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Dietary constraints on encephalization in primates.

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AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 120:171–181 (2003)
Dietary Constraints on Encephalization in Primates
Jennifer L. Fish1* and Charles A. Lockwood1,2
1
2
Department of Anthropology, Arizona State University, Tempe, Arizona 85287
Institute of Human Origins, Arizona State University, Tempe, Arizona 85287
KEY WORDS
hypothesis
brain size; comparative methods; independent contrasts; expensive tissue
ABSTRACT
Encephalization, and its relationship to
potential selective forces, have been a focus of many studies of primate adaptation. It has been argued that gut size
may constrain brain mass because these two types of
“expensive tissue” (among others) compete in their metabolic requirements (Aiello and Wheeler [1995] Curr. Anthropol. 36:199 –221). Following from the inverse correlation of gut size with diet quality, the expensive tissue
hypothesis predicts that differences in diet quality are
positively correlated with differences in brain mass, once
the correlation of each variable with body mass is taken
into account. We tested this prediction using both nonphylogenetic and phylogenetic methods. The results of both
methods are consistent with predictions made by the expensive tissue hypothesis. We also discuss several examples of independent contrasts that are consistent with the
hypothesis (e.g., Colobinae vs. Cercopithecinae), as well as
some that are not (e.g., Tarsius vs. anthropoidea). Overall,
the results indicate that improved diet quality, by allowing reduction in relative gut mass, is one mechanism
involved in increased encephalization. Am J Phys Anthropol 120:171–181, 2003. © 2003 Wiley-Liss, Inc.
Relatively large brains, along with enhanced visual and grasping capabilities, are adaptive features
characteristic of all primates. Together, these three
features are critical to primate foraging behavior
and have provided a productive area of inquiry
within the fields of primatology and paleoanthropology. Variation in relative brain mass among primates foraging strategies within the order Primates
has provided the opportunity to test not only why
primates as a whole have relatively large brains, but
also why primates vary in encephalization.
Explanations for the evolution of relatively large
brains in primates have predominantly cited selection for behaviors in response to either social (e.g.,
Byrne and Whiten, 1988; Cheney and Seyfarth,
1985; Barton, 1996; Barton and Dunbar, 1997) or
ecological (e.g., Clutton-Brock and Harvey, 1980;
Harvey and Clutton-Brock, 1985; Foley and Lee,
1992; Milton, 1981, 1988, 1993) challenges. To a
lesser extent, the role of biological constraints in
limiting brain size has been debated (e.g., McNab
and Eisenberg, 1989; Deacon, 1990; Allman et al.,
1993; Aiello and Wheeler, 1995; Martin, 1996). In
this paper, we focus on the latter subject and test
predictions that follow from negative correlations
between gut size and brain mass, specifically, the
predictions of the expensive tissue hypothesis (Aiello and Wheeler, 1995). We investigate whether
diet explains significant variance in brain size independent of that explained by body size.
forefront of the encephalization debate with the introduction of the “expensive tissue hypothesis.” This
hypothesis attempts to explain how the metabolic
cost of relatively large brains can be met without
increasing the basal metabolic rate (BMR). Of particular interest is the fact that humans do not show
an increase in BMR corresponding to their observed
increase in brain mass, which is approximately 5
times that expected for their body mass. In short,
the expensive tissue hypothesis proposes that brain
mass can increase without a corresponding increase
in BMR if another metabolically expensive tissue,
such as the gut, decreases in mass.
Aiello and Wheeler (1995) supported their hypothesis with two essential points. First, they
found a negative correlation between relative gut
size and relative brain size in a small sample of
primates. Second, when the observed and expected
mass of organs in humans was analyzed using a
regression model based on all primates, the total
organ mass fit expectations, but brain mass was
considerably larger than expected, and gut mass
Grant sponsor: Institute of Human Origins; Grant sponsor: Arizona
State University.
*Correspondence to: Jennifer Fish, California Institute of Technology, Biology Division, MC 156-29, Pasadena, CA 91125.
E-mail: fish@caltech.edu
Received 8 January 2001; accepted 13 May 2002.
THE EXPENSIVE TISSUE HYPOTHESIS
Aiello and Wheeler (1995) brought the issue of
biological constraints on relative brain mass to the
©
2003 WILEY-LISS, INC.
DOI 10.1002/ajpa.10136
Published online in Wiley InterScience (www.interscience.wiley.
com).
172
J.L. FISH AND C.A. LOCKWOOD
TABLE 1. Raw data and species included
Species
Strepsirhini
Avahi laniger
Cheirogaleus major
Cheirogaleus medius
Daubentonia madagascariensis
Galago demidoff
Galago senegalensis
Indri indri
Loris tardigradus
Microcebus murinus
Nycticebus coucang
Perodicticus potto
Propithecus verreauxi
Haplorhini
Alouatta seniculus
Aotus trivirgatus
Ateles belzebuth
Ateles geoffroyi
Callicebus moloch
Cebuella pygmaea
Cebus apella
Cercocebus albigena
Cercocebus galeritus
Cercopithecus aethiops
Cercopithecus ascanius
Cercopithecus lhoesti
Cercopithecus mitis
Colobus badius
Gorilla gorilla
Hylobates agilis
Hylobates lar
Hylobates moloch
Macaca fascicularis
Macaca nemestrina
Macaca sinica
Miopithecus talapoin
Nasalis larvatus
Pan troglodytes
Papio anubis
Papio hamadryas
Papio ursinus
Pongo pygmaeus
Presbytis entellus
Presbytis obscura
Saguinus midas
Tarsius bancanus
1
Index of diet quality1
Log brain mass (g)2
Log body mass (g)2
0.42
0.70
0.69
0.84
0.87
0.63
0.55
0.95
0.76
0.71
0.62
0.56
1.00
0.83
0.50
1.65
0.53
0.68
1.58
0.82
0.25
1.10
1.15
1.43
3.02
2.65
2.25
3.45
1.91
2.27
3.80
2.51
1.73
2.90
3.06
3.54
0.51
0.63
0.65
0.61
0.59
0.67
0.87
0.69
0.65
0.69
0.69
0.67
0.68
0.40
0.38
0.54
0.71
0.53
0.74
0.62
0.68
0.78
0.53
0.61
0.66
0.66
0.63
0.59
0.51
0.51
0.77
1.00
1.72
1.23
2.07
2.03
1.28
0.65
1.84
2.02
2.28
1.82
1.83
1.97
1.88
1.89
2.70
1.94
2.01
1.99
1.85
2.09
1.92
1.60
1.99
2.61
2.30
2.21
2.26
2.55
2.30
1.81
1.02
0.56
3.81
2.92
3.95
3.90
2.95
2.15
3.37
3.90
4.03
3.64
3.53
3.93
3.80
3.85
5.02
3.87
3.76
3.79
3.70
3.94
3.92
3.08
4.15
4.66
4.40
4.15
4.39
4.80
4.33
3.85
2.54
2.10
Compiled from Sailer et al. (1985) and Fleagle and Reed (1996).
was significantly smaller than expected. While
their interpretation was limited by the small sample available, the hypothesis of Aiello and Wheeler
(1995) derived from these observations and the
postulated correlated evolution of brain and gut
mass. Thus, “if the changes in the proportions of
the two organs were contemporary evolutionary
events, there is no reason that the BMRs of hominids would ever have been elevated above those
typical of other primates as a consequence of the
energetic costs of encephalization” (Aiello and
Wheeler, 1995, p. 205).
A direct test of the evolutionary relationship of gut
size and brain size in primates is limited by the lack
of quality data on primate gut mass, a difficulty
noted by Aiello and Wheeler (1995). However, they
also emphasized the relationship between gut mass
and diet quality. Drawing primarily on the data of
others, they suggested “that the relationship between relative brain size and diet is primarily a
2
Compiled from Stephan et al. (1981) and Marino (1998).
relationship between relative brain size and relative
gut size, the latter being determined by dietary
quality” (Aiello and Wheeler, 1995, p. 207).
