Effects Of Vegetation Coverage Research Articles

The effects of surface vegetation coverage on the spatial distribution of PM2.5 in the central area of Nanchang City, China.

The frequent occurrence of haze has caused widespread concern in China, and PM2.5 is thought to be the main cause. Previous research showed that PM2.5 was not only influenced by meteorological conditions but also by land cover especially surface vegetation. It was concluded that PM2.5 concentration is significantly influenced by surface vegetation, but spatially how and in what manner are still unanswered. Taking the central area of Nanchang City, China, as a case, this study firstly applied land use regression (LUR) model to simulate the distribution of PM2.5 in 2020. Then, the dichotomous model was used to determine vegetation coverage. A statistical regression model was used to analyze the influence of vegetation cover on PM2.5 and the scale effects. The results showed that (1) vegetation coverage and PM2.5 concentration were both significantly negatively correlated at the spatial scales selected for this study. (2) The effect of vegetation coverage on PM2.5 varied with season and the 500 m had the best correlation. (3) The non-linear regression model fits better than the linear model, and the effect of vegetation coverage on PM2.5 was complex. (4) The effect of vegetation coverage on PM2.5 concentration was different with PM2.5 concentration level. The higher the PM2.5 concentration, the more pronounced the effect of vegetation coverage on it. This study proposed the idea and method of coupling vegetation coverage with PM2.5 concentration at the regional scale from gradient landscape's point of view and provided some references for mitigating PM2.5 pollution through optimizing urban vegetation patterns.

Evaluation of the effects of grass and shrub cover on overland flow resistance and its attributes under simulated rainfall

Vegetation plays a crucial role in controlling soil erosion and regulating overland flow connectivity. However, the effects of vegetation coverage on the overland flow resistance mechanisms remain unclear. This study aimed to examine the impact of grass and shrub cover on the resistance to overland flow concerning a random patch distribution pattern. This was achieved through a series of simulated rainfall experiments. Thirty slope surfaces with different vegetation coverages, consisting of complete combinations of five grass and six shrub coverages, were tested under five rainfall intensities (60–120 mm h−1) and three slope gradients (8.75%–26.79%). The results indicated that the Darcy–Weisbach friction factor (f) values on unvegetated slopes ranged from 0.455 to 1.385, whereas those on vegetated slopes ranged from 0.500 to 5.624. Vegetation coverage increased flow resistance on hillslopes, and the relationship between f and the Reynolds number (Re) was influenced by vegetation cover and the slope gradient; thus, it showed a positive correlation when vegetation form resistance was dominant. In contrast, a negative correlation was observed. According to the t-test results, the linear superposition method had limitations in calculating overland flow resistance and was only applicable when the grass coverage was 10%. Moreover, as the coverage increased, significant differences (p < 0.05) emerged between the total resistance and the linear summation of the individual resistance components. Additional vegetation resistance plays a significant role in impeding the water flow, contributing up to 50% of the total resistance. Finally, an equation for calculating additional vegetation resistance was developed using dimensional analysis and multiple nonlinear regression. The accuracy of the equation was validated by comparing it with experimental results (NSE = 0.918, RMSE = 0.144). These findings emphasize the effectiveness of constructing grass-shrub communities and increasing vegetation coverage as measures for soil and water conservation.

Water yield response to plant community conversion caused by vegetation degradation and improvement in an alpine meadow on the northeastern Tibetan Plateau

Water provision is an important ecological function of alpine meadows on the Tibetan Plateau. Quantitative assessment of the effects of vegetation change induced by vegetation degradation and improvement on water yield (WY) in alpine meadows is urgent for rational water and grassland resources conservation and management. Previous studies mainly focused on the effects of vegetation coverage. What is less clear is how the WY of alpine meadow changes under plant community conversion caused by vegetation degradation and improvement. To test the hypotheses that lysimeter drainage (LD) decreases in the vegetation-degraded meadow and recovers in the vegetation-improved meadow, and the LD decreases as the stress tolerance of dominant strategy decreases, in situ lysimeters with intact monoliths of well-vegetated alpine meadows subjected to vegetation intact (sedge-dominated), degraded (forb-dominated) and improved (fast-growing grass-dominated) were employed, and then plant communities among treatments were compared based on the quantitative competitor, stress tolerator, and ruderal (CSR) theory. Compared to the vegetation-intact monoliths, the LD of vegetation-degraded monoliths was 59 % lower owing to the deeper roots and greater aboveground growth. The LD of vegetation-improved monoliths was 83 % higher than that of vegetation-degraded monoliths due to the shallower roots but was 25 % lower than that of vegetation-intact monoliths due to the greater aboveground growth. The LD decreased along a plant community conversion gradient in which the S-selection of the dominance strategy decreased (R2 = 0.34, P = 0.022) and the C-selection increased (R2 = 0.71, P < 0.001), likely due to the significant covariation between community-weighted CSR strategy with eco-hydrological plant and soil properties. These results indicated that the community conversion caused by vegetation degradation reduces the WY of alpine meadows, and sowing fast-growing grasses can only partly restore this function. Application of stress-tolerant plants for vegetation improvement may be more efficient in recovering the WY of degraded meadows, especially in flat meadows under humid climate.

