Abstract

To alter the sharply decreasing trend of biodiversity due to human disturbances, much emphasis has been placed on the ecological networks comprised of core areas with high ecological significance and corridors connecting them. The purpose of this paper is to introduce a novel viewpoint and method to identify, analyze and optimize the ecological network of Wuyishan City. The bidirectional least-cost distance model is applied to identify the landscape network in Wuyishan City for the year 1995 and 2005, which can incorportate digraph in ecological network modeling, overcome the limitation of failing to reflect the orientation of the species' dispersal process, and make the process of modeling more convincing by distinguishing flux orientation of “go” and “return” of two random patches. Three new metrics, i.e., network cyclicity, degree of cyclicity, and degree of connectedness, which can quantify the integrity and continuity of network and the relation between network organization and ecological process, are introduced to measure the presence and strength of cyclic pathways in a network and reflect the network's ability to transfer bio-flux. The results show that the ecological network of Wuyishan City in the year 1995 and 2005 have respectively a network size of 18 and 17, degree of connectedness of 1 and 0.7647, network cyclicity of 7.1378 and 8.2570, and degree of cyclicity of 0.3965 and 0.4857, which indicate that the network in Wuyishan City for the year 2005 has strong ability to transfer bio-flux, a high level of eco-process diversity, and a low level of integrity and continuity. It can be concluded that during the past 10 years, different areas of Wuyishan City have gone through landscape degradation and restoration. In the northeast, network components degraded severely and made several patches “isolated islands”, while in the southwest, the network has been developed because of landscape restoration. In particular, the linkages among the patches of natural reserve and its neighborhood increased remarkably, which directly increased the interaction strength and the whole network cyclicity. Then, via scenario analysis, we also identify the patches and linkages that make great contributions to the entire cyclicity and connectedness, such as patches [1,2,3,4,5,6] (Nature reserve and its neighborhood), [12] (bridging the north and west part) and [19] (bridging the south and west part), and linkages among the central patches.

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