Behavioral Ecology
doi:10.1093/beheco/ars136
Advance Access publication 7 September 2012
Original Article
Brook trout use individual recognition and
transitive inference to determine social rank
Shannon L. White and Charles Gowan
Environmental Studies Program, Randolph-Macon College, Ashland, VA 23005, USA
Transitive inference (TI) occurs when information about known relationships is used to construct novel associations, for example,
when an individual infers the order of 3 conspecifics in a linear dominance hierarchy (A > B > C) by watching 2 dyads (A > B
and B > C). TI has been demonstrated for several species, but never for organisms with hierarchies involving many individuals
whose rank order changes often. Under these circumstances, theory predicts natural selection may favor use of explicit cues to
rank conspecifics, rather than TI. Here we show that brook trout (Salvelinus fontinalis), a species that exhibits complex, shifting
dominance hierarchies, can combine individual recognition and TI to rank individuals within a hierarchy without use of explicit
cues. Subjects that were allowed to directly interact with rivals were able to identify the social rank of each individual. In addition, we found that a subject, whose rank was C within a 5-fish hierarchy (A > B > C > D > E), could use TI to correctly infer the
ranks of A and E after first interacting with B and D and then watching dyads involving A > B and D > E. This demonstration of
TI in brook trout contributes to the understanding of stream trout population dynamics as TI could lower the energetic costs
associated with movement. Key words: brook trout, individual recognition, social learning, transitive inference. [Behav Ecol]
Introduction
B
ehavioral studies of social fish indicate that the ability to recognize individuals in a group has the potential
to decrease the number and escalation of aggressive fights
(Morris et al. 1995; Johnsson 1997; Utne-Palm and Hart
2000), thereby providing an evolutionary benefit by reducing
energetic costs and risk of injury (Oliveira et al. 1998; Oliveira
et al. 1998, Earley et al. 2003; Galef and Laland 2005). An
even greater fitness benefit would result if individuals could
also use transitive inference (TI) to avoid fights altogether. TI
is a type of social learning that involves using known relationships to deduce unknown ones (see Allen 2006; Vasconcelos
2008 for comprehensive reviews of TI in nonhuman animals).
For example, an “eavesdropping” individual (sensu Oliveira
et al. 1998) could use TI to infer the order of 3 conspecifics
in a linear dominance hierarchy (A > B > C, indicating A is
dominant over B and B over C) by observing, without risk of
injury, just 2 dyads (A > B and B > C).
Considered a process of higher cognition and once thought
restricted to humans, TI has since been demonstrated for several animal species that form dominance hierarchies (Davis
1992; Hogue et al. 1996; Paz-y-Miño et al. 2004). However,
still unclear is how widespread TI is across various social structures. For example, researchers have suggested that natural
selection may favor TI only when hierarchies are composed
of relatively few individuals whose rank order remains constant over time (Allen 2006; Vasconcelos 2008), but this idea
remains untested. And, because TI has only been studied in 1
species of fish (Astatotilapia burtoni; Grosenick et al. 2007), the
ability for other fish species to use TI is unknown.
Address correspondence to Shannon L. White, who is now at
Department of Fish and Wildlife Conservation, Virginia Tech,
Blacksburg, VA 24061, USA. E-mail: [email protected].
Received January 16 2012; revised May 14 2012; accepted July 10
2012.
© The Author 2012. Published by Oxford University Press on behalf of
the International Society for Behavioral Ecology. All rights reserved.
For permissions, please e-mail: [email protected]
Brook trout are a good model organism for studying TI
because competition for food and stream position results in
the establishment of large, linear hierarchies within a single
pool (up to 27 fish in some circumstances; Gowan and Fausch
2002), and these hierarchies periodically shift due to immigration and emigration (Caron and Beaugrand 1988; Nakano
1994; Gowan 2007). Under these circumstances, an eavesdropping individual would have to observe a very large number of dyadic interactions in order to infer the rank order
of all individuals, and, if members of the hierarchy changed
often, this process might never be completed. Thus, it has
been proposed that it would be more advantageous for organisms living in complex hierarchies to use explicit cues (e.g.,
behavior or morphology) to rank rivals rather than TI (Allen
2006; Vasconcelos 2008). But, if brook trout are capable of
TI, it would suggest that natural selection may favor the development of TI under a wide variety of social systems.