Soil erosion gradient and quantitative attribution in southwest China based on karst development degree

The heterogeneity of the geographical environment determines the complexity of soil erosion patterns. Determining the effects of changing gradients and combinations of environmental factors on soil erosion is the key to combating soil erosion. In this study, based on the division of the karst development degree, the revised universal soil loss equation model was optimised based on the rocky desertification factor to determine the effect of the different gradients of environmental factors on soil erosion. The geographical detector method was used to identify the dominant and interactive factors of soil erosion under different karst development degrees. The gradient attribution shows that: soil erosion is influenced by the type of bedrock assemblage and the form of the assemblage. Soil erosion is strongest at 1400–1800 m above altitude. Grassland in karst areas is prone to soil erosion and the effect of vegetation coverage on soil erosion has a critical value of 0.6–0.7. Interaction analysis shows that the interaction between land use and slope plays a dominant role in the spatial differentiation of soil erosion, but has significantly higher explanatory power (q)in sub-karst and non-karst areas than in pure-karst areas. Combined with slope and rainfall, soil erosion is obviously intensified, and the pure-karst and sub-karst areas are higher than the non-karst areas. The significant interaction between lithology and slope is a typical feature of karst areas. The findings of this study have crucial theoretical significance for the site-specific control of soil erosion in areas with different karst development degrees.

Study on the Effect of Vegetation Coverage on Urban Cooling and Energy Conservation: A Case Study of a Typical Hilly City, Chenzhou, China

Urban vegetation coverage is a core index in urban planning, which has been confirmed to be an effective indicator for the urban thermal environment. Through the urban thermal environment, this study aims to further quantify the impact of vegetation coverage on urban energy consumption. Chenzhou, a typical hilly city, was selected as the study object for its diversified vegetation coverages. Remote sensing technology and correlation and regression models were employed in this study. Firstly, the data of land surface temperature and vegetation coverage were calculated with remote sensing technology, followed by data analysis with the correlation and regression models. Then, employing the “λ-T” model, a statistical model corresponding to urban temperature and energy, this study clarified the impact of temperature on urban energy consumption. Finally, through urban temperature, this study analyzed the impact of urban greening coverage on urban energy consumption. This study shows that when the temperature ranges from 22 °C to 28.9 °C, every 10% of additional vegetation coverage will reduce the air conditioning energy demands by 5.5%, and when the temperature is between 28.9 °C and 37 °C, every 10% of additional vegetation coverage will reduce the mean air conditioning energy demands by 2.4%.

The Effect of Vegetative Coverage and Altitude on the Vegetation Water Consumption in the Alpine Inland River Basin of the Northeastern Qinghai–Tibet Plateau

Estimating accurately the vegetation water consumption (VWC) in the Qinghai Lake Basin (QLB) is conducive to the effective utilization and management of water resources in the QLB, which is of great significance to the construction of a national park in the QLB. We used Geographic Information System (GIS) technology and remote sensing (RS) technology based on potential evapotranspiration data to calculate the VWC in the QLB from 2000 to 2020, and analyzed the influencing factors of the VWC in the QLB from 2000 to 2020. The results showed that (1) the average value of the VWC in the QLB varied from 242.96 mm to 287.99 mm, the average value of the VWC was 267.07 mm, and the average value of the total VWC was 79.05 × 108 m3 from 2000 to 2020. (2) In terms of spatial variation of the VWC, the VWC in the QLB did not increase significantly from 2000 to 2014, however, the VWC in the QLB showed a significant increase from 2015 to 2020. (3) As the altitude gradient increases, the VWC in the QLB from 2000 to 2020 showed a significant downward trend with the increase in altitude. When the altitude increases by 100 m, the value of the VWC decreases by 13.47 mm from 2000 to 2014 and 22.8 mm from 2015 to 2020, respectively. (4) Exploring the influencing factors of the VWC in the QLB from 2000 to 2020, the results showed that the VWC was mainly affected by the average annual precipitation and normalized difference vegetation index (NDVI) from 2000 to 2014. It was mainly affected by the combined effects of annual temperature, precipitation, and vegetation coverage from 2015 to 2020. The VWC was mainly affected by the average annual temperature, precipitation, and vegetation coverage along the altitude gradient from 2000 to 2014. It was mainly affected by the average annual temperature and vegetation coverage in the QLB from 2015 to 2020. Obviously, vegetation coverage was the most important factor affecting the VWC regardless of spatial or altitude gradient variations.

