The goal of smpds is to provide access to the SPECIAL Modern Pollen
Data Set for Climate Reconstructions (SMPDS).
You can(not) install the released version of SMPDS from CRAN with:
install.packages("smpds")And the development version from GitHub with:
# install.packages("remotes")
remotes::install_github("special-uor/smpds")data("climate", package = "smpds")
data("entity", package = "smpds")
data("pollen_count", package = "smpds")
data("taxon_name", package = "smpds")The function smpds::snapshot takes few different parameters and based
on the first one, x, it returns a variety of snapshots.
This function returns a list with 3 components:
-
entity: data frame (tibbleobject) with the metadata associated to the entities. -
climate: data frame (tibbleobject) with the climate and vegetation reconstructions. This one can be linked to theentitytable using the column calledID_SAMPLE. -
pollen_count: list of data frames (tibbleobjects) containing the pollen counts for 3 levels of “amalgamation”:cleanintermediateamalgamated
All these data frames can be linked to the
entitytable using the column calledID_SAMPLE.
output <- smpds::snapshot(...)
output$entity
output$climate
output$pollen_count$clean
output$pollen_count$intermediate
output$pollen_count$intermediatesmpds::snapshot("juodonys_core")
#> # A tibble: 1 × 6
#> ID_SITE ID_ENTITY ID_SAMPLE site_name entity_name pollen_counts$clean
#> <int> <int> <int> <chr> <chr> <int>
#> 1 3890 7901 1 Juodonys juodonys_core 1
#> # … with 2 more variables: pollen_counts$intermediate <int>, $amalgamated <int>smpds::snapshot("Petresiunai", use_site_name = TRUE)
#> # A tibble: 1 × 6
#> ID_SITE ID_ENTITY ID_SAMPLE site_name entity_name pollen_counts$clean
#> <int> <int> <int> <chr> <chr> <int>
#> 1 6690 14229 2 Petresiunai petresiunai_121 1
#> # … with 2 more variables: pollen_counts$intermediate <int>, $amalgamated <int>smpds::snapshot(2)
#> # A tibble: 1 × 6
#> ID_SITE ID_ENTITY ID_SAMPLE site_name entity_name pollen_counts$clean
#> <int> <int> <int> <chr> <chr> <int>
#> 1 1 2 9710 05-Mo 05-Mo-10 1
#> # … with 2 more variables: pollen_counts$intermediate <int>, $amalgamated <int>smpds::snapshot(3, use_id_site = TRUE)
#> # A tibble: 1 × 6
#> ID_SITE ID_ENTITY ID_SAMPLE site_name entity_name pollen_counts$clean
#> <int> <int> <int> <chr> <chr> <int>
#> 1 3 37 15871 11 [HFL11] HFL11 1
#> # … with 2 more variables: pollen_counts$intermediate <int>, $amalgamated <int>smpds::snapshot(1:10)
#> # A tibble: 10 × 6
#> ID_SITE ID_ENTITY ID_SAMPLE site_name entity_name pollen_counts$clean
#> <int> <int> <int> <chr> <chr> <int>
#> 1 1 1 9709 05-Mo 05-Mo 10
#> 2 1 2 9710 05-Mo 05-Mo-10 10
#> 3 1 3 9711 05-Mo 05-Mo-11 10
#> 4 1 4 9712 05-Mo 05-Mo-12 10
#> 5 1 5 9713 05-Mo 05-Mo-13 10
#> 6 1 6 9714 05-Mo 05-Mo-14 10
#> 7 1 7 9715 05-Mo 05-Mo-15 10
#> 8 1 8 9716 05-Mo 05-Mo-16 10
#> 9 1 9 9717 05-Mo 05-Mo-17 10
#> 10 1 10 9718 05-Mo 05-Mo-18 10
#> # … with 2 more variables: pollen_counts$intermediate <int>, $amalgamated <int>This will run very slow, so if only few entities are required, it would be better to indicate which, based on the previous examples.
out <- smpds::snapshot()The function smpds::write_csvs takes to parameters:
.data: a list of classsnapshot, this one can be generated using the functionsmpds::snapshot(see previous section).prefix: a prefix name to be included in each individual files, this prefix can include a relative or absolute path to a directory in the local machine.
`%>%` <- smpds::`%>%`
smpds::snapshot("juodonys_core") %>%
smpds::write_csvs(prefix = "juodonys_core")
#> # A tibble: 1 × 6
#> ID_SITE ID_ENTITY ID_SAMPLE site_name entity_name pollen_counts$clean
#> <int> <int> <int> <chr> <chr> <int>
#> 1 3890 7901 1 Juodonys juodonys_core 1
#> # … with 2 more variables: pollen_counts$intermediate <int>, $amalgamated <int>#> levelName
#> 1 .
#> 2 ¦--juodonys_core_metadata.csv
#> 3 ¦--juodonys_core_pollen_counts_amalgamated.csv
#> 4 ¦--juodonys_core_pollen_counts_clean.csv
#> 5 °--juodonys_core_pollen_counts_intermediate.csv
`%>%` <- smpds::`%>%`
smpds::snapshot("juodonys_core") %>%
smpds::write_csvs(prefix = "/special.uor/epd/juodonys_core")#> levelName
#> 1 special.uor
#> 2 °--epd
#> 3 ¦--juodonys_core_metadata.csv
#> 4 ¦--juodonys_core_pollen_counts_amalgamated.csv
#> 5 ¦--juodonys_core_pollen_counts_clean.csv
#> 6 °--juodonys_core_pollen_counts_intermediate.csv
smpds::SMPDSv2 %>%
smpds::plot_biome()
smpds::SMPDSv2 %>%
smpds::plot_gdd()
smpds::SMPDSv2 %>%
smpds::plot_mtco()
smpds::SMPDSv2 %>%
smpds::plot_mi()
Please note that the SMPDS project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
This package is a companion to the following dataset:
Villegas-Diaz, R., Harrison, S. P., 2022. The SPECIAL Modern Pollen Data Set for Climate Reconstructions, version 2 (SMPDSv2). University of Reading. Dataset. https://doi.org/10.17864/1947.000389
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