深圳市景观生态安全格局源地综合识别

城市生态安全格局是景观生态学研究的热点和重点之一,识别源地是构建生态安全格局的首要环节。在总结已有研究中重要斑块识别方法的基础上,提出了结合景观连通性分析、生物多样性服务评估和生境质量评估来提取重要斑块的方法。以深圳市为研究区,采用基于图论的景观连通性指数、生物多样性服务当量、InVEST模型生境质量评估模块和GIS技术相结合的方法识别生态用地重要斑块。结果表明:深圳市生态斑块依照连通性、生物多样性和生境质量的综合评估分为五级,其中最重要斑块主要分布在龙岗区、盐田区和罗湖区;现行基本生态控制线政策可以保护大部分重要斑块。

The integrated recognition of the source area of the urban ecological security pattern in Shenzhen

Urban ecological security pattern is the focus and emphasis of the landscape ecology research, and identifying the source area is the first link to build the ecological security pattern. This paper summarized the existing researches on the recognition methods of the important patches,overall, the commonly used method is relatively simple, which based on the biodiversity as well as the importance of ecosystem services. However, these methods are biased towards considering the structure and function of the patch itself, while ignoring the importance of patches in the entire matrix structure, as well as the relationship with the surrounding environment. Therefore, this paper attempted to propose a comprehensive recognition method of connectivity analysis, biodiversity service evaluation and habitat quality evaluation to recognize the source area of the ecological security pattern. The research area of this paper is Shenzhen City which as China''s opening up window in the south of Guangdong province. With the unconventional high-speed development, Shenzhen has accumulated a large number of ecological and environmental problems, which have threatened the ecological safety in Shenzhen and has become major restrictive conditions to achieving sustainable urban development. Therefore, the ecological protection is urgent. In this paper, both the functions of the ecological patch itself and the structure importance in the landscape pattern were incorporated when recognizing the important patches. Furthermore, as an integrated approach,the landscape connectivity index, the biodiversity service equivalent and the habitat quality evaluation module of the InVEST model were employed to recognize the important ecological patches. The results are as follows: (1) The total area of the source area of the ecological security pattern is 312.10km², accounting for 15.9% of the total area of the city. The ecological land was divided into five grades in accordance with the landscape connectivity, biodiversity service and habitat quality, the former three grades constituted the source area, in whichthe most important patches are mainly located in Longgang District, Yantian District and Luohu District. It can be seen from the distribution characteristics of the important patches that they are mainly distributed on the mountains. It is suggested that different intensity of management measures should be taken for different levels of source region patches to maximize the efficiency of protection.(2) Superimpose the recognition results with the present ecological control line to analyse the potential ecological security risk. The results shows that more than 95% of the important patches falls within the ecological control line, in this way, this recognition method is feasible to some extent. The small amount of patches exposed outside the control line is ecological risk areas, which mainly distribute in the Kuichong town and Nan''aotown, Longgang District, where we should strengthen the protection.(3) Contrast to the existing research on the recognition of the source area, the method proposed in this paper has a certain degree of improvement, which considered not only the natural factors but also the human factors. It provided a reference for the theory development of landscape pattern and urban ecological conservation practices. However, this paper has some shortcomings, only the scope of Shenzhen City was considered when assessed the habitat quality, making the evaluation of the patches on the edge inaccurate. In addition, dynamic research can be considered in the future work, through the recognition of the source area for the different years to explore the characteristics and change, thus the recognition will be more credible. At last, the rationality and universality of this method needs more practices to verify and validate.