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Non-linear trend detection in Earth observation time series has become a standard method to characterize changes in terrestrial ecosystems. However, results are largely dependent on the quality and consistency of the input data, and only few studies have addressed the impact of data artifacts on the interpretation of detected abrupt changes. Here we study non-linear dynamics and turning points (TPs) of temperate grasslands in East Eurasia using two independent state-of-the-art satellite NDVI datasets (CGLS v3 and MODIS C6) and explore the impact of water availability on observed vegetation changes during 2001-2019. By applying the Break For Additive Season and Trend (BFAST01) method, we conducted a classification typology based on vegetation dynamics which was spatially consistent between the datasets for 40.86 % (459,669 km 2 ) of the study area. When considering also the timing of the TPs, 27.09 % of the pixels showed consistent results between datasets, suggesting that careful interpretation was needed for most of the areas of detected vegetation dynamics when applying BFAST to a single dataset. Notably, for these areas showing identical typology we found that interrupted decreases in vegetation productivity were dominant in the transition zone between desert and steppes. Here, a strong link with changes in water availability was found for >80 % of the area, indicating that increasing drought stress had regulated vegetation productivity in recent years. This study shows the necessity of a cautious interpretation of the results when conducting advanced characterization of vegetation response to climate variability, but at the same time also the opportunities of going beyond the use of single dataset in advanced time-series approaches to better understanding dryland vegetation dynamics for improved anthropogenic interventions to combat vegetation productivity decrease., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Northwest China has undergone notable alterations in climate and vegetation growth in recent decades. Nevertheless, uncertainties persist concerning the response of different vegetation types to climate change and the underlying mechanisms. This study utilized the Normalized Difference Vegetation Index (NDVI) and three sets of meteorological data to investigate the interannual variations in the association between vegetation and climate (specifically precipitation and temperature) from 1982 to 2015. Several conclusions were drawn. (1) R NDVI-GP (relationship between Growing Season NDVI and precipitation) decreased significantly across all vegetation, while R NDVI-GT (relationship between Growing Season NDVI and temperature) showed an insignificant increase. (2) Trends of R NDVI-GP and R NDVI-GT exhibited great variations across various types of vegetation, with forests displaying notable downward trends in both indices. The grassland exhibited a declining trend in R NDVI-GP but an insignificant increase in R NDVI-GT , while no significant temporal changes in R NDVI-GP or R NDVI-GT were observed in the barren land. (3) The fluctuations in R NDVI-GP and R NDVI-GT closely aligned with variations in drought conditions. Specifically, in regions characterized by VPD (vapor pressure deficit) trends less than 0.02 hpa/yr, which are predominantly grasslands, a rise in SWV (soil water volume) tended to cause a reduction in R NDVI-GP but an increase in R NDVI-GT. However, a more negative trend in SWV was associated with a more negative trend in both R NDVI-GP and R NDVI-GT when the VPD trend exceeded 0.02 hPa/yr, primarily in forests. Our results underscore the variability in the relationship between climate change and vegetation across different vegetation types, as well as the role of drought in modulating these associations., (© 2024. The Author(s).)

Climate change can have positive and negative effects on the carbon pools and budgets in soil and plant fractions, but net effects are unclear and expected to vary widely within the arctic. We report responses after nine years (2012-2021) of increased snow depth (snow fences) and summer warming (open top chambers) and the combination on soil and plant carbon pools within a tundra ecosystem in West Greenland. Data included characteristics of depth-specific soil samples, including the rhizosphere soil, as well as vegetation responses of NDVI-derived traits, plant species cover and aboveground biomass, litter and roots. Furthermore, natural vegetation growth through the study period was quantified based on time-integrated NDVI Landsat 8 satellite imagery. Our results showed that summer warming resulted in a significant and positive vegetation response driven by the deciduous low shrub Betula nana (no other vascular plant species), while snow addition alone resulted in a significant negative response for Betula. A significant positive effect of summer warming was also observed for moss biomass, possibly driven increasing shade by Betula. The aboveground effects cascaded to belowground traits. The rhizosphere soil characteristics differed from those of the bulk soil regardless of treatment. Only the rhizosphere fraction showed responses to treatment, as soil organic C stock increased in near-surface and top 20 cm with summer warming. We observed no belowground effects from snow addition. The study highlights the plant species response to treatment followed by impacts on belowground C pools, mainly driven by dead fine roots via Betula nana. We conclude that the summer warming treatment and snow addition treatment separately showed opposing effects on ecosystem C pools, with lack of interactive effects between main factors in the combination treatment. Furthermore, changes in soil C are more clearly observed in the rhizosphere soil fraction, which should receive more attention in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Global climate change has altered the timing of seasonal events (i.e., phenology) for a diverse range of biota. Within and among species, however, the degree to which alterations in phenology match climate variability differ substantially. To better understand factors driving these differences, we evaluated variation in timing of nesting of eight Arctic-breeding shorebird species at 18 sites over a 23-year period. We used the Normalized Difference Vegetation Index as a proxy to determine the start of spring (SOS) growing season and quantified relationships between SOS and nest initiation dates as a measure of phenological responsiveness. Among species, we tested four life history traits (migration distance, seasonal timing of breeding, female body mass, expected female reproductive effort) as species-level predictors of responsiveness. For one species (Semipalmated Sandpiper), we also evaluated whether responsiveness varied across sites. Although no species in our study completely tracked annual variation in SOS, phenological responses were strongest for Western Sandpipers, Pectoral Sandpipers, and Red Phalaropes. Migration distance was the strongest additional predictor of responsiveness, with longer-distance migrant species generally tracking variation in SOS more closely than species that migrate shorter distances. Semipalmated Sandpipers are a widely distributed species, but adjustments in timing of nesting relative to variability in SOS did not vary across sites, suggesting that different breeding populations of this species were equally responsive to climate cues despite differing migration strategies. Our results unexpectedly show that long-distance migrants are more sensitive to local environmental conditions, which may help them to adapt to ongoing changes in climate., (© 2024 His Majesty the King in Right of Canada. Global Change Biology published by John Wiley & Sons Ltd. Reproduced with the permission of the Minister of Environment and Climate Change Canada.This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Grasslands are one of the most important terrestrial biomes, supporting a wide range of ecological functions and services. Grassland degradation due to overgrazing is a severe issue worldwide, especially in developing regions. However, observations from multiple sources have shown that temperate grasslands in China have significantly increased during the past two decades. It remains controversial what factors have driven the vegetation restoration in this region. In this study, we combined remote-sensing images and field survey datasets to quantify the contributions of different factors to vegetation restoration in six temperate grasslands in northern China. Across the six grasslands, the Normalized Difference Vegetation Index (NDVI) increased by 0.003-0.0319 year -1 . The average contributions of grazing exclusion and climate change to the NDVI increase were 49.23 % and 50.77 %, respectively. Precipitation change was the primary climate factor driving vegetation restoration, contributing 50.76 % to the NDVI variance. By contrast, climate warming tended to slow vegetation restoration, and atmospheric CO 2 concentration change contributed little to the NDVI increase in the temperate grasslands. These results emphasize the significant contributions of both climate change and human management to grassland vegetation restoration., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

This study aimed to assess the impact of land consolidation projects and climate change on changes in vegetation in the Loess Plateau during 2012-2021. The study also explored the impacts of human activities and climate change on the ecological quality of the Loess Plateau during this period. The spatial and temporal normalized difference combined meteorological monitoring data, project data, and normalized difference vegetation index (NDVI) data that was used to create the vegetation index dataset spanning from 2012-2021. The study discussed and assessed the effectiveness of the project, revealing the following results: 1) A significant increase was observed in the vegetation index of the Loess Plateau region from 2012 to 2021, with an upward trend of 0.0024 per year (P < 0.05). 2) Contributions to changes in vegetation attributed to climatic factors and the anthropogenic factors of the ditch construction project were 82.74 and 17.62%, respectively, with climatic factors dominating and the degree of response of the ditch construction project increasing annually. 3) In the Loess Plateau, climatic variables dominated changes in vegetation. However, land consolidation projects in vegetation factors played a key role in changes in vegetation, and the degree of influence was gradually increasing.

