Environmental drivers of autumn migration departure decisions in midcontinental mallards

Movement Ecology

David G. Krementz¹  Luke W. Naylor²  Kwasi Asante³  Florian G. Weller⁴  Dylan C. Kesler⁵  Elisabeth B. Webb⁶  William S. Beatty⁷ 

[1] Arkansas Cooperative Fish and Wildlife Research Unit, Department of Biological Sciences, University of Arkansas, 72701, Fayetteville, AR, USA;Arkansas Game and Fish Commission, 72205, Little Rock, AR, USA;Environmental Systems Research Institute (Esri), 3325 Springbank Ln # 200, 28226, Charlotte, NC, USA;Missouri Cooperative Fish and Wildlife Research Unit, School of Natural Resources, University of Missouri, 65211, Columbia, MO, USA;The Institute for Bird Populations, PO Box 1346, 94956, Point Reyes Station, CA, USA;U.S. Geological Survey, Missouri Cooperative Fish and Wildlife Research Unit, 65211, Columbia, MO, USA;U.S. Geological Survey, Upper Midwest Environmental Sciences Center, 54601, La Crosse, WI, USA;

关键词: Autumn migration;    Mallard;    Satellite tracking;    Discrete choice model;    Mississippi Flyway;   

DOI  :  10.1186/s40462-021-00299-x

来源: Springer

【 摘 要 】

BackgroundThe timing of autumn migration in ducks is influenced by a range of environmental conditions that may elicit individual experiences and responses from individual birds, yet most studies have investigated relationships at the population level. We used data from individual satellite-tracked mallards (Anas platyrhynchos) to model the timing and environmental drivers of autumn migration movements at a continental scale.MethodsWe combined two sets of location records (2004–2007 and 2010–2011) from satellite-tracked mallards during autumn migration in the Mississippi Flyway, and identified records that indicated the start of long-range (≥ 30 km) southward movements during the migration period. We modeled selection of departure date by individual mallards using a discrete choice model accounting for heterogeneity in individual preferences. We developed candidate models to predict the departure date, conditional on daily mean environmental covariates (i.e. temperature, snow and ice cover, wind conditions, precipitation, cloud cover, and pressure) at a 32 × 32 km resolution. We ranked model performance with the Bayesian Information Criterion.ResultsDeparture was best predicted (60% accuracy) by a “winter conditions” model containing temperature, and depth and duration of snow cover. Models conditional on wind speed, precipitation, pressure variation, and cloud cover received lower support. Number of days of snow cover, recently experienced snow cover (snow days) and current snow cover had the strongest positive effect on departure likelihood, followed by number of experienced days of freezing temperature (frost days) and current low temperature. Distributions of dominant drivers and of correct vs incorrect prediction along the movement tracks indicate that these responses applied throughout the latitudinal range of migration. Among recorded departures, most were driven by snow days (65%) followed by current temperature (30%).ConclusionsOur results indicate that among the tested environmental parameters, the dominant environmental driver of departure decision in autumn-migrating mallards was the onset of snow conditions, and secondarily the onset of temperatures close to, or below, the freezing point. Mallards are likely to relocate southwards quickly when faced with snowy conditions, and could use declining temperatures as a more graduated early cue for departure. Our findings provide further insights into the functional response of mallards to weather factors during the migration period that ultimately determine seasonal distributions.

【 授权许可】

CC BY