Marina Fontaine
email: marina.fontain@gmail.com

Alice Carravieri

Benoit Simon-Bouhet

Paco Bustamante

Nicolas Gasco

Frédéric Bailleul

Christophe Guinet

Yves Cherel

・ Benoit

Frederic Bailleul

•-A Carravieri -F

C Bailleul -•

Guinet -Y

Cherel

Simon-Bouhet -P Bustamante

Ecological tracers and at-sea observations document the foraging ecology of southern long-finned pilot whales (Globicephala melas edwardii) in Kerguelen waters

Keywords: stable isotopes, mercury, marine mammal

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Understanding the role of cetaceans in the structure and functioning of ecosystems is directly linked to a better knowledge of their foraging ecology that is often difficult to assess in the marine environment [START_REF] Bowen | Role of marine mammals in aquatic ecosystems[END_REF]. Unlike breeding pinnipeds that can be handled ashore, cetaceans remain at sea all life long and, hence, investigating the food and feeding ecology of free-ranging odontocetes and mysticetes is especially challenging. Alternatively, mass stranding events offer a unique opportunity to collect large sets of biologically relevant data from dead specimens. Pilot whales (Genus Globicephala) are one of the most frequently reported cetaceans in mass strandings [START_REF] Olson | Pilot whales Globicephala melas and G. macrorhynchus[END_REF]. Two species of pilot whales are recognized: the short-and long-finned pilot whales (G. macrorhynchus and G. melas, respectively), with the latter species including two spatially segregated subspecies, namely G. m. melas in the North Atlantic and G. m. edwardii in the Southern Ocean [START_REF] Olson | Pilot whales Globicephala melas and G. macrorhynchus[END_REF][START_REF] Oremus | Worldwide mitochondrial DNA diversity and phylogeography of pilot whales (Globicephala spp.)[END_REF]. The overall biology of the northern subspecies is well known, e.g. mortality rate, life span (longevity up to 59 and 46 years in females and males, respectively) and adult length (up to 5.1 and 6.3 m in females and males) [START_REF] Donovan | Biology of the Northern Hemisphere pilot whales. A collection of papers[END_REF]. By contrast, the biology, including the food and feeding habits of the southern subspecies, is poorly documented. Dietary investigations on the southern long-finned pilot whale focused primarily on stomach content analysis of a few stranded individuals from Tasmania [START_REF] Gales | Stomach contents of long-finned pilot whales (Globicephala melas) and bottlenose dolphins (Tursiops truncatus) in Tasmania[END_REF]), New Zealand (Beatson et al. 2007a, b;[START_REF] Beatson | Stomach contents of long-finned pilot whales, Globicephala melas, mass-stranded on Farewell Spit, Golden Bay in 2005 and 2008[END_REF], Tierra del Fuego [START_REF] Goodall | A review of the food habits of the small cetaceans of the Antarctic and sub-Antarctic[END_REF][START_REF] Clarke | Cephalopods in the diets of three odontocete cetacean species stranded at Tierra del Fuego, Globicephala melaena (Traill, 1809), Hyperoodon planifrons Flower, 1882 and Cephalorhynchus commersonii (Lacepede, 1804)[END_REF]Mansilla et al. 2012) and Brazil (dos [START_REF] Dos Santos | Cephalopods in the diet of marine mammals stranded or incidentally caught along southeastern and southern Brazil (21-34°S)[END_REF], with no available information from the southern Indian Ocean. Cephalopods form the bulk of the food, but stomach content examination of stranded individuals suffers several drawbacks including overestimation of prey with hardly digestible elements that accumulate over time (e.g. cephalopod beaks), a bias towards the presence of near shore prey species, and the unknown health status of the animals [START_REF] Santos | Assessing the importance of cephalopods in the diets of marine mammals and other top predators: problems and solutions[END_REF].

Indirect trophic methods have been developed over the last 25 years to complement more conventional means. These methods use 'ecological tracers', such as stable isotopes, lipids and contaminants, and are all based on the common principle 'you are what you eat', i.e. the biochemical composition of molecules and tissues of consumers reflects that of their food in a predictable manner [START_REF] Ramos | Trace me if you can: the use of intrinsic biogeochemical markers in marine top predators[END_REF]. Stable isotope ratios of carbon (δ 13 C) and nitrogen (δ 15 N) are increasingly popular to investigate the ecology of terrestrial and marine organisms. δ 13 C values vary little along the food chain and are mainly used to determine primary sources in a trophic network [START_REF] Kelly | Stable isotopes of carbon and nitrogen in the study of avian and mammalian trophic ecology[END_REF][START_REF] Mccutchan | Variation in trophic shift for stable isotope ratios of carbon, nitrogen, and sulfur[END_REF]. In the marine environment, δ 13 C values indicate consumer foraging areas (i.e. inshore versus offshore and pelagic versus benthic) or latitudinal variation in the contribution to food intake [START_REF] Hobson | Using stable isotopes to determine seabird trophic relationships[END_REF], Cherel et al. 2000a;[START_REF] Pajuelo | Distribution of foraging habitats of male loggerhead turtles (Caretta caretta) as revealed by stable isotopes and satellite telemetry[END_REF]. In contrast, consumer tissues are enriched in 15 N relative to their food and δ 15 N values are used as indicators of consumers' trophic positions [START_REF] Mccutchan | Variation in trophic shift for stable isotope ratios of carbon, nitrogen, and sulfur[END_REF][START_REF] Vanderklift | Sources of variation in consumer-diet δ 15 N enrichments: a meta-analysis[END_REF]. A main interest of the isotopic method is that δ 13 C and δ 15 N values provide dietary information over different temporal scales depending on tissue-specific isotopic turnover rates that range from a few days for plasma to several years for bone collagen [START_REF] Dalerum | Resolving temporal variation in vertebrate diets using naturally occurring stable isotopes[END_REF][START_REF] Newsome | Using stable isotope biogeochemistry to study marine mammal ecology[END_REF].

Mercury (Hg) concentration can also be used as a biomarker of dietary preferences and trophic positions of consumers because the main source of Hg contamination is food and Hg biomagnifies along food webs, meaning that Hg level increases with increasing trophic position of consumers within a given ecosystem [START_REF] Gray | Biomagnification in marine systems: the perspective of an ecologist[END_REF][START_REF] Ramos | Trace me if you can: the use of intrinsic biogeochemical markers in marine top predators[END_REF]. Hg derives from both natural and anthropogenic sources. Owing to its high volatility and long atmospheric residence time, Hg reaches remote areas through long-range atmospheric transport, thus contaminating oceanic islands and Polar Regions [START_REF] Fitzgerald | The case for atmospheric mercury contamination in remote areas[END_REF]. Hg levels vary with the marine environments, being enhanced in coastal waters relative to the surface ocean, higher at depths relative to oceanic surface waters and depending on oceanic water masses [START_REF] Fitzgerald | Marine biogeochemical cycling of mercury[END_REF][START_REF] Cossa | Mercury in the Southern Ocean[END_REF]). In addition, Hg is a persistent, toxic and highly mobile metal in the marine environment. In mammals, Hg toxicity is primarily manifested as central nervous system damage including sensory and motor deficits and behavioural impairments.

Reliable toxicity data for marine mammals are scarce, but the slow rate of contaminant elimination and high contaminant levels of cetaceans make them good sentinel species for the monitoring of ecosystem health [START_REF] Das | Heavy metals in marine mammals[END_REF].

