Variation In Vegetation Cover Research Articles

Responses of vegetation dynamics to complex environmental changes in the Runoff Producing area of the World’s Sixth Longest River: Evolution, Identification, and prediction

Vegetation plays a crucial role as a resilient safeguard for both natural ecosystems and human livelihoods in the source area of great rivers. Analyzing the variability of vegetation cover (VC) within the context of various complex drivers holds significant practical importance. In this study, an Evolution-Identification-Prediction (EIP) framework was developed to achieve the integrated assessment of vegetation dynamics and to identify its response to environmental changes. It is designed not only to display spatio-temporal features of vegetation change but also to emphasize determining the linkages between climate change (i.e., meteorological elements, climatic extremes, atmospheric circulation), human activities, anthropogenic factors (i.e., population, gross domestic product, land-use type), and vegetation dynamics. Furthermore, future patterns of vegetation were estimated by extracting information on historical changes in VC. In the above process, various methods and novel ideas with strong applicability have been proposed or introduced to achieve the stated objective. Then, the driving mechanisms of environmental changes on vegetation dynamics in the Upper Yellow River basin (UYRB) of China were examined across multiple dimensions, scales, and aspects. Results show that: a) complex correlation between NDVI and climate change appears, which is reflected in the differences of regions, factors, and correlation intensity; b) R10, PRCP, SDII and CWD are the main influences among extreme climate indices with explanatory power above 0.3; c) climate change and human activity jointly dominate vegetation dynamics in the UYRB, with the impact of human activity obviously enhanced; d) human activity has an overall positive effect on VC, and higher NDVI is generally found in forested, low population density and gross domestic product regions; e) the VC of the UYRB is projected to further improve under the combined influence of environmental factors, with the rate of high VC increase from 21.87% (2019) to 30.44% (2030). The findings can support the implementation of vegetation conservation and restoration initiatives to address the risks posed by environmental change.

Spatio-temporal variations of vegetation cover and its influencing factors in highland lake basin

Spatio-temporal variations of vegetation cover and its influencing factors in highland lake basin

Vegetation Density Mapping of Urban Solid Waste Landfill Coverage Using Vegetation Indexes Obtained with UAV

Objective: The objective of this study is to map the vegetation cover of a municipal solid waste landfill using high-resolution vegetation index images obtained with UAV, as a tool for geotechnical monitoring. Theoretical Framework: The theoretical framework describes the state of the art of vegetation indexes, starting from the first proposal of NVDI by Rouse et al. (1973), through to the NDWI by McFeeters (1996). Additionally, it presents the method of representing radiometric variables, considering that these indexes operate based on the ratio between spectral bands, which are displayed within intervals ranging from -1 to +1. Method: The study used a UAV equipped with MAPIR multispectral camera to capture images of the landfill. NDVI and NDWI indexes were applied to assess vegetation health and coverage. Field control points determined with GNSS-RTK, along with protogrametry software, ensured mapping accuracy, creating high-resolution orhomosaics for monitoring and determining vegetation indexes. Results and Discussion: The results indicate variation in vegetation cover, revealing areas of exposed soil ang vegetation at different stages of vigor, from senescence to full growth. The NDVI and NDWI indexes highlighted regions with water stress and soil exposure, demonstrating the effectiveness of the method in environmental and geotechnical monitoring. Conclusions: It is concluded that the use of UAVs and vegetation indexes are effective for monitoring vegetation health and landfill stability, enanbling the identification of erosion areas and the need for vegetation cover restoration.

Global evaluation of NOAA-20 VIIRS dark target aerosol products over land and ocean

