bt.quaeckdavies.2018.RdIt is shown that fish eye lens protein is an attractive host for recovery of stable isotope life histories, particularly for juvenile life stages, and especially in elasmobranchs lacking otoliths, but interpretation of lens-based records is complicated by species-specific uncertainties associated with lens growth rates.
bt.quaeckdavies.2018The list contains 5 data frame the following columns:
| species | character | teleost and elasmobranch studied |
| tl | numeric | body length (mm) |
| lens_d | numeric | lens diameter (mm) |
| d13c | numeric | stable isotope d13C values |
| d13cc | numeric | muscle d13C values have been corrected for lipid contents |
| d15n | numeric | stable isotope d15N values |
| tissue | character | muscle (M) and lens (L) |
| fish_id | character | individual fish |
| radius1 | numeric | maximum radial of the subsampled lens |
| radius2 | numeric | minimum radial of the subsampled lens |
| diam1 | numeric | maximum diamater measurements of the subsampled lens |
| diam2 | numeric | minimum diamater measurements of the subsampled lens |
| recovered_length | numeric | estimated fish length at a given lens diameter |
This dataset contains 5 data frame:
TL_LD: Paired eye lens diameter and total body length data. Paired lens diameter (Lens D, mm) and body length (TL, mm) measurements for four species, Squalus acanthias, Coryphaenoides rupestris, Lamna nasus and Aphanopus carbo.
Teleost_lensCore: Stable isotope values of lens cores in three species of fishes. Carbon (d13C) and nitrogen (d15N) values for the central regions of eye lenses in Coryphaenoides rupesitris (grenadier), Lamna nasus (porbeagle) and Aphanopus carbo (scabbard).
CrupL_M: Eye lens and muscle isotope data for juvenile C. rupestris. Eye lens and muscle isotope data (d13C and d15N values) for juvenile C. rupestris from the Rockall Trough.
Acarbo_lens: Isotopic transects across lenses of A. carbo. Stable isotope compositions (d13C d15N values) of sequential lens protein samples in 7 Aphanopus carbo individuals captured in long-line fisheries in west Portugal. Fish ID indicates the individual fish, radius 1 and 2 and diameter 1 and 2 indicate the maximum and minimum radial and diamater measurements of the subsampled lens respectively. Reconstructed length is the estimated fish length at a given lens diameter estimated from allometic scaling relationships given in the text.
Embryo: Stable isotope composition of paired embryonic muscle and lens tissues. Stable isotope (d13C and d15N) values for muscle (M) and lens (L) proteins in 19 embryonic Squalus acanthias. d13Cc values indicate that muscle d13C values have been corrected for lipid contents following Reum (2011).
Instrument: IRMS (isotope ratio mass spectrometer)
Quaeck-Davies, K. Bendall, V. A. MacKenzie, K. M. Hetherington, S. Newton, J. & Trueman, C. N. (2018). Teleost and elasmobranch eye lenses as a target for life-history stable isotope analyses. PeerJ, 6, e4883.
