reconstruct_env {commecometrics} | R Documentation |
Reconstruct past environmental conditions using ecometric models
Description
Uses fossil community trait summaries to reconstruct past environmental conditions by projecting them onto a binned ecometric trait space built from modern data. Optionally, it also assigns each fossil point to the nearest modern sampling site to retrieve observed environmental data.
Usage
reconstruct_env(
fossildata,
model_out,
inv_transform = NULL,
ci = 0.05,
match_nearest = TRUE,
fossil_lon = NULL,
fossil_lat = NULL,
modern_id = NULL,
modern_lon = NULL,
modern_lat = NULL,
crs_proj = 4326
)
Arguments
fossildata |
A data frame containing fossil trait summaries per fossil site.
Must include columns corresponding to the same two summary metrics used for modern communities,
using the column names specified by |
model_out |
Output list from |
inv_transform |
A function to back-transform environmental estimates to the original scale.
Default is |
ci |
The width of the interval to calculate around the maximum likelihood estimate (default = 0.05). |
match_nearest |
Logical; if TRUE, the function matches each fossil to its nearest modern point based on coordinates (default = TRUE). |
fossil_lon |
Name of the longitude column in |
fossil_lat |
Name of the latitude column in |
modern_id |
Name of the unique ID column in modern points (e.g., "GlobalID"). |
modern_lon |
Name of the longitude column in modern points. Required if |
modern_lat |
Name of the latitude column in modern points. Required if |
crs_proj |
Coordinate reference system to use when converting fossil and modern data to sf format (default = EPSG:4326). |
Value
A data frame (fossildata
) with reconstructed environmental values and optional nearest modern point data. Includes the following additional columns:
- fossil_bin_1
Assigned bin number for the first trait axis (based on first summary metric of trait distribution of fossil communities).
- fossil_bin_2
Assigned bin number for the second trait axis (based on second summary metric of trait distribution of fossil communities).
- fossil_env_est
Maximum likelihood estimate of the environmental variable (on transformed scale if applicable).
- fossil_minlimit
Lower bound of the confidence interval around the environmental estimate (transformed scale).
- fossil_maxlimit
Upper bound of the confidence interval around the environmental estimate (transformed scale).
- fossil_env_est_UN
(Optional) Inverse-transformed environmental estimate, on the original scale.
- fossil_minlimit_UN
(Optional) Inverse-transformed lower bound of the confidence interval.
- fossil_maxlimit_UN
(Optional) Inverse-transformed upper bound of the confidence interval.
- nearest_modern_point
(Optional) ID of the nearest modern sampling point (if
match_nearest = TRUE
).- ...
Additional columns from the matched modern site if
match_nearest = TRUE
(e.g., observed environmental values).
Examples
# Load internal data
data("geoPoints", package = "commecometrics")
data("traits", package = "commecometrics")
data("spRanges", package = "commecometrics")
data("fossils", package = "commecometrics")
# Step 1: Summarize modern trait values at sampling points
traitsByPoint <- summarize_traits_by_point(
points_df = geoPoints,
trait_df = traits,
species_polygons = spRanges,
trait_column = "RBL",
species_name_col = "sci_name",
continent = FALSE,
parallel = FALSE
)
# Step 2: Run an ecometric model with BIO12 (precipitation)
ecoModel <- ecometric_model(
points_df = traitsByPoint$points,
env_var = "precip",
transform_fun = function(x) log(x + 1),
inv_transform_fun = function(x) exp(x) - 1,
min_species = 3
)
# Step 3: Reconstruct fossil environments
recon <- reconstruct_env(
fossildata = fossils,
model_out = ecoModel,
match_nearest = TRUE,
fossil_lon = "Long",
fossil_lat = "Lat",
modern_id = "ID",
modern_lon = "Longitude",
modern_lat = "Latitude"
)