Demographic profiles and environmental drivers of variation relate to individual breeding state in a long-lived trans-oceanic migratory seabird, the Manx shearwater

Abstract

Understanding the points in a species breeding cycle when they are most vulnerable to environmental fluctuations is key to understanding interannual demography and guiding effective conservation and management. Seabirds represent one of the most threatened groups of birds in the world, and climate change and severe weather is a prominent and increasing threat to this group. We used a multi-state capture-recapture model to examine how the demographic rates of a long-lived trans-oceanic migrant seabird, the Manx shearwater Puffinus puffinus, are influenced by environmental conditions experienced at different stages of the annual breeding cycle and whether these relationships vary with an individual’s breeding state in the previous year (i.e., successful breeder, failed breeder and non-breeder). Our results imply that populations of Manx shearwaters are comprised of individuals with different demographic profiles, whereby more successful reproduction is associated with higher rates of survival and breeding propensity. However, we found that all birds experienced the same negative relationship between rates of survival and wind force during the breeding season, indicating a cost of reproduction (or central place constraint for non-breeders) during years with severe weather conditions. We also found that environmental effects differentially influence the breeding propensity of individuals in different breeding states. This suggests individual spatio-temporal variation in habitat use during the annual cycle, such that climate change could alter the frequency that individuals with different demographic profiles breed thereby driving a complex and less predictable population response. More broadly, our study highlights the importance of considering individual-level factors when examining population demography and predicting how species may respond to climate change.

Impact assessments of wind farms on seabird populations that overlook existing drivers of demographic change should be treated with caution

“…Models 4 and 5 followed the same structure as Model 2 (i.e., environmentally stochastic with stable fecundity) and Model 3 (i.e., environmentally stochastic with trended fecundity), respectively, with an additional 1% annual mortality applied to each age class (Table 1; Models 4 and 5). Extrinsic factors can differentially influence groups of individuals within populations of seabirds (e.g., Wood et al, 2021), however age‐specific impacts to seabird populations from wind energy developments are unknown and therefore we assumed a constant level across age classes. The trended values of fecundity assumed a continued constant rate of decline to that applied in Model 3 (Figure 1b).…”

Relative brain size is associated with natal dispersal rate and species' vulnerability to climate change in seabirds

“…Pelecanoididae ) mean relative brain sizes and further investigations would benefit from obtaining dispersal rate estimates in these species. Additionally, extrinsic factors can differentially influence groups of individuals within populations of seabirds (Wood et al 2021) and evidence of sex‐biased dispersal in seabirds (Hall et al 2009) suggests future analyses may also benefit from considering sex‐specific relationships between dispersal rates and brain size.…”

Interpopulation differences and temporal synchrony in rates of adult survival between two seabird colonies that differ in population size and distance to foraging grounds

“…To standardise the Leslie matrix models, we assigned an identical constant rate of fecundity ( f = 0.64, Wood et al, 2021) and breeding propensity ( b = 0.87, Wood et al, 2021) to both colonies. These values reflect the demographic profile of Manx shearwaters breeding on Skomer Island that exhibit elevated rates of fecundity and breeding propensity (Wood et al, 2021). Like many seabirds, Manx shearwaters are largely unobservable during the first years of life and estimates of juvenile survival (i.e., during the first year post fledging $$$ {\phi}_{j,t} $$$) are lacking (Horswill & Robinson, 2015).…”