Stepwise Model Fitting and Statistical Inference: Turning Noise into Signal Pollution

Statistical inference based on stepwise model selection is applied regularly in ecological, evolutionary, and behavioral research. In addition to fundamental shortcomings with regard to finding the “best” model, stepwise procedures are known to suffer from a multiple‐testing problem, yet the method is still widely used. As an illustration of this problem, we present results of a simulation study of artificial data sets of uncorrelated variables, with two to 10 predictor variables and one dependent variable. We then compared results from stepwise regression with a regression model in which all predictor variables were entered simultaneously. These analyses clearly demonstrate that significance tests based on stepwise procedures lead to greatly inflated Type I error rates (i.e., the probability of erroneously rejecting a true null hypothesis). By using a simple simulation design, our study amplifies previous warnings about using stepwise procedures, and we follow others in recommending that biologists refrain from applying these methods.Anthropolog

Rapid Evolution of Social Learning

Culture is widely thought to be beneficial when social learning is less costly than individual learning and thus may explain the enormous ecological success of humans. Rogers (1988. Does biology constrain culture. Am. Anthropol. 90: 819–831) contradicted this common view by showing that the evolution of social learning does not necessarily increase the net benefits of learned behaviours in a variable environment. Using simulation experiments, we re-analysed extensions of Rogers' model after relaxing the assumption that genetic evolution is much slower than cultural evolution. Our results show that this assumption is crucial for Rogers' finding. For many parameter settings, genetic and cultural evolution occur on the same time scale, and feedback effects between genetic and cultural dynamics increase the net benefits. Thus, by avoiding the costs of individual learning, social learning can increase ecological success. Furthermore, we found that rapid evolution can limit the evolution of complex social learning strategies, which have been proposed to be widespread in animals.Human Evolutionary Biolog

Predation and the Phasing of Sleep: An Evolutionary Individual-based Model

All mammals thus far studied sleep, yet important questions remain concerning the ecological factors that influence sleep patterns. Here, we developed an evolutionary individual-based model to investigate the effect of predation pressure on prey sleep. We investigated three ecological conditions, including one that assumed a dynamic interaction between predator and prey behaviour. In condition 1, we found that monophasic predators (i.e. with one sleep bout per 24 h) select for monophasic prey that sleep perfectly out of phase with predators. In condition 2, predators were monophasic but the safety of prey varied as a function of their activity (sleeping versus awake). In this condition, the prey adjusted their sleeping behaviour to lower the risk of predation. Finally, in condition 3, we modelled a more dynamic interaction between predator and prey, with predator activity dependent on prey activity in the previous hour. In this scenario, the prey adjusted their behaviour relative to one another, resulting in either greater or lesser synchrony in prey as a function of predator searching behaviour. Collectively, our model demonstrates that predator behaviour can have a strong influence on prey sleep patterns, including whether prey are monophasic or polyphasic (i.e. with many sleep bouts per 24 h). The model further suggests that the timing of sleep relative to predator behaviour may depend strongly on how other potential prey partition the activity period.Human Evolutionary Biolog

Investigating the Impact of Observation Errors on the Statistical Performance of Network-based Diffusion Analysis

Experiments in captivity have provided evidence for social learning, but it remains challenging to demon- strate social learning in the wild. Recently, we developed network-based diffusion analysis (NBDA; 2009) as a new approach to inferring social learning from observational data. NBDA fits alternative models of asocial and social learning to the diffusion of a behavior through time, where the potential for social learning is related to a social network. Here, we investigate the performance of NBDA in relation to variation in group size, network heterogeneity, observer sampling errors, and duration of trait diffusion. We find that observation errors, when severe enough, can lead to increased Type I error rates in detecting social learning. However, elevated Type I error rates can be prevented by coding the observed times of trait acquisition into larger time units. Collectively, our results provide further guidance to applying NBDA and demonstrate that the method is more robust to sampling error than initially expected. Supplemental materials for this article may be downloaded from http:// lb.psychonomic-journals.org/content/supplemental.Human Evolutionary Biolog

Phylogenetic Targeting of Research Effort in Evolutionary Biology

Many questions in comparative biology require that new data be collected, either to build a comparative database for the first time or to augment existing data. Given resource limitations in collecting data, the question arises as to which species should be studied to increase the size of comparative data sets. By taking hypotheses, existing data relevant to the hypotheses, and a phylogeny, we show that a method of “phylogenetic targeting” can systematically guide data collection while taking into account potentially confounding variables and competing hypotheses. Phylogenetic targeting selects potential candidates for future data collection, using a flexible scoring system based on differences in pairwise comparisons. We used simulations to assess the performance of phylogenetic targeting, as compared with the less systematic approach of randomly selecting species (as might occur when data have been collected without regard to phylogeny and variation in the traits of interest). The simulations revealed that phylogenetic targeting increased the statistical power to detect correlations and that power increased with the number of species in the tree, even when the number of species studied was held constant. We also developed a Web‐based computer program called PhyloTargeting to implement the approach (http://phylotargeting.fas.harvard.edu).Human Evolutionary Biolog

Community Structure and the Spread of Infectious Disease in Primate Social Networks

