日本朝日川潮汐河段两栖鲶鱼(Plecoglossus altivelis)产卵栖息地适宜性评估:对保护和恢复的影响

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Keisuke Yoshida, Hiroshi Yajima, Md. Touhidul Islam, Shijun Pan
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引用次数: 0

摘要

对日本沿河商业渔业至关重要的两栖鲶鱼(Plecoglossus altivelis)正因栖息地退化而出现数量下降。为此,日本正在通过放流幼鱼和培育产卵栖息地来实施修复工作。本研究以朝日川平旦地区为重点,评估了阿育产卵栖息地的适宜性(尤其是潮汐区)及其对保护的影响。通过实地调查和数值分析,研究确定了在数量不断减少的情况下产卵的最佳条件。2020年产卵高峰期的观测结果表明,水温低于20°C有利于产卵,最佳产卵地点的产卵量可达48817枚/平方米。0.85 至 53.0 毫米之间的砾石尺寸被认为是有效产卵的关键。值得注意的是,2019 年建立的人工产卵场没有产卵活动,这可能是由于潮汐造成的盐水入侵。该研究利用三维水动力-水生态系统数值模型,评估了水流、底质和水质对产卵的影响,并通过传感器数据进行了证实。一个重要发现是旭川潮汐河段的盐度与鱼卵密度呈负相关。此外,基于人工智能(AI)的 YOLOv5 模型在水下图像上经过训练后,能有效地检测到阿育鱼的聚集,在区分阿育鱼与同一水生环境中其他共存鱼类物种方面的 F1 分数为 0.757。这种人工智能方法提供了一种非侵入式方法,用于监测阿尤的种群和栖息地偏好。研究强调,成功的产卵栖息地需要最小的盐分入侵,以及最佳的盐度和水流条件。这些见解对于产卵场的开发至关重要,同时强调了潮汐效应和河床条件的管理,以促进阿尤种群的增长和保护水生生态系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessment of spawning habitat suitability for Amphidromous Ayu (Plecoglossus altivelis) in tidal Asahi River sections in Japan: Implications for conservation and restoration
The Amphidromous Ayu (Plecoglossus altivelis), vital for Japan's riverine commercial fisheries, is experiencing population decline due to habitat degradation. In response, Japan is implementing restoration efforts by releasing juvenile fish and cultivating spawning habitats. This study, focusing on the Asahi River's Heidan area, evaluates Ayu spawning habitat suitability, especially in tidal zones, and its conservation implications. Through field surveys and numerical analysis, the research identifies optimal conditions for spawning amid dwindling numbers. Observations from the 2020 peak spawning season showed that water temperatures below 20°C are conducive to spawning, with the best sites producing up to 48,817 eggs/m2. Gravel sizes between 0.85 and 53.0 mm were identified as crucial for effective spawning. Notably, artificial spawning grounds established in 2019 showed no spawning activity, likely due to saline intrusion from tides. Using the three‐dimensional hydrodynamic‐aquatic ecosystem numerical model, the study assesses flow, substrate, and water quality's impact on spawning, corroborated by sensor data. A key finding is the negative correlation between salinity and egg density in tidal sections of the Asahi River. Furthermore, an artificial intelligence (AI)‐based YOLOv5 model, trained on underwater images, effectively detected Ayu aggregations, demonstrating an F1‐score of 0.757 in differentiating Ayu from other coexisting fish species in the same aquatic environment. This AI approach provides a nonintrusive method for monitoring Ayu populations and habitat preferences. The research underlines that successful spawning habitats require minimal saline intrusion, with optimal salinity and flow conditions. These insights are critical for spawning ground development, emphasizing the management of tidal effects and riverbed conditions to bolster Ayu populations and preserve aquatic ecosystems.
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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