Evaluation of mortality trajectories in evolutionary biodemography
Author(s) -
Stephan B. Munch,
Marc Mangel
Publication year - 2006
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.0601735103
Subject(s) - juvenile , natural selection , biology , organism , life history , reproduction , life history theory , schedule , mortality rate , demography , reproductive value , outcome (game theory) , adaptation (eye) , trajectory , evolutionary biology , selection (genetic algorithm) , ecology , computer science , mathematics , genetics , artificial intelligence , pregnancy , mathematical economics , neuroscience , sociology , offspring , operating system , physics , astronomy
An important task in evolutionary biodemography is to determine the schedule of survival and reproduction as the outcome of natural selection acting on life histories. We do this by using a model in which the state of the organism is characterized by mass and accumulated damage, both of which are affected by activity and which affect the rate of mortality. Focusing on growth during the juvenile period, we determine the level of activity that maximizes reproductive value. Given this, we are able to project forward and determine the trajectory of mortality for an individual following the optimal life history, given the physiological and reproductive parameters. We show that there are two main classes of juvenile mortality trajectories: U-shaped (such as recently reported for prereproductive humans) and steadily declining and we are able to connect the shape of the mortality trajectory with the physiological and reproductive parameters characterizing the life history. Our work shows the importance of state in models of evolutionary biodemography and the power of modern computational methods to illuminate biological process.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom