"Impact of environmental conditions on the spawning migration of sea trout (Salmo trutta L.) in two large, sub-arctic river systems"

Abstract
The global decline in salmonid stocks has increased the need for knowledge of local adaptations, and life history strategies of salmonids. In this study we used radio-telemetry tracking data from sea trout populations in two large high-latitude rivers to model upstream spawning migration speed of trout in response to prevailing environmental conditions and different stages of the migration. The results indicate that studied populations had similar responses to environmental changes, as trout inhabiting both rivers displayed similar responses to variation in discharge, temperature and migrated distance covered. Higher discharge and temperature had a positive influence on trout migration speed, as did moderate discharge fluctuations. Migration distance influenced movements, as speed increased as trout moved upstream, while speed decreased late in the migration prior to spawning. These results highlight the adaptability of sea trout populations, underlining the importance of stock specific information on habitat use and migration strategies for targeted management.

General information
Title of Dataset: "Impact of environmental conditions on the spawning migration of sea trout (Salmo trutta L.) in two large, sub-arctic river systems"
DOI: 10.17632/6w9c6c7sst.1

Contact Information:
Principal Investigator Contact Information Name: Linus Lähteenmäki
Institution: Åbo Akademi University Address: Aurum, Henriksgatan 2–20520 Åbo, Finland, Email: [e-mail], [e-mail]
ORCID:https://orcid.org/0000-0002-3931-3595

Date of data collection (approximate date): 01-04-2011 - 31-12-2021

Geographic location of data collection: Teno river system (70.5° N, 28.4° E); Tornio river system (65.8° N, 24.1°E)

Dataset includes: Dataset on measured migration speed of sea trout in the two river systems, including environmental and migration characteristics used in the GAMM Analysis (data_large). Environmental data for the study periods to recreate flow and temperature figures (env_data). Population data which include individual fish measurements and migration characteristics (pop_data). Dataset of six individuals to recreate the migration patterns figure of the study (migration_fig).

Recommended citation for this dataset: Lähteenmäki, L., Romakkaniemi, A., Huusko, R., Hellström, G., Orell, P., Erkinaro, J., Rikardsen, A. H., Jensen, J., & Snickars, M. (2026). Data for: "Impact of environmental conditions on the spawning migration of sea trout (Salmo trutta L.) in two large, sub-arctic river systems". Mendeley Data, V1, doi: 10.17632/6w9c6c7sst.1

All datasets used in the data analysis and generation of the visualizations for this study are provided in this repository. Please view the "READ ME" file For more detailed information on dataset contents

### 摘要
全球鲑科鱼类种群的全球性衰退，使得学界对鲑科鱼类本地适应性与生活史策略的认知需求显著提升。本研究依托两座大型高纬度河流中海鳟种群的无线电遥测跟踪数据，构建了海鳟上游产卵洄游速度模型，以分析其对当前环境条件及洄游不同阶段的响应特征。研究结果表明，两个研究种群对环境变化的响应模式高度相似：栖息于两条河流的海鳟，在流量、水温变化以及洄游累计距离上均表现出一致的响应规律。较高的流量与水温对海鳟洄游速度具有正向促进作用，适度的流量波动亦能产生类似的积极影响。洄游距离会显著影响移动行为：海鳟向上游行进时洄游速度逐步提升，而在产卵前的洄游后期，洄游速度则会出现下降。本研究结果凸显了海鳟种群的环境适应性，同时强调了针对种群特异性的栖息地利用与洄游策略信息，对开展针对性渔业管理的重要价值。

### 数据集基本信息
数据集标题：《环境条件对两大亚北极河流系统中海鳟（*Salmo trutta* L.）产卵洄游的影响》
DOI：10.17632/6w9c6c7sst.1

#### 联系方式
项目负责人：Linus Lähteenmäki
所属机构：奥博学术大学（Åbo Akademi University）
通讯地址：芬兰图尔库，Aurum校区，Henriksgatan 2–20520
电子邮箱：[e-mail]、[e-mail]
ORCID：https://orcid.org/0000-0002-3931-3595

#### 数据采集时间（近似范围）：2011年4月1日 — 2021年12月31日

#### 数据采集地理区域
塔纳河系统（北纬70.5°，东经28.4°）；托尔尼奥河系统（北纬65.8°，东经24.1°）

#### 数据集包含内容
1. 两大河流系统中海鳟洄游速度实测数据集，包含广义相加混合模型（Generalized Additive Mixed Models, GAMM）分析所用的环境与洄游特征数据（data_large）；
2. 研究周期内的环境数据，用于复现流量与水温统计图表（env_data）；
3. 种群数据，包含个体鱼类测量信息与洄游特征数据（pop_data）；
4. 用于复现本研究洄游模式图表的6尾个体数据集（migration_fig）。

### 数据集推荐引用格式
Lähteenmäki, L., Romakkaniemi, A., Huusko, R., Hellström, G., Orell, P., Erkinaro, J., Rikardsen, A. H., Jensen, J., & Snickars, M. (2026). 数据集：《环境条件对两大亚北极河流系统中海鳟（*Salmo trutta* L.）产卵洄游的影响》. Mendeley 数据, 第1版, doi: 10.17632/6w9c6c7sst.1

本研究数据分析与可视化生成所用的全部数据集均已上传至本仓库，如需了解数据集内容的详细信息，请查阅“README”文件。