Related Experiment Video
Updated: Jan 5, 2026

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Published on: July 4, 2007
False Exclusion: A Case to Embed Predator Performance in Classical Population Models
Abstract:
We argue that predator-prey dynamics, a cornerstone of ecology, can be driven by insufficiently explored aspects of predator performance that are inherently prey dependent: that is, these have been falsely excluded. Classical (Lotka-Volterra-based) models tend to consider only prey-dependent ingestion rate. We highlight three other prey-dependent responses and provide empirically derived functions to describe them. These functions introduce neglected nonlinearities and threshold behaviors into dynamic models, leading to unexpected outcomes: specifically, as prey abundance increases predators (1) become less efficient at using prey; (2) initially allocate resources toward survival and then allocate resources toward reproduction; and (3) are less likely to die. Based on experiments using model zooplankton, we explore the consequences of including these functions in the classical structure and show that they alter qualitative and quantitative dynamics of an empirically informed generic predator-prey model. Through bifurcation analysis, our revised structure predicts (1) predator extinctions, where the classical structure allows persistence; (2) predator survival, where the classical structure drives predators toward extinction; and (3) greater stability through smaller amplitude of cycles, relative to the classical structure. Then, by exploring parameter space, we show how these responses alter predictions of predator-prey stability and competition between predators. In light of our results, we suggest that classical assumptions about predator responses to prey abundance should be reevaluated.
Related Concept Videos
Population Growth
Predator-Prey Interactions
What are Populations and Communities?
Optimal Foraging
Conservation of Declining Populations
Conservation of Small Populations