The objective of this study was to determine whether brook
trout can use individual recognition and TI to determine
social rank. We hypothesized that brook trout would be
capable of individual recognition, but that a fish’s ability to
recognize rival rank using TI could depend on the number
of members in the hierarchy and the amount of prior
information a fish had about the fish that constituted the
hierarchy. Thus, to test these hypotheses, a subject was trained
on the rank order of rivals within a dominance hierarchy
under varying levels of interaction with rivals and using 2
hierarchy sizes. We tested the subject’s ability to determine
social rank of each rival using an approach/avoidance task,
with avoidance of the dominant rival taken as evidence
that the subject could discern the dominance relationship
between 2 rivals (Grosenick et al. 2007; Vasconcelos 2008).
MATERIALS AND METHODS
Study fish
Brook trout used in this study were young-of-the-year fish
obtained from a Virginia Department of Game and Inland
64
Fisheries hatchery in February 2009 and 2010. Fish were kept
in 3 isolated 76 × 32 × 32-cm holding aquaria, each containing
approximately 50 fish. All aquaria had a pH of 7 and a consistent temperature between 13 and 15 °C. Fish were fed bloodworms (San Francisco Bay Brand, Newark, CA, USA) once
daily. Lighting was kept on a 12 light:12 dark diel cycle.
For any given training regimen, fish were size matched to
within ±2 mm total length so that size could not be used as a
cue to dominance rank. With an average fish size of 88.2 mm
(minimum = 67 mm, maximum = 110 mm, SE = 2.6), the difference in size between 2 rivals was less than 3%, and this size
difference has been shown to give a larger fish a negligible competitive advantage (Gowan and Fausch 2002). Different subjects
and rivals were used for each replicate of each training regimen.
Training tanks
Training and testing were completed in 1 of 3 replicate circular cattle troughs 1.65 m in diameter and 0.6 m in depth with a
gravel bottom and divided into 3 identical lanes by clear Plexiglas
(Figure 1). By placing fish in different lanes of the tank, we could
physically isolate them from each other, while still permitting
visual contact. Natural stream flow was mimicked using a pump
connected to an outlet in each lane. After passing through each
lane, all water was mixed in a common sump before being recirculated to the tank, thus preventing fish from using chemical
cues to identify conspecifics. Tanks were draped in black plastic
so that fish were not disturbed during experiments.
Training regimens
We trained replicate fish (the subjects) using 1 of 5, 6-day
regimens that involved the subject interacting in varying ways
Behavioral Ecology
with rivals. Two of the regimens involved determining if subjects could recognize the rivals as individuals, following direct
interaction. The other 3 training regimens tested for the ability of subjects to infer social relationships using TI.
Training for individual recognition in a 3-fish hierarchy
During this training regimen, the subject, fish B in a 3-fish
hierarchy (A > B > C), was allowed to physically interact with
rivals A and C for the duration of the training period. Prior
to training, 3 size-matched fish that had never before interacted (i.e., they were in different holding aquaria before the
study) were randomly assigned small fin clips to distinguish
them as individuals (the adipose fin or a small portion of the
upper or lower caudal fin was excised; the third fish remained
unmarked). A dominance hierarchy was established by placing the fish in a holding aquarium for 1–2 days. When 1 fish
(now designated A) established dominance as indicated by
repeatedly charging, chasing, and nipping the other 2 individuals (Cunjack and Green 1984), it was removed from the
holding aquarium and randomly assigned to either the left or
right lane of the training tank. After the dominance relationship of B and C was established, C was placed in the far lane
opposite A, and B (now the subject) was randomly assigned to
the lane with A or C. There were no fish in the center lane.
The subject interacted with either A or C in the morning,
and then at 1200 h the positions of A and C were switched
so that the subject spent an equal amount of time per day
interacting with both rivals. Training lasted for 6 days, and at
the end of the third day the location of B was switched so
that all members of the hierarchy spent an equal amount
of time in the right and left lanes during training. Training
was also balanced for time-of-day by having the subject spend
equal time with each rival during mornings and evenings
(Supplementary Table S1). Balancing training so that each
subject spent an equal amount of time with each rival in each
lane of the tank during morning and evening prevented the
subject from developing a side-of-tank preference due to associative learning (Grosenick et al. 2007).