The Dark Target (DT) algorithm has been applied to the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi-NPP (SNPP) and NOAA-20 satellites to extend the aerosol data record from the Moderate Resolution Imaging Spectrometer (MODIS). The newly released VIIRS DT Version 2.0 (V2.0) dataset includes NOAA-20 aerosol products for the first time. This study provides the first evaluation of NOAA-20 VIIRS DT aerosol products, including aerosol optical depth (AOD) and Ångstrom exponent (AE), for the period 2018–2022 using Aerosol Robotic Network (AERONET) and Maritime Aerosol Network (MAN) measurements. In addition, the operational DT aerosol products from SNPP VIIRS (V2.0) and MODIS (Collection 6.1) are also used for comparison purposes. Overall, NOAA-20 AODs over land and ocean exhibit good validation metrics globally, showing comparability to MODIS products and superiority over overestimated SNPP products. Nevertheless, it is worth noting that in South Africa specifically, NOAA-20 land AODs tends to display more pronounced negative biases, despite all products being underestimated. Furthermore, all ocean AE products demonstrate high correlation coefficients (>0.83) with the ground-based data, meeting the fraction of expected accuracy (>80%). Encouragingly, NOAA-20 AE product has significantly improved the persistent issue of overestimation at low-value in MODIS product, making it a more preferable choice for usage. Error analysis reveals that the performance of all three land products decreases in sparsely vegetated areas and when the solar zenith angle is small. However, NOAA-20 AOD exhibits relatively stable performance and is less affected by variations in aerosol loading, observation geometry, and surface vegetation cover. In addition, the performance of AOD and AE over ocean is significantly influenced by scattering angle and wind speed. This research is anticipated to serve as a reference for the utilization of operational VIIRS DT aerosol products and possible algorithm optimization.

δ13C and δ18O-based interpretation of Miocene carbonates of the Miranda-Trebiño basin, NE Iberia: preliminary insights

The stable isotopes (C and O), bulk mineralogy and sedimentary facies types of the Miocene lacustrine palustrine carbonates of the Cucho Section (Miranda-Trebiño basin, N Iberia) are studied. The results indicate deposition in a freshwater carbonate lake recording significant biogenic CO2 input, changing Precipitation/Evaporation rates and variations in vegetation cover and pedogenesis on palustrine areas. Short-lived stages of higher salinity and evaporative conditions are recorded by the relative abundance of fine-grained dolomite. The highest δ13C values suggest 12C sequestration in anoxic bottom waters due to water column stratification. These new data support the general deepening trend of the lake system established from previous sedimentological analyses.

Spatial–Temporal Evolution Pattern of Soil Erosion and Its Dominant Factors on the Loess Plateau from 2000 to 2020

Global changes have led to significant changes in soil erosion on the Loess Plateau. Soil erosion leads to the degradation of land resources and a decline in soil fertility, adversely affecting agricultural production and the socioeconomic situation. Therefore, revealing the spatiotemporal evolution patterns of soil erosion in the Loess Plateau region and investigating the influencing factors that contribute to soil erosion are crucial for its management and restoration. In this study, the RUSLE monthly model and the Geodetector model were utilized to reveal the spatiotemporal trends of soil erosion in the Loess Plateau from 2000 to 2020 and to determine the dominant influencing factors in different periods. The main results are as follows: (1) From 2000 to 2020, the soil erosion in the Loess Plateau initially weakened and then intensified, indicating that precipitation and precipitation intensity have different effects on surface soil. (2) From 2000 to 2015, the area experiencing slight and mild erosion increased. This is attributed to the increase in vegetation coverage in the Loess Plateau region, which has alleviated soil erosion in the area. (3) From 2000 to 2020, zones of severe soil erosion were mainly located in the cities of Yan’an and Yulin and their surrounding areas. The gravity center of soil erosion shifted northwestward from Yan’an City overall, indicating an improvement in the soil erosion conditions in the Yan’an area. (4) The predominant level of soil erosion across different land-use types was slight erosion, accounting for over 40%. This may be a result of forestry ecological projects that effectively reduce soil loss. (5) In slope zones of 0–5°, slight erosion accounted for the largest area proportion. As the slope increased, the area proportion of severe and extremely severe erosion also increased. This is attributed to the protective role of vegetation on soil in gentle slope areas. (6) From 2000 to 2020, vegetation was the dominant single factor influencing the spatiotemporal changes in soil erosion, while the interactions between vegetation and land use had the largest explanatory power, indicating that changes in land-use types partially affect variations in vegetation coverage. Our research findings could provide important data support for soil erosion control and eco-environment restoration in the Loess Plateau region.

MAPPING AND GEOSPATIAL DISTRIBUTION OF AÇAÍ TREES (EUTERPE OLERACEA MART) IN THE TOCANTINA-PA AMAZON

The article aims to map and analyze açaí management and planting systems in floodplain and terra firma areas in the Tocantina Amazon, specifically in the municipality of Mocajuba, Pará. To achieve this work, remote sensing and geoprocessing techniques were used, where we sought characterize the spatial and temporal distribution of açaí groves and evaluate changes in the landscape over the years. The application of the spectral indices NDVI (Normalized Difference Vegetation Index), NDWI (Normalized Difference Water Index) and NDBI (Normalized Difference Construction Index) proved to be fundamental to identify areas with greater plant biomass, humidity levels and urban expansion, respectively. The results point to the importance of sustainable management practices to guarantee productivity and environmental preservation. It is concluded that the analysis of spectral indices proved to be effective in detecting variations in vegetation cover and water availability, providing crucial information for the planning and management of plantations in the region.

