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A number of marine species in the Mediterranean are threatened by the presence of several pressure factors, which include climate change, collisions with vessels, entanglement and ingestion of marine litter, especially plastic. Risk reduction policies can only be conceived starting from an accurate analysis of the exposure to such pressure factors. To estimate spatial abundance of both marine species and plastic litter and to assess the exposure risk, a two-stage analysis approach was applied, using aerial survey data from the ACCOBAMS Survey Initiative (ASI), in synergy with the Plastic Busters MPAs (PB MPAs) project. First, a detection function was fitted to observation data to obtain detection probabilities for individuals, then a Generalized Additive Model (GAM) was employed to estimate the spatial distribution of relative abundance, based on survey observations. A bivariate Local Indicator of Spatial Association (LISA) was then applied to the maps of relative abundance to derive risk maps of exposure of marine species to marine litter. The maps, obtained with a spatial resolution of about 10 km, allow us to identify areas with the highest neighboring abundance of taxa and marine litter, in particular for the MPAs studied by the PB MPAs project, which include the North-Western Mediterranean (Pelagos Sanctuary and Tuscan Archipelago), the Ionian and Aegean Sea (Zakynthos), and the Strait of Sicily (Cabrera Archipelago).

The ACCOBAMS Survey Initiative (ASI) is the first synoptic large-scale survey of the entire ACCOBAMS Area and as such it plays a key role in filling the current gaps in our biological and ecological knowledge of large vertebrate species occurring in the region. Data gathered during the ASI were analyzed in a distance sampling surface-modelling framework to assess the summer distribution, densities and patterns, as well as to investigate the correlates of these parameters, for large vertebrate species and taxa in the Mediterranean Basin. Static and dynamic explanatory variables, including water depth (m), distance to depth contours (km), distance to canyons and seabed slope (km), sea surface temperature (°C), mixed layer depth (m) and levels of chlorophyll-a (mg/l), were considered to predict density and compute its variance spatially at a resolution of 10x10 km. A strong longitudinal gradient from low densities in the east to high densities in the west is shared by most taxa. In addition, several taxa also showed a less marked latitudinal gradient varying in direction according to species, and finally, a few of them exhibited patchy distributions.

In habitat modelling, environmental variables are assumed to be proxies of lower trophic levels distribution and by extension, of marine top predator distributions. More proximal variables, such as potential prey fields, could refine relationships between top predator distributions and their environment. In situ data on prey distributions are not available over large spatial scales but, a numerical model, the Spatial Ecosystem And POpulation DYnamics Model (SEAPODYM), provides simulations of the biomass and production of zooplankton and six functional groups of micronekton at the global scale. Here, we explored whether generalised additive models fitted to simulated prey distribution data better predicted deepdiver densities (here beaked whales Ziphiidae and sperm whales Physeter macrocephalus) than models fitted to environmental variables. We assessed whether the combination of environmental and prey distribution data would further improve model fit by comparing their explanatory power. For both taxa, results were suggestive of a preference for habitats associated with topographic features and thermal fronts but also for habitats with an extended euphotic zone and with large prey of the lower mesopelagic layer. For beaked whales, no SEAPODYM variable was selected in the best model that combined the two types of variables, possibly because SEAPODYM does not accurately simulate the organisms on which beaked whales feed on. For sperm whales, the increase model performance was only marginal. SEAPODYM outputs were at best weakly correlated with sightings of deep-diving cetaceans, suggesting SEAPODYM may not accurately predict the prey fields of these taxa. This study was a first investigation and mostly highlighted the importance of the physiographic variables to understand mechanisms that influence the distribution of deep-diving cetaceans. A more systematic use of SEAPODYM could allow to better define the limits of its use and a development of the model that would sim