Single phenological measures, like the average rate of phenological advancement, may be insufficient to explain how climate change is driving trends in animal populations. Here, we develop a multifactorial concept of spring phenology-including the onset of spring, spring duration, interannual variability, and their temporal changes-as a driver for population dynamics of migratory terrestrial species in seasonal environments. Using this conceptual model, we found that effects of advancing spring phenology on animal populations may be buffered or amplified depending on the duration and interannual variability of spring green-up, and those effects are modified by evolutionary and plastic adaptations of species. Furthermore, we compared our modelling results with empirical data on normalized difference vegetation index-based spring green-up phenology and population trends of 106 European landbird finding similar associations. We conclude how phenological changes are expected to affect migratory bird populations across Europe and identify regions that are particularly prone to suffer population declines., (© 2024 The Authors. Ecology Letters published by John Wiley & Sons Ltd.)

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 (R 2 ) 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., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Climate factors like temperature, precipitation, humidity, and sunshine time exert a profound influence on vegetation. The intricate interplay between the two is crucial to understand in the face of changing climate to develop mitigation strategies. In the current exploration, we delve how climate variability (CV) has impacted the vegetation in the Peshawar Basin (PB) using remote sensing data tools. The trend of climatic variability was investigated using the modified Mann-Kendall test and Sen's slope statistics. The changing climatic parameters were regressed on the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI). The NDVI was further analyzed for spatiotemporal variability under land surface temperature (LST) influence. Results revealed that among the climate factors, average annual temperature and solar radiation have a significant (p < 0.05) negative impact on vegetation while precipitation and relative humidity significantly (p < 0.05) influence NDVI positively. The overall positive trend shows that vegetation improved between 2001 and 2020 with time, however some years (2010, 2012, 2014, 2016, and 2017) with low NDVI. NDVI varied in space considerably due to climatic extremes brought on by CV and the urbanization of agricultural land. NDVI regressed on LST showed that there was no or very little vegetation in the grids with high LST. The study concluded that the region is significantly impacted by both CV-related extreme weather events and anthropogenic activities. The vegetation is improving, but it is in danger of being destroyed by deforestation due to CV and human activities that exacerbate the risk of future calamities. To protect vegetation and avoid disasters, there is an immense need for adaptation and mitigation measures to deal with the region's fast-changing environment. The study urges local authorities to create climate-resilient governmental policies and supports regional sustainable development and vegetation restoration., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

To explore the responses of vegetation growth to change in terrestrial water storage in Southwest China, we analyzed the change trend and relationship between vegetation and terrestrial water storage anomaly (TWSA) in Southwest China from January 2003 to December 2021 by using TWSA data of Gravity Recovery and Climate Experi-ment (GRACE) satellite and normalized differential vegetation index (NDVI) data. The results showed that NDVI in Southwest China during the study period showed an overall upward trend. Meanwhile, TWSA showed a significant downward trend in central and southern Tibet, and a significant upward trend in northwest Tibet and southeast region of Southwest China. Results of Pearson correlation analysis showed that there were significant spatial differences in responses of NDVI to TWSA changes in Southwest China. NDVI had a significant negative response to TWSA changes in most regions of Tibet, but a significant positive response to TWSA changes in most regions of southeast region of Southwest China. Such differences were driven by climate change and topography.

Recent studies highlight the potential of climate change refugia (CCR) to support the persistence of biodiversity in regions that may otherwise become unsuitable with climate change. However, a key challenge in using CCR for climate resilient management lies in how CCR may intersect with existing forest management strategies, and subsequently influence how landscapes buffer species from negative impacts of warming climate. We address this challenge in temperate coastal forests of the Pacific Northwestern United States, where declines in the extent of late-successional forests have prompted efforts to restore old-growth forest structure. One common approach for doing so involves selectively thinning forest stands to enhance structural complexity. However, dense canopy is a key forest feature moderating understory microclimate and potentially buffering organisms from climate change impacts, raising the possibility that approaches for managing forests for old-growth structure may reduce the extent and number of CCR. We used remotely sensed vegetation indices to identify CCR in an experimental forest with control and thinned (restoration) treatments, and explored the influence of biophysical variables on buffering capacity. We found that remotely sensed vegetation indices commonly used to identify CCR were associated with understory temperature and plant community composition, and thus captured aspects of landscape buffering that might instill climate resilience and be of interest to management. We then examined the interaction between current restoration strategies and CCR, and found that selective thinning for promoting old-growth structure had only very minor, if any, effects on climatic buffering. In all, our study demonstrates that forest management approaches aimed at restoring old-growth structure through targeted thinning do not greatly decrease buffering capacity, despite a known link between dense canopy and CCR. More broadly, this study illustrates the value of using remote sensing approaches to identify CCR, facilitating the integration of climate change adaptation with other forest management approaches., (© 2023 John Wiley & Sons Ltd.)

The peak growth of plant in summer is an important indicator of the capacity of terrestrial ecosystem productivity, and ongoing studies have shown its responses to climate warming as represented in the mean temperature. However, the impacts from the asymmetrical warming, that is, different rates in the changes of daytime (T max ) and nighttime (T min ) warming were mostly ignored. Using 60 flux sites (674 site-year in total) measurements and satellite observations from two independent satellite platforms (Global Inventory Monitoring and Modeling Studies [1982-2015]; MODIS [2000-2020]) over the Northern Hemisphere (≥30°N), here we show that the peak growth, as represented by both flux-based maximum primary productivity and the maximum greenness indices (maximum normalized difference vegetation index and enhanced vegetation index), responded oppositely to daytime and nighttime warming. T max - T min + (peak growth showed negative responses to T max , but positive responses to T min ) dominated in most ecosystems and climate types, especially in water-limited ecosystems, while T max + T min - (peak growth showed positive responses to T max , but negative responses to T min ) was primarily observed in high latitude regions. These contrasting responses could be explained by the strong association between asymmetric warming and water conditions, including soil moisture, evapotranspiration/potential evapotranspiration, and the vapor pressure deficit. Our results are therefore important to the understanding of the responses of peak growth to climate change, and consequently a better representation of asymmetrical warming in future ecosystem models by differentiating the contributions between daytime and nighttime warming., (© 2023 John Wiley & Sons Ltd.)

Quantify the relative effects of climate change and human activities on vegetation cover can help us understand the vegetation cover change and its drivers. Residual analysis, defined as the difference between potential normalized difference vegetation index (NDVI pot ) and observed normalized difference vegetation index (NDVI act ), was used to solve this problem. The estimation of NDVI pot is one of the important issues faced by ecologists. Due to the strictly protection of environment and ecosystems, the ecosystems in nature reserves are rarely disturbed by human activities. Therefore, establishing NDVI pot estimation model based on nature reserves can improve the estimation accuracy of NDVI pot . However, the estimation of NDVI pot based on nature reserves has not yet been reported. In this paper, the NDVI pot estimation model was established based on nature reserves, and residual analysis was used to quantify the impact of human activities on NDVI act . The results show that the NDVI act in Nanjing metropolitan area (NJMA) showed a significant upward trend from 2000 to 2019, and 74.20% of NJMA showed greening trends, while 24.47% showed browning trends. The temperature and precipitation were positively correlated with normalized difference vegetation index (NDVI), and the impact of the temperature on NDVI was greater than that of precipitation. The promotion of human activities on NDVI had become more and more significant. There was 51.88% of NJMA where the human activities had a positive promotion effect on NDVI, while there was 46.29% of the regional where the human activities had a negative inhibitory effect on NDVI. The population density (POP) and gross domestic product (GDP) were mainly positively correlated with NDVI, and the impact of the POP on NDVI was greater than that of GDP. The conversion of cropland to forests and the increase of the sown area of crops also caused the NDVI to increase, while the disorderly expansion of urban land caused the NDVI to decrease., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Europe witnessed a strong increase in climate variability and enhanced climate-induced extreme events, such as hot drought periods, mega heat waves, and persistent flooding and flash floods. Intensified land degradation, land use, and landcover changes further amplified the pressure on the environmental system functionalities and fuelled climate change feedbacks. On the other hand, global satellite observations detected a positive spectral greening trend-most likely as a response to rising atmospheric CO 2 concentrations and global warming. But which are the engines behind such shifts in surface reflectance patterns, vegetation response to global climate changes, or anomalies in the environmental control mechanisms? This article compares long-term environmental variables (1948-2021) to recent vegetation index data (Normalized Difference Vegetation Index (NDVI), 2001-2021) and presents regional trends in climate variability and vegetation response across Europe. Results show that positive trends in vegetation response, temperature, rainfall, and soil moisture are accompanied by a strong increase in climate anomalies over large parts of Europe. Vegetation dynamics are strongly coupled to increased temperature and enhanced soil moisture during winter and the early growing season in the northern latitudes. Simultaneously, temperature, precipitation, and soil moisture anomalies are strongly increasing. Such a strong amplification in climate variability across Europe further enhances the vulnerability of vegetation cover during extreme events., (© 2022. The Author(s).)

