Individual Based Modelling of Fish Migration in a 2-D River System: Model Description and Case Study.
Landsc Ecol
; 34(4): 737-754, 2019 Apr 01.
Article
em En
| MEDLINE
| ID: mdl-33424124
CONTEXT: Diadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. These stressors complicate the prioritization of proposed management actions intended to improve conditions for migratory fishes including anadromous salmon and trout. OBJECTIVES: We describe a multi-scale hybrid mechanistic-probabilistic simulation model linking migration corridor conditions to fish fitness outcomes. We demonstrate the model's utility using a case study of salmon and steelhead adults in the Columbia River migration corridor exposed to spatially- and temporally-varying stressors. METHODS: The migration corridor simulation model is based on a behavioral decision tree that governs individual interactions with the environment, and an energetic submodel that estimates the hourly costs of migration. Emergent properties of the migration corridor simulation model include passage time, energy use, and survival. RESULTS: We observed that the simulated fishes' initial energy density, the migration corridor temperatures they experienced, and their history of behavioral thermoregulation were the primary determinants of their fitness outcomes. Insights gained from use of the model might be exploited to identify management interventions that increase successful migration outcomes. CONCLUSIONS: This paper describes new methods that extend the suite of tools available to aquatic biologists and conservation practitioners. We have developed a 2-dimensional spatially-explicit behavioral and physiological model and illustrated how it can be used to simulate fish migration within a river system. Our model can be used to evaluate trade-offs between behavioral thermoregulation and fish fitness at population scales.
Texto completo:
1
Base de dados:
MEDLINE
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article