Changes in NDVI and human population in protected areas on the Tibetan Plateau

Understanding the Tibetan Plateau’s role in environmental change has gained increasing scientific attention in light of warming and changes in landmanagement. We examine changes in greenness over the Tibetan Plateau using the Normalized Difference Vegetation Index (NDVI) from the Global Inventory Monitoring and Modeling Study (GIMMS3g) to identify significant changes over the entire plateau, six ecoregions, and protected areas based on a multiyear time series of July imagery from 1982 to 2015. We also test whether there have been changes in human populations in protected areas. There has been relatively little change in mean NDVI over the Tibetan Plateau or ecoregions, however, there were significant changes at the pixel level. There are sixty-nine protected areas on the Tibetan Plateau; sixtytwo protected areas had no significant change in mean NDVI and seven protected areas experienced a significant increase in NDVI. There has been an increase in population within protected areas from 2000 to 2015; however, mean populations significantly increased in two protected areas and significantly decreased in four protected areas. Results suggest a slow greening of the Tibetan Plateau, ecoregions, and protected areas, with a more rapid greening in northern Tibet at the pixel level. Most protected areas are experiencing minor changes in NDVI independent of human population

Vegetation greenness sensitivity to precipitation and its oceanic and terrestrial component in selected biomes and ecoregions of the world

In this study, we conducted a global assessment of the sensitivity of vegetation greenness (VGS) to precipitation and to the estimated Lagrangian precipitation time series of oceanic (PLO) and terrestrial (PLT) origin. The study was carried out for terrestrial ecosystems consisting of 9 biomes and 139 ecoregions during the period of 2001–2018. This analysis aimed to diagnose the vegetative response of vegetation to the dominant component of precipitation, which is of particular interest considering the hydroclimatic characteristics of each ecoregion, climate variability, and changes in the origin of precipitation that may occur in the context of climate change. The enhanced vegetation index (EVI) was used as an indicator of vegetation greenness. Without consideration of semi-arid and arid regions and removing the role of temperature and radiation, the results show the maximum VGS to precipitation in boreal high-latitude ecoregions that belong to boreal forest/taiga: temperate grasslands, savannas, and shrublands. Few ecoregions, mainly in the Amazon basin, show a negative sensitivity. We also found that vegetation greenness is generally more sensitive to the component that contributes the least to precipitation and is less stable throughout the year. Therefore, most vegetation greenness in Europe is sensitive to changes in PLT and less to PLO. In contrast, the boreal forest/taiga in northeast Asia and North America is more sensitive to changes in PLO. Finally, in most South American and African ecoregions, where PLT is crucial, the vegetation is more sensitive to PLO, whereas the contrast occurs in the northern and eastern ecoregions of Australia.Agencia Estatal de Investigación | Ref. PID2021-122314OB-I00Xunta de Galicia | Ref. ED431C 2021/44Xunta de Galicia | Ref. ED481B-2021/134Xunta de Galicia | Ref. ED481D 2022/020Agencia Estatal de Investigación | Ref. RYC2021-034044-

Drought events and their effects on vegetation productivity in China

Many parts of the world have experienced frequent and severe droughts during the last few decades. Most previous studies examined the effects of specific drought events on vegetation productivity. In this study, we characterized the drought events in China from 1982 to 2012 and assessed their effects on vegetation productivity inferred from satellite data. We first assessed the occurrence, spatial extent, frequency, and severity of drought using the Palmer Drought Severity Index (PDSI). We then examined the impacts of droughts on China\u27s terrestrial ecosystems using the Normalized Difference Vegetation Index (NDVI). During the period 1982–2012, China\u27s land area (%) experiencing drought showed an insignificant trend. However, the drought conditions had been more severe over most regions in northern parts of China since the end of the 1990s, indicating that droughts hit these regions more frequently due to the drier climate. The severe droughts substantially reduced annual and seasonal NDVI. The magnitude and direction of the detrended NDVI under drought stress varied with season and vegetation type. The inconsistency between the regional means of PDSI and detrended NDVI could be attributed to different responses of vegetation to drought and the timing, duration, severity, and lag effects of droughts. The negative effects of droughts on vegetation productivity were partly offset by the enhancement of plant growth resulting from factors such as lower cloudiness, warming climate, and human activities (e.g., afforestation, improved agricultural management practices)

