Bird Migration Research Station, Faculty of Biology, University of Gdańsk, Wita Stwosza, Poland.
Department of Biological Sciences, University of Cape Town, Rondebosch, Cape Town, South Africa.
PeerJ. 2022 Feb 18;10:e12964. doi: 10.7717/peerj.12964. eCollection 2022.
Many migrant birds have been returning to Europe earlier in spring since the 1980s. This has been attributed mostly to an earlier onset of spring in Europe, but we found the timing of Willow Warblers' passage to be influenced by climate indices for Africa as much as those for Europe. Willow Warblers' spring passage through northern Europe involves populations from different wintering quarters in Africa. We therefore expected that migration timing in the early, middle and late periods of spring would be influenced sequentially by climate indices operating in different parts of the winter range.
Using data from daily mistnetting in 1 April-15 May over 1982-2017 at Bukowo (Poland, Baltic Sea coast), we derived an Annual Anomaly (AA, in days) of Willow Warbler spring migration. We decomposed this anomaly into three main periods (1-26 April, 27 April-5 May, 6-15 May); one-third of migrants in each period. We modelled three sequential time series of spring passage using calendar year and 15 large-scale climate indices averaged over the months of Willow Warblers' life stages in the year preceding spring migration as explanatory variables in multiple regression models. Nine climate variables were selected in the best models. We used these nine explanatory variables and calculated their partial correlations in models for nine overlapping sub-periods of AA. The pattern of relationships between AA in these nine sub-periods of spring and the nine climate variables indicated how spring passage had responded to the climate. We recommend this method for the study of birds' phenological responses to climate change.
The Southern Oscillation Index and Indian Ocean Dipole in Aug-Oct showed large partial correlations early in the passage, then faded in importance. For the Sahel Precipitation Index (PSAH) and Sahel Temperature Anomaly (TSAH) in Aug-Oct partial correlations occurred early then peaked in mid-passage; for PSAH (Nov-March) correlations peaked at the end of passage. NAO and local temperatures (April-May) showed low correlations till late April, which then increased. For the Scandinavian Index (Jun-Jul) partial correlations peaked in mid-passage. Year was not selected in any of the best models, indicating that the climate variables alone accounted for Willow Warblers' multiyear trend towards an earlier spring passage.
Climate indices for southern and eastern Africa dominated relationships in early spring, but western African indices dominated in mid- and late spring. We thus concluded that Willow Warblers wintering in southern and eastern Africa dominated early arrivals, but those from western Africa dominated later. We suggest that drivers of phenological shifts in avian migration are related to changes in climate at remote wintering grounds and at stopovers, operating with climate change in the north, especially for species with complex and long-distance migration patterns.
自 20 世纪 80 年代以来,许多候鸟在春季返回欧洲的时间提前了。这主要归因于欧洲春季的开始时间更早,但我们发现,柳莺春季迁徙的时间不仅受到欧洲气候指数的影响,还受到非洲气候指数的影响。柳莺在北欧的春季迁徙涉及来自非洲不同越冬地的种群。因此,我们预计春季早期、中期和晚期的迁徙时间将依次受到在冬季活动范围不同部位运作的气候指数的影响。
我们使用了 1982 年至 2017 年 4 月 1 日至 5 月 15 日期间,在波兰波罗的海沿岸的布科沃(Bukowo)每日进行的雾网监测数据,得出了柳莺春季迁徙的年度异常值(AA,以天数计)。我们将这个异常值分解为三个主要时期(4 月 1 日至 26 日、4 月 27 日至 5 月 5 日、5 月 6 日至 15 日);每个时期的三分之一的候鸟。我们使用日历年度和 15 个大规模气候指数作为解释变量,在春季迁徙前一年的柳莺生命阶段月份进行平均,为三个连续的春季迁徙时间序列建立了多元回归模型。在最佳模型中选择了九个气候变量。我们使用这九个解释变量,并在模型中计算了它们在 AA 的九个重叠子期间的偏相关。AA 的这九个子期间与九个气候变量之间的关系模式表明了春季迁徙对气候的响应方式。我们建议使用这种方法来研究鸟类对气候变化的物候响应。
8-10 月的南方涛动指数和印度洋偶极子在迁徙早期表现出较大的偏相关,然后重要性逐渐减弱。8-10 月的萨赫勒降水指数(PSAH)和萨赫勒温度异常(TSAH)的偏相关在迁徙中期达到峰值,然后在迁徙后期达到峰值;11-3 月的 PSAH 偏相关在迁徙后期达到峰值。4-5 月的北大西洋涛动指数(NAO)和当地温度的相关性直到 4 月下旬才较低,然后才增加。6-7 月的斯堪的纳维亚指数(Scandinavian Index)的偏相关在迁徙中期达到峰值。在任何最佳模型中都没有选择年份,这表明气候变量单独解释了柳莺多年来春季迁徙提前的趋势。
南部和东部非洲的气候指数主导了早春的关系,但西部非洲的指数在中春和晚春主导了关系。因此,我们得出的结论是,在南部和东部非洲越冬的柳莺主导了早期到达,但在西部非洲越冬的柳莺主导了晚期到达。我们认为,鸟类迁徙物候变化的驱动因素与候鸟在遥远的越冬地和中途停留地的气候变化有关,这些变化与北方的气候变化有关,特别是对于具有复杂和长途迁徙模式的物种。