The four antelope species on the Qinghai-Tibet plateau face habitat loss and redistribution to higher latitudes under climate change

Fan

Intl Journal of Climatology

2021

Many studies have examined elevation‐dependent warming in mountain regions of the world, yet little attempt has been undertaken to examine the relationship of the observed warming with both altitude and latitude on a regional scale. Here, based on the mean temperature series (1961–2015) of 105 stations in the Tibetan Plateau, the signals of warming amplification with these two factors are quantified using four groups of methods. The results, highly consistent for the different methods, confirm that the warming for the Tibetan Plateau is not only elevation‐dependent, but also latitude‐dependent, and the magnitude of altitudinal amplification trend is two orders of magnitude larger than that of latitudinal amplification trend on the annual and seasonal scales over the period 1961–2015. The annual warming is amplified by 0.066°C 10 year−1·km−1 of altitude and 0.016 × 10−2°C 10 year−1·km−1 of latitude (or 0.018°C 10 year−1·degree−1 of latitude), with the highest altitudinal (latitudinal) amplification in winter (autumn), followed by autumn (winter) and the lowest in spring and summer. Meanwhile, the estimates of altitude and latitude components of the regional warming shows that the contribution of latitude to the regional warming is larger than that of altitude on the annual scale and for all seasons excepting summer, due primarily to the much larger range of latitude than the range of altitude covered by all the stations used. Moreover, analysis of the number of snow cover days demonstrates that the snow albedo feedback has played a significant role in enhancing the warming in the Tibetan Plateau during the recent sub‐period 1996–2015, due to the decrease of snow cover days in the spring, autumn and winter seasons. These results highlight an integrated picture of Tibetan Plateau warming amplification, and a clear snow albedo feedback effect on the regional amplification, allowing better investigation of impacts and mechanisms.

Section: Discussionmentioning

confidence: 99%

Warming amplification with both altitude and latitude in the Tibetan Plateau

Fan

Intl Journal of Climatology

2021

“…Zhao et al [ 36 ] believed that the altitude of 3100 m is a better criterion to distinguish the two species, and only the plateau zokor is distributed above the altitude of 3100 m. However, below the altitude of 3100 m, it is hard to determine the zokor species. In our study, based on the MaxEnt model [ 22 , 23 ], the suitable habitat and the overlap area of the two species were predicted clearly for the first time. The suitable habitat of the plateau zokors was mainly concentrated in eastern Qinghai and the southern Hexi Corridor in Gansu, while the Gansu zokors were mainly distributed in eastern Qinghai, the southern Hexi Corridor in Gansu, southern Ningxia and north central Shaanxi.…”

Section: Discussionmentioning

confidence: 88%

“…In this study, four plateau zokors and four Gansu zokors were captured in the sympatric area, which was first predicted by the maximum entropy (MaxEnt) model [ 22 , 23 ]. Then, the biodiversity and community structure of the microbiota in different GIT segments of the two zokor species were studied and compared using high-throughput sequencing technology.…”

Section: Introductionmentioning

confidence: 99%

Microbial Biogeography along the Gastrointestinal Tract Segments of Sympatric Subterranean Rodents (Eospalax baileyi and Eospalax cansus)

Liu

Yan

et al. 2021

Animals

Self Cite

In this study, based on high-throughput sequencing technology, the biodiversity and the community structure of microbiota in different GIT segments (the stomach, small intestine, cecum and rectum) of plateau zokors and Gansu zokors were studied and compared. A source tracking analysis for the microbial communities of different GIT segments was carried out using the fast expectation–maximization microbial source tracking (FEAST) method. We found that, for both species, the microbial community richness and diversity of the small intestine were almost the lowest while those of the cecum were the highest among the four segments of the GIT. Beta diversity analyses revealed that the bacterial community structures of different GIT segments were significantly different. As for the comparison between species, the bacterial community compositions of the whole GIT, as well as for each segment, were all significantly different. Source tracking conducted on both zokors indicated that the soil has little effect on the bacterial community of the GIT. A fairly high percentage of rectum source for the bacterial community of the stomach indicated that both zokors may engage in coprophagy.

“…Snow is an important component of the cryosphere (Gao et al, 2021;Shijin et al, 2019;Wang et al, 2019). Its high reflectivity, low thermal conductivity and snowmelt effect have a significant impact on atmospheric circulation, land surface hydrological processes and regional water balance (Liu et al, 2021;Teng et al, 2021;Wen et al, 2019;J. Zhang et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Changes of Snow Cover and Its Relationship With Meteorological Factors on the Qinghai-Tibet Plateau, China

Jin¹,

chen²

2021

Preprint

The Qinghai-Tibet Plateau (TP) is one of the most sensitive areas to climate change, and its ecological environment changes directly or indirectly reflect the global climate change trend. The snow cover ratio (SCR) is an important indicator reflecting the climate and environmental changes of the TP. The daily remote sensing data of snow cover on the TP from 2003 to 2014 were used to study the spatio-temporal distribution of snow cover on the TP. The results have shown that the average snowmelt day on the TP starts on the 103rd day and ends on the 223rd day of a year, and the snowmelt duration has a downward trend. Snow is mainly distributed in the Nyainqentanglha Mountains, Karakoram Mountains and Himalayas. The SCR in summer has a downward trend, while in autumn has a rising trend. This shows that the difference in SCR during the year has enlarged, increasing the risk of snowmelt floods. The SCR is highly correlated with temperature, but weakly correlated with precipitation. Using the long-term remote sensing data of snow cover, the distribution of glacier coverage on the TP can be extracted, in which glaciers on the TP account for about 1%. This research provides an important reference for in-depth understanding of the snow cover changes on the TP and their impact on the environment.