algaeClassify (version 1.2.0)

phyto_ts_aggregate: Aggregate phytoplankton timeseries based on abundance. Up to 3 grouping variables can be given: e.g. genus, species, stationid, depth range. If no abundance var is given, will aggregate to presence/absence of grouping vars.

Description

Aggregate phytoplankton timeseries based on abundance. Up to 3 grouping variables can be given: e.g. genus, species, stationid, depth range. If no abundance var is given, will aggregate to presence/absence of grouping vars.

Usage

phyto_ts_aggregate(phyto.data, DateVar = "date_dd_mm_yy",
  SummaryType = c("abundance", "presence.absence"),
  AbundanceVar = "biovol_um3_ml", GroupingVar1 = "phyto_name",
  GroupingVar2 = NA, GroupingVar3 = NA, remove.rare = FALSE,
  fun = sum, format = "%d-%m-%y")

Arguments

phyto.data

data.frame

DateVar

character string: field name for date variable. character or POSIX data.

SummaryType

'abundance' for a matrix of aggregated abundance,'presence.absence' for 1 (present) and 0 (absent).

AbundanceVar

character string with field name containing abundance data Can be NA if data is only a species list and aggregated presence/absence is desired.

GroupingVar1

character string: field name for first grouping variable. defaults to spp.

GroupingVar2

character string: name of additional grouping var field

GroupingVar3

character string: name of additional grouping var field

remove.rare

TRUE/FALSE. If TRUE, removes all instances of GroupingVar1 that occur < 5 of time periods.

fun

function used to aggregate abundance based on grouping variables

format

character string: format for DateVar POSIXct conversion

Value

a data.frame with grouping vars, date_dd_mm_yy, and abundance or presence/absence

Examples

# NOT RUN {
data(lakegeneva)
lakegeneva<-genus_species_extract(lakegeneva,'phyto_name')
lg.genera=phyto_ts_aggregate(lakegeneva,SummaryType='presence.absence',
                             GroupingVar1='genus')
head(lg.genera)
# }