摘要
采用池塘围隔对比试验的方法,研究了不同密度(392 ind·m-2、196 ind·m-2、98 ind·m-2、0 ind·m-2)铜锈环棱螺(Bellamya aeruginosa)对藻华水体主要理化因子的影响.实验从2009年9月14日开始,持续60d.结果显示:环棱螺可以明显提高藻华水体的透明度(SD),实验中、后期,三个处理组围隔水体的SD均能保持在60cm以上,而对照组SD改变不明显,波动于29~40.3cm之间;多数时间内处理组水体的溶解氧(DO)含量都显著低于对照组,说明环棱螺的存在可直接或间接降低水体DO浓度.试验表明,单一投放螺类可有效降低藻华水体的叶绿素a(Chl-a)含量,但难以削减营养盐浓度.实验条件下,围隔水体总氮和正磷酸盐浓度的下降趋势均与螺的密度呈现负相关性(R=-0.9851,P〈0.05;R=-0.9678,P〈0.05);对SD、DO、pH、Chl-a、 NH4+-N、NO3--N、PO43--p等7个主要理化指标数据进行了Duncan多重比较分析以及聚类分析,结果显示对照组和处理组在p〈0.05水平上均存在显著差异,说明环棱螺的投放能在一定程度上调控水体质量.
The effect of different densities (392 indom-2, 196 ind.m-2, 98 ind-m-2 and 0 ind-m-2) ofBellamya aeruginosa on the physical and chemical properties of algal bloom water by setting up experimental enclosures in pond were studied. The experiment was carried out from September 14, 2009, and lasted for two months. The results showed that in the middle and late stages, water transparency in low, medium and high density groups was above 60 cm, but that in the control group showed no significant change and fluctuated from 29 cm to 40.3 cm. It indicates that B. aeruginosa can increase the secchi depth (SD) of water. Dissolved oxygen (DO) in the treated groups was significantly lower than that in the control group, suggesting that snails would reduce the DO of water. In addition, our results showed that snails reduced the total Chl-a, but not the concentration of nutrients in the water. The downward trend of TN and pO43-P concentrations showed negative correlation (R=-0.9851, P〈0.05, and R = -0.9678, P〈0.05) with the snail density. The data (SD, DO, pH, Chl-a, NH4+-N, NO3-N and PO43--P) were analyzed by the Duncan multiple comparison and cluster analysis methods, and showed that there were significant differences between the control group and treatment group at P 〈0.05 level. Therefore it is suggested that snails can to some extent improve the water quality.
出处
《生态科学》
CSCD
2010年第5期438-443,共6页
Ecological Science
基金
国家自然科学基金(30771658)
关键词
藻华水体
铜锈环棱螺
围隔实验
多重比较
聚类分析
algal bloom water
Bellamya aeruginosa, enclosure experiment
multiple comparison
cluster analysis