STOCHASTIC VARIABILITY AND HUMAN POPULATION REGULATION

这个项目旨在开发一种新的模型，用于研究 明确认识到不同水平的人口 随机影响影响并应用这些新模型来理解 调节人口数量和增长的长期过程以及 抵消累积的随机性。新车型将进行合并和改进 现有的“人口”和“环境”统计模型 随机性。估计中的参数需要长期数据 随机动态平衡模型。对于这个项目，长长的一系列教区 瑞格利和斯科菲尔德1811年前英格兰的人口统计(1981) 将为模型的参数估计和研究提供数据集 人口比率的协变模式。然后，模特们将被 应用于评价动态平衡趋势强度的问题 要求在人类史前时期保持较低的平均增长率，以及 将现有的人口调控理论与 生物学中“自由种群调控”的新理论。该项目 应该为理解长期动态提供更好的基础 有限的人口增长。

This project aims to develop new models for randomness in the size of a human population which explicitly recognize different levels at which random influences impinge and to apply these new models to an understanding of the long-term processes which regulate population size and growth and counteract cumulating randomness. The new models will combine and refine existing statistical models for "demographic" and "environmental" randomness. Long-term data are required to estimate parameters in stochastic homeostatic models. For this project, the long series of parish demographic counts for England before 1811 of Wrigley and Schofield (1981) will provide a data set for estimating parameters of the model and studying patterns of covariation of demographic rates. The models will then be applied to the problem of evaluating the strength of homeostatic tendencies required to have maintained low average growth over human prehistory, and to a comparison of existing theories of human population regulation with new theories of "liberal population regulation" in biology. The project should provide a better basis for understanding the long-term dynamics of limited population growth.