Detection of spatial and temporal variation characteristics of vegetation cover in the Lower Mekong region and the influencing factors

As the main component of terrestrial ecosystem, vegetation plays a very important role in regional ecosystem environmental change, global carbon cycle and climate regulation. The Lower Mekong region (LMR) is at the core of Southeast Asia, its vegetation changes will affect the regional ecosystem and climate. Five countries of LMR were selected as the study area, based on MODIS (Moderate-Resolution Imaging Spectroradiometer) NDVI(Normal Difference Vegetation Index) data from 2000 to 2022, using the Sen’s slope estimator, Mann–Kendall trend test and geographic detector to study the spatial and temporal variation trends and driving forces of vegetation coverage. The results showed that:(1) From 2000 to 2022,the vegetation coverage in the LMR showed an overall fluctuating upward trend, the annual average Fractional Vegetation Cover(FVC) value was 0.70, mainly with high vegetation coverage and relatively high vegetation coverage. Vegetation distribution had obviously spatial heterogeneity, and the vegetation of Myanmar, Laos and Vietnam was significantly larger than Thailand and Cambodia.(2) The variation trend analysis of Sen_MK showed that the proportion of improved and degraded vegetation coverage areas in the LMR were 56.33% and 37.55% respectively. The vegetation improvement area was much larger than the vegetation degradation area during 2000–2022. According to the variation trend analysis of different countries, the vegetation coverage improvement area in Vietnam, Myanmar and Thailand were larger than the degraded , the overall vegetation coverage variation trend were good. However, in Laos and Cambodia, the degraded areas were larger than the improved, the overall variation trends of coverage were not good.(3) The results of geographic detector showed that the Land Use and Land Cover(LULC) had the greatest influence on vegetation coverage in the study area.The influencing factors of vegetation coverage were different in the LMR. For Vietnam, Thailand and Laos,elevation and slope factors were second only to LULC, for Myanmar and Cambodia, the influence of precipitation factor was second only to LULC. The results provide scientific data support for understanding the ecological environment status and future changes in the research area.

EVALUATION OF DEFORESTATION IN THE MUNICIPALITY OF BRASIL NOVO IN THE STATE OF PARÁ - BRAZIL, USING MACHINE LEARNING TECHNIQUES

The agricultural frontier of the Brazilian Amazon, is undergoing significant changes in its land cover, primarily driven by the expansion of cattle ranching and cocoa cultivation. Through the analysis of Landsat 8 satellite images and the WorldCover 10m 2020 product, combined with climatic and socioeconomic data, this study investigated land use dynamics between 2015 and 2023, on the municipality of Brasil Novo. The results revealed a substantial reduction in forest cover, with the expansion of pasturelands as the main driver of deforestation. The temporal analysis of the Normalized Difference Vegetation Index (NDVI) indicated interannual variations in vegetation cover, associated with extreme weather events and anthropogenic pressure. Although the municipality still maintains 43.8% of forest cover, with the Arara Indigenous Land being a notable example, the pressure on natural resources demands the implementation of public policies and sustainable management practices to mitigate environmental impacts and ensure the conservation of Amazonian biodiversity. Keywords: Amazon, NDVI, remote sensing, climate change, livestock, land use.

The role of early life factors and green living environment in the development of gut microbiota in infancy: Population-based cohort study