Living in a large social group is thought to increase disease risk in wild animal populations, but comparative studies have provided mixed support for this prediction. Here, we take a social network perspective to investigate whether patterns of social contact within groups influence parasite risk. Specifically, increased modularity (i.e. sub-grouping) in larger groups could offset the increased disease risk associated with living in a large group. We simulated the spread of a contagious pathogen in random social networks to generate theoretically grounded predictions concerning the relationship between social network connectivity and the success of socially transmitted pathogens. Simulations yielded the prediction that community modularity (Q) negatively impacts parasite success. No clear predictions emerged for a second network metric we considered, the eigenvector centralization index (C), as the relationship between this measure and parasite success depended on the transmission probability of parasites. We then tested the prediction that Q reduces parasite success in a phylogenetic comparative analysis of social network modularity and parasite richness across 19 primate species. Using a Bayesian implementation of phylogenetic generalized least squares and controlling for sampling effort, we found that primates living in larger groups exhibited higher Q, and as predicted by our simulations, higher Q was associated with lower richness of socially transmitted parasites. This suggests that increased modularity mediates the elevated risk of parasitism associated with living in larger groups, which could contribute to the inconsistent findings of empirical studies on the association between group size and parasite risk. Our results indicate that social networks may play a role in mediating pressure from socially transmitted parasites, particularly in large groups where opportunities for transmitting communicable diseases are abundant. We propose that parasite pressure in gregarious primates may have favored the evolution of behaviors that increase social network modularity, especially in large social groups.Human Evolutionary Biolog

Gap Analysis and the Geographical Distribution of Parasites

Sampling biases can have enormous impacts on studies of parasite biogeography. While complete sampling is sometimes possible for local or regional patterns of parasitism, continental and global analyses often rely on data collected in a heterogeneous manner. At these larger scales, spatially-explicit methods to quantify and correct for geographic sampling biases are necessary. Approaches based on “gap analysis” can contribute to the development of corrective measures by identifying geographical variation in our knowledge of parasites and quantifying how sampling varies in relation to host characteristics and habitat features. In this chapter, we review these methods and describe how they have been applied to study gaps in our knowledge of primate parasites.Human Evolutionary Biolog

Parasite-Mediated Evolution of the Functional Part of the MHC in Primates

The major histocompatibility complex (MHC) is a key model of genetic polymorphism, but the mechanisms underlying its extreme variability are debated. Most hypotheses for MHC diversity focus on pathogen-driven selection and predict that MHC polymorphism evolves under the pressure of a diverse parasite fauna. Several studies reported that certain alleles offer protection against certain parasites, yet it remains unclear whether variation in parasite pressure more generally covaries with allelic diversity and rates of molecular evolution of MHC across species. We tested this prediction in a comparative study of 41 primate species. We characterized polymorphism of the exon 2 of DRB region of the MHC class II. Our phylogenetic analyses controlled for the potential effects of neutral mutation rate, population size, geographic origin and body mass and revealed that nematode species richness associates positively with nonsynonymous nucleotide substitution rate at the functional part of the molecule. We failed to find evidence for allelic diversity being strongly related to parasite species richness. Continental distribution was a strong predictor of both allelic diversity and substitution rate, with higher values in Malagasy and Neotropical primates. These results indicate that parasite pressure can influence the different estimates of MHC polymorphism, whereas geography plays an independent role in the natural history of MHC.Human Evolutionary Biolog

Modeling Imitation and Emulation in Constrained Search Spaces

Social transmission of behavior can be realized through distinct mechanisms. Research on primate social learning typically distinguishes two forms of information that a learner can extract from a demonstrator: copying actions (defined as imitation) or copying only the consequential results (defined as emulation). We propose a decomposition of these learning mechanisms (plus pure individual learning) that incorporates the core idea that social learning can be represented as a search for an optimal behavior that is constrained by different kinds of information. We illustrate our approach with an individual-based model in which individuals solve tasks in abstract “spaces” that represent behavioral actions, results, and benefits of those results. Depending on the learning mechanisms at their disposal, individuals have differential access to the information conveyed in these spaces. We show how different classes of tasks may provide distinct advantages to individuals with different learning mechanisms and discuss how our approach contributes to current empirical and theoretical research on social learning and culture.Human Evolutionary Biolog

Sexual Dimorphism in Primate Aerobic Capacity: A Phylogenetic Test

Male intrasexual competition should favour increased male physical prowess. This should in turn result in greater aerobic capacity in males than in females (i.e. sexual dimorphism) and a correlation between sexual dimorphism in aerobic capacity and the strength of sexual selection among species. However, physiological scaling laws predict that aerobic capacity should be lower per unit body mass in larger than in smaller animals, potentially reducing or reversing the sex difference and its association with measures of sexual selection. We used measures of haematocrit and red blood cell (RBC) counts from 45 species of primates to test four predictions related to sexual selection and body mass: (i) on average, males should have higher aerobic capacity than females, (ii) aerobic capacity should be higher in adult than juvenile males, (iii) aerobic capacity should increase with increasing sexual selection, but also that (iv) measures of aerobic capacity should co-vary negatively with body mass. For the first two predictions, we used a phylogenetic paired t-test developed for this study. We found support for predictions (i) and (ii). For prediction (iii), however, we found a negative correlation between the degree of sexual selection and aerobic capacity, which was opposite to our prediction. Prediction (iv) was generally supported. We also investigated whether substrate use, basal metabolic rate and agility influenced physiological measures of oxygen transport, but we found only weak evidence for a correlation between RBC count and agility.Human Evolutionary Biolog