evolution of morphology-personality associations
TRANSCRIPT
1
Evolution of morphology-personality associations 2
Detric Robinson1, Elizabeth M. A. Hassell
1, John Godwin
1, and R. Brian Langerhans
1 3
Department of Biological Sciences, North Carolina State University, Raleigh, NC 27695 4
5
Author for correspondence: 6
Elizabeth M. A. Hassell 7
email: [email protected] 8
9
10
Evolutionary change in one trait can elicit evolutionary changes in other traits due to genetic 11
correlations, constraining the independent evolution of traits and potentially leading to 12
unpredicted ecological and evolutionary consequences. Because many selective agents influence 13
the evolution of both behavioral and morphological-physiological traits, and because of the 14
broad, pleiotropic effects of the physiological mechanisms that underlie personalities, animals 15
might frequently exhibit morphology-personality associations. However, we currently know little 16
about genetic associations between animal personalities and non-behavioral traits. We tested for 17
associations between personality, morphology, and locomotor performance by comparing 18
zebrafish (Danio rerio) selectively bred for either a proactive or reactive stress coping style 19
(“bold” or “shy” phenotypes). We predicted that artificial selection for boldness would produce 20
correlated evolutionary responses of larger caudal regions and higher fast-start escape 21
performance (opposite for shyness). After 4–5 generations, morphology and locomotor 22
performance differed between personality lines, demonstrating genetic linkages among the traits. 23
Zebrafish from the bold line exhibited a larger caudal region and higher average velocity, as 24
predicted. We suggest these traits might typically experience correlational selection in nature and 25
manifest genetic correlations due to pleiotropy. Thus, evolution of personality can result in 26
concomitant changes in morphology and whole-organism performance, and vice versa. 27
28
Keywords: 29
behavioral syndromes, pleiotropy, predation, stress coping style, swimming performance, 30
zebrafish 31
32
1. Introduction 33
Evolutionary response to selection depends not only on the strength and nature of 34
selection, but also on the heritability of the trait in question and its genetic correlations with other 35
traits [1–3]. Because genetic correlations are not uncommon, selection on one trait can often 36
affect the evolution of other, correlated traits [4–6]. Understanding how and why this happens 37
has received considerable attention in the study of animal personalities, where a number of 38
behavioral traits covary to produce somewhat distinct “personalities,” “temperaments,” or 39
“behavioral syndromes” [7–9]. However, we know very little about whether animal personalities 40
exhibit genetic associations with non-behavioral traits, even though such associations might be 41
expected and could have major ecological and evolutionary implications [10]. We suggest that 42
animal personalities might often exhibit genetic correlations with seemingly disparate non-43
behavioral traits for two major reasons: (1) the likelihood of correlational selection on behaviors 44
and non-behavioral traits, and (2) the potentially broad, pleiotropic effects of the physiological 45
mechanisms underlying variation in animal personalities. 46
First, many selective agents influence the evolution of both behavioral traits and other 47
traits, such as morphology and physiology [11–13]. This can occur through correlational 48
selection that favors particular combinations of these traits [5,14,15]. Correlational selection 49
describes cases where the fitness effect of one trait depends on the value of another trait, 50
resulting in selection for phenotypic integration. For instance, certain behaviors may have to be 51
combined with specific morphologies to produce high-fitness results such as efficient foraging, 52
avoiding predation, attracting mates, or protecting offspring. This frequently generates genetic 53
correlations [16–20]. Brodie [21] demonstrated this phenomenon in garter snakes, where 54
correlational selection on color pattern and predator-escape behavior resulted in genetic 55
correlations among the traits. 56
In the case of animal personalities, correlational selection on personality traits and non-57
behavioral traits may be more common than we know, since suites of behaviors should have 58
different fitness consequences depending on other organismal traits. For instance, risk-prone, 59
aggressive individuals may require great strength, speed, or large body size to achieve high 60
fitness. Correlational selection on traits like these can produce genetic correlations that manifest 61
either through genes with pleiotropic effects on multiple traits, or through linkage disequilibrium 62
among separate genes maintained by persistent correlational selection [2,19]. Regardless of the 63
particular genetic source of trait associations, understanding the existence and strength of these 64
associations is important if we wish to better grasp the process of adaptation from a more holistic 65
