Variability in Billfish Vertical Distribution and Fishing Interactions Driven by Environmental Conditions in the Eastern Tropical Pacific Ocean

H. E. Blondin, D. E. Haulsee, Ryan Logan, Mahmood Shivji, E. R. Hoffmayer, J. H. Walker, J. M. Dean, E. L. Hazen, L. B. Crowder

Research output: Contribution to journalArticlepeer-review

Abstract

Blue marlin ( Makaira nigricans ) and sailfish ( Istiophorus platypterus ) are ecologically important predators and valuable species throughout the world’s recreational, commercial, and subsistence fisheries. Comparing multi-species vertical habitat use can inform ecological uncertainties such as inter-species competition, as well as relative vulnerabilities to fishing activities. In this study, we identified key differences in both depth use and which environmental variables drive these selections, which highlights the variability in the catchability both as target species in recreational fisheries and bycatch in commercial fisheries. To understand these two species’ vertical habitat use, we examined depth profiles from 26 sailfish and 48 blue marlin tagged with pop-up satellite archival tags deployed in the Eastern Tropical Pacific Ocean. While both species are surface-oriented, we found evidence of vertical niche partitioning where sailfish spend more time at deeper depths than blue marlin. Blue marlin recorded an average mean depth of 18.5 m (±10.8 m) during daytime and 5.2 m (±5.5 m) at nighttime (Figure 31a), while sailfish recorded an average mean depth of 23.6 m (±11.1 m) during daytime and 6.45 m (±4.64 m) at nighttime. Generalized additive mixed models fitted to predict mean and max depth revealed sea level anomaly (SLA), oxygen, sea surface temperature, and mixed layer depth as significant predictors of vertical habitat use for both species. We also examined catch logs from three recreational fishing lodges in Central America to understand the influence of environmental conditions on billfish sightings per unit effort. For blue marlin and sailfish, SLA was a significant predictor in each of the four depth models (mean day, mean night, max day, max night). SLA was the variable with highest percent deviance explained for all four sailfish depth models and three of the four blue marlin depth models and had a positive relationship with all response variables for all four blue marlin depth models and three sailfish depth models (mean daytime, max daytime, max nighttime), where higher positive SLA values were associated with deeper depth responses.

Original languageAmerican English
Pages (from-to)1629-1642
Number of pages14
JournalICES Journal of Marine Science
Volume80
Issue number6
DOIs
StatePublished - Aug 1 2023

Funding

We thank the generous funding provided by Pure Edge, Inc. and the Woods Institute for the Environment, Stanford University in support of HEB and DEH, as well as Guy Harvey Ocean Foundation [grant number GHOF 2019], the Guardians of the Eastern Tropical Pacific Seascape donor group, Nova Southeastern University, and the Gallo-Dubois Scholarship, Fish Florida Scholarship, and Batchelor Foundation Scholarship to RL.

FundersFunder number
Stanford University
Nova Southeastern University
Stanford Woods Institute for the Environment
Guy Harvey Ocean FoundationGHOF 2019
Batchelor Foundation

    ASJC Scopus Subject Areas

    • Ecology, Evolution, Behavior and Systematics
    • Aquatic Science
    • Oceanography
    • Ecology

    Keywords

    • billfish
    • blue marlin
    • conservation
    • fisheries
    • sailfish
    • satellite telemetry.
    • satellite telemetry

    Disciplines

    • Biology

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