| Title: | A Modular Platform for Reproducible Modeling of Species Niches and Distributions |
|---|---|
| Description: | The 'shiny' application Wallace is a modular platform for reproducible modeling of species niches and distributions. Wallace guides users through a complete analysis, from the acquisition of species occurrence and environmental data to visualizing model predictions on an interactive map, thus bundling complex workflows into a single, streamlined interface. An extensive vignette, which guides users through most package functionality can be found on the package's GitHub Pages website: <https://wallaceecomod.github.io/wallace/articles/tutorial-v2.html>. |
| Authors: | Bethany A. Johnson [aut], Jamie M. Kass [aut], Gonzalo E. Pinilla-Buitrago [aut], Andrea Paz [aut], Valentina Grisales-Betancur [aut], Dean Attali [aut], Matthew E. Aiello-Lammens [aut], Cory Merow [aut], Mary E. Blair [aut, cre], Robert P. Anderson [aut], Sarah I. Meenan [ctb], Olivier Broennimann [ctb], Peter J. Galante [ctb], Brian S. Maitner [ctb], Hannah L. Owens [ctb], Sara Varela [ctb], Bruno Vilela [ctb], Robert Muscarella [ctb] |
| Maintainer: | Mary E. Blair <[email protected]> |
| License: | GPL-3 |
| Version: | 2.1.3 |
| Built: | 2024-11-14 05:18:11 UTC |
| Source: | https://github.com/wallaceecomod/wallace |
Wallace is a shiny app that guides users through a complete
species niche/distributional modeling analysis, from the acquisition of
species occurrence and environmental data to visualizing model predictions
on an interactive map (rleaflet), thus bundling complex workflows
into a single, streamlined GUI interface. New functionality, in the form of
modules, can be added to Wallace via contributions from the user
community. In addition, executable session code (R Markdown format) can
be downloaded to share with others or use as supplementary information
for scientific papers and reports. The application is run via the
function run_wallace.
Please see the official website (https://wallaceecomod.github.io/) for more details. If you have questions about the application, please participate in the Google Group, or email the team directly: [email protected].
Create the template of a new Wallace module.
create_module(id, dir, map = FALSE, result = FALSE, rmd = FALSE, save = FALSE)create_module(id, dir, map = FALSE, result = FALSE, rmd = FALSE, save = FALSE)
id |
The id of the module. |
dir |
A directory where the new module should be created. |
map |
Whether or not the module should support modifying the map. |
result |
Whether or not the module should support showing information in the Result tab. |
rmd |
Whether or not the module should add Rmd code to the Session Code download. |
save |
Whether or not the module has some custom data to save when the user saves the current session. |
download ecoClimate layers. more info at www.ecoclimate.org
ecoClimate_getdata(AOGCM, Baseline, Scenario, logger)ecoClimate_getdata(AOGCM, Baseline, Scenario, logger)
AOGCM |
Select the AOGCM. Options are: "CCSM", "CNRM", "MIROC", "COSMOS", "FGOALS", "GISS", "IPSL", "MRI", "MPI" |
Baseline |
Select a baseline for the climatic layers. Options are: "Pre-industrial" (piControl-1760), "Historical" (1900-1949), "Modern" (1950-1999) |
Scenario |
Select a temporal scenario. Options are: "LGM" (21,000 years ago), "Holo" (6,000 years ago), "Present", "Future 2.6" (rcp 2.6), "Future 4.5" (rcp 4.5), "Future 6" (rcp 6), "Future 8.5" (rcp 8.5) |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL |
## Not run: CCSM_mod_present <- ecoclimate_getdata("CCSM", "Modern", "Present") dev.new() plot(CCSM_mod_present) ## End(Not run)## Not run: CCSM_mod_present <- ecoclimate_getdata("CCSM", "Modern", "Present") dev.new() plot(CCSM_mod_present) ## End(Not run)
select which bioclimatic variables and set the extent you want (crop the raster stack to your study extent)
ecoClimate_select(map_climate, Sels=c(1:19), extent=c(-180, 180, -90, 90))ecoClimate_select(map_climate, Sels=c(1:19), extent=c(-180, 180, -90, 90))
map_climate |
raster stack with all the variables |
Sels |
vector of integer numbers. 1 for bio1, 2 for bio2, etc. e.g. Sels= c(1,12,6) for selecting bio1, bio12 and bio6 |
extent |
vector. xmin, xmax, ymin, ymax. e.g. c() |
## Not run: CCSM_mod_present <- ecoclimate_getdata("CCSM", "Modern", "Present") Europe_CCSM_m_p_bio1_12 <- ecoClimate_select(CCSM_mod_present, c(1, 12), extent = c(-20, 80, 20, 80)) dev.new() plot(Europe_CCSM_m_p_bio1_12) ## End(Not run)## Not run: CCSM_mod_present <- ecoclimate_getdata("CCSM", "Modern", "Present") Europe_CCSM_m_p_bio1_12 <- ecoClimate_select(CCSM_mod_present, c(1, 12), extent = c(-20, 80, 20, 80)) dev.new() plot(Europe_CCSM_m_p_bio1_12) ## End(Not run)
download ecoClimate variables. See www.ecoclimate.org.
envs_ecoClimate(bcAOGCM, bcScenario, ecoClimSel, logger = NULL)envs_ecoClimate(bcAOGCM, bcScenario, ecoClimSel, logger = NULL)
bcAOGCM |
Name of the Atmospheric and Oceanic Global Circulation Model. Options are: "CCSM", "CNRM", "MIROC", "FGOALS", "GISS", "IPSL","MRI", "MPI" |
bcScenario |
Select the temporal scenario that you want to download. Options are: "LGM" (21,000 years ago), "Holo" (6,000 years ago), "Present", "Future 2.6" (rcp 2.6), "Future 4.5" (rcp 4.5), "Future 6" (rcp 6), "Future 8.5" (rcp 8.5) |
ecoClimSel |
Numeric vector with list of variables to select. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
This function is called by the module envs to download ecoClimate variables from www.ecoclimate.org. The variables to be downloaded are selected by the user with bcSel and the resolution is fixed to 0.5 degrees. This function currently gets variables from Dropbox and the process takes significantly more time than for other datasets. It returns a rasterStack of selected variables.
A rasterStack of selected variables
Sara Varela <[email protected]>
Jamie M. Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
bcAOGCM <- "CCSM" bcScenario <- "LGM" ecoClimSel <- c(1,2,3) ## Not run: varsEcoClimate <- envs_ecoClimate(bcAOGCM, bcScenario, ecoClimSel) ## End(Not run)bcAOGCM <- "CCSM" bcScenario <- "LGM" ecoClimSel <- c(1,2,3) ## Not run: varsEcoClimate <- envs_ecoClimate(bcAOGCM, bcScenario, ecoClimSel) ## End(Not run)
Load user provided rasters
envs_userEnvs(rasPath, rasName, doBrick = FALSE, logger = NULL)envs_userEnvs(rasPath, rasName, doBrick = FALSE, logger = NULL)
rasPath |
character. Path to rasters, must be the full path including file name and extension |
rasName |
character. Vector of raster names to be assigned to loaded rasters |
doBrick |
logical. Converts downloaded rasters to brick for faster processing |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL |
This function is called by the module envs to load user provided raster variables for use in further analyses. It returns either a rasterStack or rasterBrick of loaded variables with appropriate names for further analyses.