It was shown elsewhere that gut morphology and
size are related to diet quality in mammals (Chivers
and Hladik, 1980). In this context, diet quality refers
to the nutrient content and ease of digestion of a food
source. Mammals consuming low-quality foods, such
as leaves, have large, complex guts. Faunivores have
simple stomachs, and frugivores display an intermediate morphology (Chivers and Hladik, 1980). In
primates, this pattern is exemplified by colobine
monkeys, who have complex guts and a diet consisting predominantly of leaves (Chivers, 1994). Given
that diet quality is a strong correlate of gut mass,
the expensive tissue hypothesis predicts that differences in diet quality are positively correlated with
differences in brain mass, once the effects of potentially confounding factors, such as body mass, are
taken into account.
DIET AND ENCEPHALIZATION
173
Fig. 1. All primates: brain mass residuals vs. diet quality residuals. Residuals were obtained through linear least-squares
regression of each variable on body mass. The regression line has a significantly positive slope (y ⫽ 0.62x). Squares, haplorhines;
circles, strepsirhines.
Although Aiello and Wheeler (1995) concluded
that reducing biological constraints by balancing the
cost of metabolically expensive tissues was essential
to encephalization, the generalization that changes
in brain mass and diet quality were correlated evolutionary events across primates was not tested.
Here, we use multiple comparative methods to examine the evolutionary relationship of diet quality
and brain mass in primates, and test for the correlated evolution of these two traits.
MATERIALS AND METHODS
Variables
The three variables used in this study are whole
brain mass, body mass, and diet quality. Data on
whole brain mass and body mass were taken from
Stephan et al. (1981) and Marino (1998) and logtransformed (base 10) prior to use in analysis. These
data represent species averages. Both brain and
body mass data were derived from the same source
for all species.
Some recent analyses on primate encephalization
preferred to analyze neocortex mass, rather than
whole brain mass. This is sometimes justified because the neocortex, a uniquely mammalian struc-
ture in the forebrain associated with higher cognitive functions, is largely responsible for the
increased mass of the whole brain in primates (Allman, 1999). However, metabolic constraints operate
on the whole brain; therefore, whole brain mass is
the appropriate variable for our analysis.
Diet quality has often been quantified using the
percentage of a specific food type in the diet (e.g.,
percent frugivore; Dunbar, 1992). For our purposes,
it is necessary to create a value for diet quality that
is able to reflect the contribution of a range of food
types to a primate’s diet. We determined diet quality
from the percent of time spent foraging for different
food items, as reported in Sailer et al. (1985) and
Fleagle and Reed (1996).
A continuous, quantitative index for absolute diet
quality was established using the following equation:
DQ ⫽ 0.33L ⫹ 0.67F ⫹ M,
where DQ is the index of diet quality, and L, F, and
M are the percentages of time spent foraging for
leaves, fruit, and meat, respectively. The possible
range of DQ values is 0.33–1. The coefficients of
0.33, 0.67, and 1 serve as a weighting for each food
174
J.L. FISH AND C.A. LOCKWOOD
TABLE 2. Results of regression analyses of diet quality vs. body mass
Nonphylogenetic (species values)
Phylogenetic (independent contrasts)
Group
n
Slope
r
F
P*
n
Slope
r
F
P*
All primates
Strepsirhines
Haplorhines
Anthropoids
44
12
32
31
⫺0.09
⫺0.11
⫺0.11
⫺0.08
⫺0.55
⫺0.46
⫺0.59
⫺0.46
17.98
2.71
15.97
7.88
⬍0.001
0.13
⬍0.001
0.009
43
11
31
30
⫺0.10
⫺0.03
⫺0.13
⫺0.09
⫺0.34
⫺0.08
⫺0.53
⫺0.35
5.61
0.07
11.98
4.01
0.023
0.80
0.0016
0.055
* Two-tailed.
