Variation In Vegetation Cover Research Articles

Modeling suitable habitats of Edible-nest Swiftlet (Aerodramus fuciphagus) to support ecotourism in karst ecosystem of Karang Bolong, Kebumen, Indonesia

Abstract. Wibowo AA, Ningrum FU. 2023. Modeling suitable habitats of Edible-nest Swiftlet (Aerodramus fuciphagus) to support ecotourism in karst ecosystem of Karang Bolong, Kebumen, Indonesia. Intl J Trop Drylands 7: 112-119. The karst ecosystem plays a vital role as a habitat for the Edible-nest Swiftlet (Aerodramus fuciphagus (Thunberg, 1812)) (synonym: Collocalia fuciphaga) due to the availability of caves for roosting sites. Additionally, factors such as vegetation cover and drought influence the presence of A. fuciphagus in karst ecosystems. Karang Bolong in Kebumen, Indonesia is identified as a karst ecosystem inhabited by A. fuciphagus. However, there is limited information regarding potential suitable habitats for this species. This study aimed to model the potential habitat for A. fuciphagus using Species Distribution Modeling, considering vegetation cover variables represented by NDVI and drought represented by NDMI. The habitat suitability was assessed using the AUC metric, with values ranging from 0.875 to 0.968, indicating a good model fit for depicting potential habitats for the species. In Karang Bolong, the suitability of habitats was constrained by drought conditions. The model suggests suitable habitats are concentrated in caves along the Kebumen Coasts. This information is valuable for identifying areas suitable for ecotourism and providing an alternative to swiftlet nest cultivation/harvesting. Regarding ecotourism activities, birding and observing Edible-nest Swiftlets in their natural coastal habitats, featuring scenic coastal views, could be attractive options to support the tourism industry within the karst ecosystems of Karang Bolong and Kebumen.

Environmental Influences on Rabi Crops using GIS and Remote Sensing: A Case Study of Mianwali District

Current study aims at to analyze the environmental influence on Rabi crops and to analyze the rainfall pattern with the vegetation pattern. Despite a declining GDP contribution, agriculture remains a fundamental pillar of Pakistan's economy, supporting livelihoods, nutrition, and export earnings. Focused on Mianwali District, the research integrates data from Landsat satellites, MODIS LST, and rainfall records to untangle relationships between environmental factors and Rabi crop productivity. Analysis of the Normalized Difference Vegetation Index (NDVI) provides insights into crop health by revealing variations in vegetation cover. Land Surface Temperature (LST) data offers perspectives on thermal conditions during the Rabi season, crucial for understanding water stress. Rainfall data assists in assessing water availability and its impact on crop yield. Correlation analysis highlights the direct impact of environmental conditions on agricultural productivity. Temporal trends show diversification in crop types, with "High Crops" on an upward trajectory, while the overall crop area in Mianwali District consistently decreases, possibly linked to changing environmental patterns. Land Surface Temperature conditions suggest potential environmental adaptations, supported by a decrease in LST values from 2000 to 2022, indicating improved thermal conditions or adaptive strategies. Rainfall analysis underscores the significance of understanding climatic patterns for sustainable agriculture. The correlation between NDVI and LST emphasizes vegetation sensitivity to thermal conditions, providing valuable insights for ecological studies and precision agriculture. The positive correlation between Rainfall and NDVI highlights the crucial role of water availability in fostering vegetation health and guiding sustainable agricultural practices.

Importance of land use and rainfall in the dynamics of the Caatinga vegetation cover in Northeastern Brazil

