42 resultados para Mesoscale


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ABSTRACT: Oceanographic fronts are physical interfaces between water masses that differ in properties such as temperature, salinity, turbidity and chl a enrichment. Bio-physical coupling along fronts can lead to the development of pelagic biodiversity hotspots. A diverse range of marine vertebrates have been shown to associate with fronts, using them as foraging and migration habitats. Elucidation of the ecological significance of fronts generates a better understanding of marine ecosystem functioning, conferring opportunities to improve management of anthropogenic activities in the oceans. This study presents novel insight into the oceanographic drivers of habitat use in a population of marine turtles characterised by an oceanic-neritic foraging dichotomy. Using satellite tracking data from adult female loggerhead turtles nesting at Cape Verde (n = 12), we test the hypothesis that oceanic-foraging loggerheads associate with mesocale (10s – to 100s of km) thermal fronts. We use high-resolution (1 km) composite front mapping to characterise frontal activity in the Canary Current Large Marine Ecosystem (LME) over 2 temporal scales: (1) seasonal front frequency and (2) 7-day front metrics. Our use-availability analysis indicates that oceanic loggerheads show a preference for the highly productive upwelling region between Cape Verde and mainland Africa, an area of intense frontal activity. Within the upwelling region, turtles appear to forage epipelagically around mesoscale thermal fronts, exploiting profitable foraging opportunities resulting from physical aggregation of prey.

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Understanding the mechanisms linking oceanographic processes and marine vertebrate habitat use is critical to effective management of populations of conservation concern. The basking shark Cetorhinus maximus has been shown to associate with oceanographic fronts – physical interfaces at the transitions between water masses – to exploit foraging opportunities resulting from aggregation of zooplankton. However, the scale, significance and variability of these observed associations have not yet been established. Here, we quantify the influence of mesoscale (10s – 100s km) frontal activity on habitat use over timescales of weeks to months. We use animal-mounted archival tracking with composite front mapping via Earth Observation (EO) remote sensing to provide an oceanographic context to individual shark movements. We investigate levels of association with fronts occurring over two spatio-temporal scales, (i) broad-scale seasonally persistent frontal zones and (ii) contemporaneous mesoscale thermal and chl-a fronts. Using random walk simulations and logistic regression within an iterative generalised linear mixed modelling (GLMM) framework, we find that seasonal front frequency is a significant predictor of shark presence. Temporally-matched oceanographic metrics also indicate that sharks demonstrate a preference for productive regions, and associate with contemporaneous thermal and chl-a fronts more frequently than could be expected at random. Moreover, we highlight the importance of cross-frontal temperature change and persistence, which appear to interact to affect the degree of prey aggregation along thermal fronts. These insights have clear implications for understanding the preferred habitats of basking sharks in the context of anthropogenic threat management and marine spatial planning in the northeast Atlantic.

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Many established models of animal foraging assume that individuals are ecologically equivalent. However, it is increasingly recognized that populations may comprise individuals who differ consistently in their diets and foraging behaviors. For example, recent studies have shown that individual foraging site fidelity (IFSF, when individuals consistently forage in only a small part of their population's home range) occurs in some colonial breeders. Short‐term IFSF could result from animals using a win–stay, lose–shift foraging strategy. Alternatively, it may be a consequence of individual specialization. Pelagic seabirds are colonial central‐place foragers, classically assumed to use flexible foraging strategies to target widely dispersed, spatiotemporally patchy prey. However, tracking has shown that IFSF occurs in many seabirds, although it is not known whether this persists across years. To test for long‐term IFSF and to examine alternative hypotheses concerning its cause, we repeatedly tracked 55 Northern Gannets (Morus bassanus) from a large colony in the North Sea within and across three successive breeding seasons. Gannets foraged in neritic waters, predictably structured by tidal mixing and thermal stratification, but subject to stochastic, wind‐induced overturning. Both within and across years, coarse to mesoscale (tens of kilometers) IFSF was significant but not absolute, and foraging birds departed the colony in individually consistent directions. Carbon stable isotope ratios in gannet blood tissues were repeatable within years and nitrogen ratios were also repeatable across years, suggesting long‐term individual dietary specialization. Individuals were also consistent across years in habitat use with respect to relative sea surface temperature and in some dive metrics, yet none of these factors accounted for IFSF. Moreover, at the scale of weeks, IFSF did not decay over time and the magnitude of IFSF across years was similar to that within years, suggesting that IFSF is not primarily the result of win–stay, lose–shift foraging. Rather, we hypothesize that site familiarity, accrued early in life, causes IFSF by canalizing subsequent foraging decisions. Evidence from this and other studies suggests that IFSF may be common in colonial central‐place foragers, with far‐reaching consequences for our attempts to understand and conserve these animals in a rapidly changing environment.