Spatiotemporal Variations of Dryland Vegetation Phenology Revealed by Satellite-Observed Fluorescence and Greenness across the North Australian Tropical Transect

Accurate characterization of spatial patterns and temporal variations in dryland vegetation is of great importance for improving our understanding of terrestrial ecosystem functioning under changing climates. Here, we explored the spatiotemporal variability of dryland vegetation phenology using satellite-observed Solar-Induced chlorophyll Fluorescence (SIF) and the Enhanced Vegetation Index (EVI) along the North Australian Tropical Transect (NATT). Substantial impacts of extreme drought and intense wetness on the phenology and productivity of dryland vegetation are observed by both SIF and EVI, especially in the arid/semiarid interior of Australia without detectable seasonality in the dry year of 2018–2019. The greenness-based vegetation index (EVI) can more accurately capture the seasonal and interannual variation in vegetation production than SIF (EVI r2: 0.47~0.86, SIF r2: 0.47~0.78). However, during the brown-down periods, the rate of decline in EVI is evidently slower than that in SIF and in situ measurement of gross primary productivity (GPP), due partially to the advanced seasonality of absorbed photosynthetically active radiation. Over 70% of the variability of EVI (except for Hummock grasslands) and 40% of the variability of SIF (except for shrublands) can be explained by the water-related drivers (rainfall and soil moisture). By contrast, air temperature contributed to 25~40% of the variability of the effective fluorescence yield (SIFyield) across all biomes. In spite of high retrieval noises and variable accuracy in phenological metrics (MAE: 8~60 days), spaceborne SIF observations, offsetting the drawbacks of greenness-based phenology products with a potentially lagged end of the season, have the promising capability of mapping and characterizing the spatiotemporal dynamics of dryland vegetation phenology

Temporal Changes in Coupled Vegetation Phenology and Productivity are Biome-Specific in the Northern Hemisphere

Global warming has greatly stimulated vegetation growth through both extending the growing season and promoting photosynthesis in the Northern Hemisphere (NH). Analyzing the combined dynamics of such trends can potentially improve our current understanding on changes in vegetation functioning and the complex relationship between anthropogenic and climatic drivers. This study aims to analyze the relationships (long-term trends and correlations) of length of vegetation growing season (LOS) and vegetation productivity assessed by the growing season NDVI integral (GSI) in the NH (>30°N) to study any dependency of major biomes that are characterized by different imprint from anthropogenic influence. Spatial patterns of converging/diverging trends in LOS and GSI and temporal changes in the coupling between LOS and GSI are analyzed for major biomes at hemispheric and continental scales from the third generation Global Inventory Monitoring and Modeling Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) dataset for a 32-year period (1982–2013). A quarter area of the NH is covered by converging trends (consistent significant trends in LOS and GSI), whereas diverging trends (opposing significant trends in LOS and GSI) cover about 6% of the region. Diverging trends are observed mainly in high latitudes and arid/semi-arid areas of non-forest biomes (shrublands, savannas, and grasslands), whereas forest biomes and croplands are primarily characterized by converging trends. The study shows spatially-distinct and biome-specific patterns between the continental land masses of Eurasia (EA) and North America (NA). Finally, areas of high positive correlation between LOS and GSI showed to increase during the period of analysis, with areas of significant positive trends in correlation being more widespread in NA as compared to EA. The temporal changes in the coupled vegetation phenology and productivity suggest complex relationships and interactions that are induced by both ongoing climate change and increasingly intensive human disturbances

Recent trends in vegetation greenness in China significantly altered annual evapotranspiration and water yield

