Overview

What factors and selective pressures have contributed to the evolution of increased neuron density in birds? The long-standing social complexity hypothesis first proposed by Humphrey (1976) suggests that selection pressures associated with group living and increasing social complexity of within-group interactions are likely a primary driver of observed increased cognitive abilities and larger brains. Correlative support for this hypothesis has been found in studies on mammals, and notably within primates (Finlay et al. 2001) and cetaceans (Glezer et al. 1988, Barton and Harvey 2000), that have used comparative approaches to explore relationships between brain morphology and size and metrics of social complexity (e.g., mean group size, mating system,etc.). Alternatives to the social complexity hypothesis exist, and factors including metabolically- and ecologically-driven selection pressures also have likely contributed to the evolution of increased brain size and neuronal density, which in turn, provide positive feedback and would benefit the organization of socially complex group dynamics among species. Interestingly, several studies have explored these ideas in context of the ‘expensive tissue hypothesis’ related to energy constraints (Isler and Schaik 2006, Isler and Van Schaik 2006). Moreover, Isler and Van Schaik (2009) propose a ‘grey ceiling’ hypothesis to explain the counter-intuitive patterns found in birds that may push the limits on maintaining relatively larger brains through benefits conferred via social interactions that can increase lifetime fitness. The ‘grey ceiling’ hypothesis also holds implications for connections between physical energy and metabolic links between individuals and limits of population growth rates (Isler and Van Schaik 2009).

A recent study tested the social complexity hypothesis in non-human primate species (N = 140) by comparing metrics of social complexity with brain size, and controlling for the influences of body size and diet (DeCasien et al. 2017). Additionally, DeCasien et al. (2017) found that frugivorous species had larger brains than folivorous species, and that diet was overall, a stronger predictor of brain size than social complexity. Given these findings in primates, it would be very interesting to test whether the social complexity hypothesis using data from bird species that vary among taxa in their social complexity, life-history and primary foraging type, physiology, and brain size. In a previous study, Beauchamp and Fernández-Juricic (2004) compared avian brain mass to mean group size was unable to find a relationship, suggesting that ecological factors (e.g., diet and physiological constraints) may have played a more important role in shaping observed evolutionary patterns of brain size and neuron density in birds.

Here, we test the social complexity hypothesis and its explanatory power of the evolution of increased brain size and neuron density. The goal of this study is to investigate the relationship between avian body mass (g) and various region-specific avian brain metrics and the metabolic scaling relationships for frugivores and non-frugivores such as, brain mass (g), number of neurons, and neuronal densities (neurons per mg). The study then will model these relationships while controlling for phylogenetic relationships among species, social behavior covariates, and migratory behavior.



Methods

We compiled information for unique bird species (N = 1,707) ranging in body size, brain mass, diet, social complexity, and migratory behavior (see Appendix A). For all analyses, values were transformed using a natural log transformation to visualize non-linear relationships on a log-log scale. This is useful for comparison to previously-described non-linear scaling exponents (and their variation) relative to ‘universal’ scaling laws (West et al. 1997, West and Brown 2005, Glazier 2008).

Comparative avian brain data

We compiled data from previous studies on multiple species that included whole brain mass (Symonds et al. 2016), whole brain mass and region-specific brain volumes (Boire and Baron 1994), and whole brain mass, region-specific brain masses, and neuron abundance and density (Olkowicz et al. 2016). Other sources of brain data include a large data set from Sayol et al. (2016) of body mass and brain volume (cm^3).

Diet classification of species into categories

We followed previously used methods that quantified avian diets and classified species into foraging guilds based on the species’ diet constituents (Şekercioğlu et al. 2004, Daniel Kissling et al. 2009, Sayol et al. 2016). Documented food items identified in dietary studies that examined gut contents, fecal sample, or used other methods (e.g., stable isotopes) were organized into the broad categories, which we then collapsed into either a binary categorical variable: Frugivore or Non-frugivore. Frugivores here, are defined as any species that has any documented fruits within the diet, and hence include many omnivorous species. Conversely, non-frugivores are defined as species having no fruits within the diet.

Migratory behavior classification

We used a combination of data from Şekercioğlu et al. (2004), Sayol et al. (2016), and data from http://www.birdlife.org/ to designate species as either Migratory, Non-migratory, or Unknown.

Next Steps:

  • Look at plots of residuals from log-log regressions *generate plots that compare mean and var of scaling exponents, similar to Glazier (2008)
  • Add group size, developmental (i.e., precocial, semi-precocial, altricial, semi-altricial) covariates, lifespan, etc. for use in phylogenetic regression models, to test for differences between frugivore and non-frugivores compile population growth rates (means for families), beyond scope of this paper, but will be needed to explore ‘gray ceiling’ hypothesis more fully Begin draft of manuscript



Figure 1. One of 10,000 phylogenetic trees of bird species (N = 1,707) from http://www.BirdTree.org