ObjectiveEarly life microbial exposure influences the composition of gut microbiota. We investigated how early life factors, and the green living environment around infants’ homes, influence the development of gut microbiota during infancy by utilizing data from the Steps to Healthy Development follow-up study (the STEPS study). MethodsThe gut microbiota was analyzed at early (∼3 months, n = 959), and late infancy (∼13 months, n = 984) using 16S rRNA amplicon sequencing, and combined with residential green environment, measured as (1) Normalized Difference Vegetation Index, (2) Vegetation Cover Diversity, and (3) Naturalness Index within a 750 m radius. We compared gut microbiota diversity and composition between early and late infancy, identified significant individual and family level early life factors influencing gut microbiota, and determined the role of the residential green environment measures on gut microbiota development. ResultsAlpha diversity (t-test, p < 0.001) and beta diversity (PERMANOVA, R2 = 0.095, p < 0.001) differed between early and late infancy. Birth mode was the strongest contributor to the gut microbiota community composition in early infancy (PERMANOVA, R2 = 0.005, p < 0.01) and the presence of siblings in late infancy (PERMANOVA, R2 = 0.007, p < 0.01). Residential green environment showed no association with community composition, whereas time spend outdoors did (PERMANOVA, R2 = 0.002, p < 0.05). Measures of greenness displayed a statistically significant association with alpha diversity during early infancy, not during late infancy (glm, p < 0.05). In adjusted analysis, the associations remained only with the Naturalness Index, where higher human impact on living environment was associated with decreased species richness (glm, Observed richness, p < 0.05). ConclusionsThe role of the residential green environment to the infant gut microbiota is especially important in early infancy, however, other early life factors, such as birth mode and presence of sibling, had a more significant effect on the overall community composition.

Consistent generalization of plant-hummingbird networks despite increasing vegetation cover across a tropical urban landscape

Human activities, particularly urbanization, profoundly impact ecosystems often resulting in biotic homogenization. Whether or not urban landscapes can sustain diverse pollinator and plant communities is an important question to be addressed. Here, we investigated the influence of urbanization on plant-hummingbird interaction networks in a large tropical city, Belo Horizonte, Brazil. We recorded 13198 legitimate interactions between seven hummingbirds and 57 plant species across 12 local networks. Urban landscapes exhibited predominantly generalized networks, maintaining this pattern across varying vegetation cover and floral resource abundance. Although some functionally specialized hummingbirds with long bills were recorded performing more specialized interactions, urban environments did not generally support specialized networks. Nevertheless, network specialization did increase with the proportion of native nectar plants, emphasizing their importance for maintaining some specialized interactions. Furthermore, we observed a positive effect of plant richness, but not of flower abundance, on hummingbird abundance, indicating that it is not only the amount of flowers, but the diversity of floral resources that may be a key factor in maintaining hummingbirds. Therefore, promoting a diverse assemblage of native plants in urban green areas is crucial for sustainable pollinator communities. Our study highlights that while a biodiverse urban landscape will require careful urban vegetation planning considering both floral resource diversity and availability, vegetation cover per se may not be sufficient to mitigate the negative impacts of urbanization. Maintaining a diverse vegetation with different life forms, flowering phenology, and especially of native plants across the urban landscape is needed to create welcoming spaces for pollinators.

The effect of dynamic changes in vegetation coverage on the mechanism of organic carbon loss in inter-rill erosion

The intricate effects of dynamic variations in vegetation coverage, representing different vegetation growth states and erosion conditions, on properties (content, enrichment and loss) of sediment and soil organic carbon (SOC) fraction in inter-rill erosion have not yet been fully elucidated. By setting micro-plots with different vegetation coverage ranges (0 %, 15 ∼ 35 %, 25 ∼ 55 % and 35 ∼ 70 %), the interaction mechanisms between vegetation coverage and inter-rill erosion, particle size distribution and SOC fractions properties during the vegetation growing period were studied. The average sediment yield, runoff yield and sediment concentration were highest under the bare plot, and diminished progressively with increased vegetation coverage. The effective clay content decreased with the increasing coverage, while ultimate clay was highest in the vegetation coverage range of 25 ∼ 55 %. Clay particle was transported as aggregates, with enrichment for all treatments except for the vegetation coverage range of 35 ∼ 70 %, providing transportation potential for SOC fractions loss. The content of SOC and mineral-associated organic carbon, as well as their enrichment ratio, decreased and then increased with coverage, which is the opposite of particulate organic carbon, and the loss of all fractions decreased with increasing vegetation coverage. Mineral-associated organic carbon dominated change in SOC, with proportion in SOC content and loss decreasing first and then increasing with vegetation coverage. The structural equation model showed the impact of vegetation coverage on SOC fraction loss was mainly achieved through indirect regulation of inter-rill erosion and particle size distribution. Our results provide new insights into the complex relationship between natural slope vegetation coverage and SOC loss, particularly from a fractions perspective, as well as understanding the ultimate fate of SOC in such environments.

