Technical note: Prediction of sex based on five skull traits using decision analysis (CHAID)

Osteologists commonly assess the sex of skeletal remains found in forensic and archaeological contexts based on ordinal scores of subjectively assessed sexually dimorphic traits. Using known‐sex samples, logistic regression (LR) discriminant functions have been recently developed, which allow sex probabilities to be determined. A limitation of LR is that it emphasizes main effects and not interactions. Chi‐square automatic interaction detection (CHAID) is an alternative classification strategy that emphasizes the information in variable interactions and uses decision trees to maximize the probability of correct sex determinations. We used CHAID to analyze the predictive value of the 31 possible combinations of five sexually dimorphic skull traits that Walker used previously to develop logistic regression sex determination equations. The samples consisted of 304 individuals of known sex of English, African American, and European American origin. Based on practical considerations, selection criteria for the best sex predictive trait combinations (SPTCs) were set at accuracies for both sexes of 75% or greater and sex biases lower than 5%. Although several of the trees meeting these criteria were produced for the English and European American samples, none met them for the African American sample. In the series of out‐of‐sample tests we performed, the trees from the English and combined sample of all groups predicted best. Am J Phys Anthropol, 2009. © 2009 Wiley‐Liss, Inc.     

Kinship analysis of brook trout Salvelinus fontinalis during their breeding migration

Microsatellite markers were used to test whether groups of pre‐spawning adult brook trout Salvelinus fontinalis from the same population and captured at the same location during their breeding migration comprised kin. Only weak evidence for kin associations was found at the onset of breeding: the proportion of kin captured at the same location was low and similar to the proportion found across all locations and the average relatedness of S. fontinalis captured at the same location was low. A dilution of kin associations from the feeding to breeding phase is hypothesized to stem from mainly natural mortality that reduces family size by the adult stage. The results illustrate the dynamic nature of kin associations between consecutive life stages, even within the same fish population.     

Prediction Equations Do Not Eliminate Systematic Error in Self-Reported Body Mass Index

PLANKEY MICHAEL W, JUNE STEVENS, KATHERINE M FLEGAL, PHILIP F RUST. Prediction equations do not eliminate systematic error in self-reported body mass index. Epidemiological studies of the risks of obesity often use body mass index (BMI) calculated from self-reported height and weight. The purpose of this study was to examine the pattern of reporting error associated with self-reported values of BMI and to evaluate the extent to which linear regression models predict measured BMI from self-reported data and whether these models could compensate for this reporting error. We examined measured and self-reported weight and height on 5079 adults aged 30 years to 64 years from the second National Health and Nutrition Examination Survey. Measured and self-reported BMI (kg/m2) was calculated, and multiple linear regression techniques were used to predict measured BMI from self-reported BMI. The error in self-reported BMI (self-reported BMI minus measured BMI) was not constant but varied systematically with BMI. The correlation between measured BMI and the error in self-reported BMI was ?0.37 for men and ?0.38 for women. The pattern of reporting error was only weakly associated with self-reported BMI, with the correlation being 0.05 for men and ?0.001 for women. Error in predicted BMI (predicted BMI minus measured BMI) also varied systematically with measured BMI, but less consistently with self-reported BMI. More complex models only slightly improved the ability to predict measured BMI compared with self-reported BMI alone. None of the equations were able to eliminate the systematic reporting error in determining measured BMI values from self-reported data. The characteristic pattern of error associated with self-reported BMI is difficult or impossible to correct by the use of linear regression models.     

A Salience Theory of Learning and Behavior: With Perspectives on Neurobiology and Cognition

Traditional behaviorists have described behaviors fundamentally as responses to stimuli or, perhaps more liberally, as behaviors under the control of discriminative stimuli or contexts. They have held responses or behaviors to be established, strengthened, sustained, and inhibited or extinguished by contingent events: notably reinforcers, punishers, or the absence of either. In addition, they believed reinforcement acts on the response, the behavior, not on the organism. Here, and in support of Hebb’s view, we advance a contrarian view. A key principle of our framework is that species’ brains are uniquely designed to perceive and to relate stimulus events that are contiguous, salient, and relevant to adaptation. In accordance with what we here view as the constructive biases of species’ brains, stimuli are differentially organized into amalgams that reflect an exchange of salience and response-eliciting properties of component units, which are then integrated to form a basis of knowledge about the organism and its ecological niche. One can then base adaptation on overarching principles and rules, not just on simple associations. Species may create emergent behaviors with no history of specific training, and even new capacities, to service adaptation to both familiar and novel challenges.     

Assessing health risk using regional mappings based on local perceptions: A comparative study of three different hazards

Usually risk assessment falls within the competence of “hard sciences” through environmental and epidemiological measurements, evaluations, and modeling. Even if these approaches bring accurate assessment and evaluation of environmental processes, the perception of local inhabitants is often excluded or at least relegated to second place. Evaluation of human vulnerabilities and capacities to face such hazards requires us to understand the perceptions of the population exposed. Three case studies (Lao, Tunisia, and Ecuador) are presented where we applied a perception-based regional mapping, a mapping tool based on local perceptions, for assessing the connection between land uses and health issues. A selection of the results collected on these three study areas show that the perception of local inhabitants provides a good spatial representation of the different contaminations observed locally, with a good consistency with external data. It also indicates for a certain number of cases that the contamination extends far beyond the simulated radius and impacts peripheral areas. Beyond the analysis of such a method (methodological bias, spatial representation bias, etc.), the objective is to combine our results with epidemiological measurement.     

Visual census methods underestimate density and diversity of cryptic reef fishes

The diversity and density of small, benthic reef fishes were estimated using visual census and enclosed rotenone stations. Visual census underestimated the number of species present and the density of common species by up to 91%.     

Detecting outliers in species distribution data: Some caveats and clarifications on a virtual species study

Liu et al. (2018) used a virtual species approach to test the effects of outliers on species distribution models. In their simulations, they applied a threshold value over the simulated suitabilities to generate the species distributions, suggesting that using a probabilistic simulation approach would have been more complex and yield the same results. Here, we argue that using a probabilistic approach is not necessarily more complex and may significantly change results. Although the threshold approach may be justified under limited circumstances, the probabilistic approach has multiple advantages. First, it is in line with ecological theory, which largely assumes non‐threshold responses. Second, it is more general, as it includes the threshold as a limiting case. Third, it allows a better separation of the relevant intervening factors that influence model performance. Therefore, we argue that the probabilistic simulation approach should be used as a general standard in virtual species studies.