Training for individual recognition in a 5-fish hierarchy
Methods similar to those just described were used to develop
a 5-fish hierarchy (A > B > C > D > E) with C as the subject fish. During the 6-day training regimen, all rivals were
allowed to interact in 1 lane of the training tank for the
majority of the day. The only time all rivals were not together
was between 1200 and 1400 h. During this time, rivals A and
B were moved to either the left or right lane and D and E
to the opposite lane. The subject was then allowed to interact with each rival pair individually for 1 h. These separated
interactions were necessary to ensure that the subject had the
opportunity to interact with all rivals, which did not occur if
rival A was so dominant as to prevent interactions among subordinates. The order and location of each interaction was balanced, and at the conclusion of the separated interactions all
fish were reunited in a new lane such that all fish spent the
same amount of time in all 3 lanes (Supplementary Table S2).
Figure 1 Circular cattle trough used during training and approach/avoidance
tests. The tank was 1.65 m in diameter and 0.6 m in depth with a
gravel bottom and divided into 3 lanes by clear Plexiglas. Water
circulated throughout the tank to avoid rival identification based on
chemical cues.
Training for TI with some direct interaction
This training regimen included 5 fish (A > B > C > D > E)
with C as the subject. The objective during training was to
allow direct interactions among B, C, and D, and then to
allow C to observe, but not participate in, dyadic interactions
between A and B and between D and E. The subject never
interacted with A or E and never saw A and E interact.
Therefore, in order to correctly infer the full hierarchy, the
subject would have to use individual recognition to determine
its relationship to rivals B and D, and TI to distinguish the
relationship between rivals A and E.
65
White and Gowan • Transitive inference in brook trout
Prior to training, 3 size-matched fish that had never before
interacted were put into a holding aquarium. These fish
would become B, C, and D during the subsequent training
phase. Once the dominance hierarchy among those 3 fish was
determined, C was moved to the center lane of the training
tank. Fish D remained in the holding aquarium, and we introduced a succession of new size-matched fish into this aquarium until we found a fish subordinate to D. This became
E. Similarly, we repeatedly introduced B into a new holding
aquarium with a succession of rivals until we found a fish that
dominated B. This became A. At the end of this process we
had established a 5-fish hierarchy in which B, C, and D had
interacted, but in which A had only interacted with B and E
only with D.
Each day for 6 days, C was allowed to physically interact
with rivals B and D in the center lane, was physically isolated
at all times from rivals A and E, and was permitted to watch,
through the Plexiglas, interactions between A and B and
between D and E. Training began with C in the middle lane
of the training tank and A and B randomly assigned to the left
or right lane and D and E to the opposite lane. Interactions
among B, C, and D occurred from 0900 to 1700 h. Afterward,
rival pairs A and B, and D and E were reunited in the lane
opposite to where they were at the beginning of the day
(Supplementary Table S3).
Training for TI without direct interaction for a 3-fish hierarchy
During this regimen, the subject (which did not have a
place in the hierarchy) was physically isolated from 3 rivals
(A > B > C), but allowed to watch a series of nonoverlapping
dyadic interactions between those rivals. Thus, the subject
witnessed interactions between A and B and between B and
C, but never between A and C (Supplementary Table S4).
Because the subject had never seen A and C directly interact,
it would have to use TI to deduce the full hierarchy.
Methods to develop a 3-fish hierarchy for use in TI tests
were the same as for tests of individual recognition with the
exception that the subject was not part of the hierarchy in
tests of TI without direct interaction. After the dominance
relationship of 3 size-matched rivals was established, A was
randomly assigned to the left or right lane, and C was placed
in the opposite lane. B was then randomly placed in the
left or right lane of a study tank, and a randomly selected
size-matched subject who had never interacted with any of
the 3 rivals was placed in the center lane. Randomization of
the starting location for the 3 rivals ensured that the subject
viewed rival interactions in a random order. During training,
the subject remained in the center lane and the location of
rivals was switched between the left and the right lanes in a
manner that balanced for time of day and side of tank.
Training for TI without direct interaction for a 5-fish hierarchy
This training regimen was similar to that described in the previous section in that a subject (which did not have a place
within the hierarchy) witnessed interactions between nonoverlapping pairs of rivals. Because this regimen involved a
5-fish hierarchy (A > B > C > D > E), the subject witnessed
dyads involving A and B, B and C, C and D, and D and E, but
never A and E, or B and D.
