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AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 00:00–00 (2014)
Seasonality of Diet Composition is Related to Brain Size in New World Monkeys Janneke T. van Woerden, Carel P. van Schaik, and Karin Isler* Anthropological Institute and Museum, University of Zurich, CH-8057 Zurich, Switzerland KEY WORDS
encephalization; phylogenetic analysis; Platyrrhini
ABSTRACT New World monkeys exhibit a more pronounced variability in encephalization than other primate taxa. In this comparative study, we tested two current hypotheses on brain size evolution, the Expensive Brain hypothesis and the Cognitive Buffer hypothesis, in a sample of 21 platyrrhine species. A high degree of habitat seasonality may impose an energetic constraint on brain size evolution if it leads to a high variation in caloric intake over time, as predicted by the Expensive Brain Hypothesis. However, simultaneously it may also provide the opportunity to reap the fitness ben-
The primate infraorder Platyrrhini, or New World monkeys, exhibits a more pronounced variability in brain size relative to body mass than other primate taxa such as catarrhines or strepsirhines (Isler et al., 2008). Differences are mainly found at a high taxonomic level, between genera or families (Allen and Kay, 2012), indicating an early adaptive radiation with respect to brain size. In this study, we aim to investigate two current hypotheses on seasonality and brain size evolution in this diverse taxon, using a broad phylogenetic comparative approach on a newly compiled sample. The two hypotheses are depicted in Figure 1. First, an energetic viewpoint on brain size variation (Isler and van Schaik, 2009) predicts that the evolution of relatively large brains is constrained by the high costs of growing and maintaining the brain during the periods of food scarcity characteristic for highly seasonal habitats (van Woerden et al., 2010). Thus, if habitat, i.e., external seasonality, is reflected in a high variation in caloric intake over time, we expect this experienced seasonality to be negatively correlated with relative brain size across species. On the other hand, the Cognitive Buffer hypothesis proposes that the main selective advantage of having a relatively large brain and thus enhanced cognitive abilities is to deal better with novel or varying ecological conditions (Allmann et al., 1993; Deaner et al., 2003; Sol, 2009). Behavioral flexibility in finding alternative resources through cognitive means may help to avoid starvation during lean seasons. Fitness benefits of large brains would then be most pronounced in more seasonal habitats, and relatively large-brained species would be more likely to evolve or thrive in such habitats. If this effect prevails, we expect a positive correlation between brain size and habitat seasonality across species. Supporting this notion, Neotropical parrots living in more seasonal habitats were found to have relatively larger brains than those living in climatically less seasonal habitats (Schuck-Paim et al., 2008). However, the high costs of brain tissue (Niven and Laughlin, 2008)
efits of increased cognitive abilities, which enable the exploitation of high-quality food resources even during periods of scarcity, as predicted by the Cognitive Buffer hypothesis. By examining the effects of both habitat seasonality and the variation in monthly diet composition across species, we found support for both hypotheses, confirming previous results for catarrhine primates and lemurs. These findings are in accordance with an energetic and ecological view of brain size evolution. Am J Phys Anthropol 000:000–000, 2014. VC 2014 Wiley Periodicals, Inc.
may constrain energy budgets and thus outweigh any potential positive fitness effects of cognitive buffering in larger-brained species. Reader and MacDonald (2003) found no correlation between climatic variability and either relative brain size or behavioral flexibility in African anthropoid primates, which they interpreted as an absence of cognitive buffering in this group. However recently, we reported evidence for the effects of both cognitive buffering and energetic constraints on brain size in catarrhine primates; these effects more or less cancel each other, leading to the absence of a correlation between habitat seasonality and brain size (van Woerden et al., 2012). Lemurs living in more seasonal habitats even have relatively smaller rather than larger brains, because the cognitive buffer effect is weak in this taxon (van Woerden et al., 2010). Thus, to test the cognitive buffer hypothesis it is crucial not simply to look at environmental seasonality, but rather at the amount of buffering, that is, the difference between habitat seasonality and the experienced variation in net energy intake.
Additional Supporting Information may be found in the online version of this article. Grant sponsor: Swiss National Science Foundation; Grant numbers: 3100A0–117789 and 31003A-144210; Grant sponsor: Synthesis and the A. H. Schultz Foundation, Zurich, Switzerland. *Correspondence to: Karin Isler, Anthropological Institute and Museum, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland. E-mail: [email protected] Received 28 January 2014; accepted 20 May 2014 DOI: 10.1002/ajpa.22546 Published online 00 Month 2014 in Wiley Online Library (wileyonlinelibrary.com).
Ó 2014 WILEY PERIODICALS, INC.
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J.T. VAN WOERDEN ET AL.
