CONSURE: CONSURE: Spatially continuous survival, use of space and...

In SaskiaSchirmer/CONSURE: Estimating Spatially Continuous Survival, Migratory Connectivity and Recovery Probability

CONSURE: Spatially continuous survival, use of space and recovery probability estimates

Description

The CONSURE package provides functions to perform the continuous and the combined approach from the dissertation of Saskia Schirmer. It can work with both, simulated and real-world data.

Details

Nearly all functions are based on a mark_recapture_object.

A spatial point pattern can be simulated by given survival, migratory connectivity and recovery probability using sim_contin.

Visualizing raw data

Spatial point patterns of raw recoveries can be visualized by plot_raw_recoveries. The age distribution can be visualized by plot_age_distribution.

Continuous functions

The continuous estimation approach first estimates the density of the point pattern by est_kde. Then, survival can be estimated by est_s and finally migratory connectivity by est_m and a constant recovery probability by est_r. The function est_parameters is a wrapper-function performing kernel density estimation and parameter estimation at once.

All estimates can be plotted by the appropriate function: plot_kde, plot_s, plot_m. The R^2 values of the linear model used to fit survival, migratory connectivity and recovery probability can be plotted by plot_gof_of_lm.

The number of recovered individuals per area of origin can be summarized by rec_inds_func.

par_grid creates a grid containing the values of a specific function on the grid.

Uncertainty estimation

The uncertainty of the parameter estimates can be assessed by bootstrapping with the function est_uncertainty. Optionally, data can be bootstrapped before starting the estimation process using the function init_bootstrapped_datasets. bootstrap_quantiles calculates the 0.025- and 0.975-bootstrap quantiles. These quantiles can be visualized in 3D with plotly_param or alternatively, as a 2D surface with a bootstrap quantile along a profile line with plot_profile.

The following functions are used by the functions above: bootstrap_marking_data performs the actual bootstrapping of the marking data. get_bootstrap_parameters extracs the parameters of the bootstrapped data sets from the mark_recapture_object as a data frame.

The profile line is created using profile_of_parameter, raster_param, wrap_profile_of_param, profile_line and profile_points.

CONSURE needs projected data for some functions. Therefore, the data will be projected from longitude/latitude (EPSG:4326) to Mollweide projection (ESRI:54009), unless other projections are specified. project_mark_recapture, project_df , project_window perform the projection.

SaskiaSchirmer/CONSURE documentation built on Sept. 3, 2023, 8:52 a.m.