Many ecological restoration programs have been implemented in China during the last two decades. At the same time, the vegetation has turned green significantly in China. However, few studies have directly evaluated the contribution of the ecological restoration programs to vegetation greening in comparison with the contribution of climate change using high-resolution data of afforestation areas at the national scale. We used newly compiled high-resolution data on yearly forest plantation and mountain closure, the daily climate data from the 2480 meteorological stations and GIMMS 3g NDVI data. We used a multiple linear regression model to compare the influence of temperature, precipitation, and ecological restoration programs on NDVI dynamics. We then used the hierarchical variance partitioning method to evaluate the relative contribution of temperature, precipitation, and ecological restoration programs on NDVI dynamics. We found a significant greening trend in China from 1999 to 2015 with an annual increase rate of 0.0017 yr -1 in the mean growing season NDVI. The ecological restoration programs dominated the vegetation greening in northern China and the southern coastal regions, indicating a good performance of restoration programs in these regions. In contrast, temperature or precipitation dominated the vegetation greening in southwestern China, Inner Mongolia and the implementation regions of several ecological restoration programs in northeastern China. Among the ecological restoration programs except the Three-North Shelterbelt Forest Program, the effect of ecological restoration programs on vegetation greening was stronger than the total effects of temperature and precipitation changes. Our study presents a systematic assessment on the contribution of ecological restoration programs to the vegetation greening in China, accessed the role on vegetation greening of different ecosystem restoration programs. We analyzed the reasons for the differences in the contribution of different ecological restoration programs to vegetation greening and provided insights facilitating policy makers to prioritize future restoration planning., Competing Interests: Declaration of competing interest The authors have no conflicts of interest to declare., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Surface evapotranspiration (ET) is an important part of the hydrological cycle. Based on the MOD16 ET product and the data collected by meteorological stations, this study investigated, for the first time, the characteristics, variation trend and influencing factors of actual ET in Ningxia from 2001 to 2020 along temporal and spatial scales using the Theil-Sen median trend analysis, Mann-Kendall test and Hurst index, and predicted the future trend of ET. The results revealed a strong correlation between the MOD16 ET product and ET data collected at meteorological stations (r = 0.837, R 2 = 0.701). Over the past 20 years, the annual ET in Ningxia showed an overall increasing trend, and the proportion of the increasing area was 96.58%. Quarterly ET varied over time, with the highest value in the third quarter and the lowest value in the second quarter. Annual ET showed a positive correlation with normalized difference vegetation index (NDVI), surface temperature and precipitation but no correlation with relative humidity. Additionally, the Hurst index revealed areas showing a persistent increase in ET, accounting for 84.91% of the total area, indicating that the future trend of ET in Ningxia is consistent with the past trend.

The water and energy in the land surface and lower atmosphere have a strong coupling relationship. Apart from the land surface temperature (Ts) and air temperature (Ta), the land surface-air temperature difference (Ts-Ta) is also an essential parameter reflecting the coupling process. However, the global spatiotemporal variations and influencing factors of Ts-Ta remain not well explored. Here, ERA5-land reanalysis data, GIMMS NDVI data, and elevation data were used to analyze the global spatiotemporal heterogeneity and influencing factors of Ts-Ta. It was found that annual mean Ts-Ta exhibited a decreasing trend from the equator to polar areas. And the annual Ts-Ta increased at 0.009 °C/10a from 1981 to 2020. The variations of global net radiation mainly determined the spatiotemporal heterogeneity of global Ts-Ta. The different properties of the land surface and near-surface atmosphere were the main factors affecting the Ts-Ta, including soil moisture, vegetation, snow cover, and the water vapor content in the atmosphere. In addition, Ts and Ta also affected each other. These findings are conducive to a better understanding of the land-atmosphere coupling, and it is of great significance to take better measures to adapt the global climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

As a major component of temperate steppes in the Eurasian continent, the Mongolian Plateau (MP) plays a pivotal role in the East Asian and global carbon cycles. This paper describes the use of five remote sensing indices derived from satellite data to characterize vegetation cover on MP, namely: gross primary production (GPP), net primary production (NPP), normalized difference vegetation index (NDVI), leaf area index (LAI) and fractional vegetation cover (FVC). It is found that GPP, NPP, and NDVI exhibit increasing trends, whereas LAI and FVC present decreasing trends on the MP since 1982. The different indices highlight discrepancies in the spatial pattern of vegetation growth, with the greatest increase in the southeast of MP. Only 3.4% of the total land area of MP exhibited consistent trends in the indices (0.1% degradation and 3.3% growth, P < 0.01), with the synchronous change of both LAI and NPP exhibiting higher consistency than that of raw NDVI and NPP. Understanding of the characteristics and status of vegetation change on the MP has far-reaching implications for its ecological protection management, and climate change mitigation., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

As the third pole of the world, the Qinghai-Tibet Plateau (QTP) has a very special climate and geographical environment. In the past 20 years, with the increasing demand for clean energy, more than ten hydropower stations have been built. The impacts of these hydropower stations on riparian vegetation (RV) have only been described qualitatively in previous studies, while the contribution of dams and meteorological variables to riparian vegetation has not been quantitatively assessed. This study selected eight representative large-scale hydropower stations in the QTP, calculated and analyzed the dynamics of the standardized difference vegetation index (NDVI) of the RV pre-and post the dams construction, combined with the measured temperature and precipitation data to explore the driving factors of RV changes. The results show that the dams promoted the growth of RV and they were the main contributor (>50%) while precipitation and temperature had relatively small impacts. The effect of dams varies for different regions, compared with the sub-cold regions, it was more significant in humid and semi-humid regions of temperate zone. The dams affected RV in an indirect way through regulating the microclimate, promoting precipitation and slowing down the rate of temperature rise and these effects may come from the increase of the upstream water surface area., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The spatiotemporal variation and driving force of the Normalized Difference Vegetation Index (NDVI) are helpful to ecological environment protection and natural resource management. Using the Sen and Mann-Kendall methods, Hurt index, and the Geodetector, this study investigated the temporal and spatial changes and driving forces of NDVI during 1982-2015. The results showed that (1) From 1982 to 2015, the high vegetation coverage was mainly distributed in the Qinling Mountains and the Daba Mountains, while the low vegetation coverage was in high altitude areas in the west, low altitude in the east, and the Hanjiang River valley. (2) NDVI in the Qinba Mountains increased continuously accounting for 81.1%, with 68% showing slow growth. In the future, only 37.8% of the vegetation will have significant change. The area of vegetation increase will be greater than the area of decrease. (3) NDVI increased firstly and then decreased with the increase of altitude, reaching the maximum value at 1100 m. NDVI showed a trend of fluctuating growth. It reached the maximum value of 0.86 in 2015. (4) Through the Geodetector, the main factors affecting NDVI were natural factors mainly including rainfall, soil type, and digital elevation model (DEM), while human activities, including population density, had little influence on NDVI. Natural environment factors and human activities together had a greater impact on the spatial distribution of NDVI. This study could provide help for the sustainable development of the natural environment in the Qinba Mountains., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The normalized difference vegetation index (NDVI) is a useful indicator to characterize vegetation development and land use which can effectively monitor changes in ecological environments. As an important area for ecological balance and safety in China, understanding the dynamic changes in land cover and vegetation of the Yangtze River Basin would be crucial in developing effective policies and strategies to protect its natural environment while promoting sustainable growth. Based on MODIS-NDVI data and meteorological data from 2000 to 2019, the temporal and spatial distribution of vegetation coverage in the Yangtze River Basin during the past 20 years were characterized, and the impacts of human activities and climate change were quantitatively evaluated. We drew the following research conclusions: (1) From 2000 to 2019, the vegetation cover of the Yangtze River Basin presented a fluctuating inter-annual growth trend. Except for the Taihu Lake sub-basin, the vegetation cover in other sub-basins showed an upward trend. (2) The vegetation cover exhibited a spatial distribution pattern of "high in the middle and low in the east and west", with the multi-year average value of NDVI being 0.5153. (3) Areas with improved vegetation cover were significantly larger than the areas with degraded foliage. The central region has stronger overall trend of change than the east, and the east is stronger than the west. These vegetation cover changes are largely related to anthropogenic activities. (4) Vegetation cover changes due to precipitation and temperature exhibited significant spatial heterogeneity. While both temperature and precipitation influenced vegetation cover, the temperature was the leading climate factor in the area. (5) Anthropogenic and climate factors jointly promoted the change of vegetation cover in the Yangtze River Basin. Human activities contributed 79.29%, while climate change contributed 20.71%. This study could be used in subsequent studies analyzing the influencing factors affecting long-term vegetation cover in large-scale watersheds.

