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Toward trait‐based food webs: Universal traits and trait matching in planktonic predator–prey and host–parasite relationships.

Authors :
Litchman, Elena
Edwards, Kyle F.
Boyd, Philip W.
Source :
Limnology & Oceanography; Nov2021, Vol. 66 Issue 11, p3857-3872, 16p
Publication Year :
2021

Abstract

There is a growing consensus that traits offer a powerful way to examine the relationship between the environment, organismal strategies, species interactions, and ecological success. To date, trait‐based research has largely been focusing on individual trophic levels and not on cross‐level interactions. Looking at traits not only within but across trophic levels and identifying traits that together define trophic interactions holds a great potential for understanding the mechanisms of interactions. Here, we outline the conceptual foundation for cross‐trophic trait‐based frameworks, using planktonic food webs as an example. First, we compile a list of traits important within different individual trophic levels and show that there are traits that are common across trophic levels ("universal" traits), as well as trophic level‐specific traits. Next, we focus on traits that characterize interactions across trophic levels, focusing on two types of interaction—grazer–primary producer and host–parasite, identifying the similarities and differences between these interactions. We outline the trait hierarchies that define possible and realized intertrophic interactions and their strengths. We then highlight the importance of trade‐offs among those traits in shaping interactions and explaining general patterns in the structure and function of food webs. Finally, we discuss the environmental influences on traits, their eco‐evolutionary responses to changing conditions and how those responses may alter trophic interactions. The extension of trait‐based approaches from individual trophic levels to food webs and different trophic interactions should stimulate further conceptual development, enrich the field of aquatic sciences, and provide a framework to better predict global change effects on ecosystems. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00243590
Volume :
66
Issue :
11
Database :
Complementary Index
Journal :
Limnology & Oceanography
Publication Type :
Academic Journal
Accession number :
153493353
Full Text :
https://doi.org/10.1002/lno.11924