perspective. In reality, traits do not independently adapt to their environments—rather, selection 66
acts on whole-organism phenotypes, resulting in organisms with evolved adaptations that reflect 67
integrated suites of traits [6,22–25]. 68
Second, irrespective of whether correlational selection originally shaped the genetic 69
correlations or not, prior work suggests that pleiotropic effects of genes responsible for animal 70
personalities may be widespread. That is, the physiological mechanisms underlying animal 71
personalities appear to often pleiotropically affect other traits, such as dispersal behaviors, 72
metabolic rate, immune capacities, lifespan, age at reproduction, and growth rate [25–27]. These 73
same underlying factors could also affect other traits like morphology or whole-organism 74
performance abilities [28–32], yet few studies have examined whether animal personalities 75
exhibit genetic associations with such morphological-physiological traits. Considering what we 76
now understand about hormone-mediated suites of traits [33,34], and given the diverse sets of 77
trait correlations involved in pace-of-life syndromes [25,27], we might expect to find a range of 78
associations between animal personalities and morphological-physiological traits owing to their 79
potentially shared genetic/physiological bases. Uncovering these associations will aid in 80
understanding both adaptation of complex phenotypes as well as evolutionary constraints to 81
adaptive evolution (since trait correlations bias the direction of evolution and reduce the ability 82
of traits to independently respond to selection [6,35]). Here we provide one of the first tests of 83
the notion that animal personalities might exhibit genetic associations with morphological-84
physiological traits. 85
Three general types of traits—behavior (animal personality), morphology (body shape), 86
and locomotor ability (fast-start swimming performance)—often respond evolutionarily to 87
predation risk, as has been well documented in various fish species. With regard to personality, 88
greater predation risk correlates with greater boldness (e.g., Brachyrhaphis episcopi [36]), a 89
tighter association between boldness and aggression (e.g., Gasterosteus aculeatus [37]), and 90
greater tenacity/boldness (e.g., Poecilia reticulata and Rivulus harti [38]). One explanation for 91
this trend is that boldness offers a fitness advantage by permitting effective foraging and mating 92
in chronically risky environments. With regard to morphology and locomotion, predation also 93
drives evolutionary shifts in fish body shape and swimming ability: populations under high 94
predation risk often evolve larger caudal regions. This enhances fast-start escape performance 95
and increases survival in the face of predation [39,40]. 96
While these three types of traits might respond to selection independently, several 97
observations suggest otherwise. First, changes in behavior, metabolism, or hormones might 98
induce changes in morphology [30,32]. Secondly, morphological changes should affect fast-start 99
locomotor performance via trait codependence (sensu [14]), because swimming ability partially 100
derives from the thrust generated by the caudal region of a fish (i.e., the two traits are 101
mechanically linked). Further, correlational selection might favor particular trait combinations 102
such as (1) trait complementation, where boldness only effectively enhances foraging or mating 103
success when combined with high fast-start performance, (2) trait cospecialization, where bold-104
fast individuals and shy-slow individuals have high fitness because the different trait 105
combinations influence different fitness components (e.g., the former may have high mating 106
success but low longevity in high-risk situations, while the latter may have lower mating success 107
but high longevity), or (3) trait compensation, where bold individuals suffer greater frequencies 108
of predatory strikes but compensate for this cost with defensive morphologies or rapid, 109
locomotor escape abilities. Thus, it remains an open empirical question whether these different 110
types of traits evolve independently or in concert. 111
We investigated this question using artificial selection with zebrafish (Danio rerio). We 112
compared two strains selected for bold or shy behavior to determine whether body morphology 113
or locomotor performance exhibited correlated responses to selection. If genetic correlations 114
exist between animal personalities and these non-behavioral traits, then body morphology and 115
swimming abilities should diverge between selection lines as a correlated response to divergent 116
artificial selection on coping style [41–43]. We specifically predicted that artificial selection for 117
boldness would elicit correlated evolutionary responses of larger caudal regions and higher fast-118
start escape performance (and the reverse for shyness). 119
120
2. Material and methods 121
Wild zebrafish from Gaighata, India were selectively bred in captivity for either low or 122
