bt.barrow.2021.RdHow the presence and timing of movements are correlated with annual somatic growth rates is explored, a useful proxy for performance because it is easily measured and rapidly reflects environmental changes, and indicates that lifetime movement is linked to faster growth in the early years of a fish's life.
bt.barrow.2021The data frame 75,343 × 7 contains the following columns:
| fish_id_anon | character | fish identifier |
| distance | numeric | distance from the core to the edge of otolith (um) |
| oto_sr8786 | numeric | otolith 87Sr/86Sr (permil) |
| age | integer | fish age (years) |
| date | numeric | date of capture |
| capture_location | character | location of capture |
| length | numeric | fish length (mm) |
The dataset contains 87Sr/86Sr values in otoliths of 213 individual golden perch Macquaria ambigua from previous studies that sampled MDB rivers in 2014–2017 (Zampatti et al., 2018; Zampatti, Strawbridge, et al., 2018).
Instrument: LA-ICP-MS (lLaser ablation-inductively coupled plasma mass spectrometry)
Barrow, J. S., Yen, J. D., Koehn, J. D., Zampatti, B. P., Thiem, J. D., Tonkin, Z., ... & Morrongiello, J. R. (2021). Lifetime movement history is associated with variable growth of a potamodromous freshwater fish. Journal of Animal Ecology, 90(11), 2560-2572.
https://doi.org/10.1111/1365-2656.13561
Zampatti, B. P., Leigh, S. J., Bice, C. M., & Rogers, P. J. (2018). Multiscale movements of golden perch (Percichthyidae: Macquaria ambigua) in the River Murray, Australia. Austral Ecology, 43(7), 763-774. https://doi.org/10.1111/aec.12619
Zampatti, B. P., Strawbridge, A., Thiem, J. D., Tonkin, Z., Mass, R., Woodhead, J., & Fredberg, J. (2018). Golden perch (Macquaria ambigua) and silver perch (Bidyanus bidyanus) age demographics, natal origin and migration history in the River Murray. S. Publication & S.R.R.S. F2018/000116-1, South Australian Research and Development Institute (Aquatic Sciences).
Data availability are available at https://doi.org/10.26188/14122688
Traversing the paper's information via Semantic Scholar ID b6c28496cf300369595c696010ba6b8f1e7245fc using S2miner package
otolith, vertebra, trace element, stable isotope, Sr8786, Sr/Ca, d34S
### copy data into 'dat'
dat <- bt.barrow.2021
tibble::tibble(dat)
#> # A tibble: 75,343 × 7
#> fish_id_anon distance oto_sr8786 age date capture_location length
#> <chr> <int> <dbl> <int> <chr> <chr> <int>
#> 1 fish_32 0 0.707 7 29/04/2016 Lower.Murray 361
#> 2 fish_33 0 0.708 5 29/04/2016 Lower.Murray 253
#> 3 fish_34 0 0.713 19 29/04/2016 Lower.Murray 362
#> 4 fish_35 0 0.707 6 29/04/2016 Lower.Murray 409
#> 5 fish_36 0 0.713 19 29/04/2016 Lower.Murray 404
#> 6 fish_37 0 0.707 5 29/04/2016 Lower.Murray 239
#> 7 fish_38 0 0.708 5 6/04/2016 Lower.Murray 335
#> 8 fish_39 0 0.713 19 7/04/2016 Lower.Murray 373
#> 9 fish_40 0 0.714 19 12/04/2016 Lower.Murray 379
#> 10 fish_41 0 0.709 6 12/04/2016 Lower.Murray 272
#> # ℹ 75,333 more rows
if (FALSE) {
library(dplyr)
library(ggplot2)
### Sr stable isotope
ggplot(data = dat, aes(distance, oto_sr8786)) +
geom_line(aes(colour = capture_location, group = fish_id_anon),
show.legend = F, na.rm = T) +
facet_grid(capture_location ~. ,scales = "free_y")+
labs(
x = expression(paste("Distance from the core to the edge of otolith (", mu, "m)",
sep = "")),
y = expression(paste(
{}^"87",
"Sr/",
{}^"86",
"Sr"
))
) +
theme_bw() +
theme(
panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank(), axis.line = element_line(colour = "black"),
text = element_text(size = 10), legend.title = element_blank(),
plot.title = element_text(face = "bold")
)
}