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Biological Journal of the Linnean Society, 2015, 115, 173–184. With 2 figures
The macroevolutionary relationship between diet and
body mass across mammals
SAMANTHA A. PRICE1* and SAMANTHA S. B. HOPKINS2
1
Department of Evolution and Ecology, University of California, 1 Shields Avenue, Davis, CA 95616,
USA
2
Department of Geological Sciences, 1272 University of Oregon, Eugene, OR 97403, USA
Received 22 December 2014; accepted for publication 24 December 2014#
Body mass and diet are two fundamental ecological parameters that influence many other aspects of an animal’s
biology. Thus, the potential physiological and ecological processes linking size and diet have been the subject of
extensive research, although the broad macroevolutionary relationship between the two traits remains largely
unexplored phylogenetically. Using generalized Ornstein–Uhlenbeck models and data on over 1350 species of
mammal, we reveal that evolutionary changes in body mass are consistently associated with dietary changes across
mammals. Best-fitting models find that herbivores are substantially heavier than other dietary groups and that
omnivores are frequently intermediate in mass between herbivores and carnivores. Interestingly, although flying
and swimming both place very different physical constraints on mass, bats still follow the general mammalian
pattern but marine mammals do not. Such differences may be explained by reduced gravitational constraints on
size in water along with ecological differences in food availability between aquatic and terrestrial realms, allowing
marine carnivores to become the largest mammals on earth. © 2015 The Linnean Society of London, Biological
Journal of the Linnean Society, 2015, 115, 173–184.
ADDITIONAL KEYWORDS: mammalia – omnivory – Ornstein–Uhlenbeck model – phylogenetic comparative analysis.
INTRODUCTION
Body size is frequently described as one of the most
fundamental characteristics of animals because as
many ecological, biomechanical and physiological
traits scale predictably with size (Schmidt-Nielsen,
1984; Savage et al., 2004). Pragmatically, because size
is easy to measure on most living organisms and
can be estimated from museum specimens or fossil
animals (Damuth & MacFadden, 1990; Kosnik et al.,
2006; Alroy, 2012), this allometric relationship is
exploited such that size can serve as a proxy for the
more difficult-to-obtain traits (Peters, 1986; Rodriguez,
1999; Broughton et al., 2011). As a consequence, patterns of body size in time and space have been widely
studied across taxa (Lawton, 1990; Smith et al., 2004;
Venditti, Meade & Pagel, 2011; Raia et al., 2012).
*Corresponding author. E-mail: [email protected]
#Reviewed by Axios Review
Mammals have been the focus of many studies of
body size because extant species span eight orders of
magnitude in size (Jones et al., 2009) and data are
widely available for living species, as well as some
extinct groups (Smith et al., 2003; Jones et al., 2009).
A few general conclusions have emerged from these
studies; the first is that the distribution and range of
body sizes in mammals was much smaller in the
Mesozoic than it is in extant mammals (Lillegraven,
Kielan-Jaworowska & Clemens, 1979; Alroy, 1998).
The wide range of sizes in extant mammals was
established in the early Paleogene (Alroy, 1998; Smith
et al., 2010) and, for the past 50 Myr, has remained
fairly consistent through time and across continents
(Alroy, 1998; Smith et al., 2004; Smith & Lyons, 2011).
Meanwhile, minimum size has remained relatively
constant throughout the history of mammals, suggesting a lower limit (Alroy, 1998). The tempo of body
size evolution across extant lineages of mammals,
however, remains disputed. Many studies conclude
© 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, 115, 173–184
173
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S. A. PRICE and S. S. B. HOPKINS
that large changes in size occurred at the origin of
major taxonomic groups (Raia et al., 2013) and, subsequently, body size changed rapidly within each
order and then slowed down (Cooper & Purvis, 2010).
Consistent with these conclusions, size is also found
to be highly conserved within taxonomic groups, from
congeners to orders (Smith et al., 2004, 2010). By
contrast, Venditti et al. (2011) argue that size changes
rapidly across mammals, whenever it is advantageous, and that there is no pattern of early bursts of
size evolution. Nonetheless, all studies agree that
mammalian body size evolution is not simple; it has
been influenced by a complex set of interacting factors
(Smith et al., 2004, 2010; Cooper & Purvis, 2010;
Venditti et al., 2011) that can include phylogeny,
ecology, and climate.
Diet is one of the foremost ecological factors
that interacts with body size at all scales, from
the lifespan of an individual through to a
macroevolutionary time-scale, because it provides the
energy and nutrition required to grow and sustain
mass. Naturally, larger mammals have greater absolute energy requirements than smaller species; thus,
simple resource availability may be responsible for
patterns of body size evolution, with the largest
species feeding on the most common resources. In
terrestrial environments, the traditional biomass
pyramid illustrates that plants have the largest available biomass (Elton, 1927). By contrast, numerous
studies have demonstrated a drastically different
structure of trophic resources in aquatic habitats (as
reviewed by Shurin, Gruner & Hillebrand, 2006),
with the inversion of the traditional biomass pyramid.
