Trends In Vegetation Cover Research Articles

The Impact of Drought on Vegetation at Basin Scale: A Case Study of the Wei River Basin, China

Droughts in the Weihe River Basin are occurring more frequently and are becoming more intense. These events negatively affect industrial production, economic development, and ecosystems. Studying how vegetation changes in response to them is of practical significance. We report temporal and spatial trends in vegetation cover, use a copula function to analyze relationships between drought and vegetation cover, and assess the probability of vegetation loss in different drought scenarios. A vegetation index trends upwards from north to south in this basin; from 2001 to 2017, vegetation cover also trends upward in most areas, although it decreases in areas with high vegetation cover. An escalated susceptibility to drought has been observed in the southern and eastern sectors, where proximity to the riverbank correlates with heightened drought sensitivity, particularly in zones of intensified vegetation density. The probability of vegetation loss at the same vegetation loss preset point gradually increases with increased drought severity. These results will facilitate the formulation of countermeasures to prevent and combat the effects of drought on vegetation and land management.

The Environmental Legal Framework of Mexican Caribbean Dunes: A Retrospective Case Study of Vegetation and Coastal Dune Loss in the Sian Ka’an Biosphere Reserve

The Mexican Caribbean coastal dune is protected by national and international environmental legislation. However, through permits, concessions and authorizations for changes in land use, the coastal dune has been fragmented or suppressed, mainly for touristic activities, causing a decline in protective and ecological ecosystem services. In this study, we evaluated the strength and weakness of Mexican legislation to protect the Caribbean coastal dune ecosystem and estimated the historical and current effects on coastal dune vegetation and dune geomorphology, associated with legal allowances of land use change in the Sian Ka’an Biosphere Reserve (SKBR). Legislation at the federal, state and local level were critically reviewed, and with remote sensing techniques and the Remotely Piloted Aircraft System (RPAS), we conducted a case study in the SKBR to estimate coastal dune vegetation alteration trends during the period 2011–2020 and modifications on the dune geomorphology associated with land use change allowances. At the federal (four laws), state (eight laws) and local (nine Local and Territorial Planning Programs (POEL and POET) levels, we found a lack of consensus and alignment between regulations, starting with a lack of definition of ecosystems subject to protection. For coastal dunes, none of them consider topography, ecological function and a way to identify it in the field, making the surveillance highly complex and favoring land use changes, the removal of vegetation and dune geomorphology alteration. Remote sensing techniques showed that areas with land use authorizations exhibit negative vegetation cover trends (Mann–Kendall <−0.4), indicating a decline in vegetation cover density that is mostly anthropogenically induced. The RPAS analysis demonstrated drastic alterations to complete elimination of the coastal dune geomorphology in areas with land use change. In the Mexican Caribbean, the loss of coastal dune and associated ecosystem by the lack of congruent legislation threatens the environmental stability of the coastal areas.

Interplay of Environmental Shifts and Anthropogenic Factors with Vegetation Dynamics in the Ulan Buh Desert over the Past Three Decades

In arid and semiarid regions, vegetation provides essential ecosystem services, especially retarding the desertification process. Vegetation assessment through remote sensing data is crucial in understanding ecosystem responses to climatic factors and large-scale human activities. This study analyzed vegetation cover changes in the Ulan Buh Desert from 1989 to 2019, focusing on the impacts of human activities and key meteorological factors. The results showed that both climatic and human activities contributed to an increasing trend in vegetation cover (normalized difference vegetation index (NDVI)) over the 30-year period. Temperature and precipitation significantly affected the NDVI in the desert, with temperature having a more substantial influence. The combined impact of average temperature and precipitation on the NDVI was notable. Human activities and meteorological factors caused the vegetation restoration area in the desert to be approximately 35% from 1989 to 2019. Human activities were the primary influencers, responsible for about 60% of vegetation restoration across the study area. Especially from 2004 to 2019, the conversion to farmland driven by human activities dominated the region’s NDVI increase. The research underscores the importance of considering both climatic and human factors in understanding and managing ecosystem dynamics in arid areas like the Ulan Buh Desert. By integrating these factors, policymakers and land managers can develop more effective strategies for sustainable ecosystem management and combating desertification.

