Seasonal movements and behaviour of basking sharks from archival tagging: No evidence of winter hibernation

Habitat selection processes in highly migratory animals such as sharks and whales are important to understand because they influence patterns of distribution, availability and therefore catch rates. However, spatial strategies remain poorly understood over seasonal scales in most species, including, most notably, the plankton-feeding basking shark Cetorhinus maximus. It was proposed nearly 50 yr ago that this globally distributed species migrates from coastal summer-feeding areas of the northeast Atlantic to hibernate during winter in deep water on the bottom of continental-shelf slopes. This view has perpetuated in the literature even though the 'hibernation theory' has not been tested directly. We have now tracked basking sharks for the first time over seasonal scales (1.7 to 6.5 mo) using 'pop-up' satellite archival transmitters. We show that they do not hibernate during winter but instead undertake extensive horizontal (up to 3400 km) and vertical (> 750 m depth) movements to utilise productive continental-shelf and shelf-edge habitats during summer, autumn and winter. They travel long distances (390 to 460 km) to locate temporally discrete productivity 'hotspots' at shelf-break fronts, but at no time were prolonged movements into open-ocean regions away from shelf waters observed. Basking sharks have a very broad vertical diving range and can dive beyond the known range of planktivorous whales. Our study suggests this species can exploit shelf and slope-associated zooplankton communities in mesopelagic (200 to 1000 m) as well as epipelagic habitat (0 to 200 m).

Unanticipated biological changes and global warming

Evidence of global warming is now unequivocal, and studies suggest that it has started to influence natural systems of the planet, including the oceans. However, in the marine environment, it is well-known that species and ecosystems can also be influenced by natural sources of large-scale hydro-climatological variability. The North Atlantic Oscillation (NAO) was negatively correlated with the mean abundance of one of the subarctic key species Calanus finmarchicus in the North Sea. This correlation was thought to have broken down in 1996, however, the timing has never been tested statistically. The present study revisits this unanticipated change and reveals that the correlation did not break down in 1996 as originally proposed but earlier, at the time of an abrupt ecosystem shift in the North Sea in the 1980s. Furthermore, the analyses demonstrate that the correlation between the NAO and C. finmarchicus abundance is modulated by the thermal regime of the North Sea, which in turn covaries positively with global temperature anomalies. This study thereby provides evidence that global climate change is likely to alter some empirical relationships found in the past between species abundance or the ecosystem state and large-scale natural sources of hydro-climatological variability. A theory is proposed to explain how this might happen. These unanticipated changes, also called ‘surprises’ in climatic research, are a direct consequence of the complexity of both climatic and biological systems. In this period of rapid climate change, it is therefore hazardous to integrate meteo-oceanic indices such as the NAO in models used in the management of living resources, as it has been sometimes attempted in the past.

Chlorophyll enhancement in the central region of the Bay of Biscay as a result of internal tidal wave interaction

A multi-sensor satellite approach based on ocean colour, sunglint and Synthetic Aperture Radar imagery is used to study the impact of interacting internal tidal (IT) waves on near-surface chlorophyll-a distribution, in the central Bay of Biscay. Satellite imagery was initially used to characterize the internal solitary wave (ISW) field in the study area, where the “local generation mechanism” was found to be associated with two distinct regions of enhanced barotropic tidal forcing. IT beams formed at the French shelf-break, and generated from critical bathymetry in the vicinities of one of these regions, were found to be consistent with “locally generated” ISWs. Representative case studies illustrate the existence of two different axes of IT propagation originating from the French shelf-break, which intersect close to 46°N, − 7°E, where strong IT interaction has been previously identified. Evidence of constructive interference between large IT waves is then presented and shown to be consistent with enhanced levels of chlorophyll-a concentration detected by means of ocean colour satellite sensors. Finally, the results obtained from satellite climatological mean chlorophyll-a concentration from late summer (i.e. September, when ITs and ISWs can meet ideal propagation conditions) suggest that elevated IT activity plays a significant role in phytoplankton vertical distribution, and therefore influences the late summer ecology in the central Bay of Biscay.

The origin of sub-surface source waters define the sea-air flux of methane in the Mauritanian Upwelling, NW Africa

Concentrations and flux densities of methane were determined during a lagrangian study of an advective filament in the permanent upwelling region off western Mauritania. Newly upwelled waters were dominated by the presence of North Atlantic Central Water and surface CH4 concentrations of 2.2 ± 0.3 nmol L-1 were largely in equilibrium with atmospheric values, with surface saturations of 101.7 ± 14%. As the upwelling filament aged and was advected offshore, CH4 enriched South Atlantic Central Water from intermediate depths of 100 to 350m was entrained into the surface mixed layer of the filament following intense mixing associated with the shelf break. Surface saturations increased to 198.9 ± 15% and flux densities increased from a mean value over the shelf of 2.0 ± 1.1 µmol m-2d-1 to a maximum of 22.6 µmol m-2d-1. Annual CH4 emissions for this persistent filament were estimated at 0.77 ± 0.64 Gg which equates to a maximum of 0.35% of the global oceanic budget. This raises the known outgassing intensity of this area and highlights the importance of advecting filaments from upwelling waters as efficient vehicles for air-sea exchange.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.

Identifying predictable foraging habitats for a wide-ranging marine predator using ensemble ecological niche models

Aim: Ecological niche modelling can provide valuable insight into species' environmental preferences and aid the identification of key habitats for populations of conservation concern. Here, we integrate biologging, satellite remote-sensing and ensemble ecological niche models (EENMs) to identify predictable foraging habitats for a globally important population of the grey-headed albatross (GHA) Thalassarche chrysostoma. Location: Bird Island, South Georgia; Southern Atlantic Ocean. Methods: GPS and geolocation-immersion loggers were used to track at-sea movements and activity patterns of GHA over two breeding seasons (n = 55; brood-guard). Immersion frequency (landings per 10-min interval) was used to define foraging events. EENM combining Generalized Additive Models (GAM), MaxEnt, Random Forest (RF) and Boosted Regression Trees (BRT) identified the biophysical conditions characterizing the locations of foraging events, using time-matched oceanographic predictors (Sea Surface Temperature, SST; chlorophyll a, chl-a; thermal front frequency, TFreq; depth). Model performance was assessed through iterative cross-validation and extrapolative performance through cross-validation among years. Results: Predictable foraging habitats identified by EENM spanned neritic (<500 m), shelf break and oceanic waters, coinciding with a set of persistent biophysical conditions characterized by particular thermal ranges (3–8 °C, 12–13 °C), elevated primary productivity (chl-a > 0.5 mg m−3) and frequent manifestation of mesoscale thermal fronts. Our results confirm previous indications that GHA exploit enhanced foraging opportunities associated with frontal systems and objectively identify the APFZ as a region of high foraging habitat suitability. Moreover, at the spatial and temporal scales investigated here, the performance of multi-model ensembles was superior to that of single-algorithm models, and cross-validation among years indicated reasonable extrapolative performance. Main conclusions: EENM techniques are useful for integrating the predictions of several single-algorithm models, reducing potential bias and increasing confidence in predictions. Our analysis highlights the value of EENM for use with movement data in identifying at-sea habitats of wide-ranging marine predators, with clear implications for conservation and management.