Therefore, all else being equal, we would expect the
largest land mammals to be herbivores and the smallest carnivores and potentially the opposite in marine
mammals as a result of different resource availability
in terrestrial and marine realms.
An exceedingly influential hypothesis for the last 40
years, the Jarman–Bell principle (Jarman, 1968; Bell,
1971; Geist, 1974), links diet and size not only
through the availability of food but also its digestibility. First articulated by Geist (1974) this principle
states that ‘the body size and population biomass of
ungulate species is a function of the fibre content
(digestibility) and density of the forage they exploit’,
with a negative relationship between digestibility
and mass. Geist explained the existence of this relationship in terms of mass-specific metabolic rates,
energy and protein requirements scaling with
mass∼0.75 (Kleiber, 1947). Therefore, small-bodied
species require more energy per day per unit mass,
which can only be sustained on highly digestible
foods. Although developed in herbivorous hoofed
mammals, the Jarman–Bell principle has subsequently been extended to other taxa and diets
(frugivory, gummivory, and insectivory in primates:
Gaulin, 1979; Isbell, 1998; frugivory in bats: Fleming,
1991; carnivory in whales: Tershy, 1992) and has
inspired numerous studies to investigate potential
mechanisms driving the link between diet and mass
(Illius & Gordon, 1992; Clauss et al., 2007, 2013;
Müller et al., 2013). However, recent studies have
challenged the existence of any physiological link
between diet quality and mass within herbivores
(Clauss et al., 2013; Müller et al., 2013) and have
instead argued for greater focus on ecological
explanations.
Studies of the drivers of body size evolution commonly assume that diet plays a role in constraining
body size, and it is often included as a confounding
factor in such analyses (Peters & Raelson, 1984;
Robinson & Redford, 1986; Fa & Purvis, 1997).
However, the large-scale, macroevolutionary relationship between diet and body size has not been investigated across mammals, nor in a robust phylogenetic
context. Even within herbivorous mammals, comparative analyses of a relationship between body mass and
diet are rare (Clauss et al., 2013), although some
small-scale, family level analyses have been performed (Brashares, Garland & Arcese, 2000).
However, if there is a strong mechanistic link
between diet and mass, then, regardless of the precise
nature of that relationship, we would expect to see a
consistent association between diet and mass, even at
the largest phylogenetic scales. In the present study,
we describe the large-scale patterns by combining
existing data on trophic strategy (herbivory, carnivory
or omnivory) in mammals (Price et al., 2012) with
datasets on adult mass (Smith et al., 2003; Jones
et al., 2009) in a phylogenetic context (BinindaEmonds et al., 2007, 2008; Fritz, Bininda-Emonds &
Purvis, 2009) with the aim of investigating: (1) has
diet influenced body mass evolution consistently
across mammals and within individual clades and (2)
does the relationship between mass and diet differ
depending on whether mammals are terrestrial,
volant or marine? We predict that herbivorous
mammals will be larger than carnivorous species and
that habitat will mediate this relationship as the
availability of food changes between habitats, as do
physical constraints on size (e.g. bats: Norberg &
Rayner 1987; whales: Downhower & Blumer, 1988).
MATERIAL AND METHODS
DATA
Each species was classified as either herbivorous,
carnivorous or omnivorous using our previously published database of mammalian diets collated from the
scientific literature (Price et al., 2012). We collected
© 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, 115, 173–184
MAMMALIAN MASS AND DIET
reports based on stomach or cheek-pouch contents or
the contents of food stores, direct behavioural observation or faecal analysis, and recorded complete
descriptions of diet. Although this strict approach to
diet data limits the completeness of coverage, we
avoid diet data based only on the diets of related
organisms, on morphological inference or on unsupported assertions to avoid biasing our results with the
evolutionary implications of anecdotal ecological data.
We then applied uniform and explicit criteria to
convert quantitative and qualitative descriptions to a
repeatable discrete character coding using the
presence/absence of four types in the diet: invertebrate protein, vertebrate protein, fibrous plant
parts (mature leaves, stem, wood, and bark), and
nonfibrous plant parts (any other parts of the plant,
as well as fungi and lichens). We assigned each
species to a trophic strategy, herbivore (plants only),
carnivore (animal protein only) or omnivore (a combination of plants and animal protein), based on the
character coding. Although some subtleties will inevitably be lost by including a diverse range of diets
within a single category (Pineda-Munoz & Alroy,
2014) (e.g. grazers and frugivores are both herbivores), this coarse categorization allows us to investigate the broadest patterns in the relationship
between body mass and diet across mammals. Similarly, we recognize that omnivory may not be a cohesive dietary strategy (Chivers & Langer, 1994;
Pineda-Munoz & Alroy, 2014) but, because there are
hypotheses that predict specific constraints on the
size of mammals that only eat plants (Clauss et al.,
2003, 2007) or animals (Carbone, Teacher &
Rowcliffe, 2007), we have assigned species that eat a
recognizable portion of both plants and animals to a
separate category, aiming to distinguish them from
the strategies limited to a single trophic level.
We combined this dietary data with adult body
mass data from two existing databases (Smith et al.,
2003; Jones et al., 2009), generating a dataset of 1389
species of mammal for which we had both traits. Body
mass data was natural log-transformed prior to
analysis. Figure 1 illustrates the distribution of body
mass in each dietary category in each clade used in
our analyses.