Using a combination of visual observations from fishing vessels together with stable isotopes and Hg from tissues of stranded animals as ecological tracers, the main aim of this exploratory study was to investigate the food and feeding ecology of southern long-finned pilot whales in a remote archipelago (Kerguelen), where almost nothing is known about the species.

Only a few records of pilot whales have been documented in the southern Indian Ocean, including Kerguelen waters [START_REF] Robineau | Les cétacés des îles Kerguelen[END_REF][START_REF] Robineau | Nouvelles données sur les cétacés des îles Kerguelen[END_REF]. The isotopic method was validated in the area, with δ 13 C values of predators indicating their foraging habitats [START_REF] Cherel | Geographical variation in carbon stable isotope signatures of marine predators: a tool to investigate their foraging areas in the Southern Ocean[END_REF][START_REF] Jaeger | Seabird satellite tracking validates the use of latitudinal isoscapes to depict predators' foraging areas in the Southern Ocean[END_REF] and their δ 15 N values increasing with trophic level [START_REF] Cherel | Isotopic niches and trophic levels of myctophid fishes and their predators in the Southern Ocean[END_REF]. In brief, δ 13 C values decrease from inshore to offshore consumers and they decrease with increasing oceanic latitudinal foraging habitats of the predators, while δ 15 N values increase in the order crustacean-eaters < small fish consumers < large fish and squid consumers. The pilot whale isotopic niche was determined using two tissues that record trophic information at different time scales, with skin and muscle integrating periods of weeks and months, respectively [START_REF] Browning | Isotope turnover rates and diet-tissue discrimination in skin of ex situ bottlenose dolphins (Tursiops truncatus)[END_REF][START_REF] Newsome | Using stable isotope biogeochemistry to study marine mammal ecology[END_REF]. Previous and ongoing investigations on Hg exposure showed a large range of Hg concentrations within marine organisms living in Kerguelen waters that indicates Hg biomagnification in the corresponding oceanic ecosystem (Bustamante et al. 2003a;[START_REF] Bocher | Influence of the diet on the bioaccumulation of heavy metals in zooplankton-eating petrels at Kerguelen archipelago, Southern Indian Ocean[END_REF][START_REF] Blévin | Wide range of mercury contamination in chicks of Southern Ocean seabirds[END_REF][START_REF] Carravieri | Penguins as bioindicators of mercury contamination in the Southern Ocean: birds from the Kerguelen Islands as a case study[END_REF][START_REF] Carravieri | Mercury exposure in a large subantarctic avian community[END_REF]. Ontogeny, age and sex modulates the foraging ecology, and thus the isotopic signature of cetaceans [START_REF] Das | Trace metal and stable isotope measurements (δ 13 C and δ 15 N) in the harbour porpoise Phocoena phocoena relicta from the Black Sea[END_REF][START_REF] Nino-Torres | Isotopic analysis of δ 13 C, δ 15 N, and δ 34 S "A feeding tale" in teeth of the long-beaked common dolphin, Delphinus capensis[END_REF][START_REF] Newsome | Retrospective characterization of ontogenetic shifts in killer whale diets via δ 13 C and δ 15 N analysis of teeth[END_REF], and feeding habits, age, size and sex affect their Hg levels [START_REF] Das | Heavy metals in marine mammals[END_REF][START_REF] Lahaye | New insights from age determination on toxic element accumulation in striped and bottlenose dolphins from Atlantic and Mediterranean waters[END_REF].

Hence, influences of individual traits (sex and size) on foraging habitat (δ 13 C) and trophic position (δ 15 N) as well as influences of both individual traits and foraging ecology on Hg concentrations were examined on a fairly large numbers of southern long-finned pilot whales that stranded in 2006 and 2010 at Kerguelen Islands.

Materials and methods

At-sea observations

Sightings of cetaceans were recorded by fishery observers working on-board seven French long-liners that fished within the Exclusive Economic Zone off Kerguelen Islands. The fishery targets the Patagonian toothfish (Dissostichus eleginoides) in slope waters (500-2,500 m depths) surrounding the archipelago. Observers recorded the occurrence, number and location (longitude and latitude) of any cetacean found in the area. Then, the geo-referenced data were included into the Pecheker data base [START_REF] Martin | Pecheker, relational database for analysis and management of fisheries and related biological data from the French southern ocean fisheries monitoring scientific programs[END_REF]. All the pilot whale records during the period 2003-2012 were extracted from the data base and the software R.2.15.3 ('base', 'RcolorBrewer' and 'fields'; R Development Core Team 2013) was used to build a repartition map of the species in Kerguelen waters (Fig. 1). Bathymetric data around the Kerguelen Plateau were extracted from the General Bathymetric Chart of the Oceans (GEBCO) at the British Oceanographic Data Centre (BODC) website.

Study sites, stranding events and tissue sampling

Fieldwork was carried out at Kerguelen Islands (southern Indian Ocean), which is located in the southern part of the Polar Frontal Zone, in the immediate vicinity of the Polar Front [START_REF] Park | Cross-frontal exchange of Antarctic intermediate water and Antarctic bottom water in the Crozet Basin[END_REF]. Two mass strandings of 91 and 135 southern long-finned pilot whales occurred on remote beaches of the Courbet Peninsula (49°21'S, 70°18'E) in October 2006 and January 2010, respectively. The precise dates of the two events are unknown. Noticeably, most internal organs from the carcasses were already scavenged by seabirds, thus precluding the collection of stomach contents, and hence, direct dietary analysis. All the specimens but four (n = 222) were measured (total length, TL). Small individuals with TL ≤3.0 m were considered as suckling calves as the average (maximum) TL at the onset of weaning are 2. 2 (3.2) and2.2 (3.5) m for females and males, respectively [START_REF] Desportes | Preliminary results on the diet of long-finned pilot whales off the Faroe Islands[END_REF]. Tissue sampling was performed on 193 specimens (n = 91 and 102 in 2006 and 2010, respectively). Both skin and muscle samples were collected from most pilot whales (n = 137), but some specimens were sampled for skin or muscle alone (n = 29 and 27, respectively). Tissue samples were either stored in 70 % ethanol (2006) or kept frozen at -20 °C (2010) until laboratory analyses in France.

Stable isotopes, mercury and molecular sexing

Any remain of subcutaneous white adipose tissue was removed from skin samples with a scalpel. The 2006 skin and muscle samples were first oven dried at 50 °C for 48 h for ethanol evaporation. Then, samples from both years were freeze-dried during 48 h and then grinded in a mortar. Since lipids are depleted in 13 C relative to other tissue components (DeNiro and Epstein 1977), they were extracted from skin and muscle samples using cyclohexane following [START_REF] Chouvelon | Inter-specific and ontogenic differences in δ 13 C and δ 15 N values and Hg and Cd concentrations in cephalopods[END_REF]. Powdered subsamples were weighed (0.3-0.4 mg) with a microbalance and packed into tin containers. Relative abundance of carbon ( 13 C/ 12 C) and nitrogen ( 15 N/ 14 N) were determined with a continuous flow mass spectrometer (Micromass Isoprime) coupled to an elemental analyser (Euro Vector EA 3024). Results are presented in the usual δ notation (in ‰) relative to Vienna PeeDee Belemnite and atmospheric N2 for δ 13 C and δ 15 N, respectively.

Replicate measurements of internal laboratory standards (acetanilide) indicated measurement errors <0.15 ‰ for both δ 13 C and δ 15 N values.

