracted using “photosynthesis” and “structure” indices, specifically solar-induced chlorophyll fluorescence (SIF) and leaf area index (LAI), respectively. We analyzed the dynamics of phenology inverted by different indices and validated the inversion accuracy using data from FLUXNET2015 gross primary productivity (GPP). The results revealed that: (1) Both the start of the growing seasons (SOS) and the end of the growing seasons (EOS) showed significant advancing trend. On average, the SOS derived from SIF (143 days) was later than that derived from LAI (136 days), whereas the EOS derived from SIF (236 days) occurred earlier than that from LAI (245 days); (2) Across all four climatic zones, phenology was dominated by an advancing trend, with the rate of phenological change derived from SIF generally faster than that from LAI. Distinct differences in phenological trends were observed among various vegetation types; (3) Phenological parameters extracted using SIF were closer to actual observations than those derived from LAI, with the accuracy of SOS inversion generally higher than that of EOS for both indices. The study demonstrates that “photosynthesis” indices can produce more accurate photosynthetic phenology than “structure” indices, which provided a reference for the subsequent vegetation phenology studies.

Wildfires have become the primary mechanism for disturbing boreal forests. An adequate understanding of the restoration trend of forests after wildfires can help to develop forest recovery and protection measures. In this study, we employed Landsat 5 TM and MODIS data with vegetation area-series data to compare and assess the restoration of vegetation in the last 20 years after wildfires in the Daxinganling. The results show that (1) all vegetation types showed significant recovery trends in both burned zones (BZ) and unburned zones (UNBZ); (2) the rates of deciduous needleleaf forest (DNF) and mixed forest (MF) were slightly higher in UNBZ than in BZ, but the recovery rate of deciduous broadleaf forest (DBF) in BZ reached 156.5km 2 /a, which was higher than its rate in UNBZ; (3) DNF and MF had the same main period and existed in the same time scale with similar recovery periods, DBF has a 4-year period in BZ at a 6-year time scale, which represents DBF’s short recovery period and sharp fluctuations in this region. These results have important reference value for monitoring the restoration of boreal forest vegetation and ecological environmental protection after wildfires.

Fire has become a major disturbing factor in boreal forests, and giant forest disturbances play a vital role in regulating the climate under global warming. Therefore, it is essential to investigate the spatiotemporal patterns and main drivers of post-fire vegetation recovery for forest ecological research and post-fire recovery management. However, previous studies have focused on the post-fire forest change within the entire fire perimeter, lacking separate analysis and comparison of the burned zone (BZ) and unburned zone (UNBZ). Here, we propose the utilization of Moderate Resolution Imaging Spectroradiometer land cover type and vegetation index data to monitor vegetation dynamics and explore its drivers after the most serious forest fire in the history of P.R. China in the Greater Hinggan Mountains (GHM). The temporal and spatial patterns of vegetation recovery in the BZ/UNBZ in the GHM were analyzed using the Sen & Mann-Kendall method, Hurst index and coefficient of variation, and their driving mechanisms were explored using GeoDetector and geographically weighted regression. The results showed that there were significant differences in the spatial distribution and fluctuation of vegetation between the BZ and UNBZ, and that the BZ exhibited higher productivity and vigor. Vegetation recovery was influenced by different dominant factors and changed over time, in which land surface temperature and precipitation dominated all the time, whereas topographic relief and elevation had a more significant contribution to vegetation recovery in the BZ and UNBZ, respectively. This study provides a scientific basis for the protection and management of vegetation in disturbed forested areas, particularly after fires.