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Field campaigns are instrumental in providing ground truth for understanding and modeling global ocean biogeochemical budgets. A survey however can only inspect a fraction of the global oceans, typically a region hundreds of kilometers wide for a temporal window of the order of (at most) several weeks. This spatiotemporal domain is also the one in which the mesoscale activity induces through horizontal stirring a strong variability in the biogeochemical tracers, with ephemeral, local contrasts which can easily mask the regional and seasonal gradients. Therefore, whenever local in situ measures are used to infer larger-scale budgets, one faces the challenge of identifying the mesoscale structuring effect, if not simply to filter it out. In the case of the KEOPS2 investigation of biogeochemical responses to natural iron fertilization, this problem was tackled by designing an adaptive sampling strategy based on regionally optimized multisatellite products analyzed in real time by specifically designed Lagrangian diagnostics. This strategy identified the different mesoscale and stirring structures present in the region and tracked the dynamical frontiers among them. It also enabled back trajectories for the ship-sampled stations to be estimated, providing important insights into the timing and pathways of iron supply, which were explored further using a model based on first-order iron removal. This context was essential for the interpretation of the field results. The mesoscale circulation-based strategy was also validated post-cruise by comparing the Lagrangian maps derived from satellites with the patterns of more than one hundred drifters, including some adaptively released during KEOPS2 and a subsequent research voyage. The KEOPS2 strategy was adapted to the specific biogeochemical characteristics of the region, but its principles are general and will be useful for future in situ biogeochemical surveys.

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We investigated a 100 × 100 km high-salinity region of the North Atlantic subtropical gyre during the Sub-Tropical Atlantic Surface Salinity Experiment/Salinity Processes in the Upper-ocean Regional Study (STRASSE/SPURS) cruise from August 21, 2012, to September 9, 2012. Results showed great variability in sea surface salinity (SSS; over 0.3 psu) in the mesoscale, over 7 cm of total evaporation, and little diapycnal mixing below 36 m depth, the deepest mixed layers encountered. Strong currents in the southwestern part of the domain, and the penetration of freshwater, suggest that advection contributed greatly to salinity evolution. However, it was further observed that a smaller cyclonic structure tucked between the high SSS band and the strongest currents contributed to the transport of high SSS water along a narrow front. Cross-frontal transport by mixing is also a possible cause of summertime reduction of SSS. The observed structure was also responsible for significant southward salt transport over more than 200 km.

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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.

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Understanding the mechanisms linking oceanographic processes and marine vertebrate habitat use is critical to effective management of populations of conservation concern. The basking shark Cetorhinus maximus has been shown to associate with oceanographic fronts – physical interfaces at the transitions between water masses – to exploit foraging opportunities resulting from aggregation of zooplankton. However, the scale, significance and variability of these observed associations have not yet been established. Here, we quantify the influence of mesoscale (10s – 100s km) frontal activity on habitat use over timescales of weeks to months. We use animal-mounted archival tracking with composite front mapping via Earth Observation (EO) remote sensing to provide an oceanographic context to individual shark movements. We investigate levels of association with fronts occurring over two spatio-temporal scales, (i) broad-scale seasonally persistent frontal zones and (ii) contemporaneous mesoscale thermal and chl-a fronts. Using random walk simulations and logistic regression within an iterative generalised linear mixed modelling (GLMM) framework, we find that seasonal front frequency is a significant predictor of shark presence. Temporally-matched oceanographic metrics also indicate that sharks demonstrate a preference for productive regions, and associate with contemporaneous thermal and chl-a fronts more frequently than could be expected at random. Moreover, we highlight the importance of cross-frontal temperature change and persistence, which appear to interact to affect the degree of prey aggregation along thermal fronts. These insights have clear implications for understanding the preferred habitats of basking sharks in the context of anthropogenic threat management and marine spatial planning in the northeast Atlantic.

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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.

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Regional seas are potentially highly vulnerable to climate change, yet are the most directly societally important regions of the marine environment. The combination of widely varying conditions of mixing, forcing, geography (coastline and bathymetry) and exposure to the open-ocean makes these seas subject to a wide range of physical processes that mediates how large scale climate change impacts on these seas’ ecosystems. In this paper we explore the response of five regional sea areas to potential future climate change, acting via atmospheric, oceanic and terrestrial vectors. These include the Barents Sea, Black Sea, Baltic Sea, North Sea, Celtic Seas, and are contrasted with a region of the Northeast Atlantic. Our aim is to elucidate the controlling dynamical processes and how these vary between and within these seas. We focus on primary production and consider the potential climatic impacts on: long term changes in elemental budgets, seasonal and mesoscale processes that control phytoplankton’s exposure to light and nutrients, and briefly direct temperature response. We draw examples from the MEECE FP7 project and five regional model systems each using a common global Earth System Model as forcing. We consider a common analysis approach, and additional sensitivity experiments. Comparing projections for the end of the 21st century with mean present day conditions, these simulations generally show an increase in seasonal and permanent stratification (where present). However, the first order (low- and mid-latitude) effect in the open ocean projections of increased permanent stratification leading to reduced nutrient levels, and so to reduced primary production, is largely absent, except in the NE Atlantic. Even in the two highly stratified, deep water seas we consider (Black and Baltic Seas) the increase in stratification is not seen as a first order control on primary production. Instead, results show a highly heterogeneous picture of positive and negative change arising from complex combinations of multiple physical drivers, including changes in mixing, circulation and temperature, which act both locally and non-locally through advection.

