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Giraldeau, L. - A. (1997). The ecology of information use. In J. R. Krebs, & N. B. Davies (Eds.), Behavioural ecology : an evolutionary approach. Cambridge, Mass.: Blackwell Science.
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Pérez-Barbería, F. J., Shultz, S., & Dunbar, R. I. (2007). Evidence for coevolution of sociality and relative brain size in three orders of mammals. Evolution, 61.
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Kruska, D. (1988). Mammalian domestication and its effect on brain structure and behavior. In H. J. Jerison, & I. Jerison (Eds.), Intelligence and Evolutionary Biology. New York: Springer-Verlag.
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Clutton-Brock, J. (1995). Origins of the dog: domestication and early history. In J. A. Serpell (Ed.), The Domestic Dog: Its Evolution, Behaviour and Interactions with People. Cambridge: Cambridge University Press.
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Van Horik, J., Clayton, N., & Emery, N. (2012). Convergent evolution of cognition in Corvids, Apes and other animals. In J. Vonk, & T. Shackelford (Eds.), Oxford Handbook of Comparative Evolutionary Psychology. New York: Oxford University Press.
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Zeder, M. A. (2011). Pathways to animal domestication. In A. Damania, & P. Gepts (Eds.), Harlan II: Biodiversity in Agriculture: Domestication, Evolution, and Sustainability. Davis: University of California.
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Amodio, P., Boeckle, M., Schnell, A. K., Ostojic, L., Fiorito, G., & Clayton, N. S. (2018). Grow Smart and Die Young: Why Did Cephalopods Evolve Intelligence? Trends. Ecol. Evol., .
Abstract: Intelligence in large-brained vertebrates might have evolved through independent, yet similar processes based on comparable socioecological pressures and slow life histories. This convergent evolutionary route, however, cannot explain why cephalopods developed large brains and flexible behavioural repertoires: cephalopods have fast life histories and live in simple social environments. Here, we suggest that the loss of the external shell in cephalopods (i) caused a dramatic increase in predatory pressure, which in turn prevented the emergence of slow life histories, and (ii) allowed the exploitation of novel challenging niches, thus favouring the emergence of intelligence. By highlighting convergent and divergent aspects between cephalopods and large-brained vertebrates we illustrate how the evolution of intelligence might not be constrained to a single evolutionary route.
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Hofmeester, T. R., Cromsigt, J. P. G. M., Odden, J., Andrén, H., Kindberg, J., & Linnell, J. D. C. (2019). Framing pictures: A conceptual framework to identify and correct for biases in detection probability of camera traps enabling multi-species comparison. Ecol Evol, .
Abstract: Abstract Obtaining reliable species observations is of great importance in animal ecology and wildlife conservation. An increasing number of studies use camera traps (CTs) to study wildlife communities, and an increasing effort is made to make better use and reuse of the large amounts of data that are produced. It is in these circumstances that it becomes paramount to correct for the species- and study-specific variation in imperfect detection within CTs. We reviewed the literature and used our own experience to compile a list of factors that affect CT detection of animals. We did this within a conceptual framework of six distinct scales separating out the influences of (a) animal characteristics, (b) CT specifications, (c) CT set-up protocols, and (d) environmental variables. We identified 40 factors that can potentially influence the detection of animals by CTs at these six scales. Many of these factors were related to only a few overarching parameters. Most of the animal characteristics scale with body mass and diet type, and most environmental characteristics differ with season or latitude such that remote sensing products like NDVI could be used as a proxy index to capture this variation. Factors that influence detection at the microsite and camera scales are probably the most important in determining CT detection of animals. The type of study and specific research question will determine which factors should be corrected. Corrections can be done by directly adjusting the CT metric of interest or by using covariates in a statistical framework. Our conceptual framework can be used to design better CT studies and help when analyzing CT data. Furthermore, it provides an overview of which factors should be reported in CT studies to make them repeatable, comparable, and their data reusable. This should greatly improve the possibilities for global scale analyses of (reused) CT data.
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Dellert, B., & Ganslosser, U. (1997). Experimental alterations of food distribution in two species of captive equids (Equus burchelli and E. hemionus kulan). Ethol Ecol Evol, 9(1), 1–17.
Abstract: n one group each of Plains zebra (six mares, one foal, one subadult) and Asiatic wild asses (seven mares, two foals) at Nuremberg Zoo, food distribution was experimentally changed from clumped (all food in one standard hay rack) to dispersed (one heap per animal). Both groups were characterized by different social structures, which basically remained during the experiment. Plains zebras had an individually structured system of social relationships in a dominance order, wild asses a more egalitarian system without clear-cut rank differences and low frequencies of agonistic interactions. Access to food accordingly was individually (but consistently) different for zebra mares, almost equal for wild ass mares. During the dispersed feeding situation frequencies of agonistic interactions in both species decreased (however non-significantly), individual distances increased but mares also frequently ''visited'' each others' heaps. Feeding time increased for all wild ass mares. Some individuals (in both groups) behaved ''against the trend'' in agonistic behaviour. The results are discussed with regard to food distribution for ungulates in general, and equid social systems.
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Beck, B. B. (1982). Chimpocentrism: Bias in cognitive ethology. Journal of Human Evolution, 11(1), 3–17.
Abstract: Herring gulls drop hard-shelled mollusks and hermit crab-inhabited molluskan prey in order to break the shells and gain access to the edible interior. A field study of predatory shell dropping on Cape Cod, Massachusetts, U.S.A. showed that the gulls usually drop the same shell repeatedly, orient directly to dropping sites that are invisible from the point at which the mollusks are captured, drop preferentially on hard surfaces, adjust dropping heights to suit the area and elasticity of the substrate, orient directly into the wind while dropping, sever the large defensive cheliped of hermit crabs before consumption, and rinse prey that is difficult to swallow. Proficiency in prey dropping is acquired through dropping objects in play, trial-and-error learning, and perhaps, observation learning.
Observable attributes of predatory shell-dropping support inferences that the gulls are capable of extended concentration, purposefulness, mental representation of spatially and temporally displaced environmental features, cognitive mapping, cognitive modeling, selectivity, and strategy formation. Identical cognitive processes have been inferred to underlie the most sophisticated forms of chimpanzee tool-use.
Advanced cognitive capacities are not restricted to chimpanzees and other pongids, and are not associated uniquely with tool use. The chimpocentric bias should be abandoned, and reconstructions of the evolution of intelligence should be modified accordingly.
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