Our analyses require a comprehensive phylogeny of
extant mammalian species, and so we used the timecalibrated mammalian supertree (Bininda-Emonds
et al., 2007, 2008) updated to use the latest taxonomy
(Fritz et al., 2009). Polytomies were resolved using
the birth–death method of Kuhn, Mooers & Thomas
(2011) and 100 trees were sampled from the resulting
distribution of trees. Although the age estimates from
this phylogeny may be older than the true dates
(O’Leary et al., 2013) our analyses should be unaffected as the Ornstein–Uhlenbeck (OU) models that
175
we implement only require relative dates. Where
there were more recent and comprehensive timecalibrated phylogenies, we used them for the individual clade analyses: primates (Arnold, Matthews &
Nunn, 2010), carnivores (Nyakatura & BinindaEmonds, 2012), and rodents (Fabre et al., 2012). For
primates, we downloaded 100 topologies randomly
sampled from the posterior distribution from the 10k
trees website (Arnold et al., 2010). For rodents, the
posterior distribution of trees was not available
(Fabre et al., 2012) and so we used the maximum
clade credibility tree and resolved the polytomies
using the methods of Kuhn et al. (2011); this generated 10 000 topologies from which we sampled 100.
For carnivores, we used the best, upper and lower
bound dates from the recent supertree (Nyakatura &
Bininda-Emonds, 2012) and again resolved the
polytomies using the methods of Kuhn et al. (2011).
We generated 10 000 topologies, from which we
sampled 90 from the best dates and five each from the
upper and lower-bound dates.
EVOLUTIONARY
MODEL
To investigate the evolutionary influence of diet upon
size we used generalized OU models (Beaulieu et al.,
2012) in a model-fitting framework. By using OU
models, we can determine whether and how diet
influences: the optimal body size (θ), the rate of stochastic motion of body mass evolution (σ2), and/or the
strength of attraction towards the optima (α). θ is the
primary optimum, a hypothetical entity representing
the trait value reached by an ‘infinite number of
populations identical to the common ancestor evolving independently’ with diet in a fixed state (Hansen,
1997: 1342). Thus, θ is quite different from both the
realized trait optima in real populations (Hansen,
1997) and the controversial hypothesis of an optimal
size for mammals (Brown, Marquet & Taper, 1993). α
is the strength of pull towards the primary optimum;
it determines how quickly the primary optimum will
be reached following a state change and reflects the
phylogenetic covariance between species (Hansen,
1997). If the estimate of α is high, this indicates that
diet places a strong constraint on size around the
estimated optima and the influence of phylogenetic
history is wiped out. On the other hand, if α is
approaching zero, this suggests diet places weak constraints on size and phylogenetic covariance is
strong. Under some circumstances, the time to reach
a new optimum may even exceed the age of the clade,
as indicated by the phylogenetic half-life (Hansen,
1997). In such situations, if the best-fitting model
includes θ, the estimated θ values can be thought of
as differences in the phylogenetic mean between
dietary strategies. σ2 is a constant describing the rate
© 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, 115, 173–184
176
S. A. PRICE and S. S. B. HOPKINS
60
40
0
Frequency
Herbivores
Omnivores
Carnivores
20
Herbivores
Omnivores
Carnivores
80
Terrestial Mammals
0 20 40 60 80
Frequency
All Mammals
0
5
10
15
20
0
5
Ln Body Mass (g)
15
10
0
Frequency
Herbivores
Omnivores
Carnivores
5
10
15
20
0
5
Ln Body Mass (g)
10
20
15
20
Frequency
30
Herbivores
Omnivores
0 5 10
80
60
40
20
0
5
15
Primates
Herbivores
Omnivores
Carnivores
0
10
Ln Body Mass (g)
Chiroptera
Frequency
20
5
Herbivores
Omnivores
Carnivores
0
20
0
5
Ln Body Mass (g)
10
15
20
Ln Body Mass (g)
Cetartiodactyla
Terrestrial Cetartiodactyla
30
20
10
Frequency
Herbivores
Omnivores
0
10
20
30
Herbivores
Omnivores
Carnivores
0
Frequency
15
Marsupialia
0 10 20 30 40 50
Frequency
Rodentia
0
5
10
15
20
0
5
Ln Body Mass (g)
10
15
20
Ln Body Mass (g)
15
Terrestrial Carnivora
10
Omnivores
Carnivores
0
0
5
10
Frequency
Omnivores
Carnivores
5
15
Carnivora
Frequency
10
terrdat[, 3][terrdat[, 2] == 1]
0
5
10
15
Ln Body Mass (g)
20
0
5
10
15
20
Ln Body Mass (g)
Figure 1. Distribution of body mass for each trophic strategy. Histograms showing the distribution of adult body mass
of herbivores (green), carnivores (blue), and omnivores (purple) in ln(g). The vertical lines represent the median body mass
for each category.
of stochastic evolution around the optimum and,
when α = 0, the OU model collapses to a simple
Brownian motion model, with σ2 commonly referred
to as the Brownian motion rate parameter. If rates of
Brownian motion differ between dietary strategies,
all else being equal, faster rates indicate that there is
greater body size disparity between closely-related
species (O’Meara et al., 2006) with the same diet.
