Deep ocean drivers better explain habitat preferences of sperm whales Physeter macrocephalus than beaked whales in the Bay of Biscay.

Species Distribution Models are commonly used with surface dynamic environmental variables as proxies for prey distribution to characterise marine top predator habitats. For oceanic species that spend lot of time at depth, surface variables might not be relevant to predict deep-dwelling prey distributions. We hypothesised that descriptors of deep-water layers would better predict the deep-diving cetacean distributions than surface variables. We combined static variables and dynamic variables integrated over different depth classes of the water column into Generalised Additive Models to predict the distribution of sperm whales Physeter macrocephalus and beaked whales Ziphiidae in the Bay of Biscay, eastern North Atlantic. We identified which variables best predicted their distribution. Although the highest densities of both taxa were predicted near the continental slope and canyons, the most important variables for beaked whales appeared to be static variables and surface to subsurface dynamic variables, while for sperm whales only surface and deep-water variables were selected. This could suggest differences in foraging strategies and in the prey targeted between the two taxa. Increasing the use of variables describing the deep-water layers would provide a better understanding of the oceanic species distribution and better assist in the planning of human activities in these habitats.

Towards a better characterisation of deep-diving whales' distributions by using prey distribution model outputs?

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 deep-diver 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 simulate larger prey beyond 1,000 m would probably better characterise the prey of deep-diving cetaceans.

Ocean sunfish as indicators for the 'rise of slime'.

Overfishing and ocean warming are drastically altering the community composition and size structure of marine ecosystems, eliminating large bodied species [1]. Against a backdrop of such environmental change, the heaviest of all bony fish, the ocean sunfish (Mola mola), seems an improbable survivor. Indeed this indolent giant is killed globally as bycatch, and is listed as 'Vulnerable'[2]. We undertook the most extensive aerial surveys of sunfish ever conducted and found surprisingly high abundances off the Atlantic and Mediterranean coasts of Western Europe. With up to 475 individuals per 100 km2, these figures are one order of magnitude higher than abundance estimates for other areas [3-5]. Using bioenergetic modelling, we estimate that each sunfish requires 71 kg day-1 of jellyfish, a biomass intake more than an order of magnitude greater than predicted for a similarly sized teleost. Scaled up to the population level, this equates to a remarkable 20,774 tonnes day-1 of predated jellyfish across our study area in summer. Sunfish abundance may be facilitated by overfishing and ocean warming, which together cause reduced predation of sunfish by sharks and elevated jellyfish biomass. Our combined survey and bioenergetic data provide the first-ever estimate of spatialized ocean sunfish daily food requirements, and stress the importance of this species as a global indicator for the 'rise of slime'. This hypothesis posits that, in an overfished world ocean exposed to global warming, gelatinous zooplankton should flourish, to the detriment of other mesotrophic species such as small pelagic fish, causing irreversible trophic cascades as well as a series of other environmental and economic issues.