Header

UZH-Logo

Maintenance Infos

Phenotypic evolution is more constrained in simpler food webs


Barbour, Matthew A; Greyson-Gaito, Christopher J; Sootodeh, Arezoo; Locke, Brendan; Bascompte, Jordi (2020). Phenotypic evolution is more constrained in simpler food webs. bioRxiv 527416, University of Zurich.

Abstract

Global change is simplifying the structure of ecological networks; however, we are currently in a poor position to predict how these simplified communities will affect the evolutionary potential of remaining populations. Theory on adaptive landscapes provides a framework for predicting how selection constrains phenotypic evolution, but often treats the community context of evolving populations as a “black box”. Here, we integrate ecological networks and adaptive landscapes to examine how changes in food-web complexity shape evolutionary constraints. We conducted a field experiment that manipulated the diversity of insect parasitoids (food-web complexity) that were able to impose selection on an insect herbivore. We then measured herbivore survival as a function of three key phenotypic traits. We found that more traits were under selection in simpler vs. more complex food webs. The adaptive landscape was more neutral in complex food webs because different parasitoid species impose different selection pressures, minimizing relative fitness differences among phenotypes. Our results suggest that phenotypic evolution becomes more constrained in simplified food webs. This indicates that the simplification of ecological communities may constrain the adaptive potential of remaining populations to future environmental change. “What escapes the eye, however, is a much more insidious kind of extinction: the extinction of ecological interactions.” Janzen (1974)

Abstract

Global change is simplifying the structure of ecological networks; however, we are currently in a poor position to predict how these simplified communities will affect the evolutionary potential of remaining populations. Theory on adaptive landscapes provides a framework for predicting how selection constrains phenotypic evolution, but often treats the community context of evolving populations as a “black box”. Here, we integrate ecological networks and adaptive landscapes to examine how changes in food-web complexity shape evolutionary constraints. We conducted a field experiment that manipulated the diversity of insect parasitoids (food-web complexity) that were able to impose selection on an insect herbivore. We then measured herbivore survival as a function of three key phenotypic traits. We found that more traits were under selection in simpler vs. more complex food webs. The adaptive landscape was more neutral in complex food webs because different parasitoid species impose different selection pressures, minimizing relative fitness differences among phenotypes. Our results suggest that phenotypic evolution becomes more constrained in simplified food webs. This indicates that the simplification of ecological communities may constrain the adaptive potential of remaining populations to future environmental change. “What escapes the eye, however, is a much more insidious kind of extinction: the extinction of ecological interactions.” Janzen (1974)

Statistics

Citations

Dimensions.ai Metrics

Altmetrics

Downloads

2 downloads since deposited on 16 Feb 2021
2 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Working Paper
Communities & Collections:07 Faculty of Science > Institute of Evolutionary Biology and Environmental Studies
Dewey Decimal Classification:570 Life sciences; biology
590 Animals (Zoology)
Language:English
Date:2020
Deposited On:16 Feb 2021 16:06
Last Modified:17 Feb 2021 04:31
Series Name:bioRxiv
ISSN:2164-7844
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1101/527416

Download

Green Open Access

Download PDF  'Phenotypic evolution is more constrained in simpler food webs'.
Preview
Content: Published Version
Filetype: PDF
Size: 4MB
View at publisher
Licence: Creative Commons: Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)