Low Vegetation Cover Research Articles

The study on the comparative responses of aquatic vegetation to the interannual water level variation in different hydrologically connected sub‐lakes based on GEE technology

AbstractWater level variation is considered as a main controlling environment factor affecting the growth of aquatic vegetation in Poyang Lake, the largest freshwater lake in China. It is significant to study the influences of water level change on aquatic vegetation under various hydrological conditions. Taking the free connected sub‐lake Bang Lake and partially controlled sub‐lake Dahuchi Lake of Poyang Lake as research objects and based on the cloud computing platform of remote sensing of Google Earth Engine (GEE), the pixel binary model method was used to estimate the aquatic vegetation cover from 2000 to 2019, and the spatial and temporal variation characteristics were discovered first. Meanwhile, the combined method of Sen + M‐K (Theil–Sen Median method and Mann‐Kendall trend test) was conducted to simulate the trends of water fluctuation. Second, the hydrological parameters indicating water level fluctuation were established, and the relationship between these parameters and the area covered by aquatic vegetation in different sub‐lakes was explored. The results were as follows. (1) The aquatic vegetation cover of the freely connected sub‐lake Bang Lake was more susceptible to water level changes, while the partially controlled sub‐lake Dahuchi Lake was relatively stable underwater level change. (2) The aquatic vegetation was patchily and sporadically distributed in years with low vegetation cover, while in the years with high vegetation cover, it was distributed in a ringlike pattern, spreading from the centre of the lake to the shore. (3) The aquatic vegetation cover of the freely connected sub‐lake Bang Lake was more likely to be influenced by the water level fluctuation (WLF), while the aquatic vegetation cover of the partially controlled sub‐lake Dahuchi Lake was more likely to be influenced by the flooding duration of 17 m water level (L17). The flooding duration of 19 m water level (L19) had a strong negative correlation with the predicted aquatic vegetation cover of both Bang Lake and Dahuchi Lake. It suggests that there was a certain degree of time lag in the effect of water level changes on the free connected sub‐lakes, but there was no obvious time lag on the partially controlled sub‐lakes. (4) The aquatic vegetation of the freely connected sub‐lake Bang Lake were dominated by stabilization and slight improvement, while aquatic vegetation in the partially controlled sub‐lake Dahuchi Lake were dominated by stabilization and significant degradation. This study can help to further understand the vegetation changes in hydro‐ecological system with different hydrological connectivity and will provide a reference for lake management and conservation.

Integration of RUSLE Model, Remote Sensing and GIS Techniques for Assessing Soil Erosion Hazards in Arid Zones

Soil erosion constitutes one of the main environmental and food security threats, derived from the loss of its productive capacity. With the help of remote sensing (RS), geographic information systems (GIS), and a revised version of the universal soil loss equation (RUSLE), this research has mostly focused on measuring the potential soil erosion hazard and soil water conservation ratio (SWCR) in the El-Minia region of Egypt. Based on the integration of S2A images and the digital elevation model (DEM), geomorphological units of the study area were identified. The RUSLE model includes parameters that allow for mapping soil erosion, such as rain erosivity, soil erodibility, slope length and steepness, soil cover and management, and soil conservation practices. The outcomes revealed that the classes of annual erosion rates of the study area are those of “slight erosion”, “low erosion”, “moderate erosion” and “moderately high erosion”, which represent percentages of 29%, 18%, 33% and 20%, respectively, of the total area. The rate of erosion decreases from east to west. The main erosion factors in the research area are the low vegetation cover and the high slope values. This study highlights the utility of combining the classic RUSLE equation with techniques such as remote sensing (RS) and geographic information systems (GIS) as a basis for assessing current erosion conditions in arid environments and, specifically, for the application of soil management patterns aimed at increasing soil organic matter and any other soil conservation actions. The findings of this study can be used by policymakers to implement soil conservation measures if development projects are to proceed in areas with a high risk of soil erosion. The approach described here is therefore adaptable to similar environments in arid regions.

