Global S&T Development Trend Analysis Platform of Resources and Environment
Research Highlight: Modeling Technique Could Aid Estimates of Fish Populations | |
admin | |
2018-07-30 | |
发布年 | 2018 |
语种 | 英语 |
国家 | 美国 |
领域 | 资源环境 |
正文(英文) | ![]() School of sardines A team of researchers from Scripps Institution of Oceanography at UC San Diego and UC Santa Cruz demonstrated the potential effectiveness of a method for estimating how many juvenile fish will become adults, defined by fisheries scientists as “recruitment.” This is crucial for knowing how many fish will be available to meet global demand for a key food source. More than three billion people around the world rely on seafood as their main source of protein, and with demand increasing, the study addresses a key obstacle that has prevented fisheries scientists from accurately assessing recruitment. Looking at a global database of stock assessments, the team analyzed 185 populations of fishes ranging from salmon and cod to sardines and anchovies. For the analysis, they used empirical dynamic modeling (EDM), a tool pioneered by Scripps scientist and co-author George Sugihara. While many equation-based modeling systems describe idealized situations in what could be considered an oversimplification, EDM offers an approach that takes into account more complex natural settings to determine relationships between variables; in this case, recruitment and the many factors that could affect it. "For us to know how many fish are available for human consumption, as a first step, we need to better understand recruitment patterns,” said Alfredo Giron, a PhD student at Scripps and co-author of the study led by UC Santa Cruz researcher Steve Munch. “Current models have not successfully solved this problem, but EDM could offer the solution we need." Among fisheries scientists, it is well known that recruitment is different from year to year. Recruitment estimates use initial stock size (the fishable population) and other environmental factors such as water temperature, food availability, and predator abundance to anticipate the number of larvae that survive each year. Stock size has long been the predominant factor used to estimate how many recruits will enter a fishable population in a given year. Recent studies suggest otherwise, that recruitment is virtually independent of stock size and, instead, seems to be more affected by environmental factors. The team found, however, that most of the stock sizes over time that they analyzed are indeed driving recruitment; 107 out of 185 populations showed a detectable relationship between number of adults and recruits. This provides new ways to predict future recruitment, most notably with shorter-lived species. Since the ability to predict recruitment increases with the number of generations sampled, shorter-lived species can be better predicted than their longer-lived counterparts. “Improving recruitment predictability is a huge step towards better understanding variability in fish stocks’ populations,” said Giron, “though we still have a long path forward in applying EDM to better inform fisheries management.” The findings were published July 12 in the scientific journal Fish and Fisheries. The research leaves room for further studies and advances in exploring how the EDM toolkit can be extended and better adapted to fisheries science, particularly in complex multispecies systems and in cases where fluctuation in recruitment is more environment-driven. The Lenfest Ocean Program, the Department of Defense, the Environmental Protection Agency, and the National Science Foundation funded the research. – Chase Martin This story appears in explorations now, Scripps Institution of Oceanography's award-winning ocean and earth science magazine. Sign up to receive our free monthly story roundup.
|
URL | 查看原文 |
来源平台 | Scripps Institution of Oceanography |
文献类型 | 新闻 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/107367 |
专题 | 资源环境科学 |
推荐引用方式 GB/T 7714 | admin. Research Highlight: Modeling Technique Could Aid Estimates of Fish Populations. 2018. |
条目包含的文件 | 条目无相关文件。 |
个性服务 |
推荐该条目 |
保存到收藏夹 |
查看访问统计 |
导出为Endnote文件 |
谷歌学术 |
谷歌学术中相似的文章 |
[admin]的文章 |
百度学术 |
百度学术中相似的文章 |
[admin]的文章 |
必应学术 |
必应学术中相似的文章 |
[admin]的文章 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论