Dataset Information

The aridity index governs the variation of vegetation characteristics in alpine grassland, Northern Tibet Plateau.

ABSTRACT: The vegetation dynamic (e.g., community productivity) is an important index used to evaluate the ecosystem function of grassland ecosystem. However, the critical factors that affect vegetation biomass are disputed continuously, and most of the debates focus on mean annual precipitation (MAP) or temperature (MAT). This article integrated these two factors, used the aridity index (AI) to describe the dynamics of MAP and MAT, and tested the hypothesis that vegetation traits are influenced primarily by the AI. We sampled 275 plots at 55 sites (five plots at each site, including alpine steppe and meadow) across an alpine grassland of the northern Tibet Plateau, used correlation analysis and redundancy analysis (RDA) to explore which key factors determine the biomass dynamic, and explained the mechanism by which they affect the vegetation biomass in different vegetation types via structural equation modelling (SEM). The results supported our hypothesis, in all of the environmental factors collected, the AI made the greatest contribution to biomass variations in RDA , and the correlation between the AI and biomass was the largest (R = 0.85, p < 0.05). The final SEM also validated our hypothesis that the AI explained 79.3% and 84.4% of the biomass variations in the alpine steppe and the meadow, respectively. Furthermore, we found that the soils with higher carbon to nitrogen ratio and soil total nitrogen had larger biomass, whereas soil organic carbon had a negative effect on biomass in alpine steppe; however, opposite effects of soil factors on biomass were observed in an alpine meadow. The findings demonstrated that the AI was the most critical factor affecting biomass in the alpine grasslands, and different reaction mechanisms of biomass response to the AI existed in the alpine steppe and alpine meadow.

SUBMITTER: Liu B

PROVIDER: S-EPMC6638191 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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The aridity index governs the variation of vegetation characteristics in alpine grassland, Northern Tibet Plateau.

Liu Biying B Sun Jian J Liu Miao M Zeng Tao T Zhu Juntao J

PeerJ 20190715

The vegetation dynamic (e.g., community productivity) is an important index used to evaluate the ecosystem function of grassland ecosystem. However, the critical factors that affect vegetation biomass are disputed continuously, and most of the debates focus on mean annual precipitation (MAP) or temperature (MAT). This article integrated these two factors, used the aridity index (AI) to describe the dynamics of MAP and MAT, and tested the hypothesis that vegetation traits are influenced primarily ...[more]

PMID: 31341736

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Project description:A bibliometric analysis of current research, hotspots, and development trends was used to develop an overall framework of mechanisms of alpine grassland degradation on the Qinghai-Tibet Plateau. This investigation includes data from 1,330 articles on alpine grassland degradation on the Qinghai-Tibet Plateau, acquired from the Chinese Science Citation Database (CSCD) and Web of Science Core Collection (WOS). Research was divided into three themes: spatial scope and management of typical grassland degradation problems, dynamic mechanisms of grassland degradation and effects of ecological engineering, and grassland degradation risk based on remote sensing technology. The results of the analysis showed that the research can be summarized into three aspects: typical grassland degradation identification, dynamic mechanism analysis of grassland degradation, and grassland ecosystem stability strategy. The main findings can summarized, as follows: (1) Ecological analyses using the river source as a typical region defined the formation of "black soil beach" type degraded grasslands in the region, and promoted the ecological environment management and protection of the alpine grassland by discussing the causes of regional ecological environment changes; (2) Dynamic mechanism analyses of climate change and characteristics analyses of grassland vegetation-soil degradation revealed that alpine grassland degradation is the result of multiple main factors; and (3) Risk prediction methods for grassland degradation, methods of grassland management and sustainable countermeasures for agriculture and animal husbandry development, and the development of a comprehensive index of influencing factors on grassland degradation all indicate that selecting the right grassland restoration measures is the key to grassland restoration. Remote sensing monitoring and high-throughput sequencing technology should be used in future research on grassland ecosystems. In addition, multiscale, multidimensional, and multidisciplinary systematic research methods and long-term series data mining could help identify the characteristics and causes of alpine grassland system degradation. These findings can help identify a more effective coordination of landscape, water, lake, field, forest, grass, and sand management for the prevention of alpine grassland degradation.

