An adaptive model for predicting !Kung reproductive performance : a stochastic dynamic programming approach

A stochastic dynamic programming model is presented that supports and extends work on the reproductive performance of the !Kung Bushmen (Lee 1972), (Blurton Jones et al. 1978), (Blurton Jones 1986) proposing that !Kung women and their reproductive systems may be maximizing reproductive success. T...

Full description

Bibliographic Details
Main Author: Anderies, John Martin
Language:English
Published: 2009
Online Access:http://hdl.handle.net/2429/6087
id ndltd-LACETR-oai-collectionscanada.gc.ca-BVAU.2429-6087
record_format oai_dc
spelling ndltd-LACETR-oai-collectionscanada.gc.ca-BVAU.2429-60872014-03-14T15:40:59Z An adaptive model for predicting !Kung reproductive performance : a stochastic dynamic programming approach Anderies, John Martin A stochastic dynamic programming model is presented that supports and extends work on the reproductive performance of the !Kung Bushmen (Lee 1972), (Blurton Jones et al. 1978), (Blurton Jones 1986) proposing that !Kung women and their reproductive systems may be maximizing reproductive success. The stochastic dynamic programming approach allows the construction of a "whole-life" model where the physical/environmental constraints along with the uncertainty about future events !Kung women face when making reproductive choices can be explicitly built in. The model makes quantitative predictions for the optimal reproductive strategy assuming !Kung women are maximizing expected lifetime reproduction (ELR) given the physical parameters of !Kung life. The model relies on data gathered from the works cited above and some considerations from simple probability theory. The model predictions for optimal birth spacing match the !Kung reproductive data very well and support earlier findings (Blurton Jones and Sibly 1978), (Blurton Jones 1986). The utility of the dynamic modeling approach is illustrated when the effects of varying certain model parameters are investigated. By including the effect of the mother's mortality which was not included in the Blurton Jones and Sibly (1978) analysis, the model allows for further exploration of the application of an adaptive approach to human reproductive performance. By adding some considerations about the risks of childbirth for the mother the model not only predicts optimal birth spacing which is site specific but also predicts the optimal time for a woman to begin and cease having children. These predictions coincide with menarche and menopause and shed light on their possible adaptive value. 2009-03-16T21:00:14Z 2009-03-16T21:00:14Z 1996 2009-03-16T21:00:14Z 1996-11 Electronic Thesis or Dissertation http://hdl.handle.net/2429/6087 eng UBC Retrospective Theses Digitization Project [http://www.library.ubc.ca/archives/retro_theses/]
collection NDLTD
language English
sources NDLTD
description A stochastic dynamic programming model is presented that supports and extends work on the reproductive performance of the !Kung Bushmen (Lee 1972), (Blurton Jones et al. 1978), (Blurton Jones 1986) proposing that !Kung women and their reproductive systems may be maximizing reproductive success. The stochastic dynamic programming approach allows the construction of a "whole-life" model where the physical/environmental constraints along with the uncertainty about future events !Kung women face when making reproductive choices can be explicitly built in. The model makes quantitative predictions for the optimal reproductive strategy assuming !Kung women are maximizing expected lifetime reproduction (ELR) given the physical parameters of !Kung life. The model relies on data gathered from the works cited above and some considerations from simple probability theory. The model predictions for optimal birth spacing match the !Kung reproductive data very well and support earlier findings (Blurton Jones and Sibly 1978), (Blurton Jones 1986). The utility of the dynamic modeling approach is illustrated when the effects of varying certain model parameters are investigated. By including the effect of the mother's mortality which was not included in the Blurton Jones and Sibly (1978) analysis, the model allows for further exploration of the application of an adaptive approach to human reproductive performance. By adding some considerations about the risks of childbirth for the mother the model not only predicts optimal birth spacing which is site specific but also predicts the optimal time for a woman to begin and cease having children. These predictions coincide with menarche and menopause and shed light on their possible adaptive value.
author Anderies, John Martin
spellingShingle Anderies, John Martin
An adaptive model for predicting !Kung reproductive performance : a stochastic dynamic programming approach
author_facet Anderies, John Martin
author_sort Anderies, John Martin
title An adaptive model for predicting !Kung reproductive performance : a stochastic dynamic programming approach
title_short An adaptive model for predicting !Kung reproductive performance : a stochastic dynamic programming approach
title_full An adaptive model for predicting !Kung reproductive performance : a stochastic dynamic programming approach
title_fullStr An adaptive model for predicting !Kung reproductive performance : a stochastic dynamic programming approach
title_full_unstemmed An adaptive model for predicting !Kung reproductive performance : a stochastic dynamic programming approach
title_sort adaptive model for predicting !kung reproductive performance : a stochastic dynamic programming approach
publishDate 2009
url http://hdl.handle.net/2429/6087
work_keys_str_mv AT anderiesjohnmartin anadaptivemodelforpredictingkungreproductiveperformanceastochasticdynamicprogrammingapproach
AT anderiesjohnmartin adaptivemodelforpredictingkungreproductiveperformanceastochasticdynamicprogrammingapproach
_version_ 1716650794902618112