However, when α exceeds zero, σ2 and α together
determine the variance around the optima (Hansen,
1997): the faster the rate and the weaker the
strength of pull towards the optima, the greater
the expected disparity between closely-related
species.
Using the model-fitting framework, we fit models
that allow one or more of the three OU parameters to
© 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, 115, 173–184
MAMMALIAN MASS AND DIET
vary. Two models allow size to evolve independently of
diet: one is a simple single-rate Brownian model
(BM1) where size differences between species are
proportional to the time since they last shared a
common ancestor. The other is a single-optimum
model (OU1) where every species under consideration
is evolving towards the same primary optimum. If
either of these are the best-fitting model, then there is
no evidence that diet influences mammalian body
mass evolution. The other models allow diet to influence one or more of the three parameters. The BMS
model allows only σ2 to differ between diets, which
means diet influences the rate of body mass evolution
but there is no indication that mass itself differs
between species with different dietary strategies.
The two peak OUM model allows θ to vary between
dietary categories and the estimated primary optima
will indicate the influence of diet on mass. In the
OUM model α, the strength of pull towards the different θ values, is the same, whereas the OUMA
model, in addition to allowing θ to vary between
dietary strategies, also estimates a different α for
each diet. Therefore, if OUMA is the best-fitting
model, this indicates that some diets place greater
constraints upon size than others. Finally, the OUMV
model allows both θ and σ2 to vary between dietary
strategies with a single strength of attraction towards
the different optima (α).
PHYLOGENETIC
COMPARATIVE ANALYSIS
Internal branches were assigned to a dietary category
using stochastic character mapping (Nielsen, 2002;
Huelsenbeck, Nielsen & Bollback, 2003). For analyses
across mammals and within clades, we generated 50
maps on each of the 100 initial trees, setting the prior
at the maximum likelihood of the parameter estimate
(PHYTOOLS; Revell, 2012). This generated a total of
5000 maps, from which we sampled 500 to use in the
analyses of diet and body mass. Summarizing parameter estimates across a sample of stochastically
mapped trees may bias the estimates to be more
similar to each other than their underlying generating values (Revell, 2013), and so any observed differences are likely to reflect true differences in mass.
We fit these six generalized OU models across all
extant mammals in our dataset (1389 species), as well
as within each large order or clade (i.e. 100 or more
species with data): Carnivora (e.g. cats, weasels and
bears), Primates (e.g. apes), Cetartiodactyla (e.g.
whales, dolphins, deer, and cows), Rodentia (e.g. rats,
mice, and squirrels), Chiroptera (i.e. bats), and
Marsupialia (e.g. kangaroos, opossums). This allowed
us to assess whether there is one optimal size for each
dietary category across all mammals and if there are
differences between clades. Large changes in size may
177
have occurred at the origin of major taxonomic groups
(Raia et al., 2012) and so it may be unreasonable to
expect all herbivores from rodents to deer to be evolving towards the same optimum body size. We therefore expect weak α estimates across mammals.
Additionally, to investigate the influence of habitat,
we also fit the models across all terrestrial mammals
(1065 species) and the terrestrial members of the
Cetartiodactyla and Carnivora.
The analyses were run in R software (R_Core_Team
(2013) using OUwie version 1.34 (Beaulieu et al.,
2012). The most complex model, which estimates a
separate σ2, θ, and α for every dietary category
(OUMVA), did not converge in our preliminary analyses of eight trees and so it was not fit to the full
dataset. Preliminary analyses also indicated that
assuming θ at the root is distributed according to the
stationary distribution of the OU process helped to
stabilize the estimates of body size optima for each
diet and so root.station = TRUE was used for all
analyses. Because of the size of the mammal and
terrestrial mammal datasets, the analyses were batch
processed; each tree was analyzed separately with
two trees run on each vCPU of 250 Amazon Web
Services high CPU medium instances running
Amazon Linux. Analyses took between 24 and 48 h
per tree, for a total computing time of 8641 h. The
individual clade analyses were much quicker and ran
serially on two quad-core 2.83GHz Intel Xeon E5440
processors running CENTOS (http://www.centos.org).
We checked the results of the OUwie analyses to
ensure that the eigenvalues of the Hessian were positive because this is an indicator that the parameters
were reliably estimated (Beaulieu et al., 2012). When
a negative value was found, the results for that
model and tree combination were removed from the
data. Even after the removal of models with suboptimal likelihood as indicated by the eigen decomposition of the Hessian, a very few models still
estimated body mass optima that were far beyond
what is biologically feasible, and so we also removed
results that did not fall within the extant range of
mammalian body sizes (from 160 000 kg for blue
whales to bumblebee bats at approximately 2 g). The
number of analyses that did not converge for each
dataset are given in the Supporting information
(Tables S1, S2). Using the Akaike criterion corrected
for small sample size (AICc; Hurvich & Tsai, 1989),
we calculated the relative strength of the evidence for
each model in the set using the Akaike weight
(Burnham & Anderson, 2002) on each of the 500
SIMMAP trees. The SEs on the parameters for the
best-fitting model were calculated using a combination of the SDD across the 500 SIMMAP trees and
the SE given by OUwie, which is the diagonal of the
inverse of the Hessian matrix.