Analysis of Spatiotemporal Evolution and Driving Forces of Vegetation from 2001 to 2020: A Case Study of Shandong Province, China

As global climate change intensifies and human activities escalate, changes in vegetation cover, an important ecological indicator, hold significant implications for ecosystem protection and management. Shandong Province, a critical agricultural and economic zone in China, experiences vegetation changes that crucially affect regional climate regulation and biodiversity conservation. This study employed normalized difference vegetation index (NDVI) data, combined with climatic, topographic, and anthropogenic activity data, utilizing trend analysis methods, partial correlation analysis, and Geodetector to comprehensively analyze the spatiotemporal variations and primary driving factors of vegetation cover in Shandong Province from 2001 to 2020.The findings indicate an overall upward trend in vegetation cover, particularly in areas with concentrated human activities. Climatic factors, such as precipitation and temperature, exhibit a positive correlation with vegetation growth, while land use changes emerge as one of the key drivers influencing vegetation dynamics. Additionally, topography also impacts the spatial distribution of vegetation to a certain extent. This research provides a scientific basis for ecological protection and land management in Shandong Province and similar regions, supporting the formulation of effective vegetation restoration and ecological conservation strategies.

Monitoring vegetation cover trends in the steppe region of western Algeria using MODIS imagery

The steppe region of Chehaima (Tiaret Province, northwestern Algeria) covers an area of 2,202 km², representing 10.94% of the total area of Tiaret. This study identified the ecological state of the area using a spatial theme from a 24-year synchronized moderate-resolution imaging spectroradiometer (MODIS) satellite image campaign (2000–2023). The adopted method consists of analyzing spectral indices (normalized difference vegetative index, low surface temperature (LST), and soil moisture index) from MODIS sensors (MOD13Q1), making it possible to evaluate the spatiotemporal dynamics of the vegetation in the study area and to identify regions degraded by several biotic and abiotic factors. The results show a vegetation cover rate of intense fluctuations in unfavorable conditions over 24 years. The percentage of plant growth recorded does not exceed 32%. The abundance of LST vegetation decreases when the LST exceeds 35°C, with a soil that has a water deficit. The De Martonne aridity index (<em>I</em>) classifies the study area as a lower semiarid bioclimatic zone. These indicators made it possible to determine the spatiotemporal dynamics of vegetation, which modifies the plant cover, leading to the loss of native species such as alfa <em>Stipa tenacissima</em> L. Defensive measures are necessary over large areas of the study area to allow successful protection of steppe rangelands through a sustainable conservation strategy, preserving endemic species, stabilizing dunes, and adopting the steppe rotation system.

Population regeneration of two Haloxylon species in central Asian deserts as affected by groundwater depth

Haloxylon ammodendron and Haloxylon persicum are the dominant species in the deserts of Central Asia. As groundwater exploration has resulted in a decline in groundwater depth in this region, the impact on the regeneration of these two Haloxylon populations calls for urgent attention. Therefore, we conducted an intensive vegetation survey, including population density, age structure and seed production and seed characteristics, along a groundwater depth gradient in the Gurbantunggut Desert of Central Asia. The result shows that for H. ammodendron, groundwater depth of 15 m is its survival and regeneration limit, beyond which this species cannot grow. However, for H. persicum, this limit does not apply. Instead, declined groundwater depth promotes a reproduction strategy with low seed quantity, high quality, and a high germination rate for H. ammodendron. Ultimately, H. ammodendron exhibits a tighter regeneration trait coordination, with a reasonable age structure being crucial for its population continuation and environmental adaptation. In contrast, H. persicum demonstrates higher resource acquisition and reproductive ability, along with tolerance to groundwater depth decline. In conclusion, if the groundwater depth decline continues, the continuation of H. ammodendron will be seriously threatened but H. persicum will not be. This study is beneficial for evaluating the future trend of vegetation cover in desert region and planning water resources management in Central Asia.