A rasterStack or a rasterBrick (if doBrick = TRUE) of user provided rasters
Jamie Kass <[email protected] >
Gonzalo E. Pinilla-Buitrago <[email protected]>
## Not run: pathRast <- list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE) nameRast <- list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE) userEnvs <- envs_userEnvs(rasPath = pathRast, rasName = nameRast) ## End(Not run)## Not run: pathRast <- list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE) nameRast <- list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE) userEnvs <- envs_userEnvs(rasPath = pathRast, rasName = nameRast) ## End(Not run)
download WorldClim variables. See www.worldclim.com.
envs_worldclim(bcRes, bcSel, mapCntr, doBrick = FALSE, logger = NULL)envs_worldclim(bcRes, bcSel, mapCntr, doBrick = FALSE, logger = NULL)
bcRes |
numeric. Resolution of the climatic layers. Currently available resolutions are 0.5, 2.5 and 10. |
bcSel |
character. Vector with bionames to be selected. |
mapCntr |
numeric. Vector with longitude and latitude for a tile. Required for bcRes 0.5, for other resolutions world data will be downloaded. |
doBrick |
logical. Converts downloaded rasters to brick for faster processing. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
This function is called by the module envs to download WorldClim variables from www.worldclim.com. The variables to be downloaded are selected by the user with bcSel and the resolution with bcRes. It returns either a rasterStack or rasterBrick of selected variables with appropriate names for further analyses.
A rasterStack or a rasterBrick (if doBrick=TRUE) of downloaded worldclim rasters at the requested resolution.
Jamie Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
Bethany A. Johnson <[email protected]>
worldclim_global, worldclim_tile
## Not run: bcRes <- 10 # (10 arcmin) envar <- c('bio05', 'bio06', 'bio13', 'bio14') arcmin10 <- envs_worldclim(bcRes, bcSel = envar) ## End(Not run)## Not run: bcRes <- 10 # (10 arcmin) envar <- c('bio05', 'bio06', 'bio13', 'bio14') arcmin10 <- envs_worldclim(bcRes, bcSel = envar) ## End(Not run)
Function evaluates niche overlap between the two species for which the occurrence density grid was computed
espace_nicheOv( z1, z2, iter = 100, equivalency = FALSE, similarity = TRUE, logger = NULL )espace_nicheOv( z1, z2, iter = 100, equivalency = FALSE, similarity = TRUE, logger = NULL )
z1 |
ecospat niche object for species 1 from espace_occDens. |
z2 |
ecospat niche object for species 2 from espace_occDens. |
iter |
numeric. Number of iterations. |
equivalency |
logical. Whether to run equivalency test. Default is FALSE. |
similarity |
logical. Whether to run similarity test. Default is TRUE. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
The niche overlap quantification is based on the occurrence densities and the densities of environmental conditions available in the background extent that are estimated in the module Occurrence Density Grid. The function computes 4 different things; Schoener's D, unfilling, stability, expansion indices (Guisan et al. 2014 TREE), and tests for niche equivalency and niche similarity.
A list of 4 elements if all is set to TRUE. Elements are overlap (Schoener's D), USE (ecospat.niche.dyn.index), equiv and simil.
Jamie Kass <[email protected]>
Olivier Broennimann <[email protected]>
espace_pca espace_occDens
ecospat.niche.overlap
ecospat.niche.dyn.index
ecospat.niche.equivalency.test
ecospat.niche.similarity.test
## Not run: sp.name1 <- "Bassaricyon_alleni" sp.name2 <- "Bassaricyon_neblina" envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) occs.z1 <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace")) occs.z2 <- read.csv(system.file("extdata/Bassaricyon_neblina.csv", package = "wallace")) bgPts.z1 <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv", package = "wallace")) bgPts.z2 <- read.csv(system.file("extdata/Bassaricyon_neblina_bgPoints.csv", package = "wallace")) occsExt.z1 <- raster::extract(envs, occs.z1[, c("longitude", "latitude")]) occsExt.z2 <- raster::extract(envs, occs.z2[, c("longitude", "latitude")]) bgExt.z1 <- raster::extract(envs, bgPts.z1[, c("longitude", "latitude")]) bgExt.z2 <- raster::extract(envs, bgPts.z2[, c("longitude", "latitude")]) pcaZ <- espace_pca(sp.name1, sp.name2, occsExt.z1, occsExt.z2, bgExt.z1, bgExt.z2) occDens <- espace_occDens(sp.name1, sp.name2, pcaZ) nicheOv <- espace_nicheOv(z1 = occDens[[sp.name1]], z2 = occDens[[sp.name2]], iter = 100, equivalency = TRUE, similarity = TRUE) ## End(Not run)## Not run: sp.name1 <- "Bassaricyon_alleni" sp.name2 <- "Bassaricyon_neblina" envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) occs.z1 <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace")) occs.z2 <- read.csv(system.file("extdata/Bassaricyon_neblina.csv", package = "wallace")) bgPts.z1 <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv", package = "wallace")) bgPts.z2 <- read.csv(system.file("extdata/Bassaricyon_neblina_bgPoints.csv", package = "wallace")) occsExt.z1 <- raster::extract(envs, occs.z1[, c("longitude", "latitude")]) occsExt.z2 <- raster::extract(envs, occs.z2[, c("longitude", "latitude")]) bgExt.z1 <- raster::extract(envs, bgPts.z1[, c("longitude", "latitude")]) bgExt.z2 <- raster::extract(envs, bgPts.z2[, c("longitude", "latitude")]) pcaZ <- espace_pca(sp.name1, sp.name2, occsExt.z1, occsExt.z2, bgExt.z1, bgExt.z2) occDens <- espace_occDens(sp.name1, sp.name2, pcaZ) nicheOv <- espace_nicheOv(z1 = occDens[[sp.name1]], z2 = occDens[[sp.name2]], iter = 100, equivalency = TRUE, similarity = TRUE) ## End(Not run)
calculates the part of environmental space more densely populated by species & the availability of environmental conditions in the background
espace_occDens(sp.name1, sp.name2, pca, logger = NULL)espace_occDens(sp.name1, sp.name2, pca, logger = NULL)
sp.name1 |
character name of species 1 to be analyzed. |
sp.name2 |
character name of species 2 to be analyzed. |
pca |
pca output of pca component ( in list format) |
logger |
stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
This function implements a density estimation for each region in the environmental space (gridded at 100*100 pixels). Then an occurrence density is estimated using a kernel density approach. The density of environmental conditions in the background is calculated in the same way.
Returns a list of 2 lists (one for each species). Each list is an ecospat niche object that contains 10 species specific slots with information outputed by ecospat::grid.clim.dyn. z.uncor is the density of occurrence of the species and z.cor the occupancy of the environment by the species. It has the input parameters as individual slots.
Jamie Kass <[email protected] >
Olivier Broennimann <[email protected]>
espace_pca espace_nicheOv
ecospat.grid.clim.dyn
## Not run: sp.name1 <- "Bassaricyon_alleni" sp.name2 <- "Bassaricyon_neblina" envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) occs.z1 <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace")) occs.z2 <- read.csv(system.file("extdata/Bassaricyon_neblina.csv", package = "wallace")) bgPts.z1 <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv", package = "wallace")) bgPts.z2 <- read.csv(system.file("extdata/Bassaricyon_neblina_bgPoints.csv", package = "wallace")) occsExt.z1 <- raster::extract(envs, occs.z1[, c("longitude", "latitude")]) occsExt.z2 <- raster::extract(envs, occs.z2[, c("longitude", "latitude")]) bgExt.z1 <- raster::extract(envs, bgPts.z1[, c("longitude", "latitude")]) bgExt.z2 <- raster::extract(envs, bgPts.z2[, c("longitude", "latitude")]) pcaZ <- espace_pca(sp.name1, sp.name2, occsExt.z1, occsExt.z2, bgExt.z1, bgExt.z2) occDens <- espace_occDens(sp.name1, sp.name2, pcaZ) ## End(Not run)## Not run: sp.name1 <- "Bassaricyon_alleni" sp.name2 <- "Bassaricyon_neblina" envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) occs.z1 <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace")) occs.z2 <- read.csv(system.file("extdata/Bassaricyon_neblina.csv", package = "wallace")) bgPts.z1 <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv", package = "wallace")) bgPts.z2 <- read.csv(system.file("extdata/Bassaricyon_neblina_bgPoints.csv", package = "wallace")) occsExt.z1 <- raster::extract(envs, occs.z1[, c("longitude", "latitude")]) occsExt.z2 <- raster::extract(envs, occs.z2[, c("longitude", "latitude")]) bgExt.z1 <- raster::extract(envs, bgPts.z1[, c("longitude", "latitude")]) bgExt.z2 <- raster::extract(envs, bgPts.z2[, c("longitude", "latitude")]) pcaZ <- espace_pca(sp.name1, sp.name2, occsExt.z1, occsExt.z2, bgExt.z1, bgExt.z2) occDens <- espace_occDens(sp.name1, sp.name2, pcaZ) ## End(Not run)
Principal component analysis to reduce dimensionality of environmental space
espace_pca( sp.name1, sp.name2 = NULL, occs.z1, occs.z2 = NULL, bgPts.z1, bgPts.z2 = NULL, logger = NULL )espace_pca( sp.name1, sp.name2 = NULL, occs.z1, occs.z2 = NULL, bgPts.z1, bgPts.z2 = NULL, logger = NULL )
sp.name1 |
character. Name of species 1 to be analyzed. |
sp.name2 |
character. Name of species 2 to be analyzed. Default is NULL. |
occs.z1 |
table of occurrences with environmental values only for sp1. |
occs.z2 |
table of occurrences with environmental values only for sp2. Default is NULL. |
bgPts.z1 |
table of background points with environmental values only for sp1. |
bgPts.z2 |
table of background points with environmental values only for sp2. Default is NULL. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL |
This function is called by the component espace to calibrate a PCA for 2 species in environmental space. When using within Wallace, GUI parameters are obtained from the model object, in particular, table of occurrences with environmental values and table of background points with environmental values. User must be careful as these tables must contain only environmental variables and not the point coordinates as outputted by model objects. The PCA is calibrated over the whole set of background points. The provided species name(s) are only used for logger messages and not for querying or selecting occurrences.
