Wallace: A modular platform for reproducible ecological modeling

Description

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.

Details

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: wallaceEcoMod@gmail.com.

clearAll

Description

For internal use. Clean everything in leaflet map.

Usage

clearAll(map)

Arguments

Create a Wallace module

Description

Create the template of a new Wallace module.

Usage

create_module(id, dir, map = FALSE, result = FALSE, rmd = FALSE, save = FALSE)

Arguments

See Also

register_module

ecoClimate_getdata

Description

download ecoClimate layers. more info at www.ecoclimate.org

Usage

ecoClimate_getdata(AOGCM, Baseline, Scenario, logger)

Arguments

Examples

## Not run: 
CCSM_mod_present <- ecoclimate_getdata("CCSM", "Modern", "Present")
dev.new()
plot(CCSM_mod_present)

## End(Not run)

ecoClimate_select

Description

select which bioclimatic variables and set the extent you want (crop the raster stack to your study extent)

Usage

ecoClimate_select(map_climate, Sels=c(1:19), extent=c(-180, 180, -90, 90))

Arguments

Examples

## 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)

ecospat.plot.nicheDEV

Description

For internal use. Plot occ density

Usage

ecospat.plot.nicheDEV(
  z,
  title = "",
  name.axis1 = "Axis 1",
  name.axis2 = "Axis 2",
  cor = FALSE
)

Arguments

envs_ecoClimate Obtain ecoClimate variables

Description

download ecoClimate variables. See www.ecoclimate.org.

Usage

envs_ecoClimate(bcAOGCM, bcScenario, ecoClimSel, logger = NULL)

Arguments

Details

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.

Value

A rasterStack of selected variables

Author(s)

Sara Varela <sara_varela@yahoo.com>

Jamie M. Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Examples

bcAOGCM <- "CCSM"
bcScenario <- "LGM"
ecoClimSel <- c(1,2,3)
## Not run: 
varsEcoClimate <- envs_ecoClimate(bcAOGCM, bcScenario, ecoClimSel)

## End(Not run)

envs_userEnvs

Description

Load user provided rasters

Usage

envs_userEnvs(rasPath, rasName, doBrick = FALSE, logger = NULL)

Arguments

Details

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.

Value

A rasterStack or a rasterBrick (if doBrick = TRUE) of user provided rasters

Author(s)

Jamie Kass <jamie.m.kass@gmail.com >

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Examples

## 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)

envs_worldclim Obtain WorldClim variables

Description

download WorldClim variables. See www.worldclim.com.

Usage

envs_worldclim(bcRes, bcSel, mapCntr, doBrick = FALSE, logger = NULL)

Arguments

Details

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.

Value

A rasterStack or a rasterBrick (if doBrick=TRUE) of downloaded worldclim rasters at the requested resolution.

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Bethany A. Johnson <bjohnso005@citymail.cuny.edu>

See Also

worldclim_global, worldclim_tile

Examples

## Not run: 
bcRes <- 10 # (10 arcmin)
envar <- c('bio05', 'bio06', 'bio13', 'bio14')
arcmin10 <- envs_worldclim(bcRes, bcSel = envar)

## End(Not run)

espace_nicheOv Niche Overlap

Description

Function evaluates niche overlap between the two species for which the occurrence density grid was computed

Usage

espace_nicheOv(
  z1,
  z2,
  iter = 100,
  equivalency = FALSE,
  similarity = TRUE,
  logger = NULL
)

Arguments

Details

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.

Value

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.

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Olivier Broennimann <olivier.broennimann@unil.ch>

See Also

espace_pca espace_occDens ecospat.niche.overlap ecospat.niche.dyn.index ecospat.niche.equivalency.test ecospat.niche.similarity.test

Examples

## 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)

Occurrence density grid

Description

calculates the part of environmental space more densely populated by species & the availability of environmental conditions in the background

Usage

espace_occDens(sp.name1, sp.name2, pca, logger = NULL)

Arguments

Details

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.

Value

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.

