% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/climate_projection.R
\name{identify_resilient_sites}
\alias{identify_resilient_sites}
\title{Identify climate-resilient locations}
\usage{
identify_resilient_sites(projections, baseline, min_class = "Moderate")
}
\arguments{
\item{projections}{Named list returned by \code{\link[=project_suitability]{project_suitability()}}.}

\item{baseline}{Dataframe from \code{\link[=predict_oyster]{predict_oyster()}} (the baseline result).}

\item{min_class}{Character. Minimum suitability class required in all
scenarios. One of \code{"High"}, \code{"Moderate"}, \code{"Low"} (default \code{"Moderate"}).}
}
\value{
Subset of \code{baseline} for locations that meet \code{min_class} in every
scenario, with an added \code{n_scenarios_qualifying} column.
}
\description{
From a \code{\link[=project_suitability]{project_suitability()}} output, identifies locations that maintain
at least \code{min_class} suitability across all projected scenarios. These are
the most robust sites for long-term restoration or aquaculture investment.
}
\examples{
\donttest{
proj      <- project_suitability(result, tol)
resilient <- identify_resilient_sites(proj, result, min_class = "Moderate")
nrow(resilient)  # sites that stay Moderate+ even under RCP8.5
}
}
