Data from: Bayesian species recognition and abundance estimation: Unravelling the mysteries of salmonid migration in the Teno River ...

• Main Authors: Räty, Antti, Pulkkinen, Henni, Erkinaro, Jaakko, Orell, Panu, Falkegård, Morten, Mäntyniemi, Samu
• Format: Dataset
• Language: English
• Published: Dryad 2025
• Subjects: FOS: Agriculture, forestry, and fisheries; Atlantic salmon; pink salmon; sonar monitoring; Bayesian modelling; Teno River; Teno; Pink salmon
• Online Access: https://dx.doi.org/10.5061/dryad.cvdncjtds; https://datadryad.org/dataset/doi:10.5061/dryad.cvdncjtds

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 ... : # 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 ...