Package: SSDM 0.2.9

SSDM: Stacked Species Distribution Modelling

Allows to map species richness and endemism based on stacked species distribution models (SSDM). Individuals SDMs can be created using a single or multiple algorithms (ensemble SDMs). For each species, an SDM can yield a habitat suitability map, a binary map, a between-algorithm variance map, and can assess variable importance, algorithm accuracy, and between- algorithm correlation. Methods to stack individual SDMs include summing individual probabilities and thresholding then summing. Thresholding can be based on a specific evaluation metric or by drawing repeatedly from a Bernoulli distribution. The SSDM package also provides a user-friendly interface.

Authors:Sylvain Schmitt, Robin Pouteau, Dimitri Justeau, Florian de Boissieu, Lukas Baumbach, Philippe Birnbaum

SSDM_0.2.9.tar.gz
SSDM_0.2.9.zip(r-4.7-any)SSDM_0.2.9.zip(r-4.6-any)SSDM_0.2.9.zip(r-4.5-any)
SSDM_0.2.9.tgz(r-4.6-any)SSDM_0.2.9.tgz(r-4.5-any)
SSDM_0.2.9.tar.gz(r-4.7-any)SSDM_0.2.9.tar.gz(r-4.6-any)
SSDM_0.2.9.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
SSDM/json (API)

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

Bug tracker:https://github.com/sylvainschmitt/ssdm/issues

Datasets:
  • Env - A stack of three environmental variables
  • Occurrences - Plant occurrences data frame

On CRAN:

Conda:

7.16 score 49 stars 59 scripts 215 downloads 1 mentions 18 exports 98 dependencies

Last updated from:2157d1d263. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK478
source / vignettesOK374
linux-releaseOK357
macos-releaseOK356
macos-oldrelOK204
windows-develOK432
windows-releaseOK348
windows-oldrelOK346
wasm-releaseOK200

Exports:%>%ensembleensemble_modellingevaluateguiload_esdmload_occload_stackload_varmapDiversitymodellingplotprojectsave.esdmsave.stackstack_modellingstackingupdate

Dependencies:base64encbslibcachemclassclassIntclicodetoolscommonmarkcpp11crosstalkDBIdigestdismodoParalleldotCall64e1071earthevaluatefarverfastmapfieldsfontawesomeforeachFormulafsgbmggplot2gluegtablehighrhtmltoolshtmlwidgetshttpuvisobanditeratorsitertoolsjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelazyevalleafletleaflet.providerslifecyclemagrittrmapsMatrixmemoisemgcvmimenlmennetotelplotmoplotrixplyrpngpoibinpromisesproxyR6randomForestrappdirsrasterRColorBrewerRcppreshape2rlangrmarkdownrparts2S7sassscalessdmsfshinyshinydashboardsourcetoolsspspamspThinstringistringrsurvivalterratinytexunitsvctrsviridisLitewithrwkxfunxtableyaml

SSDM: Stacked Species Distribution Models with R
Data inputs | Environmental variables | Natural history records / occurrence data | Model algorithms | Individual species distribution models (SDMs) | Ensemble species distribution models (ESDMs) | Stacked species distribution models (SSDMs) | Outputs | Model accuracy assessment | Importance analysis of environmental variables | Endemism mapping | Summary plot | Model forecasting | Advanced settings | Modelling methods | Performance and speed
Rendered fromSSDM.Rmdusingknitr::rmarkdown

Last update: 2026-07-09
Started: 2017-04-10

GUI: A user-friendly interface for SSDM
Data inputs | Environmental variables | Natural history records | Model | Basic parameterization | Intermediate parameterization | Advanced parameterization | Results | Stack-level results | Species-level results | Save
Rendered fromGUI.Rmdusingknitr::rmarkdown

Last update: 2018-01-04
Started: 2017-04-10

Readme and manuals

Help Manual

Help pageTopics
An S4 class to represent an SDM based on a single algorithmAlgorithm.SDM-class
Methods to assemble multiple algorithms in an ensemble SDMensemble ensemble,Algorithm.SDM-method sum,Algorithm.SDM-method
Build an ensemble SDM that assembles multiple algorithmsensemble_modelling
An S4 class to represent an ensemble SDMEnsemble.SDM-class
A stack of three environmental variablesEnv
Evaluateevaluate evaluate,Algorithm.SDM-method evaluate,MAXENT.SDM-method evaluate,Stacked.SDM-method
SSDM package Graphic User Interfacegui
Load occurrence dataload_occ
Load environmental variablesload_var
Load ensemble SDMs and SSDMs.load.model load_esdm load_stack
Map DiversitymapDiversity mapDiversity,Stacked.SDM-method
Build an SDM using a single algorithmmodelling
Plant occurrences data frameOccurrences
Plot SDMs, ensemble SDMs, and SSDMsplot,SDM,ANY-method plot,Stacked.SDM,ANY-method plot.model
Project model into environmentproject project,Algorithm.SDM-method project,Ensemble.SDM-method project,MAXENT.SDM-method project,Stacked.SDM-method
Save ensemble SDMs and SSDMssave.esdm save.esdm,Ensemble.SDM-method save.model save.stack save.stack,Stacked.SDM-method
SSDM: Stacked species distribution modellingSSDM-package SSDM
Build an SSDM that assembles multiple algorithms and species.stack_modelling
An S4 class to represent SSDMsStacked.SDM-class
Stack different ensemble SDMs in an SSDMstacking stacking,Ensemble.SDM-method
Update a previous SSDMupdate,Stacked.SDM-method