Unmasking continental natal homing in goliath catfish

The authors test here the complementarity of both approaches (87Sr:86Sr by LA-MC-ICPMS and Se:Ca, Sr:Ca by SXFM) to investigate if the natal homing behaviour observed for Brachyplatystoma rousseauxii in the Madeira also exists along the Amazon mainstem, which would enhance our knowledge of the complex ecology of this species.

bt.hauser.2020

Format

The data frame 3,709 × 16 contains the following columns:

fish_id	integer	fish identifier
real_distance	numeric	real distance from otolith core
normalized_distance	numeric	normalized distance from otolith core
value	numeric	biogeochemical value (x1000 in trace element; ‰ in stable isotope)
elements	character	se/ca, sr/ca, sr8786
biogeochemical_tags	character	trace element and stable isotope
basin	character	basin of capture
river	character	river of capture
country	character	country of capture
dam	character	period of capture (before or after the dams)
date	integer	date of capture
sl	numeric	standard length (cm)
sex	character	fish sex
sl	integer	growth_rings
age	numeric	fish age (years)
behaviour	numeric	migratory behaviour determined by sr8786 analysis

Details

This dataset contains seven Brachyplatystoma rousseauxii for the Sr:Ca, Se:Ca, and 87Sr:86Sr profiles.

Instrument: SXFM (scanning x-ray fluorescence imaging), LA-MC-ICP-MS (laser ablation multi-collector inductively coupled plasma mass spectrometry)

Source

Hauser, M., Duponchelle, F., Hermann, T. W., Limburg, K. E., Castello, L., Stewart, D. J., ... & Doria, C. R. (2020). Unmasking continental natal homing in goliath catfish from the upper Amazon. Freshwater Biology, 65(2), 325-336. https://doi.org/10.1111/fwb.13427

Traversing the paper's information via Semantic Scholar ID 2311e44d4b5ca858ad2c8063c119259a6a3146fc using S2miner package

Author

Liuyong Ding, ly_ding@126.com

Concepts

otolith, trace element, stable isotope, Sr/Ca, Se/Ca, Sr8786

Examples

### copy data into 'dat'
dat <- bt.hauser.2020
tibble::tibble(dat)
#> # A tibble: 3,709 × 16
#>    fish_id real_distance normalized_distance   value elements biogeochemical_tags basin  river country
#>    <chr>           <dbl>               <dbl>   <dbl> <chr>    <chr>               <chr>  <chr> <chr>  
#>  1 BR56            0                 0       0.00280 SeCa     bulk elements       Upper… Mamo… Bolivia
#>  2 BR56            0.994             0.00901 0.00350 SeCa     bulk elements       Upper… Mamo… Bolivia
#>  3 BR56            1.99              0.0180  0.00300 SeCa     bulk elements       Upper… Mamo… Bolivia
#>  4 BR56            2.98              0.0270  0.00390 SeCa     bulk elements       Upper… Mamo… Bolivia
#>  5 BR56            3.98              0.0360  0.00610 SeCa     bulk elements       Upper… Mamo… Bolivia
#>  6 BR56            4.97              0.0451  0.00720 SeCa     bulk elements       Upper… Mamo… Bolivia
#>  7 BR56            5.97              0.0541  0.00660 SeCa     bulk elements       Upper… Mamo… Bolivia
#>  8 BR56            6.96              0.0631  0.00550 SeCa     bulk elements       Upper… Mamo… Bolivia
#>  9 BR56            7.96              0.0721  0.00440 SeCa     bulk elements       Upper… Mamo… Bolivia
#> 10 BR56            8.95              0.0811  0.00270 SeCa     bulk elements       Upper… Mamo… Bolivia
#> # ℹ 3,699 more rows
#> # ℹ 7 more variables: dam <chr>, date <int>, sl <int>, sex <chr>, growth_rings <int>, age <dbl>,
#> #   behaviour <chr>

if (FALSE) {
### load package
library(dplyr)
library(ggplot2)

### otolith Sr:Ca profiles
ggplot(data = dat[which(dat$elements == "SrCa"), ], aes(normalized_distance, value)) +
  geom_line(aes(group = fish_id, colour = "black"), show.legend = F, na.rm = T) +
  facet_grid(fish_id ~ ., scales = "free_y") +
  xlab("Normalized_distance from otolith core") +
  ylab("Otolith Sr:Ca (x1000)") +
  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")
  )

### otolith Se:Ca profiles
ggplot(data = dat[which(dat$elements == "SeCa"), ], aes(normalized_distance, value)) +
  geom_line(aes(group = fish_id, colour = "blue"), show.legend = F, na.rm = T) +
  facet_grid(fish_id ~ ., scales = "free_y") +
  xlab("Normalized_distance from otolith core") +
  ylab("Otolith Se:Ca (x1000)") +
  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")
  )

### otolith 87Sr:86Sr profiles
ggplot(data = dat[which(dat$elements == "Sr8786"), ], aes(normalized_distance, value)) +
  geom_line(aes(group = fish_id, colour = "red"), show.legend = F, na.rm = T) +
  facet_grid(fish_id ~ ., scales = "free_y") +
  xlab("Normalized_distance from otolith core") +
  ylab(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")
  )
}