Analysis of Vegetation Environmental Stress and the Lag Effect in Countries along the “Six Economic Corridors”

Climate conditions have a significant impact on the growth of vegetation in terrestrial ecosystems, and the response of vegetation to climate shows different lag effects with the change in spatial pattern and category of the ecosystem. Exploring the interaction mechanism between climate and vegetation growth is helpful to promote the sustainable development of the regional ecological environment. Using normalized vegetation index (NDVI) and meteorological data, based on univariate linear regression and partial correlation analysis, this study explores the temporal and spatial pattern and change trend of vegetation cover in regions and node cities along the “six economic corridors”, and analyzes the environmental stress of vegetation growth and the lag effect of climate response. This study shows that there are great differences in the overall vegetation coverage along the “six economic corridors”. The vegetation coverage in Southeast Asia is the best and that in central and West Asia is the worst. The vegetation coverage in the study area shows an improvement trend, accounting for 39.6% of the total area. There are significant differences in the lag effect of vegetation response and the main climate factors affecting vegetation growth, which is related to the diversity of vegetation and climate characteristics. In this study, we selected regions along the “six economic corridors” that exhibit large latitude and altitude gradients, diverse climate types, and significant seasonal changes and spatial differences in climate conditions as our research areas. Additionally, we considered the impact of different regions and various types of vegetation on their response to climate change. This is of great significance for gaining a deeper understanding of the response mechanism of global climate change and vegetation ecology. Furthermore, our research can provide valuable information to support the ecological environment protection of different typical vegetation against extreme climates, ultimately contributing to the sustainable development of “the Belt and Road”.

Trend analysis of MODIS NDVI time series and its relationship to temperature and precipitation in Northeastern of Iran.

Vegetation plays a crucial role in providing organic matter and regulating energy exchange on the Earth's surface. This study investigates the changes in vegetation cover, temperature, and precipitation in northeastern Iran during 2001-2020. MODIS-NDVI time series data and climatic data from 11 synoptic stations were utilized. The nonparametric Mann-Kendall method was employed to detect trends in vegetation cover and climatic variables. Additionally, the correlation between climatic parameters and vegetation was examined. Trend analysis revealed significant increases/decreases in vegetation cover in 32%/26% of the region, respectively. The increasing trend in vegetation cover was predominantly observed in highlands, suggesting that a warmer climate has enhanced the living conditions for plants in these regions. The vegetation trend map indicates an expansion of vegetation cover in the northern and central parts of Iran during the past 20years, whereas the southern and eastern portions experienced declines. The relationship between vegetation and elevation revealed that vegetation increased above 1,850m and decreased below 850m. Trend analysis showed no significant trend in precipitation data since the beginning of the twenty-first century, but an increasing trend in temperature was observed in 82% of the region's area, excluding the western strip. Correlation coefficients between temperature, precipitation, and vegetation indicated that declining temperatures are the limiting factors for vegetation in the highlands, while in lowland areas, the decrease in precipitation significantly diminishes vegetation growth.

Identification of hydrologically homogenous watersheds and climate-vegetation dynamics in the Blue Nile Basin of Ethiopia

Abstract Identification of hydrologically homogenous watersheds in the Upper Blue Nile Basin of Ethiopia is challenging due to the large number of watersheds and the lack of consistent and reliable data. Traditional methods, such as expert-based classification, are time-consuming, subjective, and often not reproducible. Therefore, this study aims to identify homogenous gauged watersheds using hydrometeorological and remote sensing data. In this study 76 watersheds were delineated from a 30-m digital elevation model (SRTM-DEM). Twelve watershed characteristics were selected to aid the classification process. Three homogenous climate regions were identified using rainfall data from 42 stations, and for each homogeneous climate region, gauged watersheds were identified. Principal component analysis (PCA) and K-means clustering were used for classification. The PCA reduced 12 watershed characteristics into three principal components using a threshold of 80% accounted variance and eigenvalues greater than one. K-means clustering classified the 76 watersheds into nine homogenous clusters. In the classified regions, vegetation dynamics within three decades have also been analyzed. This helped identify trends in vegetation cover and its spatial and temporal dynamics. The results of the investigation will potentially be used for runoff prediction of ungauged watersheds and for water resource management models in the future.

