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Hoelker, S. |
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Typologie der deutschen Pferdehaltung – Eine empirische Studie mittels Two-Step-Clusteranalyse |
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2016 |
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Berichte über Landwirtschaft Zeitschrift für Agrarpolitik und Landwirtschaft |
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94 |
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3 |
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BMEL |
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Bonn |
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Equine Behaviour @ team @ |
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6643 |
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Reader, S.M. |
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Innovation and social learning: individual variation and brain evolution |
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Journal Article |
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2003 |
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Animal Biology (formerly Netherlands Journal of Zoology) |
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Anim. Biol. Leiden. |
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53 |
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2 |
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147-158 |
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This paper reviews behavioural, neurological and cognitive correlates of innovation at the individual, population and species level, focusing on birds and primates. Innovation, new or modified learned behaviour not previously found in the population, is the first stage in many instances of cultural transmission and may play an important role in the lives of animals with generalist or opportunistic lifestyles. Within-species, innovation is associated with low neophobia, high neophilia, and with high social learning propensities. Indices of innovatory propensities can be calculated for taxonomic groups by counting the frequency of reports of innovation in published literature. These innovation rate data provide a useful comparative measure for studies of behavioural flexibility and cognition. Innovation rate is positively correlated with the relative size of association areas in the brain, namely the hyperstriatum ventrale and neostriatum in birds, and the neocortex and striatum in primates. Innovation rate is also positively correlated with the reported variety of tool use, as well as interspecific differences in learning. Current evidence thus suggests similar patterns of cognitive evolution in primates and birds. |
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Equine Behaviour @ team @ |
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3395 |
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Lefebvre, L.; Reader, S.M.; Sol, D. |
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Title |
Brains, Innovations and Evolution in Birds and Primates |
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Journal Article |
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2004 |
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Brain, Behavior and Evolution |
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Brain. Behav. Evol. |
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63 |
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4 |
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233-246 |
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Innovation W Brain evolution W Hyperstriatum ventrale W Neostriatum W Isocortex W Birds W Primates W Tool use W Invasion biology |
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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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0006-8977 |
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Equine Behaviour @ team @ |
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4738 |
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Gaunitz, C.; Fages, A.; Hanghøj, K.; Albrechtsen, A.; Khan, N.; Schubert, M.; Seguin-Orlando, A.; Owens, I.J.; Felkel, S.; Bignon-Lau, O.; de Barros Damgaard, P.; Mittnik, A.; Mohaseb, A.F.; Davoudi, H.; Alquraishi, S.; Alfarhan, A.H.; Al-Rasheid, K.A.S.; Crubézy, E.; Benecke, N.; Olsen, S.; Brown, D.; Anthony, D.; Massy, K.; Pitulko, V.; Kasparov, A.; Brem, G.; Hofreiter, M.; Mukhtarova, G.; Baimukhanov, N.; Lõugas, L.; Onar, V.; Stockhammer, P.W.; Krause, J.; Boldgiv, B.; Undrakhbold, S.; Erdenebaatar, D.; Lepetz, S.; Mashkour, M.; Ludwig, A.; Wallner, B.; Merz, V.; Merz, I.; Zaibert, V.; Willerslev, E.; Librado, P.; Outram, A.K.; Orlando, L. |
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Ancient genomes revisit the ancestry of domestic and Przewalski's horses |
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2018 |
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Science |
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360 |
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6384 |
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111-114 |
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The Eneolithic Botai culture of the Central Asian steppes provides the earliest archaeological evidence for horse husbandry, ~5,500 ya, but the exact nature of early horse domestication remains controversial. We generated 42 ancient horse genomes, including 20 from Botai. Compared to 46 published ancient and modern horse genomes, our data indicate that Przewalski's horses are the feral descendants of horses herded at Botai and not truly wild horses. All domestic horses dated from ~4,000 ya to present only show ~2.7% of Botai-related ancestry. This indicates that a massive genomic turnover underpins the expansion of the horse stock that gave rise to modern domesticates, which coincides with large-scale human population expansions during the Early Bronze Age. |
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Admin @ knut @ |
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6212 |
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Zebisch, A.; May, A.; Reese, S.; Gehlen, H. |
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Title |
Effect of different head-neck positions on physical and psychological stress parameters in the ridden horse |
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Journal Article |
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2013 |
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Journal of Animal Physiology and Animal Nutrition |
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J Anim Physiol Anim Nutr |
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98 |
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5 |
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901-907 |
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hyperflexion; head-neck position; stress; training; animal welfare |
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Summary Different head?neck positions (HNPs) are used in equestrian sports and are regarded as desirable for training and competition by riders, judges and trainers. Even though some studies have been indicative of hyperflexion having negative effects on horses, this unnatural position is frequently used. In the present study, the influence of different HNPs on physical and psychological stress parameters in the ridden horse was investigated. Heart rate (HR), heart rate variability (HRV) and blood cortisol levels were measured in 18 horses. Low frequency (LF) and high frequency (HF) are power components in the frequency domain measurement of HRV which show the activity of the sympathetic and parasympathetic nervous system. Values were recorded at rest, while riding with a working HNP and while riding with hyperflexion of the horse's head, neck and poll. In addition, rideability and behaviour during the different investigation stages were evaluated by the rider and by an observer. Neither the HR nor the HRV showed a significant difference between working HNP (HR = 105 ± 22/min; LF/HF = 3.89 ± 5.68; LF = 37.28 ± 10.77%) and hyperflexion (HR = 110 ± 18; LF/HF = 1.94 ± 2.21; LF = 38.39 ± 13.01%). Blood cortisol levels revealed a significant increase comparing working HNP (158 ± 60 nm) and hyperflexion (176 ± 64 nm, p = 0.01). The evaluation of rider and observer resulted in clear changes of rideability and behavioural changes for the worse in all parameters collected between a working HNP and hyperflexion. In conclusion, changes of the cortisol blood level as a physical parameter led to the assumption that hyperflexion of head, neck and poll effects a stress reaction in the horse, and observation of the behaviour illustrates adverse effects on the well-being of horses during hyperflexion. |
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Wiley/Blackwell (10.1111) |