© 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, 115, 173–184
178
S. A. PRICE and S. S. B. HOPKINS
RESULTS
According to the Akaike weights (Table 1), the bestfitting model across all 1389 mammals in our dataset
is one that allows diet to influence both the optimal
body mass and the rate of body mass evolution
(OUMV, AICc weight = 1) but not the strength of pull
towards the optima. The parameters estimates from
the best-fitting model (Fig. 2, Table 2) reveal that
herbivores have the largest optimal mass (median
78.43 kg) with the optima for omnivores and carnivores substantially lower but highly overlapping
(median 0.67 kg and 0.59 kg, respectively). We
recover similar results when terrestrial mammals
were analyzed alone; OUMV is the best-fitting model
and herbivores have the largest optimum mass
(median 81.80 kg) but the optima are more distinct
for omnivores and carnivores (median of 0.89 kg and
0.46 kg, respectively). The differences in rates are
minimal between dietary strategies but the highest
rates of body mass evolution, which generate greater
body size variability, are estimated in herbivores and
carnivores across all mammals and when only terrestrial mammals are analyzed (Table 2). The α estimates are low: 0.000001 for all mammals and 0.002
for terrestrial mammals.
A similar pattern is recovered within bats and
marsupials; the best fitting models are OUMV and
OUM respectively, and the body mass optima are
more clear-cut, with herbivores largest (median mass
of 58 g for bats and 16.12 kg for marsupials), omnivores intermediate (median mass of 19 g for bats and
0.15 kg for marsupials) and carnivores smallest
(median mass of 14 g for bats and 55 g for marsupials). Again, the difference in rates from the OU model
are minimal between dietary strategies in marsupials
but, in bats, the rate of carnivore body mass evolution
is almost three times faster than within omnivores
and herbivores. As expected, within orders, where
body size is less variable, the α parameters are
higher: 0.011 in marsupials and 0.035 in bats. The
pattern is the same within primates: OUM, OUMV,
and OUMA models are equally supported by the data
with distinct herbivore and omnivore body mass
optima (OUMV: median mass 3.94 kg and 0.506 kg,
respectively) but with very weak pulls towards the
optima (α = 0.000001). Within rodents, the best fitting
model is still OUMV but, although herbivorous
species have the highest estimated body size optimum
(median mass 311 g), the optimal carnivore mass is
estimated to be larger than that for omnivores
(median mass of 132 g and 66 g, respectively) with
α = 0.014. The highest rates of body size evolution
from the OU models occur within herbivorous rodents
at almost twice the rate of body size evolution within
omnivorous species.
The Cetartiodactyla and Carnivora results are
very different because they contain both terrestrial
and marine groups. When analyzed as a clade (terrestrial and marine species included), the best-fitting
models are OUMV for cetartiodactyls and BMS +
OUMV for carnivorans. The estimated optimal
masses are highest for carnivorous species
(Cetartiodactyla: median mass 2698 kg; Carnivora:
Table 1. Model support given by the median Akaike criterion corrected for small sample size (AICc) weight
All mammals
Terrestrial mammals
Marsupials
Cetartiodactyla
Terrestrial Cetartiodactyla
Rodentia
Carnivora
Terrestrial Carnivora
Primates
Chiroptera
BM1
BMS
OU1
OUM
OUMV
OUMA
0.000
0.000
0.015
0.000
0.014
0.001
0.005
0.001
0.031
0.000
0.020
0.001
0.004
0.000
0.226
0.004
0.250
0.116
0.055
0.000
0.000
0.000
0.005
0.000
0.875
0.002
0.011
0.010
0.011
0.000
0.000
0.000
0.712
0.013
0.000
0.038
0.005
0.004
0.266
0.008
1.000
0.964
0.117
0.919
0.000
0.498
0.227
0.279
0.333
0.880
0.000
0.004
0.108
0.024
0.000
0.152
0.134
0.218
0.302
0.101
AICc weights indicate the support for the model within the model set and it ranges from 0 (no support) to 1 (full support).
Models highlighted in bold are those with the strongest support; the rows do not sum to one because this is the median
AICc weight across 500 stochastically mapped trees. The absolute number of times each model is the best-fitting model
is given in the Supporting information (Table S2). There are two Brownian motion models, BM1 fits a single rate of
stochastic motion (σ2) across mammals, while BMS fits a model with different rates for each diet. There are four
Ornstein-Uhlenbeck models. OU1 fits a single optima (θ) for body mass across mammals. OUM fits different optima for
each diet but the same stochastic motion (σ2) and attraction (α) parameters. OUMA fits different optima and different
attraction parameters and OUMV fits different optima and different stochastic motion parameters for each diet.
