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Author |
Hoffman, C.L.; Suchak, M. |
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Title |
Dog rivalry impacts following behavior in a decision-making task involving food |
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Journal Article |
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2017 |
Publication |
Animal Cognition |
Abbreviated Journal |
Anim. Cogn. |
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1-13 |
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Dogs learn a great deal from humans and other dogs. Previous studies of socially influenced learning between dogs have typically used a highly trained demonstrator dog who is unfamiliar to the observer. Because of this, it is unknown how dynamics between familiar dogs may influence their likelihood of learning from each other. In this study, we tested dogs living together in two-dog households on whether individual dogs’ rivalry scores were associated with performance on a local enhancement task. Specifically, we wanted to know whether dog rivalry impacted whether an observer dog would approach a plate from which a demonstrator dog had eaten all available food, or whether the observer dog would approach the adjacent plate that still contained food. Dog rivalry scores were calculated using the Canine Behavioral Assessment and Research Questionnaire and indicated each dog’s tendency to engage aggressively with the other household dog. Low-rivalry dogs were more likely to approach the empty plate than high-rivalry dogs when the observer dog was allowed to approach the plates immediately after the demonstrator had moved out of sight. This difference between low- and high-rivalry dogs disappeared, however, when observer dogs had to wait 5 s before approaching the plates. The same pattern was observed during a control condition when a human removed the food from a plate. Compared to low-rivalry dogs, high-rivalry dogs may pay less attention to other dogs due to a low tolerance for having other dogs in close proximity. |
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1435-9456 |
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Equine Behaviour @ team @ Hoffman2017 |
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6131 |
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Author |
Griffin, A.S.; Tebbich, S.; Bugnyar, T. |
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Title |
Animal cognition in a human-dominated world |
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Journal Article |
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2017 |
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Animal Cognition |
Abbreviated Journal |
Anim. Cogn. |
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20 |
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1 |
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1-6 |
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In the USA, each year, up to one billion birds are estimated to die from colliding with windowpanes (Sabo et al. 2016). A further 573,000 are struck down by wind turbines, along with 888,000 bats (Smallwood 2013). Worldwide, unintended capture in fishing devices is recognized as the single most serious global threat to migratory, long-lived marine taxa including turtles, birds, mammals and sharks (Wallace et al. 2013). Estimates put the number of amphibians killed per year on Australian roads at 5 million (Seiler 2003). The likelihood of a green turtle erroneously ingesting plastic debris, often by mistaking them for food, rose from 30% in 1985 to almost 50% in 2012 (Schuyler et al. 2013). Human-induced rapid environmental change (HIREC, sensu Sih et al. 2011) is filling animals’ environments with new threats which bear little or excessive similarity to those they have encountered in their evolutionary history (Dwernychuk and Boag 1972; Patten and Kelley 2010; Witherington 1997). As a consequence, many of the stimuli involved fall outside the adaptive processing space of animals’ evolutionary perceptual, learning, memory and decision-making systems, making individuals particularly vulnerable to their impact. |
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1435-9456 |
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Equine Behaviour @ team @ Griffin2017 |
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6129 |
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GONÇALVES DA SILVA, A.; CAMPOS-ARCEIZ, A.; ZAVADA, M.S. |
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Title |
On tapir ecology, evolution and conservation: what we know and future perspectives–part II |
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2013 |
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Integrative Zoology |
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8 |
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1 |
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1-3 |
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Blackwell Publishing Ltd |
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1749-4877 |
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Equine Behaviour @ team @ |
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6141 |
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Byrne, R.W.; Whiten, A. |
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Tactical deception in primates: the 1990 database |
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Book Whole |
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1990 |
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Primate Reports |
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Primate Rep. |
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27 |
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1-101 |
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German Primate Center |
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Equine Behaviour @ team @ |
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6172 |
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Krueger, K.; Marr, I.; Farmer, K. |
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Title |
Equine Cognition |
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Book Chapter |
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2017 |
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Encyclopedia of Animal Cognition and Behavior |
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1-11 |
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Springer International Publishing |
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Cham |
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Vonk, J.; Shackelford, T. |
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978-3-319-47829-6 |
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Equine Behaviour @ team @ Krueger2017 |
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6181 |
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Author |
Ronnenberg, K.; Habbe, B.; Gräber, R.; Strauß, E.; Siebert, U. |
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Title |
Coexistence of wolves and humans in a densely populated region (Lower Saxony, Germany) |
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Journal Article |
