DOI: 10.5061/dryad.9p8cz8wjg
title: Atlantic salmon survival at sea: temporal changes that lack regional synchrony

description: Spatial and temporal synchrony in abundance or survival trends can be
 indicative of whether populations are affected by common environmental
 drivers. In Atlantic salmon (Salmo salar L.), return rates to natal rivers
 have generally been assumed to be affected primarily by shared oceanic
 conditions, leading to spatially synchronous trends in mortality. Here, we
 investigate the existence of parallel trends in salmon sea survival, using
 data on migrating smolts and returning adults from seven Canadian
 populations presumed to share feeding grounds. We analyse sea survival,
 using a Bayesian change-point model capable of detecting non-stationarity
 in time series data. Our results indicate that while salmon have
 experienced broadly comparable patterns in survival, finer-scale temporal
 shifts are not synchronous among populations. Our findings are not
 consistent with the hypothesis that salmon populations consistently share
 the same mortality-related stressors in the marine environment. Although
 populations may have shared greater synchrony in survival patterns in the
 past, this synchrony may be breaking down. It may be prudent to direct
 greater attention to smaller-scale regional and population-level
 correlates of survival
description: We analysed the time series of smolts and returning fish of
 Atlantic salmon populations in seven rivers in eastern Canada. In this, we
 used a Bayesian change-point model that has the Murphy's maturity
 schedule as the underlying predictive model. The
 numbers of emigrating smolts were estimated from mark-recapture studies or
 directly recorded at counting fences during their seaward migration. The
 methods are fully cited by Pardo et al. (2021). The number of returning
 adults was based on direct counts of small (&lt; 63 cm) and large
 (&lt;= 63 cm) salmon. Age determination from scales was done for a
 subset of returns each year, which allowed for calculating the proportion
 of different age classes within the size groups, and subsequently estimate
 the total proportion of each age class among the returning fish (see Pardo
 et al, 2021). In order to decrease bias in our results
 caused by measurement errors, we fitted our model using the medians of the
 posterior distributions of the true smolt abundances obtained by Pardo et
 al. (2021) as smolt abundance data. In addition, we utilized the estimated
 measurement errors by Pardo et al. (2021) in returning fish abundance data
 in our model. 
description: In each river-specific data set, there are the following
 variables: year river_name
 sw_dominance: the population is either dominated by 1SW (value
 '1') or 2SW fish ('2') logsmolts:
 the recorded number of smolts in log-scale for each year
 logsmolts_est: the estimated true smolt abundance (the posterior
 median obtained by Pardo et al., 2021) for each year
 logSW1: the recorded number of returning 1SW fish in
 log-scale logSW2: the recorded number of returning 2SW
 fish in log-scale logSW1_cv: the estimated measurement
 error in logSW1 logSW2_cv: the estimated measurement
 error in logSW2 For three rivers, there was one or two
 missing years within their time series. For those years, there had been no
 smolt count due to too much water flow. In addition, in some years for
 1SW-dominated populations, estimates of 2SW were zero. These counts were
 included in the analysis by adding a small quantity to enable
 log-transformation.