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Elena Litchman

Researcher at Michigan State University

Publications -  106
Citations -  11029

Elena Litchman is an academic researcher from Michigan State University. The author has contributed to research in topics: Phytoplankton & Population. The author has an hindex of 47, co-authored 97 publications receiving 9121 citations. Previous affiliations of Elena Litchman include Gifu University & Technical University of Denmark.

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Trait-Based Community Ecology of Phytoplankton

TL;DR: The essential components of trait-based approaches to phytoplankton ecology are summarized and mathematical techniques for integrating traits into measures of growth and fitness and predicting how community structure varies along environmental gradients are described.
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Optimal nitrogen-to-phosphorus stoichiometry of phytoplankton

TL;DR: The results show that the canonical Redfield N:P ratio of 16 is not a universal biochemical optimum, but instead represents an average of species-specific N:F ratios, which will vary from 8.2 to 45.0, depending on the ecological conditions.
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The role of functional traits and trade‐offs in structuring phytoplankton communities: scaling from cellular to ecosystem level

TL;DR: It is shown thatrait-based approaches to community structure, augmented by a mechanistic analysis of trade-offs among functional traits, can be successfully used to explain community composition of marine phytoplankton along environmental gradients.
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A global pattern of thermal adaptation in marine phytoplankton.

TL;DR: It is found that rising temperatures this century will cause poleward shifts in species’ thermal niches and a sharp decline in tropical phytoplankton diversity in the absence of an evolutionary response.
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Marine Phytoplankton Temperature versus Growth Responses from Polar to Tropical Waters – Outcome of a Scientific Community-Wide Study

TL;DR: This study provides physiological datasets fundamental to understanding functional responses of phytoplankton growth rates to temperature that can be used to parameterise global ocean model projections of environmental change and to provide initial insights into the magnitude of regional biogeographic change in ocean biota in the coming decades.