Predicting bird phenology from space: satellite-derived vegetation green-up signal uncovers spatial variation in...

Population-level studies of how tit species (Parus spp.) track the changing phenology of their caterpillar food source have provided a model system allowing inference into how populations can adjust to changing climates, but are often limited because they implicitly assume all individuals experience similar environments. Ecologists are increasingly using satellite-derived data to quantify aspects of animals' environments, but so far studies examining phenology have generally done so at large spatial scales. Considering the scale at which individuals experience their environment is likely to be key if we are to understand the ecological and evolutionary processes acting on reproductive phenology within populations. Here, we use time series of satellite images, with a resolution of 240 m, to quantify spatial variation in vegetation green-up for a 385-ha mixed-deciduous woodland. Using data spanning 13 years, we demonstrate that annual population-level measures of the timing of peak abundance of winter moth larvae (Operophtera brumata) and the timing of egg laying in great tits (Parus major) and blue tits (Cyanistes caeruleus) is related to satellite-derived spring vegetation phenology. We go on to show that timing of local vegetation green-up significantly explained individual differences in tit reproductive phenology within the population, and that the degree of synchrony between bird and vegetation phenology showed marked spatial variation across the woodland. Areas of high oak tree (Quercus robur) and hazel (Corylus avellana) density showed the strongest match between remote-sensed vegetation phenology and reproductive phenology in both species. Marked within-population variation in the extent to which phenology of different trophic levels match suggests that more attention should be given to small-scale processes when exploring the causes and consequences of phenological matching. We discuss how use of remotely sensed data to study within-population variation could broaden the scale and scope of studies exploring phenological synchrony between organisms and their environment.