NDVI-Based Assessment of Vegetation Cover in Koronadal City Using GIS and Remote Sensing

Over the years, vegetation in cities has been affecting the climate in the valley. A method called Normalized Difference Vegetation Index (NDVI) Assessment combined with Remote Sensing through satellite images is an innovative way to track the changes in vegetation cover in these areas. This study sought to examine alterations in vegetation regions within the Koronadal valley by employing the Normalized Difference Vegetation Index (NDVI) for analysis. The research design involved quantitative descriptive research, utilizing numerical data from NDVI analysis as the foundation for predicting vegetation cover trends over the next decade through linear regression. It also utilized satellite imagery from platforms like Landsat 7, 8, and 9. The results revealed a substantial increase in vegetation cover from (183.41 ± 46.53) km² to (230.73 ± 16.82) km² within Koronadal City between 2003 and 2023. Statistical analysis indicates a significant positive trend in vegetation area expansion over the specified timeframe with a regression (R) value of 0.97. Through NDVI analysis using the QGIS software, the visual diagrams show the increase in vegetation cover, illustrating a consistent rise over decades, emphasizing the government's demonstrated environmental conservation methods. The linear regression indicates a sustained increase in vegetation cover in Koronadal over the next decade. The rise in vegetation cover underscores the successful environmental preservation efforts and highlights the city's growing environmental resilience, emphasizing the need for sustainable land management practices in addressing environmental challenges.

A case study about the forest fire occurred on 05 July 2021 over Khenchela province, Algeria, using space-borne remote sensing

In this study, space-borne remote sensing (Landsat-8, MODIS) was employed to evaluate the effects of forest fires occurring on 05 July 2021, over Khenchela province, Algeria. Our objective is to understand the severity of damage caused by the fire and its implications for vegetation and land cover. Utilizing the Normalized Difference Vegetation Index (NDVI) from MODIS data and Landsat-8 imagery, we report changes in vegetation health and land cover. To identify areas affected by forest fires and evaluate the severity of damage, the Normalized Burn Ratio (NBR) and Differenced Normalized Burn Ratio (dNBR) were calculated. Analysis showed that −1825.11 ha (1.21%) of the total area experienced severe burns, 3843.54 ha (2.54%) moderate to high severity burns, 3927.97 ha (2.59%) moderate to low severity burns and 9864.45 ha (6.51%) low severity burns. The area covered by vegetation decreased from 2014 to 2021, indicating a negative trend in vegetation cover over the study period.

Spatial and temporal variation in normalized difference vegetation index of vegetation in Liaoning Province from the perspective of ecogeographic zoning

Normalized difference vegetation index (NDVI) is an important indicator reflecting vegetation cover and growth status. It is of significance for regional ecological conservation and natural resource management to investigate its spatial and temporal variation trends and response to ecological factors. We divided Liaoning Province into three ecological geographical regions, including northwest agro-pastoral zone, central agricultural zone, and eastern agroforestry zone. Based on remote sensing, vegetation, climate, topography and human activities, we used trend analysis and geographic probe model to examine the spatial and temporal trends of NDVI in Liaoning Province, and analyzed the intensity and interaction mechanism of each driver on the spatial distribution pattern of NDVI. The results showed that the annual average NDVI in Liaoning Province from 2001 to 2020 was 0-0.92, showing a distribution pattern of high in the east and low in the west, high in the inland and low in the coastal land. The overall trend of vegetation cover was increasing, and the NDVI increasing areas were mainly concentrated in the northwest agro-pastoral zone and the eastern agroforestry zone, the NDVI reduction areas were mainly concentrated at the border between the central agricultural zone and the eastern agroforestry zone, as well as in the coastal area of the eastern agroforestry zone. The annual average NDVI change varied among the three ecological-geographic zones. The NDVI of the northwest agro-pastoral zone from 2001 to 2020 were generally low, but showed a fluctuating trend of slow increase. The NDVI of the eastern agroforestry zone was high overall, and the interannual variation of NDVI was generally stable. The distribution of high and low NDVI in the central agricultural zone was staggered, and the interannual variation of NDVI showed a decreasing trend. Natural factors were the key drivers of NDVI changes in the three ecogeographic zones, with cumulative temperature and precipitation having the greatest influence. The interactions between the factors were all mutually and nonlinearly enhanced.