Many factors, such as climate, land use, and cultural and social aspects, influence the vegetation cover dynamics. We aimed to analyze the vegetation cover dynamics in three municipalities of the Brazilian semi-arid region (Aroeiras, Boqueirão, and Congo, state of Paraíba, Brazil) and to check for the influence of land use and inter-annual variations in rainfall. We selected 18 Landsat satellite images between 1995 and 2017. We performed supervised classification based on pre-established regions of interest: Closed or conserved vegetation, Sparse or disturbed vegetation, Exposed soil, Water bodies, clouds, and shadows, according to color, shape, and texture criteria. In addition, we collected data from the IBGE's Agricultural Census and annual rainfall. Variations in land use and rainfall variations worked synergistically on vegetation cover dynamics. In the municipality of Congo, very wet years were associated with higher percentages of closed vegetation and decreased soil exposure. High percentages of land use were related to a higher cover of sparse vegetation and exposed soil. In Boqueirão, we observed the opposite phenomenon, with drier years associated with higher percentages of closed vegetation and exposed soil. In Aroeiras, we identified no clear relationship between rainfall and variations in vegetation cover. Similar to that observed in the other municipalities, the abandonment of agricultural and cattle ranching activities increased dense vegetation. Our results show that the analysis of land use and vegetation cover dynamics in the semi-arid region represents a complex task ranging from regional factors, such as climate, characterized by inter-annual rainfall variations, to local factors, such as land use intensity and demographic/social aspects.

Global inequities in population exposure to urban greenspaces increased amidst tree and nontree vegetation cover expansion

Cities worldwide are expanding greenspaces, including parks, urban forests, and grasslands. However, population exposure to tree and nontree vegetation is less well understood. Here, we use multiple satellite-derived datasets on vegetation, climate, and socioeconomic factors to examine the variations of urban tree and nontree vegetation cover, drivers of changes, and the impacts on global urban population exposure between 2000 to 2020. We find that approximately 90% of cities experienced an ascending trend in tree cover, and 49% of cities showed growth in nontree vegetation (p < 0.05). The increase in urban tree cover is most evident in high-latitude areas, such as Eastern Russia and Northern Europe. Human exposure to urban tree vegetation considerably declined in the Global South, widening the disparity between the North and South. Our study underscores persistent inequalities in human exposure to green space in cities and calls for evidence-based strategies that reduce increasing disparities.

Assessment of seasonal warming trends at the Nile Delta: a paradigm for human-induced climate change.

Given its modern geographical and geomorphological characteristics, along with rapid socio-economic changes, the Nile Delta stands out as one of the world's most dynamic landscapes. The key drivers of the land use change in this region have been the reclamation of delta margins, changes in agricultural practices, and urban expansion. The present study aims to explore the variations in the seasonal daytime and nighttime trends of the land surface temperatures (LST) at this active agronomic system in response to the seasonal variations of vegetation cover as revealed by the normalized difference vegetation index (NDVI) during the past two decades. The data were exclusively acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument for the period from January 2001 to December 2021, where geospatial and statistical analyses were accomplished to construct a LST/NDVI spatio-temporal pattern throughout the Nile Delta. Results revealed a robust negative and a significant relationship between the NDVI and the diurnal LST with high regression coefficients (R2) ranging from 0.78 to 0.97 (p value < 0.05). Maximal seasonal warming trends occurred during harvesting seasons (springs and falls), while the least warming was recorded during winters (the growing seasons). It was also observed that the nocturnal warming (0.72°C/decade) was almost as double as the corresponding value of the daytime trend (0.33°C/decade). The study recognized a seasonal climatic warming throughout the Nile Delta influenced by the human-induced land use change and agricultural practices.

Effects of seasonal variations in vegetation and precipitation on catchment erosion rates along a climate and ecological gradient: insights from numerical modeling