Remote Sensing Monitoring and Evaluation of Vegetation Changes in Hulun Buir Grassland, Inner Mongolia Autonomous Region, China

Constantly increasing vegetation changes pose serious challenges to the sustainable use of global ecosystems. Thus, facing the increasingly serious climate and ecological environment problems and improving vegetation coverage is crucial to the sustainable development of the region. Along these lines, in this work, a monitoring model of vegetation cover change was proposed and developed by using Landsat TM (1989, 1999, and 2011) and Landsat OLI-TIRS (2021) data. More specifically, it was used to assess vegetation change. Based on this model, the vegetation change in the core area of Hulun Buir Grassland was systematically analyzed., From the acquired results, the existence of spatial differences in the vegetation coverage changes in the study area were demonstrated. The total area of vegetation coverage changes was 758.95 km2, and the area from low vegetation coverage to high vegetation coverage was 456.41 km2, accounting for 60.14% of the total change area. The area from high vegetation coverage to low vegetation coverage was 302.57 km2, accounting for 39.86% of the total change area, whereas the area of the area without vegetation coverage was 1963.92 km2, accounting for 72.13% of the study area, and the overall vegetation coverage is improving. Vegetation cover change monitoring models can also be used to reveal and describe large-scale vegetation landscape changes and obtain clear vegetation change results through easy-to-obtain data; our work suggests that in the process of pursuing regional economic development and accelerating urbanization, industrialization, and agricultural modernization, human beings should assume more responsibilities and pursue the sustainable development of the natural environment. The results of this work are of great importance to further study the potential driving mechanism of the vegetation coverage changes and provide theoretical guidance for relevant managers to formulate vegetation restoration measures.

Patch and matrix characteristics determine the outcome of ecosystem engineering by mole rats in dry grasslands.

Burrowing mammals are important ecosystem engineers, especially in open ecosystems where they create patches that differ from the surrounding matrix in their structure or ecosystem functions. We evaluated the fine-scale effects of a subterranean ecosystem engineer, the Lesser blind mole rat on the vegetation composition of sandy dry grasslands in Hungary. In this model system we tested whether the characteristics of the patch (mound size) and the matrix (total vegetation cover in the undisturbed grassland) influence the structural and functional contrasts between the mounds and the undisturbed grasslands. We sampled the vegetation of 80 mounds and 80 undisturbed grassland plots in four sites, where we recorded the total vegetation cover, and the occurrence and cover of each vascular plant species. We used two proxies to characterise the patches (mounds) and the matrix (undisturbed grassland): we measured the perimeter of the mounds and estimated the total vegetation cover of the undisturbed grasslands. First, we compared the vegetation characteristics of the mounds and the surrounding grasslands with general linear models. Second, we characterised the contrasts between the mounds and the undisturbed grassland by relative response indices (RRIs) of the vegetation characteristics studied in the first step. Species composition of the vegetation of the mounds and undisturbed grasslands was well separated in three out of the four study sites. Mounds were characterised by lower vegetation cover, lower cover of perennial graminoids, and higher diversity, and evenness compared to undisturbed grasslands. The contrast in vegetation cover between mounds and undisturbed grasslands increased with decreasing patch size. Increasing vegetation cover in the matrix grasslands increased the contrasts between the mounds and undisturbed grasslands in terms of total cover, perennial graminoid cover, diversity, and evenness. Our results suggest that mole rat mounds provide improved establishment conditions for subordinate species, because they are larger than other types of natural gaps and are characterised by less intense belowground competition. The ecosystem engineering effect, i.e., the contrast between the patches and the matrix was the largest in the more closed grasslands.

Evaluation of Diurnal Variations in Urban Surface Temperature with Earth Observations System

Rapid urbanisation causes the ‘heat island’ problem in megacities worldwide. The industrialisation has fuelled the increase in the urbanisation in Indian cities. This work measures and characterises Ahmedabad’s heat island variations (India). The study uses two satellite passes of the MODIS sensor over the summer for the last three years to assess urban heat island intensity (UHII). Sentinel-2B records are used to create a land-use map. The study considers the impact of land-use patterns on summer UHII diurnal fluctuations. Daily diurnal changes in land surface temperature (LST) are being analysed. Locations and land-use land-cover patterns affect UHII. Satellite observations show greater LST values during the day than at night, however, UHII is stronger at night. Urban UHII is stronger rural UHII. Lower vegetation cover area is one of the key causes of UHII development, as seen in the region’s Normalized Difference Vegetation Index (NDVI) values.

