Reproduction is adapted to survival characteristics across geographically isolated medfly populations.
We propose the hypothesis that individual longitudinal trajectories of fertility are closely coupled to varying survival schedules across geographically isolated populations of the same species, in such a way that peak reproduction takes place before substantial increases in mortality are observed. This reproductive adaptation hypothesis is investigated for medflies through a statistical analysis of biodemographic data that were obtained for female medflies from six geographically far apart regions. The following results support the hypothesis: (i) both survival and reproductive schedules differ substantially between these populations, where early peaks and subsequently fast declining reproduction are observed for short-lived and protracted reproductive schedules for long-lived flies; (ii) when statistically adjusting reproduction for the observed differences in survival, the differences in reproductive schedules largely vanish, and thus the observed differences in fertility across the populations can be explained by differences in population-specific longevity; and (iii) specific survival patterns of the medflies belonging to a specific population predict the individual reproductive schedule for the flies in this population. The analysis is based on innovative statistical tools from functional data analysis. Our findings are consistent with an adaptive mechanism whereby trajectories of fertility evolve in response to specific constraints inherent in the population survival schedules.
Department of Statistics, University of California at Davis, One Shields Avenue, Davis, CA 95616, USA. mueller@wald.ucdavis.edu
Hans-Georg
HG
Müller
Shuang
S
Wu
Alexandros D
AD
Diamantidis
Nikos T
NT
Papadopoulos
James R
JR
Carey
D000220:Adaptation, Biological / Q000502:physiology*; D000704:Analysis of Variance; D000818:Animals; D033622:Ceratitis capitata / Q000502:physiology*; D005260:Female; D005298:Fertility / Q000502:physiology; D005843:Geography; D016014:Linear Models; D008136:Longevity / Q000502:physiology*; D008954:Models, Biological; D009026:Mortality; D025341:Principal Component Analysis