Phenological mismatch strongly affects individual fitness but not population demography in a woodland passerine

Author Posting. © The Authors, 2012. The definitive version was published in Journal of Animal Ecology 82 (2013): 131-144, doi:10.1111/j.1365-2656.2012.02020.x.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, i.e. 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-44 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

Phenological indices of avian reproduction: cryptic shifts and prediction across large spatial and temporal scales

Climate change-induced shifts in phenology have important demographic consequences, and are frequently used to assess species’ sensitivity to climate change. Therefore, developing accurate phenological predictions is an important step in modeling species’ responses to climate change. The ability of such phenological models to predict effects at larger spatial and temporal scales has rarely been assessed. It is also not clear whether the most frequently used phenological index, namely the average date of a phenological event across a population, adequately captures phenological shifts in the distribution of events across the season. We use the long-tailed tit Aegithalos caudatus (Fig. 1) as a case study to explore these issues. We use an intensive 17-year local study to model mean breeding date and test the capacity of this local model to predict phenology at larger spatial and temporal scales. We assess whether local models of breeding initiation, termination, and renesting reveal phenological shifts and responses to climate not detected by a standard phenological index, that is, population average lay date. These models take predation timing/intensity into account. The locally-derived model performs well at predicting phenology at the national scale over several decades, at both high and low temperatures. In the local model, a trend toward warmer Aprils is associated with a significant advance in termination dates, probably in response to phenological shifts in food supply. This results in a 33% reduction in breeding season length over 17 years – a substantial loss of reproductive opportunity that is not detected by the index of population average lay date. We show that standard phenological indices can fail to detect patterns indicative of negative climatic effects, potentially biasing assessments of species’ vulnerability to climate change. More positively, we demonstrate the potential of detailed local studies for developing broader-scale predictive models of future phenological shifts

Food web de-synchronization in England's largest lake: an assessment based on multiple phenological metrics

Phenological changes have been observed globally for marine, freshwater and terrestrial species, and are an important element of the global biological ‘fingerprint’ of climate change. Differences in rates of change could desynchronize seasonal species interactions within a food web, threatening ecosystem functioning. Quantification of this risk is hampered by the rarity of long-term data for multiple interacting species from the same ecosystem and by the diversity of possible phenological metrics, which vary in their ecological relevance to food web interactions. We compare phenological change for phytoplankton (chlorophyll a), zooplankton (Daphnia) and fish (perch, Perca fluviatilis) in two basins of Windermere over 40 years and determine whether change has differed among trophic levels, while explicitly accounting for among-metric differences in rates of change. Though rates of change differed markedly among the nine metrics used, seasonal events shifted earlier for all metrics and trophic levels: zooplankton advanced most, and fish least, rapidly. Evidence of altered synchrony was found in both lake basins, when combining information from all phenological metrics. However, comparisons based on single metrics did not consistently detect this signal. A multimetric approach showed that across trophic levels, earlier phenological events have been associated with increasing water temperature. However, for phytoplankton and zooplankton, phenological change was also associated with changes in resource availability. Lower silicate, and higher phosphorus, concentrations were associated with earlier phytoplankton growth, and earlier phytoplankton growth was associated with earlier zooplankton growth. The developing trophic mismatch detected between the dominant fish species in Windermere and important zooplankton food resources may ultimately affect fish survival and portend significant impacts upon ecosystem functioning.We advocate that future studies on phenological synchrony combine data from multiple phenological metrics, to increase confidence in assessments of change and likely ecological consequences

Climate change, phenological shifts, eco-evolutionary responses and population viability: toward a unifying predictive approach

The debate on emission targets of greenhouse gasses designed to limit global climate change has to take into account the ecological consequences. One of the clearest ecological consequences is shifts in phenology. Linking these shifts to changes in population viability under various greenhouse gasses emission scenarios requires a unifying framework. We propose a box-in-a-box modeling approach that couples population models to phenological change. This approach unifies population modeling with both ecological responses to climate change as well as evolutionary processes. We advocate a mechanistic embedded correlative approach, where the link from genes to population is established using a periodic matrix population model. This periodic model has several major advantages: (1) it can include complex seasonal behaviors allowing an easy link with phenological shifts; (2) it provides the structure of the population at each phase, including the distribution of genotypes and phenotypes, allowing a link with evolutionary processes; and (3) it can incorporate the effect of climate at different time periods. We believe that the way climatologists have approached the problem, using atmosphere–ocean coupled circulation models in which components are gradually included and linked to each other, can provide a valuable example to ecologists. We hope that ecologists will take up this challenge and that our preliminary modeling framework will stimulate research toward a unifying predictive model of the ecological consequences of climate change

Temporal shifts and temperature sensitivity of avian spring migratory phenology:A phylogenetic meta-analysis

