Drivers of resource allocation for breeding under variable environments in a bet hedger - Daniel Oro; Cassidy Waldrep; Albert Bertolero; Meritxell Genovart (Ecology and Evolution, 2023)
Abstract The evolutionary theory of life histories predicts that there is a trade‐off between survival and reproduction: since adult survival in long‐lived organisms is high, then breeding investment is more variable and more dependent on conditions (e.g. food availability and individual experience). Clutch features influence fitness prospects, but how a bet hedger builds its clutch in temporally varying environments is quite unknown. Using 27‐year data on 2847 clutches of known‐age breeders, we analyse how Audouin's gulls (Larus audouinii), a species showing a combination of conservative and adaptive bet‐hedging breeding strategies, can allocate energy by laying clutches and eggs of different sizes. Results show that both food availability and age influenced clutch size and total egg volume in a clutch. Interestingly, we found an interaction between food and age on egg parameters: total volume in two‐egg clutches, laid mostly by younger breeders, did not significantly change with food availability and the quadratic pattern in clutch size over the range of ages was less marked as long as food conditions became harsher. With increased food, females invested more by building larger first eggs, whereas they were more conservative on second and third eggs. Furthermore, asymmetries in egg volume within three‐egg clutches increased with food availability for old females. Egg size profiles of two‐egg clutches suggest that gulls should exhibit progressive reduction of the size of the third egg before shifting to a two‐egg clutch size. Food availability influenced all parameters studied, whereas age affected the amount of energy allocated for producing eggs (their size and number) but not the way of allocating those energies (i.e. asymmetries within the clutch). Despite the range of factors affecting the clutch, results suggest that females can allocate the amount of resources in a clutch optimally to increase their fitness under variable environments via bet‐hedging.