There has been growing evidence that vegetation greenness has been increasing in many parts of the northern middle and high latitudes including China during the last three to four decades. However, the effects of increasing vegetation greenness particularly afforestation on the hydrological cycle have been controversial. We used a process-based ecosystem model and a satellite-derived leaf area index (LAI) dataset to examine how the changes in vegetation greenness affected annual evapotranspiration (ET) and water yield for China over the period from 2000 to 2014. Significant trends in vegetation greenness were observed in 26.1% of China\u27s land area. We used two model simulations driven with original and detrended LAI, respectively, to assess the effects of vegetation \u27greening\u27 and \u27browning\u27 on terrestrial ET and water yield. On a per-pixel basis, vegetation greening increased annual ET and decreased water yield, while vegetation browning reduced ET and increased water yield. At the large river basin and national scales, the greening trends also had positive effects on annual ET and had negative effects on water yield. Our results showed that the effects of the changes in vegetation greenness on the hydrological cycle varied with spatial scale. Afforestation efforts perhaps should focus on southern China with larger water supply given the water crisis in northern China and the negative effects of vegetation greening on water yield. Future studies on the effects of the greenness changes on the hydrological cycle are needed to account for the feedbacks to the climate

Climate contributions to vegetation variations in Central Asian drylands:Pre- and post-USSR collapse

Central Asia comprises a large fraction of the world’s drylands, known to be vulnerable to climate change. We analyzed the inter-annual trends and the impact of climate variability in the vegetation greenness for Central Asia from 1982 to 2011 using GIMMS3g normalized difference vegetation index (NDVI) data. In our study, most areas showed an increasing trend during 1982–1991, but experienced a significantly decreasing trend for 1992–2011. Vegetation changes were closely coupled to climate variables (precipitation and temperature) during 1982–1991 and 1992–2011, but the response trajectories differed between these two periods. The warming trend in Central Asia initially enhanced the vegetation greenness before 1991, but the continued warming trend subsequently became a suppressant of further gains in greenness afterwards. Precipitation expanded its influence on larger vegetated areas in 1992–2011 when compared to 1982–1991. Moreover, the time-lag response of plants to rainfall tended to increase after 1992 compared to the pre-1992 period, indicating that plants might have experienced functional transformations to adapt the climate change during the study period. The impact of climate on vegetation was significantly different for the different sub-regions before and after 1992, coinciding with the collapse of the Union of Soviet Socialist Republics (USSR). It was suggested that these spatio-temporal patterns in greenness change and their relationship with climate change for some regions could be explained by the changes in the socio-economic structure resulted from the USSR collapse in late 1991. Our results clearly illustrate the combined influence of climatic/anthropogenic contributions on vegetation growth in Central Asian drylands. Due to the USSR collapse, this region represents a unique case study of the vegetation response to climate changes under different climatic and socio-economic conditions

Assessing the ability of MODIS EVI to estimate terrestrial ecosystem gross primary production of multiple land cover types

© 2016 Elsevier Ltd Terrestrial ecosystem gross primary production (GPP) is the largest component in the global carbon cycle. The enhanced vegetation index (EVI) has been proven to be strongly correlated with annual GPP within several biomes. However, the annual GPP-EVI relationship and associated environmental regulations have not yet been comprehensively investigated across biomes at the global scale. Here we explored relationships between annual integrated EVI (iEVI) and annual GPP observed at 155 flux sites, where GPP was predicted with a log-log model: ln(GPP)=a×ln(iEVI)+b. iEVI was computed from MODIS monthly EVI products following removal of values affected by snow or cold temperature and without calculating growing season duration. Through categorisation of flux sites into 12 land cover types, the ability of iEVI to estimate GPP was considerably improved (R2 from 0.62 to 0.74, RMSE from 454.7 to 368.2 g C m−2 yr−1). The biome-specific GPP-iEVI formulae generally showed a consistent performance in comparison to a global benchmarking dataset (R2 = 0.79, RMSE = 387.8 g C m−2 yr−1). Specifically, iEVI performed better in cropland regions with high productivity but poorer in forests. The ability of iEVI in estimating GPP was better in deciduous biomes (except deciduous broadleaf forest) than in evergreen due to the large seasonal signal in iEVI in deciduous biomes. Likewise, GPP estimated from iEVI was in a closer agreement to global benchmarks at mid and high-latitudes, where deciduous biomes are more common and cloud cover has a smaller effect on remote sensing retrievals. Across biomes, a significant and negative correlation (R2 = 0.37, p < 0.05) was observed between the strength (R2) of GPP-iEVI relationships and mean annual maximum leaf area index (LAImax), and the relationship between the strength and mean annual precipitation followed a similar trend. LAImax also revealed a scaling effect on GPP-iEVI relationships. Our results suggest that iEVI provides a very simple but robust approach to estimate spatial patterns of global annual GPP whereas its effect is comparable to various light-use-efficiency and data-driven models. The impact of vegetation structure on accuracy and sensitivity of EVI in estimating spatial GPP provides valuable clues to improve EVI-based models

