How zebrafish maintain efficient and fair foraging behaviors

Date:
August 25, 2020
Source:
eLife
Summary:
New insight on how zebrafish achieve near-optimal foraging
efficiency and fairness among groups has been published today.



FULL STORY ==========================================================================
New insight on how zebrafish achieve near-optimal foraging efficiency
and fairness among groups has been published today in the open-access
journal eLife.


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The findings, based on analysis of the joint swimming patterns of
individual zebrafish and groups, and detailed mathematical models of
their behaviour, suggest that specialised social interactions allow the
animals to forage efficiently and result in more equal distribution of
food among group members.

Living in a group has clear benefits, including the sharing of
responsibilities and resources. Understanding the interactions among individuals that give rise to group behaviour is therefore central to
studying and analysing collective behaviour in animal groups and other biological systems.

"In real-world situations, animals are likely to encounter several
food sources or threats, where maintaining a tight group may not be
beneficial for all group members," explains lead author Roy Harpaz, who
was a PhD student at the Weizmann Institute of Science, Israel, at the
time the study was carried out, and is now Postdoctoral Fellow at Harvard University, Cambridge, US. "Indeed, schooling and shoaling species have
been shown to disperse when confronted with distributed resources. We
aimed to characterise group foraging in complex environments and map
the functional interactions among group members." Harpaz and his PhD
advisor, Elad Schneidman of the Weizmann Institute, studied free foraging
by groups of adult zebrafish in an open arena. They tracked the foraging behaviours of single adult zebrafish and of groups of three or six fish
in a large circular arena with shallow water, where small food flakes
were scattered on the surface. Tracking these activities revealed that
fish picked up on their shoal mates' swimming maneuvers which indicated
the presence of food, and responded by swimming to these locations.

The team then compared the predictive power of a family of mathematical
models, based on inferred functional and social interactions between
zebrafish. The model which accurately described individual and group
foraging behaviours suggests that the interactions among fish allow them
to combine individual and social information to achieve near-optimal
foraging efficiency and promote more equal food intake within groups.

"Of the different social models we tested, only the one based on
the social interactions we inferred from observing real fish results
in improved efficiency and equality," Harpaz says. "Also, our model
shows that the interactions that would maximise efficiency in these
social foraging models depend on group size, but not necessarily on
food distribution. We therefore hypothesise that fish adaptively pick
the subgroup of neighbours they 'listen to' to determine their own
behaviour." "Building accurate models of individual behaviour of groups
of fish allowed us to infer the details of effective social interactions
among them and reveal a highly efficient and robust foraging strategy," concludes senior author Elad Schneidman. "This work is an example of the
power of using detailed analyses of individuals in real groups to build data-driven models of social interactions, and of using these models to
link the actions of individual animals to the collective behaviour of
a group."

========================================================================== Story Source: Materials provided by eLife. Note: Content may be edited
for style and length.


========================================================================== Journal Reference:
1. Roy Harpaz, Elad Schneidman. Social interactions drive efficient
foraging
and income equality in groups of fish. eLife, 2020; 9 DOI: 10.7554/
eLife.56196 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/08/200825110629.htm

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