A list of 14 elements of classes dudi and pca as in dudi.pca
Jamie Kass <[email protected]>
Olivier Broennimann <[email protected]>
## Not run: sp.name1 <- "Bassaricyon_alleni" sp.name2 <- "Bassaricyon_neblina" envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) occs.z1 <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace")) occs.z2 <- read.csv(system.file("extdata/Bassaricyon_neblina.csv", package = "wallace")) bgPts.z1 <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv", package = "wallace")) bgPts.z2 <- read.csv(system.file("extdata/Bassaricyon_neblina_bgPoints.csv", package = "wallace")) occsExt.z1 <- raster::extract(envs, occs.z1[, c("longitude", "latitude")]) occsExt.z2 <- raster::extract(envs, occs.z2[, c("longitude", "latitude")]) bgExt.z1 <- raster::extract(envs, bgPts.z1[, c("longitude", "latitude")]) bgExt.z2 <- raster::extract(envs, bgPts.z2[, c("longitude", "latitude")]) pcaZ <- espace_pca(sp.name1, sp.name2, occsExt.z1, occsExt.z2, bgExt.z1, bgExt.z2) ## End(Not run)## Not run: sp.name1 <- "Bassaricyon_alleni" sp.name2 <- "Bassaricyon_neblina" envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) occs.z1 <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace")) occs.z2 <- read.csv(system.file("extdata/Bassaricyon_neblina.csv", package = "wallace")) bgPts.z1 <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv", package = "wallace")) bgPts.z2 <- read.csv(system.file("extdata/Bassaricyon_neblina_bgPoints.csv", package = "wallace")) occsExt.z1 <- raster::extract(envs, occs.z1[, c("longitude", "latitude")]) occsExt.z2 <- raster::extract(envs, occs.z2[, c("longitude", "latitude")]) bgExt.z1 <- raster::extract(envs, bgPts.z1[, c("longitude", "latitude")]) bgExt.z2 <- raster::extract(envs, bgPts.z2[, c("longitude", "latitude")]) pcaZ <- espace_pca(sp.name1, sp.name2, occsExt.z1, occsExt.z2, bgExt.z1, bgExt.z2) ## End(Not run)
The function generates a BIOCLIM model using ENMeval 2.0
model_bioclim(occs, bg, user.grp, bgMsk, logger = NULL, spN = NULL)model_bioclim(occs, bg, user.grp, bgMsk, logger = NULL, spN = NULL)
occs |
data frame of cleaned or processed occurrences obtained from components occs: Obtain occurrence data or, poccs: Process occurrence data. |
bg |
coordinates of background points to be used for modeling. |
user.grp |
a list of two vectors containing group assignments for occurrences (occs.grp) and background points (bg.grp). |
bgMsk |
a RasterStack or a RasterBrick of environmental layers cropped and masked to match the provided background extent. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
spN |
character. Species name to be used for all logger messages. |
The function generates a model in ENMeval using a user provided partition of occurrences from previous components in the GUI.
Function returns an ENMevaluate object with all the evaluated models and a selection of appropriate fields.
Jamie M. Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
## Not run: envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) occs <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace")) bg <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv", package = "wallace")) partblock <- part_partitionOccs(occs, bg, method = 'block') m <- model_bioclim(occs, bg, partblock, envs) ## End(Not run)## Not run: envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) occs <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace")) bg <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv", package = "wallace")) partblock <- part_partitionOccs(occs, bg, method = 'block') m <- model_bioclim(occs, bg, partblock, envs) ## End(Not run)
This functions generates maxent.jar or maxnet models using ENMeval 2.0 and user provided tuning parameters.
model_maxent( occs, bg, user.grp, bgMsk, rms, rmsStep, fcs, clampSel, algMaxent, catEnvs = NULL, parallel = FALSE, numCores = NULL, logger = NULL, spN = NULL )model_maxent( occs, bg, user.grp, bgMsk, rms, rmsStep, fcs, clampSel, algMaxent, catEnvs = NULL, parallel = FALSE, numCores = NULL, logger = NULL, spN = NULL )
occs |
data frame of cleaned or processed occurrences obtained from components occs: Obtain occurrence data or, poccs: Process occurrence data. |
bg |
coordinates of background points to be used for modeling. |
user.grp |
a list of two vectors containing group assignments for occurrences (occs.grp) and background points (bg.grp). |
bgMsk |
a RasterStack or a RasterBrick of environmental layers cropped and masked to match the provided background extent. |
rms |
vector of range of regularization multipliers to be used in the ENMeval run. |
rmsStep |
step to be used when defining regularization multipliers to be used from the provided range. |
fcs |
feature classes to be tested in the ENMeval run. |
clampSel |
Boolean use of clamping in the model. |
algMaxent |
character. algorithm to be used in modeling. A selection of "maxnet" or "maxent.jar". |
catEnvs |
if categorical predictor variables are included must provide the names. |
parallel |
logical. Whether to use parallel in the generation of models. Default is FALSE |
numCores |
numeric. If using parallel how many cores to use. Default is NULL. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
spN |
character. Species name to be used for all logger messages. |
The function generates model in ENMeval using a user provided partition of occurrences from previous components in the GUI. User can activate clamping and input tuning arguments to be used for model building.
Function returns an ENMevaluate object with all the evaluated models and a selection of appropriate fields.
