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贝叶斯多状态模型用于测量入侵鲤鱼的运动并评估遥测阵列的性能。

Bayesian multistate models for measuring invasive carp movement and evaluating telemetry array performance.

机构信息

Upper Midwest Environmental Sciences Center, United States Geological Survey, La Crosse, WI, United States of America.

Department of Natural Resource Management, South Dakota State University, Brookings, SD, United States of America.

出版信息

PeerJ. 2024 Aug 6;12:e17834. doi: 10.7717/peerj.17834. eCollection 2024.

Abstract

Understanding the movement patterns of an invasive species can be a powerful tool in designing effective management and control strategies. Here, we used a Bayesian multistate model to investigate the movement of two invasive carp species, silver carp () and bighead carp (), using acoustic telemetry. The invaded portions of the Illinois and Des Plaines Rivers, USA, are a high priority management zone in the broader efforts to combat the spread of invasive carps from reaching the Laurentian Great Lakes. Our main objective was to characterize the rates of upstream and downstream movements by carps between river pools that are maintained by navigation lock and dam structures. However, we also aimed to evaluate the efficacy of the available telemetry infrastructure to monitor carp movements through this system. We found that, on a monthly basis, most individuals of both species remained within their current river pools: averaging 76.2% of silver carp and 75.5% of bighead carp. Conversely, a smaller proportion of silver carp, averaging 14.2%, and bighead carp, averaging 13.9%, moved to downstream river pools. Movements towards upstream pools were the least likely for both species, with silver carp at an average of 6.7% and bighead carp at 7.9%. The highest probabilities for upstream movements were for fish originating from the three most downstream river pools, where most of the population recruitment occurs. However, our evaluation of the telemetry array's effectiveness indicated low probability to detect fish in this portion of the river. We provide insights to enhance the placement and use of these monitoring tools, aiming to deepen our comprehension of these species' movement patterns in the system.

摘要

了解入侵物种的活动模式是设计有效管理和控制策略的有力工具。在这里,我们使用贝叶斯多状态模型,通过声学遥测技术调查了两种入侵鲤鱼(银鲤鱼和大头鱼)的活动模式。美国伊利诺伊州和德斯普兰斯河的受入侵部分是一个高优先级管理区域,目的是更广泛地控制入侵鲤鱼的扩散,以防止它们进入大湖地区的拉伦多亚大湖区。我们的主要目标是描述由船闸和水坝结构维持的河潭之间鲤鱼的上下游移动速度。但是,我们还旨在评估现有的遥测基础设施在监测该系统中鲤鱼运动的功效。我们发现,在每月的基础上,大多数银鱼和大头鱼个体都留在其当前的河潭中:银鱼平均为 76.2%,大头鱼平均为 75.5%。相反,银鱼平均有 14.2%,大头鱼平均有 13.9%的个体移动到下游河潭。两种鱼向上游河潭移动的比例都最小,银鱼平均为 6.7%,大头鱼平均为 7.9%。最下游的三个河潭中的鱼类向上游移动的可能性最高,这些河潭是大多数种群繁殖的地方。但是,我们对遥测数组有效性的评估表明,在该河段检测鱼类的可能性较低。我们提供了一些见解,以增强这些监测工具的放置和使用,旨在加深我们对该系统中这些物种活动模式的理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83fc/11313411/102d47889a5a/peerj-12-17834-g001.jpg

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