TABLE 3. Results of regression analyses of brain mass (size-adjusted) vs. diet quality (size-adjusted)
Nonphylogenetic (species values)
Phylogenetic (independent contrasts)
Group
n
Slope
r
F
P*
n
Slope
r
F
P*
All primates
Strepsirhines
Haplorhines
Anthropoids
44
12
32
31
0.62
0.58
0.44
0.65
0.50
0.72
0.42
0.59
14.32
11.05
6.32
15.44
⬍0.001
0.008
0.018
⬍0.001
43
11
31
30
0.56
0.62
0.51
0.68
0.60
0.82
0.44
0.57
23.30
20.10
7.36
13.85
⬍0.001
0.001
0.011
⬍0.001
* Two-tailed.
type. The values of these coefficients were chosen to
represent simply the rank of relative nutrient quality and ease of digestion of each type of food (e.g.,
Fleagle, 1999; Janson and Chapman, 1999), and not
any quantitative measure of these features. This
equation is similar to that determined by Sailer et
al. (1985) for estimating dietary quality, differing
only in that we chose a more conservative weighting
for animal matter. Data for all three variables used
in the analysis were available for 44 primate species
(Table 1).
Because brain mass is highly correlated with body
mass (Jerison, 1973; Martin, 1990), we performed a
size-adjustment based on the use of residuals, as
described below. Diet, like many ecological variables, also correlates with body mass (Leonard and
Robertson, 1994). For our data, diet quality and
body mass are significantly negatively correlated in
all groups except within strepsirhines. We report
details of this correlation below, and consequently,
we use size-adjusted values of diet quality to evaluate the relationship of brain mass and diet quality.
Comparative methods
Both nonphylogenetic and phylogenetic comparative methods were used. All analyses used linear
least squares regression analysis, the null hypothesis being that the independent variable does not
explain a significant amount of variance in the dependent variable. The significance of each regression was established with the F-test. Separate analyses were conducted for four clades: all primates,
strepsirhines, haplorhines, and anthropoids.
Nonphylogenetic methods. The nonphylogenetic
methodology first adjusted for body mass through
linear least-squares regression analyses of species
values for brain mass and diet quality (dependent
variables) on body mass (independent variable). Significant results for regressions of diet quality on
body mass justify the size-adjustment. Residual values in the form observed minus predicted are left in
logarithmic form and represent size-adjusted data
(see review by Jungers et al., 1995). To determine
the relationship between brain mass residuals and
diet quality residuals, further regression analyses
were run, with diet quality residuals as the independent variable. Intercepts for the latter analyses are
always zero.
Phylogenetic methods. Nondirectional and directional phylogenetic comparative methods were
also used, following the extensive recent literature
on these methods (e.g., Harvey and Pagel, 1991;
Garland et al., 1992; Sillen-Tullberg and Moller,
1993; Garland and Janis, 1993; DiFore and Rendall, 1994; Mitani et al., 1996; Lindenfors and
Tullberg, 1998; Pagel, 1999). All analyses were
based on the primate phylogeny determined by
Purvis (1995).
The first set of analyses used independent contrasts, with each contrast representing a difference
between two sister groups. This required estimation
of nodal values throughout the phylogeny, and these
were determined using the model of Felsenstein
(1985) and equal branch lengths throughout (i.e., a
“punctuated” model of character evolution). Branch
lengths were not used because divergence dates are
missing for most of the nodes in the phylogeny of
Purvis (1995). Also, Martins and Garland (1992)
showed that independent contrast analyses which
assume equal branch lengths are robust to deviations from that assumption. Together, the independent contrasts represent all possible comparisons
between sister groups in the primate phylogeny.
Contrasts were determined, using the computer program “Comparative Analyses by Independent Contrasts” (Purvis and Rambaut, 1995).
Size-adjustment and tests of association between contrasts followed methods and formulae
described and justified by Garland et al. (1992). To
control for the effects of body mass, independent
contrasts of the dependent variables (diet quality
or brain mass) were regressed on positivized con-
175
DIET AND ENCEPHALIZATION
Fig. 2. All primates: size-adjusted contrasts in brain mass vs. size-adjusted contrasts in diet quality. The regression line has a
significantly positive slope (y ⫽ 0.56x). Squares, haplorhines; circles, strepsirhines; triangle, root contrast.
trasts in body mass, using linear least-squares
regression. Slope values and correlation coefficients (r) were determined for a regression line
forced through the origin (see Harvey and Pagel,
1991; Garland et al., 1992). Residual values from
these analyses represent size-adjusted contrasts
in the same manner that residuals from the regression analysis of species values represent sizeadjusted species values. To test whether diet quality explains a significant amount of variance in
brain mass, size-adjusted contrasts for each variable were then subjected to a linear least-squares
regression, with diet quality contrasts as the independent variable.