Jamie M. Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
## Not run: envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) occs <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace")) bg <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv", package = "wallace")) partblock <- part_partitionOccs(occs, bg, method = 'block') rms <- c(1:2) rmsStep <- 1 fcs <- c('L', 'LQ') m <- model_maxent(occs = occs, bg = bg, user.grp = partblock, bgMsk = envs, rms = rms, rmsStep, fcs, clampSel = TRUE, algMaxent = "maxnet", parallel = FALSE) ## End(Not run)## Not run: envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) occs <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace")) bg <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv", package = "wallace")) partblock <- part_partitionOccs(occs, bg, method = 'block') rms <- c(1:2) rmsStep <- 1 fcs <- c('L', 'LQ') m <- model_maxent(occs = occs, bg = bg, user.grp = partblock, bgMsk = envs, rms = rms, rmsStep, fcs, clampSel = TRUE, algMaxent = "maxnet", parallel = FALSE) ## End(Not run)
Queries a given database for occurrence data on the provided species
occs_queryDb( spNames, occDb, occNum = NULL, doCitations = FALSE, gbifUser = NULL, gbifEmail = NULL, gbifPW = NULL, RmUncertain = FALSE, logger = NULL )occs_queryDb( spNames, occDb, occNum = NULL, doCitations = FALSE, gbifUser = NULL, gbifEmail = NULL, gbifPW = NULL, RmUncertain = FALSE, logger = NULL )
spNames |
character. Species Latin name, with format "Genus species". |
occDb |
character. Biodiversity database to query; current choices are "gbif", "vertnet", and "BIEN" |
occNum |
numeric. Maximum number of occurrence records to return |
doCitations |
logical. Set TRUE to use 'occCite' to get a complete list of original data sources in a citable format |
gbifUser |
specify only if using 'occCite' with GBIF to get a complete list of original data sources in a citable format. This, as well as 'gbifEmail' and 'gbifPW' are constraints imposed by GBIF to obtain the complete set of metadata associated with occurrence records and is not stored or used by 'wallace' for any other purposes. |
gbifEmail |
specify only if using 'occCite' with GBIF to get a complete list of original data sources in a citable format. |
gbifPW |
specify only if using 'occCite' with GBIF to get a complete list of original data sources in a citable format. |
RmUncertain |
specify if occurrences without uncertainty information should be removed (default is FALSE) |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL |
This function is called by the module occs_queryDb to query a database for species occurrence records, subset to only those records with coordinates, remove records with duplicate coordinates, and select some columns with fields appropriate to studies in biogeography.
list of lists one list per species with occurrence records. Each individual species list with appropriate fields for analysis
Jamie Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
Hannah Owens
Andrea Paz <[email protected]>
## Not run: occs_queryDb(spName = "Bassaricyon alleni", occDb = "gbif", occNum = 10) ## End(Not run)## Not run: occs_queryDb(spName = "Bassaricyon alleni", occDb = "gbif", occNum = 10) ## End(Not run)
Load user database with species occurrence records. Returns a list of lists, one per species provided in database in each species list with a set of appropriate fields
occs_userOccs(txtPath, txtName, txtSep = ",", txtDec = ".", logger = NULL)occs_userOccs(txtPath, txtName, txtSep = ",", txtDec = ".", logger = NULL)
txtPath |
path to database including database name and extension |
txtName |
name of database without the extension. Database must have at least three columns named 'scientific_name', 'longitude', 'latitude' |
txtSep |
field separator used in database (as in read.delim) |
txtDec |
decimal separator used for coordinates in database |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL |
This function is called by the module occs_queryDb to load a user provided database for species occurrence records, subset to only those records with coordinates, remove records with duplicate coordinates, and select some columns with fields appropriate to studies in biogeography.
List of lists. One list per species with occurrence records. Each individual species list with appropriate fields for analysis
Jamie Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
txtPath <- system.file("extdata/Bassaricyon_alleni.csv", package = "wallace") txtName <- 'Bassaricyon_alleni' user.occs <- occs_userOccs(txtPath, txtName)txtPath <- system.file("extdata/Bassaricyon_alleni.csv", package = "wallace") txtName <- 'Bassaricyon_alleni' user.occs <- occs_userOccs(txtPath, txtName)
This function partitions occurrence data and background points according to a user-selected method.
part_partitionOccs( occs, bg, method, kfolds = NULL, bgMask = NULL, aggFact = NULL, logger = NULL, spN = NULL )part_partitionOccs( occs, bg, method, kfolds = NULL, bgMask = NULL, aggFact = NULL, logger = NULL, spN = NULL )
occs |
data frame of cleaned or processed occurrences obtained from components occs: Obtain occurrence data or, poccs: Process occurrence data. |
bg |
coordinates of background points to be used for modeling. |
method |
character. Partitioning method to be used, one of 5 options: |
kfolds |
numeric. Number of partitions to create if selected method is random k-fold (must be >=2). If other method then keep default of NULL. |
bgMask |
a RasterStack or a RasterBrick of environmental layers cropped and masked. |
aggFact |
numeric. Aggregation factor to be used when using checkerboard partition (must be >= 1). |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
spN |
data frame of cleaned occurrences obtained from component occs: Obtain occurrence data. Used to obtain species name for logger messages. |
This function is used in the partition occurrence data component. A user-selected method is used to partition occurrence and background points into different groups for model testing. A list of group assignments for both occurrences and background points is returned.
A list of two vectors containing group assignments for occurrences (occs.grp) and background points (bg.grp).
Jamie Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
Andrea Paz <[email protected]>
## Not run: envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) occs <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace")) bg <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv", package = "wallace")) partblock <- part_partitionOccs(occs, bg, method = 'rand', kfold = 4) ## End(Not run)## Not run: envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) occs <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace")) bg <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv", package = "wallace")) partblock <- part_partitionOccs(occs, bg, method = 'rand', kfold = 4) ## End(Not run)
This function generates a background area according to a user- provided method.
penvs_bgExtent(occs, bgSel, bgBuf, logger = NULL, spN = NULL)penvs_bgExtent(occs, bgSel, bgBuf, logger = NULL, spN = NULL)
occs |
data frame of cleaned or processed occurrences obtained from components occs: Obtain occurrence data or, poccs: Process occurrence data. |
bgSel |
character. Method of background building. Must be one of three options: 'bounding box' , 'point buffers' or ' minimum convex polygon'. |
bgBuf |
numeric. Buffer distance in degrees to be used in the building of the background area. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
spN |
data frame of cleaned occurrences obtained from component occs: Obtain occurrence data. Used to obtain species name for logger messages. |
This function is used in the select study region component. Here, the user can select between three methods ('bounding box', 'point buffers' or ' minimum convex polygon') to determine the background extent based on the observed occurrences. The function returns a SpatialPolygonsDataFrame object of the desired extent.
A SpatialPolygons object that contains all occurrences from occs
Jamie Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
Bethany A. Johnson <[email protected]>
penvs_userBgExtent, penvs_drawBgExtent,
penvs_bgMask , penvs_bgSample
occs <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace"))[, 2:3] occs$occID <- 1:nrow(occs) bgExt <- penvs_bgExtent(occs, bgSel = 'bounding box', bgBuf = 0.5)occs <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace"))[, 2:3] occs$occID <- 1:nrow(occs) bgExt <- penvs_bgExtent(occs, bgSel = 'bounding box', bgBuf = 0.5)
This functions crops and masks the environmental data to the provided background area.
penvs_bgMask(occs, envs, bgExt, logger = NULL, spN = NULL)penvs_bgMask(occs, envs, bgExt, logger = NULL, spN = NULL)
occs |
data frame of cleaned or processed occurrences obtained from components occs: Obtain occurrence data or, poccs: Process occurrence data. |
envs |
a RasterStack or RasterBrick of environmental layers to be processed. This determines the output type. |
bgExt |
a SpatialPolygonsDataFrame with the background area to be used for processing. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
spN |
species name to be used for all logger messages |
This function is used in the select study region component. Here, the environmental layers to be used in the modeling are cropped and masked to the provided background area. The background area is determined in the function penvs_bgExtent from the same component. The function returns the provided environmental layers cropped and masked in the provided format (either a rasterBrick or a rasterStack).
A RasterStack or a RasterBrick of environmental layers cropped and masked to match the provided background extent.
