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Iliopoulos, Y.; Sgardelis, S.; Koutis, V.; Savaris, D. |
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Title |
Wolf depredation on livestock in central Greece |
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Journal Article |
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Year |
2009 |
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Mammal Research |
Abbreviated Journal |
Mamm. Reas. |
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54 |
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1 |
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11-22 |
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We studied wolfCanis lupus Linnaeus, 1758 -- livestock conflict in central Greece by investigating patterns of 267 verified wolf attacks on livestock for 21 months. Wolves attacked adult goats 43% and cattle 218% more than expected, whereas sheep 41% less than expected from their availability. Wolves killed less than four sheep or goats in 79%, and one cow or calf in 74% of depredation events, respectively. We recorded higher attack rates during wolf post-weaning season. Wolf attacks on strayed, or kept inside non predator-proof enclosures, sheep and goats, were on average two to four times respectively more destructive than those when livestock was guarded by a shepherd. Sheepdog use reduced losses per attack. Optimal sheepdog number ranged from 3 to 9 animals depending on flock size. Losses per attack were positively related to the number of wolves involved. Total losses per farm were positively correlated with the size of livestock unit but percentage losses per capita increased with decreasing flock size. Management implications to mitigate livestock depredation are discussed. |
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2199-241x |
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Equine Behaviour @ team @ Iliopoulos2009 |
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6576 |
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Author |
Genov, P.W.; Kostava, V. |
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Title |
Untersuchungen zur zahlenmäßigen Stärke des Wolfes und seiner Einwirkung auf die Haustierbestände in Bulgarien |
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Year |
1993 |
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Zeitschrift für Jagdwissenschaft |
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39 |
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4 |
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217-223 |
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Die Untersuchung wurde in der Zeitspanne von 1984 bis 1988 durchgeführt. Es wurden die Protokolle des Staatlichen Versicherungsinstituts benutzt, die Angaben für Raubüberfälle von Wölfen auf Haustiere beinhalten (Tabelle 1). Außerdem wurden Angaben über die während dieser Zeitspanne erlegten Wölfe zusammengefaßt. Die Abschußzahlen lauten: 1984 – 163, 1985 – 147, 1986 – 179, 1987 – 211 und 1988 – 220 Tiere. Die Anzahl der in den einzelnen Gebirgen lebenden Wölfe wurde nach einer Umfrage festgestellt. Für die in Betracht kommenden Gebirge werden folgende Bestandszahlen angenommen: Rhodopen -- 60-80 Individuen, 189 bis 264 km2 pro Tier, Rila- und Piringebirge -- 60-80 Tiere, 109 bis 145 km2 pro Tier, Ossogowo-Belassiza Gebirgssystem -- 40-50 Individuen, 57-70 km2 pro Tier, West- und Mittelbalkan -- 35-38 Wölfe, 200 km2 pro Tier. Dazu kommen noch 10-15 Wölfe im Flußbecken von Beli Lom und etwa 20 Exemplare in Strandscha- und Sakargebirge. Insgesamt lebten in Bulgarien im Jahre 1988 etwa 260-330 Wölfe (Abb. 1). |
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1439-0574 |
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Equine Behaviour @ team @ Genov1993 |
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6686 |
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Ruid, D.B.; Paul, W.J.; Roell, B.J.; Wydeven, A.P.; Willging, R.C.; Jurewicz, R.L.; Lonsway, D.H. |
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Title |
Wolf-Human Conflicts and Management in Minnesota, Wisconsin, and Michigan |
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2009 |
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Recovery of Gray Wolves in the Great Lakes Region of the United States: An Endangered Species Success Story |
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279-295 |
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Springer New York |
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New York, NY |
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Wydeven, A.P.; Van Deelen, T.R.; Heske, E.J. |
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978-0-387-85952-1 |
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Equine Behaviour @ team @ Ruid2009 |
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6577 |
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Irving-Pease, E.K.; Ryan, H.; Jamieson, A.; Dimopoulos, E.A.; Larson, G.; Frantz, L.A.F. |
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Title |
Paleogenomics of Animal Domestication |
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Book Chapter |
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2019 |
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Paleogenomics: Genome-Scale Analysis of Ancient DNA |
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225-272 |
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Starting with dogs, over 15,000 years ago, the domestication of animals has been central in the development of modern societies. Because of its importance for a range of disciplines – including archaeology, biology and the humanities – domestication has been studied extensively. This chapter reviews how the field of paleogenomics has revolutionised, and will continue to revolutionise, our understanding of animal domestication. We discuss how the recovery of ancient DNA from archaeological remains is allowing researchers to overcome inherent shortcomings arising from the analysis of modern DNA alone. In particular, we show how DNA, extracted from ancient substrates, has proven to be a crucial source of information to reconstruct the geographic and temporal origin of domestic species. We also discuss how ancient DNA is being used by geneticists and archaeologists to directly observe evolutionary changes linked to artificial and natural selection to generate a richer understanding of this fascinating process. |
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Springer International Publishing |
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Cham |
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Lindqvist, C.; Rajora, O.P. |
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978-3-030-04753-5 |
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Equine Behaviour @ team @ Irving-Pease2019 |
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6583 |
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Author |
Boyce, P.N.; McLoughlin, P.D. |
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Title |
Ecological Interactions Involving Feral Horses and Predators: Review with Implications for Biodiversity Conservation |
