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A clear understanding of population structure is essential for assessing conservation status and implementing management strategies. A small, non-migratory population of humpback whales in the Arabian Sea is classified as "Endangered" on the IUCN Red List of Threatened Species, an assessment constrained by a lack of data, including limited understanding of its relationship to other populations. We analysed 11 microsatellite markers and mitochondrial DNA sequences extracted from 67 Arabian Sea humpback whale tissue samples and compared them to equivalent datasets from the Southern Hemisphere and North Pacific. Results show that the Arabian Sea population is highly distinct; estimates of gene flow and divergence times suggest a Southern Indian Ocean origin but indicate that it has been isolated for approximately 70,000 years, remarkable for a species that is typically highly migratory. Genetic diversity values are significantly lower than those obtained for Southern Hemisphere populations and signatures of ancient and recent genetic bottlenecks were identified. Our findings suggest this is the world's most isolated humpback whale population, which, when combined with low population abundance estimates and anthropogenic threats, raises concern for its survival. We recommend an amendment of the status of the population to "Critically Endangered" on the IUCN Red List.

Humpback whales (Megaptera novaeangliae) annually undertake the longest migrations between seasonal feeding and breeding grounds of any mammal. Despite this dispersal potential, discontinuous seasonal distributions and migratory patterns suggest that humpbacks form discrete regional populations within each ocean. To better understand the worldwide population history of humpbacks, and the interplay of this species with the oceanic environment through geological time, we assembled mitochondrial DNA control region sequences representing approximately 2700 individuals (465 bp, 219 haplotypes) and eight nuclear intronic sequences representing approximately 70 individuals (3700 bp, 140 alleles) from the North Pacific, North Atlantic and Southern Hemisphere. Bayesian divergence time reconstructions date the origin of humpback mtDNA lineages to the Pleistocene (880 ka, 95% posterior intervals 550-1320 ka) and estimate radiation of current Northern Hemisphere lineages between 50 and 200 ka, indicating colonization of the northern oceans prior to the Last Glacial Maximum. Coalescent analyses reveal restricted gene flow between ocean basins, with long-term migration rates (individual migrants per generation) of less than 3.3 for mtDNA and less than 2 for nuclear genomic DNA. Genetic evidence suggests that humpbacks in the North Pacific, North Atlantic and Southern Hemisphere are on independent evolutionary trajectories, supporting taxonomic revision of M. novaeangliae to three subspecies., (© 2014 The Author(s) Published by the Royal Society. All rights reserved.)

Humpback whales (Megaptera novaeangliae) are managed by the International Whaling Commission as 7 primary populations that breed in the tropics and migrate to 6 feeding areas around the Antarctic. There is little information on individual movements within breeding areas or migratory connections to feeding grounds. We sought to better understand humpback whale habitat use and movements at breeding areas off West Africa, and during the annual migration to Antarctic feeding areas. We also assessed potential overlap between whale habitat and anthropogenic activities. We used Argos satellite-monitored radio tags to collect data on 13 animals off Gabon, a primary humpback whale breeding area. We quantified habitat use for 3 cohorts of whales and used a state-space model to determine transitions in the movement behavior of individuals. We developed a spatial metric of overlap between whale habitat and models of cumulative human activities, including oil platforms, toxicants, and shipping. We detected strong heterogeneity in movement behavior over time that is consistent with previous genetic evidence of multiple populations in the region. Breeding areas for humpback whales in the eastern Atlantic were extensive and extended north of Gabon late in the breeding season. We also observed, for the first time, direct migration between West Africa and sub-Antarctic feeding areas. Potential overlap of whale habitat with human activities was the highest in exclusive economic zones close to shore, particularly in areas used by both individual whales and the hydrocarbon industry. Whales potentially overlapped with different activities during each stage of their migration, which makes it difficult to implement mitigation measures over their entire range. Our results and existing population-level data may inform delimitation of populations and actions to mitigate potential threats to whales as part of local, regional, and international management of highly migratory marine species., (© 2014 Society for Conservation Biology.)