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0931-2439 |
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doi: 10.1111/jpn.12155 |
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Equine Behaviour @ team @ |
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6427 |
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Author |
Clutton-Brock, T.H.; Harvey, P.H. |
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Primates, brains and ecology |
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1980 |
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Journal of Zoology |
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J. Zool. Lond. |
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190 |
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3 |
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309-323 |
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The paper examines systematic relationships among primates between brain size (relative to body size) and differences in ecology and social system. Marked differences in relative brain size exist between families. These are correlated with inter-family differences in body size and home range size. Variation in comparative brain size within families is related to diet (folivores have comparatively smaller brains than frugivores), home range size and possibly also to breeding system. The adaptive significance of these relationships is discussed. |
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Blackwell Publishing Ltd |
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1469-7998 |
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Equine Behaviour @ team @ |
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5451 |
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Author |
Heyes, C.M. |
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Title |
Social learning in animals: categories and mechanisms |
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1994 |
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Biological reviews of the Cambridge Philosophical Society |
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Biol. Rev. |
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69 |
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2 |
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207-231 |
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Animals; *Behavior, Animal; Conditioning (Psychology); *Learning; Reinforcement (Psychology); *Social Behavior |
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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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Department of Psychology, University College London |
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English |
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1464-7931 |
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PMID:8054445 |
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refbase @ user @ |
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708 |
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Author |
A. Wiggins; K. Crowston |
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Title |
From Conservation to Crowdsourcing: A Typology of Citizen Science |
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Conference Article |
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Year |
2011 |
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2011 44th Hawaii International Conference on System Sciences |
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2011 44th Hawaii International Conference on System Sciences |
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1-10 |
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groupware; natural sciences computing; research and development; social sciences; crowdsourcing; citizen science typology; research collaboration; scientific research projects; virtual collaboration; Communities; Education; Monitoring; Collaboration; Organizations; Biological system modeling; Production |
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Citizen science is a form of research collaboration involving members of the public in scientific research projects to address real-world problems. Often organized as a virtual collaboration, these projects are a type of open movement, with collective goals addressed through open participation in research tasks. Existing typologies of citizen science projects focus primarily on the structure of participation, paying little attention to the organizational and macrostructural properties that are important to designing and managing effective projects and technologies. By examining a variety of project characteristics, we identified five types-Action, Conservation, Investigation, Virtual, and Education- that differ in primary project goals and the importance of physical environment to participation. |
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2011 44th Hawaii International Conference on System Sciences |
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1530-1605 |
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Equine Behaviour @ team @ |
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6430 |
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Author |
A. Lanata; A. Guidi; G. Valenza; P. Baragli; E. P. Scilingo |
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Title |
Quantitative heartbeat coupling measures in human-horse interaction |
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Conference Article |
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2016 |
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2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) |
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2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (E |
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2696-2699 |
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electrocardiography; medical signal processing; signal classification; time series; Dtw; Hrv; Mpc; Msc; complex biological systems; dynamic time warping; grooming; heart rate variability time series; heartbeat dynamics; human-horse dynamic interaction; magnitude squared coherence; magnitude-phase coupling; mean phase coherence; nearest mean classifier; quantitative heartbeat coupling; real human-animal interaction; time duration; visual-olfactory interaction; Coherence; Couplings; Electrocardiography; Heart rate variability; Horses; Protocols; Time series analysis |
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Abstract— We present a study focused on a quantitative estimation of a human-horse dynamic interaction. A set of measures based on magnitude and phase coupling between heartbeat dynamics of both humans and horses in three different conditions is reported: no interaction, visual/olfactory interaction and grooming. Specifically, Magnitude Squared Coherence (MSC), Mean Phase Coherence (MPC) and Dynamic Time Warping (DTW) have been used as estimators of the amount of coupling between human and horse through the analysis of their heart rate variability (HRV) time series in a group of eleven human subjects, and one horse. The rationale behind this study is that the interaction of two complex biological systems go towards a coupling process whose dynamical evolution is modulated by the kind and time duration of the interaction itself. We achieved a congruent and consistent
statistical significant difference for all of the three indices. Moreover, a Nearest Mean Classifier was able to recognize the three classes of interaction with an accuracy greater than 70%. Although preliminary, these encouraging results allow a discrimination of three distinct phases in a real human-animal interaction opening to the characterization of the empirically proven relationship between human and horse. |
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2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (E |
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1557-170x |
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Equine Behaviour @ team @ |
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6175 |
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Bandini , E.; Motes-Rodrigo, A.; Steele, M.P.; Rutz, C.; Tennie, C. |
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Examining the mechanisms underlying the acquisition of animal tool behaviour |
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2020 |
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Biology Letters |
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Biol. Lett. |
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16 |
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2020122 |
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Equine Behaviour @ team @ |
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6660 |
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