Project description:A change in precipitation can profoundly change the structure of soil microbial communities, especially in arid and semi-arid areas which are limited by moisture conditions. Therefore, it is crucial to explore how soil bacterial community composition and diversity will respond to variation in precipitation. Here we conducted a precipitation control experiment to simulate precipitation change by reducing and increasing rainfall by 25%, 50%, and 75% in the alpine grasslands of northern Tibet. The composition, diversity, and species interaction network of soil microbial community were studied by high-throughput sequencing, and the relationship between microbial community species and soil environmental factors was analyzed. Our results showed that Proteobacteria (45%-52%) and Actinobacteria (37%-45%) were the dominant bacteria in the soil. The alpha diversity index based on Shannon, Chao1, and Simpson indices revealed that precipitation change had no significant effect on richness and evenness of soil microbial communities. Non-metric multidimensional scaling (NMDS) and analysis of similarities (ANOSIM) showed that a clear separation of soil microbial communities between D2(-50%),D3(-75%) and W2(+50%), W3(+75%) treatments. The microbial interaction network indicated that the water-increasing treatment group had closer connections, and Proteobacteria and Actinomycetes were the core species. Furthermore, there was a stronger positive correlation between species in the water-reducing treatment group, the contribution of Proteobacteria decreased significantly, the role of connecting hub decreased, and Actinomycetes became the most important core microbial species. In addition, soil water content (SWC) and available phosphorus (AP) were closely related to the variations in soil microbial compositions. The findings of this study provide a theoretical basis for the driving mechanism of global climate change on soil microbial community and grassland ecosystem in alpine grassland.

Project description:IntroductionModern agriculture emphasizes the design of cropping systems using ecological function and production services to achieve sustainability. The functional characteristics of plants (grasses vs. legumes) affect changes in soil microbial communities that drive agroecosystem services. Information on the relationship between legume-grass mixtures and soil microorganisms in different ecological zones guides decision-making toward eco-friendly and sustainable forage production. However, it is still poorly understood how cropping patterns affect soil microbial diversity in alpine grasslands and whether this effect varies with altitude.MethodsTo fill this gap in knowledge, we conducted a field study to investigate the effects of growing oats (Avena sativa L.), forage peas (Pisum sativum L.), common cornflower (Vicia sativa L.), and fava beans (Vicia faba L.) in monocultures and mixtures on the soil microbial communities in three ecological zones of the high alpine zone.ResultsWe found that the fungal and bacterial community structure differed among the cropping patterns, particularly the community structure of the legume mixed cropping pattern was very different from that of monocropped oats. In all ecological zones, mixed cropping significantly (p < 0.05) increased the α-diversity of the soil bacteria and fungi compared to oat monoculture. The α-diversity of the soil bacteria tended to increase with increasing elevation (MY [2,513 m] < HZ [2,661 m] < GN [3,203 m]), while the opposite was true for fungi (except for the Chao1 index in HZ, which was the lowest). Mixed cropping increased the abundance of soil fungi and bacteria across ecological zones, particularly the relative abundances of Nitrospira, Nitrososphaera, Phytophthora, and Acari. Factors affecting the bacterial community structure included the cropping pattern, the ecological zone, water content, nitrate-nitrogen, nitrate reductase, and soil capacity, whereas factors affecting fungal community structure included the cropping pattern, the ecological zone, water content, pH, microbial biomass nitrogen, and catalase.DiscussionOur study highlights the variation in soil microbial communities among different in alpine ecological regions and their resilience to cropping systems. Our results also underscore that mixed legume planting is a sustainable and effective forage management practice for the Tibetan Plateau.

Dataset Information

The aridity index governs the variation of vegetation characteristics in alpine grassland, Northern Tibet Plateau.

Publications

The aridity index governs the variation of vegetation characteristics in alpine grassland, Northern Tibet Plateau.

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