Package: bamm 0.5.0

bamm: Species Distribution Models as a Function of Biotic, Abiotic and Movement Factors (BAM)

Species Distribution Modeling (SDM) is a practical methodology that aims to estimate the area of distribution of a species. However, most of the work has focused on estimating static expressions of the correlation between environmental variables. The outputs of correlative species distribution models can be interpreted as maps of the suitable environment for a species but not generally as maps of its actual distribution. Soberón and Peterson (2005) <doi:10.17161/bi.v2i0.4> presented the BAM scheme, a heuristic framework that states that the occupied area of a species occurs on sites that have been accessible through dispersal (M) and have both favorable biotic (B) and abiotic conditions (A). The 'bamm' package implements classes and functions to operate on each element of the BAM and by using a cellular automata model where the occupied area of a species at time t is estimated by the multiplication of three binary matrices: one matrix represents movements (M), another abiotic -niche- tolerances (A), and a third, biotic interactions (B). The theoretical background of the package can be found in Soberón and Osorio-Olvera (2023) <doi:10.1111/jbi.14587>.

Authors:Luis Osorio-Olvera [aut, cre], Jorge Soberón [aut], Rusby G. Contreras-Díaz [ctb]

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bamm/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/luismurao/bamm/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

4.40 score 1 stars 4 scripts 310 downloads 31 exports 90 dependencies

Last updated 3 months agofrom:5dc35fe20f. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 10 2024
R-4.5-win-x86_64NOTENov 10 2024
R-4.5-linux-x86_64NOTENov 10 2024
R-4.4-win-x86_64NOTENov 10 2024
R-4.4-mac-x86_64NOTENov 10 2024
R-4.4-mac-aarch64NOTENov 10 2024
R-4.3-win-x86_64NOTENov 10 2024
R-4.3-mac-x86_64NOTENov 10 2024
R-4.3-mac-aarch64NOTENov 10 2024

Exports:adj_matbam_clustersbam_simbam_ssimbioindexbioindex_sparsecommunity_simcsdcsd_estimatecsim2pamdiversity_rangediversity_range_analysiseigen_bamg_areajaccardmodel2sparsemodels2pamnull_dispersion_field_distributionoccs2sparsepampam2bioindexpam2richnesspermute_pamplotpredictsdm_simsetAshape2Gridshowsim2Animationsim2Raster

Dependencies:animationaskpassbase64encbslibcachemclicodetoolscolorspacecpp11crosstalkcurldata.tabledigestdplyrevaluatefansifarverfastmapfontawesomefsfurrrfuturegenericsggplot2globalsgluegtablehighrhtmltoolshtmlwidgetshttrigraphisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevalleafletleaflet.providerslifecyclelistenvmagickmagrittrMASSMatrixmemoisemgcvmimemunsellnlmeopensslparallellypillarpkgconfigplotlypngpromisespurrrR6rappdirsrasterrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackrlangrmarkdownRSpectrasassscalesspstringistringrsysterratibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml

bamm

Rendered frombam.Rmdusingknitr::rmarkdownon Nov 10 2024.

Last update: 2022-12-11
Started: 2022-11-28

Readme and manuals

Help Manual

Help pageTopics
adj_mat: Function to compute the adjacency matrix of an area.adj_mat
bam_clusters: Function to estimate the connectivity of suitable areasbam_clusters
bam_sim: Simulate dispersal dynamics using the set B of the BAM framework.bam_sim
bam_ssim: Simulate dispersal dynamics using the set B of the BAM framework.bam_ssim
Class 'bam' digrambam bam-class
Class 'bioindex_sparse'biodiversity_index_sparse bioindex_sparse bioindex_sparse-class
Class 'bioindex'biodiversity_index bioindex bioindex-class
community_bam: Community 'bamm'community_sim
Class 'community_sim' digramcommunity-class community_bam community_sim-class
csd_estimate: Estimate the connectivity suitability and dispersal plotcsd_estimate
Class 'csd'csd csd-class
csim2pam: Converts community simulation to a Presence Absence Matrix (PAM)csim2pam
range_diversity_analysis: diversity analysisdiversity_range_analysis
Class 'diversity_range'diversityrange diversity_range diversity_range-class
eigen_bam: Compute the Eigen system of two bam objectseigen_bam
S4 classes to organize data and results of 'bamm' objectscoordinates-class g_area g_area-class
jaccard: Estimates the Jaccard index for comparing two binary mapsjaccard
Class 'leaflet' leafletleaflet leaflet-class
model2sparse: Converts a niche model into a diagonal sparse matrixmodel2sparse
models2pam: Converts binary rasters to a PAMmodels2pam
null_dispersion_field_distribution: Null distribution of the dispersion fieldnull_dispersion_field_distribution
occs2sparse: Converts occurrence data into a sparse matrix objectoccs2sparse
Class 'pam' Presence-Absence MatrixPAM pam pam-class
pam2bioindex: PAM to biodiversity indexpam2bioindex
pam2richness: Converts Presence Absence Matrix (pam object) to richness rasterpam2richness
permute_pam: Function to permute a Presence-Absence-Matrix.permute_pam
Plot method for objects of class diversity_range 'bamm'.plot,diversity_range,ANY-method
Predict method of the package 'bamm'.bam-method predict predict,bam-method
sdm_sim: Simulate single species dispersal dynamics using the BAM framework.sdm_sim
Class for the A set of the BAM diagramA-class setA setA-class
Class for the M set of the 'bamm' diagramM-class setM setM-class
shape2Grid: Function to create a grid given a spatial polygonshape2Grid
Show information in setA class 'bamm'.show,bioindex_sparse-method show,csd-method show,diversity_range-method show,pam-method show,setA-method show,setM-method
sim2Animation: Animate BAM simulation object.sim2Animation
sim2Raster: Convert a BAM simulation object to RasterStacksim2Raster