Improved export coefficient model for identification of watershed environmental risk areas.

As a complex system under the joint action of man and nature, land use/cover directly or indirectly affects the environmental quality of the freshwater ecosystem. Studying the response of water environment quality to land use/cover change was significant to accurately simulate lake water quality and effectively enhance the management level. As an empirical model, the classical export coefficient model has been widely used and developed in agricultural non-point source pollution research because of its simple structure and convenient application. However, it assumes that the export coefficient of a particular type of land use/cover was constant, ignoring the influence of surface runoff and interception on the output intensity of pollutants in pollutant migration. This study improved the classical export coefficient model by adding factors such as precipitation, surface cover, and topography, evaluated the contribution of land use/cover to total nitrogen load into the lake in Dianchi Lake Basin, and applied the pollution assessment results to the identification of watershed environmental risk areas. The results showed that the improved export coefficient model could better simulate the relationship between land use/cover and total nitrogen load into Dianchi Lake from the basin. At the same time, spatial characteristics of the total nitrogen load contribution of the terrestrial could be represented. The high-risk areas in the basin were mainly cultivated land and construction areas with low vegetation coverage around lakes or downstream. The contribution per unit area to the TN load into the lake from areas with a high risk was 14.28 t/km2, which was 3.47 times that of medium-high-risk areas and 52.28 times that of the medium-risk area. Land use control measures in high-risk areas in the basin should be further strengthened, especially in the lakeside zone.

Analysis of desertification combating needs based on potential vegetation NDVI-A case in the Hotan Oasis.

Combating desertification is vital for arresting land degradation and ensuring sustainable development of the global ecological environment. This study has analyzed the current desertification status and determined its control needs based on the difference between potential normalized difference vegetation index (PNDVI) and actual normalized difference vegetation index (ANDVI) in the Hotan desertoasis. The MaxEnt model, combined with the distribution point data of natural vegetation with long-term stable normalized difference vegetation index (NDVI) and 24 environmental factors was used to predict the PNDVI spatial distribution of different vegetation coverage grades and compared it with ANDVI. Excluding the areas of intense human activity such as arable land, the simulation results show that PNDVI with high, medium, and low vegetation cover was mainly distributed in the southwest and southeast of Hotan Oasis, in the midstream and downstream of Kalakash River and Yulong Kashi River, and the desert or Gobi area outside the oasis, respectively. The distribution of PNDVI with high, medium, and low vegetation cover accounted for 6.80%, 7.26%, and 9.17% of Hotan oasis, respectively. The comparison between ANDVI and PNDVI shows that 18.04% (ANDVI < PNDVI, about 3900 km2) of the study area is still suffering from desertification, which is mainly distributed in the desert-oasis ecotone in Hotan. The findings of this study implied that PNDVI could be used to assess the desertification status and endorsement of desertification control measures in vulnerable ecosystems. Hence, PNDVI can strengthen the desertification combating efforts at regional and global scales and may serve as a reference point for the policymakers and scientific community towards sustainable land development.

The Impacts of Vegetation on Summer Extreme Temperature of 4 Major Cities in China Based on Scatter Analysis and Linear Trend Analysis

In the summer of 2022, the extreme high temperature phenomenon is particularly obvious in China, especially in Chongqing, Zhengzhou, Guangzhou, and Shanghai. Some studies have pointed out that there is a strong correlation between vegetation activity and regional climate change, and some vegetation types can mitigate the rise of extreme temperature. However, few papers can put forward inductive suggestions on what types of vegetation can effectively alleviate the extreme temperature in China. Therefore, in this paper the extreme temperature data of CMIP6 (tasmax) is used to explore the correlation between the vegetation cover rate and the extreme temperature of the four major cities in China through the scatter analysis and linear trend analysis. It is found that the vegetation cover rate has a significant correlation (p&lt;0.05) with the extreme temperature: The high vegetation cover rate has a negative correlation with the extreme temperature (p=0.01), and the low vegetation cover rate has a positive correlation with the extreme temperature (p=5.86 x 10-9). According to the geographical location, 4 cities are divided into two types: inland cities and coastal cities. The results show that: (1) planting high vegetation may be more conducive to the mitigation of extreme temperature; (2) the increase of low vegetation coverage may be more conducive to the reduction of temperature rise rate; (3) inland cities may need to plant more high vegetation than coastal cities to mitigate extreme temperature.

