How Much Do Metamemory Beliefs Contribute to the Font-Size Effect in Judgments of Learning?

Evidence shows that the font size of study items significantly influences judgments of learning (JOLs) and that people’s JOLs are generally higher for larger words than for smaller words. Previous studies have suggested that font size influences JOLs in a belief-based way. However, few studies have directly examined how much people’s beliefs contribute to the font-size effect in JOLs. This study investigated the degree to which font size influenced JOLs in a belief-based way. In Experiment 1, one group of participants (learners) studied words with different font sizes and made JOLs, whereas another group of participants (observers) viewed the learners'' study phase and made JOLs for the learners. In Experiment 2, participants made both JOLs and belief-based recall predictions for large and small words. Our results suggest that metamemory beliefs play an important role in the font-size effect in JOLs.     

An Experimental Test of the Accumulated Copying Error Model of Cultural Mutation for Acheulean Handaxe Size

Archaeologists interested in explaining changes in artifact morphology over long time periods have found it useful to create models in which the only source of change is random and unintentional copying error, or ‘cultural mutation’. These models can be used as null hypotheses against which to detect non-random processes such as cultural selection or biased transmission. One proposed cultural mutation model is the accumulated copying error model, where individuals attempt to copy the size of another individual''s artifact exactly but make small random errors due to physiological limits on the accuracy of their perception. Here, we first derive the model within an explicit mathematical framework, generating the predictions that multiple independently-evolving artifact chains should diverge over time such that their between-chain variance increases while the mean artifact size remains constant. We then present the first experimental test of this model in which 200 participants, split into 20 transmission chains, were asked to faithfully copy the size of the previous participant''s handaxe image on an iPad. The experimental findings supported the model''s prediction that between-chain variance should increase over time and did so in a manner quantitatively in line with the model. However, when the initial size of the image that the participants resized was larger than the size of the image they were copying, subjects tended to increase the size of the image, resulting in the mean size increasing rather than staying constant. This suggests that items of material culture formed by reductive vs. additive processes may mutate differently when individuals attempt to replicate faithfully the size of previously-produced artifacts. Finally, we show that a dataset of 2601 Acheulean handaxes shows less variation than predicted given our empirically measured copying error variance, suggesting that other processes counteracted the variation in handaxe size generated by perceptual cultural mutation.     

An experimental demonstration of the effect of group size on cultural accumulation

Cumulative culture is thought to have played a major role in hominin evolution, and so an understanding of the factors that affect cultural accumulation is important for understanding human evolution. Population size may be one such factor, with larger populations thought to be able to support more complex cultural traits. This hypothesis has been suggested by mathematical models and empirical studies of small-scale societies. However, to date there have been few experimental demonstrations of an effect of population size on cultural accumulation. Here we provide such a demonstration using a novel task, solving jigsaw puzzles. 80 participants divided into ten transmission chains solved puzzles in one of two conditions: one in which participants had access to one semi-completed puzzle from the previous generation, and the other in which participants simultaneously saw three semi-completed puzzles from the previous generation. As predicted, the mean number of pieces solved increased over time in the three-puzzle-per-generation condition, but not in the one-puzzle-per-generation condition. Thus, our experiment provides support for a hypothesized relationship between population size and cultural accumulation. In particular, our results suggest that the ability to simultaneously learn from multiple cultural models, and combine the knowledge of those multiple models, is most likely to allow larger groups to support more complex culture.     

Success-biased social learning: Cultural and evolutionary dynamics

Success bias is a social learning strategy whereby learners tend to acquire the cultural variants of successful individuals. I develop a general model of success-biased social learning for discrete cultural traits with stochastic payoffs, and investigate its dynamics when only two variants are present. I find that success bias inherently favors rare variants, and consequently performs worse than unbiased imitation (i.e. random copying) when success payoffs are at least mildly stochastic and the optimal variant is common. Because of this weakness, success bias fails to replace unbiased imitation in an evolutionary model when selection is fairly weak or when the environment is relatively stable, and sometimes fails to invade at all. I briefly discuss the optimal strength of success bias, the complicated nature of defining success in social learning contexts, and the value of variant frequency as an important source of information to social learners. I conclude with predictions regarding the prevalence of success bias in different behavioral domains.     