https://doi.org/10.7717/peerj.4883
Traversing the paper's information via Semantic Scholar ID aa714946f791e2e9b834cf8a0b94674a98665105 using S2miner package
otolith, trace element, Sr/Ca
### copy data into 'dat'
dat <- bt.quaeckdavies.2018
### TL_LD data frame
tibble::tibble(dat$TL_LD)
#> # A tibble: 204 × 3
#> species tl lens_d
#> <chr> <dbl> <dbl>
#> 1 Squalus acanthias 870 9
#> 2 Squalus acanthias 1100 13
#> 3 Squalus acanthias 770 9.5
#> 4 Squalus acanthias 840 10
#> 5 Squalus acanthias 650 8
#> 6 Squalus acanthias 1070 11.8
#> 7 Squalus acanthias 780 10
#> 8 Squalus acanthias 830 10.2
#> 9 Squalus acanthias 400 4.75
#> 10 Squalus acanthias 530 7.5
#> # ℹ 194 more rows
### Teleost_lensCore data frame
tibble::tibble(dat$Teleost_lensCore)
#> # A tibble: 29 × 3
#> species d13c d15n
#> <chr> <dbl> <dbl>
#> 1 Coryphaenoides rupesitris -20.6 4.72
#> 2 Coryphaenoides rupesitris -17.9 6.74
#> 3 Coryphaenoides rupesitris -19.9 6.06
#> 4 Coryphaenoides rupesitris -19.5 7.46
#> 5 Coryphaenoides rupesitris -19.7 6.49
#> 6 Coryphaenoides rupesitris -18.3 4.62
#> 7 Coryphaenoides rupesitris -19.5 7.97
#> 8 Coryphaenoides rupesitris -19.6 6.74
#> 9 Coryphaenoides rupesitris -19.1 5.89
#> 10 Coryphaenoides rupesitris -20.5 6.36
#> # ℹ 19 more rows
### CrupL_M data frame
tibble::tibble(dat$CrupL_M)
#> # A tibble: 22 × 4
#> tissue d13c d15n species
#> <chr> <dbl> <dbl> <chr>
#> 1 Lens -20.6 4.93 Coryphaenoides rupesitris
#> 2 Lens -17.9 6.63 Coryphaenoides rupesitris
#> 3 Lens -19.9 6.20 Coryphaenoides rupesitris
#> 4 Lens -19.5 7.55 Coryphaenoides rupesitris
#> 5 Lens -19.7 6.60 Coryphaenoides rupesitris
#> 6 Lens -18.3 4.57 Coryphaenoides rupesitris
#> 7 Lens -19.5 8.05 Coryphaenoides rupesitris
#> 8 Lens -19.6 6.84 Coryphaenoides rupesitris
#> 9 Lens -19.1 5.93 Coryphaenoides rupesitris
#> 10 Lens -20.5 6.57 Coryphaenoides rupesitris
#> # ℹ 12 more rows
### Acarbo_lens data frame
tibble::tibble(dat$Acarbo_lens)
#> # A tibble: 73 × 10
#> fish_id sample d13c d15n radius1 radius2 diam1 diam2 recovered_length species
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 C512 C512B -18.4 15.2 -3.5 4.1 7 8.2 612. Aphanopus carbo
#> 2 C512 C512C -18.7 14.6 -2.8 3.4 5.6 6.8 536. Aphanopus carbo
#> 3 C512 C512D -19.0 14.2 -2.1 2.7 4.2 5.4 460. Aphanopus carbo
#> 4 C512 C512E -19.0 13.5 -1.4 2 2.8 4 384. Aphanopus carbo
#> 5 C512 C512F -19.4 12.2 -0.7 1.3 1.4 2.6 309. Aphanopus carbo
#> 6 C512 C512G -19.8 10.5 0 0.6 0 1.2 233. Aphanopus carbo
#> 7 C512 C512H -19.4 12.6 0.7 1.3 1.4 2.6 309. Aphanopus carbo
#> 8 C512 C512I -18.7 13.4 1.4 2 2.8 4 384. Aphanopus carbo
#> 9 C512 C512J -19.0 14.0 2.1 2.7 4.2 5.4 460. Aphanopus carbo
#> 10 C405 C405A -17.9 15.2 -3.5 4.1 7 8.2 612. Aphanopus carbo
#> # ℹ 63 more rows
### Embryo data frame
tibble::tibble(dat$Embryo)
#> # A tibble: 38 × 6
#> id tissue d15n d13cc d13c2 species
#> <int> <chr> <dbl> <dbl> <dbl> <chr>
#> 1 11 M 12.7 -15.7 -16.2 Squalus acanthias
#> 2 16 M 11.2 -16.0 -16.6 Squalus acanthias
#> 3 28 M 13.8 -15.8 -16.4 Squalus acanthias
#> 4 32 M 11.6 -16.5 -17.0 Squalus acanthias
#> 5 36 M 14.3 -15.4 -15.9 Squalus acanthias
#> 6 37 M 12.0 -16.3 -16.8 Squalus acanthias
#> 7 38 M 11.7 -16.0 -16.4 Squalus acanthias
#> 8 39 M 12.5 -15.5 -16.1 Squalus acanthias
#> 9 54 M 11.7 -15.8 -16.3 Squalus acanthias