Ecological restoration effects of the Beijing–Tianjin Sandstorm Source Control Project in China since 2000

The Beijing–Tianjin Sandstorm Source Control Project (BTSSCP) has been implemented for more than 20 years (2001–2022), and a scientific, accurate, and complete evaluation of its implementation effect is of great significance for the study of ecosystem evolution. In this study, we present a vegetation–water–soil–environment system comprising the net ecosystem productivity (NEP), water conservation (WC), soil erosion (SE), and habitat quality (HQ) to evaluate the spatiotemporal changes and future trends. The results showed that: (1) In areas with high vegetation coverage, only WC was significantly and negatively correlated with SE (−0.68, p less than 0.01). In areas with low vegetation coverage, NEP, WC, and HQ were all significantly negatively correlated with SE. This indicates that SE is a basic function that affects the performance of other ecological services. (2) From 2000 to 2020, the annual maximum average vegetation coverage increased by about 10 %; the annual average NEP increased by about 60 g C/km2, and the annual average SE decreased by about 500 t/km2. Compared with Phase I (2000–2010), the vegetation condition (coverage, NEP) in summer (July–August) was improved by about 10 %, and SE in winter (December–January) decreased by 3 t/km2 per month in Phase II (2010–2020). (3) In terms of future trends, NEP may continue to increase in the grassland area, especially in the Mu Us Sandland, but it may not change significantly in the forest area. Similarly, SE may continue to decrease in grassland-covered areas, but not in forest-covered areas. Most areas of WC could continue to increase, but the HQ will not change significantly. In general, the ecological restoration effects of the BTSSCP have improved significantly. This paper is intended to provide some key information for the management of ecological projects and regional ecological security.

Comparison of the Application of Different Process-Based Models in the Study of Spatio-Temporal Patterns of Ecosystem Service Value

Quantitative assessments of ecosystem service value (ESV) are of great significance for rational allocation of environmental resources and making regional ecological protection decisions. The method of equivalence factor per unit area is widely used for this purpose because of its simple algorithm. However, ESV is also affected by biotic and environmental factors (e.g., net ecosystem productivity (NEP) or precipitation), which are difficult to obtain at the regional scale, leading to uncertainty in ESV estimations. In this study, according to the equivalent factor modified by precipitation and NEP from four state-of-the-art process-based productivity models, i.e., CLM4.0, LPJDGVM, LPJGUESS and ORCHIDEE, we explored the temporal and spatial patterns of ESV of 15 administrative regions in northern China. The results show that the simulation accuracy of different models varied among four representative ecosystem types, i.e., typical steppe in northern China, alpine steppe in northwest China, farmland ecosystem in central China, and forest in northeast China, implying that model-based ESV estimates are ecosystem-specific. The ESV tends to decline from northeast to southwest in northern China. Regions with dense vegetation usually had high ESV due to better hydrological and thermal conditions. Low vegetation coverage areas, such as Qinghai and Xinjiang, had higher ESV because of their large geographical areas. The central and eastern developed regions without abundant natural resources had lower ESV due to their lower NEP. For different categories of ecosystem services, the regulation services (mainly water flow regulation services and climate regulation services) contributed the most to ESV. For the temporal dynamics, the total ESV of the 15 provinces, autonomous regions and municipalities showed an insignificant downward trend over the years. The regions with increasing trends of ESV were distributed in northwestern China, while pixels with decreasing trends of ESV were concentrated in northeastern China. Land use cover change may be the most important factor controlling the temporal dynamics of ESV. Our results can provide support for the enaction of reasonable strategies for ecological protection and economic development in northern China.

