https://github.com/bmaitner/s4dm

An R package focused on Species Distribution Modelling techniques for species with small sample sizes

https://github.com/bmaitner/s4dm

Science Score: 36.0%

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Keywords

open-science r-packages range-modelling rare-species species-distribution-modeling species-distribution-modelling
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Repository

An R package focused on Species Distribution Modelling techniques for species with small sample sizes

Basic Info
  • Host: GitHub
  • Owner: bmaitner
  • License: other
  • Language: R
  • Default Branch: main
  • Homepage:
  • Size: 89.7 MB
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  • Stars: 3
  • Watchers: 1
  • Forks: 1
  • Open Issues: 1
  • Releases: 1
Topics
open-science r-packages range-modelling rare-species species-distribution-modeling species-distribution-modelling
Created over 4 years ago · Last pushed over 1 year ago
Metadata Files
Readme Changelog License

README.md

Small Sample Size Species Distribution Modeling

The S4DM R package

This repository contains an R package that implements Species Distribution Modeling methods which work even when there are relatively few occurrence records (as is the case for poorly-sample or range-restricted species). These methods were primarily developed by the Drake lab, and include three types of methods: 1) Plug-and-play models, 2) environmental-range models, and 3) density-ratio models. Most of the important functions in this package are wrappers around existing functions that handle density estimation or density-ratio estimation. Much of this code was created by modifying existing code at https://github.com/DrakeLab/PlugNPlay in order to make functions more modular and extensible.

How it works

The package is build on a hierarchy of modular functions, each of which calls on lower-level functions:

  1. The highest-level functions are make_range_map and evaluate_range_map, which are wrappers for...
  2. The next-highest-level functions, fit_plug_and_play, fit_density_ratio, project_plug_and_play, and project_density_ratio, which are wrappers for ...
  3. Internal modules such as pnp_kde or dr_ulsif. These modules both model the environmental covariates and predict values at environmental covariates from fitted models. These modules are largely wrappers around existing functions for fitting density functions or density-ratios. Modules beginning with "pnp" pertain to density functions while models beginning with "dr" pertain to density ratio functions.

This hierarchical structure built on low-level internal modules is designed to allow for the easy addition of new methods by adding small, self-contained modules. The highest-level functions are intended only for quick-and-dirty analyses or quick visualizations. We recommend that users focus on the "fit" and "project" functions for work intended for publication.

What is Plug-and-Play?

In general usage, the term plug-and-play (PNP) refers to software or hardware that can be connected without any additional setup or configuration. In the context of species distribution models, plug-and-play is a framework developed by Drake and Richards (https://esajournals.onlinelibrary.wiley.com/doi/full/10.1002/ecs2.2373) that recognizes that species distribution models can be constructed by "plugging in" any methods that can estimate density functions.

Owner

  • Name: Brian Maitner
  • Login: bmaitner
  • Kind: user

GitHub Events

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  • Issues event: 1
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Dependencies

DESCRIPTION cran
  • corpcor * imports
  • densratio * imports
  • flexclust * imports
  • geometry * imports
  • kernlab * imports
  • maxnet * imports
  • mvtnorm * imports
  • np * imports
  • pROC * imports
  • robust * imports
  • rvinecopulib * imports
  • sf * imports
  • terra * imports
  • BIEN * suggests
  • geodata * suggests
  • ggplot2 * suggests
  • knitr * suggests
  • tidyterra * suggests