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Boissy, A. (1995). Fear and Fearfulness in Animals. The Quarterly Review of Biology, 70(2), 165–191.
Abstract: Persistence of individual differences in animal behavior in reactions to various environmental challenges could reflect basic divergences in temperament, which might be used to predict details of adaptive response. Although studies have been carried out on fear and anxiety in various species, including laboratory, domestic and wild animals, no consistent definition of fearfulness as a basic trait of temperament has emerged. After a classification of the events that may produce a state of fear, this article describes the great variability in behavior and in physiological patterns generally associated with emotional reactivity. The difficulties of proposing fearfulness-the general capacity to react to a variety of potentially threatening situations-as a valid basic internal variable are then discussed. Although there are many studies showing covariation among the psychobiological responses to different environmental challenges, other studies find no such correlations and raise doubts about the interpretation of fearfulness as a basic personality trait. After a critical assessment of methodologies used in fear and anxiety studies, it is suggested that discrepancies among results are mainly due to the modulation of emotional responses in animals, which depend on numerous genetic and epigenetic factors. It is difficult to compare results obtained by different methods from animals reared under various conditions and with different genetic origins. The concept of fearfulness as an inner trait is best supported by two kinds of investigations. First, an experimental approach combining ethology and experimental psychology produces undeniable indicators of emotional reactivity. Second, genetic lines selected for psychobiological traits prove useful in establishing between behavioral and neuroendocrine aspects of emotional reactivity. It is suggested that fearfulness could be considered a basic feature of the temperament of each individual, one that predisposes it to respond similarly to a variety of potentially alarming challenges, but is nevertheless continually modulated during development by the interaction of genetic traits of reactivity with environmental factors, particularly in the juvenile period. Such interaction may explain much of the interindividual variability observed in adaptive responses.
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Heyes, C. M. (1994). Social learning in animals: categories and mechanisms. Biol. Rev., 69(2), 207–231.
Abstract: There has been relatively little research on the psychological mechanisms of social learning. This may be due, in part, to the practice of distinguishing categories of social learning in relation to ill-defined mechanisms (Davis, 1973; Galef, 1988). This practice both makes it difficult to identify empirically examples of different types of social learning, and gives the false impression that the mechanisms responsible for social learning are clearly understood. It has been proposed that social learning phenomena be subsumed within the categorization scheme currently used by investigators of asocial learning. This scheme distinguishes categories of learning according to observable conditions, namely, the type of experience that gives rise to a change in an animal (single stimulus vs. stimulus-stimulus relationship vs. response-reinforcer relationship), and the type of behaviour in which this change is detected (response evocation vs. learnability) (Rescorla, 1988). Specifically, three alignments have been proposed: (i) stimulus enhancement with single stimulus learning, (ii) observational conditioning with stimulus-stimulus learning, or Pavlovian conditioning, and (iii) observational learning with response-reinforcer learning, or instrumental conditioning. If, as the proposed alignments suggest, the conditions of social and asocial learning are the same, there is some reason to believe that the mechanisms underlying the two sets of phenomena are also the same. This is so if one makes the relatively uncontroversial assumption that phenomena which occur under similar conditions tend to be controlled by similar mechanisms. However, the proposed alignments are intended to be a set of hypotheses, rather than conclusions, about the mechanisms of social learning; as a basis for further research in which animal learning theory is applied to social learning. A concerted attempt to apply animal learning theory to social learning, to find out whether the same mechanisms are responsible for social and asocial learning, could lead both to refinements of the general theory, and to a better understanding of the mechanisms of social learning. There are precedents for these positive developments in research applying animal learning theory to food aversion learning (e.g. Domjan, 1983; Rozin & Schull, 1988) and imprinting (e.g. Bolhuis, de Vox & Kruit, 1990; Hollis, ten Cate & Bateson, 1991). Like social learning, these phenomena almost certainly play distinctive roles in the antogeny of adaptive behaviour, and they are customarily regarded as 'special kinds' of learning (Shettleworth, 1993).(ABSTRACT TRUNCATED AT 400 WORDS)
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Shi, J., Dunbar, R. I. M., Buckland, D., & Miller, D. (2005). Dynamics of grouping patterns and social segregation in feral goats (Capra hircus) on the Isle of Rum, NW Scotland. Mammalia, 69.
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Gazzola, A., Avanzinelli, E., Mauri, L., Scandura, M., & Apollonio, M. (2002). Temporal changes of howling in south European wolf packs. Ital J Zool, 69.
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Harrington, F. H., & Mech, L. D. (1979). Wolf howling and its role in territory maintenance. Behaviour, 68.