Methods to develop 5-fish hierarchies for TI tests were the
same as those for tests involving individual recognition in
a 5-fish hierarchy. After the dominance hierarchy of the 5
fish was determined, A and B were randomly assigned to be
together in the left or right lane, and D and E were placed
in the opposite lane. The location of C was then randomly
assigned, either left or right. Randomization of the starting location for the rivals ensured that the subject viewed
rival interactions in random order. A randomly selected
size-matched subject who had never interacted with any of
the 5 rivals was placed in the center lane. Every day at 1200 h
the locations of A and B, and D and E were switched such
that the subject viewed all nonoverlapping rival combinations
within the same day. The location of C was also switched periodically throughout the training regimen in order to keep
the training balanced (Supplementary Table S5).
Controlling for end-anchor effects
After a subject has been trained for TI on a 5-fish hierarchy,
it can be tested on 2 pairs of rivals when evaluating TI: A and
E, and B and D. However, tests involving A and E may not
reliably indicate use of TI, because they can be confounded
by end-anchor effects (Vasconcelos 2008). That is, preference of the subject for E over A may be because E never won
a contest during training and A never lost. During testing,
the subject may simply avoid (via individual recognition)
fish A because it never lost, rather than using TI to infer the
relationship A > E. In contrast, the test involving B and D is
taken as a reliable evaluation of TI because B and D have
won and lost an equal number of contests during training
(Vasconcelos 2008).
Given that the TI with some direct interaction treatment
involved direct interaction with B and D, results of this test
cannot be used to definitively determine whether TI was
being used to determine rival rank. However, the results of
tests involving A and E for TI with some direct interaction
could be used to evaluate TI provided that strong end-anchor
effects were not present. The results of the TI without interaction studies allowed us to evaluate whether strong end-anchor
effects could account for significant treatment effects. If,
under these training regimens, subjects showed no or weak
responses to end-anchor rivals, it would indicate that subjects
were not basing rival rank on end anchors alone, and results
of test involving A and E for TI with some direct interaction
could be taken as evidence of TI.
Approach/avoidance tasks
Following training, an approach/avoidance task was used
to test the ability of a subject to identify the social rank of
rivals. For each task, the subject was put in the center lane
of the training tank and was visually exposed to 1 pair of
rivals wherein a dominant rival was in 1 lane (left or right
of the subject, randomly chosen) and a subordinate rival in
the opposite lane. For tasks involving 3-fish hierarchies, the
rivals were A and C. For tests involving 5-fish hierarchies, 2
rival combinations were tested separately: A and E, and B
and D. Collectively, we refer to all these as “training rivals,”
because the subject was trained using them. To confirm that
rival preference was not based on explicit cues unrelated to
individual recognition or TI, each subject was also tested on
2 size-matched control rivals that the subject was unfamiliar
with, but which had an established dominance hierarchy. The
order in which training and control rivals were presented to
the subject was randomized for each replicate.
For each task, the amount of time the subject spent in each
half of its center lane was recorded for 600 s, and then the
location of the rivals was switched and a second approach/
avoidance task conducted (e.g., if the combination of rivals
was A and E with A on the left and E on the right for the first
600 s, then for the second test, A was switched to the right
and E to the left).
Digital video from each 600 s approach/avoidance task was
reviewed by the first author to determine the time the subject
spent on the left side of the center lane. Positions of the
dominant and subordinate rivals were unknown to the reviewer
at the time each video was analyzed. Subsequently, videos from
66
Behavioral Ecology
10 randomly selected tasks were reviewed by an independent
viewer unfamiliar with the study. There was a strong correlation
between times measured by the 2 reviewers (r = 0.95; the
average difference in the estimates of the time the subject
spent on the left side of the lane across the 10 videos was 1.5
s, SE = 9.2 s) indicating that behavior of the subject could be
reliably determined from the videos.
Statistical analysis
We calculated a response variable, TL, by subtracting the time
the subject spent left when the dominant rival was in the left
lane from time spent left when the dominant rival was in the
right lane. We tested the null hypothesis that the subject’s
side-of-tank preference was unrelated to the location of the
dominant fish, using Monte Carlo statistics (Manly 1991) to
analyze for main effects (location of the dominant rival, left
or right) and the interaction between dominant rival location
and type of rivals (control or training; see electronic supplementary material for detailed statistical methods). For brevity
and clarity, we report only the results from the main effects
tests because, in all cases, interaction tests confirmed conclusions from main effects (see Nieuwenhuis et al. 2011 for a discussion of this issue).