high stationary behavior during an open field test (see [44] for a complete description). Briefly, 123
two selection lines were generated by imposing a selective breeding program beginning with F1 124
fish and repeated each generation, where fish that exhibited at most 16.7% stationary behavior 125
during an open field assay were bred together, and fish that exhibited at least 66.7% stationary 126
behavior were bred together. By the third generation, these two behavioral lines differed 127
consistently in six different measures of stress and anxiety-related behaviors [44]. These sets of 128
consistent differences in multiple behavioral stress responses can be termed bold and shy 129
personalities, or proactive and reactive coping styles [44]. We examined body morphology and 130
locomotor escape performance of adult zebrafish from each of these two coping style lines in 131
both the fourth and fifth generations (4th
generation: 13 females, 16 males; 5th
generation: 11 132
females, 19 males). Zebrafish used for morphological and locomotor examination were age-133
matched across bold and shy lines and had not been exposed to an open field assay prior to 134
examination. Fish were reared at North Carolina State University on a 14:10 light:dark cycle at 135
27.4°C and fed dry flakes ad libitum. 136
137
Morphology 138
We used geometric morphometrics to measure body morphology. We digitized 10 139
anatomical landmarks on lateral photographs of live individuals (Fig. 1a) using tpsDig [45], and 140
generated shape variables (partial warps and uniform components) using tpsRelw [46]. Prior to 141
Generalized Procrustes Analysis in tpsRelw, we performed the unbend function in tpsUtil [47] 142
(this uses several landmarks placed along the midline of the body to minimize postural effects). 143
We used centroid size (square root of the summed, squared distances of all landmarks from their 144
centroid) as the estimate for body size. 145
We tested for morphological differences between coping style lines using multivariate 146
analysis of covariance (MANCOVA), with the 16 geometric shape variables as dependent 147
variables, coping-style line, sex, and their interaction as independent variables, and centroid size 148
as a covariate (controlling for multivariate allometry). To evaluate how morphology differed 149
between lines, we calculated a divergence vector (d) following Langerhans [48], and visualized 150
this axis using thin-plate spline transformations. This divergence vector represents a canonical 151
analysis of the coping-style line term from the MANCOVA, describing the linear combination of 152
shape variables that exhibits the greatest differences between groups, controlling for other factors 153
in the model, in Euclidean space. 154
In our MANCOVA examining body shape differences between lines, we initially 155
included generation as an additional model term, and tested for all possible interactions, but 156
excluded these terms due to non-significance. Coping-style lines and sexes were similar in body 157
size (mean ± standard error for standard length: bold females 29.46 ± 0.89 mm, shy females 158
27.56 ± 0.82 mm, bold males 27.31 ± 0.67 mm, shy males 27.20 ± 0.68). 159
160
Performance 161
Performance trials took place in a square arena (25.4 cm l x 25.4 cm w x 6 cm d) with a 162
transparent bottom and opaque, black sides. Trials were recorded from below using a digital 163
high-speed video camera (Model N4, Integrated Design Tools, Tallahassee, FL, USA) at 600 164
frames s-1
and 1016 x 1016 pixel resolution. Tests were performed after fish were at least 8 165
months old. Testing order was randomized by individual (4th generation) or systematically 166
alternated between bold and shy lines (5th generation). Water temperature was held constant 167
(27.4°C) for all trials. We changed the water between each trial to avoid accumulating any alarm 168
cues. 169
After placing an individual in the arena, we startled each fish by waving a hand over the 170
tank and recorded the fast-start response. A fast-start reflects a rapid, stereotyped Mauthner-cell 171
initiated escape response present in most fish, which enhances survival during predatory 172
encounters [39,40]. We recorded 2–4 trials for each fish and selected one for analysis based on a 173
qualitative score of motivation, as we wished to estimate maximal fast-start capacity and avoid 174
inclusion of trials where individuals obviously performed at less than their maximal capabilities 175
[49]. Trials received a response quality score (poor, fair, good, or excellent) based on a 176
qualitative assessment of the fish’s effort. We only examined responses scored as good or 177
excellent, and included this quality score as a covariate in analyses (see below). 178
We measured fish displacement during the first 80 ms of the escape response by 179
digitizing the center of mass in each video frame using tpsDig. We smoothed displacement data 180
using the mean-squared error quantic spline [50], and used the smoothed data to calculate 181
maximum velocity, average velocity, maximum acceleration, and average acceleration. We 182