Vegetation cover change and its response to climate extremes in the Yellow River Basin

Extreme climate events have increased in frequency and severity under the background of climate change, with vegetation growth exhibiting a sensitive response to them. By assimilating GIMMS NDVI and MODIS NDVI using the Residual Network, we obtained a long time series and high resolution NDVI dataset of the Yellow River Basin (YRB). The dataset was utilized for examining the spatiotemporal variability of NDVI and analyzing the response of vegetation cover to climate extremes with meteorological data. Our findings reveal the following: (1) A significant rise in NDVI was seen in the YRB, displaying a mean growth rate of 0.019/10a (p < 0.001). However, seasonal differences exist. The mean NDVI of multi-year declines from southeast to northwest, while the overall trend of vegetation cover improves. (2) The NDVI response to extreme temperature exhibits noticeable spatiotemporal differences. Daytime extreme high temperature in the northern YRB is negatively correlated with NDVI, while they are positively correlated in the lower YRB and the southern part of the middle YRB. Nighttime extreme high temperature exhibits a positive correlation with NDVI. Overall, NDVI displays a stronger response to extreme precipitation than to extreme temperature, with a negative correlation with CWD and a positive correlation with PRCPTOT. (3) The NDVI demonstrates a lagged response to climate extremes in the YRB, with a greater lag in response to extreme temperature than extreme precipitation. The research findings can provide scientific support for the future management and planning of vegetation in the YRB, as well as contribute to the promotion of ecological environment regulation and sustainable development.

Vegetation EVI changes and response to natural factors and human activities based on geographically and temporally weighted regression

The research on vegetation changes plays a crucial role in the assessment of ecosystem health, monitoring environmental changes, providing early warnings for natural disasters, and supporting decision-making for sustainable development. However, understanding the nonstationary characteristics of drivers affecting vegetation change remains challenging. This study used Enhanced Vegetation Index (EVI) data obtained through Google Earth Engine (GEE), Theil-Sen, and Mann-Kendall methods to analyze the spatial-temporal patterns and trends of vegetation changes in Sichuan, western China from 2000 to 2020. The Geographical and Temporal Weighted Regression (GTWR) method was applied to deal with spatial and temporal nonstationarity simultaneously. Results showed that vegetation cover in Sichuan was good overall, with medium and high vegetation covering more than 78% of the area. About 72.75% of the area showed an increasing trend in vegetation cover, and areas with extremely significant and significant EVI growth (p < 0.01 and 0.01 ≤ p < 0.05) accounted for 23.94% of the total area. The areas with significant increases in vegetation EVI were mainly distributed in northeast, east, southeast, central, and southwest in Sichuan, while the areas with significant decreases were mainly distributed in the central Sichuan plain urban agglomeration and western Sichuan plateau. GTWR addressed the nonstationary effect of the temporal dimension on the drivers of natural and human activities, with a fitted R2 of 0.846. The study identified climate, terrain, and human activities as the primary driving factors behind vegetation EVI fluctuations. Annual average temperature and precipitation, human activities, and slope had a positive impact on vegetation EVI changes, while solar radiation and aspect had a negative inhibitory effect. The effects of climate, terrain, and human activities on EVI changes exhibited significant spatial heterogeneity and clustering, resulting in either positive promotion or negative inhibition. This study provides an additional methodology to solve the nonstationary problem of vegetation change trends and their response mechanisms. The revealed changes in vegetation EVI and the spatiotemporal heterogeneity characteristics of their driving factors are important for fragile ecosystems to adapt to and mitigate the effects of natural changes and human activities. Revealing the variations in vegetation EVI and their underlying drivers can showcase diverse characteristics across regions and time periods, the presence of spatiotemporal heterogeneity holds great significance in comprehending the adaptive strategies employed by fragile ecosystems to mitigate the effects of natural fluctuations and human-induced activities.

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.