RESULTS
Test for individual recognition in 3- and 5-fish hierarchies
After direct interaction, subjects were capable of recognizing
individual rivals in both 3- and 5-fish dominance hierarchies
(Figure 2). In 3-fish hierarchies, mean TL for subjects exposed
to rivals A and C was 348.9 s (n = 7, SE = 58.7, P < 0.0001).
In 5-fish hierarchies, mean TL for subjects exposed to rivals
A and E was 240.5 s (n = 6, SE = 63.8, P = 0.001), and for
rivals B and D it was 147.2 s (n = 6, SE = 23.2, P = 0.023). In
contrast, control rivals had no effect on subjects’ side-of-tank
preference in either 3-fish (mean TL = 29.3 s, n = 3 SE = 32.7,
P = 0.393) or 5-fish hierarchies (mean TL = −42.3 s, n = 6,
SE = 30.8, P = 0.716).
Figure 2 Average time (s) subjects spent on the left side of the center lane
when the dominant (open bars) or subordinate (gray bars) rival
was in the left lane during 600 s approach/avoidance tests following
6 days of direct interaction with rivals. The response variable,
TL, is the difference between each pair of open and gray bars. In
approach/avoidance tests for 3-fish hierarchies (panel A), the
rival pair was A/C. In 5-fish hierarchies (panel B), the rival pairs
were A/E and B/D. Control rivals were a pair of fish that had an
established dominance relationship, but which the subject had never
seen. Vertical bars are ± 1SE.
Tests for TI with some direct interaction
Using individual recognition and TI, subjects were able to
determine the social rank of all rivals in the 5-fish hierarchy
(Figure 3). After directly interacting with B and D, subjects
were able to identify the subordinate rival (mean TL = 203.7s,
n = 7, SE = 27.3, P = 0.001). In addition, subjects were able
to use TI to infer the relative relationships of A and E without having engaged in direct physical interactions with either
rival (mean TL = 165.1s, n = 7, SE = 29.7, P = 0.008). There
was no response to control rivals (mean TL = −3.4 s, n = 7,
SE = 25.2, P = 0.523).
Tests for TI without direct interaction
Subjects that remained physically isolated from all rivals during training did not respond strongly to rival location during
approach/avoidance tasks (Figure 4). In 3-fish hierarchies,
mean TL for subjects exposed to rivals A and C was 94.7 s
(n = 6, SE = 28.4, P = 0.10) and in 5-fish hierarchies mean TL
was 72.0 s for rival combinations A and E (n = 3, SE = 33.2,
P = 0.251) and 138.7 s for rival combinations B and D (n = 3,
SE = 70.2, P = 0.096). Subjects in 3-fish hierarchies did not
react to the control rivals (mean TL = 29.2 s, n = 6, SE = 25.7,
P = 0.351). Control rivals in 5-fish hierarchies were not tested
because all previous tests involving controls indicated no
response by the subjects.
Figure 3 Average time (s) subjects spent on the left side of the center lane
when the dominant (open bars) or subordinate (gray bars) rival
was in the left lane during 600 s approach/avoidance tests following
6 days of direct interaction with rivals B and D and visual exposure
to rivals A and E. The response variable, TL, is the difference
between each pair of open and gray bars. Control rivals were a pair
of fish that had an established dominance relationship, but which
the subject had never seen. Vertical bars are ± 1SE.
White and Gowan • Transitive inference in brook trout
Figure 4 Average time (s) subjects spent on the left side of the center lane
when the dominant (open bars) or subordinate rival (gray bars)
was in the left lane during 600 s approach/avoidance tests following
6 days of visual exposure but no direct interaction with rivals. The
response variable, TL, is the difference between each pair of open
and gray bars. In approach/avoidance tests for 3-fish hierarchies
(panel A), the rival pair was A/C. In 5-fish hierarchies (panel B), the
rival pairs were A/E and B/D. Control rivals were a pair of fish that
had an established dominance relationship, but which the subject
had never seen. Vertical bars are ± 1SE.
Discussion
When allowed to directly interact with rivals in both 3- and
5-fish hierarchies, subject brook trout were able to identify
the social rank of conspecifics and chose to avoid dominant
rivals. This result is consistent with previous studies of individual recognition in a wide variety of fish species (see Griffiths
2003 for a review). Subjects were also able to use TI to learn
the dominance ranks of unfamiliar rivals, provided that dyads
observed by the subject included 1 familiar rival. Importantly,
subjects did not respond to control rivals, confirming that
rival preference was not based on explicit cues, but rather
recognition of individuals and assessment of an individual’s
dominance status (but see Höjesjö et al. 2007 for a counter example involving rainbow trout, Oncorhynchus mykiss).