measured turning angle and mean angular velocity during stage 1 of the fast-start by digitizing 183
the center of mass and the tip of the snout during stage 1, the earliest part of an escape response 184
where a fish first bends itself into a tightly curved “C” before propelling itself forward (this was 185
typically accomplished within the first 12 ms of the response). 186
In this way we obtained six performance variables for each video sequence: maximum 187
velocity, average velocity, maximum acceleration, average acceleration, and turning angle and 188
mean angular velocity during stage 1 of the fast-start. We tested for differences in fast-start 189
performance between coping-style lines using MANCOVA, with the six performance variables 190
as dependent variables, coping-style line, sex, and their interaction as independent variables, and 191
centroid size, generation, and the response quality score as covariates. We initially tested for all 192
additional interaction terms, but excluded them from final analysis due to non-significance. We 193
used post hoc univariate analyses to interpret the nature of significant effects. In all cases, we 194
used one-tailed tests when examining a priori predictions of differences between coping-style 195
lines. 196
197
3. Results 198
We uncovered strong effects of allometry and sexual dimorphism for body shape, and 199
found significant morphological differences between coping-style lines (Table 1). For both 200
sexes, fish from bold lines exhibited a more elongate body, with larger caudal regions and 201
smaller heads (Fig. 1b,c). 202
Sexes did not differ in fast-start escape response, but effects of all other model terms 203
were evident (Table 2). Post hoc analyses indicated that the main effect of coping style reflected 204
that bold-line fish produced higher average velocities during startle responses (Fig. 2a). The 205
significant interaction term indicated that bold females exhibited a greater turning angle than shy 206
females, but males showed the opposite pattern (Fig. 2b). Other findings included (1) smaller 207
fish tended to produce greater maximum velocity and average angular velocity, and (2) fish from 208
the 4th
generation exhibited higher maximum velocity, maximum acceleration, and average 209
angular velocity than the 5th
generation. 210
211
4. Discussion 212
Zebrafish lines selectively bred for behavioral differences did not merely evolve a 213
correlated set of coping-style differences (often termed personalities), but also diverged in body 214
morphology and locomotor performance. The correlated responses of body shape and swimming 215
performance to artificial selection on an animal personality trait demonstrates genetic 216
correlations among the traits. This means that these traits cannot evolve independently, as the 217
evolution of any of these traits constrains the evolution of the others. Thus, seemingly unrelated 218
traits like body shape and personality can indeed coevolve. The ultimate and proximate causes of 219
these associations, and the prevalence of such associations in nature, require further study. 220
Nonetheless, we have several promising avenues for exploring their causes, and indications that 221
such correlations may prove widespread. Overall, this study represents one of the earliest 222
documentations of correlations between animal personalities and either whole-body morphology 223
or locomotor performance [51,52]. 224
Based on prior work demonstrating changes either in coping style or in morphology and 225
performance, we speculate that the genetic correlations we observed in zebrafish might have 226
ultimately resulted from correlational selection in the wild via predation. In the face of predation, 227
selection might favor increased fast-start velocity in conjunction with boldness, since exploratory 228
and risk-taking behaviors might offer a host of fitness advantages, but only when combined with 229
greater speed and maneuverability due to increased encounters with predators (see Introduction). 230
Meanwhile, shy, slow individuals might exhibit greater longevity, remaining more cryptic, and 231
representing an alternative, high-fitness phenotypic strategy. Most fish are subject to predation in 232
their natural environment, and the few data we have on wild zebrafish suggest they are no 233
exception [53]. Studies of high-predation populations in some fish have revealed selection for 234
greater boldness (although this needs further study), and separate studies have demonstrated 235
larger caudal regions and increased fast-start performance in high-predation populations [40]. 236
These changes appear to increase fitness [39,54]. 237
How might artificial selection for boldness have produced a body shape characteristic of 238
high speed and maneuverability? One proximate explanation is that hormonal or genetic 239
mechanisms have pleiotropic effects on both coping style and body shape. For instance, changes 240
in behavior and metabolism can alter morphologies [28,30,32]. However, it is currently unknown 241
