Jay A VonBank1,2, Mitch D Weegman3, Paul T Link4, Stephanie A Cunningham3, Kevin J Kraai5, Daniel P Collins6, Bart M Ballard7. 1. Caesar Kleberg Wildlife Research Institute, Texas A&M University - Kingsville, Kingsville, TX, 78363, USA. jvonbank@usgs.gov. 2. Present Address: U.S. Geological Survey, Northern Prairie Wildlife Research Center, Jamestown, ND, 58401, USA. jvonbank@usgs.gov. 3. School of Natural Resources, University of Missouri, Columbia, MO, 65211, USA. 4. Louisiana Department of Wildlife and Fisheries, Baton Rouge, LA, 70808, USA. 5. Texas Parks and Wildlife Department, Canyon, TX, 79015, USA. 6. U.S. Fish and Wildlife Service, Albuquerque, NM, 87102, USA. 7. Caesar Kleberg Wildlife Research Institute, Texas A&M University - Kingsville, Kingsville, TX, 78363, USA.
Abstract
BACKGROUND: Animal movement patterns are the result of both environmental and physiological effects, and the rates of movement and energy expenditure of given movement strategies are influenced by the physical environment an animal inhabits. Greater white-fronted geese in North America winter in ecologically distinct regions and have undergone a large-scale shift in wintering distribution over the past 20 years. White-fronts continue to winter in historical wintering areas in addition to contemporary areas, but the rates of movement among regions, and energetic consequences of those decisions, are unknown. Additionally, linkages between wintering and breeding regions are generally unknown, and may influence within-winter movement rates. METHODS: We used Global Positioning System and acceleration data from 97 white-fronts during two winters to elucidate movement characteristics, model regional transition probabilities using a multistate model in a Bayesian framework, estimate regional energy expenditure, and determine behavior time-allocation influences on energy expenditure using overall dynamic body acceleration and linear mixed-effects models. We assess the linkages between wintering and breeding regions by evaluating the winter distributions for each breeding region. RESULTS: White-fronts exhibited greater daily movement early in the winter period, and decreased movements as winter progressed. Transition probabilities were greatest towards contemporary winter regions and away from historical wintering regions. Energy expenditure was up to 55% greater, and white-fronts spent more time feeding and flying, in contemporary wintering regions compared to historical regions. White-fronts subsequently summered across their entire previously known breeding distribution, indicating substantial mixing of individuals of varying breeding provenance during winter. CONCLUSIONS: White-fronts revealed extreme plasticity in their wintering strategy, including high immigration probability to contemporary wintering regions, high emigration from historical wintering regions, and high regional fidelity to western regions, but frequent movements among eastern regions. Given that movements of white-fronts trended toward contemporary wintering regions, we anticipate that a wintering distribution shift eastward will continue. Unexpectedly, greater energy expenditure in contemporary wintering regions revealed variable energetic consequences of choice in wintering region and shifting distribution. Because geese spent more time feeding in contemporary regions than historical regions, increased energy expenditure is likely balanced by increased energy acquisition in contemporary wintering areas.
BACKGROUND: Animal movement patterns are the result of both environmental and physiological effects, and the rates of movement and energy expenditure of given movement strategies are influenced by the physical environment an animal inhabits. Greater white-fronted geese in North America winter in ecologically distinct regions and have undergone a large-scale shift in wintering distribution over the past 20 years. White-fronts continue to winter in historical wintering areas in addition to contemporary areas, but the rates of movement among regions, and energetic consequences of those decisions, are unknown. Additionally, linkages between wintering and breeding regions are generally unknown, and may influence within-winter movement rates. METHODS: We used Global Positioning System and acceleration data from 97 white-fronts during two winters to elucidate movement characteristics, model regional transition probabilities using a multistate model in a Bayesian framework, estimate regional energy expenditure, and determine behavior time-allocation influences on energy expenditure using overall dynamic body acceleration and linear mixed-effects models. We assess the linkages between wintering and breeding regions by evaluating the winter distributions for each breeding region. RESULTS: White-fronts exhibited greater daily movement early in the winter period, and decreased movements as winter progressed. Transition probabilities were greatest towards contemporary winter regions and away from historical wintering regions. Energy expenditure was up to 55% greater, and white-fronts spent more time feeding and flying, in contemporary wintering regions compared to historical regions. White-fronts subsequently summered across their entire previously known breeding distribution, indicating substantial mixing of individuals of varying breeding provenance during winter. CONCLUSIONS: White-fronts revealed extreme plasticity in their wintering strategy, including high immigration probability to contemporary wintering regions, high emigration from historical wintering regions, and high regional fidelity to western regions, but frequent movements among eastern regions. Given that movements of white-fronts trended toward contemporary wintering regions, we anticipate that a wintering distribution shift eastward will continue. Unexpectedly, greater energy expenditure in contemporary wintering regions revealed variable energetic consequences of choice in wintering region and shifting distribution. Because geese spent more time feeding in contemporary regions than historical regions, increased energy expenditure is likely balanced by increased energy acquisition in contemporary wintering areas.
Entities:
Keywords:
Accelerometer; Bio-logging; Movement ecology; Multistate model; Overall dynamic body acceleration; Philopatry; Waterfowl
Authors: Francesca Cagnacci; Luigi Boitani; Roger A Powell; Mark S Boyce Journal: Philos Trans R Soc Lond B Biol Sci Date: 2010-07-27 Impact factor: 6.237
Authors: Rory P Wilson; Craig R White; Flavio Quintana; Lewis G Halsey; Nikolai Liebsch; Graham R Martin; Patrick J Butler Journal: J Anim Ecol Date: 2006-09 Impact factor: 5.091
Authors: L G Halsey; E L C Shepard; F Quintana; A Gomez Laich; J A Green; R P Wilson Journal: Comp Biochem Physiol A Mol Integr Physiol Date: 2008-09-27 Impact factor: 2.320
Authors: Mitch D Weegman; Stuart Bearhop; Geoff M Hilton; Alyn J Walsh; Kaitlin M Weegman; David J Hodgson; Anthony David Fox Journal: Oecologia Date: 2016-03-19 Impact factor: 3.225