Response of subjects to end anchors was weak and not statistically significant, indicating that TI was the primary mechanism responsible for the subject avoiding rival A in favor of
E in tests of TI with some direct interaction. Taken together,
these results indicate that brook trout are capable of TI, a
complex cognitive process once thought restricted to humans
and sometimes discounted as evolutionarily nonadvantageous
67
for species living in complex social systems like that of salmonids (Vasconcelos 2008).
The adaptive value of individual recognition and TI in species that form dominance hierarchies has been demonstrated
theoretically (Nakamaru and Sasaki 2003), and is supported
by a large body of empirical evidence (Hsu et al. 2006). For
example, familiar individuals engage in fewer contests for
position, which reduces energetic costs related to both fighting and stress (Höjesjö et al. 1998), provides more time for
feeding and reproduction, and allows a greater allocation of
energy to growth and reproduction (Barnard and Burk 1979;
Schneider et al. 2001; Dugatkin and Earley 2004).
TI has been demonstrated in numerous organisms including rats, fish, birds, monkeys, and humans (Gillan 1981; von
Fersen et al. 1991; Davis 1992; Grosenick et al. 2007), but our
study is the first to test TI in a species that lives in a complex, linear social structure, where immigration and emigration result in frequent changes to rival composition, and thus
rank order. Critics have questioned the ability of organisms
that live in complex hierarchies to perform TI because an
ever-shifting hierarchy would make it impossible for an individual to learn the rank order of all conspecific rivals through
TI. In these social structures, it is theorized that direct interaction is the most assured method of assessing dominance
rank of rivals, and should be favored by natural selection
(Allen 2006; Vasconcelos 2008).
The adaptive advantage of TI in brook trout is probably best understood in the context of stream trout population dynamics across a range of spatial scales. It is now well
established that some trout move several kilometers or more
(Fausch et al. 2002) in search of suitable foraging habitat
(Gowan and Fausch 2002). Often, larger fish move most
(Gowan and Fausch 1996a), presumably because they have
high energy demands that can only be satisfied by locations of
exceptional quality (Hansen and Closs 2009), and these locations are exceedingly rare (Gowan and Fausch 2002). Finding
these locations has direct fitness benefits (Nakano 1995), but
the energetic costs of moving and then engaging in contests
for these positions are high (Railsback et al. 1999). With
the use of individual recognition and TI, energetic costs of
movement are lowered because a new fish entering a pool
can infer the local dominance hierarchy primarily through
observation rather than confrontation, and fish already in the
pool can assess the dominance rank of the new individual in
a similar manner.
Consider a situation in which a mobile fish enters a pool
containing 10 unfamiliar rivals of similar size. If fish were
capable of individual recognition but not TI, the new fish
would have to interact with all 10 residents before the new
hierarchy could be established. However, if all individuals
were capable of both individual recognition and TI, the new
hierarchy could be established with as few as 1 contest (1 that
involved the new fish winning a contest with the formerly
most dominant 1 in the pool). As such, moving among pools
is much less costly, and the information needed to decide to
stay in a new pool is obtained much more quickly, compared
with a situation in which fish use only individual recognition
and not TI. In this way, learning that occurs over small scales
is directly linked to movement that occurs over large ones,
and these large-scale movements drive population density
(Gowan and Fausch 1996b).
Grosenick et al. (2007) were the first to demonstrate TI
in fish using African cichlids, Astatotilapia burtoni, and they
did so with methods analogous to our experiment involving a bystander watching, but not interacting with, members of a 5-fish dominance hierarchy. Grosenick et al.
(2007) showed that the bystander would avoid B in favor
of D and A in favor of E during approach/avoidance tasks.
68
In contrast, brook trout in our study did not show a statistically significant response when trained for TI without
direct interaction in both 3- and 5-fish hierarchies. Though
sample sizes for the 5-fish hierarchy were small (n = 3), they
included tests on 2 sets of rivals (A and E, and B and D),
neither of which showed a response. Moreover, there was
also no statistically significant response in the 3-fish treatment, which had sample sizes (n = 6) comparable to other
treatments in which a significant response was detected.
