Abstract: We investigated the agreement between real seismograms and those predicted by long wavelength mantle models by looking at phase and amplitude differences. We computed full synthetic seismograms using a spectral element method together with 3-D mantle models and the appropriate crustal model on top. We selected differently damped mantle models to see the effect of regularization on the computed seismograms. To check the phase agreement, we measured time-shifts between the real and synthetic surface waves and body wave phases such as P, S and SS using a cross-correlation technique. We also compared the amplitudes of the real and synthetic seismograms to understand how well the models explain not only the phases, but the whole waveforms. 3-D mantle models improve the phase agreement of surface waves in particular. The remaining misfit, however, is still so large that we cannot distinguish between different tomographic models. We suggest that this is mainly due to an imperfect modelling of the crust, and/or source location if body waves are included, which have to be addressed in future inversions. Amplitude mismatches are large, regardless which 3-D mantle model is used. We observe that 3-D scattering or focusing/defocusing effects can only explain half of the surface wave amplitudes whereas body wave amplitudes are dominated by scattering effects. 1-D Q models, particularly in the crust and upper-mantle, strongly affect surface wave amplitudes and have to be modelled properly.

Abstract: 1.Currently pelagic ecosystems are changing significantly due to multiple threats. An important management policy is to establish marine protected areas, until now overlooked due to the difficulty of declaring high seas protected areas, obtaining long-term distribution data on indicator species and the dynamic nature of these ecosystems. 2.Within this framework, we developed predictive habitat suitability models of an oceanic predator, the vulnerable wandering albatross Diomedea exulans, in the highly dynamic Southern Ocean. Based on a long-term tracking database (19982008), we estimated three quantitative ecological indices that complementarily describe the hierarchical habitat use of the species at multiple spatial scales: where the species (i) spent more time (the seascape, based on the time spent per area), (ii) searched for prey (the foraging habitat, based on zones of increased foraging intensity using first passage time), and (iii) fed (the feeding habitat, based on prey capture data). 3.Predictive habitat models reasonably matched the observed distribution patterns and described albatross multi-scale habitat use as a hierarchical arrangement: albatrosses foraged over topographic features in subtropical waters, nested within the wider seascape due to the constraint imposed by the colony effect, whereas feeding occurred nested over the continental shelf and seamounts in areas of low oceanographic variability within the Polar Frontal Zone. 4.Within the current oceanographic conditions, the location of key pelagic habitats for albatrosses breeding in the southern Indian Ocean encompassed certain topographic features such as pelagic areas surrounding main breeding sites, seamounts and submarine mountain ranges. The placement of these pelagic hotspots depends on the current sea surface temperature conditions. 5.Synthesis and applications. The present study provides two key conservation and management tools. First, we provide the first map to support the development of a prospective network of priority conservation zones across the southern Indian Ocean based on habitat predictions of an oceanic indicator species. This could be used not only to support conservation of top predators but also the underlying biodiversity associated with pelagic key habitats. Secondly, the developed habitat modelling procedure is widely applicable and could be used to track changes in species distribution in both marine and terrestrial environments within the current global change scenario.