Sea Surface Temperature Images Research Articles

A Multiscale Deep Framework for Ocean Fronts Detection and Fine-Grained Location

Ocean front plays an important role in marine fishery production and biogeochemical cycling. This letter proposes a multiscale deep framework to meet the need for automatic ocean front detection and fine-grained location. The framework mainly focuses on bringing a well-trained deep learning model into front detection and location on the global satellite sea surface temperature image. First, a multiscale scanner is designed to divide the ocean into small areas of different scales. Then, we introduce the deep model to determine that a front has occurred, and translate the global image into binary ones of various grained. Here, an overlapping scanning way is suggested to locate the front in a small region. Finally, all the binary images are scale-weighted fused into one image, which presents the center and periphery with different brightness levels. Experimental illustrations on three typical areas of the ocean are featured with six scanning scales to show the effectiveness and practical use of the proposed framework. Moreover, the comparison experiments with the traditional method also show its advantages.

Vertical structure and surface patterns of Green Island wakes induced by the Kuroshio

When the Kuroshio passes Green Island off Taiwan, well-organized wakes are formed by the interaction between the Kuroshio and the island. The vertical mixing in the wake produces cold water, which entrains from the mixed layer below the surface and results in relatively colder and saltier waters with a higher chlorophyll-a concentration on the sea surface to the lee of the island. The meander of the Kuroshio maximum velocity axis has a major influence on the island wake. The shift of the Kuroshio in front of Green Island not only weakens the flow velocity but also affects the development of the wake. In the Green Island wake, the density overturns with a Thorpe scale between 2.9 m and 20.5 m and the turbulent kinetic energy dissipation rate is 0.2 × 10−6–8.5 × 10−5 W kg−1, which corresponds to an eddy diffusivity in the range of 0.01–0.23 m2 s−1. The spatial distribution patterns of the sea surface temperature (SST) in the island wake are classified into four distinct types, as obtained from moderate-resolution imaging spectroradiometer (MODIS) SST images. The most frequently occurring type is of the wake alone, which accounts for 86.7% of the island wake patterns. The other three types are a wake with a tail stretching downstream (4.0%), a wake with a small cyclonic cold core but no tail stretching downstream (6.8%) and an S-shaped meandering wake (2.5%).

Automatic detection of Moroccan coastal upwelling zones using sea surface temperature images

ABSTRACTAn efficient unsupervised method is developed for automatic segmentation of the area covered by upwelling waters in the coastal ocean of Morocco using the Sea Surface Temperature (SST) satellite images. The proposed approach first uses the two popular unsupervised clustering techniques, k-means and fuzzy c-means (FCM), to provide different possible classifications to each SST image. Then several cluster validity indices are combined in order to determine the optimal number of clusters, followed by a cluster fusion scheme, which merges consecutive clusters to produce a first segmentation of upwelling area. The region-growing algorithm is then used to filter noisy residuals and to extract the final upwelling region. The performance of our algorithm is compared to a popular algorithm used to detect upwelling regions and is validated by an oceanographer over a database of 92 SST images covering each week of the years 2006 and 2007. The results show that our proposed method outperforms the latter algorithm, in terms of segmentation accuracy and computational efficiency.

Operational oceanography applied to skipjack tuna (Katsuwonus pelamis) habitat monitoring and fishing in south‐western Atlantic

AbstractSkipjack tuna (Katsuwonus pelamis) ranks third among marine resources that sustain global fisheries. This study delimits the spatiotemporal habitat of the species in the south‐western Atlantic Ocean, based on operational oceanography. We used generalized additive models (GAMs) and catch data from six pole‐and‐line fishing vessels operating during 2014 and 2015 fishing seasons to assess the effect of environmental variables on catch. We also analysed Modis sensor images of sea surface temperature (SST) and surface chlorophyll‐α concentration (SCC) to describe fishing ground characteristics in time and space. Catch was positively related to thermocline depth (24–45 m), SST (22–24.5°C), SCC (0.08–0.14 mg/m³) and salinity (34.9–35.8). Through SST images, we identified that thermal fronts were the main surface feature associated with a higher probability to find skipjack. Also, we state that skipjack fishery is tightly related to shelf break because bottom topography drives the position of fronts in this area. Ocean colour fronts and plankton enrichment were important proxies, accessible through SCC, used to delineate skipjack fishing grounds. Catch per unit effort (CPUE) was higher towards summer (median 14 t/fishing day) due to the oceanographic characteristics of the southern region. High productivity in this sector of the Brazilian coast defines the main skipjack feeding areas and, as a consequence, the greatest abundance and availability for fishing.