Jamie Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
penvs_userBgExtent,
penvs_drawBgExtent, penvs_bgExtent,
penvs_bgSample
## Not run: occs <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace"))[, 2:3] occs$occID <- 1:nrow(occs) envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) bgExt <- penvs_bgExtent(occs, bgSel = 'bounding box', bgBuf = 0.5) bgMask <- penvs_bgMask(occs, envs, bgExt) ## End(Not run)## Not run: occs <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace"))[, 2:3] occs$occID <- 1:nrow(occs) envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) bgExt <- penvs_bgExtent(occs, bgSel = 'bounding box', bgBuf = 0.5) bgMask <- penvs_bgMask(occs, envs, bgExt) ## End(Not run)
This function samples background points from an area determined by a rasterBrick or RasterStack of environmental layers previously cropped and masked to user determined extent.
penvs_bgSample(occs, bgMask, bgPtsNum, logger = NULL, spN = NULL)penvs_bgSample(occs, bgMask, bgPtsNum, logger = NULL, spN = NULL)
occs |
data frame of cleaned or processed occurrences obtained from components occs: Obtain occurrence data or, poccs: Process occurrence data. |
bgMask |
a RasterStack or a RasterBrick of environmental layers cropped and masked. |
bgPtsNum |
numeric. Number of points to be sampled from the area, they will be sampled as long as <= non NA cells in any reference layer. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
spN |
data frame of cleaned occurrences obtained from component occs: Obtain occurrence data. Used to obtain species name for logger messages. |
This function is used in the select study region component. Here, a user provided amount of points is randomly sampled from the RasterBrick or RasterStack of environmental variables cropped and masked to a given background extent. The maximum number of points to be sampled is the number of non NA cells in each layer of the reference RasterBrick or RasterStack If the requested number of points is larger than the number of cells in the reference RasterBrick or RasterStack then only a proportion of the requested will be returned.
a dataframe containing point coordinates (longitude and latitude). All points are within the area provided in the RasterBrick or RasterStack (bgMask). Maximum number of points is equal to non NA cells in each layer of the reference brick or stack.
Jamie Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
penvs_bgMask, penvs_bgExtent
penvs_userBgExtent, penvs_drawBgExtent,
randomPoints
## Not run: occs <- occs_queryDb(spName = "Panthera onca", occDb = "gbif", occNum = 100) occs <- as.data.frame(occs[[1]]$cleaned) envs <- envs_worldclim(bcRes = 10, bcSel = c("bio03", "bio04", "bio13", "bio14"), doBrick = TRUE) bgExt <- penvs_bgExtent(occs, bgSel = 'bounding box', bgBuf = 0.5) bgMask <- penvs_bgMask(occs, envs, bgExt) bgsample <- penvs_bgSample(occs, bgMask, bgPtsNum = 1000) ## End(Not run)## Not run: occs <- occs_queryDb(spName = "Panthera onca", occDb = "gbif", occNum = 100) occs <- as.data.frame(occs[[1]]$cleaned) envs <- envs_worldclim(bcRes = 10, bcSel = c("bio03", "bio04", "bio13", "bio14"), doBrick = TRUE) bgExt <- penvs_bgExtent(occs, bgSel = 'bounding box', bgBuf = 0.5) bgMask <- penvs_bgMask(occs, envs, bgExt) bgsample <- penvs_bgSample(occs, bgMask, bgPtsNum = 1000) ## End(Not run)
This function generates a background area according to a user drawn polygon and provided buffer.
penvs_drawBgExtent( polyExtXY, polyExtID, drawBgBuf, occs, logger = NULL, spN = NULL )penvs_drawBgExtent( polyExtXY, polyExtID, drawBgBuf, occs, logger = NULL, spN = NULL )
polyExtXY |
coordinates of polygon endpoints obtained from user drawn polygon in GUI. |
polyExtID |
numeric. ID to be used in the generation of the polygon. |
drawBgBuf |
the buffer to be used in generating the SpatialPolygonsDataFrame, maybe be 0 or >0. A number must be specified. |
occs |
data frame of cleaned or processed occurrences obtained from components occs: Obtain occurrence data or, poccs: Process occurrence data. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
spN |
data frame of cleaned occurrences obtained from component occs: Obtain occurrence data. Used to obtain species name for logger messages. |
This function is used in the select study region component. Here, in the GUI, the user draws a polygon to be used as the background extent and may include a buffer to the given polygon. The buffered poylgon must include all occurrences (occs) or function will return an error. The function returns a SpatialPolygonsDataFrame object of the desired extent (+ buffer).
This functions returns a SpatialPolygons object based on the user specified coordinates (drawn on map). This SpatialPolygons object may be larger than specified if drawBgBuf > 0. The SpatialPolygons object will include all occurrences.
Jamie Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
Bethany A. Johnson <[email protected]>
penvs_userBgExtent, penvs_bgExtent,
penvs_bgMask , penvs_bgSample
occs <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace"))[, 2:3] occs$occID <- 1:nrow(occs) longitude <- c(-27.78641, -74.09170, -84.01930, -129.74867, -142.19085, -45.55045, -28.56050) latitude <- c(-40.40539, -37.02010, 2.28455, 40.75350, 56.35954, 54.55045, -7.11861) expertDrawPoly <- matrix(c(longitude, latitude), byrow = FALSE, ncol = 2) drawBgBf <- penvs_drawBgExtent(polyExtXY = expertDrawPoly, polyExtID = 1, drawBgBuf = 0.5, occs)occs <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace"))[, 2:3] occs$occID <- 1:nrow(occs) longitude <- c(-27.78641, -74.09170, -84.01930, -129.74867, -142.19085, -45.55045, -28.56050) latitude <- c(-40.40539, -37.02010, 2.28455, 40.75350, 56.35954, 54.55045, -7.11861) expertDrawPoly <- matrix(c(longitude, latitude), byrow = FALSE, ncol = 2) drawBgBf <- penvs_drawBgExtent(polyExtXY = expertDrawPoly, polyExtID = 1, drawBgBuf = 0.5, occs)
This function generates a background area according to a user provided polygon and buffer.
penvs_userBgExtent( bgShp_path, bgShp_name, userBgBuf, occs, logger = NULL, spN = NULL )penvs_userBgExtent( bgShp_path, bgShp_name, userBgBuf, occs, logger = NULL, spN = NULL )
bgShp_path |
path to the user provided shapefile or csv with vertex coordinates. |
bgShp_name |
name of the user provided shapefile or csv with vertex coordinates. |
userBgBuf |
buffer to be used in creating the background extent must be >= 0. |
occs |
data frame of cleaned or processed occurrences obtained from components occs: Obtain occurrence data or, poccs: Process occurrence data. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
spN |
Species name. |
This function is used in the select study region component. Here, the user provides either a shapefile or a csv with vertex coordinates with the desired shape for the background extent, the user may include a buffer to the given polygon. The buffered polygon must include all occurrences (occs) or function will return an error. The function returns a SpatialPolygons object of the desired extent (+ buffer).
This function returns a SpatialPolygons object with the user provided shape (+ a buffer if userBgBuf >0). The polygon will be at least large enough to contain all occurrences.
Jamie Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
Andrea Paz <[email protected]>
Bethany A. Johnson <[email protected]>
penvs_drawBgExtent, penvs_bgExtent,
penvs_bgMask , penvs_bgSample
occs <- read.csv(system.file("extdata/Bassaricyon_neblina.csv", package = "wallace"))[, 2:3] occs$occID <- 1:nrow(occs) pathShp <- list.files(system.file("extdata/shp", package = "wallace"), full.names = TRUE) nameShp <- list.files(system.file("extdata/shp", package = "wallace"), full.names = FALSE) userBgbf <- penvs_userBgExtent(bgShp_path = pathShp, bgShp_name = nameShp, userBgBuf = 0.2, occs = occs)occs <- read.csv(system.file("extdata/Bassaricyon_neblina.csv", package = "wallace"))[, 2:3] occs$occID <- 1:nrow(occs) pathShp <- list.files(system.file("extdata/shp", package = "wallace"), full.names = TRUE) nameShp <- list.files(system.file("extdata/shp", package = "wallace"), full.names = FALSE) userBgbf <- penvs_userBgExtent(bgShp_path = pathShp, bgShp_name = nameShp, userBgBuf = 0.2, occs = occs)
This function removes user selected occurrences by ID.
poccs_removeByID(occs, removeID, logger = NULL, spN = NULL)poccs_removeByID(occs, removeID, logger = NULL, spN = NULL)
occs |
data frame of cleaned occurrences obtained from component occs: Obtain occurrence data |
removeID |
the ID of the occurrence to be removed from the occurrences dataframe. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL |
spN |
data frame of cleaned occurrences obtained from component occs: Obtain occurrence data. Used to obtain species name for logger messages. |
This function is called by the remove occurrences by ID module. It allows for removal of a single occurrence flagged by the user on the map. The function will return a data frame of occurrences with all relevant columns for further analyses and without the occurrence selected by the user.