Spatial and temporal variations of vegetation cover on the central and eastern Tibetan Plateau since the Last glacial period

Long-term changes in vegetation cover of the Tibetan Plateau (TP) are essential for understanding vegetation change under future climate. Previous studies have mainly concentrated on the Holocene and the eastern region of the TP, but here, we establish a relationship between modern pollen data (including both pollen percentage and concentration) and vegetation cover using a random forest (RF) model based on 362 soil-surface samples from the TP, as well as using it to quantitatively reconstruct the vegetation cover history of the Dagze Co (central TP, covering the last 19.5 cal. ka BP) and Koucha Lake (eastern TP, covering the last 33.8 cal. ka BP) regions. The RF results indicate that both the models based on pollen percentages or concentrations perform similarly (former: R2 = 0.538, RMSEP = 19.772%; latter: R2 = 0.540, RMSEP = 19.723%). However, when considering the reconstructed vegetation cover of Dagze Co and Koucha Lake, the results based on pollen concentrations appear to be more reliable. Before 13.4 and 16.8 cal. ka BP, Dagze Co and Koucha Lake has low vegetation cover of 25% and 30%, respectively, dominated by alpine desert or desert steppe. After that, changes in vegetation cover show different trends. At Dagze Co, the vegetation cover reaches a high level (54%) between 13.4 and 5.3 cal. ka BP, followed by a decrease until it starts increasing again at 2 cal. ka BP, in response to the change in the Indian Summer Monsoon (ISM). At Koucha Lake, the vegetation cover fluctuates at around 60%, indicating less sensitivity to climate change. Our research highlights the importance of pollen concentrations in quantitatively reconstructing past vegetation cover and the sparse vegetation status during the LGM on the TP.

A first look into moss living tardigrades in boreal peatlands.

Tardigrades (Tardigrada) are a phylum of micrometazoans found in all biomes on Earth, but their ecology and habitat preferences remain vastly understudied. Boreal peatlands include a diversity of habitat types and high structural heterogeneity that represents an interesting system to study some of the poorly known habitat preferences of tardigrades. Here, we investigate for the first time tardigrade communities in peatland mosses and the latter's potential associations with key environmental variables. We collected 116 moss samples from 13 sites representing different peatland types and management histories. We found that tardigrades are common and diverse in boreal peatlands, as tardigrades were present in 72% of the collected samples and we identified 14 tardigrade genera. Tardigrade abundance seemed to increase alongside the increasing tree basal area and the density was higher in the microtopographic level further from the water table level, that is, hummocks (mean 117/moss gram) than in lawns/hollows (mean 84/moss gram). Furthermore, the highest tardigrade density was found in the moss taxa that are associated with forested peatland types (i.e., feather mosses) (321 mean/moss gram). Finally, we found interesting patterns regarding tardigrade functional diversity, as carnivorous tardigrades were found only in peatlands with tree basal area > 20 m2 and mostly in hummocks. Our study demonstrates that the habitat heterogeneity of peatlands (e.g., variation in moisture and vegetation cover) represents an interesting system to study tardigrade ecology and habitat preferences. However, since we found variation in tardigrade abundance and communities across peatland types and microhabitats within peatlands, our results highlight that such studies should be conducted with numerous replicate samples and a systematic study design that properly addresses the habitat heterogeneity between and within different peatland types.

An advanced TSMK-FVC approach combined with Landsat 5/8 imagery for assessing the long-term effects of terrain and climate on vegetation growth.