Author(s)

Jamie Kass <jamie.m.kass@gmail.com >

Olivier Broennimann <olivier.broennimann@unil.ch>

See Also

espace_pca espace_nicheOv ecospat.grid.clim.dyn

Examples

## 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)

espace_pca Principal component analysis

Description

Principal component analysis to reduce dimensionality of environmental space

Usage

espace_pca(
  sp.name1,
  sp.name2 = NULL,
  occs.z1,
  occs.z2 = NULL,
  bgPts.z1,
  bgPts.z2 = NULL,
  logger = NULL
)

Arguments

Details

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.

Value

A list of 14 elements of classes dudi and pca as in dudi.pca

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Olivier Broennimann <olivier.broennimann@unil.ch>

See Also

dudi.pca

Examples

## 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)

fmtSpN

Description

For internal use. Format species name with underscore

Usage

fmtSpN(spN)

Arguments

getRasterVals

Description

Retrieve the value range for a prediction raster for plotting

Usage

getRasterVals(r, type = "raw")

Arguments

hlSpp

Description

For internal use. Green and bold species name in Windows Log

Usage

hlSpp(spN)

Arguments

model_bioclim Generate Bioclim model

Description

The function generates a BIOCLIM model using ENMeval 2.0

Usage

model_bioclim(occs, bg, user.grp, bgMsk, logger = NULL, spN = NULL)

Arguments

Details

The function generates a model in ENMeval using a user provided partition of occurrences from previous components in the GUI.

Value

Function returns an ENMevaluate object with all the evaluated models and a selection of appropriate fields.

Author(s)

Jamie M. Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Bethany A. Johnson <bjohnso005@citymail.cuny.edu>

See Also

ENMevaluate

Examples

## 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)

model_maxent Generate maxent.jar or maxnet model

Description

This functions generates maxent.jar or maxnet models using ENMeval 2.0 and user provided tuning parameters.

Usage

model_maxent(
  occs,
  bg,
  user.grp,
  bgMsk,
  rms,
  rmsStep,
  fcs,
  clampSel,
  algMaxent,
  catEnvs = NULL,
  parallel = FALSE,
  numCores = NULL,
  logger = NULL,
  spN = NULL
)

Arguments

Details

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.

Value

Function returns an ENMevaluate object with all the evaluated models and a selection of appropriate fields.

Author(s)

Jamie M. Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Bethany A. Johnson <bjohnso005@citymail.cuny.edu>

See Also

ENMevaluate

Examples

## 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)

mxNonzeroCoefs

Description

For internal use. Pulls out all non-zero, non-redundant (removes hinge/product/threshold) predictor names

Usage

mxNonzeroCoefs(mx, alg)

Arguments

occs_queryDb Query online database for species occurrence records.

Description

Queries a given database for occurrence data on the provided species

Usage

occs_queryDb(
  spNames,
  occDb,
  occNum = NULL,
  doCitations = FALSE,
  gbifUser = NULL,
  gbifEmail = NULL,
  gbifPW = NULL,
  RmUncertain = FALSE,
  logger = NULL
)

Arguments

Details

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.

Value

list of lists one list per species with occurrence records. Each individual species list with appropriate fields for analysis

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Hannah Owens

Andrea Paz <paz.andreita@gmail.com>

Examples

## Not run: 
occs_queryDb(spName = "Bassaricyon alleni", occDb = "gbif", occNum = 10)

## End(Not run)

occs_userOccs Loads user provided occurrence records

Description

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

Usage

occs_userOccs(txtPath, txtName, txtSep = ",", txtDec = ".", logger = NULL)

Arguments

Details

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.

Value

List of lists. One list per species with occurrence records. Each individual species list with appropriate fields for analysis

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Examples

txtPath <- system.file("extdata/Bassaricyon_alleni.csv", package = "wallace")
txtName <- 'Bassaricyon_alleni'
user.occs <- occs_userOccs(txtPath, txtName)

part_partitionOccs Partition occurrence data

Description

This function partitions occurrence data and background points according to a user-selected method.