Eddies in the Western Mediterranean seen in thermal infrared imagery and SLA fields

ABSTRACTIn this article, daily fields of sea surface temperature (SST) and sea level anomaly (SLA) of the Western Mediterranean Sea obtained in 2011–2013 are being co-analysed. The study is aimed at assessing potentials of the fields of SLA for manifestation of mesoscale eddies in the region of interest. First, the SST imagery was inspected visually and locations of mesoscale eddies noticed in the images were detected. After that, closed contours were extracted in the fields of SLA and their locations were compared with locations of eddies directly seen in the SST images. Such a comparison showed that among anticyclonic eddies found in SST, about 56.3% had corresponding closed contours of SLA; the percentage was increasing with increasing eddy diameter. For cyclonic eddies, supposedly due to their smaller spatial and time scales, such percentage was only about 20.2%. During the warm season, when the mixed layer is particularly shallow and the turbulence is closer to the two-dimensional model, the correspondence between eddies seen in SST and closed contours of SLA was higher than during the cold period.

Remote sensing and in situ platform based study on impact of Bay of Bengal cyclones (Phailin, Helen, Lehar, and Madi) on ocean chlorophyll and associated physical parameters

Impact of four major cyclones: Phailin, Helen, Lehar, and Madi have been studied in terms of changes in ocean productivity utilizing Indian satellite Oceansat-2 ocean color monitor and MODIS-Aqua data during October–December 2013. The 8-day and monthly composite chlorophyll images have been generated owing to the pre-, during, and post-stages of four cyclones; out of which, three were very severe cyclonic storms and the Helen was severe cyclonic storm. The chlorophyll concentration increased two- to threefolds due to the aftereffect of cyclone in the coastal water, and the concentration was very high (around 2–3 mg/m3). To understand the possible links of cyclones to cooling and upwelling, MODIS-Aqua sea surface temperature (SST) images have been processed. The SST images have shown the cooling effect near the cyclone track pass, over Bay of Bengal. The cooling was observed by 2–3 degree Celsius during the above cyclones. To understand the in situ surface water and water column salinity and temperature variability, the Argo float data are plotted and interpreted. The surface contour shows the lowering of salinity and temperature with effects of cyclones. In addition, the Argo depth profile data have shown possible mixed layer deepening in few profiles around halocline and thermocline depths. This study will be useful for mapping potential fishing zone, ocean biogeochemistry and other useful applications and research.

Satellite observation of the winter variation of sea surface temperature fronts in relation to the spatial distribution of ichthyoplankton in the continental shelf of the southern East China Sea

ABSTRACTThe wintertime variations and distributions of sea surface temperature (SST) and thermal fronts associated with the spatial distribution of ichthyoplankton were investigated in the continental shelf waters of the southern East China Sea (ECS) by using 10 year (2005–2015) satellite SST images with an entropy-based edge detection method. The Mainland China Coastal Front and Kuroshio Front (KF) in winter (December to March) were examined with SST gradient magnitudes (GMs) of 0.20–0.40 and 0.30–0.45°C Km−1, respectively, along the 50 m and 100–200 m isobaths in the southern ECS. These two fronts coincided with isotherms of 14–16°C and 21–22°C, respectively. The Mainland China Coastal Front pattern remained fairly stable along the 50 m isobaths, and the coexisting SST front and upwelling were shifted seaward or shoreward with the recession or intrusion of the KF during the winters. Notably, the SST GMs of the KF showed a significant strengthening that was higher than those of the past two decades. Moreover, the total abundance of the nearshore waters of the KF (which was occupied by approximately 75% neritic species) was 23 times higher than that of the offshore waters (which was occupied by approximately 63.60% oceanic species). We suggest that the generation of the KF in winter may act as the biological barrier of oceanic organisms and larval fishes in the study area.