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Journal Article |
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Year |
2021 |
Publication |
The Journal of Wildlife Management |
Abbreviated Journal |
Jour. Wild. Mgmt. |
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n/a |
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n/a |
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apparent competition; artificial selection; community ecology; conservation; feral horse (Equus ferus caballus); life history; predator-prey dynamics |
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ABSTRACT For many ecosystems, feral horses are increasingly becoming an important if not dominant component of ungulate biomass and hence influence on community dynamics. Yet we still know little of how horses contribute to key ecological interactions including predator-prey and indirect competitive relationships at a community level. Notably, feral species like horses can exhibit life-history traits that differ from that of native (mainly artiodactyl) herbivore competitors. Artificial selection for traits like increased, early, or extended reproduction that have yet to be reversed by natural selection, coupled with naturally selected differences in anatomy and behavior, in addition to unique management objectives for horses compared to other species, means that the dynamics of feral horse populations are not likely to align with what might be expected of other large herbivores. Unexpected population dynamics and inherent biological asymmetries between native ungulates and feral horses may therefore influence the former via direct competition for shared resources and through enemy-mediated interactions like apparent competition. In several localities feral horses now co-exist with multiple native prey species, some of which are in decline or are species at risk. Compounding risks to native species from direct or indirect competitive exclusion by horses is the unique nature and socio-political context of feral horse management, which tends towards allowing horse populations to be limited largely by natural, density-dependent factors. We summarize the inherent asymmetries between feral horse biology and that of other ungulate prey species with consequences for conservation, focusing on predator-prey and emerging indirect interactions in multi-prey systems, and highlight future directions to address key knowledge gaps in our understanding of how feral horses may now be contributing to the (re)structuring of food webs. Observations of patterns of rapid growth and decline, and associated skews in sex ratios of feral horse populations, indicate a heightened potential for indirect interactions among large ungulate prey species, where there is a prevalence of feral horses as preferred prey, particularly where native prey are declining. In places like western North America, we expect predator-prey interactions involving feral horses to become an increasingly important factor in the conservation of wildlife. This applies not only to economically or culturally important game species but also at-risk species, both predators (e.g., wolves [Canis lupus], grizzly bears [Ursus arctos]) and prey (e.g., woodland caribou [Rangifer tarandus caribou]), necessitating an ecological understanding of the role of horses in natural environments that goes beyond that of population control. ? 2021 The Wildlife Society. |
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John Wiley & Sons, Ltd |
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0022-541x |
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https://doi.org/10.1002/jwmg.21995 |
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Equine Behaviour @ team @ |
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6642 |
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Author |
Hofmeester, T.R.; Cromsigt, J.P.G.M.; Odden, J.; Andrén, H.; Kindberg, J.; Linnell, J.D.C. |
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Title |
Framing pictures: A conceptual framework to identify and correct for biases in detection probability of camera traps enabling multi-species comparison |
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Journal Article |
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2019 |
Publication |
Ecology and Evolution |
Abbreviated Journal |
Ecol Evol |
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animal characteristics; detectability; environmental variables; mammal monitoring; reuse of data; trail camera |
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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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John Wiley & Sons, Ltd |
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2045-7758 |
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doi: 10.1002/ece3.4878 |
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Equine Behaviour @ team @ |
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6518 |
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Sueur, C.; Jacobs, A.; Amblard, F.; Petit, O.; King, A.J. |
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How can social network analysis improve the study of primate behavior? |
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Journal Article |
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2010 |
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American Journal of Primatology |
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Am. J. Primatol. |
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73 |
Issue |
8 |
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703-719 |
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interaction; association; social system; social structure; methodology; behavioral sampling |
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Abstract When living in a group, individuals have to make trade-offs, and compromise, in order to balance the advantages and disadvantages of group life. Strategies that enable individuals to achieve this typically affect inter-individual interactions resulting in nonrandom associations. Studying the patterns of this assortativity using social network analyses can allow us to explore how individual behavior influences what happens at the group, or population level. Understanding the consequences of these interactions at multiple scales may allow us to better understand the fitness implications for individuals. Social network analyses offer the tools to achieve this. This special issue aims to highlight the benefits of social network analysis for the study of primate behaviour, assessing it's suitability for analyzing individual social characteristics as well as group/population patterns. In this introduction to the special issue, we first introduce social network theory, then demonstrate with examples how social networks can influence individual and collective behaviors, and finally conclude with some outstanding questions for future primatological research. Am. J. Primatol. 73:703?719, 2011. ? 2011 Wiley-Liss, Inc. |
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Wiley-Blackwell |
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0275-2565 |
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doi: 10.1002/ajp.20915 |