Abstract. Precipitation in wet seasons influences catchment erosion and contributes to annual erosion rates. However, wet seasons are also associated with increased vegetation cover, which helps resist erosion. This study investigates the effect of present-day seasonal variations in rainfall and vegetation cover on erosion rates for four catchments along the extreme climate and ecological gradient (from arid to temperate) of the Chilean Coastal Cordillera (∼ 26–∼ 38∘ S). We do this using the Landlab–SPACE landscape evolution model to account for vegetation-dependent hillslope–fluvial processes and hillslope hydrology. Model inputs include present-day (90 m) topography and a time series (from 2000–2019) of MODIS-derived Normalized Difference Vegetation Index (NDVI) for vegetation seasonality, weather station observations of precipitation, and evapotranspiration obtained from Global Land Data Assimilation System (GLDAS) Noah. The sensitivity of catchment-scale erosion rates to seasonal average variations in precipitation and/or vegetation cover was quantified using numerical model simulations. Simulations were conducted for 1000 years (20 years of vegetation and precipitation observations repeated 50 times). After detrending the results for long-term transient changes, the last 20 years were analyzed. Results indicate that when vegetation cover is variable but precipitation is held constant, the amplitude of change in erosion rates relative to mean erosion rates ranges between 5 % (arid) and 36 % (Mediterranean setting). In contrast, in simulations with variable precipitation change and constant vegetation cover, the amplitude of change in erosion rates is higher and ranges between 13 % (arid) and 91 % (Mediterranean setting). Finally, simulations with coupled precipitation and vegetation cover variations demonstrate variations in catchment erosion of 13 % (arid) to 97 % (Mediterranean setting). Taken together, we find that precipitation variations more strongly influence seasonal variations in erosion rates. However, the effects of seasonal variations in vegetation cover on erosion are also significant (between 5 % and 36 %) and are most pronounced in semi-arid to Mediterranean settings and least prevalent in arid and humid–temperature settings.

Soil erosion triggered by the archeological excavation and conservation of trenches. The case of “Cerro de las Trincheras” in Bailén (Jaén, Spain)

Gully erosion is a landform developed due to accelerated soil erosion rates. Gullies can be identified by human impacts on geomorphological processes, as well as hydrological and erosional systems. In Spain, the trenches or "trincheras" from the Spanish Civil War (1936-1939) are considered of archaeological interest for several reasons. At Cerro de las Trincheras in Bailén (Jaén, Spain), a trench was built during the Spanish Civil War. In 2020, an archaeological excavation took place to restore the ruins, triggering the development of gullies and rills and a decrease in vegetation quality. We present a first approximation of the variations in vegetation cover and the decrease in quality (using NDVI, the normalized difference vegetation index) due to the trench acting as a gully (1956, 2005-2020) and the increase in rills and gullies after the excavation. We strongly advocate for future archaeological excavations to include a protocol (soil mapping, vegetation survey, and hydrological connectivity index) to reduce soil degradation and prevent damage to vegetation and associated ecosystems, thereby curbing the increase in soil erosion rates.

Tracing climatic and human disturbance in diverse vegetation zones in China: Over 20 years of NDVI observations

Over the past two decades (2000–2021), China has experienced a significant increase in vegetation cover. However, the intricate spatial and temporal variations in vegetation cover, arising from the interaction of climate change and human activities, remain enigmatic, particularly across diverse vegetation zones. This research endeavors to unravel the dynamics of vegetation cover using the MOD13A1 Normalized Difference Vegetation Index (NDVI) dataset, delving into China's seven distinct vegetation zones (VZ1-VZ7). This research employs residual analysis, relative analysis, and geo-detector techniques to investigate the drivers of NDVI variation and spatial heterogeneity across China's seven distinct vegetation zones. The findings reveal a compelling upward trajectory in NDVI, predicted NDVI, and residual NDVI across China during the 2000–2021 period. Notably, significant and extremely significant increases are discernible in approximately 53.90%, 50.13%, and 23.29% of China's NDVI, respectively. Among the vegetation zones, VZ3 displays the highest change rates, yet the proportion with a significant increase in VZ1 surpasses other zones. The relative analysis underscores climate change as the predominant catalyst for vegetation enhancement, although an exception is noted in VZ3. Furthermore, the spatial heterogeneity of China's NDVI is primarily influenced by the interactions between land use types and relative humidity, sunshine duration, and precipitation, especially the interaction between relative humidity and land use types. Significant changes in climate can lead to marked alterations in the structure and function of terrestrial ecosystems, while changes in land use patterns at the regional level also alter the type of land cover, which together exert a significant impact on the vegetation NDVI. These results accentuate the importance of formulating tailored ecosystem management strategies tailored to the distinct characteristics of each vegetation zone to ensure the sustainable development of terrestrial ecosystems across China.