Compositional shifts of alpine plant communities across the high Andes

AbstractAimClimate change is transforming mountain summit plant communities worldwide, but we know little about such changes in the High Andes. Understanding large‐scale patterns of vegetation changes across the Andes, and the factors driving these changes, is fundamental to predicting the effects of global warming. We assessed trends in vegetation cover, species richness (SR) and community‐level thermal niches (CTN) and tested whether they are explained by summits' climatic conditions and soil temperature trends.LocationHigh Andes.Time periodBetween 2011/2012 and 2017/2019.Major taxa studiedVascular plants.MethodsUsing permanent vegetation plots placed on 45 mountain summits and soil temperature loggers situated along a ~6800 km N‐S gradient, we measured species and their relative percentage cover and estimated CTN in two surveys (intervals between 5 and 8 years). We then estimated the annual rate of changes for the three variables and used generalized linear models to assess their relationship with annual precipitation, the minimum air temperatures of each summit and rates of change in the locally recorded soil temperatures.ResultsOver time, there was an average loss of vegetation cover (mean = −0.26%/yr), and a gain in SR across summits (mean = 0.38 species m2/yr), but most summits had significant increases in SR and vegetation cover. Changes in SR were positively related to minimum air temperature and soil temperature rate of change. Most plant communities experienced shifts in their composition by including greater abundances of species with broader thermal niches and higher optima. However, the measured changes in soil temperature did not explain the observed changes in CTN.Main conclusionsHigh Andean vegetation is changing in cover and SR and is shifting towards species with wider thermal niche breadths. The weak relationship with soil temperature trends could have resulted from the short study period that only marginally captures changes in vegetation through time.

Detection of goat herding impact on vegetation cover change using multi-season, multi-herd tracking and satellite imagery

The frequency and severity of Mediterranean forest fires are expected to worsen as climate change progresses, heightening the need to evaluate understory fuel management strategies as rigorously as possible. Prescribed small-ruminant foraging is considered a sustainable, cost-effective strategy, but demonstrating a link between animal presence and vegetation change is challenging. This study tested whether the effect of small-ruminant herd presence in Mediterranean woodlands can be detected by integrating remote sensing and herd tracking at the landscape scale. The daily foraging routes of seven shepherded goat herds that exploited a 100-km2 forested area of the Judean Hills, Israel, were tracked over six years using GPS (Global Positioning System) collars. Herd locations were converted to stocking rates, with units of animal-presence-days per unit area per defined time period, and mapped at a spatial resolution of 10 m. We estimated pixel-level vegetation cover change based on a time series of 63 monthly Landsat-8 images expressed as the normalized soil-adjusted vegetation index (SAVI). Spatiotemporal trend analysis assessed the magnitude and direction of change, and a random forest machine-learning algorithm estimated the relative impact on vegetation cover change of environmental factors as well as the herd-related factors of stocking rate that accrued over six years and distance to the closest corral. The last two factors were among the most influential factors determining vegetation cover change in the regional and individual-herd analyses. In some respects, the permanent herds differed in their spatial pattern of stocking rate from the mobile herds that periodically relocated their night corral throughout the year, but stocking rate scaled logarithmically for all herds individually and combined. The combination of multi-season GPS tracking, remote sensing, and machine-learning techniques, applied at a regional scale, detected herd impacts on vegetation cover trends, consistent with livestock foraging being an effective tool for fuel reduction in Mediterranean woodlands.

