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      Evolution and Prediction of Landscape Pattern and Habitat Quality Based on CA-Markov and InVEST Model in Hubei Section of Three Gorges Reservoir Area (TGRA)

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      Sustainability
      MDPI AG

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          Abstract

          The spatial pattern of landscape has great influence on the biodiversity provided by ecosystem. Understanding the impact of landscape pattern dynamics on habitat quality is significant in regional biodiversity conservation, ensuring ecological security guarantee, and maintaining the ecological environmental sustainability. Here, combining CA-Markov and InVEST model, we investigated the evolution of landscape pattern and habitat quality, and presented an explanation for variability of biodiversity linked to landscape pattern in Hubei section of Three Gorges Reservoir Area (TGRA). The spatial-temporal evolution characteristic of landscape pattern from 1990 to 2010 were analyzed by Markov chain. Then, the spatial pattern of habitat quality and its variation in three phases were computed by InVEST model. The driving force for landscape variation was explored by using Logistic regression analysis. Next, the CA-Markov model was used to simulate the future landscape pattern in 2020. Finally, future habitat quality maps were obtained by InVEST model predicted landscape maps. The results concluded that, the overall landscape pattern has changed slightly from 1990 to 2010. Woodland, waters and construction land had the greatest variations in proportion among the landscape types. The area of woodland has been decreasing gradually below the average elevation of 140 m, and the area of waters and construction land increased sharply. Logistics regression results indicated that terrain and climate were the most influencing natural factors compared with human factors. The Kappa coefficient reached 0.92, indicating that CA-Markov model had a good performance in future landscape prediction by adding nighttime light data as restriction factor. The biodiversity has been declining over the past 20 years due to the habitat degradation and landscape pattern variation. Overall, the maximum values of habitat degradation index were 0.1188, 0.1194 and 0.1195 respectively, showing a continuously increasing trend from 1990 to 2010. Main urban areas of Yichang city and its surrounding areas has higher habitat degradation index. The average values of habitat quality index of the whole region were 0.8563, 0.8529 and 0.8515 respectively, showing a continuously decreasing trend. The lower habitat quality index mainly located in the urban land as well as the main and tributary banks of the Yangtze River. Under the business as usual scenario, habitat quality continued to maintain the variation trend of the previous decade, showing a reducing habitat quality index and an increasing area of artificial surface. Under the ecological protection scenario, the variation of habitat quality in this scenario represented reverse trend to the previous decade, exhibiting an increase of habitat quality index and an increasing area of woodland and grassland. Construction of Three Gorges Dam, impoundment of Three Gorges Reservoir (TGR), resettlement of Three Gorges Project and urbanization were the most explanatory driving forces for landscape variation and degradation of habitat quality. The research may be useful for understanding the impact of landscape pattern dynamics on biodiversity, and provide scientific basis for optimizing regional natural environment, as well as effective decision-making support to local government for landscape planning and biodiversity conservation.

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          Modeling multiple ecosystem services, biodiversity conservation, commodity production, and tradeoffs at landscape scales

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            The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan

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              Measuring the extent and effectiveness of protected areas as an indicator for meeting global biodiversity targets.

              There are now over 100000 protected areas worldwide, covering over 12% of the Earth's land surface. These areas represent one of the most significant human resource use allocations on the planet. The importance of protected areas is reflected in their widely accepted role as an indicator for global targets and environmental assessments. However, measuring the number and extent of protected areas only provides a unidimensional indicator of political commitment to biodiversity conservation. Data on the geographic location and spatial extent of protected areas will not provide information on a key determinant for meeting global biodiversity targets: 'effectiveness' in conserving biodiversity. Although tools are being devised to assess management effectiveness, there is no globally accepted metric. Nevertheless, the numerical, spatial and geographic attributes of protected areas can be further enhanced by investigation of the biodiversity coverage of these protected areas, using species, habitats or biogeographic classifications. This paper reviews the current global extent of protected areas in terms of geopolitical and habitat coverage, and considers their value as a global indicator of conservation action or response. The paper discusses the role of the World Database on Protected Areas and collection and quality control issues, and identifies areas for improvement, including how conservation effectiveness indicators may be included in the database to improve the value of protected areas data as an indicator for meeting global biodiversity targets.
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                Author and article information

                Journal
                SUSTDE
                Sustainability
                Sustainability
                MDPI AG
                2071-1050
                November 2018
                October 24 2018
                : 10
                : 11
                : 3854
                Article
                10.3390/su10113854
                b68067fe-b56d-437c-8082-a530e84d5c69
                © 2018

                https://creativecommons.org/licenses/by/4.0/

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