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Year |
2017 |
Publication |
Basic and Applied Ecology |
Abbreviated Journal |
Basic. Appl. Ecol. |
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25 |
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1-14 |
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Grey wolf; ; Habitat use; Species distribution models; Predator-prey interactions |
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Since the first sporadic occurrences of grey wolves (Canis lupus) west of the Polish border in 1996, wolves have shown a rapid population recovery in Germany. Wolves are known to avoid people and wolf attacks on humans are very rare worldwide. However, the subjectively perceived threat is considerable, especially as food-conditioned habituation to humans occurs sporadically. Lower Saxony (Germany) has an exceedingly higher human population density than most other regions with territorial wolves; thus, the potential for human-wolf conflicts is higher. Using hunters' wildlife survey data from 455 municipalities and two years (2014-2015) and data from the official wolf monitoring (557 confirmed wolf presences and 500 background points) collected between 2012-2015, grey wolf habitat selection was modelled using generalized additive models with respect to human population density, road density, forest cover and roe deer density. Moreover, we tested whether habitat use changed in response to human population and road density between 2012/2013 and 2014/2015. Wolves showed a preference for areas of low road density. Human population density was less important as a covariate in the model of the survey data. Areas with higher prey abundance (5-10 roe deer/km2) and areas with >20% forest cover were preferred wolf habitats. Wolves were mostly restricted to areas with the lowest road and human population densities. However, between the two time periods, avoidance of human density decreased significantly. Recolonization of Germany is still in its early stages and it is unclear where this process will halt. To-date authorities mainly concentrate on monitoring measures. However, to avoid conflict, recolonization will require more stringent management of wolf populations and an improved information strategy for rural populations. |
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1439-1791 |
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Equine Behaviour @ team @ |
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6397 |
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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 |
Publication |
2011 44th Hawaii International Conference on System Sciences |
Abbreviated Journal |
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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Abstract |
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 |
Sabou, M.; Bontcheva, K.; Scharl, A. |
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Title |
Crowdsourcing Research Opportunities: Lessons from Natural Language Processing |
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Conference Article |
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2012 |
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Proceedings of the 12th International Conference on Knowledge Management and Knowledge Technologies |
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1-18 |
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crowdsourcing, games with a purpose, natural language processing, resource acquisition |
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Acm |
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New York, NY, USA |
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i-KNOW '12 |
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978-1-4503-1242-4 |
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Equine Behaviour @ team @ Sabou:2012:CRO:2362456.2362479 |
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6436 |
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Bernauer, K.; Kollross, H.; Schuetz, A.; Farmer, K.; Krueger, K. |
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Title |
How do horses (Equus caballus) learn from observing human action? |
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Journal Article |
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Year |
2020 |
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Animal Cognition |
Abbreviated Journal |
Anim. Cogn. |
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23 |
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1-9 |
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A previous study demonstrated that horses can learn socially from observing humans, but could not draw any conclusions about the social learning mechanisms. Here we develop this by showing horses four different human action sequences as demonstrations of how to press a button to open a feed box. We tested 68 horses aged between 3 and 12 years. 63 horses passed the habituation phase and were assigned either to the group Hand Demo (N = 13) for which a kneeling person used a hand to press the button, Head Demo (N = 13) for which a kneeling person used the head, Mixed Demo (N = 12) for which a squatting person used both head and hand, Foot Demo (N = 12) in which a standing person used a foot, or No Demo (N = 13) in which horses did not receive a demonstration. 44 horses reached the learning criterion of opening the feeder twenty times consecutively, 40 of these were 75% of the Demo group horses and four horses were 31% of the No Demo group horses. Horses not reaching the learning criterion approached the human experimenters more often than those who did. Significantly more horses used their head to press the button no matter which demonstration they received. However, in the Foot Demo group four horses consistently preferred to use a hoof and two switched between hoof and head use. After the Mixed Demo the horses' actions were more diverse. The results indicate that only a few horses copy behaviours when learning socially from humans. A few may learn through observational conditioning, as some appeared to adapt to demonstrated actions in the course of reaching the learning criterion. Most horses learn socially through enhancement, using humans to learn where, and which aspect of a mechanism has to be manipulated, and by applying individual trial and error learning to reach their goal. |
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Equine Behaviour @ team @ Bernauer2019 |
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6590 |
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Author |
Freitas, J.; Lagos, L.; Álvares, F. |
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Horses as prey of wolves. |
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2021 |
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Carnivore Damage Preventionnews |
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CDPnews |
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23 |
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1-9 |
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Equine Behaviour @ team @ |
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6677 |
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