The pattern, change and driven factors of vegetation cover in the Qin Mountains region

Shifting climatic responses of tree rings and NDVI along environmental gradients

Variations in the growth of aboveground biomass compartments such as tree stem and foliage significantly influence the carbon cycle of forest ecosystems. Yet the patterns of climate-driven responses of stem and foliage and their modulating factors remain poorly understood. In this study, we investigate the climatic response of Norway spruce (Picea abies) at 138 sites covering wide spatial and site fertility gradients in temperate forests in Central Europe. To characterize the annual growth rate of stem biomass and seasonal canopy vigor, we used tree-ring chronologies and time-series of NDVI derived from Landsat imagery. We calculated correlations of tree-ring width and NDVI with mean growing season temperature and standardized precipitation evapotranspiration index (SPEI). We evaluated how these climate responses varied with aridity index, soil category, stand age, and topographical factors. The results show that the climate-growth responses of tree rings shift from positive to negative for SPEI and from negative to positive for temperature from dry (warm) to wet (cold) areas. By contrast, NDVI revealed a negative response to temperature across the entire climatic gradient. The negative response of NDVI to temperature likely results from drought effects in warm areas and supporting effects of cloudy conditions on foliage greenness in wet areas. Contrary to NDVI, climate responses of tree rings differed according to stand age and were unaffected by local topographical features and soil conditions. Our findings demonstrate that the decoupling of stem and foliage climatic responses may result from their different climatic limitation along environmental gradients. These results imply that in temperate forest ecosystems, the canopy vigor may show different trends compared to stem growth under ongoing climate change.

Fire regime of peatlands in the Angolan Highlands

The Angolan Highlands region includes the Angolan miombo woodland ecoregion which supports miombo woodland, grasslands, subsistence agricultural land, and peatland deposits. Extensive fires, slash and burn agriculture, peat fuel extraction, and peatland drainage are among the anthropogenic practices that threaten these peatland deposits. Peat fires cause peatland degradation, release significant amounts of greenhouse gases, deteriorate air quality, and contribute towards climate change and biodiversity loss. This study presents an analysis of the fire regimes over the period 2001 to 2020 in an under-studied area of the Angolan Highlands. Moderate Resolution Imaging Spectroradiometer (MODIS) fire and vegetation data were used in combination with a land use/land cover (LULC) classification map to calculate fire frequency, burn area, and fire regimes. The fire patterns within the study site are comparable to those found in African woodland savannas. Across the study site, 6976 km² (11.31%) of the land surface area burned at least nine times from 2001 to 2020, occurring largely within in the river valley environment. Considering the different LULC classes, peatlands were calculated to (a) burn more frequently (average fire frequency from 2001 to 2020 = 9.12), (b) have the smallest proportion (4.11%) of area which remained unburnt over the fire archive, and (c) have the largest average proportion (45.65% or 746 km²) of burnt area per year. Peatland burning occurred predominantly during drier months from May to September. The results of this study highlight the strong influence of LULC on the fire frequency and distribution in the study area, requiring unique fire management strategies. As has been documented for boreal and tropical peatlands across the globe, we stress the importance of peatland conservation and protection; continued unsustainable management practices may lead to the loss of these important peatland deposits.

Analysis of spatial and temporal changes of vegetation cover and its driving forces in the Huainan mining area

The Huainan mining area is rich in coal resources and has sparse vegetation and many collapsed waterways. Large-scale and long-term underground coal mining has led to a fragile ecological environment in the mining area, and it is urgent to solve the contradiction between coal development and ecological environmental protection. The Huainan mining area was selected as the research object, and the vegetation cover was extracted using 10-phase Landsat multispectral remote sensing images from 1989 to 2021 to analyze its spatial and temporal changes and driving forces to provide a scientific basis for the guided restoration of the ecological environment in the region. Combined with the image dichotomous model, regression slope, correlation coefficient, and standard deviation of vegetation cover grid points in different time series, standard deviation ellipse, and center of gravity migration, we analyzed the spatial and temporal variation pattern of vegetation cover for 33 years and revealed the responses of temperature, precipitation, population density, GDP, and afforestation area to vegetation cover. Results show the following: (1) from 1989 to 2021, the overall vegetation cover in the study area tended to decrease with 36.48% of the areas increasing and 63.52% of the areas decreasing, primarily in the very low and medium range; (2) the center of gravity of different types of vegetation cover generally shifted from north to south during 33 years; (3) climate and social activities had a substantial effect on the spatial heterogeneity of the vegetation cover in the study area. There is significant spatial heterogeneity in the effects of climate and social activities on the vegetation in the study area with human activities negatively correlating with vegetation cover. Mining activities are the primary driver of the evolution of regional vegetation cover, with climate change serving as a secondary driver.

North-south geographic heterogeneity and control strategies for polycyclic aromatic hydrocarbons (PAHs) in Chinese lake sediments illustrated by forward and backward source apportionments

As universal and supervirulent pollutants, understanding the potential sources of polycyclic aromatic hydrocarbons (PAHs) in lakes is critical for formulating pollutant control policies that will ensure the ecological safety of aquatic environments. Geographic heterogeneity of PAHs in lake sediments from China nationwide was investigated to indicate north-south dissimilarities in PAH levels and sources and propose specific PAH control strategies. Geographic PAH patterns showed that higher concentrations were found in the south compared to the north due to higher energy consumption and more intense industrial activities. Furthermore, the primary contributors in the south were high molecular weight (HMW) PAHs, whereas low molecular weight (LMW) PAHs were dominant in the north. The results of forward source apportionment based on the PAH emission method (EM) were consistent with the backward method using the positive matrix factorization (PMF) model, which verified the feasibility of the combined methods. Petroleum from transport was the dominant PAH source in the south, and purifying gasoline and diesel, promoting new energy vehicles and direct injection engines might effectively reduce PAH emission. Domestic coal was the main PAH source in the north, thereby adding active substance in coal and using cleaner energy could reduce PAH release.