Five years of Homo floresiensis

Researchers have hypothesized that the degree to which an individual's actual behavior approximates the culturally valued lifestyle encoded in the dominant cultural model has consequences for physical and mental health. We contribute to this line of research by analyzing data from a longitudinal study composed of five annual surveys (2002–2006 inclusive) from 791 adults in one society of foragers–farmers in the Bolivian Amazon, the Tsimane'. We estimate the association between a standard measure of individual achievement of the cultural model, cultural consonance, and three indicators of body morphology. Drawing on research suggesting that in societies in the early stages of economic development an increase in socioeconomic status is associated with an increase in mean body mass, we expect to find a positive association between cultural consonance and three anthropometric measures. We found the expected positive association between cultural consonance and anthropometric measures—especially for men—only when using ordinary least square (OLS) regression models, but not when using fixed‐effects regression models. The real magnitude of the association was low. The comparison of estimates from OLS and fixed‐effect regression models suggests that previous findings on the effects of cultural consonance on body morphology using cross‐sectional data should be read with caution because the association might be largely explained by fixed characteristics of individuals not accounted in OLS models. Am J Phys Anthropol 143:167–174, 2010. © 2010 Wiley‐Liss, Inc.     

The evolution of reaction norms: simple models for age and size at maturity

This paper presents a simple model for the evolution of reaction norms for age and size at maturity that predicts reaction norms with a variety of shapes. Using realistic parameter values the model predicts reaction norms close to those observed in Drosophila. The major assumptions of the model are: 1) that net reproductive rate is maximized, 2) that growth is determinate, and 3) that mortality rates are independent of age and size at maturity. If, additionally, juvenile mortality is uncorrelated with a growth coefficient, k, the model predicts that selection favors maturation later at a smaller size when k is reduced by environmental factors and that decreased juvenile mortality leads to delayed maturity. These two predictions conform with those found by previous models using other measures of fitness. Correlations between k and juvenile mortality can change the shape of the predicted reaction norm. Depending on the precise form of the correlation, the model can predict done- or bowl-shaped reaction norms and can predict delayed or earlier maturity as k decreases. These shapes are qualitatively different from those predicted by previous models that used different fitness measures. Systematic estimates of the parameter values for this and for related models are required to determine the appropriate fitness measure for models of reaction norms.     

Coexistence of individual and social learners during range expansion

Individual learning and social learning are two primary abilities supporting cultural evolution. Conditions for their evolution have mostly been studied by investigating gene frequency dynamics, which essentially implies constant population size. Predictions from such “static” models may only be of partial relevance to the evolution of advanced individual learning in modern humans, because modern humans have experienced rapid population growth and range expansion during “out-of-Africa.” Here we model the spatial population dynamics of individual and social learners by a reaction–diffusion system. One feature of our model is the inclusion of the possibility that social learners may fail to find an exemplar to copy in regions where the population density is low. Due to this attenuation effect, the invasion speed of social learners is diminished, and various kinds of invasion dynamics are observed. Our primary findings are: (1) individual learners can persist indefinitely when invading environmentally homogeneous infinite space; (2) the occurrence of individual learners at the front may inhibit the spread of social learners. These results suggest that “out-of-Africa” may have driven the evolution of advanced individual learning ability in modern humans.     

Game theory and plant ecology

The fixed and plastic traits possessed by a plant, which may be collectively thought of as its strategy, are commonly modelled as density‐independent adaptations to its environment. However, plant strategies may also represent density‐ or frequency‐dependent adaptations to the strategies used by neighbours. Game theory provides the tools to characterise such density‐ and frequency‐dependent interactions. Here, we review the contributions of game theory to plant ecology. After briefly reviewing game theory from the perspective of plant ecology, we divide our review into three sections. First, game theoretical models of allocation to shoots and roots often predict investment in those organs beyond what would be optimal in the absence of competition. Second, game theoretical models of enemy defence suggest that an individual's investment in defence is not only a means of reducing its own tissue damage but also a means of deflecting enemies onto competitors. Finally, game theoretical models of trade with mutualistic partners suggest that the optimal trade may reflect competition for access to mutualistic partners among plants. In short, our review provides an accessible entrance to game theory that will help plant ecologists enrich their research with its worldview and existing predictions.     