A new occurence dataframe without the user selected occurrence mantaining all columns from original dataframe for further analyses.
Jamie Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
occs <- read.csv(system.file("extdata/Bassaricyon_neblina.csv", package = "wallace"))[, 2:3] occs$occID <- 1:nrow(occs) out.ID <- poccs_removeByID(occs, 11)occs <- read.csv(system.file("extdata/Bassaricyon_neblina.csv", package = "wallace"))[, 2:3] occs$occID <- 1:nrow(occs) out.ID <- poccs_removeByID(occs, 11)
This function removes occurrences outside of a user created polygon.
poccs_selectOccs(occs, polySelXY, polySelID = 1, logger = NULL, spN = NULL)poccs_selectOccs(occs, polySelXY, polySelID = 1, logger = NULL, spN = NULL)
occs |
data frame of cleaned occurrences obtained from component occs: Obtain occurrence data. |
polySelXY |
matrix of longitude and latitude describing the expert drawn polygon. |
polySelID |
numeric. Polygon ID to be used in SpatialPolygons creation, defaults to 1. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
spN |
data frame of cleaned occurrences obtained from component occs: Obtain occurrence data. Used to obtain species name for logger messages. |
This function is called by the select occurrences on map module. It allows for removal of occurrences outside the user drawn polygon in the map. The function will return a data frame of occurrences with all relevant columns for further analyses and without the occurrences outside of the polygon.
A new occurence dataframe including only occurences inside the provided polygon and mantaining all columns from original dataframe for further analyses.
Jamie Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
occs <- read.csv(system.file("extdata/Bassaricyon_neblina.csv", package = "wallace"))[, 2:3] occs$occID <- 1:nrow(occs) longitude <- c(-71.58400, -78.81300, -79.34034, -69.83331, -66.47149, -66.71319, -71.11931) latitude <- c(13.18379, 7.52315, 0.93105, -1.70167, 0.98391, 6.09208, 12.74980) expertAddedPoly <- matrix(c(longitude, latitude), byrow = FALSE, ncol = 2) out.occs <- poccs_selectOccs(occs, polySelXY = expertAddedPoly, polySelID = 1)occs <- read.csv(system.file("extdata/Bassaricyon_neblina.csv", package = "wallace"))[, 2:3] occs$occID <- 1:nrow(occs) longitude <- c(-71.58400, -78.81300, -79.34034, -69.83331, -66.47149, -66.71319, -71.11931) latitude <- c(13.18379, 7.52315, 0.93105, -1.70167, 0.98391, 6.09208, 12.74980) expertAddedPoly <- matrix(c(longitude, latitude), byrow = FALSE, ncol = 2) out.occs <- poccs_selectOccs(occs, polySelXY = expertAddedPoly, polySelID = 1)
The function thins the observed occurrences by a user provided distance.
poccs_thinOccs(occs, thinDist, logger = NULL, spN = NULL)poccs_thinOccs(occs, thinDist, logger = NULL, spN = NULL)
occs |
data frame of cleaned occurrences obtained from component occs: Obtain occurrence data |
thinDist |
distance in kilometers to be used for thinning. Number must be positive. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
spN |
data frame of cleaned occurrences obtained from component occs: Obtain occurrence data. Used to obtain species name for logger messages. |
This function is called by the component poccs: process occurrence data to thin the occurrence data to a user specified distance. Providing an output with preserved columns appropriate for further analyses and a maximized number of occurrences that are separated by at least the provided distance.
Output is a data frame of thinned occurences (all occurences at a distance >thinDist) with the same columns as occs
Jamie Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
occs <- read.csv(system.file("extdata/Bassaricyon_neblina.csv", package = "wallace")) occs$occID <- 1:nrow(occs) out.thin <- poccs_thinOccs(occs = occs, thinDist = 30)occs <- read.csv(system.file("extdata/Bassaricyon_neblina.csv", package = "wallace")) occs$occID <- 1:nrow(occs) out.thin <- poccs_thinOccs(occs = occs, thinDist = 30)
Before running the Wallace application with run_wallace(), you can
register your own modules to be used in Wallace.
register_module(config_file)register_module(config_file)
config_file |
The path to a YAML file that contains the information about one or more modules. |
This function runs the Wallace application in the user's default web browser.
run_wallace(launch.browser = TRUE, port = getOption("shiny.port"))run_wallace(launch.browser = TRUE, port = getOption("shiny.port"))
launch.browser |
Whether or not to launch a new browser window. |
port |
The port for the shiny server to listen on. Defaults to a random available port. |
Please see the official website (https://wallaceecomod.github.io/) for more details. If you have questions about the application, please participate in the Google Group, or email the team directly: [email protected].
Jamie Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
if(interactive()) { run_wallace() }if(interactive()) { run_wallace() }
This functions creates a bivariate plot with two of the environmental variables used for modeling as x and y axes and occurrences as observations.
vis_bioclimPlot(x, a = 1, b = 2, p = 0.9)vis_bioclimPlot(x, a = 1, b = 2, p = 0.9)
x |
bioclim model including values for each environmental layer at each occurrence point |
a |
numeric Environmental layer to be used as x axis. Default is layer 1. |
b |
numeric. Environmental layer to be used as x axis. Default is layer 2. |
p |
numeric. (0-1) percentile distribution to be used for plotting envelope and showing points outside of envelope. Default is 0.9 |
This is a bivariate plot with x and y axes representing two of the environmental layers used for modeling (user selected although 1 and 2 as default). Occurrences used for modeling are shown with differential visualization if they are outside of the selected percentile distribution (for any variable). Plot also includes a rectangle representing the bivariate bioclimatic envelope according to a provided percentile.
A bivariate plot of environmental values for occurrences. Includes a blue rectangle representing the bioclimatic envelope given p. Occurrences that are inside the envelope for all layers (included those not plotted) are shown as green circles and those outside of the envelope for one ore more variables are plotted as orange triangles.
Jamie Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
## Not run: envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) occs <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace")) bg <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv", package = "wallace")) partblock <- part_partitionOccs(occs, bg, method = 'block') m <- model_bioclim(occs, bg, partblock, envs) bioclimPlot <- vis_bioclimPlot(x = m@models$bioclim, a = 1, b = 2, p = 1) ## End(Not run)## Not run: envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) occs <- read.csv(system.file("extdata/Bassaricyon_alleni.csv", package = "wallace")) bg <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv", package = "wallace")) partblock <- part_partitionOccs(occs, bg, method = 'block') m <- model_bioclim(occs, bg, partblock, envs) bioclimPlot <- vis_bioclimPlot(x = m@models$bioclim, a = 1, b = 2, p = 1) ## End(Not run)
Function transfers the model generated in previous components to a new user drawn area.
xfer_area( evalOut, curModel, envs, xfExt, alg, outputType = NULL, clamp = NULL, logger = NULL, spN = NULL )xfer_area( evalOut, curModel, envs, xfExt, alg, outputType = NULL, clamp = NULL, logger = NULL, spN = NULL )
evalOut |
ENMevaluate output from previous module and using any of the available algorithms. |
curModel |
If algorithm is maxent, model selected by user as best or optimal, in terms of feature class and regularization multiplier (e.g 'L_1'). Else must be 1. |
envs |
environmental layers to be used for transferring the model. They must match the layers used for generating the model in the model component. |
xfExt |
extent of the area to transfer the model. This is defined by the user in the map of the GUI and is provided as a SpatialPolygons object. |
alg |
character. modeling algorithm used in the model component. Can be one of : 'BIOCLIM', 'maxent.jar' or 'maxnet'. |
outputType |
output type to be used when algorithm is maxnet or maxent.jar. |
clamp |
logical. Whether transfer will be of clamped or unclamped model. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
spN |
Character used to obtain species name for logger messages |
This functions transfers the model created in previous components to a new area. The area of transfer is user provided in the map of the GUI. The model will be transferred to the new area as long as the environmental variables are available for the area. This function returns a list including the cropped environmental variables used for transferring and the transferred model.
