Anna Dornhaus
Associate Professor, Department of Ecology & Evolutionary Biology
Joint Faculty, Department of Pyschology
Joint Faculty, Department of Entomology
(520) 626-8586
2002, PhD, Zoology, University of Würzburg

Anna Dornhaus' main interest is understanding the evolution of organization in groups. This includes how collective behaviors emerge from the actions and interactions of individuals, but also the ecological conditions that promote the evolution of particular collective strategies. She studies as model systems social insect colonies (bumble bees, honey bees and ants) in the laboratory and in the field and uses mathematical and individual-based modeling approaches. Recent work has included the role of communication in the allocation of foragers to food sources and the relevance of this for mutualistic interactions (e.g., in pollination or in ant-plant mutualisms); the evolution of different recruitment systems in different species of bees and how ecology shapes these recruitment systems; speed-accuracy trade offs in decision-making and learning and how they affect signal evolution; and whether different group sizes necessitate different organizational strategies.

Selected Citations: 

Bengston SE, Dornhaus A 2014 'Be meek or be bold? A colony-level behavioural syndrome in ants', Proceedings of the Royal Society: Biological Sciences 281: publ online

Charbonneau D, Hillis N, Dornhaus A 2014 ‘‘Lazy’ in nature: ant colony time budgets show high ‘inactivity’ in the field as well as in the lab’, Insectes sociaux published online

Dornhaus A 2014 ‘Finding food: foraging affects all aspects of an animal’s life’, in: Yasukawa K ‘Animal Behavior, Volume II: Function and Evolution of Animal Behavior’, Praeger Publishers

Jandt J, Dornhaus A 2014 'Bumblebee response thresholds and body size: does worker diversity increase colony performance?', Animal Behavior 87:97-106

Jandt J, Bengston S, Pinter-Wollman N, Pruitt J, Raine N, Dornhaus A, Sih A 2014 'Behavioral syndromes and social insects: personality at multiple levels', Biological Reviews 89: 48-67

Leonard AS, Brent J, Papaj D, Dornhaus A 2013 ‘Floral Nectar Guide Patterns Discourage Nectar Robbing by Bumble Bees’, PLoS One 8:e55914

Charbonneau D, Blonder B, Dornhaus A 2013 ‘Social insects: a model system for network dynamics’, In Holme P and Jari S: Temporal Networks. Springer books

Donaldson-Matasci MC, DeGrandi-Hoffman G, Dornhaus A 2013 ‘Bigger is better: honeybee colonies as distributed information-gathering systems’, Animal Behaviour 85: 585-592

Goldsby HJ, Dornhaus A, Kerr B, Ofria C 2012 ‘Task-switching costs promote the evolution of division of labor and shifts in individuality’, PNAS 109: 13686-13691

Blonder B, Wey TW, Dornhaus A, James R, Sih A 2012 ‘Temporal dynamics and network analysis’, Methods in Ecology and Evolution 3: 958–972

Dornhaus A 2012 ‘Finding optimal collective strategies using individual-based simulations: colony organization in social insects’, Mathematical and Computer Modelling of Dynamical Systems 18: 25-37

Dornhaus A, Powell S 2010 ‘Foraging and defence strategies’ In: ‘Ant Ecology’, Eds. L Lach, C Parr, K Abbott, Ant Ecology, Oxford University Press

Couvillon MJ, Dornhaus A 2009 ‘Location, location, location: larvae position inside the nest is correlated with adult body size in worker bumble bees (Bombus impatiens)’, Proceedings of the Royal Society: Biological Sciences 276: 2411-2418

Marshall JAR, Bogacz R, Dornhaus A, Planque R, Kovacs T, Franks NR, 2009 ‘On optimal decision-making in brains and social insect colonies’ Journal of The Royal Society Interface 6: 1065-1074

Dornhaus A 2008 ‘Specialization does not predict individual efficiency in an ant’ PLoS Biology 6: e285

Chittka, L., Dyer, A., Bock, F., Dornhaus, A., 2003, “Bees trade off foraging speed for accuracy”, Nature 424: 388 

Dornhaus, A., Chittka, L., 1999, “Evolutionary origins of bee dances”, Nature 401: 38

Research Themes: 
Informatics, Modeling, and Remote Sensing
Modeling and simulation
Natural Environment and Biodiversity
Animal behavior
Ecological behavior
Modeling and simulation
Science Engagement

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