Promoting vegetation coverage using fertilization treatments in abandoned farmland in Mongolia

AbstractWe investigated the changes in vegetation responses following fertilization in abandoned farmland in Mongolia. Nitrogen (N), phosphorus (P) and potassium were sprayed alone or in combination on abandoned farmland on a typical steppe in Mongolia, and changes in soil nutrients, species composition and vegetation cover were investigated. Abandoned farmland had lower vegetation cover and soil N and P levels than natural grassland. Phosphorus fertilization significantly affected soil phosphate levels. Nitrogen fertilization in abandoned farmland effectively increased vegetation cover. Moreover, combined N and P fertilization increased plant cover over either element alone, possibly via improved uptake of nitrate ions and the promotion of growth. The effect of increasing cover following fertilization was primarily observed in the genus Artemisia. These results suggest that fertilization of abandoned farmland might not contribute to a return to natural steppe vegetation but rather increase the vegetation cover of annual forbs such as field weeds. Species composition did not appear to be affected by fertilization. This speaks to the difficulty of promoting species regeneration in abandoned farmland using fertilization alone. However, combining fertilization with the introduction of native plant material, e.g., seed sowing, may be beneficial in early restoration treatments, given the promotion of plant growth via fertilization and the importance of reducing wind erosion via the establishment of ground cover.

Analysis of Vegetation Coverage Evolution and Degradation under Coal Mine Construction in Permafrost Region

The ecological environment in permafrost regions is very sensitive to climate change and human activities. The effects of coal mining on the vegetation in permafrost regions have been poorly studied. Herein, on the basis of a field survey in the Juhugen mining area of Qilian Mountain, China, we investigated and quantified the influence of open-pit coal mining on vegetation coverage degradation in permafrost areas. According to the NDVI and field survey, the vegetation coverage was divided into five levels from low to high in the Arc GIS platform. Compared with the area not affected by coal mining, vegetation degradation was significant in the coal-mining-affected area, especially in the high-vegetation-coverage area. The vegetation coverage in Level 5 decreased from 51.99% to 21.35%. According to the conversion matrix, the transfer-out area in high coverage was larger, while the transfer-in area in low vegetation coverage was larger. The transfer-out area of five levels was significant in levels 2–5, accounting for 36.1% to 62.8% of the total area. The transfer-in area of five levels was significant in levels 1–4, accounting for 55.2% to 75.0% of the total area. Moreover, the ground surface temperature and water change were monitored in the vegetation degradation area. The results showed that the above degradation was related to an increase in the ground surface temperature and a decrease in the ground surface moisture.

Characteristics of grassland degradation and its relationship with climate factors on Qinghai-Tibetan Plateau, China

Understanding the distribution, characteristics, and changing trend and persistence of grassland degradation and revealing its mechanism on the Qinghai-Tibetan Plateau can provide scientific basis for effective grassland management and conservation. We selected grassland coverage as the remote sensing monitoring index to establish the remote sensing monitoring and evaluation index system of grassland degradation and evaluate grassland degradation during 2016 to 2020 on the Qinghai-Tibet Plateau. The changing trend and persistence of grassland coverage were analyzed using linear regression and Hurst index analysis on a long time series scale (1982-2020). The partial correlation analysis was used to examine the influence of climate on grassland degradation. The results showed that grassland degradation reached 24.3% during 2016 to 2020, which was mainly light and moderate degradation, and largely distributed in low altitude and high fractional vegetation cover areas. From 1982 to 2020, grassland coverage tended to increase in the north, west and southwest, and decreased in the east and center of the Qinghai-Tibetan Plateau. The Hurst index of grassland coverage was less than 0.5 in 98.1% of the total grassland, indicating grassland coverage showed negatively persistent. The partial correlation coefficient between grassland coverage and precipitation (0.096) was higher than that of temperature (-0.033). About 16.0% area was dominated by temperature, which was mainly distributed in the central and southeast. About 12.2% area was dominated by precipitation, which was distributed in the northeast and west of the Qinghai-Tibetan Plateau.