Usage

part_partitionOccs(
  occs,
  bg,
  method,
  kfolds = NULL,
  bgMask = NULL,
  aggFact = NULL,
  logger = NULL,
  spN = NULL
)

Arguments

Details

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.

Value

A list of two vectors containing group assignments for occurrences (occs.grp) and background points (bg.grp).

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Andrea Paz <paz.andreita@gmail.com>

Bethany A Johnson <bjohnso005@citymail.cuny.edu>

See Also

partitions

Examples

## 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)

penvs_bgExtent Generate background extent

Description

This function generates a background area according to a user- provided method.

Usage

penvs_bgExtent(occs, bgSel, bgBuf, logger = NULL, spN = NULL)

Arguments

Details

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.

Value

A SpatialPolygons object that contains all occurrences from occs

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Bethany A. Johnson <bjohnso005@citymail.cuny.edu>

See Also

penvs_userBgExtent, penvs_drawBgExtent, penvs_bgMask , penvs_bgSample

Examples

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)

penvs_bgMask Mask environmental data

Description

This functions crops and masks the environmental data to the provided background area.

Usage

penvs_bgMask(occs, envs, bgExt, logger = NULL, spN = NULL)

Arguments

Details

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).

Value

A RasterStack or a RasterBrick of environmental layers cropped and masked to match the provided background extent.

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

See Also

penvs_userBgExtent, penvs_drawBgExtent, penvs_bgExtent, penvs_bgSample

Examples

## 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)

penvs_bgSample Sample background points

Description

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.

Usage

penvs_bgSample(occs, bgMask, bgPtsNum, logger = NULL, spN = NULL)

Arguments

Details

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.

Value

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.

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

See Also

penvs_bgMask, penvs_bgExtent penvs_userBgExtent, penvs_drawBgExtent, randomPoints

Examples

## 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)

penvs_drawBgExtent: Draw background extent

Description

This function generates a background area according to a user drawn polygon and provided buffer.

Usage

penvs_drawBgExtent(
  polyExtXY,
  polyExtID,
  drawBgBuf,
  occs,
  logger = NULL,
  spN = NULL
)

Arguments

Details

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).

Value

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.

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Bethany A. Johnson <bjohnso005@citymail.cuny.edu>

See Also

penvs_userBgExtent, penvs_bgExtent, penvs_bgMask , penvs_bgSample

Examples

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)

penvs_userBgExtent: user provided background extent

Description

This function generates a background area according to a user provided polygon and buffer.

Usage

penvs_userBgExtent(
  bgShp_path,
  bgShp_name,
  userBgBuf,
  occs,
  logger = NULL,
  spN = NULL
)

Arguments

Details

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).

Value

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.

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Andrea Paz <paz.andreita@gmail.com>

Bethany A. Johnson <bjohnso005@citymail.cuny.edu>

See Also

penvs_drawBgExtent, penvs_bgExtent, penvs_bgMask , penvs_bgSample

Examples

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)

poccs_removeByID Remove occurrence by ID

Description

This function removes user selected occurrences by ID.

Usage

poccs_removeByID(occs, removeID, logger = NULL, spN = NULL)

Arguments

Details

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.

Value

A new occurence dataframe without the user selected occurrence mantaining all columns from original dataframe for further analyses.

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Examples

occs <- read.csv(system.file("extdata/Bassaricyon_neblina.csv",
                 package = "wallace"))[, 2:3]
occs$occID <- 1:nrow(occs)
out.ID <- poccs_removeByID(occs, 11)

poccs_selectOccs Remove occurrences outside of polygon

Description

This function removes occurrences outside of a user created polygon.

Usage

poccs_selectOccs(occs, polySelXY, polySelID = 1, logger = NULL, spN = NULL)

Arguments

Details

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.

Value

A new occurence dataframe including only occurences inside the provided polygon and mantaining all columns from original dataframe for further analyses.

