River health assessment in a large river: Bioindicators of fish population

Large river systems are some of the most important aquatic resource for human beings. Unfortunately, ecological integrity of large rivers has been altered severely by human activities. To monitor and manage these ecosystems, a large number of fish-based indexes, especially at community-level have been developed in the past decades. However, community-level methods have presented unique challenges in large river assessment. Comparatively, the population-level method could not only avoid the challenges, but also show many other advantages. Therefore, the aim of this paper is to develop and validate a population-based method applicable for large river. The present study was carried out at the Dongjiang River, with Xenocypris davidi and Hemibarbus labeo being selected as the sentinel indicators. In developing our method we sought population metrics, including growth, survival and reproduction related, to reflect ecological characteristics. Candidate biological metrics were screened for stability, responsiveness and redundancy. The metrics of standard length, average age and fecundity were finally selected for X. davidi, and standard length, weight, average age, and gonadosomatic index for H. labeo. Through the relationship between biological traits and catchments human disturbance information, Xunwu and Anyuan were ultimately chosen as the reference sites for X. davidi and H. labeo, respectively. The star plot areas, representing the degree of similarity with the reference conditions, showed a large variation among different sampling sites, ranging from 0.15 to 0.94 for X. davidi and 0.13 to 1.91 for H. labeo. It was indicated that all sampling sites except for XW could be assigned to the “impaired”. The publicly available census data were used as independent data set to validate our method. The high agreement of both methods suggested that our method could provide an accurate measure for river ecosystem condition. We believe our methodology would be helpful for water resource management of large river. The methodology established here may also serve as a reference of how to develop a population-based index for similar assessments in other large river systems.