Between 5 and 15 mg of freeze-dried and powdered samples were analysed in an advanced Hg analyser spectrophotometer (Altec AMA 254) following [START_REF] Bustamante | Total and organic Hg concentrations in cephalopods from the North Eastern Atlantic waters: influence of geographical origin and feeding ecology[END_REF]. Hg determination involved evaporation of Hg by progressive heating until 800 °C under oxygen atmosphere for 2 min 30 s and subsequent amalgamation on a gold trap. The net was heated to liberate the collected Hg that was measured by UV atomic absorption spectrophotometry.

Samples were analysed for total Hg. All analyses were repeated 2-3 times until having a relative standard deviation <10 %. Accuracy was checked using certified reference material [Tort-2 Lobster Hepatopancreas, NRC, Canada; mean 0.27 ± 0.06 μg g -1 dry weight (dw)]. Our measured values were 0.29 ± 0.02 μg g -1 dw (n = 56). Blanks were analysed at the beginning of each set of samples and the detection limit of the method was 0.005 μg g -1 dw.

Sampled individuals were sexed genetically using polymerase chain reaction (PCR) of introns within the Zfx and Zfy genes [START_REF] Shaw | A reliable molecular method of gender determination for mammals[END_REF]. DNA was extracted and purified from a 25 mg aliquot of skin with the extraction kit 'NucleoSpin®Tissue'. PCR was performed on purified DNA ranging from 0.1 to 136 ng in a 20 μl reaction volume containing 12.5 μl of pure water, 2 μl of 1*Taq polymerase reaction buffer, 1.5 μM MgCl2, 150 μM dNTPs, 1.5 U of Taq polymerase (Invitrogen) and either 0.3 μM of primers ZFX0582 forward, ZFX0928 reverse (for Zfx/Zfy amplification) and SRY reverse or 0.06 μM of primer SRY forward (for SRY amplification, [START_REF] Rosel | PCR-based sex determination in odontocete cetaceans[END_REF]. PCRs were performed as follows: 1 cycle for 30 s at 92 °C, then 35 cycles of denaturation for 30 s at 94 °C, annealing for 45 s at 51 °C and amplification for 45 s at 72 °C. Then, each sample was loaded on a 3 % agarose gel and the fragments were separated by electrophoresis. Zfx-/Zfy-specific primers (Online Resource 1) allowed differentiating males (2 bands, 339 basepairs (bp) for the X-specific band and 382 bp for the Y-specific fragment) from females (1 band).

Methodological issue and statistical analyses

Since the precise dates of the two stranding events were unknown, the effect of the 'quality' of the skin samples was visually assessed. Samples were considered either 'bad' if skin was altered and not easily differentiable from the subcutaneous connective tissue or 'good' if skin was easily differentiable. The influence of sample quality on skin δ 13 C, δ 15 N and Hg values within each stranding event was tested with Welch's t tests using R.2.15.3 ('stats'). In both 2006 and 2010, skin samples of bad quality had significantly higher δ 13 C and δ 15 N values and significantly lower Hg values than good quality samples (Online Resource 2).

Muscle samples were then grouped according to the corresponding quality of skin samples and an identical quality effect was found for δ 15 N and Hg values but not for δ 13 C values in 2010 samples. In contrast, no significant differences between muscle samples of good and bad quality and Hg values from good 2010 muscle samples were used for statistical analyses (Table 1).

Welch's t tests (two-sample unpooled t tests for unequal variances) were used to check if the two tissues (skin and muscle) differed or not in various parameters (δ 13 C, δ 15 N and Hg). The influence of size (TL), sex and year of stranding on δ 13 C, δ 15 N and Hg values were investigated using generalized linear models (GLMs) using R.2.15.3 ('stats'). In models where Hg concentrations were the response variable, δ 13 C (but not δ 15 N values, see 'Results') was also incorporated as an explanatory variable. Models were constructed by incorporating the different variables and biologically significant interactions. Correlations between explanatory variables were tested using Pearson's correlation tests. The most parsimonious models were selected through forward selection according to the bias-adjusted Akaïke's Information Criterion (AICc), which is a small sample size adjustment [START_REF] Akaïke | Information theory and an extension of the maximum likelihood principle[END_REF][START_REF] Burnham | Model selection and multimodel inference: a practical information-theoretic approach[END_REF].

As a general guideline, if AICc values differ by more than 2, the model with the lowest AICc value is the most accurate, whereas models with AICc values differing by less than 2 are fairly similar in their ability to describe the data, and the model including the least number of parameters (the simplest) is the most accurate [START_REF] Lebreton | Modeling survival and testing biological hypotheses using marked animals: a unified approach with case studies[END_REF]). Residuals of selected models were checked for normality using Shapiro-Wilk test and Q-Q plots. The explained variation is reported for each model (Table 2). The relationship between Hg concentrations in skin and muscle was best described by a linear model. Values are mean ± SD.

Results

At-sea observations

A total of 131 at-sea observations of southern long-finned pilot whales were recorded within the Kerguelen Exclusive Economic Zone during the period from 31 October 2003 to 12 December 2012 (~9 years). The number of individuals per sighting averaged 53 individuals and ranged from 1 to ~300 individuals. The resulting map (Fig. 1) highlights the presence of the species in slope waters surrounding the Kerguelen Archipelago. Seasonal differences between winter and summer were found neither in pilot whale repartition nor in differences in the number of their at-sea observations (weighted by fishing effort that was quantified using the number of hooks).

Stranded individuals

TL of stranded southern long-finned pilot whales averaged 4.2 ± 1.1 m with no significant differences between the 2 years (Welch's t test, t = 0.22, p = 0.826). TL ranged from 1.6 to 6.9 m with a mode at 4-5 m (Fig. 2), which corresponds to the size range of the species (Bloch et al. 1993a, b). Skin and muscle δ 13 C, δ 15 N and Hg values during the 2 years are presented in Table 1. In 2006, δ 13 C and δ 15 N values were significantly lower in muscle than in skin, while Hg concentration was higher in muscle (t = -12.32, -10.68 and 5.12, respectively, all p < 0.0001). In 2010, δ 13 C value was again lower in muscle (t = -5.21, p < 0.0001), but δ15N values of the two tissues were not statistically different and Hg concentration was higher in skin than in muscle (t = -2.93, p < 0.010). A statistical comparison of the 2 years showed that skin δ 13 C values, but not skin δ15N and Hg values, were different (t = 5.16, p < 0.0001), and that muscle δ 13 C, δ 15 N and Hg values were all significantly different between 2006 and 2010 (t = 5.96, -3.59 and 10.19, p < 0.0001, <0.01 and <0.0001, respectively).

Statistical analyses of the influence of individual traits (sex and TL) and year of stranding on isotopic values (Table 2) showed that the most parsimonious GLM selected by AICc values included the effect of year in explaining tissue δ 13 C values, with δ 13 C values being significantly higher in 2006 than in 2010 (see above). Skin δ 15 N values were best explained by an effect of sex, TL and year, and muscle δ 15 N values by an effect of TL and year. Tissue δ 15 N values decreased with increasing TL in small individuals (≤3 m), but did not change with increasing TL in mature individuals (>3 m, Fig. 3). Indeed, skin and muscle δ 15 N values were significantly higher in small pilot whales (≤3 m) than in larger individuals (Welch's t tests, t = 3.28 and 3.61, p < 0.001 and <0.01, respectively).

