Estimating thermal response metrics for North American freshwater fish using Bayesian phylogenetic regression
Autor: | Brian J. Shuter, Michael Escobar, Sarah Hasnain |
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Rok vydání: | 2018 |
Předmět: |
0106 biological sciences
0301 basic medicine biology Phylogenetic tree Range (biology) Ecology media_common.quotation_subject Bayesian probability Aquatic Science biology.organism_classification 010603 evolutionary biology 01 natural sciences Regression 03 medical and health sciences 030104 developmental biology Freshwater fish Fish Reproduction Ecology Evolution Behavior and Systematics media_common |
Zdroj: | Canadian Journal of Fisheries and Aquatic Sciences. 75:1878-1885 |
ISSN: | 1205-7533 0706-652X |
Popis: | Physiological performance in fish peaks within a well-defined range of temperatures, which is distinct for each species. Species-specific thermal responses for growth, survival, and reproduction are most commonly quantified directly through laboratory experiment or field observation, with a focus on six specific metrics: optimum growth temperature and final temperature preferendum (growth), upper incipient lethal temperature and critical thermal maximum (survival), and optimum spawning temperature and optimum egg development temperature (reproduction). These values remain unknown for many North American freshwater fish species. In this paper, we present a new statistical method (Bayesian phylogenetic regression) that uses relationships between these metrics and phenetic relatedness to estimate unknown metric values. The reliability of these estimates was compared with those derived from models incorporating taxonomic family and models without any taxonomic information. Overall, incorporating taxonomic family relatedness improved estimation accuracy across all metrics. For Salmonidae and Cyprinidae, estimates derived from Bayesian phylogenetic regression typically had the highest expected reliability. We used our methods to generate 274 estimates of unknown metric values for over 100 North American freshwater fish species. |
Databáze: | OpenAIRE |
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