127 research outputs found

    Social network and dominance hierarchy analyses at Chimpanzee Sanctuary Northwest

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    Different aspects of sociality bear considerable weight on the individual- and group-level welfare of captive nonhuman primates. Social Network Analysis (SNA) is a useful tool for gaining a holistic understanding of the dynamic social relationships of captive primate groups. Gaining a greater understanding of captive chimpanzees through investigations of centrality, preferred and avoided relationships, dominance hierarchy, and social network diagrams can be useful in advising current management practices in sanctuaries and other captive settings. In this study, we investigated the dyadic social relationships, group-level social networks, and dominance hierarchy of seven chimpanzees (Pan troglodytes) at Chimpanzee Sanctuary Northwest. We used focal-animal and instantaneous scan sampling to collect 106.75 total hours of associative, affiliative, and agonistic data from June to September 2016. We analyzed our data using SOCPROG to derive dominance hierarchies and network statistics, and we diagrammed the group\u27s social networks in NetDraw. Three individuals were most central in the grooming network, while two others had little connection. Through agonistic networks, we found that group members reciprocally exhibited agonism, and the group\u27s dominance hierarchy was statistically non-linear. One chimpanzee emerged as the most dominant through agonism but was least connected to other group members across affiliative networks. Our results indicate that the conventional methods used to calculate individuals\u27 dominance rank may be inadequate to wholly depict a group\u27s social relationships in captive sanctuary populations. Our results have an applied component that can aid sanctuary staff in a variety of ways to best ensure the improvement of group welfare

    Technological Change in Economic Models of Environmental Policy: A Survey

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    This paper provides an overview of the treatment of technological change in economic models of environmental policy. Numerous economic modeling studies have confirmed the sensitivity of mid- and long-run climate change mitigation cost and benefit projections to assumptions about technology costs. In general, technical progress is considered to be a noneconomic, exogenous variable in global climate change modeling. However, there is overwhelming evidence that technological change is not an exogenous variable but to an important degree endogenous, induced by needs and pressures. Hence, some environmenteconomy models treat technological change as endogenous, responding to socio-economic variables. Three main elements in models of technological innovation are: (i) corporate investment in research and development, (ii) spillovers from R&D, and (iii) technology learning, especially learning-by-doing. The incorporation of induced technological change in different types of environmental-economic models tends to reduce the costs of environmental policy, accelerates abatement and may lead to positive spillover and negative leakage

    Climate policy and ancillary benefits : a survey and integration into the modelling of international negotiations on climate change

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    Currently informal and formal international negotiations on climate change take place in an intensive way since the Kyoto Protocol expires already in 2012. A post-Kyoto regulation to combat global warming is not yet stipulated. Due to rapidly increasing greenhouse gas emission levels, industrialized countries urge major polluters from the developing world like China and India to participate in a future agreement. Whether these developing countries will do so, depends on the prevailing incentives to participate in international climate protection efforts. This paper identifies ancillary benefits of climate policy to provide important incentives to attend a new international protocol and to positively affect the likelihood of accomplishing a post-Kyoto agreement which includes commitments of developing countries

    Combinatoriality in the vocal systems of nonhuman animals

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    A key challenge in the field of human language evolution is the identification of the selective conditions that gave rise to language's generative nature. Comparative data on nonhuman animals provides a powerful tool to investigate similarities and differences among nonhuman and human communication systems and to reveal convergent evolutionary mechanisms. In this article, we provide an overview of the current evidence for combinatorial structures found in the vocal system of diverse species. We show that considerable structural diversity exits across and within species in the forms of combinatorial structures used. Based on this we suggest that a fine‐grained classification and differentiation of combinatoriality is a useful approach permitting systematic comparisons across animals. Specifically, this will help to identify factors that might promote the emergence of combinatoriality and, crucially, whether differences in combinatorial mechanisms might be driven by variations in social and ecological conditions or cognitive capacities
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