Weller Florian G, Beatty William S, Webb Elisabeth B, Kesler Dylan C, Krementz David G, Asante Kwasi, Naylor Luke W
Missouri Cooperative Fish and Wildlife Research Unit, School of Natural Resources, University of Missouri, Columbia, MO, 65211, USA.
U.S. Geological Survey, Upper Midwest Environmental Sciences Center, La Crosse, WI, 54601, USA.
Mov Ecol. 2022 Jan 5;10(1):1. doi: 10.1186/s40462-021-00299-x.
The 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.
We 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.
Departure 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%).
Our 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.
鸭子秋季迁徙的时间受到一系列环境条件的影响,这些条件可能引发个体鸟类的独特经历和反应,但大多数研究都是在种群层面研究它们之间的关系。我们利用卫星追踪的绿头鸭(Anas platyrhynchos)个体数据,在大陆尺度上对秋季迁徙运动的时间和环境驱动因素进行建模。
我们整合了两组卫星追踪的绿头鸭在密西西比飞行路线秋季迁徙期间(2004 - 2007年和2010 - 2011年)的位置记录,并确定了表明迁徙期间开始长距离(≥30公里)向南移动的记录。我们使用离散选择模型对个体绿头鸭出发日期的选择进行建模,该模型考虑了个体偏好的异质性。我们开发了候选模型,以预测出发日期,条件是32×32公里分辨率下的每日平均环境协变量(即温度、雪和冰覆盖、风况、降水、云量和气压)。我们用贝叶斯信息准则对模型性能进行排名。
一个包含温度、积雪深度和持续时间的“冬季条件”模型对出发日期的预测效果最佳(准确率60%)。基于风速、降水、气压变化和云量的模型得到的支持较低。积雪天数、近期经历的积雪天数(降雪日)和当前积雪对出发可能性的正向影响最强,其次是经历的冰冻温度天数(霜冻日)和当前低温。主导驱动因素以及沿移动轨迹的正确与错误预测分布表明,这些反应适用于整个迁徙纬度范围。在记录的出发情况中,大多数是由降雪日(65%)驱动的,其次是当前温度(30%)。
我们的结果表明,在测试的环境参数中,秋季迁徙绿头鸭出发决策的主要环境驱动因素是降雪条件的出现,其次是接近或低于冰点温度的出现。绿头鸭在面对下雪情况时可能会迅速向南迁移,并可以将温度下降作为更渐进的早期出发信号。我们的研究结果为绿头鸭在迁徙期间对天气因素的功能反应提供了进一步的见解,这些因素最终决定了季节性分布。