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

Abstract

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.

Summer distribution of the Mediterranean sperm whale: insights from the acoustic Accobams survey initiative

“…In addition, other environmental and biological variables could have been considered. Some studies use other variables to study cetacean distribution such as the distribution and concentration of prey species (Pendleton et al, 2020;Virgili et al, 2021) or canyon areas, because submarine canyons are widely recognised as hotspots in cetacean distribution (Tepsich et al, 2014). Pendleton et al (2020) suggested that using modelled prey availability, rather than oceanographic proxies, could be important to forecast species distributions.…”

Species distribution modeling of deep‐diving cetaceans

“…Some previous studies have used biological predictors related to prey availability in cetacean species distribution models, but results have been inconsistent. In a recent paper, Virgili et al (2021) investigated the use of SEAPODYM micronekton estimates in SDMs of ziphiid beaked whales and sperm whales in the North Atlantic basin. The authors found that these predictors were not selected for the beaked whale model and only marginally improved performance for the sperm whale model.…”

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

“…The addition of deep-water variables alone did not entirely explain the distribution of deep-divers but improved the explanatory power of the models and highlighted other processes that could influence their distribution at depth. More direct parameters such as prey distribution data simulated from numerical models could further improve our distribution models 50 , 51 . However, prey models need refinements to better characterise the prey of deep-diving cetaceans and thus to improve whale distribution models.…”