© 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, 115, 173–184
MAMMALIAN MASS AND DIET
1.5
Herbivore
Omnivore
Carnivore
1.0
1.5
0.5
1.0
0.0
0.5
0.0
Density
Herbivore
Omnivore
Carnivore
2.0
Terrestrial Mammals
2.0
All mammals
0
5
10
15
20
0
5
2.0
1.5
1.0
Density
0.5
0.0
0
5
10
15
20
0
5
20
10
15
20
15
20
Primates
15
10
5
0
Density
15
0.0 0.2 0.4 0.6 0.8 1.0
Chiroptera
0
5
10
15
20
0
5
10
Terrestrial Cetartiodactyla
0
2
4
6
8
0.0 0.5 1.0 1.5 2.0 2.5
Cetartiodactyla
Density
10
Marsupialia
0.0 0.5 1.0 1.5 2.0 2.5
Rodentia
0
5
10
15
20
0
5
10
15
20
Terrestrial Carnivora
0.0
0.0
0.5
0.5
1.0
1.0
1.5
1.5
2.0
2.0
Carnivora
Density
179
0
5
10
15
Ln Body Mass (g)
20
0
5
10
15
20
Ln Body Mass (g)
Figure 2. Estimated primary optima of mass for each trophic strategy. The probability density distribution of optimal adult
body mass (θ) of herbivores (green), carnivores (blue), and omnivores (purple) in ln(g) from the best-fitting generalized
Ornstein–Uhlenbeck (OU) model for each dataset. The probability density was generated by running the analyses on 500
stochastically mapped trees thereby representing the uncertainty in the result as a result of phylogeny, branch length, and
the mapping of trophic strategy upon the tree. The vertical lines represent the median θ for each category.
© 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, 115, 173–184
θ is the primary body mass optimum, α is the strength of attraction to the optimum, and σ2 is the rate of stochastic motion. NA, not applicable.
0.000 ± 0.004
0.002 ± 0.006
0.011 ± 0.545
0.029 ± 1.049
NA
0.014 ± 0.493
0.015 ± 0.823
NA
0.026 ± 0.908
0.035 ± 0.316
NA
NA
NA
0.035 ± 0.448
0.000 ± 0.004
0.002 ± 0.006
0.011 ± 0.545
0.029 ± 1.049
0.028 ± 1.282
0.014 ± 0.493
NA
NA
NA
NA
0.000 ± 0.008
0.000 ± 0.027
0.000 ± 0.006
0.035 ± 0.448
OUMV
OUMV
OUM
OUMV
OU1
OUMV
OUMV
BMS
OUMV
OUMA
OUMV
OUM
OUMA
OUMV
All mammals
Terrestrial mammals
Marsupials
Cetartiodactyla
Terrestrial Cetartiodactyla
Rodentia
Carnivora
Carnivora
Terrestrial Carnivora
Terrestrial Carnivora
Primates
Primates
Primates
Chiroptera
11.270 ± 2.838
11.312 ± 2.624
9.688 ± 1.849
11.253 ± 0.763
11.147 ± 0.537
5.741 ± 0.698
NA
NA
NA
NA
8.280 ± 1.22
8.510 ± 815397
8.320 ± 1.257
4.066 ± 0.554
6.387 ± 1.895
6.500 ± 2.244
6.127 ± 1.511
6.795 ± 1.870
4.002 ± 1.470
5.020 ± 0.830
14.808 ± 1.045 10.606 ± 0.925
NA
11.147 ± 0.537
4.886 ± 1.284
4.187 ± 0.834
9.535 ± 1.144
8.857 ± 0.993
NA
NA
9.037 ± 0.788
8.827 ± 0.986
8.933 ± 1.062
8.863 ± 0.866
NA
6.226 ± 1.073
NA
6.481 ± 1587818
NA
6.280 ± 1.044
2.668 ± 0.173
2.964 ± 0.578
0.074 ± 0.070
0.076 ± 0.084
0.079 ± 2.548
0.144 ± 4.377
0.137 ± 5.245
0.079 ± 2.644
NA
NA
NA
NA
0.017 ± 0.008
0.023 ± 0.027
0.023 ± 0.007
0.055 ± 0.558
0.085 ± 0.055
0.071 ± 0.039
0.079 ± 2.548
0.238 ± 11.061
NA
0.028 ± 0.643
0.062 ± 3.720
0.052 ± 0.145
0.074 ± 6.647
0.145 ± 1.453
NA
NA
NA
0.099 ± 2.004
0.044 ± 0.004
0.049 ± 0.065
0.079 ± 2.548
0.011 ± 1.901
0.137 ± 5.245
0.067 ± 1.421
0.180 ± 8.799
0.152 ± 0.494
0.236 ± 4.141
0.145 ± 1.453
0.028 ± 0.009
0.023 ± 0.027
0.023 ± 0.007
0.028 ± 0.838
Carnivore α
Herbivore α
Omnivore σ2
Carnivore σ2
Herbivore σ2
Omnivore θ
Carnivore θ
Herbivore θ
Model
Clade
Table 2. Parameter estimates and their SEs from the best-fitting model(s)
0.000 ± 0.004
0.002 ± 0.006
0.011 ± 0.545
0.029 ± 1.049
0.028 ± 1.282
0.014 ± 0.493
0.015 ± 0.823
NA
0.026 ± 0.908
0.025 ± 0.343
0.000 ± 0.008
0.000 ± 0.027
0.000 ± 0.006
0.035 ± 0.448
S. A. PRICE and S. S. B. HOPKINS
Omnivore α
180
median mass 13.84 kg), with α = 0.029 in cetartiodactyls and 0.015 in carnivorans. When only the
terrestrial species are analyzed, the best-fitting
model is a single-optima model (OU1) for herbivorous and omnivorous cetartiodactyls (α = 0.028) and
OUMV/OUMA models for Carnivora but the body
size optima for carnivores and omnivores are highly
overlapping (α = 0.035).
