This vignette goes through the spatial thinning example presented in
“spThin: An R package for spatial thinning of species occurrence records
for use in ecological niche models”. Here we demonstrate how spThin can
be used to spatially thin species occurence records, we test how many
repetitions of the thinning algorithm are necessary to achieve the optimal
number of thinned records for a dataset previously thinned “by hand”, and
we examine whether there is a notable increase in efficiency if an occurence
dataset is thinned as multiple smaller groups of occurrences,
rather than a single large set of occurrences.
spThin R packageHere we load the R package from source code. This source code will soon be submitted to CRAN, so that this package can be loaded using standard package management methods
library( spThin )
## Loading required package: spam
## Loading required package: dotCall64
## Loading required package: grid
## Spam version 2.2-2 (2019-03-07) is loaded.
## Type 'help( Spam)' or 'demo( spam)' for a short introduction
## and overview of this package.
## Help for individual functions is also obtained by adding the
## suffix '.spam' to the function name, e.g. 'help( chol.spam)'.
##
## Attaching package: 'spam'
## The following objects are masked from 'package:base':
##
## backsolve, forwardsolve
## Loading required package: fields
## Loading required package: maps
## See https://github.com/NCAR/Fields for
## an extensive vignette, other supplements and source code
## Loading required package: knitr
To demonstrate the use of spThin we used a set of 201 verified, georeferenced
occurrence records for the Caribbean spiny pocket mouse Heteromys anomalus.
These occurrences are from Columbia, Venezuela, and
three Caribbean islands: Trinidad, Tobago, and Margarita. This dataset
is included as part of the spThin package.
data( Heteromys_anomalus_South_America )
head( Heteromys_anomalus_South_America )
## SPEC LAT LONG REGION
## 1 anomalus 7.883333 -75.20000 mainland
## 2 anomalus 8.000000 -76.73333 mainland
## 3 anomalus 10.616667 -75.03333 mainland
## 4 anomalus 8.633333 -74.06667 mainland
## 5 anomalus 9.966667 -75.06667 mainland
## 6 anomalus 10.216667 -73.38333 mainland
Here we load and examine the dataset. The name assigned to this dataset
is Heteromys_anomalus_South_America.
Note that this dataset includes a column indicating which REGION the
occurrences was collected. Regions here refer to either the mainland or
three islands in which an occurrence was collected. We can see that
there are many more occurrences collected for the mainland than for
the three islands. Note that Trinidad has been shortened to 'trin'
an Margarita has been shortened to 'mar'.
table( Heteromys_anomalus_South_America$REGION )
##
## mainland mar tobago trin
## 174 2 4 21
spThin::thin on the full datasetthin involves multiple settings. This allows for extensive
flexibility in how the user spatially thins a dataset.
However, many have
default values. See ?thin for further information.
thinned_dataset_full <-
thin( loc.data = Heteromys_anomalus_South_America,
lat.col = "LAT", long.col = "LONG",
spec.col = "SPEC",
thin.par = 10, reps = 100,
locs.thinned.list.return = TRUE,
write.files = FALSE,
write.log.file = FALSE)
## **********************************************
## Beginning Spatial Thinning.
## Script Started at: Fri Nov 15 12:36:51 2019
## lat.long.thin.count
## 122 123 124
## 10 47 43
## [1] "Maximum number of records after thinning: 124"
## [1] "Number of data.frames with max records: 43"
## [1] "No files written for this run."
Below is the same call, but in this case we are writing a number of files to disk. This files include a set of *.csv files of the thinned data and a log file.
thinned_dataset_full <-
thin( loc.data = Heteromys_anomalus_South_America,
lat.col = "LAT", long.col = "LONG",
spec.col = "SPEC",
thin.par = 10, reps = 100,
locs.thinned.list.return = TRUE,
write.files = TRUE,
max.files = 5,
out.dir = "hanomalus_thinned_full/", out.base = "hanomalus_thinned",
write.log.file = TRUE,
log.file = "hanomalus_thinned_full_log_file.txt" )
In the case above, we found that 10 repetitions were sufficient
to return spatially thinned datasets with the optimal number of
occurrence records (124). Because this is a random process,
it is possible that a similarly repeated run would not return any
datasets with the optimal number of occurrence records.