Recurring cyanobacterial blooms have seriously hindered the sustainable development of cities. In this study, the variation trend of cyanobacterial blooms was analyzed by taking Lake Chaohu in China as the study area, and the Normalized Difference Vegetation Index (NDVI) derived from Landsat observations combined with the development index of surrounding cities from 2009 to 2019 was used to quantitatively analyze the response of cyanobacterial blooms to urban development and climate change. The results showed that the NDVI of the Northwest Lake region was significantly higher than that of other regions. Summer and autumn were the main seasons for the outbreak of cyanobacterial blooms. The NDVI of Lake Chaohu and Baohe Lake region showed a significant correlation with the gross domestic product (GDP) growth rate of Hefei city (HF), the districts and counties around the lake (DCL), Baohe District (BH), and the population (P). As the economic regions gradually focused on BH rather than on HF and DCL, there was an increasing trend correlation between the NDVI of Baohe Lake region and the GDP growth rate. However, the elimination of GDP in BH did not affect the consistency relationship between the economic growth of other regions and the NDVI of Lake Chaohu on a large scale. In addition, the results of relative importance analysis indicated that the GDP growth rate of BH and the area of Hefei except DCL (HF-DCL) accounted for important contribution to the [Formula: see text] of the regression. This study has momentous reference value for understanding the coupling relationship between urban development and lake environment., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The impacts of climate change on vegetation cover in different regions in China are not entirely clear because of the interference of non-climatic factors, such as human activity. This study aims to analyze the spatiotemporal differences in climate impacts qualitatively and quantitatively by applying trend, correlation, and multiple linear regression (MLR) analyses to the data of Normalized Difference Vegetation Index (NDVI) and two climatic factors (air temperature and precipitation) during 1982-2015 in China. The MLR equation linking two climatic variables with NDVI was used to identify the NDVI trend caused by climate change. We demonstrated that the central and eastern regions of China, dominated by deciduous and evergreen broadleaf forests, experienced a rapid increase in NDVI from 1982 to 2015. The response of NDVI to variations in temperature and precipitation exhibited large spatiotemporal differences across China, which was closely related to climatic conditions and vegetation types. Overall, warming, particularly the sharp rise in spring, was the main climatic driving force behind China's NDVI increase, and precipitation also influenced the NDVI increase in temperate grassland and desert regions due to the relatively arid climate, particularly in summer. The contributions of climate change to the total NDVI trend (CC) showed a large spatiotemporal heterogeneity across China. Overall, only 45% of the pixels (with a resolution of 8 km) in the study area showed that the MLR equations between NDVI and two climatic factors were significant at the 0.05 significance level during the growing season (April-October), and the average CC of these pixels was 38%. Among the eight vegetation sub-regions of China, the temperate desert and Qinghai-Tibet Plateau alpine meadow regions generally exhibited relatively larger CCs than other vegetation sub-regions in different seasons. At a national scale, the regional average CC reached 64% during the growing season. These results at multiple scales can help to deeply understand the mechanisms of regional environmental variation and sustainability., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Changes in land management and climate alter vegetation dynamics; however, the factors driving vegetation changes remain elusive at multiple spatiotemporal levels. Here, we assess the drivers of changes in greenness from 2000 to 2015 in Northwest China (NW China). We used multiple stepwise linear regression (MSLR), redundancy analysis (RDA), and 12 other models to quantify the impacts of precipitation and temperature metrics, gross domestic product (GDP), population, and grazing intensity on the normalized difference vegetation index (NDVI) at three administrative levels (county, town, and village), four temporal levels (yearly, May, July, and September), two vegetation types (woodland and grassland), and at annual precipitation gradients of <200, 200-400, and >400 mm. The results suggest that NW China underwent vegetation greening from 2000 to 2015. Precipitation and temperature were the most influential factors contributing to the NDVI change. Population was the main determinant of NDVI under the precipitation gradient of <200 mm, and the effect of GDP on NDVI was moderate. On the temporal scale, annual precipitation, precipitation before the previous year, and precipitation in the current year determined the NDVI in May, July, and September, respectively, for both woodland and grassland. At multiple scales, climate change was the primary driver of vegetation change in NW China, rather than human disturbance. These findings expand our understanding on drivers of NDVI at multiple levels over a long period. Measures to manage decreasing vegetation coverage may be more effective and could be implemented sooner based on predicted climate change in drylands worldwide., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Southwest China is an important biodiversity hotspot in the world and is controlled by the Pacific and Indian Ocean monsoon in the east and west part respectively. However, how abiotic and biotic factors affect the response of vegetation to climate change in different monsoon regions is still not clear. Here we used the annual change rate of growing-season normalized difference vegetation index (NDVI trend) during 1982-2015 to explore the vulnerability of vegetation (forests and shrubs) activity to climate change in southwest China. We examined NDVI trend in relation to: 1) climate change trends, i.e. annual change rate of water and energy availability, indicated by the Palmer Drought Index (PDSI) and potential evapotranspiration (PET), respectively; 2) climatic condition, i.e. mean PDSI and PET during 1982-2015; 3) vegetation height; 4) biome type; 5) monsoon region. The results showed that NDVI generally increased in the Pacific monsoon region, especially in the southern areas, probably because the vegetation under more productive climate were more resistant to climate change, and also because decreased temperature lead to lower evapotranspiration which alleviated the slight drought trend in this region. In contrast, NDVI generally decreased in the Indian Ocean monsoon region which showed more pronounced drought trend, especially in the tall subalpine and tropical forests of Southeast Tibetan Mountains, which supports the "hydraulic limitation hypothesis" that vegetation height interacted with climate change in affecting vegetation vulnerability. Our analysis highlighted the critical roles of different monsoon systems, climate condition and vegetation height in affecting ecosystem vulnerability. We suggest that the (sub)tropical forests in the Pacific monsoon region may have act as an important carbon sink during the past decades, while the tall forests in Southeast Tibetan mountains (a biodiversity center with high carbon stock) are highly vulnerable to climate change and should have priority in ecosystem protection., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Subalpine meadow is extremely sensitive to climate change. Few studies, however, focused on the responses of subalpine meadow to climatic factors in subtropical regions. It is still a challenge to extract the biophysical parameters from optical remote sensing imagery during the growing season. Based on the normalized difference vegetation index (NDVI) time series dataset from the MOD13Q1 vegetation index products and meteorological data, we analyzed the changes of vegetation growth of subalpine meadow at Huanggang Mountain in the top of Wuyishan National Park from 2000 to 2019, its responses to climate factors and the time lag effects. The results showed that NDVI in summer increased insignificantly during 2000-2019, and that NDVI in the growing season, spring, and autumn increased significantly. The enhancement of NDVI was mainly contributed by the increasing temperature (0.026 ℃·a -1 ) from 2000 to 2019. The increasing temperature in spring and autumn influenced meadow growth more than that in summer and growing season. NDVI of the growing season in subalpine meadow was sensitive to precipitation,indicating that the growth of subalpine meadow was strongly affected by precipitation even in the subtropical region with sufficient precipitation. Temperature and precipitation in different growth periods had different time lag effects on the NDVI of subalpine meadowo. The time lag effects of temperature on subalpine meadow were 0-1 month, and that of precipitation were 2-3 month.

The long-term series of geographic data and remote sensing data contain noise and perio-dic fluctuation. We used the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) to decompose the data of the normalized difference vegetation index (NDVI), precipitation, and temperature from 1982 to 2015 on per-pixels in the Loess Pla-teau to obtain residuals. Using the residual with less noise and periodic fluctuations, we examined the changes of NDVI and the relationship between NDVI and climatic factors. The results showed that the spatial change trend of NDVI was mainly increasing from 1982 to 2015 in the Loess Plateau. The significance of the change trend of residual NDVI (95.9%) was greater than the original NDVI (72.3%), with spatial variations. Temperature and precipitation could largely explain the changes in vegetation coverage. The proportions of areas with extremely significant positive and negative correlations between temperature and NDVI on the Loess Plateau were 83.7% and 13.9%, respectively, while that between precipitation and NDVI were 54.4% and 37.2%, respectively. There were obvious spatial variations in the responses of vegetation to climate change on the Loess Plateau. Different climatic factors had different effects on different types of vegetation. In general, temperature had stronger correlation with different vegetation than precipitation. Therefore, temperature was the main driving factor for the changes of vegetation cover in the Loess Plateau.

