Predicting top predator habitats in the Southwest Indian Ocean

Abstract

International audienceTop predators need to develop optimal strategies of resources and habitats utilization in order to optimize their foraging success. At the individual scale, a predator has to maximize his intake of food while minimizing his cost of foraging to optimize his energetic gain. At the ecosystem scale, we hypothesized that foraging strategies of predators also respond to their general energetic constraints. Predators with energetically costly lifestyles may be constrained to select high quality habitats whereas more phlegmatic predators may occupy both low and high quality habitats. The objectives of this study were 1) to investigate predator responses to heterogeneity in habitat quality with reference to their energetic strategies and 2) to evaluate their responses to contemporaneous versus averaged habitat quality. We collected cetacean and seabird data from an aerial survey in the Southwest Indian Ocean, a region characterized by heterogeneous oceanographic conditions. We classified cetaceans and seabirds into energetic guilds and described their habitats using remotely sensed covariates at contemporaneous and time-averaged resolutions and static covariates. We used generalized additive models to predict their habitats at the regional scale. Strategies of habitat utilization appeared in accordance with predators energetic constraints. Cetaceans responded to the heterogeneity in habitat quality, with higher densities predicted in more productive areas. However, the costly Delphininae appeared to be more dependent on habitat quality (showing a 1-to-13 ratio between the lowest and highest density sectors) than the more phlegmatic sperm and beaked whales (showing only a 1-to-3 ratio). For seabirds, predictions primarily reflected colony locations, although the colony effect was stronger for costly seabirds. Moreover, our results suggest that predators may respond better to persistent oceanographic features. To provide a third dimension to habitat quality, cetacean strategies of utilization of the vertical habitat could be related to the distribution of micronekton in the water column

A giant squid (Architeuthis dux) off Reunion Island, western Indian Ocean: the greatest giant ever?

“…propeller of a vessel), given the preferences of giant squid to deep-water habitats (Kubodera & Mori, 2005) and visible patterns of tissue damage ( Figure 1A). Injuries at the mantle tip ( Figure 1A) suggest predation by a large animal, probably a sperm whale, as they are known to prey on giant squid and regularly occur within the region (Clarke, 1980;Jefferson et al, 1993;Mannocci et al, 2014), or possibly a great white shark (Carcharodon carcharias), which occasionally visit Reunion Island waters (Zuffa et al, 2002;Jaquemet, unpublished data). Smaller predators such as squid or fish leave predation marks that differ in size and shape from the ones observed here (Chapman et al, 2006;Lowry et al, 2009;Papastamatiou et al, 2010).…”

Unexpected patterns of global population structure in melon-headed whales Peponocephala electra

“…Large oceanic populations of MHWs are known to exist, at least within the Pacific Ocean (Brownell et al 2009b, Hamilton et al 2009), but also most likely in the Indian Ocean (Mannocci et al 2014). Although most of our samples came from animals known to show some long-term fidelity to islands, satellite tag data show that animals from the Hawaiian Islands population actually spend most of their time offshore (Baird 2016).…”

Temporal resolutions in species distribution models of highly mobile marine animals: Recommendations for ecologists and managers

“…However, relatively few modellers have studied the influence of temporal resolution on SDMs (Becker et al, 2010;Mannocci et al, 2014;Roberts et al, 2016;Scales et al, 2017). To do so, modellers must evaluate complex trade-offs.…”

“…SDMs have been successfully used to examine many ecological, management and conservation questions (Elith & Leathwick, 2009). In particular, they have been widely used to explain and predict distribution patterns of highly mobile marine animals in a variety of ecosystems (Benson et al, 2011;Forney, Becker, Foley, Barlow, & Oleson, 2015;Hartog, Hobday, Matear, & Feng, 2011;Mannocci et al, 2014).…”

“…SDMs have been successfully used to examine many ecological, management and conservation questions (Elith & Leathwick, 2009). In particular, they have been widely used to explain and predict distribution patterns of highly mobile marine animals in a variety of ecosystems (Benson et al, 2011;Forney, Becker, Foley, Barlow, & Oleson, 2015;Hartog, Hobday, Matear, & Feng, 2011;Mannocci et al, 2014).It has become apparent that the hierarchical structure of processes in the marine environment drives the distribution and movement patterns of marine animals at multiple spatio-temporal scales (Benoit-Bird, Battaile, Nordstrom, & Trites, 2013;Fauchald, Erikstad, & Skarsfjord, 2000;Fauchald & Tveraa, 2006;Fritz, Said, & Weimerskirch, 2003;Pinaud & Weimerskirch, 2005) (Figure 1). At fine scales, animals track ephemeral prey patches that extend over tens of metres to satisfy their energy requirements (Goldbogen et al, 2008;Heaslip, Iverson, Bowen, & James, 2012 (Benson et al, 2011;Hobday & Hartog, 2014;Tew Kai & Marsac, 2010).…”