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In migratory species, the timing of arrival at the breeding grounds is a life-history trait with major fitness consequences. The optimal arrival date varies from year-to-year, and animals use cues to adjust their arrival dates to match this annual variation. However, which cues they use to time their arrival and whether these cues actually predict the annual optimal arrival date is largely unknown. Here, we integrate causal and evolutionary analysis by identifying the environmental variables used by a migratory songbird to time its arrival dates and testing whether these environmental variables also predicted the optimal time to arrive. We used 11 years of male arrival data of a pied flycatcher population. Specifically, we tested whether temperature and normalized difference vegetation index (NDVI) values from their breeding grounds in the Netherlands and from their wintering grounds in Ivory Coast explained the variation in arrival date, and whether these variables correlated with the position of the annual fitness peak at the breeding grounds. We found that temperature and NDVI, both from the wintering and the breeding grounds, explained the annual variation in arrival date, but did not correlate with the optimal arrival date. We explore three alternative explanations for this lack of correlation. Firstly, the date of the fitness peak may have been incorrectly estimated because a potentially important component of fitness (i.e., migration date dependent mortality en route or directly upon arrival) could not be measured. Secondly, we focused on male timing but the fitness landscape is also likely to be shaped by female timing. Finally, the correlation has recently disappeared because climate change disrupted the predictive value of the cues that the birds use to time their migration. In the latter case, birds may adapt by altering their sensitivity to temperature and NDVI.

Timing of reproduction has major fitness consequences, which can only be understood when the phenology of the food for the offspring is quantified. For insectivorous birds, like great tits (Parus major), synchronisation of their offspring needs and abundance of caterpillars is the main selection pressure. We measured caterpillar biomass over a 20-year period and showed that the annual peak date is correlated with temperatures from 8 March to 17 May. Laying dates also correlate with temperatures, but over an earlier period (16 March-20 April). However, as we would predict from a reliable cue used by birds to time their reproduction, also the food peak correlates with these temperatures. Moreover, the slopes of the phenology of the birds and caterpillar biomass, when regressed against the temperatures in this earlier period, do not differ. The major difference is that due to climate change, the relationship between the timing of the food peak and the temperatures over the 16 March-20 April period is changing, while this is not so for great tit laying dates. As a consequence, the synchrony between offspring needs and the caterpillar biomass has been disrupted in the recent warm decades. This may have severe consequences as we show that both the number of fledglings as well as their fledging weight is affected by this synchrony. We use the descriptive models for both the caterpillar biomass peak as for the great tit laying dates to predict shifts in caterpillar and bird phenology 2005-2100, using an IPCC climate scenario. The birds will start breeding earlier and this advancement is predicted to be at the same rate as the advancement of the food peak, and hence they will not reduce the amount of the current mistiming of about 10 days.

Summary Populations are shifting their phenology in response to climate change, but these shifts are often asynchronous among interacting species. Resulting phenological mismatches can drive simultaneous changes in natural selection and population demography, but the links between these interacting processes are poorly understood. Here we analyse 37 years of data from an individual‐based study of great tits (Parus major) in the Netherlands and use mixed‐effects models to separate the within‐ and across‐year effects of phenological mismatch between great tits and caterpillars (a key food source for developing nestlings) on components of fitness at the individual and population levels. Several components of individual fitness were affected by individual mismatch (i.e. late breeding relative to the caterpillar food peak date), including the probability of double‐brooding, fledgling success, offspring recruitment probability and the number of recruits. Together these effects contributed to an overall negative relationship between relative fitness and laying dates, that is, selection for earlier laying on average. Directional selection for earlier laying was stronger in years where birds bred on average later than the food peak, but was weak or absent in years where the phenology of birds and caterpillars matched (i.e. no population mismatch). The mean number of fledglings per female was lower in years when population mismatch was high, in part because fewer second broods were produced. Population mismatch had a weak effect on the mean number of recruits per female, and no effect on mean adult survival, after controlling for the effects of breeding density and the quality of the autumnal beech (Fagus sylvatica) crop. These findings illustrate how climate change‐induced mismatch can have strong effects on the relative fitness of phenotypes within years, but weak effects on mean demographic rates across years. We discuss various general mechanisms that influence the extent of coupling between breeding phenology, selection and population dynamics in open populations subject to strong density regulation and stochasticity.

Climate change has led to changes in the strength of directional selection on seasonal timing. Understanding the causes and consequences of these changes is crucial to predict the impact of climate change. But are observed patterns in one population generalizable to others, and can spatial variation in selection be explained by environmental variation among populations? We used long-term data (1955–2022) on blue and great tits co-occurring in four locations across the Netherlands to assess inter-population variation in temporal patterns of selection on laying date. To analyse selection, we combine reproduction and adult survival into a joined fitness measure. We found distinct spatial variation in temporal patterns of selection which overall acted towards earlier laying, and which was due to selection through reproduction rather than through survival. The underlying relationships between temperature, bird and caterpillar phenology were however the same across populations, and the spatial variation in selection patterns is thus caused by spatial variation in the temperatures and other habitat characteristics to which birds and caterpillars respond. This underlines that climate change is not necessarily equally affecting populations, but that we can understand this spatial variation, which enables us to predict climate change effects on selection for other populations.

AbstractThe phenology of many species shows strong sensitivity to climate change; however, with few large scale intra-specific studies it is unclear how such sensitivity varies over a species’ range. We document large intra-specific variation in phenological sensitivity to temperature using laying date information from 67 populations of two co-familial European songbirds, the great tit (Parus major) and blue tit (Cyanistes caeruleus), covering a large part of their breeding range. Populations inhabiting deciduous habitats showed stronger phenological sensitivity than those in evergreen and mixed habitats. However, populations with higher sensitivity tended to have experienced less rapid change in climate over the past decades, such that populations with high phenological sensitivity will not necessarily exhibit the strongest phenological advancement. Our results show that to effectively assess the impact of climate change on phenology across a species’ range it will be necessary to account for intra-specific variation in phenological sensitivity, climate change exposure, and the ecological characteristics of a population.