Coastal upwelling by wind-driven forcing in Jervis Bay, New South Wales: A numerical study for 2011

The Princeton Ocean Model (POM) was used to investigate an upwelling event in Jervis Bay, New South Wales (SE Australia), with varying wind directions and strengths. The POM was adopted with a downscaling approach for the regional ocean model one-way nested to a global ocean model. The upwelling event was detected from the observed wind data and satellite sea surface temperature images. The validated model reproduced the upwelling event showing the input of bottom cold water driven by wind to the bay, its subsequent deflection to the south, and its outcropping to the surface along the west and south coasts. Nevertheless, the behavior of the bottom water that intruded into the bay varied with different wind directions and strengths. Upwelling-favorable wind directions for flushing efficiency within the bay were ranked in the following order: N (0°; northerly) > NNE (30°; northeasterly) > NW (315°; northwesterly) > NE (45°; northeasterly) > ENE (60°; northeasterly). Increasing wind strengths also enhance cold water penetration and water exchange. It was determined that wind-driven downwelling within the bay, which occurred with NNE, NE and ENE winds, played a key role in blocking the intrusion of the cold water upwelled through the bay entrance. A northerly wind stress higher than 0.3 N m−2 was required for the cold water to reach the northern innermost bay.

Increased chlorophyll-a concentration in the South China Sea caused by occasional sea surface temperature fronts at peripheries of eddies

ABSTRACTThis study investigates the processes of occasional sea surface temperature (SST) fronts and their impacts on chlorophyll-a concentration (chl-a) in the South China Sea (SCS), based on satellite remote sensing and in situ observations in 2009–2013. The SST fronts were detected by an entropy-based edge detection algorithm method from satellite-derived SST images with a 0.011° grid size. Three offshore SST front case studies (S1, S2 and S3) at the peripheries of eddies in the northern SCS were studied. In case S1 in September 2013, two SST fronts were detected with gradient magnitudes (GMs) greater than 0.06°C km–1 in the cyclonic eddy and 0.08°C km–1 in the periphery waters, and the fronts only existed for one and two days, respectively. After three and seven days, the high chl-a was found in the strong SST front waters which were about 51 and 54% higher than the concentration in the surrounding waters. The depth of the maximum chl-a elevated from the subsurface (50 m) to the surface. In case S2 in August 2013, two SST fronts were detected at the periphery of an anti-cyclonic eddy with GM stronger than 0.06°C km–1 and only existed for one day. After two days, the chl-a in the SST front waters was about 40% higher than the levels in the surrounding waters. In case S3 in June 2009, the GM of the eddy-feature SST front was stronger than 0.12°C km–1 and existed for three days, which was generated by tropical cyclone Linfa. The chl-a in the eddy-feature phytoplankton bloom was 6 times higher than in the surrounding waters. The results show that, in general, occasional offshore SST fronts at peripheries of eddies have stronger influence on surface chl-a, comparing to those seasonal coastal and permanent offshore SST fronts, via ‘Wind Pump’ effects.

Optimization of Sea Surface Current Retrieval Using a Maximum Cross-Correlation Technique on Modeled Sea Surface Temperature

AbstractUsing sea surface temperature from satellite images to retrieve sea surface currents is not a new idea, but so far its operational near-real-time implementation has not been possible. Validation studies are too region specific or uncertain, sometimes because of the satellite images themselves. Moreover, the sensitivity of the most common retrieval method, the maximum cross correlation, to the parameters that have to be set is unknown. Using model outputs instead of satellite images, biases induced by this method are assessed here, for four different seas of western Europe, and the best of nine settings and eight temporal resolutions are determined. The regions with strong currents return the most accurate results when tracking a 20-km pattern between two images separated by 6–9 h. The regions with weak currents favor a smaller pattern and a shorter time interval, although their main problem is not inaccurate results but missing results: where the velocity is too low to be picked by the retrieval. The results are not impaired by the restrictions imposed by ocean surface current dynamics and available satellite technology, indicating that automated sea surface current retrieval from sea surface temperature images is feasible, for pollution confinement, search and rescue, and even for more energy-efficient and comfortable ship navigation.

