Zooplankton Ecology

Zooplankton Ecology

Zooplankton Ecology

Zooplankton Ecology

eBook

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Overview

This book aims at providing students and researchers an advanced integrative overview on zooplankton ecology, covering marine and freshwater organisms, from microscopic phagotrophic protists, to macro-jellyfishes and active fish larvae. The first book section addresses zooplanktonic organisms and processes, the second section is devoted to zooplankton spatial and temporal distribution patterns and trophic dynamics, and the final section is dedicated to emergent methodological approaches (e.g., omics). Book chapters include comprehensive synthesis, observational and manipulative studies, and sediment-based analysis, a vibrant imprint of benthic-pelagic coupling and ecosystem connectivity. Most chapters also address the impacts of anticipated environmental changes (e.g., warming, acidification).


Product Details

ISBN-13: 9781351021807
Publisher: CRC Press
Publication date: 11/19/2020
Sold by: Barnes & Noble
Format: eBook
Pages: 292
File size: 21 MB
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About the Author

Maria Alexandra Teodosio

Table of Contents

Functional Trait Approaches for the Study of Metazooplankton Ecology. Zooplankton-Phytoplankton Interactions in a Changing World. Leading Hypothesis about the Influence of Temperate Marine Fish Larvae on Recruitment Variability that Shaped Larval Ecology. Ocean Acidification Impacts on Zooplankton. Diversity and Biogeography as Revealed by Morphologies and DNA Sequences: Tintinnid Ciliates as an Example. Planktonic Shelled Protists (Foraminifera and Radiolaria Polycystina): Global Biogeographic Patterns in the Surface Sediments. Metazooplankton Dynamics in Coastal Upwelling Systems. Interactions in Plankton Food Webs: Seasonal Succession and Phenology of Baltic Sea Zooplankton. Visualizing and Exploring Zooplankton Spatial-Temporal Variability. New Approaches to Study Jellyfish: From Autonomous Apparatus to Citizen Science. Metabarcoding to Study Zooplankton Diversity. Omics Advances in the Study of Zooplankton: Big Data for Small Drifting Organisms.

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