• •

### 基于地理加权回归的漫湾库区景观破碎化及影响因子分析

1. 北京师范大学环境学院水环境模拟国家重点实验室, 北京100875
• 收稿日期:2013-05-03 修回日期:2013-08-22 出版日期:2014-07-10 发布日期:2014-07-10
• 作者简介:

作者简介：刘世梁（1976-）,男,山东沂水人,副教授,博士,主要从事景观生态研究。E-mail: shiliangliu@bnu.edu.cn

• 基金资助:
国家自然科学基金项目(50939001)、环保公益项目 (2012090290)、中央高校基本科研业务费专项资金 (105564GK) 资助

### Landscape Fragmentation and Affecting Factors of Manwan Reservoir Based on Geographically Weighted Regression

Shi-liang LIU(), Qi LIU, Cong WANG, Qing-he ZHAO, Li DENG, Shi-kui DONG

1. State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875
• Received:2013-05-03 Revised:2013-08-22 Online:2014-07-10 Published:2014-07-10

Abstract:

Applying Geographic Weighted Regression model, this article analyzed the spatial relationships between landscape fragmentation index-effective mesh size and related factors of Manwan Reservoir, Lancing River, Yunnan Provence. The selected explanatory variables covers factors of nature and human activity, including distance to main road, distance to county, distance to river and slop, aiming to determining the contribution of different factors to fragmentation. The results showed that: all the related factors exhibited significant positive correlations with effective mesh size after dam construction, which indicates these three variables can be used as factors for the spatial analysis of effective mesh size. We compared GWR model with Ordinary Least Square（OLS）model which presented that GWR model gave a much better fitting result with lower AICc value and higher adjusted R2 value. Besides, the spatial distribution of residuals can examine the validity of the results. Apparent gathering characteristic indicated that the results of the model are invalid because the key explanatory factor is lost. Therefore global Moran′s I statistics on the residuals from OLS and GWR models were tested. For all the GWR models global Moran′s I ranges from 0.042 7-0.344 2 (p<0.01), while for all the OLS models it ranges from 0.478 6 to 0.545 8 (p<0.01) which indicated that the GWR models produced smaller global Moran′s I than OLS models with the same explanatory variables and reduced the spatial autocorrelation residuals of the models. Hence a GWR model improved the reliability of the relationships and was the optimization of OLS models. Coefficients of regression models reflect the sensitivity of the effective mesh size to each factor. The big coefficient represented the strong impact explanatory variable had on the effective mesh size. So we got the maximum value of coefficients as the most sensitive factor of effective mesh size. The most sensitive area to distance to road gradually reduced in 1974-1988. Before the dam construction in 1974, road was the most influential factor to the landscape fragmentation of the study area and its affected area occupied by almost 50% of study area, while after the construction and operation of Manwan hydropower station, its affected area reduced to 25% of the study area. However, the most sensitive area to distance to river and slop gradually increased. The most sensitive area to distance to county exhibited a trend of increasing firstly and then reducing. Although the impact of slope on effective mesh size in the three periods was the smallest, it showed a significant change. In terms of spatial distribution, the most sensitive area to distance to river located within 2 km to Manwan dam, the tail of the reservoir and the narrow-shaped part in the middle of the reservoir, which expanded to the entire reservoir area in 1974-2004.

• P901