Hg concentrations in skin and muscle were positively and linearly related, with linear models explaining 68 and 50 % of Hg variability in 2006 and 2010, respectively (Fig. 4). Given the size-induced effect in tissue δ 15 N values (see above), the effect of δ 15 N values on tissue Hg concentrations was tested separately on mature individuals only. There was no correlation between Hg concentrations and δ 15 N values in skin (F1,60 = 0.146, R² adj = 0, p = 0.704), whereas in muscle a negative relationship was highlighted (F1,75 = 19.33, p < 0.001), but the explained variance was very low (R² adj = 0.19). The influence of individual traits (sex and TL), year of stranding and δ 13 C values on tissue Hg concentrations was tested through GLMs.

For skin, the most parsimonious model selected by AICc values included the effect of TL and sex in explaining Hg values (Table 2). Females had significantly higher skin Hg concentrations than males (4.8 ± 2.1 vs. 3.6 ± 2.7 μg g -1 dw), with concentrations increasing with TL (Fig. 5).

For muscle, the best fit to the Hg data was obtained for the maximal model, which included the effect of sex, TL, year, δ 13 C values and their interactions (Table 2). Muscle Hg concentration was significantly higher in females than in males (6.0 ± 2.8 vs. 5.1 ± 3.1 μg g -1 dw) and higher in 2006 than in 2010 (Table 1).

Discussion

Foraging ecology and at-sea distribution

Sightings from long-liners emphasize the regular occurrence of southern long-finned pilot whales in slope waters around the Kerguelen Archipelago (Fig. 1). These at-sea observations were highly biased towards the Patagonian toothfish fishing grounds. However, the few previous sightings again points out the importance of slope waters for pilot whales in the area, with rare observations near the Kerguelen coastline [START_REF] Robineau | Les cétacés des îles Kerguelen[END_REF][START_REF] Robineau | Nouvelles données sur les cétacés des îles Kerguelen[END_REF]. These observations are in agreement with long-finned pilot whales inhabiting deep oceanic waters and zones of higher productivity along the continental and island shelf breaks, apparently venturing sometimes into neritic waters [START_REF] Abend | Review of distribution of the long-finned pilot whale (Globicephala melas) in the North Atlantic and Mediterranean[END_REF].

Muscle δ 13 C and δ 15 N values of long-finned pilot whales from Kerguelen Islands are similar to the isotopic data from Australian specimens [START_REF] Davenport | A trophic study of a marine ecosystem off southeastern Australia using stable isotopes of carbon and nitrogen[END_REF]. However, spatial variations in isotopic baselines preclude direct comparison of raw δ 13 C and δ 15 N values of pilot whales living in different water masses (Table 3). In contrast, isotopic comparisons together with the known food and feeding ecology of air-breathing vertebrates from Kerguelen Islands helped delineating the whale foraging habitat (δ 13 C) and dietary habits (δ 15 N). In brief, many investigations were conducted over the last 20 years on various Kerguelen seabirds (e.g. penguins, albatrosses and petrels) and pinnipeds (e.g. elephant seal and fur seals) and their prey using a variety of complementary methods (dietary analyses, bio-logging and stable isotopes) thus allowing defining relevant control species from different habitats (benthic versus pelagic, coastal versus offshore) and with different diets (crustaceans, cephalopods and fish) (Online Resource 3).

The relatively high muscle δ 13 C values of Kerguelen pilot whales preclude feeding in Antarctic waters [START_REF] Cherel | Isotopic niches of emperor and Adélie penguins in Adélie Land, Antarctica[END_REF]. Instead, their muscle δ 13 C values are similar to those of the Patagonian toothfish that feed over the Kerguelen outer shelf and slope waters (Cherel et al. 2008, unpublished data). Alternatively, since inshore-offshore and latitudinal δ 13 C gradients overlap in the area [START_REF] Cherel | Geographical variation in carbon stable isotope signatures of marine predators: a tool to investigate their foraging areas in the Southern Ocean[END_REF], the δ 13 C values may also suggest that pilot whales migrated from the subtropical to the subantarctic zone. However, the lack of associated high muscle δ 15 N values resulting from high δ 15 N baseline level in the subtropics [START_REF] Altabet | Sedimentary nitrogen isotopic ratio as a recorder for surface ocean nitrate utilization[END_REF][START_REF] Lourey | Sensitivity of δ 15 N of nitrate, surface suspended and deep sinking particulate nitrogen to seasonal nitrate depletion in the Southern Ocean[END_REF] does not support the migration hypothesis. Hence, the most parsimonious explanation of their muscle δ 13 C values is that southern long-finned pilot whales foraged primarily over the Kerguelen shelf break and nearby subantarctic oceanic waters in the months preceding their stranding, which is in agreement with at-sea observations of the species (see above).

Muscle δ 15 N value of pilot whales was much higher than that of crustacean-eaters from Kerguelen Islands, namely the southern rockhopper penguin and Antarctic and thin-billed prions (Cherel et al. 2010, Online Resource 3). The whale δ 15 N value was 1 ‰ above that of the myctophid fish consumers king penguin and Antarctic fur seal and 1 ‰ below the δ 15 N value of black-browed albatross, which has a catholic diet including large fish and squid (Cherel et al. 2000b[START_REF] Cherel | Stable isotopes reveal the trophic position and mesopelagic fish diet of female southern elephant seals breeding on the Kerguelen Islands[END_REF][START_REF] Cherel | Isotopic niches and trophic levels of myctophid fishes and their predators in the Southern Ocean[END_REF]. Accordingly, pilot whale muscle Hg concentration was two and one order of magnitude higher than those of planktivorous petrels and of the crustacean-and myctophid-eater blue petrel, respectively [START_REF] Bocher | Influence of the diet on the bioaccumulation of heavy metals in zooplankton-eating petrels at Kerguelen archipelago, Southern Indian Ocean[END_REF]. Furthermore, the pilot whale Hg concentration was two times higher than that of the white-chinned petrel, which has a more diverse diet, including various fish and squid species [START_REF] Delord | Atsea distribution and diet of an endangered top predator: relationship between white-chinned petrels and commercial longline fisheries[END_REF][START_REF] Cipro | Trace elements in tissues of white-chinned petrels (Procellaria aequinoctialis) from Kerguelen waters, Southern Indian Ocean[END_REF].

Hence, both trophic markers (δ 15 N and Hg) indicate that pilot whales did not prey primarily upon crustaceans, but favoured a mixed diet of fish and squid in Kerguelen waters. While prey cannot be determined at the species level using δ 15 N values, feeding on a large spectrum of fish and squid is in general agreement with stomach content analysis of long-finned pilot whales elsewhere [START_REF] Desportes | Preliminary results on the diet of long-finned pilot whales off the Faroe Islands[END_REF][START_REF] Pauly | Diet composition and trophic levels of marine mammals[END_REF][START_REF] Spitz | Prey preferences among the community of deepdiving odontocetes from the Bay of Biscay, Northeast Atlantic[END_REF]. The trophic position of the long-finned pilot whale within the Kerguelen oceanic ecosystem can be estimated at 4.7, using the combination of the mean whale muscle δ 15 N value, an assumed trophic level of 2.0 for the herbivorous salp Salpa thompsoni with a 3.4 ‰ δ 15 N value [START_REF] Cherel | Stable isotopes reveal the trophic position and mesopelagic fish diet of female southern elephant seals breeding on the Kerguelen Islands[END_REF], and a 2.7 ‰ 15 N enrichment factor between prey and cetacean muscle [START_REF] Borrell | Discrimination of stable isotopes in fin whale tissues and application to diet assessment in cetaceans[END_REF]. The trophic position compares well with those previously estimated for the northern subspecies using muscle isotopic measurements (4.9), standardized diet composition (4.4) and ecosystem modelling (4.7) [START_REF] Pauly | Diet composition and trophic levels of marine mammals[END_REF][START_REF] Lassalle | An assessment of the trophic structure of the Bay of Biscay continental shelf food web: comparing estimates derived from an ecosystem model and isotopic data[END_REF]. In Kerguelen waters, the southern long-finned pilot whale is a top consumer close to other marine mammals (e.g. southern elephant seal, 4.6) and large fish (e.g. Patagonian toothfish, 5.0), but the albatross trophic position is higher (5.3-5.7) and the oceanic ecosystem is dominated by the colossal squid (6.1; [START_REF] Cherel | Stable isotopes reveal the trophic position and mesopelagic fish diet of female southern elephant seals breeding on the Kerguelen Islands[END_REF].