Environmental Variability and Oceanographic Dynamics of the Central and Southern Coastal Zone of Sonora in the Gulf of California

This study analyzed monthly and inter-annual variability of mesoscale phenomena, including the El Niño Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO) climate indexes and wind intensity considering their influence on sea surface temperature (SST) and chlorophyll a (Chl-a). These analyses were performed to determine the effects, if any, of climate indexes and oceanographic and environmental variability on the central and southern coastal ecosystem of Sonora in the Gulf of California (GC). Monthly satellite images of SST (°C) and Chl-a concentration were used with a 1-km resolution for oceanographic and environmental description, as well as monthly data of the climate indexes and wind intensity from 2002–2015. Significant differences (p > 0.05) were observed while analyzing the monthly variability results of mesoscale phenomena, SST and Chl-a, where the greatest percentage of anti-cyclonic gyres and filaments was correlated with a greater Chl-a concentration in the area of study, low temperatures and, thus, greater productivity. Moreover, the greatest percentage of intrusion was correlated with the increase in temperature and cyclonic gyres and a strong decrease of Chl-a concentration values, causing oligotrophic conditions in the ecosystem and a decrease in upwelling and filament occurrence. As for the analysis of the interannual variability of mesoscales phenomena, SST, Chl-a and winds, the variability between years was not significant (p > 0.05), so no correlation was observed between variabilities or phenomena. The results of the monthly analyses of climate indexes, environmental variables and wind intensity did not show significant differences for the ENSO and PDO indexes (p > 0.05). Nonetheless, an important correlation could be observed between the months of negative anomalies of the ENSO with high Chl-a concentration values and intense winds, as well as with low SST values. The months with positive ENSO anomalies were correlated with high SST values, low Chl-a concentration and moderate winds. Significant inter-annual differences were observed for climate indexes where the years with high SST values were related to the greatest positive anomaly of ENSO, of which 2002 and 2009 stood out, characterized as moderate Niño years, and 2015 as a strong El Niño year. The years with the negative ENSO anomaly were related to the years of lower SST values, of which 2007–2008 and 2010–2011 stood out, characterized as moderate Niñas. Thus, variability associated with mesoscale oceanographic phenomena and seasonal and inter-annual variations of climate indexes had a great influence on the environmental conditions of the coastal ecosystem of Sonora in the Gulf of California.

Temporal trends in sea surface temperature gradients in the South Atlantic Ocean

In this study, we investigate the spatial and temporal characteristics of Sea Surface Temperature (SST) gradients in the South Atlantic Ocean (SAO) using satellite data. 12 years (2003–2014) of high resolution synoptic SST images acquired from NASA's MODIS instrument onboard Terra and Aqua platforms were processed to mitigate quality issues related to stripe noise and cloud misclassification and then compiled into monthly, yearly, and decadal maps of SST gradient magnitudes. We used these composite maps and corresponding time series to identify regions with strong frontal activity and characterize the seasonal and long term evolution of thermal gradients. While a clear seasonal cycle was observed in most subregions of the SAO, the satellite data do not suggest significant interannual variability or long term changes in the magnitude of thermal fronts in the SAO except in the upwelling region of Cape Frio Brazil, where SST gradients have increased at an approximate rate of 1% per year since 2003.

Temperature Surface of Guaíba Lake, RS, from time series of MODIS images

ABSTRACT The Guaíba lake is located in an area of complex weather variation and is influenced by many atmospheric circulation systems, bringing about violent occluded fronts, and, sometimes, intense precipitation. In Rio Grande do Sul, during El Niño, air temperatures and the precipitation index are higher, contrary to La Niña. Moreover, the Guaíba Lake receives water from the Guaíba's Hydrographical Region, which corresponds to 1/3 of Rio Grande do Sul State, and is thus an important water body to the metropolitan region of Porto Alegre. Methods that seek to understand the behavior of Guaíba lake surface water temperature (LSWT) may lead to relevant information to identify periods of more or less water warming, as well as the relations between LSWT, water quality deterioration and risks to human health. This paper aims to comprehend the behavior of Guaíba LSWT during periods of climatic anomalies (El Niño/La Niña). Therefore, 418 sea surface temperature (SST) images from the MODIS sensor were processed with SeaDas 7.2 software. The quarterly averages of LSWT were obtained and compared to the climatological anomalies in Equatorial Pacific Ocean. LSWT behavior is more complex in El Niño/La Niña periods. The results show that during climatic abnormality periods there are no direct relationship between the warming/cooling of Guaíba LSWT and the warming/cooling of Equatorial Pacific Ocean’s SST. The precipitation indices were more significant to the behavior of LSWT during El Niño periods, but for all periods (of climatic normality and abnormality), air temperature is what most influences LSWT. This relation occurs with climatic factors of water retention time, water entry and precipitation, and air temperature. There is a major correspondence during La Niña periods with the cooling of Guaíba LSWT only for some years. On the other hand, during El Niño periods there are no correspondences of this phenomenon with the warming of Guaíba LSWT. There are only more intense oscillations in surface temperatures than during regular and La Niña periods, but with a tendency to LSWT warming.

