Regional-scale vegetation-climate interactions on the Qinghai-Tibet Plateau

2021 ◽  
pp. 101413
Author(s):  
Chan Diao ◽  
Yu Liu ◽  
Liang Zhao ◽  
Ga Zhuo ◽  
Yongqing Zhang

Author(s):  
Siqi Sun ◽  
Yihe Lü ◽  
Da Lü ◽  
Cong Wang

Forests are critical ecosystems for environmental regulation and ecological security maintenance, especially at high altitudes that exhibit sensitivity to climate change and human activities. The Qinghai-Tibet Plateau—the world’s largest water tower region—has been breeding many large rivers in Asia where forests play important roles in water regulation and water quality improvement. However, the vulnerability of these forest ecosystems at the regional scale is still largely unknown. Therefore, the aim of this research is to quantitatively assess the temporal–spatial variability of forest vulnerability on the Qinghai-Tibet Plateau to illustrate the capacity of forests to withstand disturbances. Geographic information system (GIS) and the spatial principal component analysis (SPCA) were used to develop a forest vulnerable index (FVI) to assess the vulnerability of forest ecosystems. This research incorporates 15 factors covering the natural context, environmental disturbances, and socioeconomic impact. Results indicate that the measure of vulnerability was unevenly distributed spatially across the study area, and the whole trend has intensified since 2000. The three factors that contribute the most to the vulnerability of natural contexts, environmental disturbances, and human impacts are slope aspect, landslides, and the distance to the farmland, respectively. The vulnerability is higher in forest areas with lower altitudes, steeper slopes, and southerly directions. These evaluation results can be helpful for forest management in high altitude water tower regions in the forms of forest conservation or restoration planning and implementation towards sustainable development goals.



2019 ◽  
Vol 11 (7) ◽  
pp. 792 ◽  
Author(s):  
Jin Liu ◽  
Linna Chai ◽  
Zheng Lu ◽  
Shaomin Liu ◽  
Yuquan Qu ◽  
...  

High-quality and long time-series soil moisture (SM) data are increasingly required for the Qinghai-Tibet Plateau (QTP) to more accurately and effectively assess climate change. In this study, to evaluate the accuracy and effectiveness of SM data, five passive microwave remotely sensed SM products are collected over the QTP, including those from the soil moisture active passive (SMAP), soil moisture and ocean salinity INRA-CESBIO (SMOS-IC), Fengyun-3B microwave radiation image (FY3B), and two SM products derived from the advanced microwave scanning radiometer 2 (AMSR2). The two AMSR2 products are generated by the land parameter retrieval model (LPRM) and the Japan Aerospace Exploration Agency (JAXA) algorithm, respectively. The SM products are evaluated through a two-stage data comparison method. The first stage is direct validation at the grid scale. Five SM products are compared with corresponding in situ measurements at five in situ networks, including Heihe, Naqu, Pali, Maqu, and Ngari. Another stage is indirect validation at the regional scale, where the uncertainties of the data are quantified by using a three-cornered hat (TCH) method. The results at the regional scale indicate that soil moisture is underestimated by JAXA and overestimated by LPRM, some noise is contained in temporal variations in SMOS-IC, and FY3B has relatively low absolute accuracy. The uncertainty of SMAP is the lowest among the five products over the entire QTP. In the SM map composed by five SM products with the lowest pixel-level uncertainty, 66.64% of the area is covered by SMAP (JAXA: 19.39%, FY3B: 10.83%, LPRM: 2.11%, and SMOS-IC: 1.03%). This study reveals some of the reasons for the different performances of these five SM products, mainly from the perspective of the parameterization schemes of their corresponding retrieval algorithms. Specifically, the parameterization configurations and corresponding input datasets, including the land-surface temperature, the vegetation optical depth, and the soil dielectric mixing model are analyzed and discussed. This study provides quantitative evidence to better understand the uncertainties of SM products and explain errors that originate from the retrieval algorithms.



Parasitology ◽  
2003 ◽  
Vol 127 (S1) ◽  
pp. S121-S131 ◽  
Author(s):  
P. GIRAUDOUX ◽  
P. S. CRAIG ◽  
P. DELATTRE ◽  
G. BAO ◽  
B. BARTHOLOMOT ◽  
...  