Examining the spatially varying effects of climatic and environmental pollution factors on the NDVI based on their spatially heterogeneous relationships in Bohai Rim, China

Variations in vegetation patterns can provide a scientific basis for assessing environmental quality and monitoring ecosystem dynamics under environmental pollution and global warming conditions. To evaluate the ecological environment of the Bohai Rim, Theil-Sen trend analysis, the Mann-Kendall (MK) test and the Hurst exponent were applied to analyze the patterns of variation in the vegetation coverage, climate factors (temperature, precipitation, relative humidity) and particulate matter and to assess sustainability in the near future. Fine particulate matter, also known as PM2.5 (PM2.5,μg/m3), refers to atmospheric particles with a diameter of less than or equal to 2.5 μm, also known as respirable particles. These not only lead to a decline in atmospheric visibility but also increase human mortality and respiratory disease rates. Given the spatiotemporal nonstationarity of climate factors and PM2.5, geographically weighted regression (GWR) was applied to confirm the spatially heterogeneous relationship among the vegetation coverage, climate factors and PM2.5. The vegetation coverage in the Bohai Rim was mostly comprised of slightly degraded areas, followed by unchanged areas, improved areas, and severely degraded areas from 2002 to 2017. The slightly degraded area accounted for 30.9 %, while 15.8 % of the area remained at the same level during the period, and 16.8 % improved. Slight degradation was mainly observed on agricultural lands and forests, whereas severely degraded areas were distributed among grasslands and wetlands. Approximately 20.9 % of the improved area, most of which was agricultural lands, forests and grasslands, continued to improve. Seasonal trends indicated that a large proportion of the areas remained unchanged or were slightly degraded from autumn to spring, whereas areas improved from spring to autumn. During the winter, slightly and severely degraded areas continuously expanded. GWR indicated that temperature, PM2.5, and precipitation displayed a significant heterogeneous spatial relationship with the vegetation coverage and had an obvious influence on the medium, high and low vegetation cover areas. When considering the joint influence of climate factors and PM2.5 on the vegetation coverage, the model accuracy was not high for the high and medium vegetation cover areas. In the Bohai region, human activities significantly affect coastal areas. These results can support sustainable coastal ecosystem management, relevant management measures and ecological development plans.

Multitemporal Analysis of the Influence of PM10 on Human Mortality According to Urban Land Cover

High urbanization and a consequent change in land cover can lead to a deterioration in air quality and generate impacts on public health. The objective of this paper is to provide a multitemporal analysis of the influence of particulate matter ≤ 10 μm (PM10) on human mortality from the land cover variation in a Latin American megacity. Six monitoring stations (monitoring daily PM10 concentration, increases in daily mortality (IDM), and land cover) were established throughout the megacity. The results suggest that for every 10% increase in vegetation cover, the daily PM10 concentration and IDM decreases by 7.5 μg/m3 and 0.34%, respectively. Moreover, it is evident that the monitoring station with the lowest vegetation cover (8.96 times) shows an increase of 1.56 times and 4.8 times in the daily PM10 concentration and IDM, respectively, compared with the monitoring station with the highest vegetation cover (46.7%). It is also suggested that for each increase of 100 inhabitants/hectare in population density, the daily PM10 concentration and IDM increases by 9.99 µg/m3 and 0.45%, respectively. Finally, the population densification of the megacity possibly implies a loss of vegetation cover and contributes to the increase in PM10 and IDM.

Spatiotemporal Evolution and Driving Forces of Vegetation Cover in the Urumqi River Basin.

