bt.wallace.2014.RdEye lens isotopes appear to be useful for reconstructing the isotopic histories of individual fish; these histories can be compared with spatially-derived isoscapes to reconstruct individual histories for site fidelity, movement and trophic position.
bt.wallace.2014The data frame 131 × 10 contains the following columns:
| fish_id | character | fish number assigned at capture |
| species | character | fish studied |
| lens_layer | integer | number assigned lamina during disection; 1 = eye lens core |
| d15n | numeric | bulk d15N (‰) of lamina |
| d13c | numeric | bulk d13C (‰) of lamina |
| lamina_radius | numeric | lamina radius (mm) |
| llamina_mid_pt | numeric | average of the two radius measurements(mm) (before and after) |
| lamina_weight | numeric | lamina weight (mg) |
| resolution | character | low or high resolution using individual lens laminae |
| lamina_side | character | lamina side (left or right) |
The dataset contains fish eye-lens stable isotopes (d13C and d15N) from the eastern Gulf of Mexico, summer 2013, including four red grouper (Epinephelus morio) and three gag (Mycteroperca microlepsis) were obtained from an FWC survey conducted 9–10 July, 2013; eight red snapper (Lutjanus campechanus) were obtained from John's Pass charter vessels on 10 September, 2013 and one white grunt (Haemulon plumierii) was obtained from a charter vessel on 11 June, 2013.
Instrument: CF-IRMS (continuous-flow isotope ratio mass spectrometry)
Reference materials: NIST857, NIST8574, NIST1577b (National Institutes of Standards and Technology)
Wallace, A. A., Hollander, D. J., & Peebles, E. B. (2014). Stable isotopes in fish eye lenses as potential recorders of trophic and geographic history. PLoS One, 9(10), e108935. https://doi.org/10.1371/journal.pone.0108935
Bradley, C. J., Wallsgrove, N. J., Choy, C. A., Drazen, J. C., Hetherington, E. D., Hoen, D. K., & Popp, B. N. (2015). Trophic position estimates of marine teleosts using amino acid compound specific isotopic analysis. Limnology and oceanography: Methods, 13(9), 476-493. https://doi.org/10.1002/lom3.10041
Data availability are available at https://data.gulfresearchinitiative.org/data/R1.x135.120:0006
Traversing the paper's information via Semantic Scholar ID 39a17c40509adbe97e530196b663895a89938f6c using S2miner package
eye lenses, stable isotope, d13C, d15N
### copy data into 'dat'
dat <- bt.wallace.2014
tibble::tibble(dat)
#> # A tibble: 131 × 10
#> fish_id species lens_layer d15n d13c lamina_radius lamina_mid_pt lamina_weight resolution
#> <int> <chr> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
#> 1 48 Lutjanus campe… 1 10.6 -17.4 NA NA NA Low
#> 2 48 Lutjanus campe… 2 11.1 -17.9 NA NA NA Low
#> 3 48 Lutjanus campe… 3 10.6 -17.0 NA NA NA Low
#> 4 48 Lutjanus campe… 4 10.8 -15.7 NA NA NA Low
#> 5 48 Lutjanus campe… 5 11.8 -17.1 NA NA NA Low
#> 6 43 Lutjanus campe… 1 9.94 -18.1 NA NA NA Low
#> 7 43 Lutjanus campe… 2 10.7 -16.7 NA NA NA Low
#> 8 43 Lutjanus campe… 3 11.5 -17.0 NA NA NA Low
#> 9 43 Lutjanus campe… 4 12.2 -17.3 NA NA NA Low
#> 10 46 Lutjanus campe… 1 10.8 -17.9 NA NA NA Low
#> # ℹ 121 more rows
#> # ℹ 1 more variable: lamina_side <chr>
if (FALSE) {
library(dplyr)
library(ggplot2)
### bulk d15N of lamina with low-resolution screening
ggplot(data = dat[which(dat$resolution == "Low"),], aes(lens_layer,d15n))+
geom_point(aes(colour = species, group = fish_id),size = 2, show.legend = F, na.rm = T)+
geom_line(aes(colour = species, group = fish_id),show.legend = F, na.rm = T)+
facet_grid(species ~.,scales = "free_y")+
xlab("Laminae")+
ylab(expression(delta * ""^15 * "N" * " (‰ Air)"))+
scale_x_continuous(breaks = 1:5)+
theme_bw() +
theme(
panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank(), axis.line = element_line(colour = "black"),
text = element_text(size = 10), legend.title = element_blank(),
plot.title = element_text(face = "bold")
)
### bulk d13C of lamina with low-resolution screening
ggplot(data = dat[which(dat$resolution == "Low"),], aes(lens_layer,d13c))+
geom_point(aes(colour = species, group = fish_id),size = 2, show.legend = F, na.rm = T)+
geom_line(aes(colour = species, group = fish_id),show.legend = F, na.rm = T)+
facet_grid(species ~.,scales = "free_y")+
xlab("Laminae")+
ylab(expression(delta * ""^13 * "C" * " (‰ PDB)"))+
scale_x_continuous(breaks = 1:5)+
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")
)
### bulk d15N of lamina with high-resolution screening
ggplot(data = dat[which(dat$resolution == "High"),], aes(lens_layer,d15n))+
geom_point(aes(colour = species, group = fish_id),size = 2, show.legend = F, na.rm = T)+
geom_line(aes(colour = species, group = fish_id),show.legend = F, na.rm = T)+
facet_grid(species ~.,scales = "free_y")+
xlab("Laminae")+
ylab(expression(delta * ""^15 * "N" * " (‰ Air)"))+
scale_x_continuous(breaks = 1:17)+
theme_bw() +
theme(
panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank(), axis.line = element_line(colour = "black"),
text = element_text(size = 10), legend.title = element_blank(),
plot.title = element_text(face = "bold")
)
### bulk d13C of lamina with high-resolution screening
ggplot(data = dat[which(dat$resolution == "High"),], aes(lens_layer,d13c))+
geom_point(aes(colour = species, group = fish_id),size = 2, show.legend = F, na.rm = T)+
geom_line(aes(colour = species, group = fish_id),show.legend = F, na.rm = T)+
facet_grid(species ~.,scales = "free_y")+
xlab("Laminae")+
ylab(expression(delta * ""^13 * "C" * " (‰ PDB)"))+
scale_x_continuous(breaks = 1:17)+
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")
)
### High-resolution comparisons of left and right eyes of white grunt specimen 2
ggplot(data = dat[-which(is.na(dat$lamina_side)),], aes(lamina_mid_pt,d13c))+
geom_point(aes(colour = lamina_side),size = 2, na.rm = T)+
geom_line(aes(colour = lamina_side), na.rm = T)+
xlab("Radial midpoint of lamina (mm)")+
ylab(expression(delta * ""^13 * "C" * " (‰ PDB)"))+
scale_x_continuous(breaks = c(0,0.5,1,1.5,2,2.5,3))+
theme_bw() +
theme(
legend.position = "top",
panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
panel.background = element_blank(), axis.line = element_line(colour = "black"),
text = element_text(size = 10), legend.title = element_blank(),
plot.title = element_text(face = "bold")
)
ggplot(data = dat[-which(is.na(dat$lamina_side)),], aes(lamina_mid_pt,d15n))+
geom_point(aes(colour = lamina_side),size = 2, na.rm = T)+
geom_line(aes(colour = lamina_side), na.rm = T)+
xlab("Radial midpoint of lamina (mm)")+
ylab(expression(delta * ""^15 * "N" * " (‰ Air)"))+
scale_x_continuous(breaks = c(0,0.5,1,1.5,2,2.5,3))+
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")
)
}