Spatial-Temporal Evolution and Driving Forces of NDVI in China's Giant Panda National Park

Identifying the ecological evolution trends and vegetation driving mechanisms of giant panda national parks can help to improve the protection of giant panda habitats. Based on the research background of different geomorphological zoning, we selected the MODIS NDVI data from 2000 to 2020 to analyze the NDVI trends using a univariate linear model. A partial correlation analysis and multiple correlation analysis were used to reveal the influence of temperature and precipitation on NDVI trends. Fourteen factors related to meteorological factors, topographic factors, geological activities, and human activities were selected, and the Geographically Weighted Regression model was used to study the mechanisms driving NDVI change. The results were as follows: (1) The NDVI value of Giant Panda National Park has fluctuated and increased in the past 21 years, with an annual growth rate of 4.7%/yr. Affected by the Wenchuan earthquake in 2008, the NDVI value fluctuated greatly from 2008 to 2012, and reached its peak in 2018. (2) The NDVI in 94% of the study area improved, and the most significant improvement areas were mainly distributed in the northern and southern regions of Southwest Subalpine and Middle Mountain and the Xiaoxiangling area. Affected by the distribution of fault zones and their local activities, vegetation degradation was concentrated in the Dujiangyan-Anzhou area of Hengduan Mountain Alpine Canyon. (3) The Geographically Weighted Regression analysis showed that natural factors were dominant, with climate and elevation having a double-factor enhancement effect, the peak acceleration of ground motion and fault zone having a superimposed effect, and river density and slope having a double effect, all of which had a significant impact on the NDVI value of the surrounding area. To optimize the ecological security pattern of the Giant Panda National Park, we recommended strengthening the construction of ecological security projects through monitoring meteorological changes, preventing, and controlling geo-hazards, and optimizing the layout and intensity of human activities.

Vegetation Response to Holocene Climate Change in the Qinling Mountains in the Temperate–Subtropical Transition Zone of Central–East China

Global warming is having a profound influence on vegetation and biodiversity patterns, especially in alpine areas and high latitudes. The Qinling Mountain range is located in the transition zone between the temperate and subtropical ecosystems of central–east China and thus the vegetation of the area is diverse. Understanding the long-term interactions between plant diversity and climate change can potentially provide a reference for future landscape management and biodiversity conservation strategies in the Qinling Mountains region. Here, we use a pollen record from the Holocene sediments of Daye Lake, on Mount Taibai in the Qingling Mountains, to study regional vegetation changes based on biomes reconstruction and diversity analysis. Temperature and precipitation records from sites close to Daye Lake are used to provide environmental background to help determine the vegetation response to climate change. The results indicate that climate change was the main factor influencing vegetation and palynological diversity in the Qinling Mountains during the Holocene. The cold and dry climate at the beginning of the early Holocene (11,700–10,700 cal yr BP) resulted in a low abundance and uneven distribution of regional vegetation types, with the dominance of coniferous forest. During the early Holocene (10,700–7,000 cal yr BP), temperate deciduous broadleaf forest expanded, palynological diversity and evenness increased, indicating that the warm and humid climate promoted vegetation growth. In the middle Holocene (7,000–3,000 cal yr BP), the climate became slightly drier but a relatively warm environment supported the continued increase in palynological diversity. After ∼3,000 cal yr BP, palynological diversity and the evenness index commenced a decreasing trend, in agreement with the decreased temperature and precipitation in the Qinling Mountains. It’s noteworthy that human activity at this time had a potential influence on the vegetation. During the past few centuries, however, palynological diversity has increased along with the global temperature, and therefore it is possible that in the short-term ongoing climatic warming will promote vegetation development and palynological diversity in the area without human interference.

Mapping Land Use/Cover Dynamics of the Yellow River Basin from 1986 to 2018 Supported by Google Earth Engine

Changes in the land use/cover alter the Earth system processes and affect the provision of ecosystem services, posing a challenge to achieve sustainable development. In the past few decades, the Yellow River (YR) basin faced enormous social and environmental sustainability challenges associated with environmental degradation, soil erosion, vegetation restoration, and economic development, which makes it important to understand the long-term land use/cover dynamics of this region. Here, using three decades of Landsat imagery (17,080 images) and incorporating physiography data, we developed an effective annual land use/cover mapping framework and provided a set of 90 m resolution continuous annual land use/cover maps of the YR basin from 1986 to 2018 based on the Google Earth Engine and the Classification and Regression Trees algorithm. The independent random sampling validations based on the field surveys (640 points) and Google Earth (3456 points) indicated that the overall accuracy of these maps is 78.3% and 80.0%, respectively. The analysis of the land system of the YR basin showed that this region presents complex temporal and spatial changes, and the main change patterns include no change or little change, cropland loss and urban expansion, grassland restoration, increase in orchard and terrace, and increase in forest during the entire study period. The major land use/cover change has occurred in the transitions from forests, grasslands, and croplands to the class of orchard and terrace (19.8% of all change area), which not only increase the greenness but also raised the income, suggesting that YR progress towards sustainable development goals for livelihood security, economic growth, and ecological protection. Based on these data and analysis, we can further understand the role of the land system in the mutual feedback between society and the environment, and provide support for ecological conservation, high-quality development, and the formulation of sustainable management policies in this basin, highlighting the importance of continuous land use/cover information for understanding the interactions between the human and natural systems.