• Energy Research
• 2. Zero hunger close
• 13. Climate action close

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.

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.

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.

Climate change has led to phenological shifts in many species, but with large variation in magnitude among species and trophic levels. The poster child example of the resulting phenological mismatches between the phenology of predators and their prey is the great tit (Parus major), where this mismatch led to directional selection for earlier seasonal breeding. Natural climate variability can obscure the impacts of climate change over certain periods, weakening phenological mismatching and selection. Here, we show that selection on seasonal timing indeed weakened significantly over the past two decades as increases in late spring temperatures have slowed down. Consequently, there has been no further advancement in the date of peak caterpillar food abundance, while great tit phenology has continued to advance, thereby weakening the phenological mismatch. We thus show that the relationships between temperature, phenologies of prey and predator, and selection on predator phenology are robust, also in times of a slowdown of warming. Using projected temperatures from a large ensemble of climate simulations that take natural climate variability into account, we show that prey phenology is again projected to advance faster than great tit phenology in the coming decades, and therefore that long-term global warming will intensify phenological mismatches. Data was collected in our long-term population of great tits (Parus major) at the Hoge Veluwe population (Netherlands). It was processed using ACCESS database queries and R-scripts. See the ReadMe file.

Climate change does not equally affect temporal patterns of natural selection on reproductive timing across populations in two songbird species --- There are 8 EXCEL files: **1\. Tbl\_Fitness\_GT\_HVVLOHLBWH\_FirstClutches:** This file provides the breeding data of blue and great tits of four study areas. For each brood, it contains information about mother's identity, laying dates, brood size and whether manipulations were made. Area Four study areas Species Two species YearOfBreeding Year of breeding Mother Ring ID of female parent of the brood LayDateApril Date of first egg of first brood of the year for that mother (in April days, 1 April = day 1) ClutchSize Number of eggs laid within one clutch NumberFledged Number of chicks that fledged NumberFlededDeviation The number gives the number of chicks that might have fledged in addition to the number given in column "NumberFledged". The best estimate of the actual number of fledged chicks is: NumberFledged + 0.5 \* NumberFledgedDeviation NumberRecruitsAllBroodsSummed Number of recruiting offspring produced, summed over all broods of that year Include Is 1 if there has been no manipulation of the brood, otherwise is 0 **2\. Qry\_survival\_04\_Survial\_output:** This file contains information about the survival of each breeding female for all four blue and great tit populations. RingNumberFemale Ring numbers of the breeding females BroodYear Year Area Four study sites Species Great or blue tit LayDate Date of first egg of first brood of the year for that mother (in April days, 1 April = day 1) Survival 0-survival means bird has not been seen again, 1-survival means bird survived/was seen again **3\. tbl\_PeakDate\_Biomass\_AllAreas\_AllSpecies:** This file contains data on the caterpillar biomass and the dates, where biomass reached its maximum, i.e. peak date. AreaName Four study areas Year Year MidDate Date of maximum of the caterpillar biomass (in April days, 1 April = day 1) MaxBiom Maximum biomass on peak date in [g/(day \* m²)] **4\. Tbl\_budburst\_HV which:** This file gives the annual average date of bud burst of oak trees at the Hoge Veluwe. AreaShortName Only data on Hoge Veluwe (= HV) Year Year AprilAVG Average April day of oak bud burst (1 April= day 1) SumOfTrees Total number of trees measured in that year **5\. Tbl\_BeechCropIndex:** This file gives the beech crop index at the Hoge Veluwe. The index is a 3-point scale categorizing the amount of beech nuts into low, intermediate and high crop. Year Year NoTreesSampled Total number of trees sampled in that year BeechCropNet Net beech crop in [g/m²] BCINet Scale of 1 to 3, grouping net beech crop into low (=1), intermediate (=2) and high (=3) **6\. Qry\_mark\_05\_input\_file:** This file was created as the input data for the survival analysis with RMark. It is a more condensed version of the first file (Tbl\_Fitness\_GT\_HVVLOHLBWH\_FirstClutches) and contains information on the identity of each breeding female and the timing of her broods. RingNumberFemale Ring numbers of breeding females BroodYear Year Area Four study sites Species Great or blue tit LayDate Date of first egg of first brood of the year for that mother (in April days, 1 April= day 1) **7\. deBilt\_1955\_2022:** This file contains the daily temperature data of the weather station "de Bilt" for years 1955 to 2022 as derived from the KNMI. Temperatures are given in 0.1 °C. STN = 260 Meteo Station = DeBilt YYYYMMDD Year - Month - Day TN Minimum daily temperature in [0.1 °C] TX Maximum daily temperature in [0.1 °C] **8\. temp\_deKooy\_1955\_2022:** This file contains the daily temperature data of the weather station "de Kooy" for years 1955 to 2022 as derived from the KNMI. Temperatures are given in 0.1 °C. STN = 235 Meteo Station = DeKooy YYYYMMDD Year - Month - Day TN Minimum daily temperature in [0.1 °C] TX Maximum daily temperature in [0.1 °C] Data was derived from the following sources: Temperature data of both stations was derived from the KNMI (https://www.knmi.nl/nederland-nu/klimatologie/daggegevens). There are 3 separate, reproducible R-scripts using the data files listed above: 1. R\_script\_Mainanalysis Code to run all selection and phenology analyses and to create all figures (except Figure S3) from the main manuscript and the electronic supplementary material 2. R\_script\_climwin\_analysis Code to run the climate window analysis with package climwin to find the respective windows in the year in which temperatures are best correlated with either laying date or food peak date for all populations 3. R\_script\_Survival\_analysis Code to run the survival analyses with RMARK (note that program MARK is additionally needed to execute the R package RMARK) and to produce Figure S3 in the supplementary material 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 predicting the impact of climate change. But are observed patterns in one population generalisable 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. Long-term data on breeding birds were collected by regular nest checks and by capturing and ringing birds. Data on caterpillar biomass was collected using frass nets. All data was stored in an relational SQL database and analysed using R. Excel & R

