Abstract

Physical cage aquaculture structure can attract native fish species in marine and freshwater ecosystems. Most studies on the effects of cage farms on native fish distribution have been undertaken in marine environments and outside of Asia as the main freshwater cage aquaculture producing region. Many studies have emphasised connections between native fish distribution and feeding time. Previous research also has shown the necessity to use modelling to monitor this effect to reduce data collection costs. Here we analyse the distribution of an endemic fish species, Rasbora maninjau, and a native fish, Gobiopterus sp., associated with tilapia cage aquaculture occurrence using a Maximum Entropy Model (MaxEnt). We find that the application of the MaxEnt model can produce reliable and accurate information on the impacts of cage aquaculture on the native fish species distribution aligning with the more expensive count data method. Our results also suggest that the species-specific interaction between the native fish and cage farms is mainly arising from an interaction between the ecological behaviour of the native fish with dimensions of the environmental condition such as turbidity. Our study therefore highlights the importance for improved appraisal of the ecology of native fish in the cage aquaculture risk assessment.

摘要

实体网箱水产养殖结构可以吸引海洋和淡水生态系统中的本地鱼类。大多数关于网箱养殖场对本地鱼类分布的影响的研究都是在海洋环境和作为主要淡水网箱水产养殖产区的亚洲以外进行的。许多研究都强调了本地鱼类分布与进食时间之间的联系。先前的研究还表明，有必要使用建模来监测这种影响，以降低数据收集成本。在这里，我们分析了一种地方性鱼类Rasbora maninjau和一种本地鱼类Gobiopterus sp的分布., 与使用最大熵模型 (MaxEnt) 的罗非鱼网箱养殖发生相关。我们发现 MaxEnt 模型的应用可以产生关于网箱养殖对本地鱼类物种分布的影响的可靠和准确的信息，与更昂贵的计数数据方法一致。我们的结果还表明，本地鱼类和网箱养殖场之间的物种特异性相互作用主要是由于本地鱼类的生态行为与环境条件（如浑浊度）之间的相互作用。因此，我们的研究强调了在网箱水产养殖风险评估中改进本地鱼类生态评估的重要性。