On the journey to wintering sites, migratory birds usually alternate between flights and stopovers where they rest and refuel. Migration strategies are assumed to differ according to season: a time-minimization pre-breeding migration strategy towards breeding locations, and an energy-minimization post-breeding migration strategy to wintering ones. The duration of flights and stopovers determines the energy requirements and the total duration of the journey. Since migrating birds actually spend most of the time at stopovers, selection to minimize the amount of energy or time spent on migration is very likely to operate on the effectiveness of stopover rest and refueling. Here we address the relative contribution of factors to departure decisions from stopover sites during the post-breeding migration in a long-distance migratory songbird. When capture probability is low it is impossible to assess the variation in body condition over the entire duration of the stopover. To get around this, we use Time Since Arrival (TSA) as a proxy for the changes in the state of individuals during the stopover. We propose that TSA is an integrative proxy for resting, feeding and fattening efficiency. We develop a capture-recapture model to address the relationship between departure probability, estimated TSA, and weather conditions. Using a 20-year dataset from sedge warblers, we show that TSA has a larger effect on departure probability than weather conditions. Low humidity and an increase in atmospheric pressure in the days preceding departure are associated with higher departure probability, but these effects are smaller than that of TSA.

中文翻译：

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什么时候离开中途停留站点？自到达时间比当前天气情况更重要

在前往越冬地点的旅程中，候鸟通常会在飞行和中途停留之间交替，在那里休息并加油。假定迁移策略根据季节而有所不同：向繁殖地点迁移的时间最小化的育种前迁移策略，向越冬种群的能量最小化的育种后迁移策略。飞行和中途停留的持续时间决定了能量需求和旅程的总持续时间。由于迁徙鸟类实际上大部分时间都停留在中途停留，因此选择尽可能减少迁徙所需的能量或时间很可能取决于中途休息和加油的有效性。在这里，我们解决了长距离迁徙鸣禽繁殖后迁移过程中因素对中途停留地点离开决定的相对贡献。当捕获概率较低时，就无法评估中途停留整个过程中身体状况的变化。为了解决这个问题，我们使用“到达后的时间”（TSA）作为中途停留期间个人状态变化的代理。我们建议TSA是休息，喂养和育肥效率的综合指标。我们开发了一个捕获-捕获模型来解决出发概率，估计的TSA和天气状况之间的关系。使用莎草莺的20年数据集，我们显示TSA对离开概率的影响大于天气条件。离港前几天的低湿度和大气压力的升高与离港概率较高有关，但这些影响小于TSA。