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The ESA Data User Element (DUE) funded GlobCurrent project (http://www.globcurrent.org) aims to: (i) advance the quantitative estimation of ocean surface currents from satellite sensor synergy; and (ii) demonstrate impact in user-led scientific, operational and commercial applications that, in turn, will improve and strengthen the uptake of satellite measurements. Today, a synergetic approach for quantitative analysis can build on high-resolution imaging radar and spectrometer data, infrared radiometer data and radar altimeter measurements. It will further integrate Sentinel-3 in combination with Sentinel-1 SAR data. From existing and past missions, it is often demonstrated that sharp gradients in the sea surface temperature (SST) field and the ocean surface chlorophyll-a distribution are spatially correlated with the sea surface roughness anomaly fields at small spatial scales, in the sub-mesocale (1-10 km) to the mesoscale (30-80 km). At the larger mesoscale range (>50 km), information derived from radar altimeters often depict the presence of coherent structures and eddies. The variability often appears largest in regions where the intense surface current regimes (>100 - 200 km) are found. These 2-dimensional structures manifested in the satellite observations represent evidence of the upper ocean (~100-200 m) dynamics. Whereas the quasi geostrophic assumption is valid for the upper ocean dynamics at the larger scale (>100 km), possible triggering mechanisms for the expressions at the mesoscale-to-submesoscale may include spiraling tracers of inertial motion and the interaction of the wind-driven Ekman layer with the quasi-geostrophic current field. This latter, in turn, produces bands of downwelling (convergence) and upwelling (divergence) near fronts. A regular utilization of the sensor synergy approach with the combination of Sentinel-3 and Sentinel-1 will provide a highly valuable data set for further research and development to better relate the 2-dimensional surface expressions and the upper ocean dynamics.

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Investigating the variability of Agulhas leakage, the volume transport of water from the Indian Ocean to the South Atlantic Ocean, is highly relevant due to its potential contribution to the Atlantic Meridional Overturning Circulation as well as the global circulation of heat and salt and hence global climate. Quantifying Agulhas leakage is challenging due to the non-linear nature of this process; current observations are insufficient to estimate its variability and ocean models all have biases in this region, even at high resolution . An Eulerian threshold integration method is developed to examine the mechanisms of Agulhas leakage variability in six ocean model simulations of varying resolution. This intercomparison, based on the circulation and thermo- haline structure at the Good Hope line, a transect to the south west of the southern tip of Africa, is used to identify features that are robust regardless of the model used and takes into account the thermohaline biases of each model. When determined by a passive tracer method, 60 % of the magnitude of Agulhas leakage is captured and more than 80 % of its temporal fluctuations, suggesting that the method is appropriate for investigating the variability of Agulhas leakage. In all simulations but one, the major driver of variability is associated with mesoscale features passing through the section. High resolution (<1/10 deg.) hindcast models agree on the temporal (2–4 cycles per year) and spatial (300–500 km) scales of these features corresponding to observed Agulhas Rings. Coarser resolution models (<1/4 deg.) reproduce similar time scale of variability of Agulhas leakage in spite of their difficulties in representing the Agulhas rings properties. A coarser resolution climate model (2 deg.) does not resolve the spatio-temporal mechanism of variability of Agulhas leakage. Hence it is expected to underestimate the contribution of Agulhas Current System to climate variability.

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Investigating the variability of Agulhas leakage, the volume transport of water from the Indian Ocean to the South Atlantic Ocean, is highly relevant due to its potential contribution to the Atlantic Meridional Overturning Circulation as well as the global circulation of heat and salt and hence global climate. Quantifying Agulhas leakage is challenging due to the non-linear nature of this process; current observations are insufficient to estimate its variability and ocean models all have biases in this region, even at high resolution . An Eulerian threshold integration method is developed to examine the mechanisms of Agulhas leakage variability in six ocean model simulations of varying resolution. This intercomparison, based on the circulation and thermo- haline structure at the Good Hope line, a transect to the south west of the southern tip of Africa, is used to identify features that are robust regardless of the model used and takes into account the thermohaline biases of each model. When determined by a passive tracer method, 60 % of the magnitude of Agulhas leakage is captured and more than 80 % of its temporal fluctuations, suggesting that the method is appropriate for investigating the variability of Agulhas leakage. In all simulations but one, the major driver of variability is associated with mesoscale features passing through the section. High resolution (<1/10 deg.) hindcast models agree on the temporal (2–4 cycles per year) and spatial (300–500 km) scales of these features corresponding to observed Agulhas Rings. Coarser resolution models (<1/4 deg.) reproduce similar time scale of variability of Agulhas leakage in spite of their difficulties in representing the Agulhas rings properties. A coarser resolution climate model (2 deg.) does not resolve the spatio-temporal mechanism of variability of Agulhas leakage. Hence it is expected to underestimate the contribution of Agulhas Current System to climate variability.