Mutualistic networks: moving closer to a predictive theory

Plant–animal mutualistic networks sustain terrestrial biodiversity and human food security. Global environmental changes threaten these networks, underscoring the urgency for developing a predictive theory on how networks respond to perturbations. Here, I synthesise theoretical advances towards predicting network structure, dynamics, interaction strengths and responses to perturbations. I find that mathematical models incorporating biological mechanisms of mutualistic interactions provide better predictions of network dynamics. Those mechanisms include trait matching, adaptive foraging, and the dynamic consumption and production of both resources and services provided by mutualisms. Models incorporating species traits better predict the potential structure of networks (fundamental niche), while theory based on the dynamics of species abundances, rewards, foraging preferences and reproductive services can predict the extremely dynamic realised structures of networks, and may successfully predict network responses to perturbations. From a theoretician's standpoint, model development must more realistically represent empirical data on interaction strengths, population dynamics and how these vary with perturbations from global change. From an empiricist's standpoint, theory needs to make specific predictions that can be tested by observation or experiments. Developing models using short‐term empirical data allows models to make longer term predictions of community dynamics. As more longer term data become available, rigorous tests of model predictions will improve.     

Models for clutch size and sex ratio with sibling interaction

General models are constructed to predict sex ratio and clutch size simultaneously for those organisms in which members of a clutch interact to affect each other's fitness. The same set of underlying factors can be shown to predict both optimal sex ratios and clutch sizes. The presence or absence of these factors enables different life histories or models to be classified. Previous sibling interaction sex ratio and clutch size models are special cases of the general model. The circumstances in which it is wrong to consider clutch size and sex ratio in isolation are identified. A distinction is made between those models that maximise sex ratio or clutch size with respect to a single clutch and those that consider either several clutches or lifetime fitness.     

Occam's Razor in sensorimotor learning

A large number of recent studies suggest that the sensorimotor system uses probabilistic models to predict its environment and makes inferences about unobserved variables in line with Bayesian statistics. One of the important features of Bayesian statistics is Occam''s Razor—an inbuilt preference for simpler models when comparing competing models that explain some observed data equally well. Here, we test directly for Occam''s Razor in sensorimotor control. We designed a sensorimotor task in which participants had to draw lines through clouds of noisy samples of an unobserved curve generated by one of two possible probabilistic models—a simple model with a large length scale, leading to smooth curves, and a complex model with a short length scale, leading to more wiggly curves. In training trials, participants were informed about the model that generated the stimulus so that they could learn the statistics of each model. In probe trials, participants were then exposed to ambiguous stimuli. In probe trials where the ambiguous stimulus could be fitted equally well by both models, we found that participants showed a clear preference for the simpler model. Moreover, we found that participants’ choice behaviour was quantitatively consistent with Bayesian Occam''s Razor. We also show that participants’ drawn trajectories were similar to samples from the Bayesian predictive distribution over trajectories and significantly different from two non-probabilistic heuristics. In two control experiments, we show that the preference of the simpler model cannot be simply explained by a difference in physical effort or by a preference for curve smoothness. Our results suggest that Occam''s Razor is a general behavioural principle already present during sensorimotor processing.     

In the Elderly,Failure to Update Internal Models Leads to Over-Optimistic Predictions about Upcoming Actions

Before an action is performed, the brain simulates the body''s dynamic behavior in relation to the environment, estimates the possible outcomes and assesses the feasibility of potential actions. Here, we tested a hypothesis whereby age-related changes in sensorimotor abilities result in failure to update internal models of action in the elderly. Young and older adults were required to judge in advance whether or not they could stand on an inclined plane (Experiment 1). Relative to young adults, elderly adults overestimated their postural capabilities: although the two groups made similar feasibility judgments, elderly participants showed significantly worse postural performance levels. This tendency to overestimate their own ability persisted when elderly adults had to not only estimate the feasibility of an action but also endanger themselves by walking towards an obstacle that was too high for them to clear (Experiment 2). An age-related failure to update internal models may prompt the elderly to make over-optimistic predictions about upcoming actions. In turn, this may favor risky motor decision-making and promote falls.     