Climate models for semiarid and arid regions predict increasing average temperatures and reduced amounts of total annual rainfall. This warming and drying trend could have critical, adverse effects on natural vegetation activity and survival in arid and semiarid zones. We investigated the long-term effects of climate change and surface-runoff variations on the production of natural vegetation in a dry, undisturbed, first-order watershed in the northern Negev, Israel. Vegetation dynamics were estimated by normalized difference vegetation index. Yearly annual vegetation cover varied greatly during the monitoring period (2000-2013), but a significant positive regression was found with annual rainfall and runoff amounts, suggesting a strong relationship between annual vegetation dynamics and rainfall amount in a given year. A significant positive linear regression was found between annual ET 0 values and year of measurement (1994-2013), with no corresponding decrease in vegetation condition. Surface runoff in the watershed affected the vegetation's water source. Large variation in annual runoff amounts was observed for 1994-2011, averaging 22.3 and 9 mm for the first (2000-2006) and second (2007-2013) vegetation-monitoring subperiods, respectively. Perennial vegetation was less sensitive to drought years than annual vegetation, likely due to differences in water-source availability. Perennials also benefited from the arrival of nutrients, organic matter, and fertile soil flowing with the surface runoff and eroded soil into their growing area., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

A widespread increase in forest cover is underway in northern Mediterranean forests because of land abandonment and decreased wood demand, but the resilience of these successional forests to climate change remains unresolved. Here we use 18-year time series of canopy greenness derived from satellite imagery (NDVI) to evaluate the impacts of climate change on Spain's forests. Specifically, we analyzed how NDVI was influenced by the climatic water balance (i.e. Standardized Precipitation-Evapotranspiration Index, SPEI), using monthly time-series extracted from 3,100 pixels of forest, categorized into ten forest types. The forests increased in leaf area index by 0.01 per year on average (from 1.7 in 2000 to 1.9 in 2017) but there was enormous variation among years related to climatic water balance. Forest types varied in response to drought events: those dominated by drought-avoiding species showed strong covariance between greenness and SPEI, while those dominated by drought-tolerant species showed weak covariance. Native forests usually recovered more than 80% of greenness within the 18 months and the remainder within 5 years, but plantations of Eucalyptus were less resilient. Management to increase the resilience of forests-a key goal of forestry in the Mediterranean region-appears to have had a positive effect: canopy greenness within protected forests was more resilient to drought than within non-protected forests. In conclusion, many of Spain's successional forests have been resilient to drought over the past 18 years, from the perspective of space. Future studies will need to combine remote sensing with field-based analyses of physiological tolerances and mortality processes to understand how Mediterranean forests will respond to the rapid climate change predicted for this region in the coming decades., (© 2020 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Continued long-term monitoring of vegetation activity in national key ecological function zones (NKEFZs) has implications for national ecological security and sustainability in China. We used Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) dataset to map and analyze the spatiotemporal patterns of change in vegetation growth and their linkage with climate change and human activities in NKEFZs during 1982-2013. Statistically significant increases of growing season, spring, and autumn NDVI were observed during all or most periods while 25 NKEFZs are taken as a whole. Non-significant decreases of NDVI were found in 7 NKEFZs during a few periods, and obvious increases were observed during fifteen periods in all other NKEFZs. Vegetation growth in NKEFZs was mainly regulated by a thermal factor, and the dominant climatic drivers varied across different regions and seasons. The influence of temperature was stronger on vegetation activity in spring and autumn for those NKEFZs located in high latitudes and high elevations, while precipitation was the main climatic control factor for NKEFZs in the arid and semi-arid regions. The effects of human activity on the NDVI of NKEFZs were not ignored; a significant decrease of NDVI in the Sanjiang Plain may be related to the rapid change in land use from wetland into farmland.

Since the Silk-road Economic belt initiatives were proposed, Xinjiang has provided a vital strategic link between China and Central Asia and even Eurasia. However, owing to the weak and vulnerable ecosystem in this arid region, even a slight climate change would probably disrupt vegetation dynamics and land cover change. Thus, there is an urgent need to determine the Normalized Difference Vegetation Index (NDVI) and Land-use/Land-cover (LULC) responses to climate change. Here, the extreme-point symmetric mode decomposition (ESMD) method and linear regression method (LRM) were applied to recognize the variation trends of the NDVI, temperature, and precipitation between the growing season and other seasons. Combining the transfer matrix of LULC, the Pearson correlation analysis was utilized to reveal the response of NDVI to climate change and climate extremes. The results showed that: (1) Extreme temperature showed greater variation than extreme precipitation. Both the ESMD and the LRM exhibited an increased volatility trend for the NDVI, with the significant improvement regions mainly located in the margin of basins. (2) Since climate change had a warming trend, the permanent snow has been reduced by 20,436 km 2 . The NDVI has a higher correlation to precipitation than temperature. Furthermore, the humid trend could provide more suitable conditions for vegetation growth, but the warm trend might prevent vegetation growth. Spatially, the response of the NDVI in North Xinjiang (NXC) was more sensitive to precipitation than that in South Xinjiang (SXC). Seasonally, the NDVI has a greater correlation to precipitation in spring and summer, but the opposite occurs in autumn. (3) The response of the NDVI to extreme precipitation was stronger than the response to extreme temperature. The reduction in diurnal temperature variation was beneficial to vegetation growth. Therefore, continuous concentrated precipitation and higher night-time-temperatures could enhance vegetation growth in Xinjiang. This study could enrich the understanding of the response of land cover change and vegetation dynamics to climate extremes and provide scientific support for eco-environment sustainable management in the arid regions., Competing Interests: The authors declare no conflict of interest. The funders had no role in the design of the study; the collection, analyses, or interpretation of data; the writing of the manuscript, or in the decision to publish the results.

In recent decades, many forest die-off events have been reported in relation to climate-change-induced episodes, such as droughts and heat waves. To understand how these extreme climatic events induce forest die-off, it is important to find a tool to standardize the climatic conditions experienced by different populations during a specific climatic event, taking into account the historic climatic conditions of the site where these populations live (bioclimatic niche). In this study, we used estimates of climatic suitability calculated from species distribution models (SDMs) for such purpose. We studied forest die-off across France during the 2003 heatwave that affected Western Europe, using 2,943 forest inventory plots dominated by 14 single tree species. Die-off severity was estimated by Normalized Difference Vegetation Index (NDVI) loss using Moderate-resolution Imaging Spectroradiometer remote sensor imagery. Climatic suitability at the local level during the historical 1979-2002 period (HCS), the episode time (2003; ECS) and suitability deviance during the historical period (HCS-SD) were calculated for each species by means of boosted regression tree models using the CHELSA climate database and occurrences extracted from European forest inventories. Low HCS-SD and high mean annual temperature explained the overall regional pattern of vulnerability to die-off across different monospecific forests. The combination of high historical and low episode climatic suitability also contributed significantly to overall forest die-off. Furthermore, we observed different species-specific relationships between die-off vulnerability and climatic suitability: Sub-Mediterranean and Mediterranean species tended to be vulnerable in historically more suitable localities (high HCS), whereas Euro-Siberian species presented greater vulnerability when the hot drought episode was more intense. We demonstrated that at regional scale, past climatic legacy plays an important role in explaining NDVI loss during the episode. Moreover, we demonstrated that SDMs-derived indexes, such as HCS, ECS and HCS-SD, could constitute a tool for standardizing the ways that populations and species experience climatic variability across time and space., (© 2020 John Wiley & Sons Ltd.)

