Analysis of the spatio-temporal variability of spawning mackerel in the Northeast Atlantic

IF 2.8 2区 生物学 Q1 MARINE & FRESHWATER BIOLOGY Frontiers in Marine Science Pub Date : 2025-01-15 DOI:10.3389/fmars.2024.1461982
Gersom Costas
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Abstract

The northeast Atlantic (NEA) mackerel (Scomber scombrus) is a commercially significant species, with expansive spawning migrations occurring along the continental shelf of northwestern Europe. To identify the main variables influencing the spatial distribution of mackerel eggs, this study analyzed data from egg surveys conducted by the Working Group on Mackerel and Horse Mackerel Egg Surveys (WGMEGS) of the International Council for the Exploration of the Sea (ICES). To achieve this objective, a Random Forest model was used to predict the presence of mackerel eggs based on temporal, geographical, and environmental variables. Applying the Random Forest model to the survey data revealed that the main variables affecting mackerel spawning were the bottom depth, latitude, temperature, and salinity. Subsequently, Quotient Analysis was used to determine the optimal ranges of the key variables identified as influencing mackerel spawning. The results demonstrated a clear preference for spawning at depths between 100 m and 200 m, as well as a consistent preference for the area between 43° and 44° North, corresponding to the Cantabrian Sea. Furthermore, the results indicated that mackerel exhibited a considerable range of temperature tolerance throughout the spawning process, with a preference for cooler waters in the Western area in recent years. Salinity seems to have an effect on spawning at salinities between 35.0 ppm to 35.5 ppm, but results were imprecise. These results contribute to our understanding of how environmental and geographical variables influence the spawning behavior of NEA mackerel.
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东北大西洋鲭鱼产卵的时空变异分析
东北大西洋(NEA)鲭鱼(Scomber scombrus)是一种具有重要商业价值的鱼种,沿着欧洲西北部大陆架进行广泛的产卵洄游。为了确定影响鲭鱼鱼卵空间分布的主要变量,本研究分析了国际海洋考察理事会(ICES)鲭鱼和马鲛鱼卵调查工作组(WGMEGS)进行的鱼卵调查数据。为实现这一目标,使用随机森林模型根据时间、地理和环境变量预测马鲛鱼卵的存在。将随机森林模型应用于调查数据后发现,影响马鲛鱼产卵的主要变量是海底深度、纬度、温度和盐度。随后,利用商数分析法确定了影响青花鱼产卵的主要变量的最佳范围。结果表明,马鲛鱼明显偏好在水深 100 米至 200 米的水域产卵,并始终偏好北纬 43 度至 44 度之间的区域,即坎塔布连海。此外,研究结果表明,青花鱼在整个产卵过程中对温度的耐受范围相当大,近年来更偏好西部地区的凉爽水域。盐度在 35.0 ppm 至 35.5 ppm 之间时似乎对产卵有影响,但结果并不精确。这些结果有助于我们了解环境和地理变量如何影响东北大西洋鲭鱼的产卵行为。
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来源期刊
Frontiers in Marine Science
Frontiers in Marine Science Agricultural and Biological Sciences-Aquatic Science
CiteScore
5.10
自引率
16.20%
发文量
2443
审稿时长
14 weeks
期刊介绍: Frontiers in Marine Science publishes rigorously peer-reviewed research that advances our understanding of all aspects of the environment, biology, ecosystem functioning and human interactions with the oceans. Field Chief Editor Carlos M. Duarte at King Abdullah University of Science and Technology Thuwal is supported by an outstanding Editorial Board of international researchers. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, policy makers and the public worldwide. With the human population predicted to reach 9 billion people by 2050, it is clear that traditional land resources will not suffice to meet the demand for food or energy, required to support high-quality livelihoods. As a result, the oceans are emerging as a source of untapped assets, with new innovative industries, such as aquaculture, marine biotechnology, marine energy and deep-sea mining growing rapidly under a new era characterized by rapid growth of a blue, ocean-based economy. The sustainability of the blue economy is closely dependent on our knowledge about how to mitigate the impacts of the multiple pressures on the ocean ecosystem associated with the increased scale and diversification of industry operations in the ocean and global human pressures on the environment. Therefore, Frontiers in Marine Science particularly welcomes the communication of research outcomes addressing ocean-based solutions for the emerging challenges, including improved forecasting and observational capacities, understanding biodiversity and ecosystem problems, locally and globally, effective management strategies to maintain ocean health, and an improved capacity to sustainably derive resources from the oceans.
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