As an exceptional geographical entity, the vegetation of the Qinghai-Tibetan Plateau (QTP) exhibits high sensitivity to climate change. The Baima Snow Mountain National Nature Reserve (BNNR) is located in the south-eastern sector of the QTP, serving as a transition area from sub-tropical evergreen broadleaf forest to high-mountain vegetation. However, there has been limited exploration into predicting the temporal and spatial variability of vegetation cover using anti-interference methods to address outliers in long-term historical data. Additionally, the correlation between these variables and environmental factors in natural forests with complex terrain has rarely been analyzed. This study has developed an advanced approach based on TS (Theil-Sen slope estimator) MK (Mann-Kendall test)-FVC (fractional vegetation cover) to accurately evaluate and predict the time and spatial shifts in FVC within the BNNR, utilizing the GEE (Google Earth Engine). The satellite data utilized in this paper consisted of Landsat images spanning from 1986 to2020. By integrating TS and MK methodologies to monitor and assess the FVC trend, the Hurst index was employed to forecast FVC. Furthermore, the association between FVC and topographic factors was evaluated, the partial correlation between FVC and climatic influences was analyzed at the pixel level (30×30m). Here are the results of this research: (1) Overall, the FVC of the BNNR exhibits a growth trend, with the mean FVC value increasing from 59.40% in 1986 to 68.67% in 2020. (2) The results based on the TS-MK algorithm showed that the percentage of the area of the study area with an increasing and decreasing trend was 59.03% (significant increase of 28.04%) and 22.13% (significant decrease of 6.42%), respectively. The coupling of the Hurst exponent with the Theil-Sen slope estimator suggests that the majority of regions within the BNNR are projected to sustain an upward trend in FVC in the future. (3) Overlaying the outcomes of TS-MK with the terrain factors revealed that the FVC changes were notably influenced by elevation. The partial correlation analysis between climate factors and vegetation changes indicated that temperature exerts a significant influence on vegetation cover, demonstrating a high spatial correlation.

Temperature and palaeolake evolution during a Middle Pleistocene interglacial–glacial transition at the Palaeolithic locality of Schöningen, Germany

The Middle Pleistocene Reinsdorf sequence at the Lower Palaeolithic sites of Schöningen offers the opportunity to reconstruct a rarely well‐preserved post‐Holsteinian environmental transition from an interglacial into a glacial phase along with its highly dynamic interjacent climatic oscillations. Combining biological proxies, element composition and stable isotope ratios of two lakeshore sequences at excavation site 13 II, we demonstrate repeated variations in climate, hydrology and catchment vegetation cover. New ostracod‐based quantitative mean summer and winter air temperature reconstructions with the Mutual Ostracod Temperature Range (MOTR) method provide the first detailed information about the temperature evolution. The interglacial temperature maximum, probably corresponding to Marine Isotope Stage 9e, is followed by a first dry phase and, during the younger part of the Reinsdorf sequence, by a second dry period. Both were marked by lower precipitation/evaporation ratios, reduced vegetation cover in the catchment and increased surface inflows from springs. Temperature reconstructions of these two steppe (open woodland) phases yield very narrow ranges for mean January (−4–0 °C) and July (+17–19 or +17–21 °C) air temperatures, demonstrating that, while summers were similar to those of today, winters were at least 1 °C colder, hinting at a more pronounced continental climate. Precise temperature estimates for the interjacent woodland and steppe (woodland) phase are hindered by generally wider ranges produced by the MOTR method (January mean −4–3 °C, July mean +15–21 °C). The development of a more extensive vegetation cover, reducing surface runoff and erosion in favour of increased river and groundwater discharge, as indicated by a shift in microfossil and stable isotope records, suggests generally more humid climates with higher precipitation/evaporation ratios as well as reduced seasonal temperature variations.

Restoration of vegetation in the Yellow River Basin of Inner Mongolia is limited by geographic factors

Studying the relationships between vegetation cover and geography in the Mongolian region of the Yellow River Basin will help to optimize local vegetation recovery strategies and achieve harmonious human relations. Based on MOD13Q1 data, the spatial and temporal variations in fractional vegetation cover (FVC) in the Mongolian Yellow River Basin during 2000–2020 were investigated via trend and correlative analysis. The results are as follows: (1) From 2000 to 2020, the vegetation cover in the Mongolian section of the Yellow River Basin recovered well, the mean increase in the FVC was 0.001/a, the distribution of vegetation showed high coverage in the southeast and low coverage in the northwest, and 31.19% of the total area showed an extremely significant and significant increase in vegetation cover. (2) The explanatory power of each geographic factor significantly differed. Precipitation, soil type, air temperature, land use type and slope were the main driving factors influencing the spatial distribution of the vegetation cover, and for each factor, the explanatory power of its interaction with other factors was greater than that of the single factor. (3) The correlation coefficients between FVC and temperature and precipitation are mainly positive. The mean value of the FVC and its variation trend are characterized by differences in terrain and soil characteristics, population density and land use. Land use conversion can reflect the characteristics of human activities, and positive effects, such as returning farmland to forest and grassland and afforestation of unused land, promote the significant improvement of regional vegetation, while negative effects, such as urban expansion, inhibit the growth of vegetation.