Socially induced brain development in a facultatively eusocial sweat bee Megalopta genalis (Halictidae)

Changes in the relative size of brain regions are often dependent on experience and environmental stimulation, which includes an animal''s social environment. Some studies suggest that social interactions are cognitively demanding, and have examined predictions that the evolution of sociality led to the evolution of larger brains. Previous studies have compared species with different social organizations or different groups within obligately social species. Here, we report the first intraspecific study to examine how social experience shapes brain volume using a species with facultatively eusocial or solitary behaviour, the sweat bee Megalopta genalis. Serial histological sections were used to reconstruct and measure the volume of brain areas of bees behaving as social reproductives, social workers, solitary reproductives or 1-day-old bees that are undifferentiated with respect to the social phenotype. Social reproductives showed increased development of the mushroom body (an area of the insect brain associated with sensory integration and learning) relative to social workers and solitary reproductives. The gross neuroanatomy of young bees is developmentally similar to the advanced eusocial species previously studied, despite vast differences in colony size and social organization. Our results suggest that the transition from solitary to social behaviour is associated with modified brain development, and that maintaining dominance, rather than sociality per se, leads to increased mushroom body development, even in the smallest social groups possible (i.e. groups with two bees). Such results suggest that capabilities to navigate the complexities of social life may be a factor shaping brain evolution in some social insects, as for some vertebrates.     

Sequence learning recodes cortical representations instead of strengthening initial ones

We contrast two computational models of sequence learning. The associative learner posits that learning proceeds by strengthening existing association weights. Alternatively, recoding posits that learning creates new and more efficient representations of the learned sequences. Importantly, both models propose that humans act as optimal learners but capture different statistics of the stimuli in their internal model. Furthermore, these models make dissociable predictions as to how learning changes the neural representation of sequences. We tested these predictions by using fMRI to extract neural activity patterns from the dorsal visual processing stream during a sequence recall task. We observed that only the recoding account can explain the similarity of neural activity patterns, suggesting that participants recode the learned sequences using chunks. We show that associative learning can theoretically store only very limited number of overlapping sequences, such as common in ecological working memory tasks, and hence an efficient learner should recode initial sequence representations.     

Review. Theoretical and empirical evidence for the impact of inductive biases on cultural evolution

The question of how much the outcomes of cultural evolution are shaped by the cognitive capacities of human learners has been explored in several disciplines, including psychology, anthropology and linguistics. We address this question through a detailed investigation of transmission chains, in which each person passes information to another along a chain. We review mathematical and empirical evidence that shows that under general conditions, and across experimental paradigms, the information passed along transmission chains will be affected by the inductive biases of the people involved-the constraints on learning and memory, which influence conclusions from limited data. The mathematical analysis considers the case where each person is a rational Bayesian agent. The empirical work consists of behavioural experiments in which human participants are shown to operate in the manner predicted by the Bayesian framework. Specifically, in situations in which each person's response is used to determine the data seen by the next person, people converge on concepts consistent with their inductive biases irrespective of the information seen by the first member of the chain. We then relate the Bayesian analysis of transmission chains to models of biological evolution, clarifying how chains of individuals correspond to population-level models and how selective forces can be incorporated into our models. Taken together, these results indicate how laboratory studies of transmission chains can provide information about the dynamics of cultural evolution and illustrate that inductive biases can have a significant impact on these dynamics.     

Relationships Among Informant Based Measures of Social Skills and Student Achievement: A Longitudinal Examination of Differential Effects by Sex

Children's social skills are an important class of learned behaviors that facilitate success in the classroom; the primary method used in the assessment of social skills involves having parents or teachers complete standardized checklists using judgments of frequency or intensity. Children's (N = 1,102) social skills were modeled as time-varying predictors of student achievements within a latent growth curve model that allowed for estimation of student level variation and the possibility of non-linear achievement growth across 4–5 years of age and grades one, three, and five. Separate models were examined to determine whether ratings provided by mothers' accounted for more achievement score variance than ratings provided by teachers', and multi-group time-varying conditional latent growth curve models were investigated for boys and girls separately by informant type. Results indicated that children's social skills accounted for levels of achievement score variance that were most pronounced at pre-school age, that teachers' ratings of children's social skills generally accounted for more achievement score variance than those obtained by mothers' regardless of the child's sex, and that the explanatory power of social skills for boys and girls was dependent upon the type of achievement considered.     

