fishdata provides some basic datasets for the study of fish population dynamics. All data was collected in the Wellington region of New Zealand between 2015-2016. Study species in question was the amphidromous fish Galaxis maculatus, commonly known as ‘whitebait’. This data was collected as part of my Masters thesis at Victoria University of Wellington.
Six datasets are provided by the package (three for juvenile fish, three for adult fish). The base datasets contain one row per fish, and provide basic data around catch date and location.
library(fishdata)
data("juveniles")
data("adults")
head(juveniles)
#> fish_code fish otolith_code site day month catch_date
#> 1 W13.1 582 34 Wainuiomata 13 October 2015-10-30
#> 2 W13.2 583 20 Wainuiomata 13 October 2015-10-30
#> 3 W13.3 584 359 Wainuiomata 13 October 2015-10-30
#> 4 W13.4 585 422 Wainuiomata 13 October 2015-10-30
#> 5 W13.5 586 54 Wainuiomata 13 October 2015-10-30
#> 6 W13.6 587 471 Wainuiomata 13 October 2015-10-30
head(adults)
#> fish_code site day catch_date
#> 1 H.1 Hutt H1 2016-03-25
#> 2 H.2 Hutt H2 2016-04-07
#> 3 H.3 Hutt H2 2016-04-07
#> 4 H.4 Hutt H2 2016-04-07
#> 5 H.7 Hutt H3 2016-04-13
#> 6 H.9 Hutt H3 2016-04-13Building on the base datasets are the ‘metrics’ datasets which provide info around age, birthdate, and growth rates. These are still in the one row per fish format.
data("juvenile_metrics")
head(juvenile_metrics)
#> fish_code standard_length body_depth age birthdate growth_rate early_growth
#> 1 W13.1 42.535 3.527 168 2015-05-15 1.723470 3.1096
#> 2 W13.2 46.651 3.923 179 2015-05-04 1.730324 2.7884
#> 3 W13.3 45.466 3.820 189 2015-04-24 1.530831 2.0416
#> 4 W13.4 43.483 3.918 185 2015-04-28 1.636211 3.2546
#> 5 W13.5 44.896 3.572 182 2015-05-01 1.659885 1.9756
#> 6 W13.6 46.581 4.032 174 2015-05-09 1.773362 2.5970
#> late_growth
#> 1 1.3636
#> 2 1.1018
#> 3 0.9476
#> 4 1.4226
#> 5 1.0654
#> 6 1.3134
data("adult_metrics")
head(adult_metrics)
#> fish_code standard_length body_depth age birthdate growth_rate
#> 1 H.1 5.631 0.817 274 2015-06-25 1.6938
#> 2 H.2 5.838 0.768 317 2015-05-26 1.9324
#> 3 H.3 5.876 0.824 298 2015-06-14 1.7972
#> 4 H.4 5.330 0.543 305 2015-06-07 1.8331
#> 5 H.7 6.873 0.827 291 2015-06-27 2.0771
#> 6 H.9 4.752 0.559 296 2015-06-22 1.7332Finally, there are the growth datasets. The growth datasets contain measures of daily growth per fish (estimated using otolith rings). As these datasets use a row to represent one day of growth in a fish’s life, they allow for the complete reconstruction of growth profiles. The ages of fish can also be calculated by finding the maximum period (or ‘increment’) for each fish.
data("juvenile_growth")
head(juvenile_growth)
#> fish_code otolith_code period position distance
#> 1 W4.3 133 1 4.935 4.935
#> 2 W4.3 133 2 7.615 2.680
#> 3 W4.3 133 3 9.096 1.481
#> 4 W4.3 133 4 10.516 1.420
#> 5 W4.3 133 5 12.308 1.792
#> 6 W4.3 133 6 13.628 1.320
data("adult_growth")
head(adult_growth)
#> fish_code period position distance
#> 1 H.1 1 4.528 4.528
#> 2 H.1 2 6.524 1.996
#> 3 H.1 3 8.518 1.994
#> 4 H.1 4 10.434 1.915
#> 5 H.1 5 12.324 1.891
#> 6 H.1 6 14.274 1.950For information on the column meanings, please see the documentation. For more information on the underlying data model (i.e., how the tables link to each other), please check out the ‘Data Model’ vignette. Finally, for some examples of using this data, please see ‘Examples’ vignette.
