Package: webSDM 1.1-5

webSDM: Including Known Interactions in Species Distribution Models

A collection of tools to fit and work with trophic Species Distribution Models. Trophic Species Distribution Models combine knowledge of trophic interactions with Bayesian structural equation models that model each species as a function of its prey (or predators) and environmental conditions. It exploits the topological ordering of the known trophic interaction network to predict species distribution in space and/or time, where the prey (or predator) distribution is unavailable. The method implemented by the package is described in Poggiato, Andréoletti, Pollock and Thuiller (2022) <doi:10.22541/au.166853394.45823739/v1>.

Authors:Giovanni Poggiato [aut, cre, cph], Jérémy Andréoletti [aut]

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webSDM.pdf |webSDM.html✨
webSDM/json (API)
NEWS

# Install 'webSDM' in R:
install.packages('webSDM', repos = c('https://giopogg.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/giopogg/websdm/issues

Pkgdown site:https://giopogg.github.io

Datasets:
  • G - Simulated environemntal covariates G
  • X - Simulated environmental covariates X
  • Y - Simulated species distribution Y

On CRAN:

Conda:

5.71 score 17 stars 9 scripts 157 downloads 8 exports 151 dependencies

Last updated 9 months agofrom:ec86bf9f60. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 21 2025
R-4.5-winOKMar 21 2025
R-4.5-macOKMar 21 2025
R-4.5-linuxOKFeb 19 2025
R-4.4-winOKMar 21 2025
R-4.4-macOKMar 21 2025
R-4.4-linuxOKMar 21 2025
R-4.3-winOKMar 21 2025
R-4.3-macOKMar 21 2025

Exports:computeVariableImportanceevaluateModelFitplotGplotG_inferredpredictPotentialSDMfittrophicSDMtrophicSDM_CV

Dependencies:abindbackportsbase64encbayesplotBHbootbridgesamplingbrmsBrobdingnagbroombroom.mixedbslibcachemcallrcheckmateclicodacodetoolscolorspacecolourpickercommonmarkcpp11crayoncrosstalkdescdigestdismodistributionaldplyrDTdygraphsevaluatefansifarverfastmapfontawesomeforcatsforeachfsfurrrfuturefuture.applygenericsGGallyggplot2ggridgesggstatsglmnetglobalsgluegridExtragtablegtoolshighrhmshtmltoolshtmlwidgetshttpuvigraphinlineisobanditeratorsjquerylibjsonlitejtoolsknitrlabelinglaterlatticelazyevallifecyclelistenvlme4loomagrittrmarkdownMASSMatrixmatrixStatsmemoisemgcvmimeminiUIminqamunsellmvtnormnleqslvnlmenloptrnumDerivpanderparallellypatchworkpillarpkgbuildpkgconfigplyrposteriorprettyunitsprocessxprogresspromisespspurrrQuickJSRR6rappdirsrasterrbibutilsRColorBrewerRcppRcppEigenRcppParallelRdpackreformulasreshape2rlangrmarkdownrstanrstanarmrstantoolssandwichsassscalesshapeshinyshinyjsshinystanshinythemessourcetoolsspStanHeadersstringistringrsurvivaltensorAterrathreejstibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunxtablextsyamlzoo

Composite variables and biotic-abiotic interactions

Rendered fromComposite_variables.Rmdusingknitr::rmarkdownon Mar 21 2025.

Last update: 2022-11-21
Started: 2022-11-13

Introduction to trophic SDM

Rendered fromIntroduction.Rmdusingknitr::rmarkdownon Mar 21 2025.

Last update: 2023-09-18
Started: 2022-10-23

Subtle and obvious differences between SDM and trophic SDM

Rendered fromDifferences_with_SDMs.Rmdusingknitr::rmarkdownon Mar 21 2025.

Last update: 2023-09-18
Started: 2022-11-08