Overall, our results reliably indicate that subjects trained
under TI without direct interaction showed a much weaker
response to rivals than subjects allowed to directly interact
with at least some rivals in the hierarchy. We suspect that
larger sample sizes would have provided the power necessary to declare the responses statistically significant, but the
fact remains that subjects in tests without direct interaction
showed much weaker responses to rivals than subjects in
tests with direct interaction.
One explanation for the weaker response in tests lacking direct interaction is that brook trout are incapable of TI
unless direct interaction occurs with a least some rivals. A second explanation is that subjects did use TI to learn the order
of the dominance hierarchy, but did not react strongly during approach/avoidance tasks because subjects had no cues
about their position within the hierarchy. The second explanation is corroborated by the consistently positive TL values
in our studies of TI with no interaction and has been demonstrated in several bird species (Hogue et al. 1996; Peake et al.
2002; Paz-y-Miño et al. 2004). In contrast, in several species
of fish including rainbow trout (Höjesjö et al. 2007), green
swordtails (Xiphophorus helleri; Early and Dugatkin 2002), and
fighting fish (Betta splendens; Oliveira et al. 1998), subjects did
react to dominant and subordinate rivals even in the absence
of direct interactions. Our study was the first to directly compare the strength of responses with and without direct interaction, and our results indicate brook trout exhibited much
stronger responses when they knew their position within the
hierarchy rather than simply the rank order of rivals.
Natural selection favored development of TI in brook
trout, a species with large, shifting hierarchies. This finding is
in contrast to recent reviews (Allen 2006; Vasconcelos 2008),
and provides evidence that ability to use TI may be widely distributed across a variety of social systems. Moreover, TI helps
explain the processes driving movement and population
dynamics of stream salmonids.
SUPPLEMENTARY MATERIAL
Supplementary material can be found at http://www.beheco.
oxfordjournals.org/
FUNDING
‍ his project was funded by the Randolph-Macon College
T
Biology Department.
Special thanks to C. Noyes for help in the early stages of project
development and J. Harris for assistance in the lab. L. Grosenick,
R. Fernald, K. Fausch, D. Lahti, A. Owen, and E. Young provided valuable comments on an earlier draft. This research was approved under
an Animal Care and Use Committee Protocol from Randolph-Macon
College.
References
Allen C. 2006. Transitive inference in animals: reasoning or conditioned associations? In: Hurley S, Nudds M, editors. Rational animals? Oxford: Oxford University Press. p. 175–185.
Behavioral Ecology
Barnard CJ, Burk T. 1979. Dominance hierarchies and the evolution
of “individual recognition.” J Theor Biol. 81:65–73.
Caron J, Beaugrand JP. 1988. Social and spatial structure in brook
chars (Salvelinus fontinalis) under competition for food and shelter/shade. Behav Process. 16:173–191.
Cunjack RA, Green JM. 1984. Species dominance by brook trout and
rainbow trout in a simulated stream environment. T Am Fish Soc.
113:737–743.
Davis H. 1992. Transitive inference in rats (Rattus norvegicus). J Comp
Psychol. 106:342–349.
Dugatkin LA, Earley RL. 2004. Individual recognition, dominance
hierarchies, and winner and loser effects. Proc R Soc Lond B Biol
Sci. 271: 1537–1540.
Earley RL, Dugatkin LA. 2002. Eavesdropping on visual cues in green
swordtail (Xiphophorus helleri) fights: a case for networking. Proc R
Soc Lond B Biol Sci. 269:943–952.
Earley RL, Tinsley M, Dugatkin LA. 2003. To see or not to see:
does previewing a future opponent affect the contest behavior of
green swordtail males (Xiphophorus helleri)? Naturwissenschaften.
90:226–230.
Fausch KD, Torgersen CE, Baxter CV, Li HW. 2002. Landscapes to
riverscapes: bridging the gap between research and conservation of
stream fishes. BioScience. 52:483–498.
von Fersen L, Wynne CDL, Delius JD. 1991. Transitive inference
formation in pigeons. J Exp Psychol Anim Behav Process.
17:334–341.
Galef BG, Laland KN. 2005. Social learning in animals: empirical
studies and theoretical models. BioScience. 55:489–497.
Gillan DJ. 1981. Reasoning in the chimpanzee: II. Transitive inference. J Exp Psychol Anim Behav Process. 7:150–164.