The second phylogenetic comparative method was
a test for directional relationship that helps illustrate the phylogenetic relationship between brain
mass and diet quality. In this case, size-adjusted
values for diet quality and brain mass were derived
for each species, using methods described above in
Nonphylogenetic Methods. Residual species values
of diet quality from linear regression on body mass
ranged from ⫺0.3 to 0.3. This range was arbitrarily
divided into six tenths, converting diet quality into
an ordered discrete character with six character
states. With each species thus assigned a character
state, the evolution of diet quality was reconstucted
in MacClade, version 3.07, using accelerated transformation parsimony (Maddison and Maddison,
1992).
Brain mass species residuals were evaluated as a
continuous trait, using a model of squared-change parsimony, also in MacClade. At branches where changes
in diet quality residuals occurred (positive or negative), descendant and ancestral values of brain mass
residuals were compared to identify whether changes
in brain mass were in the same direction as changes in
diet quality. The significance of these results was evaluated using Fisher’s exact test.
RESULTS
Diet quality and body mass
Our index of diet quality is negatively correlated
with body mass in primates as a whole, within haplorhines, and within anthropoids (Table 2). This is
true using phylogenetic or nonphylogenetic methods, although the anthropoid analysis of independent contrasts is only significant at P ⫽ 0.055. These
variables are not significantly correlated in our
small sample of strepsirhines.
All subsequent analyses use residuals from these
regressions as size-adjusted values for diet quality.
This does not affect the results for strepsirhines,
176
J.L. FISH AND C.A. LOCKWOOD
Fig. 3. Strepsirhines: size-adjusted contrasts in brain mass vs. size-adjusted contrasts in diet quality. The regression line has a
significantly positive slope (y ⫽ 0.62x). Note that without the contrast between Daubentonia and Indriidae, the relationship is no
longer significant (n ⫽ 10, r ⫽ 0.55, F ⫽ 3.96, P ⫽ 0.078).
while it results in slightly higher correlations for
analyses of other groups (as expected, given the
negative correlation of diet quality with body mass
in primates).1
Evaluation of predictions
In all analyses of primates as a whole or of subgroups of primates, diet quality and brain mass are
significantly positively correlated (Table 3). Figure 1
shows the nonphylogenetic regression analysis of
size-adjusted values of diet quality and brain mass
for all primates. Analyses of size-adjusted contrasts
in brain mass vs. size-adjusted contrasts in diet
quality are presented in Figure 2 (for all primates),
Figure 3 (for strepsirhines), Figure 4 (for haplorhines), and Figure 5 (for anthropoids).
The directional relationship between changes in brain
mass and diet quality is also highly significant (Table 4).
1
Barton (1999) cautions that correcting two variables for their correlations with a third (such as body mass) can result in spurious
correlations. The differences between our correlation values obtained
using raw diet quality contrasts, and size-adjusted contrasts, range
from 0 – 0.07. No interpretations about the significance of relationships change based on this size-adjustment, but the magnitudes of
correlation and the probability levels are more appropriate. The results are also robust to varying the estimates of body mass used.
For illustrative purposes, Figure 6 depicts the primate
phylogeny used here, with character evolution mapped
onto it. Changes in diet quality and brain mass are
graphically represented by arrows. Evolutionary
changes in diet quality are generally associated with
corresponding changes in brain mass (Fisher’s exact test,
P ⫽ 0.0032). Thus, in branches where diet quality increases, ancestral values for brain size tend to be less
than descendant values, and vice versa. Therefore, the
results of this study are consistent with predictions made
by the expensive tissue hypothesis about the relationship
between diet quality and brain mass.