Dust model sensitivity to dust source mask, sandblasting efficiency, air density, and land use: Implications for model improvement

This study compares dust storm simulations using two commonly adopted methods for representing four important dust emission parameters. Compared with a dynamic dust source mask based on land use and vegetation cover, a static mask based solely on land use overestimates dust concentration and optical depth by a factor of 2, besides generating spurious emissions. The results reinforce that seasonal variations in vegetation cover can significantly affect dust emissions. For sandblasting efficiency, a clay-dependent semiempirical expression produces 12 times more dust than does a physics-based expression. Simulations using model-predicted versus constant air density differ by only 8%. However, this difference (often overlooked) could range between 12% and 22% for annual simulations over global dust source regions. Simulations with updated versus old land use data, using the same dust source mask, differ twofold, indicating the significant impact of land use change on regional dust emission in central Arizona. The difference between simulations within each of the four pairs is generally larger than the uncertainty due to meteorology. The simulations align better with observation when using the dynamic dust source mask, the physics-based sandblasting efficiency, and the up-to-date land use data. Given the high sensitivity of dust to surface conditions, the results discussed have implications for improving the dust cycle in weather and climate models and for interpreting model intercomparisons.

Urban expansion and vegetation dynamics: The role of protected areas in preventing vegetation loss in a growing mega city

The decrease in vegetation cover due to urban expansion poses serious challenge to urban sustainability. Protected areas (PAs) are the most effective tools to prevent the loss of urban vegetation cover and to control urban expansion. Hence, this study aims to assess the importance of PAs in protecting urban vegetation and the urban expansion in the mega city of Delhi. For this, Landsat datasets were used for land use and land cover (LULC) mapping and then land cover change rate (LCCR) and land cover intensity (LCI) were calculated. For assessing urban expansion dynamics, mean landscape expansion index (MLEI) and the area-weighted LEI (AWLEI) were calculated. To evaluate the significance of PAs in protecting vegetation cover, kernel density estimation (KDE) was applied to assess the spatial variation and concentration of vegetation cover under different PAs. The result shows that urban expansion in Delhi was initially characterized by edge expansion during 1991–2001, followed by outlying expansion of built-up area during 2001–2021, while infilling of open and vegetated areas by built-up area was consistent during 1991–2021. Vegetation cover on the other hand, has followed a fluctuating trend in the city, but has overall it has declined from 13.36% to 9.30% during 1991–2021. The vegetation cover has declined significantly in eastern, northern, and western parts of Delhi but has increased significantly in central and southern parts, especially during 2001–21. This is because the central and southern parts of Delhi are well planned and have several PAs while the western, northern, and eastern parts of Delhi are unplanned regions and have only a few PAs. The KDE chart shows that the PAs have played an important role in protecting the vegetation cover in Delhi with R2 value > 0.70. Hence, this study suggests to give special emphasis on preservation and expansion of PAs in urban planning for the long-term conservation of urban vegetation cover and sustainable urban development.

Spatiotemporal patterns, sustainability, and primary drivers of NDVI-derived vegetation dynamics (2003-2022) in Nepal.

Understanding the vegetation dynamics and their drivers in Nepal has significant scientific reference value for implementing sustainable ecological policies. This study provides a comprehensive analysis of the spatio-temporal variations in vegetation cover in Nepal from 2003 to 2022 using MODIS NDVI data and explores the effects of climatic factors and anthropogenic activities on vegetation. Mann-Kendall test was used to assess the significant trend in NDVI and was integrated with the Hurst exponent to predict future trends. The driving factors of NDVI dynamics were analyzed using Pearson's correlation, partial derivative, and residual analysis methods. The results indicate that over the last 20 years, Nepal has experienced an increasing trend in NDVI at 0.0013 year-1, with 80% of the surface area (vegetation cover) showing an increasing vegetation trend (~ 28% with a significant increase in vegetation). Temperature influenced vegetation dynamics in the higher elevation areas, while precipitation and human interventions influenced the lower elevation areas. The Hurst exponent analysis predicts an improvement in the vegetation cover (greening) for a larger area compared to vegetation degradation (browning). A significantly increased area of NDVI residuals indicates a positive anthropogenic influence on vegetation cover. Anthropogenic activities have a higher relative contribution to NDVI variation followed by temperature and then precipitation. The results of residual trend and Hurst analysis in different regions of Nepal help identify degraded areas, both in the present and future. This information can assist relevant authorities in implementing appropriate policies for a sustainable ecological environment.