Fertility Tradeoffs (1.1.0)

Fertility Tradeoffs is an agent-based model that examines how parental investment strategies evolve under density-dependent conditions. Humans occupy territories that compete for limited space, and reproduction requires both resources and available territory. Individuals inherit investment strategies that determine how much time and resources are required to raise a child, creating a tradeoff between number of children and investment per child. As space fills, territory costs increase and population growth slows, producing logistic-like dynamics. By manipulating child mortality and resource availability, the model demonstrates how environmental conditions shape both population outcomes and the evolution of reproductive strategies.

Release Notes

Fertility Tradeoffs — Version 1.1.0

Overview

This update improves model structure, performance, and clarity while aligning terminology with parental investment theory and spatial resource competition.

New Features

• Replaced households with Territories to better represent spatial competition.
• Investment trait renamed and clarified (formerly “education”).
• Improved initialization: fewer starting Territories with paired adults and sufficient space.
• Added per-capita growth rate calculation.
• Added new plots:
• Population Structure (adults vs. children)
• Distribution of Investment Alleles

Interface Updates

• Reorganized plots to reflect causal structure:
• Spatial Resource Competition
• Density-Dependent Growth
• Population Structure
• Reproduction and Investment
• Strategy Distribution
• Updated terminology:
• Education → Investment
• Households → Territories
• Funds → Resources

Performance Improvements

• Eliminated repeated global scans of agents.
• Territories now store members and owned patches.
• Reduced computational complexity and improved runtime.

Model Logic Improvements

• Reproduction requires:
• Two adults
• No current child
• Available space
• Territory expansion occurs when space is needed for a mate or child.
• Child development depends on reaching inherited investment level.
• Mutation implemented as small proportional changes (±5%).

Bug Fixes

• Fixed multiple context (self vs. myself) errors.
• Corrected patch vs. agent reference issues.
• Prevented reproduction without available space.
• Resolved early simulation slowdown.

Summary

Version 1.1.0 improves performance, consistency, and interpretability while more clearly demonstrating density-dependent growth and the evolution of reproductive strategies.

Associated Publications