Micro-scale fragmentation of the alpine meadow landscape on the Qinghai-Tibet Plateau under external disturbances

Abstract Detailed characterization of alpine meadow ecosystems using spatial metrics is important to understand the underlying processes of meadow degradation and to inform its proper management. The change in the fragmentation of the alpine meadow on the Qinghai-Tibet Plateau during 2018–2019 was studied in relation to plateau pika (Ochotona curzoniae) population and simulated grazing both independently and interactively. For the first time this study has quantified their effect on the changes in the spatial metrics of ​​bare and healthy meadow patches with the assistance of multi-temporal UAV images in ArcGIS. The spatial index reflecting the fragmentation degree of landscape caused by external disturbances was obtained via spatial analysis in the Fragstats 4.2 software. The results showed that the impact of pika on landscape fragmentation was higher than that of simulated grazing, so pikas populaton should be controlled within the manageable level. The influence of each disturbance on the degree of fragmentation was the highest in high density pika and severe mowing plot, followed by the plots of medium density pika, the control treatments, high density pika, other three interactive effect groups, moderate mowing and severe mowing. In the interactive effect, at the same mowing intensity, landscape fragmentation increased with pika population. At the same pika population, landscape fragmentation increased with mowing intensity. The correlation coefficient between the change in pika burrows and area of bare patches is 0.538, and the proportion of bare patches to the landscape is 0.541. This study provides a reference for studying the feasibility of grassland fragmentation monitoring in the future and the landscape stability of the alpine meadow.

• Publication year

  2021

• Venue

  Catena

• Publication date

  2021-06-01

• Fields of study

  Environmental Science

• Identifiers
  DOI 10.1016/J.CATENA.2021.105220
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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