Wind conditions and geography shape the first outbound migration of juvenile honey buzzards and their distribution across sub-Saharan Africa

Vansteelant, Wouter M. G.; Kekkonen, Jaana; Byholm, Patrik

doi:10.1098/rspb.2017.0387

Cited by 63 publications

(92 citation statements)

References 72 publications

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“…Origination bias • Juveniles of some migratory birds exhibit more route variation than older individuals (Mueller et al, 2013;Oppel et al, 2015;Vansteelant et al, 2017) Developmental variation biased in its origination • The inventors of novel behavior are usually more likely to be experienced individuals than youngsters in nonhuman primates (Kendal et al, 2005;, and more commonly low-ranking than dominants .…”

Section: Category Examplesmentioning

confidence: 99%

“…For instance, inexperienced individuals may be more likely to try novel behaviors, as in several large migratory bird species where juveniles exhibit more variation in migratory routes than older individuals (Mueller, O'Hara, Converse, Urbanek, & Fagan, 2013;Oppel et al, 2015;Vansteelant, Kekkonen, & Byholm, 2017), particularly when there are few experienced adults in the population (Mueller et al, 2013;Oppel et al, 2015). For instance, inexperienced individuals may be more likely to try novel behaviors, as in several large migratory bird species where juveniles exhibit more variation in migratory routes than older individuals (Mueller, O'Hara, Converse, Urbanek, & Fagan, 2013;Oppel et al, 2015;Vansteelant, Kekkonen, & Byholm, 2017), particularly when there are few experienced adults in the population (Mueller et al, 2013;Oppel et al, 2015).…”

Section: Biases Arising From Individual Learningmentioning

confidence: 99%

“…Additionally, unlike genetic mutations, which generally occur equally likely across all members of the population, behavioral innovations may be significantly more likely to arise among particular classes of individuals in the population. For instance, inexperienced individuals may be more likely to try novel behaviors, as in several large migratory bird species where juveniles exhibit more variation in migratory routes than older individuals (Mueller, O'Hara, Converse, Urbanek, & Fagan, 2013;Oppel et al, 2015;Vansteelant, Kekkonen, & Byholm, 2017), particularly when there are few experienced adults in the population (Mueller et al, 2013;Oppel et al, 2015). Although juveniles suffer from higher mortality, they are thought to be more likely to discover novel adaptive routes.…”

Section: Biases Arising From Individual Learningmentioning

confidence: 99%

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Animal learning as a source of developmental bias

Laland

Toyokawa

Oudman

2019

Evolution and Development

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As a form of adaptive plasticity that allows organisms to shift their phenotype toward the optimum, learning is inherently a source of developmental bias. Learning may be of particular significance to the evolutionary biology community because it allows animals to generate adaptively biased novel behavior tuned to the environment and, through social learning, to propagate behavioral traits to other individuals, also in an adaptively biased manner. We describe several types of developmental bias manifest in learning, including an adaptive bias, historical bias, origination bias, and transmission bias, stressing that these can influence evolutionary dynamics through generating nonrandom phenotypic variation and/or nonrandom environmental states. Theoretical models and empirical data have established that learning can impose direction on adaptive evolution, affect evolutionary rates (both speeding up and slowing down responses to selection under different conditions) and outcomes, influence the probability of populations reaching global optimum, and affect evolvability. Learning is characterized by highly specific, path-dependent interactions with the (social and physical) environment, often resulting in new phenotypic outcomes. Consequently, learning regularly introduces novelty into phenotype space. These considerations imply that learning may commonly generate plasticity first evolution. K E Y W O R D Sdevelopmental bias, evolvability, learning, plasticity, plasticity first

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Section: Category Examplesmentioning

confidence: 99%

Section: Biases Arising From Individual Learningmentioning

confidence: 99%

Section: Biases Arising From Individual Learningmentioning

confidence: 99%

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Animal learning as a source of developmental bias

Laland

Toyokawa

Oudman

2019

Evolution and Development

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“…Winds can determine longitudes at which juveniles settle for stopover and non-breeding sites during the first migration (Vansteelant, Kekkonen, & Byholm, 2017), sites that they may continue to use for the rest of their lives (cf Cresswell, 2014). Environmental factors could thus influence the degree of migratory connectivity between important parts of the annual cycle in many migrant species, depending on innate migratory direction in juvenile birds, locomotion mode and migratory strategy (Åkesson & Hedenström, 2007;Alerstam & Hedenström, 1998;Berthold & Helbig, 1992;Marra et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Wind‐associated detours promote seasonal migratory connectivity in a flapping flying long‐distance avian migrant

