Retrospective and Predictive Investigation of Fish Kill Events.
Retrospective and Predictive Investigation of Fish Kill Events.
复制标题
鱼类死亡事件的回顾性和预测性调查。
DOI：
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发表时间：
2019
影响因子：
1.2
通讯作者：
L. Escobar
中科院分区：
文献类型：
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作者：
N. Phelps;I. Bueno;D. A. Poo;Sarah J Knowles;Sarah Massarani;Rebecca Rettkowski;Ling Shen;H. Rantala;Paula L F Phelps;L. Escobar
鱼类死亡调查对于了解对水生生态系统的威胁至关重要，可以作为环境破坏的衡量标准以及新出现疾病的早期指标。本研究的目的是分析明尼苏达州野生鱼类种群中与此类事件相关的历史数据，以评估数据的质量和完整性以及鱼类死亡的潜在趋势。在排除具有不完整数据的事件（例如，其中位置没有报告），我们分析了2003年至2013年明尼苏达州自然资源部两个数据库中记录的225起独特的鱼类死亡事件。在所有年份中，报告最多的鱼类死亡发生在2007年（n = 41）和6月份（n = 81）。在大多数鱼类死亡事件（138起）中，出现了Centrarchid物种，其次是鲤科和叉尾目物种，分别出现在53起和40起事件中。环境因素是报告的最常见死亡原因。环境因子模型表明，夜间最高地表温度是鱼类死亡的最关键因素，其次是初级生产力和人为干扰的变化。在这项研究的过程中，发现了数据缺口，包括报告不足，调查不一致，缺乏明确的诊断，使我们的结果的解释具有挑战性。即便如此，了解这些历史趋势和数据缺口对于生成假设和推进数据收集系统以调查未来的鱼类死亡可能是有用的。我们的研究是对鱼类死亡的初步调查，提供了有关可能的区域，季节和鱼类群体的信息，这些信息可以指导积极的环境监测和鱼类流行病学监测。
Fish kill investigations are critical to understanding threats to aquatic ecosystems and can serve as a measure of environmental disruption as well as an early indicator of emerging disease. The goal of this study was to analyze historical data related to such events among wild fish populations in Minnesota in order to assess the quality and completeness of the data and potential trends in fish kills. After excluding events with incomplete data (e.g., in which the location was not reported), we analyzed 225 unique fish kills from 2003 to 2013 that were recorded in two Minnesota Department of Natural Resources databases. The most reported fish kills occurred during 2007 (n = 41) and during the month of June (n = 81) across all years. Centrarchid species were present in the most fish kills (138), followed by cyprinid and ictalurid species, which were present in 53 and 40 events, respectively. Environmental factors were the most common cause of death reported. Models of environmental factors revealed that the maximum nighttime land surface temperature was the most critical factor in fish mortality, followed by changes in primary productivity and human disturbances. During the course of this study, data gaps were identified, including underreporting, inconsistent investigation, and the lack of definitive diagnoses, making interpretation of our results challenging. Even so, understanding these historical trends and data gaps can be useful in generating hypotheses and advancing data collection systems for investigating future fish kills. Our study is a primer investigation of fish kills providing information on the plausible areas, seasons, and fish groups at risk that can guide active environmental monitoring and epidemiological surveillance of fishes.