DISCUSSION
Evaluation of methods
It has been noted that phylogenetic comparative
methods are often applied without first asking
whether variation in the traits of interest is empirically related to phylogeny, and that this may
encourage unnecessary error in the analysis, perhaps by choice of incorrect phylogeny or branch
lengths (Gittleman et al., 1996; Abouheif, 1999). If
variation in the trait is independent of phylogeny,
it may be argued that traditional nonphylogenetic
methods should be applied. However, we also
think phylogenetic methods are useful because of
DIET AND ENCEPHALIZATION
177
Fig. 4. Haplorhines: size-adjusted contrasts in brain mass vs. size-adjusted contrasts in diet quality. The regression line has a
significantly positive slope (y ⫽ 0.51x).
the perspective they offer, regardless of statistical
benefits. In this study, therefore, we do not directly test whether diet quality or brain mass is
strongly influenced by phylogeny prior to evaluating the relationship between them. Instead, by
comparing results from different methods, we indirectly examine the impact of inherited similarity
at different levels of the analysis.
The magnitudes of the correlations (and associated F-tests) between diet quality and body mass, or
diet quality and brain mass, are similar for nonphylogenetic and phylogenetic analyses, with the phylogenetic results slightly more significant. (Tables 2
and 3). This general similarity is noteworthy, given
statements in the literature that nonphylogenetic
comparative methods are essentially invalid (Harvey and Pagel, 1991; Harvey and Purvis, 1991; Martins and Garland, 1992; Purvis and Webster, 1999).
Two inferences can be made from the similarity
among our results: 1) the apparent significance of
the relationship between brain mass and diet quality is not inflated by inherited similarity among
close relatives, and 2) the phylogeny and assumptions used in the phylogenetic comparisons do not
misrepresent the evolution of these traits.
These inferences cannot be generalized beyond
this data set. For example, our sampling of taxa is
broad (across the order Primates) but not particularly dense within major subgroups. If we were to
sample a large number of species within a speciose
genus, a larger phylogenetic effect might become
evident. Moreover, at the broad level of our study,
phylogenetic relationships are relatively wellknown, and phylogenetic comparisons are not likely
to be led astray by problems such as sampling errors
in close relatives (Purvis and Webster, 1999).
A more important result is that for primates as a
whole, the relationship of brain mass to diet quality
is stronger when using independent contrasts than
when using species values. The basis for this is seen
in comparing Figures 1 and 2. Strepsirhines generally have smaller brain masses for a given diet than
do anthropoids. This difference obscures the relationship between brain mass and diet quality when
traditional comparative methods are used. However,
in the analysis of independent contrasts, the difference between clades is reduced to one point (Fig. 2),
and the relationship between variables of interest is
more evident. This result follows other examples
where phylogenetic methods can reduce the confounding effect of differences between speciose
clades, and lends support to the use of these methods (Nunn and Barton, 2001, p. 94).
178
J.L. FISH AND C.A. LOCKWOOD
Fig. 5. Anthropoids: size-adjusted contrasts in brain mass vs. size-adjusted contrasts in diet quality. The regression line has a
significantly positive slope (y ⫽ 0.68x).
TABLE 4. Directional test of the relationship between
diet quality and brain mass1
Brain mass
Diet quality
Increase
Decrease
1
Increase
Decrease
10
1
2
7
One-tailed Fisher’s exact test, P ⫽ 0.0032.
Individual contrasts
Phylogenetic methods serve not only to account
for the statistical effects of inherited similarity; they
are also useful in that they allow for further understanding of the comparative relationship through
the examination of influential contrasts. This can be
shown with several examples. First, the highest correlation between brain mass and diet quality occurs
within Strepsirhini (Table 3). However, the significance of the correlation is limited due to small sample size. In fact, the high correlation depends largely
on a single contrast, that of Daubentonia vs. Indriidae (Fig. 3). Relative to other strepsirhines, the
insectivorous Daubentonia has a large brain and a
high-quality diet. Daubentonia also displays high
levels of sensorimotor intelligence, which may be
linked to the extractive foraging behavior of these
animals (Sterling and Povinelli, 1999).
