Contributions of climate change and human activities to vegetation dynamics in Qilian Mountain National Park, northwest China

Understanding vegetation phenology responses to easily ignored climate factors in china's mid-high latitudes

Previous studies have primarily focused on the influence of temperature and precipitation on phenology. It is unclear if the easily ignored climate factors with drivers of vegetation growth can effect on vegetation phenology. In this research, we conducted an analysis of the start (SOS) and end (EOS) of the growing seasons in the northern region of China above 30°N from 1982 to 2014, focusing on two-season vegetation phenology. We examined the response of vegetation phenology of different vegetation types to preseason climatic factors, including relative humidity (RH), shortwave radiation (SR), maximum temperature (Tmax), and minimum temperature (Tmin). Our findings reveal that the optimal preseason influencing vegetation phenology length fell within the range of 0-60 days in most areas. Specifically, SOS exhibited a significant negative correlation with Tmax and Tmin in 44.15% and 42.25% of the areas, respectively, while EOS displayed a significant negative correlation with SR in 49.03% of the areas. Additionally, we identified that RH emerged as the dominant climatic factor influencing the phenology of savanna (SA), whereas temperature strongly controlled the SOS of deciduous needleleaf forest (DNF) and deciduous broadleaf forest (DBF). Meanwhile, the EOS of DNF was primarily influenced by Tmax. In conclusion, this study provides valuable insights into how various vegetation types adapt to climate change, offering a scientific basis for implementing effective vegetation adaptation measures.

Water-related ecosystem services interactions and their natural-human activity drivers: Implications for ecological protection and restoration

Sustainable development faces the crucial challenge of safeguarding water-related ecosystem services, particularly in arid regions. However, scale-dependent interactions and their influencing factors remain unclear. This study addresses this local gap on the regional level by focusing on ecologically vulnerable mountain areas, employing a comprehensive quantitative and spatial analysis approach, utilizing Spearman coefficient, trade-off/synergy index, and trade-off/synergy criterion, to examine water-related ecosystem services interactions across scales in arid area. Additionally, a Geographical detector was used to identify dominant natural and human activity factors. Finally, we determined ecologically optimal and worst areas and proposed spatial planning and management recommendations for ecological protection and restoration. Key results indicate that: (1) From 1995 to 2015, water yield and nutrient delivery ratio exhibited a declining trend, while soil retention showed an increasing trend, with the weakest nutrient delivery ratio function in the reserve. (2) At the grid scale, there were 2 trade-offs among water-related ecosystem services in 1995, which decreased to 1 trade-off in 2005 and 2015. The synergistic was most prominent near Qinghai Lake, while the trade-off was most obvious in the western mountainous areas. Conversely, the county scale demonstrated synergy. (3) NDVI, slope, and precipitation dominantly influence the spatial heterogeneity patterns of soil retention_water yield, soil retention_nutrient delivery ratio, and water yield_nutrient delivery ratio, respectively, with natural factors outweighing human activities in impacting water-related ecosystem services. This study contributes to the improvement and optimization of ecological environment management decisions.

Vegetation Dynamics and Food Security against the Background of Ecological Restoration in Hubei Province, China