Gowan C, Fausch KD. 1996a. Mobile brook trout in two high-elevation
Colorado streams: re-evaluating the concept of restricted movement. Can J Fish Aquat Sci. 53:1370–1381.
Gowan C, Fausch KD. 1996b. Long-term demographic responses of
trout populations to habitat manipulation in six Colorado streams.
Ecol Appl. 6:931–946.
Gowan C, Fausch KD. 2002. Why do foraging stream salmonids move
during summer? Environ Biol Fish. 64:139–153.
Gowan C. 2007. Short-term cues used by foraging trout in a California
stream. Environ Biol Fish. 78:317–331.
Griffiths SW. 2003. Learned recognition of conspecifics by fishes. Fish
Fish. 4:256–268.
Grosenick L, Clement TS, Fernald RD. 2007. Fish can infer social
rank by observation alone. Nature. 445:429–432.
Hansen EA, Closs GP. 2009. Long-term growth and movement in relation to food supply and social status in a stream fish. Behav Ecol.
20:616–623.
Hogue ME, Beaugrand JP, Lague PC. 1996. Coherent use of information by hens observing their former dominant defeating or being
defeated by a stranger. Behav Process. 38:241–252.
Höjesjö J, Anderson P, Engman A, Johnson JI. 2007. Rapid bystander
assessment of intrinsic fighting ability: behavioural and heart rate
responses in rainbow trout. Anim Behav. 74:1743–1751.
Höjesjö J, Johnsson JI, Petersson E, Järvi T. 1998. The importance of
being familiar: individual recognition and social behavior in sea
trout (Salmo trutta). Behav Ecol. 9:445–451.
Hsu Y, Earley, RL, Wolf, LL. 2006. Modulating aggression through
experience. In: Brown C, Laland K, Krause J, editors. Fish cognition and behavior. Oxford: Blackwell Publishing Ltd. p. 96–118.
Johnsson JI. 1997. Individual recognition affects aggression and dominance relations in rainbow trout, Oncorhynchus mykiss. Ethology.
103:267–282.
Manly BFJ. 1991. Randomization and Monte Carlo methods in biology. London: Chapman and Hall.
Morris MR, Gass L, Ryan, MJ. 1995. Assessment and individual recognition of opponents in the pygmy swordtails Xiphophorus nigrensis
and X. multilineatus. Behav Ecol Sociobiol. 37:303–310.
Nakamaru M, Sasaki A. 2003. Can transitive inference evolve in animals playing the hawk-dove game? J Theor Biol. 222:461–470.
Nakano S. 1994. Variation in agonistic encounters in a dominance hierarchy of freely interacting red-spotted masu salmon
(Oncorhynchus masou ishikawae). Ecol Freshw Fish. 3:153–158.
Nakano S. 1995. Competitive interactions for foraging microhabitats in
a size-structured interspecific dominance hierarchy of two sympatric
stream salmonids in a natural habitat. Can J Zool. 73:1845–1854.
White and Gowan • Transitive inference in brook trout
Nieuwenhuis S, Forstmann BU, Wagenmakers EJ. 2011. Erroneous
analysis of the interactions in neuroscience: a problem of significance. Nat Neurosci. 14:1105–1107.
Oliveira RF, McGregor PK, Latruffe C. 1998. Know thine enemy:
fighting fish gather information from observing conspecific interactions. Proc R Soc Lond B Biol Sci. 265:1045–1049.
Paz-y-Miño CG, Bond AB, Kamil AC, Balda RP. 2004. Pinyon jays use
transitive inference to predict social dominance. Nature. 430:778–781.
Peake TM, Terry AMR, McGregor PK, Dabelsteen, T. 2002. Do great tits
assess rivals by combining direct experience with information gathered by eavesdropping? Proc R Soc Lond B Biol Sci. 269:1925–1929.
69
Railsback SF, Lamberson RH, Harvey BC, Duffy WE. 1999. Movement
rules for individual-based models of stream fish. Ecol Model.
123:73–89.
Schneider RA, Huber R, Moore PA. 2001. Individual and status
recognition in the crayfish, Orconectes rusticus: the effects of urine
release on fight dynamics. Behaviour. 138:137–153.
Utne-Palm AC, Hart PJB. 2000 The effects of familiarity on competitive interactions between threespined sticklebacks. Oikos.
91:225–232.
Vasconcelos M. 2008. Transitive inference in non-human animals: an
empirical and theoretical analysis. Behav Process. 78:313–334.