Distinguishing the effects of climate change and vegetation greening on soil moisture variability along aridity gradient in the drylands of northern China

Drylands are particularly sensitive to climate change, and soil water availability is critical for dryland ecosystems. Climate change and large-scale ecological restoration have led to significant vegetation greening and soil moisture (SM) variations in the drylands. However, the influencing mechanisms of climate change and vegetation greening on SM variability were not well understood. In this study, the spatiotemporal variations of climate variables, vegetation cover, surface SM (SM_surf) and root-zone SM (SM_root) along aridity gradient in the drylands of northern China during 1981–2018 were investigated. The random forest model and partial least-squares structural equation modelling (PLS-SEM) analysis were employed to quantify the contributions of climate change and vegetation greening to SM variability and identify the influencing pathways. The climate change showed temporal trends of wetting to drying before 2000 and drying to more wetting in 2000–2018, and vegetation greening was significant in 2000–2018. The variations of SM displayed obvious east-negative and west-positive trends. The temporal trend of SM deficit decreased during 1981–2018 in most regions, and SM showed a significant increasing trend in all regions of different aridity gradient after 2000. The correlations of climate factors and vegetation cover with SM became stronger in the area with lower aridity. The vegetation greening-induced SM change was limited compared to climate change. The climate factors can directly impact SM availability, and also indirectly influence SM availability through vegetation (e.g., precipitation→LAI→SM_surf). The SM_surf had positive responses to vegetation greening, especially in semiarid subarea. In contrast, vegetation greening exacerbated SM_root consumption in semiarid and dry subhumid subareas, which became intensive after 2000. This study fills the knowledge gap in the underlying reasons for the variations of both surface and root zone SM in water-limited areas and reveals the potential risks of SM depletion, particularly in dry subhumid areas.

Spatiotemporal Variation of Fractional Vegetation Cover and Its Response to Climate Change and Topography Characteristics in Shaanxi Province, China

Since the beginning of the 21st century in Shaanxi Province, China, ecological restoration has increased fractional vegetation cover (FVC) and decreased soil and water erosion. The climate and topography will be critical factors for maintaining vegetation coverage in the future. Based on the moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data, we monitored FVC variations in Shaanxi Province, China, as well as in three subregions of the Loess Plateau (LOP), Qinling–Bashan Mountain (QBM), and Guanzhong Plain (GZP). Using Sen+Mann–Kendall, correlation analysis, and geodetector methods, we detected trends and responses to climate change and topographical characteristics in Shaanxi Province from 2000 to 2018. The results indicated that 73.86% of the area in Shaanxi Province exhibited an increasing FVC with a growth rate of 0.0026 year−1 from 2000 to 2018. The FVC in the three subregions varied, as QBM (87.24–91.47%) &gt; GZP (47.45–66.93%) &gt; LOP (36.33–49.74%), which displayed a significant increase, slight increase, and slight decrease, respectively. The variation of FVC was significantly positively correlated with climate factors (precipitation, temperature, sunshine duration) at monthly and seasonal scales. The time-lag duration between FVC and climate factors was 1–3 months except for the conjunctional areas of GZP with the LOP and QBM, which exhibited a time-lag of 5–6 months. Topographically, the landform of hills had the highest FVC increase at an altitude of 500–1500 m and a slope of 2°–6°. The dominant driving factors affecting FVC variation in Shaanxi Province and LOP area were climatic factors. In the QBM area, the dominant factors were related to topography (relief, elevation, slope), whereas in the GZP area, they were relief and sunshine duration. We can conclude that local topography characteristics are important in implementing revegetation projects because they strongly influence water, temperature, and sunshine redistribution.

Climate change and carnivores: shifts in the distribution and effectiveness of protected areas in the Amazon.

