Articles • scari

Initialization of renv package for dependencies
Bioclim variable rasters: CHELSA
SLF occurrence records: GBIF, lydemapR, literature
Setup for global-scale MaxEnt model
Run global-scale MaxEnt model
Workflow for the functions 'compute_MaxEnt_summary_statistics()'
Setup for regional-scale MaxEnt models
Run 'Ri.NAmerica' model trained on SLF invaded region in North America
Run 'Ri.Asia' model trained on SLF invaded range in Japan and South Korea
Run 'Rn' model trained on SLF native range in east Asia
Run an Extrapolation Detection (NT2) analysis and calculate MIC
Ensemble regional-scale models using a weighted mean
Create risk maps of each model scale and intersect predictions
Plot shift in SLF risk to important viticultural regions under climate change
Infer stability of known SLF populations due climate change effects
Analyze biological realism of model response curves
Assess model goodness of fit via AUC, TSS and confusion matrices
Plot variable importance for all models
Example usage of create_risk_report(), applied to create reports for French Viticultural areas
Create risk reports for global countries and provinces
Create risk reports for the USA nationally and per state
Generate IVR/SLF risk tables and other figures
Analyses- R package scari
Create risk reports for Lycorma delicatula
Get started using scari