The vulnerability of ecosystem structure in the semi-arid area revealed by the functional trait networks

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Date
2022-06
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American English
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Elsevier
Abstract

The ecosystems were characterized by complex, nonlinear interactions determined by different plant functional traits. The characteristics of the multiple relationships between ecosystem functional traits affected the vulnerability to drought. A three-level network analysis on instead of the network metrics, relationships among inter-components, and essential traits was conducted in dryland ecosystems of China. The new network of functional traits included leaf, root, and biomass components was constructed to simulate different aridity conditions. Results show that the multiple relationships of functional traits that co-regulated ecosystem biomass differ along an aridity gradient. The highest network modularity and degree centrality were observed in the semi-arid ecosystems indicating low integration and high sensitivity of semi-arid ecosystems (269% and 23.7% higher than in dry sub-humid site, and 142% and 51.1% higher than arid sites). The leaf quantity strongly affected the connection between functional traits at the semi-arid zone. The semi-arid areawas found to have relatively low resistance to environmental change because of low integration and high sensitivity of the ecosystem structure at that site. An increase of degree centrality of the root traits and trade-off relationships between roots and leaves indicated greater allocation of resources by vecgetation to underground components by the arid ecosystems to increase water absorption. The study reveals the complex relationships between leaf, root, and biomass components, and the essential traits of the ecosystem. It enhanced understanding of the vulnerability of semi-arid ecosystems to environmental change.

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Gao, D., Wang, S., Wei, F., Wu, X., Zhou, S., Wang, L., Li, Z., Chen, P., & Fu, B. (2022). The vulnerability of ecosystem structure in the semi-arid area revealed by the functional trait networks. Ecological Indicators, 139, 108894. https://doi.org/10.1016/j.ecolind.2022.108894
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