Study of the Temporal and Spatial Analysis by using SST Satellite Data

It is studied the sea surface temperature(SST) variation around Korean Peninsula by using Group for High Resolution Sea Surface Temperature(GHRSST) images for 22-year data from 1993 January 1 to 2014 December 31. For the accuracy of GHRSST data, near observation station were collected to correlate GHRSST and water temperature data. Mean correlation in Yellow Sea was 0.968, mean correlation in South Sea was 0.963, and mean correlation in East Sea was 0.962. The result of harmonic analysis showed that the amplitude of SST in Yellow Sea was 10~16℃ and the amplitude of SST in East Sea and South Sea was 8~12℃. The phase of SST in Yellow Sea was 230~235°, and the phase of SST in South Sea and East Sea was 240~244. EOF analysis resulted that the first mode of coefficient was 97.59%. When it is used with various climate data, for example, sea level, wind, air temperature, it will be represented the specific variation of SST.

Ocean Front Detection From Instant Remote Sensing SST Images

Identifying fronts manually from satellite images is a tedious and subjective task. Accordingly, edge detection algorithms are introduced for automatic detection of fronts. However, traditional algorithms cannot be applied to cloud-contaminated images, because missing data caused by occasional cloud coverage interferes with front detection. To diminish this risk, this letter proposes a new algorithm for a quick and an accurate detection of fronts from an instant cloud-contaminated sea surface temperature (SST) image, instead of depending on the daily or weekly averaged SST images. This algorithm adopts a data-driven analog interpolation method, which estimates missing values from the historical data of the same region. After reducing the contour between the interpolated data and the original data, an instant front detection algorithm is proposed based on microcanonical multiscale formalism (MMF). The algorithm utilizes MMF to detect singularity exponents (SEs), and then enhances the features detected in a cloud-contaminated region. Finally, a threshold is set to extract fronts from SE. Experimental results on an AVHRR satellite SST image of 12:00 o’clock covering China Coastal waters confirmed the effectiveness of the proposed algorithm.

Improving the Altimeter-Derived Surface Currents Using High-Resolution Sea Surface Temperature Data: A Feasability Study Based on Model Outputs

AbstractAccurate knowledge of ocean surface currents at high spatial and temporal resolutions is crucial for a gamut of applications. The altimeter observing system, by providing repeated global measurements of the sea surface height, has been by far the most exploited system to estimate ocean surface currents over the past 20 years. However, it neither permits the observation of currents moving away from the geostrophic balance nor is it capable of resolving the shortest spatial and temporal scales of the currents. Therefore, to overcome these limitations, in this study the ways in which the high-spatial-resolution and high-temporal-resolution information from sea surface temperature (SST) images can improve the altimeter current estimates are investigated. The method involves inverting the SST evolution equation for the velocity by prescribing the source and sink terms and employing the altimeter currents as the large-scale background flow. The method feasibility is tested using modeled data from the Mercator Ocean system. This study shows that the methodology may improve the altimeter velocities at spatial scales not resolved by the altimeter system (i.e., below 150 km) but also at larger scales, where the geostrophic equilibrium might not be the unique or dominant process of the ocean circulation. In particular, the major improvements (more than 30% on the meridional component) are obtained in the equatorial band, where the geostrophic assumption is not valid. Finally, the main issues anticipated when this method is applied using real datasets are investigated and discussed.

Space-based observation of chlorophyll, sea surface temperature, nitrate, and sea surface height anomaly over the Bay of Bengal and Arabian Sea