Effect of Vegetation Coverage on the Temporal and Spatial Distribution of PM2.5 Concentration in China's Eight Major Economic Regions from 1998 to 2016

The study researched the relationship between vegetation cover and PM2.5 pollution. The raster NDVI dataset from 1998 to 2016 were reclassified into low, medium, and high vegetation coverage area, and the corresponding PM2.5 concentration in eight economic regions in China were then calculated. On this basis, the temporal and spatial characteristics of PM2.5 pollution were analyzed and Pearson correlation coefficient was used to explore its correlation with NDVI landscape pattern indexes separately from landscape and class level NDVI. The preliminary results showed that:①The northern, eastern, southern coastal, middle reaches of the Yangtze River, and the northeast economic zones have relatively low vegetation coverage in areas with relatively serious PM2.5 pollution. However, the middle reaches of the Yellow River, the southwestern and the Northwestern Economic Zones in areas with relatively low vegetation coverage showed lighter PM2.5 pollution. ②PM2.5 increased in most areas between 1998 and 2016. ③A significant correlation between PM2.5 and NDVI landscape pattern indexes was not found for all areas. ④Therefore, the impacts of the landscape shape index(LSI), percent of landscape(PLAND), number of patches(NP), largest patch index(LPI), and aggregation index(AI) on PM2.5 are heterogeneous.

Estimation of Evapotranspiration in Sparse Vegetation Areas by Applying an Optimized Two-Source Model

Evapotranspiration (ET) is an important part of the water, carbon, and energy cycles in ecosystems, especially in the drylands. However, due to the particularity of sparse vegetation, the estimation accuracy of ET has been relatively low in the drylands. Therefore, based on the dry climate and sparse vegetation distribution characteristics of the drylands, this study optimized the core algorithms (canopy boundary resistance, aerodynamic resistance, and sparse vegetation coverage) and explored an ET estimation method in the Shuttleworth–Wallace two-layer model (SW model). Then, the Beijing–Tianjin sandstorm source region (BTSSR) was used as the study area to evaluate the applicability of the improved model in the drylands. Results show that: (1) The R2 value of the improved model results was increased by 1.4 and the RMSE was reduced by 1.9 mm, especially in extreme value regions of ET (maximum or minimum). (2) Regardless of the spatial distribution and seasonal changes of the ET (63–790 mm), the improved ET estimation model could accurately capture the differences. Furtherly, the different vegetation regions could stand for the different climate regions to a certain extent. The accuracy of the optimized model was higher in the semi-arid region (R2 = 0.92 and 0.93), while the improved model had the best improvement effect in the arid region, with R2 increasing by 0.12. (3) Precipitation was the decisive factor affecting vegetation transpiration and ET, with R2 value for both exceeding 0.9. The effect of vegetation coverage (VC) was less. This method is expected to provide a more accurate and adaptable model for the estimation of ET in the drylands.

Environmental determinants impacting the spatial heterogeneity of karst ecosystem services in Southwest China

AbstractSevere rocky desertification and considerable terrain relief in karst areas increase the difficulty of identifying determinants of ecosystem services (ESs), leading to relatively insufficient research on the quantitative attribution of karst ESs. This study investigates environmental determinants and their interactions affecting karst ESs in Southwest China and spatially variable correlations between environmental determinants and karst ESs in geomorphological regions using the geographical detector and geographical weighted regression methodologies. Results show that land use and vegetation coverage are the determinants of water yield and soil loss at the basin scale, with explanatory power of 67.2% and 32.3%, respectively; and the combination of elevation and vegetation coverage determines the spatial distribution of carbon sequestration. The determinants of ESs differed substantially among diverse geomorphological types due to differences in the inner characteristics of each. In addition to the dominant role of land use in each geomorphological type, the effects of vegetation coverage and precipitation on the water yield are significant in mountainous regions. The explanatory power of land use for soil loss decreases with increased terrain relief, while that of the vegetation coverage shows the opposite trend. For carbon sequestration, terrain factors play a more important role than land use at the basin scale, while land use is more influential in each geomorphological type. Furthermore, precipitation and vegetation coverage have the largest impact area on water yield and soil loss in each geomorphological type, respectively, and the impact area of each determinant of carbon sequestration shows obvious regional differences.