To visually assess whether we are using enough reps to
approach the optimal number we use the function plotThin,
This function produces three plots: 1) the cumulative number of
records retained versus the number of repetitions, 2) the log
cumulative number of records retained versus the log number of
repetitions, and 3) a histogram of the maximum number of records
retained for each thinned dataset.
plotThin( thinned_dataset_full )
Looking at the plot of cumulative maximum records retained versus number of repetitions, we see that in this run, this value is constant through out the dataset creation process, indicating that a single repetition would have sufficed to reach 124. This is likely not always the case, but this plot can be examined to assess whether a given number of repetitions is sufficient to achieve a plateau (sensu species accumulation curves in Ecology).
spThin::thin on datasets separated by regionthinned_dataset_mainland <-
thin( loc.data = Heteromys_anomalus_South_America[ which( Heteromys_anomalus_South_America$REGION == "mainland" ) , ],
lat.col = "LAT", long.col = "LONG",
spec.col = "SPEC",
thin.par = 10, reps = 100,
locs.thinned.list.return = TRUE,
write.files = FALSE,
write.log.file = FALSE)
## **********************************************
## Beginning Spatial Thinning.
## Script Started at: Fri Nov 15 12:36:52 2019
## lat.long.thin.count
## 109 110
## 39 61
## [1] "Maximum number of records after thinning: 110"
## [1] "Number of data.frames with max records: 61"
## [1] "No files written for this run."
thinned_dataset_trin <-
thin( loc.data = Heteromys_anomalus_South_America[ which( Heteromys_anomalus_South_America$REGION == "trin" ) , ],
lat.col = "LAT", long.col = "LONG",
spec.col = "SPEC",
thin.par = 10, reps = 10,
locs.thinned.list.return = TRUE,
write.files = FALSE,
write.log.file = FALSE)
## **********************************************
## Beginning Spatial Thinning.
## Script Started at: Fri Nov 15 12:36:52 2019
## lat.long.thin.count
## 11 12
## 6 4
## [1] "Maximum number of records after thinning: 12"
## [1] "Number of data.frames with max records: 4"
## [1] "No files written for this run."
thinned_dataset_mar <-
thin( loc.data = Heteromys_anomalus_South_America[ which( Heteromys_anomalus_South_America$REGION == "mar" ) , ],
lat.col = "LAT", long.col = "LONG",
spec.col = "SPEC",
thin.par = 10, reps = 10,
locs.thinned.list.return = TRUE,
write.files = FALSE,
write.log.file = FALSE )
## **********************************************
## Beginning Spatial Thinning.
## Script Started at: Fri Nov 15 12:36:52 2019
## lat.long.thin.count
## 1
## 10
## [1] "Maximum number of records after thinning: 1"
## [1] "Number of data.frames with max records: 10"
## [1] "No files written for this run."
thinned_dataset_tobago <-
thin( loc.data = Heteromys_anomalus_South_America[ which( Heteromys_anomalus_South_America$REGION == "tobago" ) , ],
lat.col = "LAT", long.col = "LONG",
spec.col = "SPEC",
thin.par = 10, reps = 10,
locs.thinned.list.return = TRUE,
write.files = FALSE,
write.log.file = FALSE )
## **********************************************
## Beginning Spatial Thinning.
## Script Started at: Fri Nov 15 12:36:52 2019
## lat.long.thin.count
## 1
## 10
## [1] "Maximum number of records after thinning: 1"
## [1] "Number of data.frames with max records: 10"
## [1] "No files written for this run."