Ambystoma population dynamics differential equation modeling

Knowledge graph centered on Ambystoma population dynamics differential equation modeling with 21 nodes and 70 connections. Top connected: Ambystoma mavortium, Zooplankton, Mexican Cut Nature Preserve, Odonata, Ambystoma macrodactylum.

Method synopsis

Development and analysis of a seven-dimensional nonlinear differential equation system modeling tiger salamander population dynamics across life stages and morphological forms. The model incorporates phenotypic plasticity through a morphological choice parameter controlling metamorphosis rates.

Synthesized from method descriptions across 2 papers using this protocol.

Procedure from a recent peer-reviewed implementation

Steps below were extracted from the most recent peer-reviewed implementation of this protocol in the corpus — Modeling the population dynamics and community impacts of <i>Ambystoma tigrinum</i>: A case study of phenotype plasticity (2017), Mathematical Biosciences. The protocol was originally introduced by A model of inter-cohort cannibalism and paedomorphosis in Arizona tiger salamanders, <i>Ambystoma tigrinum nebulosum</i> (2016), International Journal of Biomathematics. Implementations in other papers (listed below) may differ.

1. Develop mathematical model structure
   Constructed a seven-dimensional nonlinear system of ordinary differential equations with compartments for small invertebrates (Z), large invertebrates (B), young of year Ambystoma (Y), juvenile Ambystoma (J), terrestrial metamorphs (A), and aquatic paedomorphs (P). Incorporated birth, maturation, predation, and death processes with specific functional forms including Type 2 functional response for predation and logistic growth terms.
   Quantities: Seven differential equations with approximately 25 parameters totalDuration: Not specifiedConditions: Mathematical modeling environment
   Equipment: Mathematical formulation
2. Conduct sensitivity analysis
   Varied each parameter from its default level by ±10% and recorded biomass values at equilibrium. Tested three different values of the morphological choice parameter (qj = 0.1, 0.5, 0.9) representing different percentages of juveniles maturing into metamorphs versus paedomorphs.
   Quantities: Three qj values tested (0.1, 0.5, 0.9), ±10% parameter variationsDuration: Not specifiedConditions: Computational simulation environment
   Equipment: Matlab software

Typical Equipment

• Matlab software

Output Measurements

• biomass trajectories
• equilibrium population compositions
• trophic level dynamics

Papers Using This Protocol (2)

Species Studied With This Protocol

Places Where Used