Applications of Underwater Video for Imperiled Fish Species Population Monitoring

Pub Date : 2024-06-11 DOI:10.3996/jfwm-23-036
Robert Mollenhauer, Megan G. Bean, Dominik Chilleri, Preston T. Bean
{"title":"Applications of Underwater Video for Imperiled Fish Species Population Monitoring","authors":"Robert Mollenhauer, Megan G. Bean, Dominik Chilleri, Preston T. Bean","doi":"10.3996/jfwm-23-036","DOIUrl":null,"url":null,"abstract":"\n Common freshwater fish sampling methods (e.g., seining and electrofishing) are inherently invasive and often not appropriate for imperiled species. Visual observation methods provide a noninvasive alternative for population monitoring. Despite increasing popularity, the use of underwater video to monitor imperiled fishes is relatively unexplored. We evaluated the efficacy of underwater video to estimate occurrence and abundance of the imperiled Comanche Springs Pupfish Cyprinodon elegans using both point observations and time intervals (surveys). We deployed camera traps at sites within major habitat types (pool, canal, and ciénaga) of Balmorhea State Park, Texas, United States in March and October 2019 (seasons). We detected Comanche Springs at all occupied sites in both seasons when viewing ~30 min of video. The species was detected at 80% of occupied sites when viewing ~10 min and ~5 min of video in March and October, respectively. Comanche Springs Pupfish detection probability was higher in October, with no variability among habitat types. On average, cumulative species detection probability was >0.9 with fifteen 60-s surveys. However, species detection probability of a single survey ranged from 0.02 to 0.62 (mean = 0.14). Although there was no variation between seasons or among habitats, variation was high in the detection of the maximum Comanche Springs Pupfish count among sites even with observations every 5 s. Individual capture probability from a repeated-count abundance model was less variable than species detection probability (0.01-0.33) and generally low (mean = 0.06). Site absolute abundance was generally comparable among major habitats, but with higher uncertainty with increasing maximum count. Our study provides a comprehensive assessment of underwater video for imperiled fish species population monitoring. The findings show a trade-off between processing effort and information loss and limitations associated with imperfect detection and individual capture common to any fish sampling method.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.3996/jfwm-23-036","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Common freshwater fish sampling methods (e.g., seining and electrofishing) are inherently invasive and often not appropriate for imperiled species. Visual observation methods provide a noninvasive alternative for population monitoring. Despite increasing popularity, the use of underwater video to monitor imperiled fishes is relatively unexplored. We evaluated the efficacy of underwater video to estimate occurrence and abundance of the imperiled Comanche Springs Pupfish Cyprinodon elegans using both point observations and time intervals (surveys). We deployed camera traps at sites within major habitat types (pool, canal, and ciénaga) of Balmorhea State Park, Texas, United States in March and October 2019 (seasons). We detected Comanche Springs at all occupied sites in both seasons when viewing ~30 min of video. The species was detected at 80% of occupied sites when viewing ~10 min and ~5 min of video in March and October, respectively. Comanche Springs Pupfish detection probability was higher in October, with no variability among habitat types. On average, cumulative species detection probability was >0.9 with fifteen 60-s surveys. However, species detection probability of a single survey ranged from 0.02 to 0.62 (mean = 0.14). Although there was no variation between seasons or among habitats, variation was high in the detection of the maximum Comanche Springs Pupfish count among sites even with observations every 5 s. Individual capture probability from a repeated-count abundance model was less variable than species detection probability (0.01-0.33) and generally low (mean = 0.06). Site absolute abundance was generally comparable among major habitats, but with higher uncertainty with increasing maximum count. Our study provides a comprehensive assessment of underwater video for imperiled fish species population monitoring. The findings show a trade-off between processing effort and information loss and limitations associated with imperfect detection and individual capture common to any fish sampling method.
分享
查看原文
水下视频在有害鱼类种群监测中的应用
常见的淡水鱼取样方法(如围网和电鱼)本身具有入侵性,通常不适合濒危物种。目视观察法为种群监测提供了一种非侵入性的替代方法。尽管使用水下视频监测濒危鱼类越来越受欢迎,但这种方法还相对缺乏探索。我们利用点观测和时间间隔(调查)评估了水下视频在估算濒危物种科曼奇泉瞳鱼(Cyprinodon elegans)的出现率和丰度方面的功效。我们于 2019 年 3 月和 10 月(季节)在美国得克萨斯州巴尔莫瑞亚州立公园的主要栖息地类型(水池、运河和 ciénaga)内的地点部署了相机陷阱。在观看约 30 分钟的视频时,我们在两个季节的所有占用地点都发现了科曼奇泉。在 3 月和 10 月,观看 ~10 分钟和 ~5 分钟视频时,分别在 80% 的占用地点检测到该物种。科曼奇泉瞳鱼的检测概率在 10 月份较高,不同生境类型之间没有差异。平均而言,15 次 60 秒调查的累计物种探测概率大于 0.9。然而,单次调查的物种检出概率从 0.02 到 0.62 不等(平均值 = 0.14)。重复计数丰度模型得出的个体捕获概率比物种检出概率(0.01-0.33)的变化要小,且普遍较低(平均值 = 0.06)。各主要栖息地的绝对丰度基本相当,但随着最大计数的增加,不确定性也随之增加。我们的研究对用于濒危鱼类种群监测的水下视频进行了全面评估。研究结果表明,在任何鱼类取样方法中,都需要在处理工作量和信息损失之间进行权衡,同时也要考虑与不完全探测和个体捕获相关的局限性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信