Tissue-related isotopic differences result from two nonexclusive explanations, namely different biochemical compositions leading to tissue-specific isotopic discrimination factors, and tissuespecific isotopic turn-over rates inducing different trophic temporal integrations [START_REF] Wolf | Ten years of experimental animal isotopic ecology[END_REF]. Little or no differences were found in the isotopic ratios of lipid-extracted skin and muscle of cetaceans and hence in their discrimination factors [START_REF] Borrell | Discrimination of stable isotopes in fin whale tissues and application to diet assessment in cetaceans[END_REF][START_REF] Horstmann-Dehn | Stable carbon and nitrogen isotope ratios in muscle and epidermis of arctic whales[END_REF]. Consequently, the consistent ~0.7 ‰ δ 13 C difference between the two tissues of southern long-finned pilot whales suggests a temporal shift associated with a spatial change in the main foraging habitat, since skin and muscle integrate periods of weeks and months, respectively [START_REF] Newsome | Using stable isotope biogeochemistry to study marine mammal ecology[END_REF][START_REF] Browning | Isotope turnover rates and diet-tissue discrimination in skin of ex situ bottlenose dolphins (Tursiops truncatus)[END_REF]. However, isotopic variability of Kerguelen southern long-finned pilot whales overall remained low (<1 ‰, Table 1) within and between tissues and when compared the two stranding events. Such a low degree of isotopic variability suggests no major changes in the whale feeding ecology in Kerguelen waters over the medium-and long-term (skin versus muscle, and 2006 versus 2010, respectively).

Interestingly, most small individuals presented higher skin and muscle δ 15 N values than larger pilot whales. An ontogenetic isotopic shift associated with nursing and weaning was previously described in pinnipeds and cetaceans, which can be explained by the consumption of milk by calves and the resulting higher trophic position (δ 15 N) of the young relative to its mother [START_REF] Ducatez | Stable isotopes document winter trophic ecology and maternal investment of adult female southern elephant seals (Mirounga leonina) breeding at the Kerguelen Islands[END_REF][START_REF] Newsome | Retrospective characterization of ontogenetic shifts in killer whale diets via δ 13 C and δ 15 N analysis of teeth[END_REF]. In pilot whales, juveniles are weaned during a protracted period during which they progressively increase their consumption of natural prey [START_REF] Desportes | Preliminary results on the diet of long-finned pilot whales off the Faroe Islands[END_REF], thus inducing a concomitant δ 15 N decrease down to adult values. Neither tissue δ 13 C nor δ 15 N values changed with size thereafter, suggesting no major foraging variations associated with growth and age after weaning in Kerguelen pilot whales (Fig. 3).

Hg exposure

Exposure to Hg was previously investigated in many species of marine mammals, with liver exhibiting consistently the highest Hg concentrations, followed by kidney, muscle and skin [START_REF] Thompson | Metal levels in marine vertebrates[END_REF][START_REF] Das | Heavy metals in marine mammals[END_REF]. Accordingly, long-finned pilot whales presented relatively low and almost similar Hg levels in muscle and skin samples (Frodello et al. 2000, this study).

Cetacean skin is a fragile and highly vascularised surface tissue in which Hg is first sequestered into keratin and then eliminated by epidermal sloughing [START_REF] Wagemann | Mercury distribution in the skin of beluga (Delphinapterus leucas) and narwhal (Monodon monoceros) from the Canadian Arctic and mercury burdens and excretion by moulting[END_REF].

Despite Hg excretion by desquamation, positive correlations had been reported between Hg levels in skin and internal organs like liver (e.g. Dall's porpoises and small delphinids in [START_REF] Yang | Trace elements in skin of Dall's porpoises (Phocoenoides dalli) from the northern waters of Japan: an evaluation for utilization as non-lethal tracers[END_REF]Aubail et al. 2013, respectively). The equation between Hg levels in skin and liver of delphinids [START_REF] Aubail | Use of skin and blubber tissues of small cetaceans to assess the trace element content of internal organs[END_REF] allows calculating an estimated mean value and range of 494 ± 490 (0.3-2,210) μg g -1 dw in the liver of southern long-finned pilot whales from Kerguelen Islands. Within that context, the present study showed for the first time significant positive correlation between skin and muscle Hg values in cetaceans (Fig. 4). Hence, skin biopsy may be used as a non-destructive tool for assessing Hg concentrations of free-ranging pilot whales and for predicting their Hg concentrations in liver and muscle that are the two main Hg body reservoirs in marine mammals [START_REF] Yamamoto | Tissue distribution of heavy metals in Weddell Seals (Leptonychotes weddellii)[END_REF].

Hg burden was not previously investigated in the southern long-finned pilot whale but was determined in the northern subspecies and in the congeneric short-finned pilot whale (Globicephala macrorhynchus) that lives in warmer waters. Muscle Hg concentration of pilot whales from Kerguelen Islands was close to the levels measured in populations inhabiting the Faroe Islands and northern Japan. It was 2.5 times lower than Hg level in specimens from the Lesser Antilles and 4.4-7.8 times lower than Hg concentrations in animals living in the Mediterranean Sea (Corsica), southern Japan and New Caledonia (Table 3). Local biogeochemistry, geology and anthropogenic activities indirectly affect Hg content of cetaceans through Hg concentrations of their prey. For example, pelagic organisms are naturally Hg enriched in the Mediterranean Sea due to high organic Hg availability, and consequently Mediterranean predators, including cetaceans, contain high Hg levels [START_REF] Cossa | The Mediterranean mercury anomaly, a geochemical or a biological issue[END_REF][START_REF] Savery | Global mercury and selenium concentrations in skin from free-ranging sperm whales (Physeter macrocephalus)[END_REF]. Conversely, the comparatively low Hg burden of Kerguelen pilot whales can be explained by the combination of low organic Hg availability in subantarctic waters [START_REF] Cossa | Mercury in the Southern Ocean[END_REF] together with the absence of human activities releasing Hg in the area. Within odontocetes, the Kerguelen long-finned pilot whale was less contaminated or their muscle Hg concentrations were within the same range of values than most species so far investigated, but their muscle Hg level was consistently higher than that of mysticetes [START_REF] Thompson | Metal levels in marine vertebrates[END_REF][START_REF] Endo | Mercury contamination in the red meat of whales and dolphins marketed for human consumption in Japan[END_REF][START_REF] Endo | Contamination by mercury and cadmium in the cetacean products from Japanese market[END_REF][START_REF] Endo | Stable isotope ratios and mercury levels in red meat products from baleen whales sold in Japanese markets[END_REF]. These taxa-related differences can be explained by different feeding habits, with baleen whales generally preying upon lower trophic level prey than toothed whales, i.e. crustaceans and small fish versus squid and larger fish, respectively.

