DOI: 10.5061/dryad.cvdncjtds
title: Data from: Bayesian species recognition and abundance estimation: Unravelling the mysteries of salmonid migration in the Teno River

description: In Teno River, annual sonar monitoring is used to estimate the abundance
 of three salmonid species: Atlantic salmon, pink salmon and sea trout.
 However, the size distribution of these species is partially overlapping
 making species recognition impossible from plain sonar data. A Bayesian
 model was developed to tackle this problem and to estimate abundance and
 migration timing for these three species. The model integrates multiple
 sources of data including catch, video count, daily average school sizes
 and expert knowledge. Given the limited catch and video statistics for
 2021, the use of school size data and expert knowledge on migration
 intensity enhanced the estimation when other data sources were
 unavailable. The model estimated a median of 11.8 thousand Atlantic
 salmon, 6.6 thousand sea trout and 52.0 thousand pink salmon migrating
 into the river during 2021. These findings offer a more accurate
 representation of species distribution, support future conservation and
 management efforts, and provide a modelling-based solution for
 distinguishing similarly sized species from sonar counting data.
description: # Data from: Bayesian species recognition and abundance estimation:
 Unravelling the mysteries of salmonid migration in the Teno River
 [https://doi.org/10.5061/dryad.cvdncjtds](https://doi.org/10.5061/dryad.cvdncjtds) ## Description of the data and file structure The data was collected to model the abundance of Atlantic salmon, pink salmon, and sea trout in the Teno River in 2021. Experimental efforts included systematic data collection using sonar monitoring, video monitoring, and small-scale experimental fishing. ### Files and variables #### File: data\_for\_running\_the\_model.RDS **Description:**  The file contains all necessary data for running the model. Variable names match those used in the model code. The data is provided in .RDS format, which is compatible with R software. Missing values are indicated as NA. n:  Number of individual days. obs_index: Individual days for which sonar counts are available. catch_index: Individual days for which catch data is available. video_index: Individual days for which video counts are available. n_obs: Number of sonar-detected fish per day. catch: Number of caught fish per day (Atlantic salmon or pink salmon or sea trout). c_at: Number of caught Atlantic salmon per day. c_pi: Number of caught pink salmon per day. c_tr: Number of caught sea trout per day. video: Number of fish observed on video per day (Atlantic salmon or pink salmon or sea trout). v_at: Number of Atlantic salmon observed on video per day. v_pi: Number of pink salmon observed on video per day. v_tr: Number of sea trout observed on video per day. k: Number of fish schools per day. mu_q_at: Expert-defined expected values for the intensity of Atlantic salmon migration. mu_q_pi: Expert-defined expected values for the intensity of pink salmon migration. mu_q_tr: Expert-defined expected values for the intensity of sea trout migration. ## Code/software R software is required to view the data. The data can be loaded into R using the readRDS() function, which is included in the base R package. R version 4.4.1 was used to create the data and run the model. To run the JAGS model, JAGS version 4.3 was used along with the R-package runjags.