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]

webSDM_1.1-5.tar.gz
webSDM_1.1-5.zip(r-4.7)webSDM_1.1-5.zip(r-4.6)webSDM_1.1-5.zip(r-4.5)
webSDM_1.1-5.tgz(r-4.6-any)webSDM_1.1-5.tgz(r-4.5-any)
webSDM_1.1-5.tar.gz(r-4.7-any)webSDM_1.1-5.tar.gz(r-4.6-any)
webSDM_1.1-5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
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/docs site:https://giopogg.github.io

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

On CRAN:

Conda:

5.43 score 18 stars 9 scripts 229 downloads 8 exports 151 dependencies

Last updated from:ec86bf9f60. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK434
source / vignettesOK315
linux-release-x86_64OK453
macos-release-arm64OK268
macos-oldrel-arm64OK304
windows-develOK435
windows-releaseOK431
windows-oldrelOK386
wasm-releaseOK184

Exports:computeVariableImportanceevaluateModelFitplotGplotG_inferredpredictPotentialSDMfittrophicSDMtrophicSDM_CV

Dependencies:abindbackportsbase64encbayesplotBHbootbridgesamplingbrmsBrobdingnagbroombroom.mixedbslibcachemcallrcheckmateclicodacodetoolscolourpickercommonmarkcpp11crayoncrosstalkdescdigestdismodistributionaldplyrDTdygraphsevaluatefarverfastmapfontawesomeforcatsforeachfsfurrrfuturefuture.applygenericsGGallyggplot2ggridgesggstatsglmnetglobalsgluegridExtragtablegtoolshighrhmshtmltoolshtmlwidgetshttpuvigraphinlineisobanditeratorsjquerylibjsonlitejtoolsknitrlabelinglaterlatticelazyevallifecyclelistenvlitedownlme4loomagrittrmarkdownMASSMatrixmatrixStatsmemoisemgcvmimeminiUIminqamvtnormnleqslvnlmenloptrnumDerivotelpanderparallellypatchworkpillarpkgbuildpkgconfigplyrposteriorprettyunitsprocessxprogresspromisespspurrrQuickJSRR6rappdirsrasterrbibutilsRColorBrewerRcppRcppEigenRcppParallelRdpackreformulasreshape2rlangrmarkdownrstanrstanarmrstantoolsS7sandwichsassscalesshapeshinyshinyjsshinystanshinythemessourcetoolsspStanHeadersstringistringrsurvivaltensorAterrathreejstibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunxtablextsyamlzoo

Composite variables and biotic-abiotic interactions

Rendered fromComposite_variables.Rmdusingknitr::rmarkdownon May 08 2026.

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

Introduction to trophic SDM

Rendered fromIntroduction.Rmdusingknitr::rmarkdownon May 08 2026.

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

Subtle and obvious differences between SDM and trophic SDM

Rendered fromDifferences_with_SDMs.Rmdusingknitr::rmarkdownon May 08 2026.

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