Significant variations in Hg burdens occurred between the two mass-stranding events. Muscle Hg concentration was three times lower in 2010 than in 2006, with no corresponding change in skin values. These inter-annual differences are difficult to interpret, but they might result from differential Hg turnover rates between skin and muscle that remain to be determined. Tissue Hg concentrations were positively correlated to individual TL in southern long-finned pilot whales, which is consistent with previous findings on cetaceans [START_REF] Honda | Heavy metal concentrations in muscle, liver and kidney tissue of striped dolphin, Stenella coeruleoalba, and their variations with body length, weight, age and sex[END_REF][START_REF] Thompson | Metal levels in marine vertebrates[END_REF][START_REF] Leonzio | Heavy metals and selenium in stranded dolphins of the Northern Tyrrhenian (NW Mediterranean)[END_REF]. Since tissue δ 15 N values did not increase with TL, the size-related Hg change was not a consequence of a progressive dietary shift and there was therefore a decoupling between Hg concentrations and trophic position. Compared to males, female pilot whales grow more slowly, are smaller (mean adult lengths 4.5 versus 5.7 m) and live longer (up to 59 and 46 years, respectively) (Bloch et al. 1993b). Hence, for a given body size, females are older than males and, accordingly, more Hg contaminated (Fig. 5). Overall, skin and muscle Hg concentrations were also higher in females, which is in agreement with higher liver Hg levels in females than in males of the northern subspecies [START_REF] Caurant | Factors influencing the accumulation of metals in pilot whales (Globicephala melas) off the Faroe Islands[END_REF].

In conclusion, both ecological tracers (δ 13 C, δ 15 N, Hg) and at-sea observations indicate that Kerguelen southern long-finned pilot whales foraged primarily in slope waters and oceanic subantarctic waters where they occupy a high trophic position. Their precise feeding habits remain to be determined, but it is likely that they prey on a mixed diet of fish and squid in the deep sea, as other populations of pilot whales do [START_REF] Aguilar De Soto | Cheetahs of the deep sea: deep foraging sprints in short-finned pilot whales off Tenerife (Canary Islands)[END_REF][START_REF] Spitz | Prey preferences among the community of deepdiving odontocetes from the Bay of Biscay, Northeast Atlantic[END_REF].

Muscle Hg concentration of southern long-finned pilot whales is close to or lower than that of many odontocete species. Noticeably, they are less Hg contaminated than most pilot whale populations studied so far, thus suggesting that the southern subspecies is not at a high risk to Hg-induced damages in the remote islands of the Southern Ocean.

  were found in 2006. Consequently, δ 13 C, δ 15 N and Hg values from good 2006 and 2010 skin samples, all 2006 muscle δ 13 C, δ 15 N and Hg values, all 2010 muscle δ 13 C values, but only δ 15 N

Figure 1 .Figure 2 .Figure 3 .

 123 Figure 1. Location of Kerguelen Islands within the Indian Ocean (inset) and spatial at-sea observations of long-finned pilot whales from long-liners targeting Patagonian toothfish in Kerguelen waters during the period 2003-2012. Colour scale on the right indicates bathymetry (m)

Figure 4 .

 4 Figure 4. Relationship between skin and muscle Hg concentrations of calves (triangles up), females (circles), males (squares) and unsexed (triangle down) long-finned pilot whales that stranded in 2006 (white) and 2010 (black). Linear regressions: y = 0.69x + 0.80, r2 = 0.68, F1,37 = 78.36, p < 0.0001 and y = 0.89x + 1.62, r2 = 0.50, F1,24 = 23.90, p < 0.0001 in 2006 and 2010, respectively.

Figure 5 .

 5 Figure 5. Relationship between skin Hg concentrations and total length of long-finned pilot whales (individuals from the two stranding events were pooled according to sexes and including calves). Best GLM model (Gaussian distribution, identity link function, 73 % of explained variation): y (females, white circles) = 1.88x -2.34, y (males, black squares) = 1.88x -3.75

Table3. A review of skin and muscle δ 13 C, δ 15 N and Hg values in pilot whales. Values are mean ± SD; nm no measurements ; a Values are mean ± SE; b Results were initially reported in wet weight and were converted here to dry weight using a factor of 0.285[START_REF] Dam | Screening of mercury and persistent organochlorine pollutants in long-finned pilot whale (Globicephala melas) in the Faroe Islands[END_REF]

Acknowledgements:

The authors thank Y. Charbonnier, A. Chevallier, J. Nezan and other fieldworkers who collected tissue samples in the field, G. Guillou for stable isotope analysis, and C. Churlaud and M. Brault-Favrou for their assistances during Hg analysis. We are grateful to the fishery observers on longliners, COPEC Service of Territoire des Terres Australes et Antarctiques Françaises (TAAF). The present work was supported financially and logistically by the Agence Nationale de la Recherche Programme TOPP-PATCHES (F. Bailleul), the Institut Polaire Français Paul Emile Victor (IPEV, Programme No. 109, H. Weimerskirch), and the TAAF.

Table 2. Generalized linear models (Gaussian distribution, identity link function) selected for each tissue (skin: δ 13 Cs, δ 15 Ns, Hgs; muscle: δ 13 Cm, δ 15 Nm, Hgm) with their corresponding AIC. AICc Akaike's Information Criteria adjusted for small sample sizes, Exp. Var. explained variation adjusted by sample size and number of parameters, TL total length


Ricardo Campos
email: ricardo.campos@inesctec.pt

Gaël Dias
email: gael.dias@unicaen.fr

Alipio Jorge
email: amjorge@fc.up.pt

Celia Nunes
email: celian@ubi.pt

Alípio Mário

Célia Nunes

GTE-Rank: Searching for Implicit Temporal Query Results

Keywords: Implicit Temporal Query Results H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval -Query Formulation; H.3.4 [Information Storage and Retrieval]: Systems and Software -Performance Temporal Information Retrieval, Implicit Temporal Queries, Temporal Re-Ranking, Temporal Query Understanding

come

INTRODUCTION

Despite the emergence of a large spectrum of time-aware search and retrieval applications, most popular search engines still do not take advantage of the temporal information contained in web pages. Current search engines either give users the possibility to specify a point-in-time of their interest or apply freshness metrics to push to the top list the most recent web search results. While this may be a suitable solution for the news domain for which a huge quality of time-stamped web pages are available and for recent events which require evidence spike phenomena, it may prove to be inefficient if the user is more interested in wide coverage temporally diversified information. This is particular evident for implicit temporal queries (e.g., "Haiti earthquake", "BP oil spill" or "Madagascar"), which beyond not being explicitly tagged with a temporal feature, span over a broad timeline. In this paper, we present GTE-Rank an online search interface, which allows searching for topics through time. GTE-Rank is designed to enhance user's experience through a balanced approach that takes into account both the conceptual and the temporal dimensions of the topic. The rationale is that offering the user a comprehensive temporal contextualization of the topic is intuitively more informative than simply retrieving only the most recent results or just its contextual perspective. For instance, when querying for the well-known American actor "Philip Seymour Hoffman", who has passed away recently, it would be interesting to know who he was or when did he die, but also to be provided with other important topics and time information, such as, when did he begin acting in television, where he was born or which movie gave him the award for the best actor performance. Such a new presentation of the results would enable users to gain not only a broad insight of the topic but also to understand its multiple temporal dimensions, thus contributing to improve user's satisfaction [START_REF] Alonso | Effectiveness of Temporal Snippets[END_REF].