#> 10 56 M 12 -16.1 -16.6 Squalus acanthias
#> # ℹ 28 more rows
if (FALSE) {
### load package
library(dplyr)
library(ggplot2)
### TL_LD data frame
ggplot(data = dat$TL_LD, aes(tl, lens_d)) +
geom_point(aes(colour = species), na.rm = T, size = 2) +
geom_smooth(aes(colour = species),
show.legend = F, formula = "y ~ x",
method = "lm", na.rm = T
) +
xlab("Total Length (mm)") +
ylab("Lens Diameter (mm)") +
theme_bw() +
theme(
legend.position = "top",
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")
)
### Teleost_lensCore data frame
ggplot(data = dat$Teleost_lensCore, aes(d13c, d15n)) +
geom_point(aes(colour = species), na.rm = T, size = 3) +
xlab(expression(paste("Lens cores ", delta^{
13
}, "C"))) +
ylab(expression(paste("Lens cores ", delta^{
15
}, "N"))) +
theme_bw() +
theme(
legend.position = "top",
panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank(), axis.line = element_line(colour = "black"),
text = element_text(size = 10), legend.title = element_blank(),
plot.title = element_text(face = "bold")
)
### CrupL_M data frame
ggplot(data = dat$CrupL_M, aes(tissue, d13c)) +
geom_boxplot(aes(colour = tissue), na.rm = T, show.legend = F) +
geom_point(aes(colour = tissue), na.rm = T, show.legend = F) +
xlab("Tissue") +
ylab(expression(paste(delta^{
13
}, "C"))) +
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")
)
ggplot(data = dat$CrupL_M, aes(tissue, d15n)) +
geom_boxplot(aes(colour = tissue), na.rm = T, show.legend = F) +
geom_point(aes(colour = tissue), na.rm = T, show.legend = F) +
xlab("Tissue") +
ylab(expression(paste(delta^{
15
}, "N"))) +
theme_bw() +
theme(
panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank(), axis.line = element_line(colour = "black"),
text = element_text(size = 10), legend.title = element_blank(),
plot.title = element_text(face = "bold")
)
### Acarbo_lens data frame
ggplot(data = dat$Acarbo_lens, aes(radius1, d13c)) +
geom_point(aes(group = fish_id, colour = fish_id), na.rm = T, show.legend = F) +
geom_line(aes(group = fish_id, colour = fish_id), na.rm = T, show.legend = F) +
xlab("Lens radius (mm)") +
ylab(expression(paste(delta^{
13
}, "C"))) +
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")
)
ggplot(data = dat$Acarbo_lens, aes(radius1, d15n)) +
geom_point(aes(group = fish_id, colour = fish_id), na.rm = T, show.legend = F) +
geom_line(aes(group = fish_id, colour = fish_id), na.rm = T, show.legend = F) +
xlab("Lens radius (mm)") +
ylab(expression(paste(delta^{
15
}, "N"))) +
theme_bw() +
theme(
panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank(), axis.line = element_line(colour = "black"),
text = element_text(size = 10), legend.title = element_blank(),
plot.title = element_text(face = "bold")
)
### Embryo data frame
ggplot(data = dat$Embryo, aes(tissue, d13cc)) +
geom_boxplot(aes(colour = tissue), na.rm = T, show.legend = F) +
geom_point(aes(colour = tissue), na.rm = T, show.legend = F) +
xlab("Tissue") +
ylab(expression(paste(delta^{
13
}, "C"))) +
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")
)
ggplot(data = dat$Embryo, aes(tissue, d15n)) +
geom_boxplot(aes(colour = tissue), na.rm = T, show.legend = F) +
geom_point(aes(colour = tissue), na.rm = T, show.legend = F) +
xlab("Tissue") +
ylab(expression(paste(delta^{
15
}, "N"))) +
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")
)
}