DynaMETE iterative simulation

Knowledge graph centered on DynaMETE iterative simulation with 58 nodes and 113 connections. Top connected: Lepidoptera, small mammals, species diversity, Rocky Mountain Biological Laboratory, space use.

Method synopsis

Iterative numerical procedure for solving dynamic macroecological theory equations by cycling through MaxEnt structure function calculation, state variable updates, and Lagrange multiplier optimization. Simulates ecosystem responses to disturbance over time.

Synthesized from method descriptions across 1 paper using this protocol.

Procedure as described in the canonical source

Steps below were extracted from the paper that introduces this protocol — DynaMETE: a hybrid MaxEnt-plus-mechanism theory of dynamic macroecology (2021), Ecology Letters. Implementations in other papers (listed below) may differ.

1. Initialize system at steady state
   Set initial state variables S, N, E to steady-state values derived from static METE theory. Calculate initial Lagrange multipliers λ1, λ2, λ5 from constraints imposed by static state variables using equations 3-6.
   Quantities: State variables: S=320 species, N=230,000 individuals, E=2.04×10^7 metabolic rate unitsDuration: Initial time step onlyConditions: Steady-state ecosystem before perturbation
   Equipment: computational framework
2. Impose perturbation
   Change one or more rate parameters in transition functions at time t=0. Examples include reducing immigration rate m0 from 500 to 0, increasing death rate d0 from 0.2 to 0.25, or reducing ontogenic growth rate w0 from 1.0 to 0.95.
   Quantities: Parameter changes: m0: 500→0, d0: 0.2→0.25, w0: 1.0→0.95, μ: 0.0219→0.024Duration: Instantaneous at t=0Conditions: Represents disturbance event
   Equipment: computational framework
3. Calculate structure function
   Use MaxEnt with constraints from current state variable values S, N, E and their time derivatives to determine structure function R(n,ε,{Xi},{ci}) using equation 19. Calculate Lagrange multipliers λ1-λ5 from constraint equations 14-18.
   Quantities: 5 Lagrange multipliers calculated iteratively

Typical Equipment

• computational framework
• MaxEnt optimization algorithms

Output Measurements

• state variable trajectories
• species abundance distributions
• metabolic rate distributions
• macroecological metrics

Papers Using This Protocol (1)

Species Studied With This Protocol

Places Where Used