Carnivore mammals are animals vulnerable to human interference, such as climate change and deforestation. Their distribution and persistence are affected by such impacts, mainly in tropical regions such as the Amazon. Due to the importance of carnivores in the maintenance and functioning of the ecosystem, they are extremely important animals for conservation. We evaluated the impact of climate change on the geographic distribution of carnivores in the Amazon using Species Distribution Models (SDMs). Do we seek to answer the following questions: (1) What is the effect of climate change on the distribution of carnivores in the Amazon? (2) Will carnivore species lose or gain representation within the Protected Areas (PAs) of the Amazon in the future? We evaluated the distribution area of 16 species of carnivores mammals in the Amazon, based on two future climate scenarios (RCP 4.5 and RCP 8.5) for the year 2070. For the construction of the SDMs we used bioclimatic and vegetation cover variables (land type). Based on these models, we calculated the area loss and climate suitability of the species, as well as the effectiveness of the protected areas inserted in the Amazon. We estimated the effectiveness of PAs on the individual persistence of carnivores in the future, for this, we used the SDMs to perform the gap analysis. Finally, we analyze the effectiveness of PAs in protecting taxonomic richness in future scenarios. The SDMs showed satisfactory predictive performance, with Jaccard values above 0.85 and AUC above 0.91 for all species. In the present and for the future climate scenarios, we observe a reduction of potencial distribution in both future scenarios (RCP4.5 and RCP8.5), where five species will be negatively affected by climate change in the RCP 4.5 future scenario and eight in the RCP 8.5 scenario. The remaining species stay stable in terms of total area. All species in the study showed a loss of climatic suitability. Some species lost almost all climatic suitability in the RCP 8.5 scenario. According to the GAP analysis, all species are protected within the PAs both in the current scenario and in both future climate scenarios. From the null models, we found that in all climate scenarios, the PAs are not efficient in protecting species richness.

Spatial and Temporal Variation in Vegetation Cover and Its Response to Topography in the Selinco Region of the Qinghai-Tibet Plateau

In recent years, the vegetation cover in the Selinco region of the Qinghai-Tibet Plateau has undergone significant changes due to the influence of global warming and intensified human activity. Consequently, comprehending the distribution and change patterns of vegetation in this area has become a crucial scientific concern. To address this concern, the present study employed MODIS-NDVI and elevation data, integrating methodologies such as trend analysis, Hurst exponent analysis, and sequential cluster analysis to explore vegetation cover changes over the past 21 years and predict future trends, while examining their correlation with topographic factors. The study findings indicate a fluctuating upward trend in vegetation cover, with a notable decrease in 2015. Spatially, the overall fractional vegetation cover (FVC) in the study area showed a basic stability with a percentage of 78%. The analysis of future trends in vegetation cover revealed that the majority of areas (68.26%) exhibited an uncertain trend, followed by stable regions at 15.78%. The proportion of areas showing an increase and decrease in vegetation cover accounted for only 9.63% and 5.61%, respectively. Elevation and slope significantly influence vegetation cover, with a trend of decreasing vegetation cover as elevation increases, followed by an increase, and then another decrease. Likewise, as the slope increases, initially, there is a rise in vegetation cover, followed by a subsequent decline. Notably, significant abrupt changes in vegetation cover are observed within the 4800 m elevation band and the 4° slope band in the Selinco region. Moreover, aspect has no significant effect on vegetation cover. These findings offer comprehensive insights into the spatial and temporal variations of vegetation cover in the Selinco region and their association with topographic factors, thus serving as a crucial reference for future research.

Contributions of natural and anthropogenic factors to historical changes in vegetation cover and its future projections in the Yellow River basin, China