An evaluation of topsoil carbon storage in Chinese deserts

Deserts are important components of the terrestrial ecosystem, and significantly affect the terrestrial carbon cycle. However, their carbon storage is poorly understood. To evaluate the topsoil carbon storage in Chinese deserts, we systematically collected topsoil samples (to a depth of 10 cm) from 12 deserts in northern China and analyzed their organic carbon storage. We used partial correlation and boosted regression tree (BRT) analysis to analyze the factors influencing the spatial distribution of soil organic carbon density based on climate, vegetation, soil grain-size distribution, and element geochemistry. The total organic carbon pool of Chinese deserts was 4.83 × 108 t, the mean soil organic carbon density was 1.37 ± 0.18 kg C m−2, and the mean turnover time was 16.50 ± 2.66 yr. With the largest area, the Taklimakan Desert had the highest topsoil organic carbon storage (1.77 × 108 t). The organic carbon density was high in the east and low in the west, whereas the turnover time showed the opposite trend. The soil organic carbon density was >2 kg C m−2 in the four sandy lands in the eastern region, and was greater than the values for the eight deserts (0.72 to 1.22 kg C m−2). Grain-size (i.e., the silt and clay contents) had the strongest influence on the organic carbon density in Chinese deserts, followed by element geochemistry. Precipitation was the main climatic factor that affected the distribution of organic carbon density in the deserts. Based on climate and vegetation cover trends during the past 20 years, Chinese deserts have a high potential for future organic carbon sequestration.

Spatio-temporal Variation in Vegetation Cover and Its Driving Mechanism Exploration in Southwest China from 2000 to 2020

Using the MOD13A3 NDVI time series from 2000 to 2020, climate date from 1999 to 2020, and land use type data in 2000 and 2020, the spatio-temporal variation in vegetation cover and the driving mechanisms of climate change and human activities to vegetation variation were analyzed based on Theil-Sen Median analysis, the Mann-Kendall significance test, the multi-collinearity test, residual analysis, and relative analysis. The results showed that the vegetation cover exhibited a fluctuating and increasing trend with a magnitude of 0.0016 a-1 in southwest China from 2000 to 2020. The increasing trend of vegetation cover was mostly significant in the Guangxi Hills and Yunnan-Guizhou Plateau and slightly significant in the Tibet Plateau. The vegetation cover had increased in the context of climate change and human activities, with an increasing rate of 0.0010 a-1 and 0.0006 a-1, respectively. The vegetation improvement was mostly dominated by the combination effects of climate change and human activities. The vegetation improvement was dominated by climate change, and the relative role of climate change reached 61.86%. What is more, the vegetation degradation was dominated by human activities, and the relative role of human activities reached 58.39%. Vegetation cover was positively related to minimum temperature, precipitation, maximum temperature, potential evapotranspiration rate, and relative humidity and negatively related to mean temperature, atmosphere pressure, sunshine duration, warmth index, and humidity index. As a whole, the minimum temperature, sunshine duration, and precipitation were the dominant climate factors affecting the vegetation variation in southwest China. Furthermore, the land use and land cover change were significantly related to vegetation variation in southwest China. The implementation of ecological afforestation projects could be beneficial to regional vegetation improvement, whereas the vegetation degradation was mostly conducted by the built-up land expansion.

Long-Term Trends in Vegetation on Bureau of Land Management Rangelands in the Western United States

The US Bureau of Land Management (BLM) manages nearly 1 million km2 of public lands that support recreation, livestock production, and wildlife habitat. Monitoring the condition of vegetation on these lands is crucial for sound management but has historically been difficult to do at scale. Here we used newly developed remote-sensing tools to conduct an unprecedented assessment of trends in vegetation cover and production for all BLM rangelands from 1991 to 2020. We found widespread increases in cover and production of annual grasses and forbs, declines in herbaceous perennial cover, and expansion of trees. Cover and production of annual plants now exceed that of perennials on > 21 million ha of BLM rangeland, marking a fundamental shift in the ecology of these lands. This trend was most dramatic in the Western Cold Desert of Nevada and parts of surrounding states where aboveground production of annuals has more than tripled. Trends in annuals were negatively correlated with trends in bare ground but not with trends in perennials, suggesting that annuals are filling in bare ground rather than displacing perennials. Tree cover increased in half of ecoregions affecting some 44 million ha and underscoring the threat of woodland expansion for western rangelands. A multiscale variance partitioning analysis found that trends often varied the most at the finest spatial scale. This result reinforces the need to combine plot-level field data with moderate-resolution remote sensing to accurately quantify vegetation changes in heterogeneous rangelands. The long-term changes in vegetation on public rangelands argue for a more hands-on approach to management, emphasizing preventative treatment and restoration to preserve rangeland habitat and functioning. Our work shows the power of new remote-sensing tools for monitoring public rangelands and developing effective strategies for adaptive management and conservation.