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Equine Behaviour @ team @ |
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6410 |
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Author |
McGreevy, P.; Yeates, J. |
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Horses (Equus caballus) |
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2018 |
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Companion Animal Care and Welfare |
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animal company; behavioural signs; diseases; domestic horses; euthanasia; human interaction; nutritional requirements |
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Summary Domestic horses are equid members of the class Mammalia, order Perissodactyla, and family Equidae. Horses are obligate herbivores, with nutritional requirements as listed in a table. Adequate space is necessary for exercise, exploration, flight, sharing resources, play, and rolling. Company is essential for all horses, including stallions. Company provides opportunities for mutual grooming and play and allows horses to stand head-to-tail to remove flies. Unhandled horses may respond to humans as they would to predators, whereas handled horses' responses depend on their previous interactions with humans. Horses can suffer from several diseases as listed in another table. The best method of euthanasia of horses is usually sedation followed by either cranial shooting or the injection of an overdose of pentobarbitone into the jugular vein. Behavioural signs of distress can include increased locomotory activity, vigilance behaviours, neighing, snorting, pawing, nibbling walls and buckets, defaecation, rearing, kicking stable walls or doors, and high-stepping 'prancing'. |
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Wiley Online Books |
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Companion Animal Care and Welfare |
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9781119333708 |
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doi:10.1002/9781119333708.ch13 |
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Equine Behaviour @ team @ |
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6506 |
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Beery, A.K.; Kaufer, D. |
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Stress, social behavior, and resilience: Insights from rodents |
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2015 |
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Neurobiology of Stress |
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Neurobiol. Stress |
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1 |
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Stress Resilience |
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116-127 |
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Stress; Anxiety; Social behavior; Sociality; Social stress; Social buffering |
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The neurobiology of stress and the neurobiology of social behavior are deeply intertwined. The social environment interacts with stress on almost every front: social interactions can be potent stressors; they can buffer the response to an external stressor; and social behavior often changes in response to stressful life experience. This review explores mechanistic and behavioral links between stress, anxiety, resilience, and social behavior in rodents, with particular attention to different social contexts. We consider variation between several different rodent species and make connections to research on humans and non-human primates. |
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2352-2895 |
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Equine Behaviour @ team @ |
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6413 |
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Bücheler, T.; Sieg, J.H. |
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Title |
Understanding Science 2.0: Crowdsourcing and Open Innovation in the Scientific Method |
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Journal Article |
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2011 |
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Procedia Computer Science |
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Proceedings of the 2nd European Future Technologies Conference and Exhibition 2011 (FET 11) |
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7 |
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327-329 |
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Crowdsourcing; Open Innovation; Simulation; Agent-Based Modeling; Science 2.0; Citizen Science |
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The innovation process is currently undergoing significant change in many industries. The World Wide Web has created a virtual world of collective intelligence and helped large groups of people connect and collaborate in the innovation process [1]. Von Hippel [2], for instance, states that a large number of users of a given technology will come up with innovative ideas. This process, originating in business, is now also being observed in science. Discussions around “Citizen Science” [3] and “Science 2.0” [4] suggest the same effects are relevant for fundamental research practices. “Crowdsourcing” [5] and “Open Innovation” [6] as well as other names for those paradigms, like Peer Production, Wikinomics, Swarm Intelligence etc., have become buzzwords in recent years. However, serious academic research efforts have also been started in many disciplines. In essence, these buzzwords all describe a form of collective intelligence that is enabled by new technologies, particularly internet connectivity. The focus of most current research on this topic is in the for-profit domain, i.e. organizations willing (and able) to pay large sums to source innovation externally, for instance through innovation contests. Our research is testing the applicability of Crowdsourcing and some techniques from Open Innovation to the scientific method and basic science in a non-profit environment (e.g., a traditional research university). If the tools are found to be useful, this may significantly change how some research tasks are conducted: While large, apriori unknown crowds of “irrational agents” (i.e. humans) are used to support scientists (and teams thereof) in several research tasks through the internet, the usefulness and robustness of these interactions as well as scientifically important factors like quality and validity of research results are tested in a systematic manner. The research is highly interdisciplinary and is done in collaboration with scientists from sociology, psychology, management science, economics, computer science, and artificial intelligence. After a pre-study, extensive data collection has been conducted and the data is currently being analyzed. The paper presents ideas and hypotheses and opens the discussion for further input. |
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1877-0509 |
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Equine Behaviour @ team @ |
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6434 |
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