AbstractThe fragile ecology of the Yellow River basin (YRB) is vulnerable to global warming and human activities. As the second largest river in China, the YRB covers the subhumid, semi‐arid, arid and alpine climate zones, with considerably spatial differences in vegetation cover (VC), thus demonstrating substantial variations in response to climate change. In this study, characteristics of VC variations in different climate zones of the YRB during 1982–2019 were analysed, impacts of climate change and human activities on VC variations were identified, and possible VC variations in the future were projected under different climate scenarios. Results show that NDVI in the YRB significantly increased at a rate of 2.3 × 10−3 year−1 from 1982 to 2019, especially in the middle reaches of the YRB. Temperature is the main driver of VC variations in the source region of the YRB (alpine zone), wherein the warming trend contributes to the greening. The internal variability of VC is also influenced by temperature, with a marginal effect of precipitation minus evaporation (P − E). In the middle and lower reaches of the YRB consisting of arid, semi‐arid, and subhumid zones, VC benefited only from the warming trend and had a less relationship with the internal variability of temperature, whereas the internal variability of VC was influenced by P − E and had a weaker relationship with the P − E trend. Contributions of climate change to VC variations in the source region and middle and lower reaches of the YRB are approximately 62%, 42%, and 27%, respectively. Human activities considerably impact the ecological environment but mostly play a positive role. In the future, VC will increase in the YRB, especially under the SSP5‐8.5 scenario, and VC reveals the most prominent changes in the lower reaches. This study suggests that climate change might be favourable to VC in YRB, and emphasizes that human activities should adapt to climate change in an orderly manner.

InSAR-based method for deformation monitoring of landslide source area in Baihetan reservoir, China

As a cascading disaster, the surge caused by the reservoir bank landslide seriously affects the stability of the reservoir bank and the dam body. In addition, large-scale hydropower projects are usually built in mountain and canyon areas with active geological structure movement, which provides rich material sources for the occurrence of landslides, so it is of great significance to monitor the deformation in the landslide source area of the reservoir. As science and technology have been leaping forward, a wide variety of high and novel technologies have been proposed, which can be adopted to monitor landslide deformation. It is noteworthy that InSAR is capable of monitoring target monitoring areas all time under all weathers without the need to install any equipment. In this study, the time series deformation of the main landslide source area of the Baihetan reservoir after water storage was determined based on the time series InSAR method. The average annual deformation rate of the landslide source area of the Baihetan reservoir from April 2021 to January 2023 was determined by combining the Sentinel-1 SAR data of 55 ascending tracks and 46 descending tracks. Moreover, the vegetation cover variations from April 2021 to January 2023 in the study area were determined by combining the remote sensing data of Landsat8-9. A total of four typical source areas were selected based on the field investigation to analyze the deformation monitoring results and the vegetation cover variations. As indicated by the results: 1) After water storage, the slope deformation in all source areas was larger in the short term, and the deformation rate of the lower part turned out to be more significant, and the deformation rate exceeded 334.583 mm/year. 2) On the steep slope, the effect of different types of vegetation on restraining deformation was different. The optimal effect was reported in shrubs, followed by grasslands, and the worst effect was reported in woodlands. The results of this study can provide scientific support for the prevention and control of regional geological disasters.

Structure and stability characteristics of zonal soil aggregates in the Three Rivers Source of the Qinghai‐Tibetan Plateau

AbstractThis study aimed to explore the structure and stability characteristics of zonal soil aggregates in cold high‐altitude regions and reveal the variation patterns of alpine soil aggregates, using the Three Rivers Source of the Qinghai‐Tibetan Plateau as an example. Zonal soils representing the local vegetation types (alpine meadow soil, alpine grassland soil) were collected, and soil aggregates were separated using wet and dry sieving methods. Random forest modeling was used with climate data from 2011 to 2019 as variables in order to generate multifactor digital maps of water‐stable and mechanically stable aggregates. The composition and differences of zone‐specific soil aggregates were compared and analyzed using the evaluation indices of macroaggregate content (R &gt; 0.25), mean weight diameter (MWD), geometric mean diameter, and fractal dimensions. Their controlling factors were also explored. The study results showed that the model's explanatory power for soil aggregates was over 68%. In the random forest model, elevation and sunshine duration contributed more to soil water‐stable aggregates, whereas precipitation contributed more to soil mechanically stable aggregates. The content of large aggregates with particle size greater than 0.5 mm was higher in alpine meadow soils than in alpine grassland soils. In contrast, the content of large aggregates with particle size less than 0.5 mm was lower than that of alpine grassland soils. There are also some differences in the distribution of water‐stable aggregates and mechanically stable aggregates between alpine meadow soils and alpine grassland soils in each particle size, and these differences are most pronounced in the particle sizes &gt;2 and &lt;0.25 mm. In addition, the stability of alpine meadow soil aggregates is higher than that of alpine grassland soil aggregates. Finally, the mapping results show that the stability of soil aggregates in the study area has similar zonal characteristics to the zonal variation of vegetation cover and climate and other factors.

