基于模型的萨利希海浮游动物生物量的季节和区域变化及其对观测结果的评价

IF 3.8 3区 地球科学 Q1 OCEANOGRAPHY
Karyn D. Suchy , Elise Olson , Susan E. Allen , Moira Galbraith , BethElLee Herrmann , Julie E. Keister , R. Ian Perry , Akash R. Sastri , Kelly Young
{"title":"基于模型的萨利希海浮游动物生物量的季节和区域变化及其对观测结果的评价","authors":"Karyn D. Suchy ,&nbsp;Elise Olson ,&nbsp;Susan E. Allen ,&nbsp;Moira Galbraith ,&nbsp;BethElLee Herrmann ,&nbsp;Julie E. Keister ,&nbsp;R. Ian Perry ,&nbsp;Akash R. Sastri ,&nbsp;Kelly Young","doi":"10.1016/j.pocean.2023.103171","DOIUrl":null,"url":null,"abstract":"<div><p>We used a three-dimensional coupled biophysical model to examine zooplankton dynamics in the Salish Sea, NE Pacific. First, we evaluated the two zooplankton classes of the SalishSeaCast model using a transboundary zooplankton dataset comprised of observation data from the Canadian and United States waters of the Salish Sea from 2015 to 2019. Model zooplankton classes correspond to micro- and meso-zooplankton whose biomass is tightly coupled to phytoplankton through modelled food web dynamics (Z1) and mesozooplankton with life cycle-based seasonal grazing impacts (Z2). Overall, the model effectively captured seasonal patterns in observed biomass, although with slightly higher biomass estimates for both Z1 and Z2 (Bias = 0.10 and 0.08 g C m<sup>−2</sup>, respectively). Model fit varied regionally, with a weaker model fit being observed in nearshore regions. In addition, an autumn peak in Z2 was observed in the model, but not in the observations, suggesting some seasonal variations in model fit. Following the model evaluation, we used the model to determine seasonal and regional patterns of zooplankton grazing. Seasonally, the main peak in modelled zooplankton biomass increased in April or May in most of the regions defined within the Salish Sea and was driven by grazing on diatoms. Regionally, depth-integrated zooplankton biomass was consistently highest in areas adjacent to regions of strong tidal mixing. In addition, model-based zooplankton grazing was highest in the tidally mixed regions where phytoplankton biomass was high due to advection into the region despite low primary productivity. Our model-based results provide an opportunity to examine bottom-up food web processes at spatio-temporal scales not achievable with <em>in situ</em> sampling and help to elucidate key drivers of lower trophic level dynamics within the Salish Sea.</p></div>","PeriodicalId":20620,"journal":{"name":"Progress in Oceanography","volume":null,"pages":null},"PeriodicalIF":3.8000,"publicationDate":"2023-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0079661123002148/pdfft?md5=7dde40cb1f55f2c9fc24a6fbdc685934&pid=1-s2.0-S0079661123002148-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Seasonal and regional variability of model-based zooplankton biomass in the Salish Sea and evaluation against observations\",\"authors\":\"Karyn D. Suchy ,&nbsp;Elise Olson ,&nbsp;Susan E. Allen ,&nbsp;Moira Galbraith ,&nbsp;BethElLee Herrmann ,&nbsp;Julie E. Keister ,&nbsp;R. Ian Perry ,&nbsp;Akash R. Sastri ,&nbsp;Kelly Young\",\"doi\":\"10.1016/j.pocean.2023.103171\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>We used a three-dimensional coupled biophysical model to examine zooplankton dynamics in the Salish Sea, NE Pacific. First, we evaluated the two zooplankton classes of the SalishSeaCast model using a transboundary zooplankton dataset comprised of observation data from the Canadian and United States waters of the Salish Sea from 2015 to 2019. Model zooplankton classes correspond to micro- and meso-zooplankton whose biomass is tightly coupled to phytoplankton through modelled food web dynamics (Z1) and mesozooplankton with life cycle-based seasonal grazing impacts (Z2). Overall, the model effectively captured seasonal patterns in observed biomass, although with slightly higher biomass estimates for both Z1 and Z2 (Bias = 0.10 and 0.08 g C m<sup>−2</sup>, respectively). Model fit varied regionally, with a weaker model fit being observed in nearshore regions. In addition, an autumn peak in Z2 was observed in the model, but not in the observations, suggesting some seasonal variations in model fit. Following the model evaluation, we used the model to determine seasonal and regional patterns of zooplankton grazing. Seasonally, the main peak in modelled zooplankton biomass increased in April or May in most of the regions defined within the Salish Sea and was driven by grazing on diatoms. Regionally, depth-integrated zooplankton biomass was consistently highest in areas adjacent to regions of strong tidal mixing. In addition, model-based zooplankton grazing was highest in the tidally mixed regions where phytoplankton biomass was high due to advection into the region despite low primary productivity. Our model-based results provide an opportunity to examine bottom-up food web processes at spatio-temporal scales not achievable with <em>in situ</em> sampling and help to elucidate key drivers of lower trophic level dynamics within the Salish Sea.</p></div>\",\"PeriodicalId\":20620,\"journal\":{\"name\":\"Progress in Oceanography\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2023-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0079661123002148/pdfft?md5=7dde40cb1f55f2c9fc24a6fbdc685934&pid=1-s2.0-S0079661123002148-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Progress in Oceanography\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0079661123002148\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"OCEANOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Progress in Oceanography","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0079661123002148","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OCEANOGRAPHY","Score":null,"Total":0}
引用次数: 0