© The Authors, 2019. This article is distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 4.0 International License. The definitive version was published in Molecular Phylogenetics and Evolution (2019), doi:10.1016/j.ympev.2019.02.003., The advent of massive parallel sequencing technologies has resulted in an increase of studies based upon complete mitochondrial genome DNA sequences that revisit the taxonomic status within and among species. Spatially distinct monophyly in such mitogenomic genealogies, i.e., the sharing of a recent common ancestor among con-specific samples collected in the same region has been viewed as evidence for subspecies. Several recent studies in cetaceans have employed this criterion to suggest subsequent intraspecific taxonomic revisions. We reason that employing intra-specific, spatially distinct monophyly at non-recombining, clonally inherited genomes is an unsatisfactory criterion for defining subspecies based upon theoretical (genetic drift) and practical (sampling effort) arguments. This point was illustrated by a re-analysis of a global mitogenomic assessment of fin whales, Balaenoptera physalus spp., published by Archer et al. (2013), which proposed to further subdivide the Northern Hemisphere fin whale subspecies, B. p. physalus. The proposed revision was based upon the detection of spatially distinct monophyly among North Atlantic and North Pacific fin whales in a genealogy based upon complete mitochondrial genome DNA sequences. The extended analysis conducted in this study (1,676 mitochondrial control region, 162 complete mitochondrial genome DNA sequences and 20 microsatellite loci genotyped in 358 samples) revealed that the apparent monophyly among North Atlantic fin whales reported by Archer et al. (2013) to be due to low sample sizes. In conclusion, defining sub-species from monophyly (i.e., the absence of para- or polyphyly) can lead to erroneous conclusions due to relatively “trivial” aspects, such as sampling. Basic population genetic processes (i.e., genetic drift and migration) also affect the time to the most recent common ancestor and hence the probability that individuals in a sample are monophyletic., We are grateful to Hanne Jørgensen, Anna Sellas, Mary Beth Rew and Christina Færch-Jensen for technical assistance. We thank Drs. P. E. Rosel and K. D. Mullin (U.S. National Marine Fisheries Service Southeast Fisheries Science Center) and members of the U.S. Northeast and Southeast Region Marine Mammal Stranding Network and its response teams, including the International Fund for Animal Welfare, the Marine Mammal Stranding Center, Mystic Aquarium, the Riverhead Foundation for Marine Research and Preservation (K. Durham) and the Marine Mammal Stranding Program of the University of North Carolina Wilmington for access to fin whale samples from the western North Atlantic. We thank Gisli Vikingsson for providing samples. We are indebted to Dr. Eduardo Secchi for facilitating data sharing. Data collection in the Southern Ocean was conducted under research projects Baleias (CNPq grants 557064/2009-0 and 408096/2013-6), INTERBIOTA (CNPq 407889/2013-2) and INCT-APA (CNPq 574018/2008-5), of the Brazilian Antarctic Program and a contribution by the research consortium ‘Ecology and Conservation of Marine Megafauna – EcoMega-CNPq’. MAS was supported through a FCT Investigator contract funded by POPH, QREN European Social Fund, and Portuguese Ministry for Science and Education. Data collection in the Azores was funded by TRACE-PTDC/MAR/74071/2006 and MAPCET-M2.1.2/F/012/2011 [FEDER, COMPETE, QREN European Social Fund, and Proconvergencia Açores/EU Program]. Fin whale illustration herein is used with the permission of Frédérique Lucas. We acknowledge the Center for Information Technology of the University of Groningen for IT support and access to the Peregrine high performance-computing cluster.

Heterogeneous data collection in the marine environment has led to large gaps in our knowledge of marine species distributions. To fill these gaps, models calibrated on existing data may be used to predict species distributions in unsampled areas, given that available data are sufficiently representative. Our objective was to evaluate the feasibility of mapping cetacean densities across the entire Mediterranean Sea using models calibrated on available survey data and various environmental covariates. We aggregated 302,481 km of line transect survey effort conducted in the Mediterranean Sea within the past 20 years by many organisations. Survey coverage was highly heterogeneous geographically and seasonally: large data gaps were present in the eastern and southern Mediterranean and in non-summer months. We mapped the extent of interpolation versus extrapolation and the proportion of data nearby in environmental space when models calibrated on existing survey data were used for prediction across the entire Mediterranean Sea. Using model predictions to map cetacean densities in the eastern and southern Mediterranean, characterised by warmer, less productive waters, and more intense eddy activity, would lead to potentially unreliable extrapolations. We stress the need for systematic surveys of cetaceans in these environmentally unique Mediterranean waters, particularly in non-summer months.