AIC model selection (Plantae)

Knowledge graph centered on AIC model selection (Plantae) with 52 nodes and 150 connections. Top connected: Ipomopsis, I. aggregata, Ipomopsis aggregata, Spruce, Asteraceae.

Method synopsis

Multiple candidate models incorporating different combinations of climate predictors were fitted and ranked using Akaike Information Criterion to select optimal models for demographic functions.

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 — Spatial patterns and climate relationships of major plant traits in the New World differ between woody and herbaceous species (2018), Journal of Biogeography. Implementations in other papers (listed below) may differ.

1. Statistical model selection and analysis
   Model selection was performed using AIC weight according to Akaike information criteria. Trait-climate relationships were examined using all six climate variables in linear and quadratic form (12 explanatory variables total). Model complexity was limited to maximum of six terms in model output. Separate analyses were performed for woody and herbaceous species, followed by combined analyses testing for growth form interactions using standardized variables.
   Quantities: Maximum 6 terms per model, 12 total explanatory variables (6 linear + 6 quadratic climate terms)Duration: Not specifiedConditions: Statistical modeling with complexity constraints
   Equipment: AIC model selection, R 'MuMIn' package, Lasso model selection

Typical Equipment

• Statistical modeling software

Output Measurements

• AIC values
• degrees of freedom
• ΔAIC

Papers Using This Protocol (2)

Species Studied With This Protocol