DISCUSSION
Our findings offer robust phylogenetic evidence for
an evolutionary link between mammalian diet and
adult body mass that is mediated by habitat and
phylogenetic history. Across all mammals and almost
every clade, the best-fitting models all with strong
support according to AIC weights estimate a separate
optimal mass (θ) for each trophic strategy but the
same strength of pull towards that optima (OUMV or
OUM models). Moreover, these models consistently
estimate the optimal herbivore body mass to be substantially heavier than that of omnivores and carnivores, except in the clades that contain marine groups
(Cetartiodactyla and Carnivora) where the carnivores
are the heaviest.
By contrast to our expectation, models with separate α values for each dietary category were not
preferred, and so there is little evidence that omnivorous mammals experience a weaker pull towards
their optimal mass. Generally, there is at best a very
weak pull towards the optimal sizes that we estimate
for any diet in any dataset. Across mammals, this is
not unexpected because major taxonomic groups
differ greatly in size (Cooper & Purvis, 2010; Raia
et al., 2012) and so we expect phylogenetic constraint
to be strong, as indicated by low α values (Hansen,
1997). The strongest α values that we estimate are in
bats, which may reflect that size is also constrained
by the requirements of flight. But, even within bats,
the phylogenetic half-life [ln(2)/α] (Hansen, 1997) (i.e.
the time it takes to move half-way to a new primary
optimum) is 19 Myr. Thus, a bat lineage that switches
diets would take approximately 38 Myr to evolve the
mass optimal for that diet, which is more than half
the crown-age of Chiroptera (Teeling, 2009). We therefore interpret this slow rate of adaptation as an
indication that size is still highly constrained by
phylogeny within orders, a conclusion that is consistent with the finding that body size generally has a
strong phylogenetic signal (Blomberg, Garland &
Ives, 2003). However, it is clear that diet does influence body size because models with separate θ values
for each dietary category fit the data much better
than Brownian motion models.
Although both volant and marine mammals experience different physical constraints on mass relative
© 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, 115, 173–184
MAMMALIAN MASS AND DIET
to terrestrial species, it is only the marine habitat
that appears to influence the relationship between
diet and size. Bats are necessarily small because the
demands of powered flight cause positive allometric
loading of the wings with increasing body mass
(Norberg & Rayner, 1987; Norberg, 1990) but fruit
bats are still heavier than insectivorous bats and
omnivorous species are intermediate. The vast majority of extant marine mammals are carnivorous:
pinnipeds nested within Carnivora and the cetaceans
nested within Cetartiodactyla, with the only exception being the herbivorous Sirenia (dugongs and
manatees). In both pinnipeds and cetaceans, the estimated θ for carnivores exceeds that of other trophic
strategies. Removing the aquatic species from the
analyses yields results more compatible with the patterns across mammals, indicating that the large sizes
obtained by whales and pinnipeds are inconsistent
with patterns for the terrestrial members of both
clades. However, our result is consistent with recent
theoretical work on the differing body size constraints
on marine carnivores. The drastically different structure of trophic resources in aquatic habitats (Shurin
et al., 2006) suggests that the amount of animal
protein available to marine mammals exceeds that of
plant material; thus, the marine realm should be able
to sustain more and larger carnivorous species than
the terrestrial biome. In particular, the abundance
and clumped distribution of small prey in marine
systems is likely to be important to the ability of
exceptionally large carnivores to depend on smallsized prey species (Tucker & Rogers, 2014). The presence of large filter-feeding carnivores may simply be
the result of foraging efficiency and the scaling of
metabolic demands in aquatic habitats (Carbone
et al., 2014). Moreover, the three-dimensional structure of pelagic habitats, where most aquatic vertebrates forage, allows greater rates of prey capture
and, in turn, enables greater body size among consumers than in the more two-dimensional terrestrial
habitats (Pawar, Dell & Savage, 2012). Unrelated to
diet, the more rapid heat loss in water also makes
larger sizes beneficial for aquatic homeotherms and
the buoyant environment reduces gravitational constraints on body mass, allowing marine carnivores
to evolve to even greater sizes than terrestrial
herbivores.
In the absence of marine groups, clade-specific differences are also evident: the overall results are
repeated in marsupials, primates, and bats, although
rodents and terrestrial cetartiodactyls are different.
