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Marine protected areas (MPAs), particularly large MPAs, are increasing in number and size around the globe in part to facilitate the conservation of marine megafauna under the assumption that large-scale MPAs better align with vagile life histories; however, this alignment is not well established. Using a global tracking dataset from 36 species across five taxa, chosen to reflect the span of home range size in highly mobile marine megafauna, we show most MPAs are too small to encompass complete home ranges of most species. Based on size alone, 40% of existing MPAs could encompass the home ranges of the smallest ranged species, while only < 1% of existing MPAs could encompass those of the largest ranged species. Further, where home ranges and MPAs overlapped in real geographic space, MPAs encompassed < 5% of core areas used by all species. Despite most home ranges of mobile marine megafauna being much larger than existing MPAs, we demonstrate how benefits from MPAs are still likely to accrue by targeting seasonal aggregations and critical life history stages and through other management techniques.

As part of the Post-2020 Biodiversity Framework, nations are assessing progress over the past decade in addressing the underlying drivers that influence direct pressures on biodiversity and formulating new policies and strategies for the decade to come. For marine conservation, global marine protected area (MPA) coverage is still falling short of the 10% target set in 2010. Here we show that while this reflects a lack of progress in many low- and middle-income countries, a few of these nations have met or exceeded international commitments. To provide an in-depth explanation of how this was achieved in Gabon, we summarize the lessons learnt by our consortium of policy makers and practitioners who helped implement a comprehensive and ecologically representative network of 20 MPAs. We show the importance of creating a national framework, building long-term stakeholder support, and focusing on research that guides implementation and policy; and outline a four-step approach that countries and donors could use as an example to help meet international commitments. By responding to calls to share lessons learned to inform future Convention on Biological Diversity targets, we show how Gabon's experiences could inform change elsewhere.

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 variatio

The description of genetic population structure over a species' geographic range can provide insights into its evolutionary history and also support effective management efforts. Assessments for globally distributed species are rare, however, requiring significant international coordination and collaboration. The global distribution of demographically discrete populations for the humpback whale Megaptera novaeangliae is not fully known, hampering the definition of appropriate management units. Here, we present the first circumglobal assessment of mito - chondrial genetic population structure across the species' range in the Southern Hemisphere and Arabian Sea. We combine new and existing data from the mitochondrial (mt)DNA control region that resulted in a 311 bp consensus sequence of the mtDNA control region for 3009 individuals sampled across 14 breeding stocks and subpopulations currently recognized by the International Whaling Commission. We assess genetic diversity and test for genetic differentiation and also estimate the magnitude and directionality of historic matrilineal gene flow between putative populations. Our results indicate that maternally directed site fidelity drives significant genetic population structure between breeding stocks within ocean basins. However, patterns of connectivity differ across the circumpolar range, possibly as a result of differences in the extent of longitudinal movements on feeding areas. The number of population comparisons observed to be significantly differentiated were found to diminish at the subpopulation scale when nucleotide differences were examined, indicating that more complex processes underlie genetic structure at this scale. It is crucial that these complexities and uncertainties are afforded greater consideration in management and regulatory efforts.

© The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Royal Society Open Science 3 (2016): 160616, doi:10.1098/rsos.160616., Assessing the movement patterns and key habitat features of breeding humpback whales is a prerequisite for the conservation management of this philopatric species. To investigate the interactions between humpback whale movements and environmental conditions off Madagascar, we deployed 25 satellite tags in the northeast and southwest coast of Madagascar. For each recorded position, we collated estimates of environmental variables and computed two behavioural metrics: behavioural state of ‘transiting’ (consistent/directional) versus ‘localized’ (variable/non-directional), and active swimming speed (i.e. speed relative to the current). On coastal habitats (i.e. bathymetry < 200 m and in adjacent areas), females showed localized behaviour in deep waters (191 ± 20 m) and at large distances (14 ± 0.6 km) from shore, suggesting that their breeding habitat extends beyond the shallowest waters available close to the coastline. Males' active swimming speed decreased in shallow waters, but environmental parameters did not influence their likelihood to exhibit localized movements, which was probably dominated by social factors instead. In oceanic habitats, both males and females showed localized behaviours in shallow waters and favoured high chlorophyll-a concentrations. Active swimming speed accounts for a large proportion of observed movement speed; however, breeding humpback whales probably exploit prevailing ocean currents to maximize displacement. This study provides evidence that coastal areas, generally subject to strong human pressure, remain the core habitat of humpback whales off Madagascar. Our results expand the knowledge of humpback whale habitat use in oceanic habitat and response to variability of environmental factors such as oceanic current and chlorophyll level., Funding was provided by Total Foundation to NeuroPSI, and by individuals and foundations to the WCS Ocean Giants Program.