The mountain systems of the Hindu Kush Himalaya (HKH) are changing rapidly due to climatic change, but an overlooked component is the subnival ecosystem (between the treeline and snow line), characterized by short-stature plants and seasonal snow. Basic information about subnival vegetation distribution and rates of ecosystem change are not known, yet such information is needed to understand relationships between subnival ecology and water/carbon cycles. We show that HKH subnival ecosystems cover five to 15 times the area of permanent glaciers and snow, highlighting their eco-hydrological importance. Using satellite data from the Landsat 5, 7 and 8 missions, we measured change in the spatial extent of subnival vegetation from 1993 to 2018. The Landsat surface reflectance-derived Normalized Difference Vegetation Index product was thresholded at 0.1 to indicate the presence/absence of vegetation. Using this product, the strength and direction of time-series trends in the green pixel fraction were measured within three regions of interest. We controlled for cloud cover, snow cover and evaluated the impact of sensor radiometric differences between Landsat 7 and Landsat 8. Using Google Earth Engine to expedite data processing tasks, we show that there has been a weakly positive increase in the extent of subnival vegetation since 1993. Strongest and most significant trends were found in the height region of 5,000-5,500 m a.s.l. across the HKH extent: R 2  = .302, Kendall's τ = 0.424, p < .05, but this varied regionally, with height, and according to the sensors included in the time series. Positive trends at lower elevations occurred on steeper slopes whilst at higher elevations, flatter areas exhibited stronger trends. We validated our findings using online photographs. Subnival ecological changes have likely impacted HKH carbon and water cycles with impacts on millions of people living downstream, but the strength and direction of impacts of vegetation expansion remain unknown., (© 2019 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

As the upper section of the Mekong River Basin, the vegetation quality of the Lancang River Basin (LRB) and the related ecological functions are critical for the whole basin. With time-series Moderate Resolution Imaging Spectroradiometer (MODIS) images from 2000 to 2015 and local daily climatic data since 1976, their vertical interaction differences were identified. The results showed that the spatial variation in Normalized difference vegetation index (NDVI) of grassland and forest were sensitive to elevation. The NDVI value in the southern area at elevations less than 3000 m was more than 0.80 and decreased to 0.30-0.60 with elevations higher than 4500 m. The general vegetation quality showed a positive trend under climate change over 16 years. The M-K test of daily precipitation and temperature from 12 local weather stations showed that the basin temperature varied more significantly than precipitation. The temporal correlation between NDVI with precipitation as well as temperature at each pixel indicated that temperature was the dominant factor affecting grassland and forest dynamics in the LRB. The interaction between vegetation and climate was more sensitive at elevations lower than 3000 m. Based on the RCP4.5 scenario, the future temperature distribution was predicted, and its impact on NDVI was simulated at the pixel scale. Under future drier and warmer climate conditions, the responded NDVI in the upper stream with higher elevation may increase soil erosion and decrease streamflow. The NDVI in the downstream area will be improved and be able to adapt to the related climate impacts. Because of the large amount of water and biomass in this basin, higher temperatures will accelerate the decomposition of forest foliar litter. Thus, more organic carbon and forest diffuse pollution will be discharged into the water, potentially affecting the water quality of the whole basin., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Though temperature over the past three decades has shown an asynchronous warming trend between daytime and nighttime, the response of vegetation activity to such non-uniform warming is still not very clear. In this study, the least squares linear trend analysis and geographic information system spatial analysis were conducted to analyze the spatiotemporal patterns of the daytime and nighttime warming based on the daily temperature data from 1982 to 2015 in Northwest China. The normalized difference vegetation index (NDVI) from Global Inventory Monitoring and Modeling System and vegetation type data were used to investigate the responses of vegetation activity to the daytime and nighttime warming using the partial correlation analysis. Our results suggested that (1) there was a very significant increasing trend in both daytime and nighttime temperatures in Northwest China from 1982 to 2015; night temperatures increased about 1.2 times faster than daytime temperatures, showing diurnal asymmetric warming; (2) the responses of vegetation activity to daytime and nighttime warming in Northwest China showed a distinct spatial pattern; the change in night temperatures had a more significant (positive in most regions) effect on vegetation; (3) various types of vegetation responded differently to asymmetric daytime and nighttime warming. Grassland NDVI, broad-leaved, and coniferous forest NDVI significantly responded to daytime warming. Shrub NDVI and desert NDVI significantly responded to night warming. These findings can deepen the understanding of the effects of the daytime and nighttime warming on vegetation activities in arid regions in the context of the current asymmetric warming.

The fragile alpine vegetation in the Tibetan Plateau (TP) is very sensitive to environmental changes, making TP one of the hotspots for studying the response of vegetation to climate change. Existing studies lack detailed description of the response of vegetation to different climatic factors using the method of multiple nested time series analysis and the method of grey correlation analysis. In this paper, based on the Normalized Difference Vegetation Index (NDVI) of TP in the growing season calculated from the MOD09A1 data product of Moderate-resolution Imaging Spectroradiometer (MODIS), the method of multiple nested time series analysis is adopted to study the variation trends of NDVI in recent 17 years, and the lag time of NDVI to climate change is analyzed using the method of Grey Relational Analysis (GRA). Finally, the characteristics of temporal and spatial differences of NDVI to different climate factors are summarized. The results indicate that: (1) the spatial distribution of NDVI values in the growing season shows a trend of decreasing from east to west, and from north to south, with a change rate of -0.13/10° E and -0.30/10° N, respectively. (2) From 2001 to 2017, the NDVI in the TP shows a slight trend of increase, with a growth rate of 0.01/10a. (3) The lag time of NDVI to air temperature is not obvious, while the NDVI response lags behind cumulative precipitation by zero to one month, relative humidity by two months, and sunshine duration by three months. (4) The effects of different climatic factors on NDVI are significantly different with the increase of the study period.

This study investigated climatic determinants for regional greenness in China and spatially variable correlations between climatic determinants and vegetation in specific regions using the geographical detector and geographically weighted regression (GWR) methodologies. The analyses were based on normalized difference vegetation index (NDVI) and interpolations of climatic determinants from 652 Chinese meteorological stations. The study period (1982-2013) was divided into two stages (T1-T2) before and after the inflection year identified by the accumulative anomaly of NDVI. Three typical regions (R1-R3) were then selected according to the same NDVI variation trend as China in the two periods. Precipitation was the dominant climatic factor of NDVI in China, and the effect of temperature on greenness increased with warming from T1 to T2. In a relatively arid region (R1), the effect of precipitation in T2 was further strengthened compared to T1. Meanwhile, the effect of minimum temperature in T2 also increased compared with T1 in a relatively humid region (R2), becoming the major climatic determinant. In addition to the regional differentiation, spatial variability was investigated by comparing normalized coefficients of GWR for climatic determinants; this showed significant spatial heterogeneity within each region. Temperature impact areas also existed within precipitation-dominated regions (R1 and R3), where areas of precipitation impact expanded from T1 to T2. Furthermore, regression coefficients between NDVI dynamics and climate variability revealed relationships between regional differentiation and spatial variability. For example, the increasing precipitation rate could mediate the adverse impacts on greenness caused by the higher warming rate in relatively arid regions (R1).

Significant increases in vegetation cover on the Loess Plateau since the early 2000s have been well documented. However, the relevant hydrological effects are still unclear. Here, we investigated the changes in actual evapotranspiration (ET a ) from 2000 to 2016 and related them to climate change and vegetation greening in Yanhe River basin (YRB), a typical hilly-gully basin on the Loess Plateau, by using the remote-sensing based VIP model. Results showed that the annual ET a in the YRB increased significantly with a trend of 3.45mmyr -1 (p<0.01) and changes of ET a in summer months dominated the annual trend. Partial correlation analysis suggested that vegetation greening was the dominant driving factor of ET a inter-annual variations in 56% area of YRB. Model simulation experiments illustrated that relative contributions of NDVI, precipitation, and potential evapotranspiration (ET p ) to the ET a trend were 93.0%, 18.1%, and -7.4%, respectively. Vegetation greening, which is closely related to the Grain for Green (GFG) afforestation, was the main driver to the long-term tendency of water consumption in the YRB. This study highlights potential water demanding conflicts between the socio-economic system and the natural ecosystem on the Loess Plateau due to the rapid vegetation expansion in this water-limited area., (Copyright © 2018. Published by Elsevier B.V.)

