startISDM {PointedSDMs}

startISDM: Function used to initialize the integrated species distribution model.

Description

This function is used to create an object containing all the data, metadata and relevant components required for the integrated species distribution model and INLA to work. As a result, the arguments associated with this function are predominantly related to describing variable names within the datasets that are relevant, and arguments related to what terms should be included in the formula for the integrated model. The output of this function is an R6 object, and so there are a variety of public methods within the output of this function which can be used to further specify the model (see ?specifyISDM or .$help() for a comprehensive description of these public methods).

Usage

startISDM(
  ...,
  spatialCovariates = NULL,
  Projection,
  Mesh,
  IPS = NULL,
  Boundary = NULL,
  pointCovariates = NULL,
  Offset = NULL,
  pointsIntercept = TRUE,
  pointsSpatial = "copy",
  responseCounts = "counts",
  responsePA = "present",
  trialsPA = NULL,
  temporalName = NULL,
  Formulas = list(covariateFormula = NULL, biasFormula = NULL)
)

Arguments

...

The datasets to be used in the model. Must come as either sf objects, or as a list of named sf objects.

spatialCovariates

The spatial covariates used in the model. These covariates must be measured at every location (pixel) in the study area, and must be a SpatialRaster object. Can be either numeric, factor or character data. Defaults to NULL which includes no spatial effects in the model.

Projection

The coordinate reference system used by both the spatial points and spatial covariates. Must be of class character.

Mesh

An inla.mesh object required for the spatial random fields and the integration points in the model (see inla.mesh.2d from the INLA package for more details).

IPS

The integration points to be used in the model (that is, the points on the map where the intensity of the model is calculated). See fm_int from the inlabru package for more details regarding these points; however defaults to NULL which will create integration points from the Mesh and Boundary objects.

Boundary

A sf object of the study area. If not missing, this object is used to help create the integration points.

pointCovariates

The non-spatial covariates to be included in the integrated model (for example, in the field of ecology the distance to the nearest road or time spent sampling could be considered). These covariates must be included in the same data object as the points, and do not necessarily need to be present in all datasets.

Offset

Name of the offset variable (class character) in the datasets. Defaults to NULL; if the argument is non-NULL, the variable name needs to be standardized across datasets (but does not need to be included in all datasets). The offset variable will be transformed onto the log-scale in the integrated model.

pointsIntercept

Logical argument: should the points be modeled with intercepts. Defaults to TRUE.

pointsSpatial

Argument to determine whether the spatial field is shared between the datasets, or if each dataset has its own unique spatial field. The datasets may share a spatial field with INLA's "copy" feature if the argument is set to copy. May take on the values: "shared", "individual", "copy" or NULL if no spatial field is required for the model. Defaults to "copy".

responseCounts

Name of the response variable in the counts/abundance datasets. This variable name needs to be standardized across all counts datasets used in the integrated model. Defaults to 'counts'.

responsePA

Name of the response variable (class character) in the presence absence/detection non-detection datasets. This variable name needs to be standardized across all present absence datasets. Defaults to 'present'.

trialsPA

Name of the trials response variable (class character) for the presence absence datasets. Defaults to NULL.

temporalName

Name of the temporal variable (class character) in the model. This variable is required to be in all the datasets. Defaults to NULL.

Formulas

A named list with two objects. The first one, covariateFormula, is a formula for the covariates and their transformations for the distribution part of the model. Defaults to NULL which includes all covariates specified in spatialCovariates into the model. The second, biasFormula, specifies which covariates are used for the PO datasets. Defaults to NULL which includes no covariates for the PO datasets.

Value

A specifyISDM object (class R6). Use ?specifyISDM to get a comprehensive description of the slot functions associated with this object.

Note

The idea with this function is to describe the full model: that is, all the covariates and spatial effects will appear in all the formulas for the datasets and species. If some of these terms should not be included in certain observation models in the integrated model, they can be thinned out using the .$updateFormula function. Note: the point covariate will only be included in the formulas for where they are present in a given dataset, and so these terms do not need to be thinned out if they are not required by certain observation models.

Examples

## Not run: 
 if (requireNamespace('INLA')) {
   
 #Get Data
 data("SolitaryTinamou")
 proj <- "+proj=longlat +ellps=WGS84"
 data <- SolitaryTinamou$datasets
 mesh <- SolitaryTinamou$mesh
 mesh$crs <- proj
 
 #Set base model up
 baseModel <- startISDM(data, Mesh = mesh,
                             Projection = proj, responsePA = 'Present')
 
 #Print summary
 baseModel
 
 #Set up model with dataset specific spatial fields
 indSpat <- startISDM(data, Mesh = mesh,
                     Projection = proj, pointsSpatial = 'individual', responsePA = 'Present')
                     
 #Model with offset variable
 offSet <- startISDM(data, Mesh = mesh,
                     Projection = proj, Offset = 'area', responsePA = 'Present')
 
 #Add own formula
 quadModel <- startISDM(data, Mesh = mesh, 
                        Projection = proj, pointsSpatial = 'copy', responsePA = 'Present',
                        Formulas = list(covariateFormula = ~ NPP + I(NPP^2)))                    
                      
 }
 
## End(Not run)