An area close to the Qinghai-Tibet plateau region and subject to intensive deforestation contains a large focus of human alveolar echinococcosis while sporadic human cases occur in the Doubs region of eastern France. The current review analyses and compares epidemiological and ecological results obtained in both regions. Analysis of rodent species assemblages within quantified rural landscapes in central China and eastern France shows a significant association between host species for the pathogenic helminth Echinococcus multilocularis, with prevalences of human alveolar echinococcosis and with land area under shrubland or grassland. This suggests that at the regional scale landscape can affect human disease distribution through interaction with small mammal communities and their population dynamics. Lidicker's ROMPA hypothesis helps to explain this association and provides a novel explanation of how landscape changes may result in increased risk of a rodent-borne zoonotic disease.



PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0252149
Author(s):  
Jinke Sun ◽  
Ying Yue ◽  
Haipeng Niu

Estimating net primary productivity (NPP) is significant in global climate change research and carbon cycle. However, there are many uncertainties in different NPP modeling results and the process of NPP is challenging to model on the absence of data. In this study, we used meteorological data as input to simulate vegetation NPP through climate-based model, synthetic model and CASA model. Then, the results from three models were compared with MODIS NPP and observed data over China from 2000 to 2015. The statistics evaluation metrics (Relative Bias (RB), Pearson linear Correlation Coefficient (CC), Root Mean Square Error (RMSE), and Nash-Sutcliffe efficiency coefficient (NSE)) between simulated NPP and MODIS NPP were calculated. The results implied that the CASA-model performed better than the other two models in terms of RB, RMSE, NSE and CC whether on the national or the regional scale. It has a higher CC with 0.51 and a smaller RMSE with 111.96 g C·m-2·yr-1 in the whole country. The synthetic model and CASA-model has the same advantages at some regions, and there are lower RMSE in Southern China (86.35 g C·m-2·yr-1), Xinjiang (85.53 g C·m-2·yr-1) and Qinghai-Tibet Plateau (93.22 g C·m-2·yr-1). The climate-based model has widespread overestimation and large systematic errors, along with worse performances (NSEmax = 0.45) and other metric indexes unsatisfactory, especially Qinghai-Tibet Plateau with relatively lower accuracy because of the unavailable observation data. Overall, the CASA-model is much more ideal for estimating NPP all over China in the absence of data. This study provides a comprehensive intercomparison of different NPP-simulated models and can provide powerful help for researchers to select the appropriate NPP evaluation model.





2021 ◽  
Vol 166 ◽  
pp. 104093
Author(s):  
Fei Peng ◽  
Wenjuan Zhang ◽  
Chimin Lai ◽  
Chengyang Li ◽  
Quangang You ◽  
...  


Author(s):  
Deyan Ge ◽  
Anderson Feijó ◽  
Zhixin Wen ◽  
Alexei V Abramov ◽  
Liang Lu ◽  
...  

Abstract For organisms to survive and prosper in a harsh environment, particularly under rapid climate change, poses tremendous challenges. Recent studies have highlighted the continued loss of megafauna in terrestrial ecosystems and the subsequent surge of small mammals, such as rodents, bats, lagomorphs, and insectivores. However, the ecological partitioning of these animals will likely lead to large variation in their responses to environmental change. In the present study, we investigated the evolutionary history and genetic adaptations of white-bellied rats (Niviventer Marshall, 1976), which are widespread in the natural terrestrial ecosystems in Asia but also known as important zoonotic pathogen vectors and transmitters. The southeastern Qinghai-Tibet Plateau (QHTP) was inferred as the origin center of this genus, with parallel diversification in temperate and tropical niches. Demographic history analyses from mitochondrial and nuclear sequences of Niviventer demonstrated population size increases and range expansion for species in Southeast Asia, and habitat generalists elsewhere. Unexpectedly, population increases were seen in N. eha, which inhabits the highest elevation among Niviventer species. Genome scans of nuclear exons revealed that among the congeneric species, N. eha has the largest number of positively selected genes. Protein functions of these genes are mainly related to olfaction, taste and tumor suppression. Extensive genetic modification presents a major strategy in response to global changes in these alpine species.



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