Sea surface temperatures (SSTs) strongly influence atmospheric circulation and the Earth's climate, which in turn significantly affects vegetation productivity. Most of the previous studies on the subject have focused on links between the El Niño-Southern Oscillation (ENSO) and vegetation productivity, but few studies have addressed the effects of West Pacific Warm Pool (WPWP) on that although the early stages of the ENSO phenomenon may first develop there. In this paper, we use the mean SST values in the WPWP to construct a climate index, known as the WPWP index (WPI), and study the impacts of the WPWP on global vegetation productivity. We provide evidence for a robust link among the alternating warm and cool WPI pattern, terrestrial vegetation productivity and carbon balance. The analysis is based on both satellite observations and model simulations. The results of this study show that the warm and cool WPWP phases have inverse effects on land surface temperature and precipitation. A warm (cool) WPWP is associated with a warmer (cooler) climate on global land surfaces as well as a drier (wetter) climate in southern hemisphere, and hence enhances (suppresses) vegetation productivity in the latitudes of approximately 10-70°N and suppresses (enhances) vegetation growth in the latitudes of approximately 10-30°S. The underlying mechanism is also discussed. The WPI serves as a meaningful climate index for studying the ocean-vegetation teleconnections., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Vegetation in Northern Hemisphere, being sensitive to climate change, plays an important role in the carbon cycles between land and the atmosphere. The response of vegetation to climate change was analyzed at pixel, biome and regional scale in Amur-Heilongjiang River Basin (AHRB) for growing season, spring, summer and autumn using Normalized Difference Vegetation Index and gridded climate data for the period 1982-2015. NDVI and climate variables trend detection methods and correlation analysis were applied. The potential impacts of human activities on growing season NDVI dynamics were investigated further using residual trend analysis. Results showed that at river basin scale, growing season vegetation experienced a discontinuous greening trend with two reversals, demonstrating that NDVI initially increased to mid-1990s, then declined to mid-2000s, and finally rebounded to 2015. This may be attributed to the shifting between drought and wet trends, indicating growing season NDVI was mainly regulated by precipitation. Temperature was the dominant factor on affecting spring vegetation growth while autumn NDVI showed negative correlation with precipitation due to the relation of precipitation with sunshine hours available for photosynthesis. The response of vegetation growth to climatic variations varied among vegetation types. Grassland NDVI exhibited positive correlation with precipitation in all time ranges. NDVI of needleleaved forest, broadleaved forest, mixed forest and woodland were positively correlated with temperature in all seasons, while showing significant negative correlation with autumn precipitation. Residual trend analysis revealed that human activities might lead to the vegetation degradation in China farming zone of AHRB. Fires also play an important role in regulating vegetation dynamics in the region. Results of our analysis can be used by national governments from three countries of AHRB in managing and negotiating vegetation resources of the region., (Copyright © 2018. Published by Elsevier B.V.)

Widespread changes in arctic and boreal Normalized Difference Vegetation Index (NDVI) values captured by satellite platforms indicate that northern ecosystems are experiencing rapid ecological change in response to climate warming. Increasing temperatures and altered hydrology are driving shifts in ecosystem biophysical properties that, observed by satellites, manifest as long-term changes in regional NDVI. In an effort to examine the underlying ecological drivers of these changes, we used field-scale remote sensing of NDVI to track peatland vegetation in experiments that manipulated hydrology, temperature, and carbon dioxide (CO 2 ) levels. In addition to NDVI, we measured percent cover by species and leaf area index (LAI). We monitored two peatland types broadly representative of the boreal region. One site was a rich fen located near Fairbanks, Alaska, at the Alaska Peatland Experiment (APEX), and the second site was a nutrient-poor bog located in Northern Minnesota within the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment. We found that NDVI decreased with long-term reductions in soil moisture at the APEX site, coincident with a decrease in photosynthetic leaf area and the relative abundance of sedges. We observed increasing NDVI with elevated temperature at the SPRUCE site, associated with an increase in the relative abundance of shrubs and a decrease in forb cover. Warming treatments at the SPRUCE site also led to increases in the LAI of the shrub layer. We found no strong effects of elevated CO 2 on community composition. Our findings support recent studies suggesting that changes in NDVI observed from satellite platforms may be the result of changes in community composition and ecosystem structure in response to climate warming., (© 2018 John Wiley & Sons Ltd.)

Interannual variations of photosynthesis in tropical seasonally dry vegetation are one of the dominant drivers to interannual variations of atmospheric CO 2 growth rate. Yet, the seasonal differences in the response of photosynthesis to climate variations in these ecosystems remain poorly understood. Here using Normalized Difference Vegetation Index (NDVI), we explored the response of photosynthesis of seasonally dry tropical vegetation to climatic variations in the dry and the wet seasons during the past three decades. We found significant (p < 0.01) differences between dry and wet seasons in the interannual response of photosynthesis to temperature (γ int ) and to precipitation (δ int ). γ int is ~1% °C -1 more negative and δ int is ~8% 100 mm -1 more positive in the dry season than in the wet season. Further analyses show that the seasonal difference in γ int can be explained by background moisture and temperature conditions. Positive γ int occurred in wet season where mean temperature is lower than 27°C and precipitation is at least 60 mm larger than potential evapotranspiration. Two widely used Gross Primary Productivity (GPP) estimates (empirical modeling by machine-learning algorithm applied to flux tower measurements, and nine process-based carbon cycle models) were examined for the GPP-climate relationship over wet and dry seasons. The GPP derived from empirical modeling can partly reproduce the divergence of γ int , while most process models cannot. The overestimate by process models on negative impacts by warmer temperature during the wet season highlights the shortcomings of current carbon cycle models in representing interactive impacts of temperature and moisture on photosynthesis. Improving representations on soil water uptake, leaf temperature, nitrogen cycling, and soil moisture may help improve modeling skills in reproducing seasonal differences of photosynthesis-climate relationship and thus the projection for impacts of climate change on tropical carbon cycle., (© 2018 John Wiley & Sons Ltd.)

Climate and land-use change are the major drivers of global biodiversity loss. Their effects are particularly acute for wide-ranging consumers, but little is known about how these factors interact to affect the abundance of large carnivores and their herbivore prey. We analyzed population densities of a primary and secondary consumer (mule deer, Odocoileus hemionus, and mountain lion, Puma concolor) across a climatic gradient in western North America by combining satellite-based maps of plant productivity with estimates of animal abundance and foraging area derived from Global Positioning Systems telemetry data (GPS). Mule deer density exhibited a positive, linear relationship with plant productivity (r 2  = 0.58), varying by a factor of 18 across the climate-vegetation gradient (range: 38-697 individuals/100 km 2 ). Mountain lion home range size decreased in response to increasing primary productivity and consequent changes in the abundance of their herbivore prey (range: 20-450 km 2 ). This pattern resulted in a strong, positive association between plant productivity and mountain lion density (r 2  = 0.67). Despite varying densities, the ratio of prey to predator remained constant across the climatic gradient (mean ± SE = 363 ± 29 mule deer/mountain lion), suggesting that the determinacy of the effect of primary productivity on consumer density was conserved across trophic levels. As droughts and longer term climate changes reduce the suitability of marginal habitats, consumer home ranges will expand in order for individuals to meet basic nutritional requirements. These changes portend decreases in the abundance of large-bodied, wide-ranging wildlife through climatically driven reductions in carrying capacity, as well as increased human-wildlife interactions stemming from anthropogenic land use and habitat fragmentation., (Published 2018. This article is a U.S. Government work and is a public domain in USA.)

Understanding regional water and sediment transport patterns and their responses to climate and land use changes can provide a theoretical basis for the prevention and control of soil erosion, and is an important prerequisite for the integrated development of land and water resources. Based on monthly monitoring meteorological, runoff, and sediment data from 1963 to 2013, combined with the land use data in the 1980s and 2000 and NDVI data, using the Mann-Kendall trend analysis and abrupt change test method, we systematically analyzed the long-term variations of the climate, runoff and sediment transport, with the changes of land use and vegetation coverage being identified in the Xiaonanchuan (XNC) River basin, a typical watershed in the Northwest arid region. Based on the analysis of single element change, the impacts of climate and land use change on water and sediment transport were quantified by the multiple linear regression analysis. Simultaneously, the key action factors were identified. Results showed that air temperature was developing to the polarization, the precipitation increased gradually. A generally warm and wet tendency of climate change and an increased frequency of extreme climate events were found in the XNC River basin. Moreover, the speed and magnitude of climate change were intensified after the 1990s, which was the abrupt change point of the climate. Since the 1980s, with economic and social development, the area of arable land and built land expanded, that of the forest area increased, and the ecological environments were improved in the XNC River basin. Under the dominant driving effects of land use and vegetation coverage change, the runoff and sediment load gradually reduced with the average rate of 1.7×10 6 m 3 ·(10 a) -1 and 1.5×10 8 m 3 ·(10 a) -1 , respectively. Quantifying the influence of land use and climate change on the water and sediment transport indicated that vegetation cove-rage and mean daily maximum temperature were the two key factors affecting the runoff change, while the vegetation coverage and maximum daily precipitation were the two key factors affecting the sediment load change. Under the condition of current climate change, ecological restoration could be one of the most effective ways to prevent water and soil losses in the arid area.

