• Energy Research

Organisms time activities by using environmental cues to forecast the future availability of important resources. Presently, there is limited understanding of the relationships between cues and optimal timing, and especially about how this relationship will be affected by environmental changes. We develop a general model to explore the relation between a cue and the optimal timing of an important life history activity. The model quantifies the fitness loss for organisms failing to time behaviours optimally. We decompose the immediate change in fitness resulting from environmental changes into a component that is due to changes in the predictive power of the cue and a component that derives from the mismatch of the old response to the cue to the new environmental conditions. Our results show that consequences may range from negative, neutral to positive and are highly dependent on how cue and optimal timing and their relation are specifically affected by environmental changes.

AbstractSingle phenological measures, like the average rate of phenological advancement, may be insufficient to explain how climate change is driving trends in animal populations. Here, we develop a multifactorial concept of spring phenology—including the onset of spring, spring duration, interannual variability, and their temporal changes—as a driver for population dynamics of migratory terrestrial species in seasonal environments. Using this conceptual model, we found that effects of advancing spring phenology on animal populations may be buffered or amplified depending on the duration and interannual variability of spring green‐up, and those effects are modified by evolutionary and plastic adaptations of species. Furthermore, we compared our modelling results with empirical data on normalized difference vegetation index‐based spring green‐up phenology and population trends of 106 European landbird finding similar associations. We conclude how phenological changes are expected to affect migratory bird populations across Europe and identify regions that are particularly prone to suffer population declines.

The timing of migration and migratory steps is highly relevant for fitness. Because environmental conditions vary between years, the optimal time for migration varies accordingly. Therefore, migratory animals could clearly benefit from acquiring information as to when it is the best time to migrate in a specific year. Thus, environmental predictability and variability are fundamental characteristics of migration systems but their relationship and consequence for migratory progression has remained unexplored. We develop a simple dynamic model to identify the optimal migration behaviour in environments that differ in predictability, variability and the number of intermediate stop-over sites. Our results indicate that higher predictability along migration routes enables organisms to better time migration when phenology deviates from its long-term average and thus, increases fitness. Information is particularly valuable in highly variable environments and in the final migration-step, i.e. before the destination. Furthermore, we show that a general strategy for obtaining information in relatively uninformative but variable environments is using intermediate stop-over sites that enable migrants to better predict conditions ahead. Our study contributes to a better understanding of the relationship between animal movement and environmental predictability—an important, yet underappreciated factor that strongly influences migratory progression.

AbstractLong‐term shifts in vegetation phenology generally follow the pattern of global warming. Yet, topographical complexity and biome diversity cause uneven spatial trends in the phenological response of vegetation to climate change. If phenology changes similarly along migration routes, individuals may adequately respond by shifting the whole migration schedule to still time life history with local phenological events. On the contrary, phenological shifts that differ in direction or magnitude between sites can enhance the risk of mistiming, resulting in reduced survival and reproductive success and eventually population declines. We identified the direction and magnitude of long‐term shifts in vegetation phenology along avian migration routes, using remotely sensed vegetation data over 29 yr (1982–2010) to estimate the risk of mistiming for different sets of assumptions concerning cues and adaptability of migration timing. For this study, we used individual series of non‐breeding, spring stopover and breeding sites (determined by light‐level geolocation) of three European populations of Luscinia megarhynchos (Common Nightingale), an insectivorous Palearctic long‐distance migrant. The breeding populations in France, Italy, and Bulgaria are representatives for populations migrating on the western, central, and eastern flyway toward sub‐Saharan Africa. The direction and magnitude of phenological shifts differed between migration stages and across flyways and under most sets of assumptions, the resulting risk of mistiming was higher in the Western compared to Central and Eastern flyway. We emphasize that estimates for the risk of mistiming as resulting from phenological shifts highly depend on the cues that migrants use to time migratory progression and on the adaptive potential of the particular migratory species to react to phenological shifts.