Aware of the above, researchers have started to address the problem of returning documents that are not only topically relevant but that are also from the most important time periods and not just the latest. Different studies have been proposed to solve this problem. The research that are most related to our approach are [START_REF] Berberich | A Language Modeling Approach for Temporal Information Needs[END_REF][START_REF] Metzler | Improving Search Relevance for Implicitly Temporal Queries[END_REF][START_REF] Kanhabua | Determining Time of Queries for Re-Ranking Search Results[END_REF]. Berberich et al. [START_REF] Berberich | A Language Modeling Approach for Temporal Information Needs[END_REF] for example, ranks documents according to the estimated probability of generating the query through a language model framework that requires documents and queries to be explicitly time stamped. The methods put forward by Metzler et al. [START_REF] Metzler | Improving Search Relevance for Implicitly Temporal Queries[END_REF] and Kanhabua & Nørvåg [START_REF] Kanhabua | Determining Time of Queries for Re-Ranking Search Results[END_REF] suggest an alternative solution. They propose a timedependent ranking model to explicitly adjust the score of a document in favor of those matching the determined time(s) of an implicit temporal query. None of these works however, consider extracting temporal features from the documents contents in order to determine the possible time(s) of the query. Metzler et al. [START_REF] Metzler | Improving Search Relevance for Implicitly Temporal Queries[END_REF] uses query logs and Kanhabua & Nørvåg [START_REF] Kanhabua | Determining Time of Queries for Re-Ranking Search Results[END_REF] takes advantage of the creation date of the document, which may be significantly different from the actual content. We differ from previous studies on this subject in several other aspects. First, our methodology is unsupervised as no specific training process is needed to determine the time(s) of the query. Second, it is mostly language-independent as it implements a rule-based model supported by simple regular expressions to extract relevant dates. Finally, besides estimating the degree of relevance of a temporal expression, we propose to determine whether or not a date is query relevant, thus using this information to improve the re-ranking of web search results. The remainder of this paper is organized as follows. Section 2 describes the architecture behind the GTE-Rank system. Section 3 presents the proposed demonstration. Finally, Section 4 concludes this paper with some final remarks.

SYSTEM ARCHITECTURE

In this section, we describe the main components of the GTE-Rank system. GTE-Rank proceeds in two steps. First, the system evaluates the correlation between a given query and the candidate dates extracted within web snippets leading to the identification of top relevant dates. Second, a linear combination of topical and temporal scores is defined to reflect the relevance of any web snippet both in the topical and in the temporal dimensions. The overall structure of GTE-Rank architecture is represented in Figure 1 The GTE-Rank interface receives a query from the user, fetches related web snippets from a given search engine and applies text processing to all web snippets. This processing task involves selecting the most relevant words and collecting the candidate years in each web snippet. Each candidate year is then given a temporal similarity value to the query computed in the temporal similarity module. We then apply a classification strategy in the date filtering module, to determine whether the candidate years are actually relevant or not to the query. Non-relevant ones will be simply discarded by the system. Each snippet is then reordered according to its contents and how they relate to the query both in the temporal and in the topical dimensions. A brief description of each component is provided below.

(1) Web Search. We apply a web search API, which, given an implicit temporal query, accesses an up-to-date index search engine to obtain a collection of web results. Since results are produced "on-the-fly", we simply return the set of n-top web snippets retrieved in response to the user's query, thus keeping the system computationally efficient.

(2) Web Snippet Representation. Each snippet is represented by a bag-of-relevant-words and a set of candidate temporal expressions extracted from the title of the snippet and from the text itself. As shown by Alonso et al. [START_REF] Alonso | Effectiveness of Temporal Snippets[END_REF], web snippets offer an interesting alternative for the representation of web documents, where years often appear, thus avoiding the cost of parsing full web pages. We rely on a segmentation process and a numerical selection heuristic to extract relevant words 1 and a simple rulebased model supported on regular expressions to extract explicit temporal patterns. We focus on the extraction of temporal patterns of the year granularity level to keep the system mostly language-independent. The obtained result is a set of distinct candidate years extracted from the set of all web snippets.

(3) Temporal Similarity. Each candidate year d j is then given a temporal similarity value representing its degree of relevance to the query q. To model this relevance, we apply our temporal similarity measure GTE [START_REF] Campos | GTE: A Distributional Second-Order Co-Occurrence Approach to Improve the Identification of Top Relevant Dates[END_REF], which retrieves a value ranging from 0 to 1. A web service of GTE is provided 2 so that it can be tested by the research community. The web service returns in XML format, the temporal similarity value calculated between the query and all the candidate dates, together with the corresponding contents where the candidate dates appear. (4) Date Filtering. Next, the system determines whether or not the candidate temporal expressions are relevant to the query by applying GTE-Class [START_REF] Campos | GTE: A Distributional Second-Order Co-Occurrence Approach to Improve the Identification of Top Relevant Dates[END_REF], a classical threshold-based strategy, which considers a candidate date to be relevant, if and only if ( ) and non-relevant otherwise. Based on this, each snippet is no longer represented by a set of candidate temporal expressions but by a set of relevant dates. One consequence of this, is a direct impact on the quality of the retrieved results, as non-relevant or wrong dates are simply discarded. A description of the GTE-Class demo 3 can be found in our recent work [START_REF] Campos | GTE-Cluster: A Temporal Search Interface for Implicit Temporal Queries[END_REF]. (5) Temporal Ranking. The final step of the GTE-Rank architecture is our temporal re-ranking model. GTE-Rank relies on a linear combination approach that considers topical and temporal scores. The underlying idea is that a document should be ranked higher if its contents are topically and temporally related to the query. GTE-Rank is defined below.

[ ] and are the tuning parameters setting the importance of each of the two dimensions, is the query, is one of the relevant dates of the snippet , is one of the most relevant terms of the snippet and IS [START_REF] Dias | Topic Segmentation Algorithms for Text Summarization and Passage Retrieval: An Exhaustive Evaluation[END_REF] a second-order similarity measure that calculates the correlation between all pairs of two context vectors and , where is the context vector representation of and of . Both context vectors are formed by a combination of the best relevant terms and best relevant dates determined by the DICE coefficient measure.

( ) ∑ ( ) ∑ ( )
Central to this ranking function is the computation of two similarities. GTE gives the similarity between the query and each of the relevant dates found in the snippet. IS gives the similarity between the query and each of the relevant words found in the snippet. Note that one of the advantages of our approach relies precisely on the use of GTE as it enables GTE-Class to filter out from the ranking module the set of all nonrelevant dates. Experiments with a publicly available dataset 4 consisting of 1900 web snippets and 38 implicit text queries show that GTE-Rank is able to achieve better results under several evaluation metrics compared to three different baselines.

A fully detailed description of the underlying scientific approach and the evaluation methodology can be found in [START_REF] Campos | Disambiguating Implicit Temporal Queries for Temporal Information Retrieval Applications[END_REF].

