Optimal vegetation cover in the Horqin Sands, China. Issue 4 (27th September 2015)

• Record Type: Journal Article
• Authors: Mo, Kangle; Cong, Zhentao; Lei, Huimin
• Is Part Of: Ecohydrology. Volume 9:Issue 4(2016)
• Page Start: 700
• Page End: 711
• Publication Date: 2015-09-27
• Subjects: vegetation cover -- optimality -- ecohydrology -- horqin -- climate change; Ecohydrology -- Periodicals; Hydrology -- Periodicals; Water -- Environmental aspects -- Periodicals; 577.6
• DOI: 10.1002/eco.1668
• Languages: English
• ISSNs: 1936-0584

Abstract

Abstract: Vegetation cover is an important index describing vegetation distribution, which is widely used to study vegetation dynamics. Eagleson presented an optimal vegetation cover hypothesis by the tradeoff of water supply and water demand based on strict mathematical and physical derivation. According to Eagleson's ecohydrological optimality, the positive correlation curve between canopy conductance and vegetation cover is obtained based on water demand; the negative correlation curve between canopy conductance and vegetation cover is obtained based on water supply. The optimal vegetation cover can be estimated by the cross point of these two curves. This method was applied in the Horqin Sands, China. Normalized difference vegetation index of Moderate Resolution Imaging Spectroradiometer dataset was used to calculate vegetation cover and the anthropological disturbance was excluded; meteorological data from three stations were used to estimate optimal vegetation cover. The vegetation cover by ecohydrological optimality (0.318) is consistent with the vegetation cover by remote sensing (0.317). The spatial map of optimal vegetation cover showed a more smooth transit in this area. Under this framework, the vegetation cover would decrease 17% with 10% precipitation decrease and it would decrease 16% with 10% air temperature decrease in this area. This method can be widely applied to determine the appropriate vegetation cover in vegetation restoration practice and to predict vegetation variation under climate change. Copyright © 2015 John Wiley & Sons, Ltd.