It is important to determine long-term changes in vegetation cover, and the associated driving forces, to better understand the natural and human-induced factors affecting vegetation growth. We calculated the fractional vegetation coverage (FVC) of the Urumqi River basin and selected seven natural factors (the clay and sand contents of surface soils, elevation, aspect, slope, precipitation and temperature) and one human factor (land use type). We then used the Sen-Man-Kendall method to calculate the changing trend of the FVC from 2000 to 2020. We used the optimal parameters-based geographical detector (OPGD) model to quantitatively analyze the influence of each factor on the change in vegetation coverage in the basin. The FVC of the Urumqi River basin fluctuated from 2000 to 2020, with average values between 0.22 and 0.33. The areas with no and low vegetation coverage accounted for two-thirds of the total area, whereas the areas with a medium, medium-high and high FVC accounted for one-third of the total area. The upper reaches of the river basin are glacial and forest areas with no vegetation coverage and a high FVC. The middle reaches are concentrated in areas of urban construction with a medium FVC. The lower reaches are in unstable farmland with a medium and high FVC and deserts with a low FVC and no vegetation. From the perspective of the change trend, the areas with an improved FVC accounted for 62.54% of the basin, stable areas accounted for 5.66% and degraded areas accounted for 31.8%. The FVC showed an increasing trend in the study area. The improvement was mainly in the areas of urban construction and desert. Degradation occurred in the high-elevation areas, whereas the transitional zone was unchanged. The analysis of driving forces showed that the human factor explained more of the changes in the FVC than the natural factors in the order: land use type (0.244) &gt; temperature (0.216) &gt; elevation (0.205) &gt; soil clay content (0.172) &gt; precipitation (0.163) &gt; soil sand content (0.138) &gt; slope (0.059) &gt; aspect (0.014). Apart from aspect, the explanatory power (Q value) of the interaction of each factor was higher than that of the single factor. Risk detection showed that each factor had an interval in which the change in the FVC was inhibited or promoted. The optimum elevation interval of the study area was 1300-2700 m and the greatest inhibition of the FVC was seen above 3540 m. Too much or too little precipitation inhibited vegetation coverage.

Validation and Analysis of MAIAC AOD Aerosol Products in East Asia from 2011 to 2020

East Asia is one of the most important sources of aerosols in the world. The distribution of aerosols varies across time and space. Accurate aerosol data is crucial to identify its spatiotemporal dynamics; thus, it is of great significance to obtain and verify new aerosol data for this region. Based on the Aerosol Optical Depth (AOD) data of the Aerosol Robotic Network (AERONET) program for 17 stations from 2011 to 2020, this study comprehensively verified the accuracy and applicability of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) AOD 1 km products among different seasons, elevations, and climate zones over entire East Asia. The results showed that: (1) The overall accuracy of MAIAC AOD was high in East Asia, and the accuracy of Terra was slightly better than that of Aqua. MAIAC AOD showed significant heterogeneity among sites. MAIAC AOD performed well in areas with high vegetation cover and flat terrain, while the inversion accuracy was relatively low in areas with low vegetation cover and high terrain. (2) In general, MAIAC AOD and AERONET AOD showed good agreement in different seasons, presenting as winter &gt; spring &gt; autumn &gt; summer. Yet the accuracy and consistency of Terra AOD product were better than Aqua product. (3) MAIAC AOD showed different accuracy at different elevations and climate zones. It had a high correlation and best inversion accuracy with AERONET AOD at low and medium elevations. MAIAC AOD had better inversion accuracy in the arid and warm temperate zones than that in the equatorial and cold temperate zones. (4) AOD distribution and its trend showed significant spatial differences in East Asia. The high AOD values were dominant in the Sichuan basin and the eastern plains of China, as well as in India and Bangladesh, while the relatively low AOD values were distributed in southwestern China and the areas north of 40°N. AOD in most parts of East Asia showed a negative trend, indicating a great improvement in air quality in these regions.

GIS-Based Watershed Unit Forest Landscape Visual Quality Assessment in Yangshuo Section of Lijiang River Basin, China