Spatial and temporal variations of vegetation cover and its influencing factors in Shandong Province based on GEE.

Economic development has rapidly progressed since the implementation of reform and opening up policies, posing significant challenges to sustainable development, especially to vegetation, which plays a crucial role in maintaining ecosystem service functions and promoting green low-carbon transformations. In this study, we estimated the fractional vegetation cover (FVC) in Shandong Province from 2000 to 2020 using the Google Earth Engine (GEE) platform. The spatial and temporal changes in FVC were analyzed using gravity center migration analysis, trend analysis, and geographic detector, and the vegetation changes of different land use types were analyzed to reveal the internal driving mechanism of FVC changes. Our results indicate that vegetation cover in Shandong Province was in good condition during the period 2000 to 2020. The high vegetation cover classes dominated, and overall changes were relatively small, with the center of gravity of vegetation cover generally shifting towards the southwest. Land use type, soil type, population density, and GDP factors had the most significant impact on vegetation cover change in Shandong Province. The interaction of these factors enhanced the effect on vegetation cover change, with land use type and soil type having the highest degree of influence. The observational results of this study can provide data support for the policy makers to formulate new ecological restoration strategies, and the findings would help facilitate the sustainability management of regional ecosystem and natural resource planning.

Variations of Runoff-Sediment Processes at Flood Event Scale at a Typical Catchment in the Loess Plateau of China

The flood season is the main period for runoff and sediment yield, and understanding the variations of runoff and sediment of flood events is of great significance for distinguishing the runoff-sediment processes in the Loess Plateau. In this study, we analyzed the variations of runoff and sediment at the flood event scale in the Qiaogou catchment and investigated the influencing factors. The results showed that runoff and sediment of flood events were mainly produced by rainfall with short rainfall duration and heavy rainfall intensity in the study area. Based on the 28 flood events and corresponding precipitation data from the reference period (P-I, 1986–1989) and the revegetation period (P-II, 2001–2009), we analyzed the variations of runoff-sediment processes at the flood event scale in the Qiaogou catchment, a typical catchment of the Loess Plateau. The results showed that the flood variables were lower in the revegetation period than those in the reference period, except for the flood peak discharge time and the flood duration. The sediment transport capacity per unit runoff depth in the revegetation period was weaker than that in the reference period. The hysteresis analysis indicated that the patterns of the hysteretic loop were dominated by the figure-of-eight pattern and the compound pattern, respectively, in the reference period and revegetation period. Compared to the reference period, runoff and sediment-related variables for flood events of counter-clockwise, figure-of-eight, and compound patterns were less in the revegetation period. With similar rainfall conditions, the main reason for the noticeable difference in runoff and sediment of flood events for the two periods was the variations in vegetation cover. The mentioned results indicated that revegetation performed a critical function in the variations of runoff and sediment at the flood event scale. This study revealed the variations of runoff-sediment processes of flood events and their responses to rainfall and revegetation in a typical catchment of the Loess Plateau, which can provide a basis for decision-making on soil erosion management and sustainable development of the ecological environment in the Loess Plateau.

NDVI-based spatial and temporal vegetation trends and their response to precipitation and temperature changes in the Mu Us Desert from 2000 to 2019.