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.

AbstractThe ultimate reason why birds should advance their phenology in response to climate change is to match the shifting phenology of underlying levels of the food chain. In a seasonal environment, the timing of food abundance is one of the crucial factors to which birds should adapt their timing of reproduction. They can do this by shifting egg‐laying date (LD), and also by changing other life‐history characters that affect the period between laying of the eggs and hatching of the chicks. In a long‐term study of the migratory Pied Flycatcher, we show that the peak of abundance of nestling food (caterpillars) has advanced during the last two decades, and that the birds advanced their LD. LD strongly correlates with the timing of the caterpillar peak, but in years with an early food peak the birds laid their eggs late relative to this food peak. In such years, the birds advance their hatching date by incubating earlier in the clutch and reducing the interval between laying the last egg to hatching of the first egg, thereby partly compensating for their relative late LD. Paradoxically, they also laid larger clutches in the years with an early food peak, and thereby took more time to lay (i.e. one egg per day). Clutch size therefore declined more strongly with LD in years with an early food peak. This stronger response is adaptive because the fitness of an egg declined more strongly with date in early than in late years. Clearly, avian life‐history traits are correlated and Pied Flycatchers apparently optimize over the whole complex of the traits including LD, clutch size and the onset of incubation. Climate change will lead to changing selection pressures on this complex of traits and presumably the way they are correlated.

AbstractLocal biodiversity trends over time are likely to be decoupled from global trends, as local processes may compensate or counteract global change. We analyze 161 long-term biological time series (15–91 years) collected across Europe, using a comprehensive dataset comprising ~6,200 marine, freshwater and terrestrial taxa. We test whether (i) local long-term biodiversity trends are consistent among biogeoregions, realms and taxonomic groups, and (ii) changes in biodiversity correlate with regional climate and local conditions. Our results reveal that local trends of abundance, richness and diversity differ among biogeoregions, realms and taxonomic groups, demonstrating that biodiversity changes at local scale are often complex and cannot be easily generalized. However, we find increases in richness and abundance with increasing temperature and naturalness as well as a clear spatial pattern in changes in community composition (i.e. temporal taxonomic turnover) in most biogeoregions of Northern and Eastern Europe.