Linkages between Atmospheric Circulation, Weather, Climate, Land Cover and Social Dynamics of the Tibetan Plateau

The Tibetan Plateau (TP) is an important landmass that plays a significant role in both regional and global climates. In recent decades, the TP has undergone significant changes due to climate and human activities. Since the 1980s anthropogenic activities, such as the stocking of livestock, land cover change, permafrost degradation, urbanization, highway construction, deforestation and desertification, and unsustainable land management practices, have greatly increased over the TP. As a result, grasslands have undergone rapid degradation and have altered the land surface which in turn has altered the exchange of heat and moisture properties between land and the atmosphere. But gaps still exist in our knowledge of land-atmosphere interactions in the TP and their impacts on weather and climate around the TP, making it difficult to understand the complete energy and water cycles over the region. Moreover, human, and ecological systems are interlinked, and the drivers of change include biophysical, economic, political, social, and cultural elements that operate at different temporal and spatial scales. Current studies do not holistically reflect the complex social-ecological dynamics of the Tibetan Plateau. To increase our understanding of this coupled human-natural system, there is a need for an integrated approach to rendering visible the deep interconnections between the biophysical and social systems of the TP. There is a need for an integrative framework to study the impacts of sedentary and individualized production systems on the health and livelihoods of local communities in the context of land degradation and climate change. To do so, there is a need to understand better the spatial variability and landscape patterns in grassland degradation across the TP. Therefore, the main goal of this dissertation is to contribute to our understanding of the changes over the land surface and how these changes impact the plateau\u27s weather, climate, and social dynamics. This dissertation is structured as three interrelated manuscripts, which each explore specific research questions relating to this larger goal. These manuscripts constitute the three primary papers of this dissertation. The first paper documents the significant association of surface energy flux with vegetation cover, as measured by satellite based AVHRR GIMMS3g normalized difference vegetation index (NDVI) data, during the early growing season of May in the western region of the Tibetan Plateau. In addition, a 1°K increase in the temperature at the 500 hPa level was observed. Based on the identified positive effects of vegetation on the temperature associated with decreased NDVI in the western region of the Tibetan Plateau, I propose a positive energy process for land-atmosphere associations. In the second paper, an increase in Landsat-derived NDVI, i.e., a greening, is identified within the TP, especially during 1990 to 2018 and 2000 to 2018 time periods. Larger median growing season NDVI change values were observed for the Southeast Tibet shrublands and meadows and Tibetan Plateau Alpine Shrublands and Meadows grassland regions, in comparison to the other three regions studied. Land degradation is prominent in the lower and intermediate hillslope positions in comparison to the higher relative topographic positions, and change is more pronounced in the eastern Southeast Tibet shrublands and meadows and Tibetan Plateau Alpine Shrublands and Meadows grasslands. Geomorphons were found to be an effective spatial unit for analysis of hillslope change patterns. Through the extensive literature review presented in third paper, this dissertation recommends using critical physical geography (CPG) to study environmental and social issues in the TP. The conceptual model proposed provides a framework for analysis of the dominant controls, feedback, and interactions between natural, human, socioeconomic, and governance activities, allowing researchers to untangle climate change, land degradation, and vulnerability in the Tibetan Plateau. CPG will further help improve our understanding of the exposure of local people to climate and socio-economic and political change and help policy makers devise appropriate strategies to combat future grassland degradation and to improve the lives and strengthen livelihoods of the inhabitants of the TP