摘要

我们使用三维耦合生物物理模型来研究东北太平洋萨利希海的浮游动物动力学。首先,我们使用由2015-2019年加拿大和美国萨利希海水域的观测数据组成的跨界浮游动物数据集评估了SalishSeaCast模型的两个浮游动物类别。模拟浮游动物类别对应于微浮游动物和中浮游动物,它们的生物量通过模拟食物网动态(Z1)与浮游植物紧密耦合,而中浮游动物具有基于生命周期的季节性放牧影响(Z2)。总体而言,该模型有效地捕获了观测生物量的季节模式,尽管Z1和Z2的生物量估计值略高(偏差分别为0.10和0.08 g C m-2)。模式拟合因区域而异,在近岸地区观测到较弱的模式拟合。此外,在模型中观测到Z2的秋季峰值,但在观测值中没有观测到,表明模型拟合存在一定的季节变化。在模型评估的基础上,我们利用该模型确定了浮游动物的季节和区域放牧模式。季节上,模拟浮游动物生物量的主要高峰出现在4月或5月,这是由对硅藻的放牧所驱动的。从区域上看,深度综合浮游动物生物量在与强潮汐混合区相邻的区域始终最高。此外,基于模型的浮游动物放牧在潮汐混合区最高,尽管初级生产力较低,但由于平流进入该区域,浮游植物生物量较高。我们基于模型的结果提供了一个机会,在时空尺度上考察自下而上的食物网过程,这是原位采样无法实现的,并有助于阐明萨利希海低营养级动态的关键驱动因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Seasonal and regional variability of model-based zooplankton biomass in the Salish Sea and evaluation against observations

We used a three-dimensional coupled biophysical model to examine zooplankton dynamics in the Salish Sea, NE Pacific. First, we evaluated the two zooplankton classes of the SalishSeaCast model using a transboundary zooplankton dataset comprised of observation data from the Canadian and United States waters of the Salish Sea from 2015 to 2019. Model zooplankton classes correspond to micro- and meso-zooplankton whose biomass is tightly coupled to phytoplankton through modelled food web dynamics (Z1) and mesozooplankton with life cycle-based seasonal grazing impacts (Z2). Overall, the model effectively captured seasonal patterns in observed biomass, although with slightly higher biomass estimates for both Z1 and Z2 (Bias = 0.10 and 0.08 g C m−2, respectively). Model fit varied regionally, with a weaker model fit being observed in nearshore regions. In addition, an autumn peak in Z2 was observed in the model, but not in the observations, suggesting some seasonal variations in model fit. Following the model evaluation, we used the model to determine seasonal and regional patterns of zooplankton grazing. Seasonally, the main peak in modelled zooplankton biomass increased in April or May in most of the regions defined within the Salish Sea and was driven by grazing on diatoms. Regionally, depth-integrated zooplankton biomass was consistently highest in areas adjacent to regions of strong tidal mixing. In addition, model-based zooplankton grazing was highest in the tidally mixed regions where phytoplankton biomass was high due to advection into the region despite low primary productivity. Our model-based results provide an opportunity to examine bottom-up food web processes at spatio-temporal scales not achievable with in situ sampling and help to elucidate key drivers of lower trophic level dynamics within the Salish Sea.

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
Progress in Oceanography
Progress in Oceanography 地学-海洋学
CiteScore
7.20
自引率
4.90%
发文量
138
审稿时长
3 months
期刊介绍: Progress in Oceanography publishes the longer, more comprehensive papers that most oceanographers feel are necessary, on occasion, to do justice to their work. Contributions are generally either a review of an aspect of oceanography or a treatise on an expanding oceanographic subject. The articles cover the entire spectrum of disciplines within the science of oceanography. Occasionally volumes are devoted to collections of papers and conference proceedings of exceptional interest. Essential reading for all oceanographers.
×
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