Norevik

Åkesson

Artois

et al. 2019

Journal of Animal Ecology

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It is essential to gain knowledge about the causes and extent of migratory connectivity between stationary periods of migrants to further the understanding of processes affecting populations, and to allow efficient implementation of conservation efforts throughout the annual cycle. Avian migrants likely use optimal routes with respect to mode of locomotion, orientation and migration strategy, influenced by external factors such as wind and topography. In self‐powered flapping flying birds, any increases in fuel loads are associated with added flight costs. Energy‐minimizing migrants are therefore predicted to trade‐off extended detours against reduced travel across ecological barriers with no or limited foraging opportunities. Here, we quantify the extent of detours taken by different populations of European nightjars Caprimulgus europaeus, to test our predictions that they used routes beneficial according to energetic principles and evaluate the effect of route shape on seasonal migratory connectivity. We combined data on birds tracked from breeding sites along a longitudinal gradient from England to Sweden. We analysed the migratory connectivity between breeding and main non‐breeding sites, and en route stopover sites just south of the Sahara desert. We quantified each track's route extension relative to the direct route between breeding and wintering sites, respectively, and contrasted it to the potential detour derived from the barrier reduction along the track while accounting for potential wind effects. Nightjars extended their tracks from the direct route between breeding and main non‐breeding sites as they crossed the Mediterranean Sea–Sahara desert, the major ecological barrier in the Palaearctic–African migration system. These clockwise detours were small for birds from eastern sites but increased from east to west breeding longitude. Routes of the tracked birds were associated with partial reduction in the barrier crossing resulting in a trade‐off between route extension and barrier reduction, as expected in an energy‐minimizing migrant. This study demonstrates how the costs of barrier crossings in prevailing winds can disrupt migratory routes towards slightly different goals, and thereby promote migratory connectivity. This is an important link between individual migration strategies in association with an ecological barrier, and both spatially and demographic population patterns.

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“…Adult birds are more able to account and correct for the effects of wind but inexperienced juveniles, who are likely not navigating to a specific location, are not as able to rectify their direction (Thorup et al, ). The direction and strength of the wind are likely to have a large effect on where young birds initially arrive in Sub‐Saharan Africa (Vansteelant et al, ). However, it is not clear how this may affect where they eventually settle.…”

Section: Introductionmentioning

confidence: 99%

Evidence of large‐scale range shift in the distribution of a Palaearctic migrant in Africa

Howes

Symes

Byholm

2019

Diversity and Distributions

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Aim Long‐distance Palaearctic migrant birds are declining at a faster rate than short‐distance migrant or resident species. This is often attributed to changes on their non‐breeding grounds and along their migratory routes. The European honey buzzard (Pernis apivorus) is a scarce migrant in southern Africa that is declining globally. This study assessed the distribution and abundance of honey buzzards in southern Africa over the past four decades and compared it to trends in the East African population to examine possible drivers of population expansion in southern Africa. Location Southern and East Africa. Methods European honey buzzard reporting data were collected from a variety of sources including citizen science databases (1983–2017). In addition, records of all other southern African vagrants (including ten other regularly occurring species) were gathered to account for changes in birdwatching effort in the subregion. To assess the effect of forest loss on honey buzzard abundance, rolling correlations were performed using forest cover in East Africa and number of honey buzzard records in both subregions. Results European honey buzzard records in southern Africa have increased over five times more than other regularly occurring vagrant species and almost 40 times more than honey buzzard in Tanzania, where the population has remained stable. Loss of forested area in East Africa was correlated with an increase in European honey buzzard records in southern Africa. Main conclusions We suggest that the European honey buzzard shift in wintering range may be driven by a decline in suitable habitat further north in Africa amongst other possible reasons. This effect may have been amplified by an increase in appropriate habitat across southern Africa brought about by anthropogenic changes to vegetation such as increased tree cover in urban areas. This study further highlights the importance of using African distributional data banks to understand the effects of global change on Palaearctic migrant bird species.

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Wind conditions and geography shape the first outbound migration of juvenile honey buzzards and their distribution across sub-Saharan Africa

Cited by 63 publications

References 72 publications

Animal learning as a source of developmental bias

Animal learning as a source of developmental bias

Wind‐associated detours promote seasonal migratory connectivity in a flapping flying long‐distance avian migrant

Evidence of large‐scale range shift in the distribution of a Palaearctic migrant in Africa

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