Industrial development and land use/cover change and their effects on local environment: a case study of Changshu in eastern coastal China

The interactions among industrial development, land use/cover change (LUCC), and environmental effects in Changshu in the eastern coastal China were analyzed using high-resolution Landsat TM data in 1990, 1995, 2000, and 2006, socio-economic data and water environmental quality monitoring data from research institutes and governmental departments. Three phases of industrial development in Changshu were examined (i.e., the three periods of 1990 to 1995, 1995 to 2000, and 2000 to 2006). Besides industrial development and rapid urbanization, land use/cover in Changshu had changed drastically from 1990 to 2006. This change was characterized by major replacements of farmland by urban and rural settlements, artificial ponds, forested and constructed land. Industrialization, urbanization, agricultural structure adjustment, and rural housing construction were the major socio-economic driving forces of LUCC in Changshu. In addition, the annual value of ecosystem services in Changshu decreased slightly during 1990-2000, but increased significantly during 2000-2006. Nevertheless, the local environmental quality in Changshu, especially in rural areas, has not yet been improved significantly. Thus, this paper suggests an increased attention to fully realize the role of land supply in adjustment of environment-friendly industrial structure and urban-rural spatial restructuring, and translating the land management and environmental protection policies into an optimized industrial distribution and land-use pattern.

A methodology of characterizing status and trend of land changes in oases: A case study of Sangong River watershed, Xinjiang, China

National Natural Science Foundation of China [40471134]; program of Lights of the West China by the Chinese Academy of Science

Construction of habitat suitability models (HSMs) for benthic macroinvertebrate and their applications to instream environmental flows: A case study in Xiangxi River of Three Gorges Reservior region, China

Based on a long-term ecological monitoring, the present study chose the most dominant benthic macroinvertebrate (Baetis spp.) as target organisms in Xiangxi River, built the habitat suitability models (HSMs) for water depth, current velocity and substrate, respectively, which is the first aquatic organisms model for habitat suitability in the Chinese Mainland with a long-term consecutive in situ measurement. In order to protect the biointegrity and function of the river ecosystem, the theory system of instream environmental flow should be categorized into three hierarchies, namely minimum required instream flow (hydrological level), minimum instream environmental flow (biospecies level), and optimum instream environmental flow (ecosystem level). These three hierarchies of instream environmental flow models were then constructed with the hydrological and weighted usable area (WUA) method. The results show that the minimum required instream flow of Xiangxi River calculated by the Tennant method (10% of the mean annual flow) was 0.615 m(3) s(-1); the minimum instream environmental flow accounted for 19.22% of the mean annual flow (namely 1.182 m(3) s(-1)), which was the damaged river channel. ow in the dry season; and 42.91% of the mean annual flow (namely 2.639 m(3) s(-1)) should be viewed as the optimum instream environmental flow in order to protect the health of the river ecosystem, maintain the instream biodiversity, and reduce the impact of small hydropower stations nearby the Xiangxi River. We recommend that the hydrological and biological methods can help establish better instream environmental. ow models and design best management practices for use in the small hydropower station project. (C) 2008 National Natural Science Foundation of China and Chinese Academy of Sciences. Published by Elsevier Limited and Science in China Press. All rights reserved.

A nonlinear model for assessing multiple probabilistic risks: A case study in South five-island of Changdao National Nature Reserve in China

Several methods for estimating the potential impacts caused by multiple probabilistic risks have been suggested. These existing methods mostly rely on the weight sum algorithm to address the need for integrated risk assessment. This paper develops a nonlinear model to perform such an assessment. The joint probability algorithm has been applied to the model development. An application of the developed model in South five-island of Changdao National Nature Reserve, China, combining remote sensing data and a GIS technique, provides a reasonable risk assessment. Based on the case study, we discuss the feasibility of the model. We propose that the model has the potential for use in identifying the regional primary stressor, investigating the most vulnerable habitat, and assessing the integrated impact of multiple stressors. (C) 2006 Elsevier Ltd. All rights reserved.