补远江鱼类多样性研究

Research on fish species diversity in the Buyuan River

中文摘要:

      根据澜沧江下游一级支流补远江2006年鱼类洄游季节3~6月的采样数据，分析了该流域鱼类多样性，并结合同期水文、水质数据，应用人工神经网络分析环境因子与鱼类多样性的关联。结果表明，2006年3~6月共采集补远江鱼类34种，隶属于3目8科22属，其中有8种洄游鱼类。3月份多样性指数最高，各月均匀度指数无差异，4、6月优势度指数高，主要是优势种马口鱼、月斑长臀鲃造成。4、5月鱼类组成相似性最高。最低水位对鱼类数量影响最大，其次是平均流速和平均水温；最高水温对鱼类体重影响最大，其次是总磷和溶解氧。人工神经网络下模拟值与实测值相关性高，具较好的适用性。

英文摘要:

      Based on the fish sampling data during fish migration season (March to June, 2006) in the Buyuan River, which is a first order tributary at the downstream of the Lancang River, the fish species diversity was analyzed. With reference to the water quality and hydrological data in the same period, relationship between the environment and the number and weight of fishes were analyzed using artificial neural network (ANN). Results showed that 34 species belonging to 3 orders, 8 families and 22 genera, were collected, among which 8 species were migratory species. Diversity index (H') was at the highest in March, while domination index (Sp) was higher in April and June for the appearance of Mystacoleucus chilopterus and Opsariichthys bidens. There was no significant difference of evenness index (E) among all the sampling months. The lowest water level (LWL) was the most influential factor on the number of fish species, followed by the average runoff velocity (ARV) and average water temperature (AWT). The highest water temperature (HWT) had significant influence on the weight of fish, followed by the total phosphorus and the dissolved oxygen. The simulant values obtained by using ANN were similar with the actual values, which indicated that the ANN method was applicable.