我们真的可以使用渔船上没有设计的水声数据来评估海洋物种的丰度和分布吗?南极磷虾的概念验证分析

IF 7 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Ecological Indicators Pub Date : 2025-03-01 Epub Date: 2025-02-28 DOI:10.1016/j.ecolind.2025.113284
J.A. Canseco , E.J. Niklitschek , G. Skaret
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引用次数: 0

摘要

南极大鳞蝽是一种众所周知的南极甲壳类动物,具有重要的经济和生态意义,其管理需要准确和精确的丰度和分布估计。鉴于其地理分布的偏远性、广泛性和巨大的时空变异性,这种估计很难实现。磷虾渔船在正常捕捞作业期间收集的声学数据有很大的潜力来提高这种丰度和分布估计。在目前的工作中,我们验证了一个假设,即在常规捕鱼作业中收集的无设计水声数据可以用于产生丰度和分布估计,其准确度和精度与基于设计的科学调查相似。因此,我们利用常规捕鱼作业期间收集的无设计水声数据,或2017年夏季和2019年夏季在南奥克尼群岛进行的科学调查中收集的基于设计的数据,制作并比较了分布和丰度估计值。采用贝叶斯地质统计学方法,同时考虑和拟合数据的时空相关性,我们测试了不同的自相关结构,并选择了信息量最大的模型。比较包括存在概率(p)、条件密度(d)和相对丰度指数(RAI)估计的均值和变异系数(CV)。此外,我们还模拟了平行和正交样条的场景,并从每个场景中获得了RAI估计值,以与基于设计和无设计的每年估计值进行比较。2017年,使用无设计数据估计的平均RAI (94 421 m2;CV: 14%)比基于设计的数据(60 232 m2;CV: 42%),均在捕鱼区内。2019年,使用无设计数据估计的平均RAI (509 413 m2 CV: 6%)比使用基于设计的数据获得的平均RAI (113 654 m2;CV: 33%)。无设计RAI估计值对于将推断区域从捕鱼区外推到高密度分区高度敏感。另一方面,从小时分辨时空模型到纯空间模型的变化可以忽略不计。尽管观察到的平均估计值存在差异,但两种方法都确定了南奥克尼群岛北部和西北部南极磷虾高存在和密度相似的地区。2017年的无设计数据估计可能受到磷虾分散较大以及常规捕捞作业期间观察到的有效区域较少的影响。我们的研究结果表明,尽管使用了最先进的方法来处理和分析渔船队收集的无设计的声学数据,但它仍然得出了不可靠的RAI估计。当使用平行或正交样条时,与无设计数据相关的偏差和不确定性降低了,尽管正交样条的结果精度提高了,因为它们在2017年和2019年分别仅比真实值低21%和高0.02%。另一种可能的减少偏差的方法是整合来自多艘船的水声信息。
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Can we really use design-free hydroacoustic data from fishing vessels for assessing abundance and distribution of marine species? A proof of concept analysis on Antarctic krill
Euphausia superba is a well-known Antarctic crustacean of great economic and ecological importance, whose management requires accurate and precise abundance and distribution estimates. Such estimates are difficult to achieve given the remoteness, extension, and large spatio-temporal variability of its geographic distribution. Acoustic data collected on board krill fishing vessels during normal fishing operation has a great potential to enhance such abundance and distribution estimates. In the present work we test the hypothesis that design-free hydroacoustic data collected during regular fishing operations can be used to produce abundance and distribution estimates with similar accuracy and precision than design-based scientific surveys. Thus, we produced and compared distribution and abundance estimates produced using either design-free hydroacoustic data collected during regular fishing operations or design-based data from scientific surveys conducted off the South Orkney Islands during summer 2017 and 2019. Following a Bayesian geostatistical approach that considered and fitted simultaneously the spatial and temporal correlation of the data, we tested different auto-correlation structures and selected the most informative models. The comparison included the means and coefficients of variation (CV) of the probability of presence (p), conditional density (d) and relative abundance index (RAI) estimates. In addition, we also simulated scenarios of parallel and orthogonal transects and obtained RAI estimates from each scenario to compare with design-based and design-free estimates for each year. In 2017, the mean RAI estimated using design-free data (94 421 m2; CV: 14 %) was ∼ 50 % higher than the one estimated with design-based data (60 232 m2; CV: 42 %), both within the fishing area. In 2019, the mean RAI estimated using design-free data (509 413 m2 CV: 6 %) was ∼ 5-fold higher than the one obtained using design-based data (113 654 m2; CV: 33 %) in the same area. Design-free RAI estimates were highly sensitive to extrapolating the inference area from fishing to the high-density sub-area. On the other hand, changing from an hourly-resolved spatio-temporal model to a purely spatial model resulted in neglectable changes. Despite observed differences in mean estimates, both methods identified similar areas of high presence and density of Antarctic krill north and north-west of the South Orkney Islands. The 2017 estimate from design-free data was probably affected by a larger dispersion of krill, and a less observed effective area during regular fishing operations. Our results show that despite using state-of-the-art methods for processing and analyzing design-free, acoustic data collected by the fishing fleet, it still yielded unreliable RAI estimates. The bias and uncertainty related to design-free data were reduced when parallel or orthogonal transects were applied although orthogonal transects yielded results with increased accuracy as they were only 21 % lower and 0.02 % higher than the true value in 2017 and 2019, respectively. Other possible approach to minimize bias would be integrating hydroacoustic information from multiple vessels.
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来源期刊
Ecological Indicators
Ecological Indicators 环境科学-环境科学
CiteScore
11.80
自引率
8.70%
发文量
1163
审稿时长
78 days
期刊介绍: The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published. • All aspects of ecological and environmental indicators and indices. • New indicators, and new approaches and methods for indicator development, testing and use. • Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources. • Analysis and research of resource, system- and scale-specific indicators. • Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs. • How research indicators can be transformed into direct application for management purposes. • Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators. • Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.
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