Rodents show a greater body mass for carnivores than
for omnivores. This result may be a reflection of the
very limited group of carnivorous rodents upon which
this inference is based (21 of 409 rodent species
included in this analysis) because carnivory is rare
181
among rodents (Landry, 1957). However, intriguingly,
at least 11 out of the 21 carnivorous rodents are
semi-aquatic (Anotomys, Chibchanomys, Ichthyomys,
Neusticomys, and Rheomys), feeding on fish, crabs,
and aquatic snails; thus, the larger size may again
reflect greater prey availability or, indeed, adaptations to more rapid heat loss in aquatic environments.
Similarly, the relatively large estimated size for omnivores in the terrestrial Cetartiodactyla may reflect
the existence of very few omnivores in this clade (only
five of 145 terrestrial cetartiodactyl species included
in our analyses are omnivores) and/or the fact that
the omnivorous artiodactyls such as pigs, peccaries
and a few duikers have relatively plant-rich diets and
evolved from ancestors with plant-dominated diets
(Harris & Cerling, 2002).
Our results potentially offer additional insights into
the nature of mammalian omnivory. Within terrestrial and volant clades, the estimated omnivore mass
is much closer to the carnivore θ than the herbivore θ
(Fig. 1, Table 2). This finding suggests that omnivores
may not be eating the most widely available plant
parts such as leaves and stems, which are also more
difficult to digest but, instead, prefer to feed on seeds
and fruits, etc., that have more patchy distributions
spatially and temporally but are more energy rich.
This inference is consistent with the observations on
gut length, which find that intermediate lengths
between the short carnivore and long herbivore guts
are within frugivores (Chivers & Langer, 1994) and
with the fact that, within our dataset, just over half of
all omnivorous species combine animal protein with
only nonfibrous plant parts. Therefore, if we were to
use more fine-grained dietary categories we would
expect frugivores and omnivores to have similar
optimal masses, whereas the optimum for folivores
would be much heavier.
The immense range of body sizes represented by
living mammals is a testimony to the ecological diversity represented by mammals. Our results provide an
important addition to previous large-scale studies of
mammalian body size evolution (Smith et al., 2003,
2004, 2010; Cooper & Purvis, 2010; Venditti et al.,
2011) by explicitly examining the relationship
between mass and diet because the availability of
food items and potentially different nutritional contents are two of the factors hypothesized to interact
with body size (Jarman, 1968; Bell, 1971; Geist, 1974;
Clauss et al., 2013). Although a strong relationship
between diet and size has been assumed for years,
its existence has never been fully tested in a
phylogenetic framework across mammals with a wide
variety of diets. Our analyses therefore confirm for
the first time, using robust phylogenetic methods,
that there is a consistent macroevolutionary relationship between trophic strategy and body mass, within
© 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, 115, 173–184
182
S. A. PRICE and S. S. B. HOPKINS
clades and across terrestrial and volant mammals. In
general, herbivores are larger than omnivores and
carnivores and, although omnivores are intermediate,
their mass is far more similar to that estimated for
carnivores. This pattern is reversed in clades that
include marine taxa (Carnivora and Cetartiodactyla):
carnivores are substantially heavier than herbivores
and omnivores. Such consistent findings at a broad
scale may reflect the existence of a universal
mechanism linking diet and mass and, with the main
differences identified between marine and the terrestrial biomes, there is a hint that it may be ecological
in nature.
ACKNOWLEDGEMENTS
We thank Kathleen Smith and V. Louise Roth for
early discussion and their collaboration in collecting
the dietary data. Jeremy Beaulieu and Brian O’Meara
offered help and discussion with implementing OUwie
analyses, as did Christopher Oufiero. We also want to
thank Marcus Clauss for thorough and thoughtful
comments on an earlier version of this manuscript, as
well as V. Louise Roth, Lars Schmitz, and Edward
Davis. This work was supported by NESCent shortterm visitor awards (NSF-0717009) and an NSF grant
(DEB-1256897) to SAP and SSBH. The authors
declare that they have no competing interests. We
thank Axios Review (axiosreview.org) for the efficient
reviewing of this paper.
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SUPPORTING INFORMATION
Additional Supporting Information may be found in the online version of this article at the publisher’s web-site:
Table S1. Number of trees where model did not converge.
Table S2. Number of trees where model was the best-fit.
SHARED DATA
The data sets used in the present study have been published and are available in the Dryad digital repository,
(Price & Hopkins, 2015) and the Ecological Archives repository (http://esapubs.org/archive/ecol/E090/184/
default.htm) and [http://www.esapubs.org/archive/ecol/e084/094/]. The mammalian phylogeny used is available
as supporting information for Fritz et al. (2009): (http://onlinelibrary.wiley.com/doi/10.1111/j.1461-0248.2009
.01307.x/suppinfo). The 500 primate phylogenies were downloaded from the 10k trees website (http://
10ktrees.fas.harvard.edu), whereas the carnivore and rodent phylogenies are available online as additional files:
carnivores (Nyakatura & Bininda-Emonds, 2012: http://www.biomedcentral.com/content/supplementary/17417007-10-12-s5.nex) and rodents (Fabre et al., 2012: http://www.biomedcentral.com/1471-2148/12/88/additional).
© 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, 115, 173–184