Abstract: The process of domestication involves adaptation, usually to a captive environment. Domestication is attained by some combination of genetic changes occurring over generations and developmental mechanisms (e.g., physical maturation, learning) triggered by recurring environmental events or management practices in captivity that influence specific biological traits. The transition from free-living to captive status is often accompanied by changes in availability and/or accessibility of shelter, space, food and water, and by changes in predation and the social environment. These changes set the stage for the development of the domestic phenotype. Behavioral development in animals undergoing domestication is characterized by changes in the quantitative rather than qualitative nature of responses. The hypothesized loss of certain behavior patterns under domestication can usually be explained by the heightening of response thresholds. Increases in response frequency accompanying domestication can often be explained by atypical rates of exposure to certain forms of perceptual and locomotor stimulation. Genetic changes influencing the development of the domestic phenotype result from inbreeding, genetic drift, artificial selection, natural selection in captivity, and relaxed selection. Experiential contributions to the domestic phenotype include the presence or absence of key stimuli, changes in intraspecific aggressive interactions and interactions with humans. Man's role as a buffer between the animal and its environment is also believed to have an important effect on the development of the domestic phenotype. The domestication process has frequently reduced the sensitivity of animals to changes in their environment, perhaps the single-most important change accompanying domestication. It has also resulted in modified rates of behavioral and physical development. Interest in breeding animals in captivity for release in nature has flourished in recent decades. The capacity of domestic animals to survive and reproduce in nature may depend on the extent to which the gene pool of the population has been altered during the domestication process and flexibility in behavioral development. “Natural” gene pools should be protected when breeding wild animals in captivity for the purpose of reestablishing free-living natural populations. In some cases, captive-reared animals must be conditioned to live in nature prior to their release.

Abstract: Two experiments investigated the spontaneous construction of precursory logicomathematical operations by human-enculturated and language-reared chimpanzees (Pan troglodytes, Pan paniscus) when they were interacting freely with objects. In experiment 1, three chimpanzees ranging in age from 6 to 18 years were presented with sets of six objects. Chimpanzees constructed equivalence, order and reversibility relations within single sets of objects as well as between two or three contemporaneous sets of objects. The chimpanzees' logicomathematical operations were more advanced, including infrequent and minimal operations on three sets, than those of some previously investigated younger nonenculturated common chimpanzees. In experiment 2, six chimpanzees ranging in age from 6 to 21 years were presented with sets of 12 objects. Chimpanzees constructed more advanced operations on single sets, but not on contemporaneous sets. The results suggest partial convergence and partial divergence between development of logicomathematical cognition in chimpanzees and humans.

Abstract: The research described here builds on our previous work by generalizing the univariate models described there to models for multivariate relations. This family, labelled p*, generalizes the Markov random graphs of Frank and Strauss, which were further developed by them and others, building on Besag's ideas on estimation. These models were first used to model random variables embedded in lattices by Ising, and have been quite common in the study of spatial data. Here, they are applied to the statistical analysis of multigraphs, in general, and the analysis of multivariate social networks, in particular. In this paper, we show how to formulate models for multivariate social networks by considering a range of theoretical claims about social structure. We illustrate the models by developing structural models for several multivariate networks.