The Yangshuo Section of the Lijiang River Basin (YS of LRB) is the essence of the Guilin landscape in China. The typical karst landforms and changing topography form a unique forest landscape in YS of LRB. In order to reveal the visual quality of itse forest landscape, this research used GIS spatial analysis technology combined with Analytic Hierarchy Process (AHP), the assessment factors were leveled and assigned, and some abstract assessment indicators in the visual quality assessment were quantified. Three primary indicators of forest landscape visual quality (FLVQ) assessment in YS of LRB, including Scenic Quality (SQ), Visual Sensitivity (VS), and Visual Absorption Capability (VAC), are proposed. Visual assessment units are divided based on the watershed, and a process and framework for the comprehensive assessment of FLVQ was established at the watershed scale. The results show that the FLVQ in YS of LRB is generally at a low level. The area percentage of FLVQ at high (13′&amp;11′), medium (9′) and low (7′&amp;5′) levels are 10.95%, 29.67% and 59.38%, respectively. The comprehensive score of FLVQ in the karst area is slightly lower than that in the non-karst area, but the karst area of the units with the highest FLVQ accounts for 99.58% of the FLVQ of karst areas along the Lijiang River distributed in the Lijiang River Scenic Area, greater than that of any other areas. The FLVQ in regions with high vegetation coverage and large topographic changes is relatively higher. Slope, relief amplitude, and vegetation richness directly affect the visual quality of forest landscape. Under the influence of local scenic area protection policies and relatively stable natural climate, the FLVQ in YS of LRB has maintained a stable level in the past 20 years. The areas with low FLVQ are mainly cultivated land and construction land, which have low vegetation coverage and no obvious change in terrain. Based on the comprehensive assessment results of FLVQ in YS of LRB, the management goals and future development suitability of forest landscape is discussed. This research proposes appropriate construction and management strategies for forest landscape structures. The results are helpful for providing a scientific research basis for forest landscape resource conservation, landscape site selection, and forest ecotourism development in the Karst landscape area. The impact of human disturbance on the forest landscape fragmentation and the growth characteristics of forests under different landforms are the focus of future FLVQ research on similar areas.

A Monitoring Method Based on Vegetation Abnormal Information Applied to the Case of Jizong Shed-Tunnel Landslide

Landslides are one of the most dangerous natural disasters, which have affected national economic development and social stability. This paper proposes a method to indirectly monitor the deformation characteristics of landslides by extracting the abnormal vegetation information, especially for the inaccessible high-mountain landslides in southwestern China. This paper extracts the vegetation anomaly information in the Jizong Shed-Tunnel landslide which is located on the main traffic road to Tibet by the optical remote sensing Gaofen-1 (GF-1) data, and analyzes the temporal and spatial characteristics of the vegetation anomaly information through a time series. Then, we use the small baseline subsets interferometry synthetic aperture radar (SBAS-InSAR) technology to process Sentinel-1 data to obtain the time-series surface deformation information. Finally, we analyze and verify the results of the two methods. The results show that there is obvious vegetation coverage (VC) decline, with a maximum increasing percentage of 8.77% for the low and medium VC, and obvious surface deformation around the landslide, with the highest settlement rate of between 0 mm/year and 30 mm/year. Through the time-series analysis, we find that the change trends of the two methods are basically the same. This paper shows that the method of using abnormal vegetation information to monitor the Jizong Shed-Tunnel landslide has a certain degree of reliability and practicability. It can provide a new idea and effective supplement for landslide monitoring.

Mongolian Marmot (&lt;i&gt;Marmota sibirica&lt;/i&gt;) Ecosystem Engineering Effects on Herpetofauna

The Mongolian marmot (Marmota sibirica) is a relatively large-bodied, social rodent that lives in colonies across the Mongolian steppes and adjacent parts of China and Russia. Marmots serve as ecosystem engineers that display multiple functions on the steppe environments they inhabit. Mongolian marmots experienced a 75% decline across Mongolia in the 1990s that led to their listing as endangered globally. The decline of marmots likely affected other species given their importance to the ecosystems they inhabit. To examine the role of marmots on herpetofauna, we established drift fence arrays with associated pitfall and funnel traps on active marmot colonies, inactive colonies, and control sites in the forest-steppe and semi-desert zones of Mongolia. In total, we identified 555 individuals representing 5 species of reptiles in Ikh Nart Nature Reserve (semi-desert) from 2010 – 2011 and 22 individuals of 3 species of reptiles and one amphibian species in Hustai National Park (forest-steppe) in 2014 and 2016. We found significantly higher species abundance and some diversity indices on active and inactive colonies compared to control sites in Hustai. Vegetation height and cover significantly affected the abundance and species richness of reptiles in Ikh Nart. In Ikh Nart, we found that under conditions of higher vegetation cover and height, reptiles were distributed more widely across the landscape, but with lower vegetation cover and height, reptiles associated more strongly with marmot burrows. Burrows likely provide shelter from extreme climatic conditions and refugia from predation. Our research provides insights into how marmots create important habitats for associated fauna. This and similar experimental approaches will allow us to better understand the biodiversity patterns in and around marmot burrows.