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README.md

ecomon

R tools for reading and querying Ecomon version 2.6 datasets.

Data source

  • Kane J (2007) Zooplankton abundance trends on Georges Bank, 1977-2004. ICES Journal of Marine Science 64(5):909-919
  • Kane J (2011) Inter-decadal variability of zooplankton abundance in the Middle Atlantic Bight. Journal of Northwest Atlantic Fishery Science 43: 81-92

Data prep

Data were downloaded in an multi-tab Excel spreadsheet. Tabs labeled 10m2 and 100m3 were exported as comma delimited text files and gzipped. These are stored in the package distribution. The data can be read using the read_zoop() function or by using the convenience class ZoopRefClass as shown below.

Requirements

Installation

It is easy to install with devtools

library(devtools)
install_github("BigelowLab/ecomon")

Read ZOOP data

library(ecomon)
X <- Zoop(what = 'm2')   # same as X <- Zoop()
                         # or for volumetric data X <- Zoop(what = 'm3')
X 
# ... lot of stuff printed

# get just salp data within a bounding box
x <- X$get(species = 'salps', bb = c(-75,-60, 35, 38))
str(x)
# 'data.frame':	1189 obs. of  8 variables:
#  $ cruise_name : chr  "AA8704" "AA8704" "AA8704" "AA8704" ...
#  $ station     : int  3 5 11 13 21 22 23 26 27 29 ...
#  $ lat         : num  35.9 36.3 36.6 36.8 37.2 ...
#  $ lon         : num  -74.9 -74.8 -74.9 -74.8 -74.8 ...
#  $ date        : POSIXct, format: "1987-04-13 17:00:00" "1987-04-13 23:15:00" "1987-04-14 11:30:00" ...
#  $ depth       : num  88 360 47 50 68 57 36 41 100 108 ...
#  $ volume_100m3: num  21.9 19.7 87.7 36.2 21.4 ...
#  $ salps       : int  1190 1155 0 842 110 0 0 0 1201 0 ...
 
 
# lighten the load by dropping all but one or more species
X$retain(c("salps","evadnespp"))

# get all the remianing species within a bounding box and within two dates
x <- X$get(bb = c(-75,-60, 35, 38), date_filter = as.POSIXct(c("2008-01-01", "2009-01-01")))
str(x)
# 'data.frame':	21 obs. of  8 variables:
#  $ cruise_name : chr  "AL0801" "AL0801" "AL0801" "DE0808" ...
#  $ station     : int  91 96 97 20 24 25 28 37 38 39 ...
#  $ lat         : num  36.6 36.2 36.1 37.7 37.1 ...
#  $ lon         : num  -74.8 -74.9 -74.7 -74.5 -74.8 ...
#  $ date        : POSIXct, format: "2008-03-22 06:22:00" "2008-03-22 17:27:00" "2008-03-22 19:34:00" ...
#  $ depth       : num  62 45 619 59 63 35 117 227 68 42 ...
#  $ volume_100m3: num  16.8 11.87 2.15 50.11 66.71 ...
#  $ salps       : int  0 0 0 29934 29199 11111 6432 0 0 0 ...

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R tools for reading and querying Ecomon datasets

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