Passive acoustic monitoring was used to document the presence of singing humpback whales off the coast of Northern Angola, and opportunistically test for the effect of seismic survey activity in the vicinity on the number of singing whales. Two Marine Autonomous Recording Units (MARUs) were deployed between March and December 2008 in the offshore environment. Song was first heard in mid June and continued through the remaining duration of the study. Seismic survey activity was heard regularly during two separate periods, consistently throughout July and intermittently in mid-October/November. Numbers of singers were counted during the first ten minutes of every hour for the period from 24 May to 1 December, and Generalized Additive Mixed Models (GAMMs) were used to assess the effect of survey day (seasonality), hour (diel variation), moon phase and received levels of seismic survey pulses (measured from a single pulse during each ten-minute sampled period) on singer number. Application of GAMMs indicated significant seasonal variation, which was the most pronounced effect when assessing the full dataset across the entire season (p<0.001); however seasonality almost entirely dropped out of top-ranked models when applied to a reduced dataset during the July period of seismic survey activity. Diel variation was significant in both the full and reduced datasets (from p<0.01 to p<0.05) and often included in the top-ranked models. The number of singers significantly decreased with increasing received level of seismic survey pulses (from p<0.01 to p<0.05); this explanatory variable was included among the top ranked models for one MARU in the full dataset and both MARUs in the reduced dataset. This suggests that the breeding display of humpback whales is disrupted by seismic survey activity, and thus merits further attention and study, and potentially conservation action in the case of sensitive breeding populations.

Although humpback whales are among the best-studied of the large whales, population boundaries in the Southern Hemisphere (SH) have remained largely untested. We assess population structure of SH humpback whales using 1,527 samples collected from whales at fourteen sampling sites within the Southwestern and Southeastern Atlantic, the Southwestern Indian Ocean, and Northern Indian Ocean (Breeding Stocks A, B, C and X, respectively). Evaluation of mtDNA population structure and migration rates was carried out under different statistical frameworks. Using all genetic evidence, the results suggest significant degrees of population structure between all ocean basins, with the Southwestern and Northern Indian Ocean most differentiated from each other. Effective migration rates were highest between the Southeastern Atlantic and the Southwestern Indian Ocean, followed by rates within the Southeastern Atlantic, and the lowest between the Southwestern and Northern Indian Ocean. At finer scales, very low gene flow was detected between the two neighbouring sub-regions in the Southeastern Atlantic, compared to high gene flow for whales within the Southwestern Indian Ocean. Our genetic results support the current management designations proposed by the International Whaling Commission of Breeding Stocks A, B, C, and X as four strongly structured populations. The population structure patterns found in this study are likely to have been influenced by a combination of long-term maternally directed fidelity of migratory destinations, along with other ecological and oceanographic features in the region.

Humpback whales seasonally migrate long distances between tropical and polar regions. However, inter-oceanic exchange is rare and difficult to document. Using skin biopsy samples collected in the Indian Ocean and in the South Atlantic Ocean, and a genetic capture-recapture approach based on microsatellite genotyping, we were able to reveal the first direct genetic evidence of the inter-oceanic migration of a male humpback whale. This exceptional migration to wintering grounds of two different ocean basins questions traditional notions of fidelity to an ocean basin, and demonstrates how the behaviour of highly mobile species may be elucidated from combining genetics with long-term field studies. Our finding has implications for management of humpback whale populations, as well as for hypotheses concerning cultural transmission of behaviour.

Aim: Species distribution modelling is a useful tool for determining important habitats. By accounting for specific animal behaviour in the model, it is possible to identify finer‐scale patterns of habitat use. Together with spatially explicit data on anthropogenic activities, models can be used to assess human impacts and inform conservation management. This study used observations of breeding behaviour to identify fine‐scale breeding habitats of humpback whales (Megaptera novaeangliae), as well as potential overlap of these habitats with cumulative anthropogenic impacts. Location: Eastern Tropical Atlantic, West Africa. Methods: Maxent was used to model humpback distribution using pertinent environmental predictors and an integrated dataset of humpback whale occurrences filtered for breeding‐specific behaviours. In conjunction with multiple anthropogenic activities, a subsequent cumulative utilization and impact analysis assessed the degree of overlap between predicted breeding habitat and potential anthropogenic impacts. Results: Greatest habitat suitability occurred in warm coastal waters of Gabon, and other highly suitable areas occurred off Equatorial Guinea (Bioko Island), Cameroon and Angola. Sea surface temperature and height contributed most to the model. Highest overlap between humpback whales and potential impacts from anthropogenic activities occurred off Gabon, Equatorial Guinea (Bioko Island), Cameroon and Angola. Impacts associated with oil and gas development (where oil and gas platforms serve as an indicator for industry activity) appeared to contribute most to potential cumulative impact. Main Conclusions: Depth and sea surface temperature of predicted breeding habitats were consistent with previous studies. However, lesser known characteristics such as sea surface height and wind speed, resulting in potentially more sheltered areas for breeding whales, may also be important in delineating finer‐scale habitat suitability. Identified areas of high potential cumulative impact occurred within exclusive economic zones of multiple countries and likely represent the minimum level of impact to humpback whales in the region, highlighting the need for additional research and effective management throughout the area. [ABSTRACT FROM AUTHOR]

