[Spatio-temporal characteristics of the matching degree of water, soil, and heat resources based on ecosystem services in Central Asia].

[Spatio-temporal characteristics of the matching degree of water, soil, and heat resources based on ecosystem services in Central Asia].

Yan, Xue;Meng, De-Kun;Chen, Di-Tao;Li, Qian;Yang, Tao;Li, Lan-Hai;
Ying yong sheng tai xue bao = The journal of applied ecology 2020 Vol. 31 pp. 794-806
181
yan2020spatiotemporalying

Abstract

The status of matching degree among water, soil, and heat resources determines ecosystem stability and sustainability. Under the framework of ecosystem services related to human well-being, we constructed the matching index of water, soil, and heat resources in Central Asia by the vegetation net primary productivity (NPP) index method based on remote sensing data. We analyzed the spatio-temporal characteristics of the matching degree in Central Asia, and correlations between the matching degree and climatic factors, water use efficiency using trend analysis and the Hurst index. The results showed that the matching degree of water, soil, and heat resources was generally low in Central Asia with a mean value of 9.3. There were obvious differences in the mat-ching degree in different biomes, with the order of alpine forest region > alpine meadow region > typical steppe region > desert steppe region > lake > desert region. From 2000 to 2015, the matching degree of water, soil, and heat resources in each biome and in the whole Central Asia showed a fluctuating downward trend. However, the matching degree changed slightly, with relatively poor persistence. There was a large difference and misalignment of spatial variation in temperature and precipitation, which was the main cause of low matching degree of water, soil, and heat resources. The effect of precipitation on the matching degree of water, soil, and heat resources in Central Asia was stronger than that of the temperature. There was a strong correlation between the matching degree and water use efficiency in Central Asia.

Citation

ID: 107917
Ref Key: yan2020spatiotemporalying
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
107917
Unique Identifier:
10.13287/j.1001-9332.202003.012
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet