A quantitative framework for ovarian dynamics
Résumé
The ovarian processes of many species are highly dynamic, responding to both individual physiological factors, such as energetic reserves or mating status, and environmental factors, such as resource availability and quality or temperature (Wheeler 1996; Papaj 2000; Nager 2006; Krysko et al. 2008; Vezina & Salvante 2010). At the individual level, ovarian production is regulated by the balance of two processes: oogenesis, resulting in the production of eggs that can be fertilized or laid, and oosorption (or egg resorption or egg atresia), during which eggs are destroyed and their nutrient content may be partially recovered. Throughout oogenesis, an egg goes through different stages as it undergoes different physiological processes (e.g. vitellogenesis and choriogenesis). The current state of an egg not only determines which state it will be in the near future, but it also determines an egg's sensitivity to endogenous and exogenous factors (e.g. apoptosis and endocrine factors; Terashima & Bownes 2004; Thomson, Fitzpatrick & Johnson 2010). Thus, when many eggs undergo oogenesis at the same time, the patterns of ovarian production over time not only depend on the conditions experienced by the female, but also on how eggs are distributed among states (Telfer, Gosden & Faddy 1991; Faddy & Gosden 1995; Faddy 2000). This essentially makes it a problem of structured population dynamics; therefore, any quantitative inference aiming to link conditions experienced, ovarian state and reproductive output must account for the multivariate nature of ovarian state. Most of the discussion that follows primarily focuses on the significance of these processes in insect species, but applicability of the approach is much broader and includes any species producing eggs in a dynamic fashion, including plants. The high degree of flexibility in insect egg production has largely been interpreted as an evolutionary response to the selective pressures acting on oviposition behaviour