Comparison of solitary and collective foraging strategies of Caenorhabditis elegans in patchy food distributions
Author(s) -
Siyu Serena Ding,
Leah Sophie Muhle,
André EX Brown,
Linus J. Schumacher,
Robert G. Endres
Publication year - 2020
Publication title -
philosophical transactions of the royal society b biological sciences
Language(s) - English
Resource type - Journals
eISSN - 1471-2970
pISSN - 0962-8436
DOI - 10.1098/rstb.2019.0382
Subject(s) - foraging , caenorhabditis elegans , collective behavior , biology , optimal foraging theory , ecology , range (aeronautics) , group behavior , social psychology , psychology , engineering , genetics , sociology , anthropology , gene , aerospace engineering
Collective foraging has been shown to benefit organisms in environments where food is patchily distributed, but whether this is true in the case where organisms do not rely on long-range communications to coordinate their collective behaviour has been understudied. To address this question, we use the tractable laboratory model organismCaenorhabditis elegans , where a social strain (npr-1 mutant) and a solitary strain (N2) are available for direct comparison of foraging strategies. We first developed an on-lattice minimal model for comparing collective and solitary foraging strategies, finding that social agents benefit from feeding faster and more efficiently simply owing to group formation. Our laboratory foraging experiments withnpr-1 and N2 worm populations, however, show an advantage for solitary N2 in all food distribution environments that we tested. We incorporated additional strain-specific behavioural parameters ofnpr-1 and N2 worms into our model and computationally identified N2's higher feeding rate to be the key factor underlying its advantage, without which it is possible to recapitulate the advantage of collective foraging in patchy environments. Our work highlights the theoretical advantage of collective foraging owing to group formation alone without long-range interactions and the valuable role of modelling to guide experiments.This article is part of the theme issue ‘Multi-scale analysis and modelling of collective migration in biological systems'.
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