S. D. Tuljapurkar

Density dependence shapes life-history trade-offs in a food limited ungulate population

This study shows density dependence shapes life-history trade-offs and reproductive success distribution in Soay sheep populations.

Transient dynamics and nonlinear fitness: a unified matrix approach to press and pulse perturbation

The paper develops a unified matrix framework to analyze both pulse and press disturbances in populations, showing how transient dynamics influence long-term fitness and demographic responses.

Structured demographic buffering: A framework to explore the environment drivers and demographic mechanisms underlying demographic buffering

The paper introduces a framework to quantify the effects of environmental factors, population structure, and demographic rates on demographic buffering in plant species.

Sensitivity and uncertainty in the Lee-Carter mortality model

This study analyzes the robustness of the Lee-Carter mortality model by examining sensitivity and uncertainty, finding it resilient to random perturbations and short-term changes.

Adaptive and neutral processes that select on life course diversification

The paper analyzes structured population models across taxa to explore how selective forces act on non-genetic, non-environmental life course variation, finding it is neither clearly neutral nor selected for or against.

Density dependent environments can select for extremes of body size

The paper develops size-structured models to explore how density dependence influences body size evolution, showing that gigantism or dwarfism depends on population maturity proportions and developmental trajectories.

Life-history dynamics: damping time, demographic dispersion and generation time

The paper analyzes damping time across 600+ species and finds it scales with generation time, independent of demographic dispersion, suggesting slow life-history species are more vulnerable to disturbances.

Distributions of LRS in varying environments

The paper examines how lifetime reproductive success (LRS) distributions vary in different environments using Roe deer data and stochastic models.