A list of two elements: xferExt and xferArea. The first is a RasterBrick or a RasterStack of the environmental variables cropped to the area of transfer. The second element is a raster of the transferred model with the specified output type.
Jamie Kass <[email protected]>
Andrea Paz <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
Bethany A. Johnson <[email protected]>
predict, xfer_time
xfer_userEnvs
## Not run: envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) # extent of transfer longitude <- c(-71.58400, -78.81300, -79.34034, -69.83331, -66.47149, -66.71319, -71.11931) latitude <- c(13.18379, 7.52315, 0.93105, -1.70167, 0.98391, 6.09208, 12.74980) selCoords <- matrix(c(longitude, latitude), byrow = FALSE, ncol = 2) polyExt <- sp::SpatialPolygons(list(sp::Polygons(list(sp::Polygon(selCoords)), ID = 1))) # load model m <- readRDS(system.file("extdata/model.RDS", package = "wallace")) modXfer <- xfer_area(evalOut = m, curModel = 1, envs, outputType = 'cloglog', alg = 'maxent.jar', clamp = TRUE, xfExt = polyExt) ## End(Not run)## Not run: envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) # extent of transfer longitude <- c(-71.58400, -78.81300, -79.34034, -69.83331, -66.47149, -66.71319, -71.11931) latitude <- c(13.18379, 7.52315, 0.93105, -1.70167, 0.98391, 6.09208, 12.74980) selCoords <- matrix(c(longitude, latitude), byrow = FALSE, ncol = 2) polyExt <- sp::SpatialPolygons(list(sp::Polygons(list(sp::Polygon(selCoords)), ID = 1))) # load model m <- readRDS(system.file("extdata/model.RDS", package = "wallace")) modXfer <- xfer_area(evalOut = m, curModel = 1, envs, outputType = 'cloglog', alg = 'maxent.jar', clamp = TRUE, xfExt = polyExt) ## End(Not run)
This function creates a polygon object from coordinates of user drawn poylgon in the GUI.
xfer_draw(polyXfXY, polyXfID, drawXfBuf, logger = NULL, spN = NULL)xfer_draw(polyXfXY, polyXfID, drawXfBuf, logger = NULL, spN = NULL)
polyXfXY |
coordinates of polygon endpoints obtained from user drawn polygon |
polyXfID |
numeric .ID to be used in the generation of the polygon |
drawXfBuf |
the buffer to be used in generating the SpatialPolygonsDataFrame, must be >=0 . A number must be specified. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL |
spN |
character. Used to obtain species name for logger messages |
This function is used in the transfer model component. In the GUI, the user draws a polygon to be used as the extent of transfer and may include a buffer to the given polygon. The function returns a SpatialPolygonsDataFrame object of the desired extent (+ buffer).
This functions returns a SpatialPolygons object based on the user specified coordinates (drawn on map). This SpatialPolygonsDataFrame may be larger than specified if drawBgBuf > 0.
Gonzalo Pinilla <[email protected]>
Bethany A. Johnson <[email protected]>
longitude <- c(-27.78641, -74.09170, -84.01930, -129.74867, -142.19085, -45.55045, -28.56050) latitude <- c(-40.40539, -37.02010, 2.28455, 40.75350, 56.35954, 54.55045, -7.11861) userDrawPoly <- matrix(c(longitude, latitude), byrow = FALSE, ncol = 2) drawXfBuf <- 0.5 polyXfID <- 1 polygonTest <- xfer_draw(polyXfXY = userDrawPoly, polyXfID, drawXfBuf)longitude <- c(-27.78641, -74.09170, -84.01930, -129.74867, -142.19085, -45.55045, -28.56050) latitude <- c(-40.40539, -37.02010, 2.28455, 40.75350, 56.35954, 54.55045, -7.11861) userDrawPoly <- matrix(c(longitude, latitude), byrow = FALSE, ncol = 2) drawXfBuf <- 0.5 polyXfID <- 1 polygonTest <- xfer_draw(polyXfXY = userDrawPoly, polyXfID, drawXfBuf)
This function generates a MESS map for the new variables for transferring based on variables and points used for modeling in previous components.
xfer_mess(occs, bg, bgMsk, xferExtRas, logger = NULL, spN = NULL)xfer_mess(occs, bg, bgMsk, xferExtRas, logger = NULL, spN = NULL)
occs |
a data frame of occurrences used for modeling and values of environmental variables for each point. |
bg |
a data frame of points used as background for modeling and values of environmental variables for each point. |
bgMsk |
a rasterBrick or rasterStack of environmental variables used for modeling. They must be cropped and masked to extent used in model training. |
xferExtRas |
a rasterStack or rasterBrick of environmental variables to be used for transferring. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
spN |
character. Used to obtain species name for logger messages |
This functions allows for the creation of a MESS map for the new provided variables for transferring. These variables are either user uploaded or selected from WorldClim database. MESS map is based on occurrence and background points used for generating the model and the environmental values at those points.
Jamie Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
## Not run: envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) # load model m <- readRDS(system.file("extdata/model.RDS", package = "wallace")) occsEnvs <- m@occs bgEnvs <- m@bg envsFut <- list.files(path = system.file('extdata/wc/future', package = "wallace"), full.names = TRUE) envsFut <- raster::stack(envsFut) ## run function xferMess <- xfer_mess(occs = occsEnvs, bg = bgEnvs, bgMsk = envs, xferExtRas = envsFut) ## End(Not run)## Not run: envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) # load model m <- readRDS(system.file("extdata/model.RDS", package = "wallace")) occsEnvs <- m@occs bgEnvs <- m@bg envsFut <- list.files(path = system.file('extdata/wc/future', package = "wallace"), full.names = TRUE) envsFut <- raster::stack(envsFut) ## run function xferMess <- xfer_mess(occs = occsEnvs, bg = bgEnvs, bgMsk = envs, xferExtRas = envsFut) ## End(Not run)
Function transfers the model generated in previous components to a new time and area using provided layers.
xfer_time( evalOut, curModel, envs, xfExt, alg, outputType = NULL, clamp = NULL, logger = NULL, spN = NULL )xfer_time( evalOut, curModel, envs, xfExt, alg, outputType = NULL, clamp = NULL, logger = NULL, spN = NULL )
evalOut |
ENMevaluate output from previous module and using any of the available algorithms. |
curModel |
if algorithm is maxent, model selected by user as best or optimal, in terms of feature class and regularization multiplier (e.g 'L_1'). Otherwise must be 1. |
envs |
environmental layers of different time to be used for transferring the model. They must match the layers used for generating the model in the model component. |
xfExt |
extent of the area to transfer the model. This is defined by the user in the map of the GUI and is provided as a SpatialPolygons object. |
alg |
modeling algorithm used in the model component. Can be one of: 'bioclim', 'maxent.jar' or 'maxnet'. |
outputType |
output type to be used when algorithm is maxnet or maxent.jar. |
clamp |
logical. Whether transfer will be of clamped or unclamped model. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
spN |
character. Used to obtain species name for logger messages. |
This functions allows transferring the model created in previous components to a new time and area. The area of transfer is user provided in the map of the GUI and the transfer time user selected. The model will be transferred to the new area and time as long as the environmental variables are available for the area. This function returns a list including the cropped environmental variables used for transferring and the transferred model.
A list of two elements: xferExt and xferTime. The first is a RasterBrick or RasterStack of the environmental variables cropped to the area of transfer. The second element is a raster of the transferred model with the specified output type.