In contrast, the correlation between brain size and
diet quality in anthropoids is consistent throughout
the clade. Two examples in particular illustrate this
relationship. These are the contrasts of Cercopithecinae vs. Colobinae and Pan vs. Gorilla, which
are highlighted in Figure 5. Colobines and cercopithecines are morphologically distinct in their dietary adaptations. The sharply cusped teeth and
large, complex stomachs of colobine monkeys reflect
their adaptation to a high-cellulose diet (Fleagle,
1999). Differences in brain mass between the subfamilies correspond to differences in diet and gut
morphology. A similar divergence in diet quality and
brain mass characterizes the African hominoids. Gorillas have a primarily folivorous diet, while chimpanzees, with relatively larger brains, specialize in
ripe fruits.
Both of these examples reflect contrasts between
sister groups that have very different lifestyles. In
each case, there is a clear divergence in dietary
adaptation that is also associated with a difference
in relative brain size. By highlighting closely related
species where there has been a significant evolutionary change in both brain mass and diet quality since
their divergence from a common ancestor, we are
DIET AND ENCEPHALIZATION
179
Fig. 6. Directional phylogenetic test for Primates (relationships derived from Purvis, 1995). Arrows indicate direction of change
between nodes. Brain mass (size-adjusted) is represented by solid arrow-halves; diet quality (also size-adjusted) is represented by open
arrow-halves. See text for further explanation.
180
J.L. FISH AND C.A. LOCKWOOD
better able to evaluate the overall pattern of the
relationship between these traits.
Finally, the Tarsius vs. Anthropoidea contrast
(noted in Fig. 4) demonstrates an interesting exception encountered in this study that deviates especially from the overall pattern within haplorhines.
Tarsiers have small brains relative to anthropoids,
even after adjusting for body mass. At the same
time, they are completely insectivorous, which gives
them the highest possible index value for diet quality. The difference represented by this contrast is
sufficient to alter the correlation coefficient within
haplorhines, as the addition of the tarsier as the
sister group to anthropoids has a dramatic negative
effect on the correlation (see Table 3). The effect can
also be seen in Figure 4, where the contrast between
tarsiers and anthropoids is exceptional, given the
trend among other contrasts.
It has been suggested that outlying contrasts in
phylogenetic comparisons often indicate distinct
evolutionary trajectories within different clades
(“grade shifts,” Martin and Harvey, 1985; Nunn and
Barton, 2001). One possibility, then, is that the Tarsius-Anthropoidea contrast reflects a shift in brain
mass relative to diet quality between prosimians
and anthropoids. As can be seen in Figure 1, Tarsius
is similar to many strepsirhines in its relatively
small brain mass.
Another possible explanation for its low brain
mass is the fact that Tarsius has the largest orbits of
all primates relative to skull size (Kay and Cartmill,
1977; Martin, 1990). Martin (1990) suggested that
tarsier eyes are large to compensate for the absence
of the tapetum lucidum in these nocturnal animals.
It may be that orbit volume, in this extreme condition, has a role in constraining brain volume. Determining which of these alternative hypotheses best
explains the pattern observed in Tarsius warrants
further investigation.
CONCLUSIONS
Consistent with the expensive tissue hypothesis
(Aiello and Wheeler, 1995), diet quality and brain
mass are significantly positively correlated in primates as a whole, and evolutionary changes in diet
quality are directionally related to evolutionary
changes in relative brain mass. Moreover, comparisons between nonphylogenetic and phylogenetic
comparative methods provide broadly similar results, increasing confidence in the overall trend. In
primates as a whole, phylogenetic methods appear
to be more appropriate, as they are less affected by
the confounding differences in relative brain mass
between strepsirhines and anthropoids.
Relative brain mass may ultimately be influenced
by multiple factors, perhaps including selection on
social behavior and foraging strategy. However, we
agree with suggestions that physiological constraints are a primary factor affecting brain mass.
Our results support the hypothesis that improved
diet quality is one mechanism involved in the evolution of relatively large brains, by allowing reduc-
tion in relative gut mass. Deviations from the overall pattern (e.g., Tarsius) may illustrate the effect of
other constraints and warrant further investigation.
ACKNOWLEDGMENTS
We thank John Fleagle, Bill Jungers, Bill Kimbel,
Charlie Nunn, Kaye Reed, and three anonymous
reviewers for their comments and suggestions on
earlier drafts of the manuscript.
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