分析瑞典电鱼系统 (SERS) 数据时需要考虑的因素,特别是 RivFishTIME 长期河流鱼类调查数据库

Q3 Agricultural and Biological Sciences
Joacim Näslund, Mikael Andersson, Sara Bergek, Erk Degerman, Serena Donadi, Jon Duberg, Kerstin Holmgren, Anders Kinnerbäck, Berit Sers, Thomas Staveley, Helena Strömberg, Erik Myrstener
{"title":"分析瑞典电鱼系统 (SERS) 数据时需要考虑的因素,特别是 RivFishTIME 长期河流鱼类调查数据库","authors":"Joacim Näslund, Mikael Andersson, Sara Bergek, Erk Degerman, Serena Donadi, Jon Duberg, Kerstin Holmgren, Anders Kinnerbäck, Berit Sers, Thomas Staveley, Helena Strömberg, Erik Myrstener","doi":"10.5324/fn.v42i0.5647","DOIUrl":null,"url":null,"abstract":"The published database RivFishTIME (Comte et al. 2021, Global Ecology and Biogeography, doi: 10.1111/geb.13210) includes a large section of time-series data on fish abundance in Swedish rivers from the Swedish Electrofishing RegiSter, SERS. Knowledge about the limitations of the source data are important when extracting and analyzing data and with this brief note we provide some details that may be helpful for interpreting the Swedish time-series. The note highlights the importance of linking vital metadata to extracted focal data when constructing new databases, especially concerning time series data from monitoring programs conducted in non-randomly selected sites with human environmental impacts. Many of the SERS data come from rivers that have been affected by human impact, e.g. liming to mitigate environmental acidification and hydropower dams, since before monitoring was initiated. Data in SERS are also biased towards shallow salmonid habitats, due to the configuration of Swedish monitoring programs. Hence, data from many rivers are not representative of their fish biodiversity in general. This information is vital for appropriate interpretation of fish biodiversity trends. For RivFishTIME analyses considerations are important since Swedish data constitutes a large proportion of the database. We also provide background information about SERS and references to other Swedish databases containing complementary information. Finally, we provide contact information of the SERS database  curators, who can assist prospective analysts with data extraction from SERS.","PeriodicalId":35994,"journal":{"name":"Fauna Norvegica","volume":"30 9","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Considerations needed for analysing data from the Swedish Electrofishing RegiSter (SERS), with special reference to the RivFishTIME database of long-term riverine fish surveys\",\"authors\":\"Joacim Näslund, Mikael Andersson, Sara Bergek, Erk Degerman, Serena Donadi, Jon Duberg, Kerstin Holmgren, Anders Kinnerbäck, Berit Sers, Thomas Staveley, Helena Strömberg, Erik Myrstener\",\"doi\":\"10.5324/fn.v42i0.5647\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The published database RivFishTIME (Comte et al. 2021, Global Ecology and Biogeography, doi: 10.1111/geb.13210) includes a large section of time-series data on fish abundance in Swedish rivers from the Swedish Electrofishing RegiSter, SERS. Knowledge about the limitations of the source data are important when extracting and analyzing data and with this brief note we provide some details that may be helpful for interpreting the Swedish time-series. The note highlights the importance of linking vital metadata to extracted focal data when constructing new databases, especially concerning time series data from monitoring programs conducted in non-randomly selected sites with human environmental impacts. Many of the SERS data come from rivers that have been affected by human impact, e.g. liming to mitigate environmental acidification and hydropower dams, since before monitoring was initiated. Data in SERS are also biased towards shallow salmonid habitats, due to the configuration of Swedish monitoring programs. Hence, data from many rivers are not representative of their fish biodiversity in general. This information is vital for appropriate interpretation of fish biodiversity trends. For RivFishTIME analyses considerations are important since Swedish data constitutes a large proportion of the database. We also provide background information about SERS and references to other Swedish databases containing complementary information. Finally, we provide contact information of the SERS database  curators, who can assist prospective analysts with data extraction from SERS.\",\"PeriodicalId\":35994,\"journal\":{\"name\":\"Fauna Norvegica\",\"volume\":\"30 9\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Fauna Norvegica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5324/fn.v42i0.5647\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Agricultural and Biological Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fauna Norvegica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5324/fn.v42i0.5647","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 0

摘要

已发布的 RivFishTIME 数据库(Comte 等人,2021 年,《全球生态学与生物地理学》,doi: 10.1111/geb.13210)包含了瑞典河流鱼类丰度的大量时间序列数据,这些数据来自瑞典电鱼区(SERS)。在提取和分析数据时,了解源数据的局限性非常重要,我们在本简短说明中提供了一些细节,可能对解读瑞典的时间序列数据有所帮助。本说明强调了在构建新数据库时将重要元数据与提取的焦点数据联系起来的重要性,尤其是在非随机选择的、对人类环境有影响的地点开展的监测项目中的时间序列数据。许多 SERS 数据来自于在监测开始之前就受到人类影响的河流,如为缓解环境酸化而进行的石灰化和水电大坝。由于瑞典监测计划的配置,SERS 中的数据也偏向于浅层鲑鱼栖息地。因此,许多河流的数据并不能代表其鱼类生物多样性的总体情况。这些信息对于适当解释鱼类生物多样性趋势至关重要。对于 RivFishTIME 分析而言,由于瑞典数据在数据库中占很大比例,因此考虑这些因素非常重要。我们还提供了有关 SERS 的背景信息,以及包含补充信息的其他瑞典数据库的参考资料。最后,我们还提供了 SERS 数据库管理员的联系信息,他们可以帮助潜在的分析人员从 SERS 中提取数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Considerations needed for analysing data from the Swedish Electrofishing RegiSter (SERS), with special reference to the RivFishTIME database of long-term riverine fish surveys
The published database RivFishTIME (Comte et al. 2021, Global Ecology and Biogeography, doi: 10.1111/geb.13210) includes a large section of time-series data on fish abundance in Swedish rivers from the Swedish Electrofishing RegiSter, SERS. Knowledge about the limitations of the source data are important when extracting and analyzing data and with this brief note we provide some details that may be helpful for interpreting the Swedish time-series. The note highlights the importance of linking vital metadata to extracted focal data when constructing new databases, especially concerning time series data from monitoring programs conducted in non-randomly selected sites with human environmental impacts. Many of the SERS data come from rivers that have been affected by human impact, e.g. liming to mitigate environmental acidification and hydropower dams, since before monitoring was initiated. Data in SERS are also biased towards shallow salmonid habitats, due to the configuration of Swedish monitoring programs. Hence, data from many rivers are not representative of their fish biodiversity in general. This information is vital for appropriate interpretation of fish biodiversity trends. For RivFishTIME analyses considerations are important since Swedish data constitutes a large proportion of the database. We also provide background information about SERS and references to other Swedish databases containing complementary information. Finally, we provide contact information of the SERS database  curators, who can assist prospective analysts with data extraction from SERS.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Fauna Norvegica
Fauna Norvegica Agricultural and Biological Sciences-Animal Science and Zoology
CiteScore
1.10
自引率
0.00%
发文量
0
审稿时长
28 weeks
×
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