Effects of vegetation coverage and seasonal change on soil microbial biomass and community structure in the dry-hot valley region

Soil microorganisms are sensitive indicator of soil health and quality. Understanding the effects of vegetation biomass and seasonal change on soil microorganisms is vital to evaluate the soil quality and implement vegetation restoration. This study analyzed the soil phospholipid fatty acids (PLFAs) in fresh and withered Kudzu (Pueraria montana var. lobata) vegetation conditions in different seasons. The results showed that vegetation biomass and seasonal change significantly affected microbial biomass and its community structure. Both fresh and withered Kudzu cover significantly increased soil microbial biomass, and the growth effect of microbes in the soil with fresh Kudzu cover was more obvious than that with withered Kudzu cover. Compared with the dry season, the rainy season significantly increased the microbial biomass and the B/F (the ratio of bacterial to fungal PLFAs) ratio but dramatically reduced the G+/G- (the ratio of gram-positive to gram-negative bacteria PLFAs). Kudzu cover and seasonal change had a significant effect on microbial structure in soil covered by higher vegetation biomass. Furthermore, soil temperature and moisture had different correlations with specific microbial biomass in the two seasons. Our findings highlight the effect of Kudzu vine cover on the soil microenvironment and soil microhabitat, enhancing the soil quality in the Dry-hot Valley of Jinsha River, Southwest China.

Effects of Re-vegetation on Herbaceous Species Composition and Biological Soil Crusts Development in a Coal Mine Dumping Site.

Despite the critical roles of plant species' diversity and biological soil crusts (BSCs) in arid and semi-arid ecosystems, the restoration of the diversity of herbaceous species and BSCs are rarely discussed during the process of vegetation restoration of anthropogenically damaged areas in these regions. In this study, the herbaceous plant species composition, along with the BSCs coverage and thicknesses, was investigated at six different re-vegetation type sites, and the natural vegetation site of the Heidaigou open pit coal mine in China's Inner Mongolia Autonomous Region was used as a reference. The highest total species richness (16), as well as the species richness (4.4), occurred in the Tree and Herbaceous vegetation type site. The species composition similarities between the restored sites and the reference site were shown to be very low, and ranged from 0.09 to 0.42. Also, among the restored sites, the similarities of the species were fairly high and similar, and ranged from 0.45 to 0.93. The density and height of the re-vegetated woody plants were significantly correlated with the indexes of the diversity of the species. The Shrub vegetation type site showed the greatest total coverage (80%) of BSCs and algae crust coverage (48%). The Shrub and Herbaceous type had the greatest thicknesses of BSCs, with as much as 3.06 mm observed, which was followed by 2.64 mm for the Shrub type. There was a significant correlation observed between the coverage of the total BSCs, and the total vegetation and herbaceous vegetation coverage, as well as between the algae crust coverage and the herbaceous vegetation coverage. It has been suggested that the re-vegetated dwarf woody plant species (such as shrubs and semi-shrubs) should be chosen for the optimal methods of the restoration of herbaceous species diversity at dumping sites, and these should be planted with low density. Furthermore, the effects of vegetation coverage on the colonization and development the BSCs should be considered in order to reconstruct the vegetation in disturbed environments, such as mine dumpsites in arid areas.

Analysis of urban heat island effect using an improved CTTC and STTC model

An improved cluster thermal time constant (CTTC) and surface thermal time constant (STTC) numerical model was introduced, which took into account the effect of vegetation coverage and modified the expression of net long-wave radiation of the canyon layer. In the case study the model was used to calculate the air temperature variation at downtown of Tianjin City. The relative error between the calculated and measured air temperatures was less than 3%. The tendency of air temperature variation was predicted when the building aspect ratio, vegetation rate, and wind speed changed respectively. It is demonstrated that when the aspect ratio of a building with south-north orientation increased, the heat island intensity at day time was mitigated; however, it became worse after sunset. The vegetation coverage rate and wind speed both had negative relationship with the urban heat island intensity.

Effects of vegetation coverage on oviposition by Luehdorfia japonica (Lepidoptera: Papilionidae)

The effects of canopy and shrub layer coverage on the frequency of oviposition by a papilionid butterfly, Luehdorfia japonica, were investigated. Density of larval host plant tended to be higher where shrub layer was thinner, and the frequency of oviposition was correlated with host plant abundance. On the other hand, host plant abundance and the frequency of oviposition were not correlated with canopy layer coverage. Eggs were mainly found at or near the forest edge irrespective of host plant abundance.

Effects of vegetation coverage on the spatial distribution of soil nematode trophic groups

The spatial variability of total soil nematodes and trophic groups in bare and fallow plots in Shenyang Experimental Station of Ecology, Chinese Academy of Sciences was examined using geostatistics combined with classic statistics. Results showed that the soil pH value had a negative effect on plant-parasites in both bare and fallow plots; the mean number of total nematodes was significantly higher in fallow plots than in bare plots, which was 1485.3 and 464.0 individuals per 100 g dry soil in fallow and bare plots, respectively; the nugget (C0)/sill (C0+C) ratio of total nematodes, plant-parasites and bacterivores were lower in fallow plots (27.3%–45.6%) than in bare plots (49.5%–100%); the spatial distribution of total nematodes and trophic groups was found to be different between fallow and bare plots, which indicated that vegetation coverage had an effect on soil nematodes.