Characteristics of Greening along Altitudinal Gradients on the Qinghai–Tibet Plateau Based on Time-Series Landsat Images

Spatial variations in the difference in elevational shifts between greenness and temperature isolines across the Tibetan Plateau grasslands under warming

Climate warming has induced widespread isotherm shifts toward higher elevations on the Tibetan Plateau, but elevational shifts of vegetation greenness (indicated by Normalized Difference Vegetation Index, NDVI) do not necessarily keep pace with the isotherm shifts. Thus, there should be spatial variations in the difference between the velocities of vertical movement of greenness isolines (VNDVI) and isotherms (VT) across the Tibetan Plateau grasslands. Using satellite-observed NDVI and gridded climate data during 2000-2017, we found uphill shifts of the isotherms in 81.8 % of the surveyed areas, mainly in the eastern, central, southwestern, and northeastern parts, whereas upward shifts of the greenness isolines were observed only in 49.7 % of these areas, mainly in the southeastern, west-central, and southwestern edge of Tibetan Plateau grasslands. In the areas where both the greenness isolines and isotherms shifted uphill, VDNVI was faster than VT in the west-central and northeastern parts, and VNDVI was smaller than VT in the western, south-central, central, and southeastern regions; the difference between VNDVI and VT was positively related with elevational gradient of NDVI (NDVIEG) in the areas where NDVIEG was negative and the temporal trend of NDVI was positive, and was negatively related with NDVIEG and temporal trends of NDVI and temperature in the areas where NDVIEG was positive and temporal trend of NDVI was negative. Our results revealed spatial heterogeneity in the difference in the elevational shifts between the isotherm and vegetation greenness isoline across the Tibetan Plateau grasslands, which is related with both diverse adaptation to local environment (NDVIEG) and complex responses of vegetation greenness to warming in terms of both direction and magnitude. These findings have important implications for the prediction of vegetation production and carbon cycle and the adaptive management of alpine grasslands under climate change.

Distribution patterns of fern species richness along elevations the Tibetan Plateau in China: regional differences and effects of climate change variables

Because of its distinct geological history, frigid temperature, and rich biodiversity, the Tibetan Plateau gives an excellent opportunity to assess the effect of climate change on determining species richness. The distribution patterns of fern species richness and their underlying processes have long been a matter of debate in ecology research, with various hypotheses suggested over the years. Here, we explore richness patterns of fern species in Xizang on the southern and western Tibetan Plateau along an elevational gradient (100-5300 m a.s.l.) and evaluate climatic factors causing the spatial decrease and increase of fern species richness. We used regression and correlation analyses to relate the species richness with elevation and climatic variables. Throughout our research, we identified 441 fern species from 97 genera and 30 families. The Dryopteridaceae family (S = 97) has the highest number of species. All energy-temperature and moisture variables except drought index (DI) had a significant correlation with elevation. The altitude has a unimodal relationship with fern species, and the species richness is the largest at an altitude of 2500 m. The horizontal richness pattern of fern species on the Tibetan Plateau also showed that areas of extremely high species richness are mainly distributed in Zayü and Mêdog County, with an average elevation of 2800 m and 2500 m, respectively. The richness of fern species has a log-linear relationship with moisture-related factors such as moisture index (MI), mean annual precipitation (MAP), and drought index (DI). Because the peak corresponds spatially with the MI index, the unimodal patterns confirm the significance of moisture on fern distributions. Our results showed that mid-altitudes have the highest species richness (high MI), but high elevations have lower richness due to high solar radiation, and low elevations have lower richness due to high temperatures and low precipitation. Twenty-two of the total species are classified as nearly threatened, vulnerable or critically endangered, and varied in elevation from 800 m to 4200 m. Such relationships between the distribution and richness of fern species and climates on the Tibetan Plateau can provide data support for future predictions of the impacts of climate change scenarios on fern species, the ecological protection of representative fern species, and references for the planning and construction of nature reserves in the future.

Reconstructing High-Spatiotemporal-Resolution (30 m and 8-Days) NDVI Time-Series Data for the Qinghai–Tibetan Plateau from 2000–2020

As the largest and highest alpine ecoregion in the world, the Qinghai–Tibetan Plateau (QTP) is extremely sensitive to climate change and has experienced extraordinary warming during the past several decades; this has greatly affected various ecosystem processes in this region such as vegetation production and phenological change. Therefore, numerous studies have investigated changes in vegetation dynamics on the QTP using the satellite-derived normalized-difference vegetation index (NDVI) time-series data provided by the Moderate-Resolution Imaging Spectroradiometer (MODIS). However, the highest spatial resolution of only 250 m for the MODIS NDVI product cannot meet the requirement of vegetation monitoring in heterogeneous topographic areas. In this study, therefore, we generated an 8-day and 30 m resolution NDVI dataset from 2000 to 2020 for the QTP through the fusion of 30 m Landsat and 250 m MODIS NDVI time-series data. This dataset, referred to as QTP-NDVI30, was reconstructed by employing all available Landsat 5/7/8 images (>100,000 scenes) and using our recently developed gap-filling and Savitzky–Golay filtering (GF-SG) method. We improved the original GF-SG approach by incorporating a module to process snow contamination when applied to the QTP. QTP-NDVI30 was carefully evaluated in both quantitative assessments and visual inspections. Compared with reference Landsat images during the growing season in 100 randomly selected subregions across the QTP, the reconstructed 30 m NDVI images have an average mean absolute error (MAE) of 0.022 and a spatial structure similarity (SSIM) above 0.094. We compared QTP-NDVI30 with upscaled cloud-free PlanetScope images in some topographic areas and observed consistent spatial variations in NDVI between them (averaged SSIM = 0.874). We further examined an application of QTP-NDVI30 to detect vegetation green-up dates (GUDs) and found that QTP-NDVI30-derived GUD data show general agreement in spatial patterns with the 250 m MODIS GUD data, but provide richer spatial details (e.g., GUD variations at the subpixel scale). QTP-NDVI30 provides an opportunity to monitor vegetation and investigate land-surface processes in the QTP region at fine spatiotemporal scales.

Climatic Niche of Vegetation Greenness Is Likely to Be Conservative in Degraded Land

Satellite data have been widely used to study changes in vegetation greenness in geographical space; however, this change is rarely considered in climatic space. Here, the climatic niche dynamics of vegetation greenness, represented by the normalized difference vegetation index (NDVI), was quantified in the climate space of the Loess Plateau, a piece of degraded land greening significantly from 2000 to 2018. The niche similarity test was used to examine the niche conservatism of vegetation greenness during the 19 years of restoration. The results show that the climate niche of vegetation greenness is always more similar than expected. The stability niche occupied most parts (83–98%) of their climatic niche, and niche overlap reached 0.52–0.69. Climate niche conservatism suggests that potential greenness constructed by statistical methods could be used as a criterion or baseline for ecosystem function restoration on the Loess Plateau. The study also suggests that the integrated niche similarity test in decision-making for restoration of degraded land will clarify our understanding of the climatic niche dynamics of vegetation greenness and the making of forecasts.