Interannual and Seasonal Vegetation Changes and Influencing Factors in the Extra-High Mountainous Areas of Southern Tibet

The ecosystem of extra-high mountain areas is very fragile. Understanding local vegetation changes is crucial for projecting ecosystem dynamics. In this paper, we make a case for Himalayan mountain areas to explore vegetation dynamics and their influencing factors. Firstly, the interannual trends of the normalized difference vegetation index (NDVI) were extracted by the Ensemble Empirical Mode Decomposition (EEMD) algorithm and linear regression method. Moreover, the influence of environmental factors on interannual NDVI trends was assessed using the Random Forests algorithm and partial dependence plots. Subsequently, the time-lag effects of seasonal NDVI on different climatic factors were discussed and the effects of these factors on seasonal NDVI changes were determined by partial correlation analysis. The results show that (1) an overall weak upward trend was observed in NDVI variations from 1982 to 2015, and 1989 is considered to be the breakpoint of the NDVI time series; (2) interannual temperature trends and the shortest distance to large lakes were the most important factors in explaining interannual NDVI trends. Temperature trends were positively correlated with NDVI trends. The relationship between the shortest distance to large lakes and the NDVI trend is an inverted U-shaped; (3) the time-lags of NDVI responses to four climatic factors were shorter in Autumn than that in Summer. The NDVI responds quickly to precipitation and downward long-wave radiation; (4) downward long-wave radiation was the main climate factor that influenced NDVI changes in Autumn and the growing season because of the warming effect at night. This study is important to improve the understanding of vegetation changes in mountainous regions.

Attribution Analysis of Dry Season Runoff in the Lhasa River Using an Extended Hydrological Sensitivity Method and a Hydrological Model

In this study, a coupled water–energy balance equation at an arbitrary time scale was proposed as an extension of the Budyko hypothesis. The second mixed partial derivative was selected to represent the magnitude of the interaction. The extended hydrological sensitivity method was used to quantitatively evaluate the impacts of climate change, anthropogenic activities, and their interaction on dry season runoff in the Lhasa River. In addition, an ABCD model, which is a monthly hydrological model included a snowmelt module, was used to calculate the change in soil water and groundwater storage. The Mann–Kendall test, Spearman’s test, dynamic linear model (DLM), and Yamamoto’s method were used to identify trends and change points in hydro-climatic variables from 1956–2016. The results found that dry season runoff increased non-significantly over the last 61 years. Climate change, which caused an increase in dry season runoff, was the dominant factor, followed by anthropogenic activities and their interaction, which led to varying degrees of decrease. This study concluded that the methods tested here performed well in quantifying the relative impacts of climate change, anthropogenic activities, and their interaction on dry season runoff change.

Phenological responses of Icelandic subarctic grasslands to short-term and long-term natural soil warming

The phenology of vegetation, particularly the length of the growing season (LOS; i.e., the period from greenup to senescence), is highly sensitive to climate change, which could imply potent feedbacks to the climate system, for example, by altering the ecosystem carbon (C) balance. In recent decades, the largest extensions of LOS have been reported at high northern latitudes, but further warming-induced LOS extensions may be constrained by too short photoperiod or unfulfilled chilling requirements. Here, we studied subarctic grasslands, which cover a vast area and contain large C stocks, but for which LOS changes under further warming are highly uncertain. We measured LOS extensions of Icelandic subarctic grasslands along natural geothermal soil warming gradients of different age (short term, where the measurements started after 5 years of warming and long term, i.e., warmed since ≥50 years) using ground-level measurements of normalized difference vegetation index. We found that LOS linearly extended with on average 2.1 days per °C soil warming up to the highest soil warming levels (ca. +10°C) and that LOS had the potential to extend at least 1 month. This indicates that the warming impact on LOS in these subarctic grasslands will likely not saturate in the near future. A similar response to short- and long-term warming indicated a strong physiological control of the phenological response of the subarctic grasslands to warming and suggested that genetic adaptations and community changes were likely of minor importance. We conclude that the warming-driven extension of the LOSs of these subarctic grasslands did not saturate up to +10°C warming, and hence that growing seasons of high-latitude grasslands are likely to continue lengthening with future warming (unless genetic adaptations or species shifts do occur). This persistence of the warming-induced extension of LOS has important implications for the C-sink potential of subarctic grasslands under climate change.