Data from: Genetic consequences of improved river connectivity in brown trout (Salmo trutta)
Data files
Feb 20, 2024 version files 233.93 KB
Abstract
Fragmentation of watercourses poses a significant threat to biodiversity, particularly for migratory fish species. Mitigation measures such as fishways, have been increasingly implemented to restore river connectivity and support fish migration. The effects of such restoration efforts are typically tested using telemetry and fisheries methods, which do not fully capture the broader population movements that may have important consequences for population viability. We performed a before-and-after control-impact (BACI) study using genetic tools (SNPs) to investigate the effect of a newly implemented fishway, aiming to enhance upstream spawning migration of brown trout (Salmo trutta Linnaeus) in a reservoir with two headwater tributaries fragmented by man-made weirs. Another reservoir with two barrier-free tributaries was also analysed as a control. Our results showed that the isolated brown trout population was spawning in the reservoir before the installation of the fishway, and we found genetic structuring and differentiation between fragmented headwater tributaries before the fishway construction, but not in the control reservoir. Unexpectedly, after the fishway construction we observed signals consistent with increased genetic differentiation between populations of newly recruited juvenile fish in the reservoir tributary and fish in the reservoir. We propose this was caused by newly enabled philopatric behaviour of brown trout to their natal spawning tributary. In contrast, we did not find any genetic changes in the tributary without a fishway or in the barrier-free reservoir system. Given the scarcity of similar studies, we advocate for an increased use of genetic analyses in BACI studies to monitor and evaluate the effect of efforts to restore habitat connectivity and inform future management strategies.
README: Files and code for: Moccetti et al. 2024 - Genetic consequences of improved river connectivity in brown trout (Salmo trutta) - Evolutionary Applications
https://doi.org/10.5061/dryad.80gb5mkxk
Description of the data
The folder 'input_files' contains SNP data, map file, and other necessary files to run the analyses. Specifically:
- 'allChr_orderedped_trout.txt': this is the 'ped' file containing the SNP calls for each individual
- 'trout_all_chr.map.txt': this is the 'map' file containing information for each SNP marker. The four columns represent (from left to right): Chromosome ID (e.g. '1'), SNP ID (e.g. '470946'), Genetic distance (in this case unknown for all SNPs, labelled as'0') and physical position in centimorgans (e.g. '42.452').
- 'AMP7_Lang_and_Grim_before_only_29.06.23': this is a list of individuals used to subset the dataset in the example provided in the code.
'Samples_INFO.csv': this is the file with all the information for each sample included in the study. It includes the following columns:
- sampling.date: exact date of sampling when available (format: DD/MM/YYYY)
- Year: year of sampling.
- Period: "Before" or "After" the construction of the fish pass on the RLD.
- Group: information about the location (i.e., 'BGB'= Blea Gill beck, 'Grimwith'=Grimwith Reservoir, 'GUG'=Gate Up Gill, 'RLD'=River Little Don, 'Langsett'= Langsett Reservoir, 'TWB'= Thickwoods Brook) combined with period of sampling ('Before' or 'After').
- Location: sampling location (i.e., 'BGB', 'Grimwith res', 'GUG', 'RLD', 'Langsett res', 'TWB').
- Tributary: the tributary of origin of the samples (if not the main reservoir).
- Site: sampling site name.
- Site.notes: when available notes about sampling locations.
- Length..mm.: fork length of samples in mm.
- ref.genetics: ID used for genetic analyses
- System: reservoir system of origin ('Langsett' or 'Grimwith')
** IMPORTANT NOTE:** the extensions of the following files must be changed manually in the following way to be able to run the provided code.
'allChr_orderedped_trout.txt' --> change into'allChr_orderedped_trout.ped'
'trout_all_chr.map.txt' --> change into'trout_all_chr.map.map'
Code
An example code to run the analyses of the study using the provided files is included in the folder called: 'CODE_Moccetti_et_Al_2024_EvoAppl'. Here, the script is contained in the file called 'CODE_Moccetti_et_Al_2024_EvoAppl.md', while some supporting figures mentioned in or produced through the code can be found in the "Figures" subfolder.