Jamie Kass <[email protected]>
Andrea Paz <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
Bethany A. Johnson <[email protected]>
predict, xfer_time
xfer_userEnvs
## Not run: envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) ## extent to transfer # set coordinates longitude <- c(-71.58400, -78.81300, -79.34034, -69.83331, -66.47149, -66.71319, -71.11931) latitude <- c(13.18379, 7.52315, 0.93105, -1.70167, 0.98391, 6.09208, 12.74980) # generate matrix selCoords <- matrix(c(longitude, latitude), byrow = FALSE, ncol = 2) polyExt <- sp::SpatialPolygons(list(sp::Polygons(list(sp::Polygon(selCoords)), ID = 1))) # load model m <- readRDS(system.file("extdata/model.RDS", package = "wallace")) occsEnvs <- m@occs bgEnvs <- m@bg envsFut <- list.files(path = system.file('extdata/wc/future', package = "wallace"), full.names = TRUE) envsFut <- raster::stack(envsFut) modXfer <- xfer_time(evalOut = m, curModel = 1, envs = envsFut, alg = 'maxent.jar', xfExt = polyExt, clamp = FALSE, outputType = 'cloglog') ## End(Not run)## Not run: envs <- envs_userEnvs(rasPath = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = TRUE), rasName = list.files(system.file("extdata/wc", package = "wallace"), pattern = ".tif$", full.names = FALSE)) ## extent to transfer # set coordinates longitude <- c(-71.58400, -78.81300, -79.34034, -69.83331, -66.47149, -66.71319, -71.11931) latitude <- c(13.18379, 7.52315, 0.93105, -1.70167, 0.98391, 6.09208, 12.74980) # generate matrix selCoords <- matrix(c(longitude, latitude), byrow = FALSE, ncol = 2) polyExt <- sp::SpatialPolygons(list(sp::Polygons(list(sp::Polygon(selCoords)), ID = 1))) # load model m <- readRDS(system.file("extdata/model.RDS", package = "wallace")) occsEnvs <- m@occs bgEnvs <- m@bg envsFut <- list.files(path = system.file('extdata/wc/future', package = "wallace"), full.names = TRUE) envsFut <- raster::stack(envsFut) modXfer <- xfer_time(evalOut = m, curModel = 1, envs = envsFut, alg = 'maxent.jar', xfExt = polyExt, clamp = FALSE, outputType = 'cloglog') ## End(Not run)
The function transfers the model generated in previous components to user uploaded environmental variables.
xfer_userEnvs( evalOut, curModel, envs, xfExt, alg, outputType = NULL, clamp = NULL, logger = NULL, spN = NULL )xfer_userEnvs( evalOut, curModel, envs, xfExt, alg, outputType = NULL, clamp = NULL, logger = NULL, spN = NULL )
evalOut |
ENMevaluate output from previous module and using any of the available algorithms. |
curModel |
if algorithm is maxent, model selected by user as best or optimal, in terms of feature class and regularization multiplier (e.g 'L_1'). Otherwise it must be 1. |
envs |
user provided environmental layers (in raster format) to be used for transferring. |
xfExt |
extent of the area to transfer the model. This must be provided by the user as a shapefile or as a SpatialPolygons object. |
alg |
modeling algorithm used in the model component. Can be one of: 'BIOCLIM', 'maxent.jar' or 'maxnet'. |
outputType |
output type to be used when algorithm is maxnet or maxent.jar. |
clamp |
logical. Whether transfer will be of clamped or unclamped model. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
spN |
character. Used to obtain species name for logger messages. |
This functions allows transferring the model created in previous components to a new time and area provided by the user. The transferring time and area is user-provided. The model will be transferred to the new time and area as long as the environmental variables provided are available for the area and match the variables used for model building. This function returns a list including the cropped environmental variables used for transferring and the transferred model.
Jamie Kass <[email protected]>
Andrea Paz <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
Bethany A. Johnson <[email protected]>
predict, xfer_time
xfer_userExtent
## Not run: ## extent to transfer # set coordinates longitude <- c(-71.58400, -78.81300, -79.34034, -69.83331, -66.47149, -66.71319, -71.11931) latitude <- c(13.18379, 7.52315, 0.93105, -1.70167, 0.98391, 6.09208, 12.74980) # generate matrix selCoords <- matrix(c(longitude, latitude), byrow = FALSE, ncol = 2) polyExt <- sp::SpatialPolygons(list(sp::Polygons(list(sp::Polygon(selCoords)), ID = 1))) # load model m <- readRDS(system.file("extdata/model.RDS", package = "wallace")) envsFut <- list.files(path = system.file('extdata/wc/future', package = "wallace"), full.names = TRUE) envsFut <- raster::stack(envsFut) ### run function modXfer <- xfer_userEnvs(evalOut = m, curModel = 1, envs = envsFut, outputType = "cloglog", alg = "maxent.jar", clamp = FALSE, xfExt = polyExt) ## End(Not run)## Not run: ## extent to transfer # set coordinates longitude <- c(-71.58400, -78.81300, -79.34034, -69.83331, -66.47149, -66.71319, -71.11931) latitude <- c(13.18379, 7.52315, 0.93105, -1.70167, 0.98391, 6.09208, 12.74980) # generate matrix selCoords <- matrix(c(longitude, latitude), byrow = FALSE, ncol = 2) polyExt <- sp::SpatialPolygons(list(sp::Polygons(list(sp::Polygon(selCoords)), ID = 1))) # load model m <- readRDS(system.file("extdata/model.RDS", package = "wallace")) envsFut <- list.files(path = system.file('extdata/wc/future', package = "wallace"), full.names = TRUE) envsFut <- raster::stack(envsFut) ### run function modXfer <- xfer_userEnvs(evalOut = m, curModel = 1, envs = envsFut, outputType = "cloglog", alg = "maxent.jar", clamp = FALSE, xfExt = polyExt) ## End(Not run)
This function generates an area of transfer according to a user provided polygon and buffer.
xfer_userExtent(bgShp_path, bgShp_name, userBgBuf, logger = NULL, spN = NULL)xfer_userExtent(bgShp_path, bgShp_name, userBgBuf, logger = NULL, spN = NULL)
bgShp_path |
path to the user provided shapefile or csv with vertex coordinates. |
bgShp_name |
name of the user provided shapefile or csv with vertex coordinates. |
userBgBuf |
numeric. Buffer to be used in creating the background extent must be >= 0. |
logger |
Stores all notification messages to be displayed in the Log Window of Wallace GUI. Insert the logger reactive list here for running in shiny, otherwise leave the default NULL. |
spN |
data frame of cleaned occurrences obtained from component occs: Obtain occurrence data. Used to obtain species name for logger messages. |
This function is used in the transfer component. Here, the user provides either a shapefile or a csv with vertex coordinates with the desired shape for the extent of transfer, the user may include a buffer to the given polygon. The function returns a SpatialPolygons object of the desired extent (+ buffer).
This function returns a SpatialPolygons object with the user provided shape (+ a buffer is userBgBuf >0).
Jamie Kass <[email protected]>
Gonzalo E. Pinilla-Buitrago <[email protected]>
Andrea Paz <[email protected]>
Bethany A. Johnson <[email protected]>
penvs_drawBgExtent, penvs_bgExtent,
penvs_bgMask , penvs_bgSample
pathShp <- list.files(system.file("extdata/shp", package = "wallace"), full.names = TRUE) nameShp <- list.files(system.file("extdata/shp", package = "wallace"), full.names = FALSE) xferUser <- xfer_userExtent(bgShp_path = pathShp, bgShp_name = nameShp, userBgBuf = 1)pathShp <- list.files(system.file("extdata/shp", package = "wallace"), full.names = TRUE) nameShp <- list.files(system.file("extdata/shp", package = "wallace"), full.names = FALSE) xferUser <- xfer_userExtent(bgShp_path = pathShp, bgShp_name = nameShp, userBgBuf = 1)