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Examples

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)

poocs_thinOccs Thin occurrences

Description

The function thins the observed occurrences by a user provided distance.

Usage

poccs_thinOccs(occs, thinDist, logger = NULL, spN = NULL)

Arguments

Details

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.

Value

Output is a data frame of thinned occurences (all occurences at a distance >thinDist) with the same columns as occs

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

See Also

thin

Examples

occs <- read.csv(system.file("extdata/Bassaricyon_neblina.csv",
                             package = "wallace"))
occs$occID <- 1:nrow(occs)
out.thin <- poccs_thinOccs(occs = occs, thinDist = 30)

polyZoom

Description

For internal use. Zooms appropriately for any polygon

Usage

polyZoom(xmin, ymin, xmax, ymax, fraction)

Arguments

popUpContent

Description

For internal use. Make new column for leaflet marker popup content

Usage

popUpContent(occs)

Arguments

predictMaxnet

Description

Create a raster prediction for a maxnet model

Usage

predictMaxnet(mod, envs, clamp, type)

Arguments

printVecAsis

Description

For internal use. Print vector as character string

Usage

printVecAsis(x, asChar = FALSE)

Arguments

Register a Wallace module

Description

Before running the Wallace application with run_wallace(), you can register your own modules to be used in Wallace.

Usage

register_module(config_file)

Arguments

See Also

create_module

remEnvsValsNA

Description

For internal use. Remove occs with NA values

Usage

remEnvsValsNA(occs, occsEnvsVals, spN, logger)

Arguments

reverseLabel

Description

For internal use. Reverse label in leaflet legends

Usage

reverseLabel(..., reverse_order = FALSE)

Arguments

Run Wallace Application

Description

This function runs the Wallace application in the user's default web browser.

Usage

run_wallace(launch.browser = TRUE, port = getOption("shiny.port"))

Arguments

Note

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: wallaceEcoMod@gmail.com.

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Examples

if(interactive()) {
run_wallace()
}

smartProgress

Description

For internal use. Either prints a message to console or makes a progress bar in the shiny app the entry of the first param "logs" turns on shiny functionality

Usage

smartProgress(logs, message, expr)

Arguments

spName

Description

For internal use. Retrieves the species name for use internally in non-shiny functions

Usage

spName(spN)

Arguments

Spurious package call to avoid note of functions outside R folder

Description

For internal use.

Usage

spurious(x)

Arguments

vis_bioclimPlot Visualize bivariate plot of BIOCLIM model

Description

This functions creates a bivariate plot with two of the environmental variables used for modeling as x and y axes and occurrences as observations.

Usage

vis_bioclimPlot(x, a = 1, b = 2, p = 0.9)

Arguments

Details

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.

Value

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.

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Bethany A. Johnson <bjohnso005@citymail.cuny.edu>

See Also

model_bioclim ENMevaluate

Examples

## 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)

writeLog

Description

For internal use. Add text to a logger

Usage

writeLog(logger, ..., type = "default")

Arguments

write_csv_robust

Description

For internal use. Write Robust CSV

Usage

write_csv_robust(x, ...)

Arguments

xfer_area Transfer model to a new area

Description

Function transfers the model generated in previous components to a new user drawn area.

Usage

xfer_area(
  evalOut,
  curModel,
  envs,
  xfExt,
  alg,
  outputType = NULL,
  clamp = NULL,
  logger = NULL,
  spN = NULL
)

Arguments

Details

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.

Value

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.

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Andrea Paz <paz.andreita@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Bethany A. Johnson <bjohnso005@citymail.cuny.edu>

See Also

predict, xfer_time xfer_userEnvs

Examples

## 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)))
# build model
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_maxent(occs, bg,
  user.grp = partblock,
  bgMsk = envs, rms = c(1:2),
  rmsStep = 1, fcs = c('L', 'LQ'),
  clampSel = TRUE,
  algMaxent = "maxnet",
  parallel = FALSE)
### run function
modXfer <- xfer_area(evalOut = m, curModel = 1, envs,
                     outputType = 'cloglog', alg = 'maxnet',
                     clamp = TRUE, xfExt = polyExt)

## End(Not run)

xfer_draw Draw extent of transfer

Description

This function creates a polygon object from coordinates of user drawn poylgon in the GUI.

