Recommendations for advancing mixoplankton research through empirical-model integration

Author:

Millette Nicole C.,Leles Suzana G.,Johnson Matthew D.,Maloney Ashley E.,Brownlee Emily F.,Cohen Natalie R.,Duhamel Solange,Poulton Nicole J.,Princiotta Sarah D.,Stamieszkin Karen,Wilken Susanne,Moeller Holly V.

Abstract

Protist plankton can be divided into three main groups: phytoplankton, zooplankton, and mixoplankton. In situ methods for studying phytoplankton and zooplankton are relatively straightforward since they generally target chlorophyll/photosynthesis or grazing activity, while the integration of both processes within a single cell makes mixoplankton inherently challenging to study. As a result, we understand less about mixoplankton physiology and their role in food webs, biogeochemical cycling, and ecosystems compared to phytoplankton and zooplankton. In this paper, we posit that by merging conventional techniques, such as microscopy and physiological data, with innovative methods like in situ single-cell sorting and omics datasets, in conjunction with a diverse array of modeling approaches ranging from single-cell modeling to comprehensive Earth system models, we can propel mixoplankton research into the forefront of aquatic ecology. We present eight crucial research questions pertaining to mixoplankton and mixotrophy, and briefly outline a combination of existing methods and models that can be used to address each question. Our intent is to encourage more interdisciplinary research on mixoplankton, thereby expanding the scope of data acquisition and knowledge accumulation for this understudied yet critical component of aquatic ecosystems.

Publisher

Frontiers Media SA

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3