This paper explores the relationship between normalized vegetation index (NDVI) response to precipitation and temperature conditions by analyzing the spatial and temporal variation of vegetation cover (NDVI) in Mu Us Desert during 2000-2019. MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Maximum Value Composites (MVC) is an internationally used statistical method for NDVI data. Based on MODIS remote sensing data, the NDVI of Mu Us Desert sandy land from 2000 to 2019 was analyzed by using the linear regression slope method. In 2000-2010 and 2010-2019, there was a difference in the change rate of vegetation index in Mu Us Desert, with the average slope of 0.0650/10a for the former and 0.0782/10a for the latter. The trends of NDVI values in the study area during 2000-2019 were roughly the same as those of precipitation, and slightly different from those of temperature, but the overall correlation between NDVI values and both was good. There is a significant positive correlation between NDVI and annual precipitation (0.687), and a weak correlation with temperature (0.264). The vegetation growth in Mu Us Desert is affected by both precipitation and temperature.

Environmental determinants of vegetation in the drawdown zones of a Columbia River Treaty reservoir: a template for ecosystem enhancement.

Water storage reservoirs alternately inundate and expose the drawdown zones, limiting riparian vegetation that provides wildlife habitats and contributes to the aquatic food-web. To characterize plant distributions and hydrogeomorphic associations, we inventoried quadrats in transects extending from the full-pool (FP) margin, downwards 12 m through the drawdown zones at sites around the Duncan Reservoir in British Columbia, Canada. Among the 69 plant species, black cottonwoods (Populus trichocarpa), willows (primarily Salix sitchensis) and other trees and shrubs occurred sparsely, rarely extending below 2 m below FP. Perennial herbaceous plants, especially horsetail (Equisetum arvense) and sedges (primarily Carex utriculata), were most common, extending down ~5 m below FP, and ruderal annual plants occurred sparsely at greater depths. Vegetation Cover and Species Richness were correlated with environmental factors, with (1) Elevation being highly influential, reflecting inundation duration and depth. (2) Position, longitudinal location, reflected greater vegetation diversity downstream of the reservoir. (3) Finer Substrate texture was favorable to retain moisture, but coarse sediments would resist erosion. (4) Shallow Slope was favorable to reduce drainage and included finer sediments. (5) Distance from the FP shoreline could reflect seed source proximity. Stepwise linear modeling with combined environmental factors accounted for ~30% of the variation in Vegetation Cover and Richness, and Canonical Correspondence Analysis revealed plant groupings relative to the environmental influences. At this and other storage reservoirs, regimes that reduce the frequency and duration of inundation could promote vegetation in locations with suitable environmental conditions in the upper drawdown zones, thus providing ecosystem enhancement.

Sensitivity of Grassland Coverage to Climate across Environmental Gradients on the Qinghai-Tibet Plateau

Grassland cover is strongly influenced by climate change. The response of grassland cover to climate change becomes complex with background climate. There have been some advances in research on the sensitivity of grassland vegetation to climate change around the world, but the differences in climate sensitivity among grassland types are still unclear in alpine grassland. Therefore, we applied MODIS NDVI data and trend analysis methods to quantify the spatial and temporal variation of grassland vegetation cover on the Qinghai-Tibet Plateau. Then, we used multiple regression models to analyze the sensitivity of fractional vegetation cover (FVC) to climatic factors (Temperature, Precipitation, Solar radiation, Palmer drought severity index) and summarized the potential mechanisms of vegetation sensitivity to different climatic gradients. Our results showed (1) a significant increasing trend in alpine desert FVC from 2000–2018 (1.12 × 10−3/a, R2 = 0.56, p &lt; 0.001) but no significant trend in other grassland types. (2) FVC sensitivity to climatic factors varied among grassland types, especially in the alpine desert, which had over 60% of the area with positive sensitivity to temperature, precipitation and PDSI. (3) The sensitivity of grassland FVC to heat factors decreases with rising ambient temperature while the sensitivity to moisture increases. Similarly, the sensitivity to moisture decreases while the sensitivity to thermal factors increases along the moisture gradient. Furthermore, the results suggest that future climate warming will promote grassland in cold and wet areas of the Qinghai-Tibet Plateau and may suppress vegetation in warmer areas. In contrast, the response of the alpine desert to future climate is more stable. Studying the impact of climate variation at a regional scale could enhance the adaptability of vegetation in future global climates.