precisely how specific changes in activity, growth, or metabolism across coping style lines might 242
produce the particular body-shape differences observed here. 243
Bold zebrafish tended to exhibit greater average velocity than shy zebrafish, consistent 244
with our prediction. As with pleiotropic effects on behaviors and body morphology, the 245
underlying causes of personality differences might affect locomotor ability as well. However, 246
we consider it more likely that morphology directly influences locomotor performance through 247
biomechanics (e.g., larger caudal regions generate greater thrust during unsteady locomotion 248
[39,40]). Thus, changes in behaviors that indirectly affect morphology can also indirectly affect 249
locomotor performance [31,55]. 250
Female bold fish additionally had significantly greater turning angles, a trait generally 251
reflecting more flexible bodies with greater maneuverability; but this trend reversed for males. 252
What drives this significant interaction is uncertain, but sexual dimorphism in body shape may 253
play a role. 254
The correlated responses of body shape and locomotor performance, observed here in 255
response to artificial selection on an animal personality trait, most likely indicate genetic 256
correlations among the traits, which could arise from pleiotropy, physical linkage or linkage 257
disequilibrium among separate loci [2]. An alternative interpretation is that correlated responses 258
reflect socially-induced phenotypic changes, where bold fish that mostly interact with other bold 259
fish develop different body shapes and locomotor capacities than shy fish that mostly interact 260
with other shy fish. In this scenario, social interactions, and not underlying genes per se, create 261
phenotypic correlations. Because the different selection lines were housed separately in this 262
study, we cannot rule out this explanation. However, to our knowledge, all existing prior 263
information regarding potential causes of these phenotypic differences indicate that this 264
explanation is far less likely than genetic correlations, especially in light of the evidence for 265
pleiotropy and the absence of any previous demonstration of such socially-induced phenotypic 266
consequences. 267
Because correlational selection on animal personalities and non-behavioral traits might be 268
common, and because personalities are underlain by mechanisms with broad phenotypic 269
consequences, we might expect personality to often correlate with non-behavioral traits such as 270
morphology and performance [52,56,57]. However, we currently know very little about 271
morphology-personality associations in nature. If complex behaviors often coevolve with 272
disparate traits like morphology, not only will this alter our understanding of whole-organism 273
adaptation and the role of evolutionary constraints among different types of traits, but we might 274
also apply this knowledge in activities such as livestock improvement, companion-animal 275
breeding, captive breeding programs, and management of pests and invasive species. Results of 276
this study suggest morphology-personality associations exist; now we need further research to 277
understand their frequency and importance. 278
279
We thank R. Wong for experimental assistance and the Langerhans Lab for comments on the 280
manuscript. The study was supported by the NCSU Initiative for Maximizing Student Diversity 281
to DR (NIH-GM083242), NIH grant (1R21MH080500) to JG, and NSF grant (DEB-0842364) to 282
RBL. 283
284
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439
440
Table 1. MANCOVA results examining body shape variation. *one-tailed test. 441
Source F df P
coping style 1.96 16, 39 0.0220*
sex 12.84 16, 39 < 0.0001
sex × coping style 1.38 16, 39 0.2007
centroid size 5.71 16, 39 < 0.0001
442
443
Table 2. MANCOVA results examining variation in fast-start locomotor performance. *one-444
tailed test. 445
Source F df P
coping style 2.24 6, 47 0.0278*
sex 0.76 6, 47 0.6085
sex × coping style 2.60 6, 47 0.0296
centroid size 2.84 6, 47 0.0194
generation 9.28 6, 47 < 0.0001
response quality score 2.63 6, 47 0.0280
446
447
Figure Legends 448
Figure 1. Landmarks used for morphological analysis (a), and morphological differences 449
between bold and shy coping-style lines of zebrafish females (b) and males (c). Body shape 450
variation along the divergence vector, d (see text) depicted with thin-plate spline transformation 451
grids (no magnification; solid lines connecting outer landmarks drawn to aid interpretation). 452
Landmark vectors beneath each set of grids convey the direction and relative magnitude of 453
change in the location of each landmark, pointing toward values characteristic of bold lines. 454
455
Figure 2. Differences in fast-start locomotor performance between coping-style lines in 456
zebrafish (LSM ± SE). 457
Figure 1
shy bold
(b)
(c)
(a)
Figure 2
females males
avera
ge v
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cit
y (
cm
s-1)
30
35
40
45
50
55
60
shy
bold
females males
av
era
ge t
urn
ing a
ngle
(d
eg)
40
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(a) (b)