Early 'Discovery mark' data together with recent photo-identification, acoustic, genetic and satellite-radio tag data revealed linkages between humpback whales migrating from breeding grounds (C) off East Africa and the Area III feeding area, from Western Australian breeding grounds (D) and the Antarctic Area IV feeding area and the East Australian breeding grounds (E1) and Antarctic Area V feeding area. These data also revealed low levels of intermingling between (E1) and (D) humpback whales in the Antarctic Area IV feeding area consistent with these being separate populations. Greenpeace photographed the ventral tail flukes of 30 individual humpback whales in the Antarctic Area IV feeding area (70°E-130°E) from 2 to 9 January 2008, between 62°47'S and 64°14'S latitude and 80°00'E and 112°57'E longitude. Comparisons of the Antarctic Area IV Greenpeace fluke catalogue (n = 30) with existing reconciled fluke catalogues from East Africa (n = 842), Western Australia (n = 1,558) and Eastern Australia (n = 1,964), yielded no photo-identification matches. An analysis of the frequencies of whales seen and not seen in Antarctica, East Africa, Western Australia and Eastern Australia relative to the frequencies expected to have been seen and not seen, based on the estimated population sizes and the sizes of the catalogues, provided evidence that the Antarctic whales photographed are from a different population to the East African and East Australian populations. There was weak evidence supporting the hypothesis that the Antarctic whales are from the Western Australian population but insufficient data were available to determine a clear outcome. A comparison of the Antarctic Area IV Greenpeace catalogue (n = 30) with other existing African, Indian Ocean, Western and Eastern Australian and/or Antarctic catalogues, together with increased sampling across the humpback whale feeding season in Antarctica and along the Western and Eastern Australian coastline during their winter migration, is likely to provide further evidence of the migratory destination of these humpback whales. It will also add to our limited knowledge of the extent of population overlap within the Antarctic Area III, IV and V feeding areas. [ABSTRACT FROM AUTHOR]

Machine learning algorithms are often used to model and predict animal habitat selection—the relationships between animal occurrences and habitat characteristics. For broadly distributed species, habitat selection often varies among populations and regions; thus, it would seem preferable to fit region- or population-specific models of habitat selection for more accurate inference and prediction, rather than fitting large-scale models using pooled data. However, where the aim is to make range-wide predictions, including areas for which there are no existing data or models of habitat selection, how can regional models best be combined? We propose that ensemble approaches commonly used to combine different algorithms for a single region can be reframed, treating regional habitat selection models as the candidate models. By doing so, we can incorporate regional variation when fitting predictive models of animal habitat selection across large ranges. We test this approach using satellite telemetry data from 168 humpback whales across five geographic regions in the Southern Ocean. Using random forests, we fitted a large-scale model relating humpback whale locations, versus background locations, to 10 environmental covariates, and made a circumpolar prediction of humpback whale habitat selection. We also fitted five regional models, the predictions of which we used as input features for four ensemble approaches: an unweighted ensemble, an ensemble weighted by environmental similarity in each cell, stacked generalization, and a hybrid approach wherein the environmental covariates and regional predictions were used as input features in a new model. We tested the predictive performance of these approaches on an independent validation dataset of humpback whale sightings and whaling catches. These multiregional ensemble approaches resulted in models with higher predictive performance than the circumpolar naive model. These approaches can be used to incorporate regional variation in animal habitat selection when fitting range-wide predictive models using machine learning algorithms. This can yield more accurate predictions across regions or populations of animals that may show variation in habitat selection. [ABSTRACT FROM AUTHOR]

Humpback whales (Megaptera novaeangliae) annually undertake the longest migrations between seasonal feeding and breeding grounds of any mammal. Despite this dispersal potential, discontinuous seasonal distributions and migratory patterns suggest that humpbacks form discrete regional populations within each ocean. To better understand the worldwide population history of humpbacks, and the interplay of this species with the oceanic environment through geological time, we assembled mitochondrial DNA control region sequences representing approximately 2700 individuals (465 bp, 219 haplotypes) and eight nuclear intronic sequences representing approximately 70 individuals (3700 bp, 140 alleles) from the North Pacific, North Atlantic and Southern Hemisphere. Bayesian divergence time reconstructions date the origin of humpback mtDNA lineages to the Pleistocene (880 ka, 95% posterior intervals 550-1320 ka) and estimate radiation of current Northern Hemisphere lineages between 50 and 200 ka, indicating colonization of the northern oceans prior to the Last Glacial Maximum. Coalescent analyses reveal restricted gene flow between ocean basins, with long-term migration rates (individual migrants per generation) of less than 3.3 for mtDNA and less than 2 for nuclear genomic DNA. Genetic evidence suggests that humpbacks in the North Pacific, North Atlantic and Southern Hemisphere are on independent evolutionary trajectories, supporting taxonomic revision of M. novaeangliae to three subspecies. [ABSTRACT FROM AUTHOR]