China's urban economy has developed rapidly over the decades, and the Cheng-Yu urban agglomeration has become one of China's four typical urban agglomerations, with a large population and a high level of economic development. However, the conflict between humans and the environment is becoming increasingly prominent together with economic development. In order to protect the ecological environment in urban areas, thus scientific understanding and assessment of ecological vulnerability are beneficial to establishing regional conservation measures, and serve as a key means to maintain environmental health. Based on the "SensitivityResilience-Pressure" (SRP) model, this study considered remote sensing, geographic and statistical data to construct an evaluation system for regional ecological vulnerability. In addition, the coupled AHP (Analytic hierarchy process)-Entropy weighting model was proposed to obtain the weight of each evaluation indicator and analyze the spatio-temporal distribution characteristics of the ecological vulnerability of the study area during 2000-2020. The changes and the divergence pattern were depicted by the transfer matrix, dynamic degree and spatial auto-correlation. The results indicated that the ecological vulnerability of Cheng-Yu urban agglomeration is mainly mild and moderate, with an overall high distribution in Chongqing and Chengdu, while low in the central and north zone (e.g., Ziyang, Mianyang). It is consistent with the distribution of H-H (High-High) and LL (Low-Low) clusters, respectively, having a significant positive spatial correlation. In particular, the severely vulnerable area increased from 7059 km2 in 2000 to 23553 km2 in 2020, with an increased rate of 233.66 %. Combining the transfer matrix and dynamic degree, it was found that the ecological environment underwent a rapid deterioration followed by a slow recovery. This study provides a scientific reference for the ecological policy making which serves sustainable urban development.

Panzhihua City, a typical eco-fragile region for agro-sylvo-pastoral industry in China, is located in the dry-hot valley of the Jinsha River, characterized by its big landform undulation, great elevation difference, uneven hydrothermal conditions, and complex geological structure. As a crucial ecological barrier in upper reaches of the Yangtze River, this area is abundant in water resources and mineral resources, such as vanadium and titanium. However, due to its over-development for nonnatural urban economy in the mining industry, agriculture, and animal husbandry, ecological problems are getting worse. Such problems as soil erosion and groundwater pollution have led obvious ecological degeneration in Panzhihua city. Therefore, for protecting the eco-environment and planning construction, it is significant to scientifically recognize that how eco-environment changes based on spatial-temporal, and how the driving mechanism affects Panzhihua city. Nowadays, there are some theories and methods that study eco-environmental protection and city construction in Panzhihua, but they are not comprehensive enough to study its spatial-temporal evolution and driving-force system. This study takes Panzhihua City as the research area of which evaluation factors, for example, topography, soil, vegetation, and meteorological factors, are chosen to construct an evaluation system suitable for the ecological environment vulnerability of Panzhihua City. These factors are selected in three aspects, which are ecological sensitivity, ecological recovery, and ecological pressure from 2005 to 2015 in this area. Then, spatial principal component analysis method, CA-Markov model, and dynamic degree model are applied to analyze the spatial-temporal evolution for ecological vulnerability based on three periods from 2005 to 2015 in Panzhihua City. Besides, GeoDetector is used to quantitatively analyze how spatial-temporal disparities change and what drives them to change. The results show that (1) during these 10 years, the overall ecological fragility of Panzhihua City is steadily increasing from northwest to southeast. The overall ecological quality is moderate, and regional differences are obvious. Places of moderate vulnerability or above are distributed in central and eastern regions of frequent human activities; places of mild vulnerability or below are distributed in the regions of Yanbian County and Miyi County. (2) The comparison of the changing rates based on vulnerability levels is severe > potential > moderate > mild > slight. The overall vulnerability changes within a small trend, showing a balanced two-way transition state between adjacent vulnerability levels. The comprehensive index for overall ecological vulnerability decreases period by period. (3) The interactions between each two factors toward spatial differentiation and explanatory power by ecological vulnerability show a two-factor-enhanced relation, indicating that multiple factors form the ecological vulnerability of Panzhihua City.

In this study, the evaluation factors of Panzhihua City from 2005 to 2015 were selected from the three aspects of “ecological sensitivity-ecological resilience-ecological stress” to construct an evaluation system suitable for the ecological environment vulnerability of Panzhihua City, and explore the ecological vulnerability of each period. The law of spatial and temporal differentiation is different. The results show that: (1) The overall vulnerability of Panzhihua City from 2005 to 2015 is gradually increasing in the northwest to the southeast, and the overall ecological quality is moderate; (2) The overall ecological vulnerability index of Panzhihua City is decreasing from 2005 to 2015. It shows that the fragile situation of the ecological environment in the study area is developing in a direction of gradual recovery.