neotoma (version 1.7.4)

compile_downloads: Compile download objects

Description

Function to convert multiple downloads into a single large table.

From the assemblage data for multiple cores, return a single data.frame with columns for site metadata and assemblage data.

To support further synthesis and analysis compile_download works to transform a list returned by get_download into a large data frame with columns for site and sample attributes and also with the associated assemblage data at each sample depth. This function also does the same for single sites.

Usage

compile_downloads(downloads)

Arguments

downloads

A download_list as returned by get_download, or multiple downloads joined in a list.

Value

This command returns a data frame.

References

Neotoma Project Website: http://www.neotomadb.org

Gavin DG, Oswald WW, Wahl ER, Williams JW. 2003. A statistical approach to evaluating distance metrics and analog assignments for pollen records. Quaternary Research 60: 356-367.

Whitmore J, Gajewski K, Sawada M, Williams JW, Shuman B, Bartlein PJ, Minckley T, Viau AE, Webb III T, Shafer S, Anderson P, Brubaker L. 2005. Modern pollen data from North America and Greenland for multi-scale paleoenvironmental applications. Quaternary Science Reviews 24: 1828-1848.

Williams J, Shuman B. 2008. Obtaining accurate and precise environmental reconstructions from the modern analog technique and North American surface pollen dataset. Quaternary Science Reviews. 27:669-687.

API Reference: http://api.neotomadb.org/doc/resources/contacts

Examples

# NOT RUN {
#  Search for sites with "Thuja" pollen that are older than 8kyr BP and
#  that are on the west coast of North America:
t8kyr.datasets <- get_dataset(taxonname='Thuja*', 
                              loc=c(-150, 20, -100, 60), 
                              ageyoung = 8000)

#  Returns 3 records (as of 04/04/2013), get dataset for the first record, 
#  Gold Lake Bog.
thuja.sites <- get_download(t8kyr.datasets)

gold.p25 <- compile_taxa(thuja.sites, 'P25')

all.gold <- compile_downloads(gold.p25)

pollen.sums <- rowSums(all.gold[,11:ncol(all.gold)], na.rm=TRUE)

plot(x = all.gold$age, 
     y = all.gold$Cupressaceae.Taxaceae / pollen.sums, 
     col = all.gold$site.name,
     pch = 19)

# }