AbstractAimKnowledge of broad‐scale biogeographical patterns of animal migration is important for understanding ecological drivers of migratory behaviours. Here, we present a flyway‐scale assessment of the spatial structure and seasonal dynamics of the Afro‐Palaearctic bird migration system and explore how phenology of the environment guides long‐distance migration.LocationEurope and Africa.Time period2009–2017.Major taxa studiedBirds.MethodsWe compiled an individual‐based dataset comprising 23 passerine and near‐passerine species of 55 European breeding populations, in which a total of 564 individuals were tracked during migration between Europe and sub‐Saharan Africa. In addition, we used remotely sensed primary productivity data (the normalized difference vegetation index) to estimate the timing of vegetation green‐up in spring and senescence in autumn across Europe. First, we described how individual breeding and non‐breeding sites and the migratory flyways link geographically. Second, we examined how the timing of migration along the two major Afro‐Palaearctic flyways is tuned with vegetation phenology at the breeding sites.ResultsWe found the longitudes of individual breeding and non‐breeding sites to be related in a strongly positive manner, whereas the latitudes of breeding and non‐breeding sites were related negatively. In autumn, migration commenced ahead of vegetation senescence, and the timing of migration was 5–7 days earlier along the Western flyway compared with the Eastern flyway. In spring, the time of arrival at breeding sites was c. 1.5 days later for each degree northwards and 6–7 days later along the Eastern compared with the Western flyway, reflecting the later spring green‐up at higher latitudes and more eastern longitudes.Main conclusionsMigration of the Afro‐Palaearctic landbirds follows a longitudinally parallel leapfrog migration pattern, whereby migrants track vegetation green‐up in spring but depart before vegetation senescence in autumn. The degree of continentality along migration routes and at the breeding sites of the birds influences the timing of migration on a broad scale.

AbstractClimate change is drastically changing the timing of biological events across the globe. Changes in the phenology of seasonal migrations between the breeding and wintering grounds have been observed across biological taxa, including birds, mammals, and insects. For birds, strong links have been shown between changes in migration phenology and changes in weather conditions at the wintering, stopover, and breeding areas. For other animal taxa, the current understanding of, and evidence for, climate (change) influences on migration still remains rather limited, mainly due to the lack of long‐term phenology datasets. Bracken Cave in Texas (USA) holds one of the largest bat colonies of the world. Using weather radar data, a unique 23‐year (1995–2017) long time series was recently produced of the spring and autumn migration phenology of Brazilian free‐tailed bats (Tadarida brasiliensis) at Bracken Cave. Here, we analyse these migration phenology time series in combination with gridded temperature, precipitation, and wind data across Mexico and southern USA, to identify the climatic drivers of (changes in) bat migration phenology. Perhaps surprisingly, our extensive spatiotemporal search did not find temperature to influence either spring or autumn migration. Instead, spring migration phenology seems to be predominantly driven by wind conditions at likely wintering or spring stopover areas during the migration period. Autumn migration phenology, on the other hand, seems to be dominated by precipitation to the east and north‐east of Bracken Cave. Long‐term changes towards more frequent migration and favourable wind conditions have, furthermore, allowed spring migration to occur 16 days earlier. Our results illustrate how some of the remaining knowledge gaps on the influence of climate (change) on bat migration and abundance can be addressed using weather radar analyses.

Abstract The timing of migration and migratory steps is highly relevant for fitness. Since environmental conditions vary between years, the optimal time for migration varies accordingly. Therefore, migratory animals could clearly benefit from acquiring information as to when it is the best time to migrate in a specific year. Thus, environmental predictability and variability are fundamental characteristics of migration systems but their relation and consequence for migratory progression has remained unexplored. We develop a simple dynamic model to identify the optimal migration behaviour in environments that differ in predictability, variability and the number of intermediate stop-over sites. Our results indicate that higher predictability along migration routes enables organisms to better time migration when phenology deviates from its long-term average and thus, increases fitness. Information is particularly valuable in highly variable environments and in the final migration-step, i.e. before the destination. Furthermore, we show that a general strategy for obtaining information in relatively uninformative but variable environments is using intermediate stop-over sites that enable migrants to better predict conditions ahead. Our study contributes to a better understanding of the relation between animal movement and environmental predictability - an important, yet underappreciated factor that strongly influences migratory progression.