We used the correlation analysis of Larix chinensis tree-ring width chronologies, meteorological data as well as regional NDVI data to reconstruct the NDVI sequence variation of the north and south aspects of Taibai Mountain Nature Reserve in the recent 172 years. The results showed that the NDVI variation of Taibai Mountain Nature Reserve was consistent with plant growth dyna-mics. Hydrothermal condition in growing season was the dominant factor controlling NDVI changes. Tree-ring width was significantly positively correlated with NDVI in growing season. The strongest correlation occurred in July. Thus, we used the long time series of tree ring width index in July to reconstruct the regional historical period variation of NDVI sequence. The results demonstrated that historical changes of July NDVI sequence existed five dense periods and five sparse periods. Further analysis indicated that these periods corresponded with the climate change trends and drought events. The reconstructed July NDVI sequence of both northern and southern slopes of Taibai Mountain Nature Reserve highlighted the existence of quasi periodic variation of 60 years.

Increasing tree mortality from global change drivers such as drought and biotic infestations is a widespread phenomenon, including in the boreal zone where climate changes and feedbacks to the Earth system are relatively large. Despite the importance for science and management communities, our ability to forecast tree mortality at landscape to continental scales is limited. However, two independent information streams have the potential to inform and improve mortality forecasts: repeat forest inventories and satellite remote sensing. Time series of tree-level growth patterns indicate that productivity declines and related temporal dynamics often precede mortality years to decades before death. Plot-level productivity, in turn, has been related to satellite-based indices such as the Normalized difference vegetation index (NDVI). Here we link these two data sources to show that early warning signals of mortality are evident in several NDVI-based metrics up to 24 years before death. We focus on two repeat forest inventories and three NDVI products across western boreal North America where productivity and mortality dynamics are influenced by periodic drought. These data sources capture a range of forest conditions and spatial resolution to highlight the sensitivity and limitations of our approach. Overall, results indicate potential to use satellite NDVI for early warning signals of mortality. Relationships are broadly consistent across inventories, species, and spatial resolutions, although the utility of coarse-scale imagery in the heterogeneous aspen parkland was limited. Longer-term NDVI data and annually remeasured sites with high mortality levels generate the strongest signals, although we still found robust relationships at sites remeasured at a typical 5 year frequency. The approach and relationships developed here can be used as a basis for improving forest mortality models and monitoring systems., (© 2018 John Wiley & Sons Ltd.)

Background: Malaria has historically been entrenched in indigenous populations of the República de Panamá. This scenario occurs despite the fact that successful methods for malaria elimination were developed during the creation of the Panamá Canal. Today, most malaria cases in the República de Panamá affect the Gunas, an indigenous group, which mainly live in autonomous regions of eastern Panamá. Over recent decades several malaria outbreaks have affected the Gunas, and one hypothesis is that such outbreaks could have been exacerbated by climate change, especially by anomalous weather patterns driven by the EL Niño Southern Oscillation (ENSO)., Results: Monthly malaria cases in Guna Yala (1998-2016) were autocorrelated up to 2 months of lag, likely reflecting parasite transmission cycles between humans and mosquitoes, and cyclically for periods of 4 months that might reflect relapses of Plasmodium vivax, the dominant malaria parasite transmitted in Panamá. Moreover, malaria case number was positively associated (P < 0.05) with rainfall (7 months of lag), and negatively with the El Niño 4 index (15 months of lag) and the Normalized Difference Vegetation Index, NDVI (8 months of lag), the sign and magnitude of these associations likely related to the impacts of weather patterns and vegetation on the ecology of Anopheles albimanus, the main malaria vector in Guna Yala. Interannual cycles, of approximately 4-year periods, in monthly malaria case numbers were associated with the El Niño 4 index, a climatic index associated with weather and vegetation dynamics in Guna Yala at seasonal and interannual time scales., Conclusion: The results showed that ENSO, rainfall and NDVI were associated with the number of malaria cases in Guna Yala during the study period. These results highlight the vulnerability of Guna populations to malaria, an infection sensitive to climate change, and call for further studies about weather impacts on malaria vector ecology, as well as the association of malaria vectors with Gunas paying attention to their socio-economic conditions of poverty and cultural differences as an ethnic minority.

South Asia experienced a weakening of summer monsoon circulation in the past several decades, resulting in rainfall decline in wet regions. In comparison with other tropical ecosystems, quantitative assessments of the extent and triggers of vegetation change are lacking in assessing climate-change impacts over South Asia dominated by crops. Here, we use satellite-based Normalized Difference Vegetation Index (NDVI) to quantify spatial-temporal changes in vegetation greenness, and find a widespread annual greening trend that stands in contrast to the weakening of summer monsoon circulation particularly over the last decade. We further show that moisture supply is the primary factor limiting vegetation activity during dry season or in dry region, and cloud cover or temperature would become increasingly important in wet region. Enhanced moisture conditions over dry region, coinciding with the decline in monsoon, are mainly responsible for the widespread greening trend. This result thereby cautions the use of a unified monsoon index to predict South Asia's vegetation dynamics. Current climate-carbon models in general correctly reproduce the dominant control of moisture in the temporal characteristics of vegetation productivity. But the model ensemble cannot exactly reproduce the spatial pattern of satellite-based vegetation change mainly because of biases in climate simulations. The moisture-induced greening over South Asia, which is likely to persist into the wetter future, has significant implications for regional carbon cycling and maintaining food security., (© 2017 John Wiley & Sons Ltd.)

As an important crop growing area, Northeast China (NEC) plays a vital role in China's food security, which has been severely affected by climate change in recent years. Vegetation phenology in this region is sensitive to climate change, and currently, the relationship between the phenology of NEC and climate change remains unclear. In this study, we used a satellite-derived normalized difference vegetation index (NDVI) to obtain the temporal patterns of the land surface phenology in NEC from 2000 to 2015 and validated the results using ground phenology observations. We then explored the relationships among land surface phenology, temperature, precipitation, and sunshine hours for relevant periods. Our results showed that the NEC experienced great phenological changes in terms of spatial heterogeneity during 2000-2015. The spatial patterns of land surface phenology mainly changed with altitude and land cover type. In most regions of NEC, the start date of land surface phenology had advanced by approximately 1.0 days year -1 , and the length of land surface phenology had been prolonged by approximately 1.0 days year -1 except for the needle-leaf and cropland areas, due to the warm conditions. We found that a distinct inter-annual variation in land surface phenology related to climate variables, even if some areas presented non-significant trends. Land surface phenology was coupled with climate variables and distinct responses at different combinations of temperature, precipitation, sunshine hours, altitude, and anthropogenic influence. These findings suggest that remote sensing and our phenology extracting methods hold great potential for helping to understand how land surface phenology is sensitive to global climate change.

The desertification risk affects around 40% of the agricultural land in various regions of Romania. The purpose of this study is to analyse the risk of desertification in the south-west of Romania in the period 1984-2011 using the change vector analysis (CVA) technique and Landsat thematic mapper (TM) satellite images. CVA was applied to combinations of normalised difference vegetation index (NDVI)-albedo, NDVI-bare soil index (BI) and tasselled cap greenness (TCG)-tasselled cap brightness (TCB). The combination NDVI-albedo proved to be the best in assessing the desertification risk, with an overall accuracy of 87.67%, identifying a desertification risk on 25.16% of the studied period. The classification of the maps was performed for the following classes: desertification risk, re-growing and persistence. Four degrees of desertification risk and re-growing were used: low, medium, high and extreme. Using the combination NDVI-albedo, 0.53% of the analysed surface was assessed as having an extreme degree of desertification risk, 3.93% a high degree, 8.72% a medium degree and 11.98% a low degree. The driving forces behind the risk of desertification are both anthropogenic and climatic causes. The anthropogenic causes include the destruction of the irrigation system, deforestation, the destruction of the forest shelterbelts, the fragmentation of agricultural land and its inefficient management. Climatic causes refer to increase of temperatures, frequent and prolonged droughts and decline of the amount of precipitation.