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Zlatanova, D., Ahmed, A., Valasseva, A., & Genov, P. (2014). Adaptive Diet Strategy of the Wolf (Canis lupus L.) in Europe: a Review. Acta zool. bulg., 66(4), 439–452.
Abstract: The diet strategy of the wolf in Europe is reviewed on the basis of 74 basic and 14 additional literature
sources. The comparative analysis reveals clear dependence on the latitude (and, therefore, on the changing
environmental conditions) correlated with the wild ungulate abundance and diversity. Following a
geographic pattern, the wolf is specialised on different species of ungulates: moose and reindeer in Scandinavia,
red deer in Central and Eastern Europe and wild boar in Southern Europe. Where this large prey
is taken, the roe deer is hunted with almost the same frequency in every region. The wolf diet in Europe
shows two ecological adaptations formed by a complex of variables: 1. Wolves living in natural habitats
with abundance of wild ungulates feed mainly on wild prey. 2. In highly anthropogenic habitats, with low
abundance of wild prey, wolves feed on livestock (where husbandry of domestic animals is available) and
take also a lot of plant food, smaller prey (hares and rodents) and garbage food. The frequency of occurrence
of wild ungulates in the diet of wolves in North Europe varies from 54.0% in Belarus to 132.7% in
Poland, while that of livestock is in the range from 0.4% in Norway to 74.9% in Belarus. In South Europe,
the frequency of occurrence of wild prey varies from 0% in Italy and Spain to 136.0% in Italy, while of domestic
ungulates ranges between 0% and 100% in Spain. The low density or lack of wild prey triggers the
switch of the wolf diet to livestock, plant food (32.2-85% in Italy) or even garbage (up to 41.5% in Italy).
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Harris, F. (1978). On the Use of Windows for Harmonic Analysis with the Discrete Fourier Transform. Proc IEEE, 66.
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Kruska, D. C. T. (2005). On the evolutionary significance of encephalization in some eutherian mammals: effects of adaptive radiation, domestication, and feralization. Brain Behav Evol, 65.
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Lefebvre, L., Reader, S. M., & Sol, D. (2004). Brains, Innovations and Evolution in Birds and Primates. Brain. Behav. Evol., 63(4), 233–246.
Abstract: Abstract
Several comparative research programs have focusedon the cognitive, life history and ecological traits thataccount for variation in brain size. We review one ofthese programs, a program that uses the reported frequencyof behavioral innovation as an operational measureof cognition. In both birds and primates, innovationrate is positively correlated with the relative size of associationareas in the brain, the hyperstriatum ventrale andneostriatum in birds and the isocortex and striatum inprimates. Innovation rate is also positively correlatedwith the taxonomic distribution of tool use, as well asinterspecific differences in learning. Some features ofcognition have thus evolved in a remarkably similar wayin primates and at least six phyletically-independent avianlineages. In birds, innovation rate is associated withthe ability of species to deal with seasonal changes in theenvironment and to establish themselves in new regions,and it also appears to be related to the rate atwhich lineages diversify. Innovation rate provides a usefultool to quantify inter-taxon differences in cognitionand to test classic hypotheses regarding the evolution ofthe brain.
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Mori, E., Benatti, L., Lovari, S., & Ferretti, F. (2016). What does the wild boar mean to the wolf? European Journal of Wildlife Research, 63(1), 9.
Abstract: Generalist predators are expected to shape their diets according to the local availability of prey species. In turn, the extent of consumption of a prey would be influenced by the number of alternative prey species. We have tested this prediction by considering the wild boar and the grey wolf: two widespread species whose distribution ranges overlap largely in Southern Europe, e.g. in Italy. We have reviewed 16 studies from a total of 21 study areas, to assess whether the absolute frequency of occurrence of wild boar in the wolf diet was influenced by (i) occurrence of the other ungulate species in diet and (ii) the number of available ungulate species. Wild boar turned out to be the main prey of the wolf (49% occurrence, on average), followed by roe deer (24%) and livestock (18%). Occurrence of wild boar in the wolf diet decreased with increasing usage of roe deer, livestock, and to a lower extent, chamois and red deer. The number of prey species did not influence the occurrence of wild boar in the wolf diet. The wild boar is a gregarious, noisy and often locally abundant ungulate, thus easily detectable, to a predator. In turn, the extent of predation on this ungulate may not be influenced so much by the availability of other potential prey. Heavy artificial reductions of wild boar numbers, e.g. through numerical control, may concentrate predation by wolves on alternative prey (e.g. roe deer) and/or livestock, thus increasing conflicts with human activities.
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