Contrasting Phylogeographic Patterns Among Northern and Southern Hemisphere Fin Whale Populations With New Data From the Southern Pacific

Abstract

Four fin whale sub-species are currently considered valid: Balaenoptera physalus physalus in the North Atlantic, B. p. velifera in the North Pacific, B. p. quoyi and B. p. patachonica in the Southern Hemisphere. The last, not genetically validated, was described as a pygmy-type sub-species, found in low to mid latitudes of the Southern Hemisphere. Genetic analyses across hemispheres show strong phylogeographic structure, yet low geographic coverage in middle latitudes of the Southern Hemisphere impeded an assessment within the area, as well as evaluating the validity of B. p. patachonica. New mtDNA sequences from the Southeastern Pacific allowed an improved coverage of the species’ distribution. Our phylogenetic analyses showed three main lineages and contrasting phylogeographic patterns between Northern and Southern Hemispheres. Absence of recurrent female mediated gene flow between hemispheres was found; however, rare dispersal events revealing old migrations were noted. The absence of genetic structure suggests the existence of one single taxa within the Southern Hemisphere. Thus, until further evidence supporting this subspecies can be produced, such as genetic, ecological, behavioral, or morphological data, we propose that all fin whales from the Southern Hemisphere, including those from middle latitudes of the Southeastern Pacific belong to B. p. quoyi subspecies. This information is important for the current assessment of fin whales, contributing to the evaluation of the taxonomic classification and the conservation of the species.

Phylogeography and demographic inference of the endangered sei whale, with implications for conservation

“…At the inter-hemispheric level, some species do present occasional gene flow across hemispheres but still show a marked phylogeographic structure, probably related to the delayed migration behaviour precluding mixing between hemispheres (Jackson et al, 2014). This is the case, for example, with fin whales (Archer et al, 2013;Cabrera et al, 2019;Pérez-Alvarez et al, 2021), humpback whales (Jackson et al, 2014) and minke whales (Glover et al, 2010).…”

First evidence for fin whale migration into the Pacific from Antarctic feeding grounds at Elephant Island

“…Genetic analysis of biopsy samples collected from fin whales may also help to gain insights into population structure and the likelihood of populations mixing on the feeding ground. Recent phylogenetic analyses, however, have shown an absence of strong genetic structure in fin whales of the Southern Hemisphere [16]. In the Northern Hemisphere, genetic differentiation between the Atlantic and the Pacific is strong [17,36].…”

“…In the Northern Hemisphere, genetic differentiation between the Atlantic and the Pacific is strong [17,36]. A pattern that has been observed also for humpback whales [36] and which is likely related to continents separating ocean basins and preventing inter-oceanic dispersal [16]. In the Southern Hemisphere, low genetic differentiation and high gene flow among regions have been reported for humpback whales despite the existence of discrete breeding stocks [37].…”

“…Fin whales of the Southern Hemisphere are thought to belong to one subspecies, B. physalus quoyi [16], but their finer-scale population structure is still poorly understood [16,17]. Therefore, whether fin whales feeding at Elephant Island belong to one or several breeding populations is still unknown.…”

Survivors and colonizers: Contrasting biogeographic histories reconciled in the Antarctic freshwater copepod Boeckella poppei

“…For example, in katydid insects the intraspecific mutation rate calibrated with a post-Pleistocene event was 14.4%-17.3% per million years, 13 times greater than the phylogenetic mutation rate (Ney et al, 2018). Similar corrections have been implemented in population-based studies of several Antarctic organisms, including fin whales (Pérez-Alvarez et al, 2021), copepods (Maturana et al, 2020), sea urchins (Diaz et al, 2018), gentoo penguins (Vianna et al, 2017), algae (Billard et al, 2015) and limpets (González-Wevar et al, 2011). The two independent MCMC calculations were run for 50 × 10 6 generations (sampled every 1,000 iterations), discarding the first 10% of parameter values as burn-in.…”