Abstract
Fin whales (Balaenoptera physalus) have a global distribution, but the population inhabiting the Gulf of California (GoC) is thought to be geographically and genetically isolated. However, their distribution and movements are poorly known. The goal of this study was to describe fin whale movements for the first time from 11 Argos satellite tags deployed in the southwest GoC in March 2001. A Bayesian Switching State-Space Model was applied to obtain improved locations and to characterize movement behavior as either “area-restricted searching” (indicative of patch residence, ARS) or “transiting” (indicative of moving between patches). Model performance was assessed with convergence diagnostics and by examining the distribution of the deviance and the behavioral parameters from Markov Chain Monte Carlo models. ARS was the predominant mode behavior 83% of the time during both the cool (December-May) and warm seasons (June-November), with slower travel speeds (mean = 0.84 km/h) than during transiting mode (mean = 3.38 km/h). We suggest ARS mode indicates either foraging activities (year around) or reproductive activities during the winter (cool season). We tagged during the cool season, when the whales were located in the Loreto-La Paz Corridor in the southwestern GoC, close to the shoreline. As the season progressed, individuals moved northward to the Midriff Islands and the upper gulf for the warm season, much farther from shore. One tag lasted long enough to document a whale’s return to Loreto the following cool season. One whale that was originally of undetermined sex, was tagged in the Bay of La Paz and was photographed 10 years later with a calf in the nearby San Jose Channel, suggesting seasonal site fidelity. The tagged whales moved along the western GoC to the upper gulf seasonally and did not transit to the eastern GoC south of the Midriff Islands. No tagged whales left the GoC, providing supporting evidence that these fin whales are a resident population.
Highlights
Population ecology has traditionally focused on understanding temporal fluctuations of animal abundance, but how animals move over time is fundamental for understanding population processes, and it is still relatively poorly understood[1]
state-space modeling (SSM) analysis of animal telemetry data has been used in various ways, including to filter error-prone Argos [50] and light-based [65] locations, or to estimate unobserved behavioral states (e.g., 27,30)
Tracks with few Argos locations that were spread over many days led to problems of stability and convergence in all Markov chain Monte Carlo (MCMC) parameters
Summary
Population ecology has traditionally focused on understanding temporal fluctuations of animal abundance, but how animals move over time is fundamental for understanding population processes, and it is still relatively poorly understood[1]. The distribution and population structure of the globally distributed fin whales (Balaenoptera physalus) appears to be more complex than previously thought Their migration patterns do not conform to seasonal movement from summer feeding grounds to winter breeding grounds traditionally posited for baleen whales [28,29]. Sighting data from the southern GoC and the Pacific coast of Baja California give no indication that fin whales migrate between the GoC and the Pacific Ocean [36] This is the main reason previous researchers have recommended satellite tagging in addition to genetic and photo-identification techniques as valuable tools for examining this hypothesis and for better describe their movements [39]. The goal of this study is to fill this knowledge gap by describing fin whale movements and their inferred behavior in the GoC in space and time, using the first satellite telemetry data gathered on this supposedly resident population
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