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气候驱动的中途停歇地变化对北极鹅迁徙时间表和健康状况的影响。

The consequences of climate-driven stop-over sites changes on migration schedules and fitness of Arctic geese.

作者信息

Bauer Silke, Van Dinther Martijn, Høgda Kjell-Arild, Klaassen Marcel, Madsen Jesper

机构信息

Netherlands Institute of Ecology (NIOO-KNAW), Centre for Limnology, PO Box 1299, 3600 BG Maarssen, the Netherlands.

出版信息

J Anim Ecol. 2008 Jul;77(4):654-60. doi: 10.1111/j.1365-2656.2008.01381.x. Epub 2008 Apr 4.

Abstract
  1. How climatic changes affect migratory birds remains difficult to predict because birds use multiple sites in a highly interdependent manner. A better understanding of how conditions along the flyway affect migration and ultimately fitness is of paramount interest. 2. Therefore, we developed a stochastic dynamic model to generate spatially and temporally explicit predictions of stop-over site use. For each site, we varied energy expenditure, onset of spring, intake rate and day-to-day stochasticity independently. We parameterized the model for the migration of pink-footed goose Anser brachyrhynchus from its wintering grounds in Western Europe to its breeding grounds on Arctic Svalbard. 3. Model results suggested that the birds follow a risk-averse strategy by avoiding sites with comparatively high energy expenditure or stochasticity levels in favour of sites with highly predictable food supply and low expenditure. Furthermore, the onset of spring on the stop-over sites had the most pronounced effect on staging times while intake rates had surprisingly little effect. 4. Subsequently, using empirical data, we tested whether observed changes in the onset of spring along the flyway explain the observed changes in migration schedules of pink-footed geese from 1990 to 2004. Model predictions generally agreed well with empirically observed migration patterns, with geese leaving the wintering grounds earlier while considerably extending their staging times in Norway.
摘要
  1. 气候变化如何影响候鸟仍然难以预测,因为鸟类以高度相互依存的方式利用多个地点。更好地了解迁徙路线沿线的条件如何影响迁徙以及最终的适应性至关重要。2. 因此,我们开发了一个随机动态模型,以生成对中途停留地使用情况的时空明确预测。对于每个地点,我们分别改变能量消耗、春季开始时间、摄入率和每日随机性。我们为粉脚雁从西欧越冬地到北极斯瓦尔巴群岛繁殖地的迁徙对该模型进行了参数化。3. 模型结果表明,鸟类采取规避风险的策略,避开能量消耗相对较高或随机性水平较高的地点,而选择食物供应高度可预测且消耗低的地点。此外,中途停留地的春季开始时间对停留时间有最显著的影响,而摄入率的影响出人意料地小。4. 随后,我们利用实证数据检验了沿迁徙路线观察到的春季开始时间变化是否能解释1990年至2004年粉脚雁迁徙时间表的变化。模型预测与实证观察到的迁徙模式总体上吻合良好,大雁更早离开越冬地,同时在挪威的停留时间大幅延长。

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