Fig. 1. Correlations between relative brain size and seasonality as predicted by an energetic constraint and the cognitive buffer hypothesis. If the two effects are equally strong, we expect no correlation between relative brain size and habitat seasonality. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.] TABLE 1. Phylogenetic models for testing the effects of seasonality on brain size
(A)
Model parameters
Body mass CV_diet ResidualsBuffer (B)
Model parameters
Body mass CV_diet ResidualsBuffer % leaves in diet
Platyrrhini N 5 21
Catarrhini N 5 36
Lemuriformes N 5 19
k 5 1, j 5 2.80, F 5 78.8, AIC 5 233.8
K 5 0.94, j 5 1.74, F 5 75.5, AIC 5 257.0
k 5 0.74, j 5 2.77, F 5 132.8, AIC 5 213.0
Estimate
P
Estimate
P
Estimate
P
0.819 20.902 0.662
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AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 00:00–00 (2014)
Seasonality of Diet Composition is Related to Brain Size in New World Monkeys Janneke T. van Woerden, Carel P. van Schaik, and Karin Isler* Anthropological Institute and Museum, University of Zurich, CH-8057 Zurich, Switzerland KEY WORDS
encephalization; phylogenetic analysis; Platyrrhini
ABSTRACT New World monkeys exhibit a more pronounced variability in encephalization than other primate taxa. In this comparative study, we tested two current hypotheses on brain size evolution, the Expensive Brain hypothesis and the Cognitive Buffer hypothesis, in a sample of 21 platyrrhine species. A high degree of habitat seasonality may impose an energetic constraint on brain size evolution if it leads to a high variation in caloric intake over time, as predicted by the Expensive Brain Hypothesis. However, simultaneously it may also provide the opportunity to reap the fitness ben-
The primate infraorder Platyrrhini, or New World monkeys, exhibits a more pronounced variability in brain size relative to body mass than other primate taxa such as catarrhines or strepsirhines (Isler et al., 2008). Differences are mainly found at a high taxonomic level, between genera or families (Allen and Kay, 2012), indicating an early adaptive radiation with respect to brain size. In this study, we aim to investigate two current hypotheses on seasonality and brain size evolution in this diverse taxon, using a broad phylogenetic comparative approach on a newly compiled sample. The two hypotheses are depicted in Figure 1. First, an energetic viewpoint on brain size variation (Isler and van Schaik, 2009) predicts that the evolution of relatively large brains is constrained by the high costs of growing and maintaining the brain during the periods of food scarcity characteristic for highly seasonal habitats (van Woerden et al., 2010). Thus, if habitat, i.e., external seasonality, is reflected in a high variation in caloric intake over time, we expect this experienced seasonality to be negatively correlated with relative brain size across species. On the other hand, the Cognitive Buffer hypothesis proposes that the main selective advantage of having a relatively large brain and thus enhanced cognitive abilities is to deal better with novel or varying ecological conditions (Allmann et al., 1993; Deaner et al., 2003; Sol, 2009). Behavioral flexibility in finding alternative resources through cognitive means may help to avoid starvation during lean seasons. Fitness benefits of large brains would then be most pronounced in more seasonal habitats, and relatively large-brained species would be more likely to evolve or thrive in such habitats. If this effect prevails, we expect a positive correlation between brain size and habitat seasonality across species. Supporting this notion, Neotropical parrots living in more seasonal habitats were found to have relatively larger brains than those living in climatically less seasonal habitats (Schuck-Paim et al., 2008). However, the high costs of brain tissue (Niven and Laughlin, 2008)
efits of increased cognitive abilities, which enable the exploitation of high-quality food resources even during periods of scarcity, as predicted by the Cognitive Buffer hypothesis. By examining the effects of both habitat seasonality and the variation in monthly diet composition across species, we found support for both hypotheses, confirming previous results for catarrhine primates and lemurs. These findings are in accordance with an energetic and ecological view of brain size evolution. Am J Phys Anthropol 000:000–000, 2014. VC 2014 Wiley Periodicals, Inc.
may constrain energy budgets and thus outweigh any potential positive fitness effects of cognitive buffering in larger-brained species. Reader and MacDonald (2003) found no correlation between climatic variability and either relative brain size or behavioral flexibility in African anthropoid primates, which they interpreted as an absence of cognitive buffering in this group. However recently, we reported evidence for the effects of both cognitive buffering and energetic constraints on brain size in catarrhine primates; these effects more or less cancel each other, leading to the absence of a correlation between habitat seasonality and brain size (van Woerden et al., 2012). Lemurs living in more seasonal habitats even have relatively smaller rather than larger brains, because the cognitive buffer effect is weak in this taxon (van Woerden et al., 2010). Thus, to test the cognitive buffer hypothesis it is crucial not simply to look at environmental seasonality, but rather at the amount of buffering, that is, the difference between habitat seasonality and the experienced variation in net energy intake.
Additional Supporting Information may be found in the online version of this article. Grant sponsor: Swiss National Science Foundation; Grant numbers: 3100A0–117789 and 31003A-144210; Grant sponsor: Synthesis and the A. H. Schultz Foundation, Zurich, Switzerland. *Correspondence to: Karin Isler, Anthropological Institute and Museum, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland. E-mail: [email protected] Received 28 January 2014; accepted 20 May 2014 DOI: 10.1002/ajpa.22546 Published online 00 Month 2014 in Wiley Online Library (wileyonlinelibrary.com).
Ó 2014 WILEY PERIODICALS, INC.
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J.T. VAN WOERDEN ET AL.
Fig. 1. Correlations between relative brain size and seasonality as predicted by an energetic constraint and the cognitive buffer hypothesis. If the two effects are equally strong, we expect no correlation between relative brain size and habitat seasonality. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.] TABLE 1. Phylogenetic models for testing the effects of seasonality on brain size
(A)
Model parameters
Body mass CV_diet ResidualsBuffer (B)
Model parameters
Body mass CV_diet ResidualsBuffer % leaves in diet
Platyrrhini N 5 21
Catarrhini N 5 36
Lemuriformes N 5 19
k 5 1, j 5 2.80, F 5 78.8, AIC 5 233.8
K 5 0.94, j 5 1.74, F 5 75.5, AIC 5 257.0
k 5 0.74, j 5 2.77, F 5 132.8, AIC 5 213.0
Estimate
P
Estimate
P
Estimate
P
0.819 20.902 0.662