A series of ecological restoration projects have been proposed to solve ecological problems resulting from human activities. The project of returning farmlands to forests, initiated in 1999, was the most widely implemented ecological restoration project in China. Large amounts of cropland with steep slopes have been converted to forests or grasslands to promote vegetation restoration, reduce soil erosion, and control nonpoint source pollution. Therefore, identifying the dynamics of vegetation and food security is crucial for further decision making. Based on the mean normalized difference vegetation index (NDVI) and grain yield data, this study explored the vegetation dynamics and food security of Hubei Province against the background of ecological restoration. The results show that, on a whole, the NDVI significantly increased from 2000 to 2018. The spatial agglomeration of the NDVI decreased between 2000 and 2008 and then increased from 2009 onwards. High-high NDVI agglomerations were more concentrated in mountainous areas. Food security was not threatened, and the grain yield in Hubei Province and most of the cities exhibited significant upward trends, as a whole. The change trend of the grain yield was not stable during the period from 2000 to 2018. The grain yield for Hubei Province and almost all of the cities decreased during the first 5 to 11 years, probably due to the sharp decrease in the sloping cropland areas against the background of ecological restoration. Grain yield was more sensitive and had a longer downward trend in regions with steeper slopes. Increasing trends in grain yield were detected during the last 6 to 10 years for most of the cities, and this can mainly be attributed to the newly added croplands that were created from land with other kinds of land uses, the increase in grain productivity, and strict cropland protection policies. The project of returning farmlands to forests is suggested as a long-term policy from the perspective of ecological restoration, and effective measures should also be continuously taken to maintain grain production and food security.

Evaluation of the Carbon Sink Capacity of the Proposed Kunlun Mountain National Park

National parks, as an important type of nature protected areas, are the cornerstone that can effectively maintain biodiversity and mitigate global climate change. At present, China is making every effort to build a nature-protection system, with national parks as the main body, and this approach considers China's urgent goals of obtaining carbon neutrality and mitigating climate change. It is of great significance to the national carbon-neutralization strategy to accurately predict the carbon sink capacity of national park ecosystems under the background of global change. To evaluate and predict the dynamics of the carbon sink capacity of national parks under climate change and different management measures, we combined remote-sensing observations, model simulations and scenario analyses to simulate the change in the carbon sink capacity of the proposed Kunlun Mountain National Park ecosystem over the past two decades (2000-2020) and the change in the carbon sink capacity under different zoning controls and various climate change scenarios from 2020 to 2060. Our results show that the carbon sink capacity of the proposed Kunlun Mountain National Park area is increasing. Simultaneously, the carbon sink capacity will be improved with the implementation of park management and control measures; which will be increased by 2.04% to 2.13% by 2060 in the research area under multiple climate change scenarios. The research results provide a scientific basis for the establishment and final boundary determination of the proposed Kunlun Mountain National Park.

Phenological Responses to Snow Seasonality in the Qilian Mountains Is a Function of Both Elevation and Vegetation Types

In high-elevation mountains, seasonal snow cover affects land surface phenology and the functioning of the ecosystem. However, studies regarding the long-term effects of snow cover on phenological changes for high mountains are still limited. Our study is based on MODIS data from 2003 to 2021. First, the NDPI was calculated, time series were reconstructed, and an SG filter was used. Land surface phenology metrics were estimated based on the dynamic thresholding method. Then, snow seasonality metrics were also estimated based on snow seasonality extraction rules. Finally, correlation and significance between snow seasonality and land surface phenology metrics were tested. Changes were analyzed across elevation and vegetation types. Results showed that (1) the asymmetry in the significant correlation between the snow seasonality and land surface phenology metrics suggests that a more snow-prone non-growing season (earlier first snow, later snowmelt, longer snow season and more snow cover days) benefits a more flourishing vegetation growing season in the following year (earlier start and later end of growing season, longer growing season). (2) Vegetation phenology metrics above 3500 m is sensitive to the length of the snow season and the number of snow cover days. The effect of first snow day on vegetation phenology shifts around 3300 m. The later snowmelt favors earlier and longer vegetation growing season regardless of the elevation. (3) The sensitivity of land surface phenology metrics to snow seasonality varied among vegetation types. Grass and shrub are sensitive to last snow day, alpine vegetation to snow season length, desert to number of snow cover days, and forest to first snow day. In this study, we used a more reliable NDPI at high elevations and confirmed the past conclusions about the impact of snow seasonality metrics. We also described in detail the curves of snow seasonal metrics effects with elevation change. This study reveals the relationship between land surface phenology and snow seasonality in the Qilian Mountains and has important implications for quantifying the impact of climate change on ecosystems.