There are wide reports of advances in the timing of spring migration of birds over time and in relation to rising temperatures, though phenological responses vary substantially within and among species. An understanding of the ecological, life-history and geographic variables that predict this intra- and interspecific variation can guide our projections of how populations and species are likely to respond to future climate change. Here, we conduct phylogenetic meta-analyses addressing slope estimates of the timing of avian spring migration regressed on (i) year and (ii) temperature, representing a total of 413 species across five continents. We take into account slope estimation error and examine phylogenetic, ecological and geographic predictors of intra- and interspecific variation. We confirm earlier findings that on average birds have significantly advanced their spring migration time by 2·1 days per decade and 1·2 days °C−1. We find that over time and in response to warmer spring conditions, short-distance migrants have advanced spring migratory phenology by more than long-distance migrants. We also find that larger bodied species show greater advance over time compared to smaller bodied species. Our results did not reveal any evidence that interspecific variation in migration response is predictable on the basis of species' habitat or diet. We detected a substantial phylogenetic signal in migration time in response to both year and temperature, suggesting that some of the shifts in migratory phenological response to climate are predictable on the basis of phylogeny. However, we estimate high levels of species and spatial variance relative to phylogenetic variance, which is consistent with plasticity in response to climate evolving fairly rapidly and being more influenced by adaptation to current local climate than by common descent. On average, avian spring migration times have advanced over time and as spring has become warmer. While we are able to identify predictors that explain some of the true among-species variation in response, substantial intra- and interspecific variation in migratory response remains to be explained

Spatiotemporal Variation in Avian Migration Phenology: Citizen Science Reveals Effects of Climate Change

A growing number of studies have documented shifts in avian migratory phenology in response to climate change, and yet there is a large amount of unexplained variation in the magnitude of those responses across species and geographic regions. We use a database of citizen science bird observations to explore spatiotemporal variation in mean arrival dates across an unprecedented geographic extent for 18 common species in North America over the past decade, relating arrival dates to mean minimum spring temperature. Across all species and geographic locations, species shifted arrival dates 0.8 days earlier for every °C of warming of spring temperature, but it was common for some species in some locations to shift as much as 3–6 days earlier per °C. Species that advanced arrival dates the earliest in response to warming were those that migrate more slowly, short distance migrants, and species with broader climatic niches. These three variables explained 63% of the interspecific variation in phenological response. We also identify a latitudinal gradient in the average strength of phenological response, with species shifting arrival earlier at southern latitudes than northern latitudes for the same degree of warming. This observation is consistent with the idea that species must be more phenologically sensitive in less seasonal environments to maintain the same degree of precision in phenological timing

Potential responses to climate change in organisms with complex life histories: evolution and plasticity in Pacific salmon

Salmon life histories are finely tuned to local environmental conditions, which are intimately linked to climate. We summarize the likely impacts of climate change on the physical environment of salmon in the Pacific Northwest and discuss the potential evolutionary consequences of these changes, with particular reference to Columbia River Basin spring/summer Chinook (Oncorhynchus tshawytscha) and sockeye (Oncorhynchus nerka) salmon. We discuss the possible evolutionary responses in migration and spawning date egg and juvenile growth and development rates, thermal tolerance, and disease resistance. We know little about ocean migration pathways, so cannot confidently suggest the potential changes in this life stage. Climate change might produce conflicting selection pressures in different life stages, which will interact with plastic (i.e. nongenetic) changes in various ways. To clarify these interactions, we present a conceptual model of how changing environmental conditions shift phenotypic optima and, through plastic responses, phenotype distributions, affecting the force of selection. Our predictions are tentative because we lack data on the strength of selection, heritability, and ecological and genetic linkages among many of the traits discussed here. Despite the challenges involved in experimental manipulation of species with complex life histories, such research is essential for full appreciation of the biological effects of climate change

Regression with Empirical Variable Selection: Description of a New Method and Application to Ecological Datasets

Despite recent papers on problems associated with full-model and stepwise regression, their use is still common throughout ecological and environmental disciplines. Alternative approaches, including generating multiple models and comparing them post-hoc using techniques such as Akaike's Information Criterion (AIC), are becoming more popular. However, these are problematic when there are numerous independent variables and interpretation is often difficult when competing models contain many different variables and combinations of variables. Here, we detail a new approach, REVS (Regression with Empirical Variable Selection), which uses all-subsets regression to quantify empirical support for every independent variable. A series of models is created; the first containing the variable with most empirical support, the second containing the first variable and the next most-supported, and so on. The comparatively small number of resultant models (n = the number of predictor variables) means that post-hoc comparison is comparatively quick and easy. When tested on a real dataset – habitat and offspring quality in the great tit (Parus major) – the optimal REVS model explained more variance (higher R2), was more parsimonious (lower AIC), and had greater significance (lower P values), than full, stepwise or all-subsets models; it also had higher predictive accuracy based on split-sample validation. Testing REVS on ten further datasets suggested that this is typical, with R2 values being higher than full or stepwise models (mean improvement = 31% and 7%, respectively). Results are ecologically intuitive as even when there are several competing models, they share a set of “core” variables and differ only in presence/absence of one or two additional variables. We conclude that REVS is useful for analysing complex datasets, including those in ecology and environmental disciplines