Monthly chlorophyll and sea surface temperature (SST) images were generated using MODIS-Aqua data sets during 2014 and 2015 in the Bay of Bengal and Arabian Sea. The in situ data-based nitrate algorithm was used to generate nitrate images by using the satellite-derived chlorophyll and SST images. To link ocean productivity with the sea surface features and sea level anomaly, the Indo-French altimeter mission SARAL-ALTIKA-derived sea surface height anomaly (SSHa) data sets were processed and maps were generated. The monthly average chlorophyll concentration ranged from 0.001 to 3.0mgm−3, SST ranged from 24 to 32°C, nitrate concentration ranged from 0.01 to 6.0μM, and overall SSH anomaly ranged from −52 to +40cm. Nitrate concentration was observed to be high (3–5μM) during December–January, possibly due to convective eddies and winter cooling as well as atmospheric aerosols and dust inducing ocean productivity. The nitrate concentration was observed to be associated more with chlorophyll than SST, as nitrate inherently enhances the ocean chlorophyll and productivity, acting as proxy. The SSH anomaly showed irregular features and depicting few eddies, upwelling, and ocean circulation features. The low SSHa was mostly due to high chlorophyll concentration. It was observed that the low SST (∼24–26°C) is attributed to high chlorophyll concentration (1.5–3.0mgm−3) over the study area. The lag phase and enhancement in chlorophyll mean during September was due to the decrease in average SST during August. The SSHa showed seasonal trend over the study area during the monsoon period with observation of negative anomaly. Arabian Sea was found to have more negative SSH anomaly monthly mean values than Bay of Bengal. The impact and interrelationship of SSHa indicated better relationship with chlorophyll than with nitrate and SST, as observed from multiple regression analysis. The analysis of variance (ANOVA) results between the 2-year monthly data showed that the interannual variability is lowest for SST, followed by chlorophyll (p=0.002), SSHa (p=0.053), and nitrate (p=0.068).

Species composition and assemblages of ichthyoplankton during summer in the East China Sea

The East China Sea (ECS) is one of the most important fish spawning and nursery grounds in the north Pacific. Even though summer is an important spawning season for many fishes in the region, large-scale molecular identification studies on ichthyoplankton during this season are few. In this study, we sampled 8,933 fish eggs and 12,161 fish larvae from 25 stations during the summer of 2009. Using DNA barcoding, a number of the fish eggs and larvae were identified and classified into 45 and 124 taxa, respectively. Principal component analysis (PCA) categorized the inshore stations of the Changjiang Diluted Water area as having the hydrographic features of low sea surface temperature (SST), salinity (SSS) and high chlorophyll a (SSC) contents, whereas the continental shelf and offshore stations under the influence of the Kuroshio Current displayed the opposite results. Ichthyoplankton was more abundant at the inshore stations than the offshore stations, but species diversity was lower at the former locations. Species compositions of both fish eggs and fish larvae at the 25 stations were categorized into three different assemblages based on a non-metric multidimensional scaling analysis. Combining the assemblage patterns of ichthyoplankton with the results of the PCA and satellite images of SST and SSC showed that the assemblage patterns of fish eggs were correlated with water mass, while those of the fish larvae were not.

Reconstrução dos Dados Faltantes em Imagens Orbitais de Temperatura da Superfície do Mar para a Região Sudoeste do Atlântico Sul

An empirical orthogonal function-based technique was used to reconstruct missing data of Sea Surface Temperature (SST) images. Sea surface temperature data was used to assess the benefits of a univariate reconstruction, and the combination of both SST and Maps of Sea Level Anomalies (MSLA) data was used in a multivariate approach. In the multivariate approach the effect of addition of MSLA data in the reconstruction of Brazil Current (BC) features was assessed. Results were satisfactory in both approaches. The combination of SST plus MSLA significantly improves results obtained by reconstruction; statistical analyses found an improvement of ~ 5%. All experiments correctly represent the mesoscale features off the southwest South Atlantic.

Environmentally-Mediated Flexible Foraging Strategies in Brown Boobies in the Gulf of California

The Brown Booby Sula leucogaster is a seabird with a pantropical distribution across a wide variety of oceanic environments. Sexual size dimorphism in Brown Boobies has been proposed as an explanation for intersexual differences in foraging, but results have been inconsistent. We investigated whether there is context-dependent foraging behaviour driven by local environmental conditions. In this study, we evaluated (1) inter-sex differences in foraging behaviour (by capillary tubes, temperature and depth recorders, and diet) at two colonies in the Gulf of California: Isla San Jorge (ISJ) and Farallon de San Ignacio (FSI) and, (2) intercolonial and interannual differences in foraging behaviour, and (at ISJ) their relationship with local-scale environmental variation, using 5-day composite images of sea surface temperature (SST) and primary productivity (PP) as proxies. Inter-sex differences were few and inconsistent between years, and smaller than overall differences between years and localities. At ISJ, Br...