Higher frequency of social learning in China than in the West shows cultural variation in the dynamics of cultural evolution

Cultural evolutionary models have identified a range of conditions under which social learning (copying others) is predicted to be adaptive relative to asocial learning (learning on one''s own), particularly in humans where socially learned information can accumulate over successive generations. However, cultural evolution and behavioural economics experiments have consistently shown apparently maladaptive under-utilization of social information in Western populations. Here we provide experimental evidence of cultural variation in people''s use of social learning, potentially explaining this mismatch. People in mainland China showed significantly more social learning than British people in an artefact-design task designed to assess the adaptiveness of social information use. People in Hong Kong, and Chinese immigrants in the UK, resembled British people in their social information use, suggesting a recent shift in these groups from social to asocial learning due to exposure to Western culture. Finally, Chinese mainland participants responded less than other participants to increased environmental change within the task. Our results suggest that learning strategies in humans are culturally variable and not genetically fixed, necessitating the study of the ‘social learning of social learning strategies'' whereby the dynamics of cultural evolution are responsive to social processes, such as migration, education and globalization.     

Communicative roots of complex sociality and cognition

Mammals living in more complex social groups typically have large brains for their body size and many researchers have proposed that the primary driver of the increase in brain size through primate and hominin evolution was the selection pressures associated with sociality. Many mammals, and especially primates, use flexible signals that show a high degree of voluntary control and these signals may play an important role in forming and maintaining social relationships between group members. However, the specific role that cognitive skills play in this complex communication, and how in turn this relates to sociality, is still unclear. The hypothesis for the communicative roots of complex sociality and cognition posits that cognitive demands behind the communication needed to form and maintain bonded social relationships in complex social settings drives the link between brain size and sociality. We review the evidence in support of this hypothesis and why key features of cognitively complex communication such as intentionality and referentiality should be more effective in forming and maintaining bonded relationships as compared with less cognitively complex communication. Exploring the link between cognition, communication and sociality provides insights into how increasing flexibility in communication can facilitate the emergence of social systems characterised by bonded social relationships, such as those found in non‐human primates and humans. To move the field forward and carry out both within‐ and among‐species comparisons, we advocate the use of social network analysis, which provides a novel way to describe and compare social structure. Using this approach can lead to a new, systematic way of examining social and communicative complexity across species, something that is lacking in current comparative studies of social structure.     

Model-based uncertainty in species range prediction

Aim Many attempts to predict the potential range of species rely on environmental niche (or ‘bioclimate envelope’) modelling, yet the effects of using different niche‐based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions, identify key reasons why model output may differ and discuss the implications that model uncertainty has for policy‐guiding applications. Location The Western Cape of South Africa. Methods We applied nine of the most widely used modelling techniques to model potential distributions under current and predicted future climate for four species (including two subspecies) of Proteaceae. Each model was built using an identical set of five input variables and distribution data for 3996 sampled sites. We compare model predictions by testing agreement between observed and simulated distributions for the present day (using the area under the receiver operating characteristic curve (AUC) and kappa statistics) and by assessing consistency in predictions of range size changes under future climate (using cluster analysis). Results Our analyses show significant differences between predictions from different models, with predicted changes in range size by 2030 differing in both magnitude and direction (e.g. from 92% loss to 322% gain). We explain differences with reference to two characteristics of the modelling techniques: data input requirements (presence/absence vs. presence‐only approaches) and assumptions made by each algorithm when extrapolating beyond the range of data used to build the model. The effects of these factors should be carefully considered when using this modelling approach to predict species ranges. Main conclusions We highlight an important source of uncertainty in assessments of the impacts of climate change on biodiversity and emphasize that model predictions should be interpreted in policy‐guiding applications along with a full appreciation of uncertainty.     

Predicting predation through prey ontogeny using size-dependent functional response models

The functional response is a critical link between consumer and resource dynamics, describing how a consumer's feeding rate varies with prey density. Functional response models often assume homogenous prey size and size-independent feeding rates. However, variation in prey size due to ontogeny and competition is ubiquitous, and predation rates are often size dependent. Thus, functional responses that ignore prey size may not effectively predict predation rates through ontogeny or in heterogeneous populations. Here, we use short-term response-surface experiments and statistical modeling to develop and test prey size-dependent functional responses for water bugs and dragonfly larvae feeding on red-eyed treefrog tadpoles. We then extend these models through simulations to predict mortality through time for growing prey. Both conventional and size-dependent functional response models predicted average overall mortality in short-term mixed-cohort experiments, but only the size-dependent models accurately captured how mortality was spread across sizes. As a result, simulations that extrapolated these results through prey ontogeny showed that differences in size-specific mortality are compounded as prey grow, causing predictions from conventional and size-dependent functional response models to diverge dramatically through time. Our results highlight the importance of incorporating prey size when modeling consumer-prey dynamics in size-structured, growing prey populations.