Usage

xfer_draw(polyXfXY, polyXfID, drawXfBuf, logger = NULL, spN = NULL)

Arguments

Details

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).

Value

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.

Author(s)

Gonzalo Pinilla <gepinillab@gmail.com>

Bethany A. Johnson <bjohnso005@citymail.cuny.edu>

See Also

xfer_userEnvs

Examples

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)

xfer_mess generate MESS map for transferred raster

Description

This function generates a MESS map for the new variables for transferring based on variables and points used for modeling in previous components.

Usage

xfer_mess(occs, bg, bgMsk, xferExtRas, logger = NULL, spN = NULL)

Arguments

Details

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.

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

See Also

mess, xfer_time xfer_userEnvs

Examples

## 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)

xfer_time Transfer model to a new time

Description

Function transfers the model generated in previous components to a new time and area using provided layers.

Usage

xfer_time(
  evalOut,
  curModel,
  envs,
  xfExt,
  alg,
  outputType = NULL,
  clamp = NULL,
  logger = NULL,
  spN = NULL
)

Arguments

Details

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.

Value

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.

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Andrea Paz <paz.andreita@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Bethany A. Johnson <bjohnso005@citymail.cuny.edu>

See Also

predict, xfer_time xfer_userEnvs

Examples

## 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)))
# build model
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_maxent(occs, bg, user.grp = partblock, bgMsk = envs, rms = c(1:2),
rmsStep = 1, fcs = c('L', 'LQ'),
clampSel = TRUE, algMaxent = "maxnet", parallel = FALSE)
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 = 'maxnet',
                     xfExt = polyExt, clamp = FALSE, outputType = 'cloglog')

## End(Not run)

xfer_userEnvs Transfer model to user specified area and time

Description

The function transfers the model generated in previous components to user uploaded environmental variables.

Usage

xfer_userEnvs(
  evalOut,
  curModel,
  envs,
  xfExt,
  alg,
  outputType = NULL,
  clamp = NULL,
  logger = NULL,
  spN = NULL
)

Arguments

Details

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.

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Andrea Paz <paz.andreita@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Bethany A. Johnson <bjohnso005@citymail.cuny.edu>

See Also

predict, xfer_time xfer_userExtent

Examples

## 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)))
# build model
occs <- read.csv(system.file("extdata/Bassaricyon_alleni.csv",package = "wallace"))
bg <- read.csv(system.file("extdata/Bassaricyon_alleni_bgPoints.csv",
package = "wallace"))
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))
partblock <- part_partitionOccs(occs, bg, method = 'block')
m <- model_maxent(occs, bg, user.grp = partblock, bgMsk = envs, rms = c(1:2),
rmsStep = 1, fcs = c('L', 'LQ'), clampSel = TRUE, algMaxent = "maxnet", parallel = FALSE)
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 = "maxnet",
                         clamp = FALSE, xfExt = polyExt)

## End(Not run)

xfer_userExtent: user provided extent of transfer

Description

This function generates an area of transfer according to a user provided polygon and buffer.

Usage

xfer_userExtent(bgShp_path, bgShp_name, userBgBuf, logger = NULL, spN = NULL)

Arguments

Details

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).

Value

This function returns a SpatialPolygons object with the user provided shape (+ a buffer is userBgBuf >0).

Author(s)

Jamie Kass <jamie.m.kass@gmail.com>

Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Andrea Paz <paz.andreita@gmail.com>

Bethany A. Johnson <bjohnso005@citymail.cuny.edu>

See Also

penvs_drawBgExtent, penvs_bgExtent, penvs_bgMask , penvs_bgSample

Examples

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)

zoom2Occs

Description

For internal use. Zoom to occ pts.

Usage

zoom2Occs(map, occs)

Arguments