DEMONSTRATION OVERVIEW

As a result of our research, we publicly provide an online demo (http://wia.info.unicaen.fr/GTERankAspNet_Server).GTE-Rank was implemented using .Net technology (C#) and asp.net on the server side. The implemented version is designed to demonstrate the current state of the demo, thus concerns of design nature where not taken into account. Although the main motivation of our work is focused on queries with temporal nature, GTE-Rank allows the execution of any query including non-temporal ones. Since our system does not pose any constraint in terms of language or domain, users can issue queries in any language, ranging from business (e.g. "iPad"), cinema (e.g. "true grit"), politics (e.g. "Margaret Thatcher"), natural disasters (e.g. "Haiti earthquake"), musical topics (e.g. "Radiohead"), to cite just a few. To retrieve the results, we use a prospective search where the query is first issued before results are gathered and indexed.

For this purpose we rely on Bing Search API 5 with the en-US language parameter defined to retrieve 50 results per query. The proposed solution is computationally efficient and can easily be tested online (limited to 5000 queries per month). In response to a query submitted in a search box, GTE-Rank displays a set of ranked web snippets on the fly. We offer two types of retrieval: one that returns only web snippets having dates and one that returns the set of all the 50 web snippets, whether or not they have dates. In addition, we give users the chance to adjust the temporal and conceptual parts of the system. Through an interactive browsing tuning parameter, the user is thus able to define the importance of the two dimensions. is currently

Identification of Top Relevant Dates

Temporal Ranking GTE-Rank preset to 0.8 as GTE-Rank has achieved the best performance with this value in the experiments carried out. Each web snippet is also assigned a relevance ranking value reflecting its topical and temporal similarity with the user's query. This value is positioned in front of the number in red color, which defines the ranking position initially obtained by Bing search engine. In this demo, we show the ability of the ranking system not only in how it pulls up to the top the relevant documents, but also in how it pushes down to the tail the non-relevant ones, thus ensuring that they will not occupy top positions of the ranking results. An illustration of the interface is provided in Figure 2 for the query "true grit" (top 10 results). It is interesting to note that our algorithm retrieves in the second, third, sixth, seventh and tenth position, five relevant results that were initially retrieved by the Bing search engine in the thirty-fifth, thirty-first, twenty-first, thirty-ninth and twenty-fifth positions, respectively. Furthermore, we show that our algorithm is also able to promote to the top, relevant documents which do not include any temporal expression.

CONCLUSION

In this article we present GTE-Rank an online searching system that aims to retrieve in the top list of the results, documents that are not only topically relevant but that are also from the most important time periods. GTE-Rank relies on a similarity measure that is capable of identifying top relevant dates for queries where no temporal information is provided and a re-ranking model that combines both conceptual and temporal relevancies in a single score, thus offering a balanced approach of the results. We adopt a methodology that can be applied to real-world search scenarios and a content-based approach, which enables to return documents about a given period, as opposed to the retrieval of documents written or published at a given date. As a practical demonstration of our research, we provide a demo service so that GTE-Rank can be tested by the research community. Although we focus on web snippets, our approach is similarly applicable to small texts collections embodying temporal information, such as Twitter posts.

  and consists of five different modules: (1) Web search; (2) Web snippet representation; (3) Temporal similarity; (4) Date filtering and (5) Temporal ranking.

Figure 1 :

 1 Figure 1: GTE-Rank Architecture.

  1 http://wia.info.unicaen.fr/TokenExtractor/api/Token?query= [May 29th, 2014] 2 http://wia.info.unicaen.fr/GTEAspNetFlatTempCluster_Server/api/GTE?FilterDates=false&query= 3 http://wia.info.unicaen.fr/GTEAspNetFlatTempCluster_Server[May 29th, 2014]

Figure 2 :

 2 Figure 2: GTE-Rank interface for the query "true grit". Top 10.Finally, Figure3shows the tail 5 ranking results for the same query. It is interesting to note that our algorithm is able to position well down in the list of the results, temporally nonrelevant documents that were initially positioned at top positions by Bing search engine, of which IDs 5, 13 and 17 are elucidative examples. A video outlining the demo proceeding is available at http://www.ccc.ipt.pt/~ricardo/software.html.

Figure 3 :

 3 Figure 3: GTE-Rank interface for the "true grit". Tail 5.

ACKNOWLEDGMENTS

This research was funded by Project NORTE-07-0124-FEDER-000059 which is financed by the North Portugal Regional Operational Programme (ON.2 -O Novo Norte), under the National Strategic Reference Framework (NSRF), through the European Regional Development Fund (ERDF), and by national funds, through FCT. It was also financed by the ERDF through the COMPETE Programme (operational programme for competitiveness), by National Funds through the FCT within project «FCOMP-01-0124-FEDER-037281» and by the Center of Mathematics, UBI, within project «PEst-OE/MAT/UI0212/2014».


Jose G Moreno
email: jose.moreno@unicaen.fr

Gaël Dias
email: gael.dias@unicaen.fr

HULTECH at the NTCIR-11 IMine Task: Mining Intents with Continuous Vector Space Models

Keywords:

In this paper, we present our participation in the Subtopic Mining subtask of the NTCIR-11 IMine task, for the English language. Our participation presents a novel strategy for intent mining given a list of candidates for a specific query topic. This strategy is based on a topic exploration through the use of continuous vector space models for each of the candidates based on classical vectorial operations. Our best run outperforms the other participants' submissions in terms of F -score and achieves a high position in the general ranking.

INTRODUCTION

Adequate hierarchical intent identification for Web queries is a challenging task [START_REF] Liu | Overview of the ntcir-11 imine task[END_REF]. For this reason, the IMine Subtopic Mining subtask 1 for this year is concentrated on this challenge. In brief, this subtask consists in, given a query topic, returning as output a two level hierarchical structure of strings that cover the possible intents of the query. Moreover, the output must follow two restrictions: [START_REF] Hinton | Distributed representations[END_REF] the first level can only include a maximum of four different strings and (2) in the second level, a maximum of ten string could be associated to each string in the first level. For evaluation purposes, the organizers propose a set of novel metrics for hierarchical evaluation and others previously introduced in [START_REF] Sakai | Evaluating diversified search results using per-intent graded relevance[END_REF].

In this paper, we describe the HULTECH team participation in the mentioned challenge. Indeed, this is our second participation in the NTCIR tasks related to intent identification. In our previous participation [START_REF] Moreno | Hultech at the ntcir-10 intent-2 task: Discovering user intents through search results clustering[END_REF], we propose a modified version of the classical k-means algorithm to identify intents through the clustering of search results [START_REF] Moreno | Post-retrieval clustering using third-order similarity measures[END_REF]. An extended version of this strategy can be found in [START_REF] Moreno | Query log driven web search results clustering[END_REF] where this strategy has been successfully tested in intent identification. For this year, we decide to focus our efforts in new exploratory ideas. Indeed, we try to introduce a novel technique, called continuous vector space models, to calculate word similarities instead of our previous word-word frequencies strategy.

Recently, many studies have been concerned with this task [START_REF] Sakai | Summary of the ntcir-10 intent-2 task: Subtopic mining and search result diversification[END_REF]. However, none of them have exploited recent advances in vectorial word representations. In this paper, we present a novel strategy that uses this new way to represent words with a special interest in the new available word-word operations. The underlying idea is that diversification of the intents can be achieved using classical vector operations. Results show that our strategy achieves top performance when compared to other participants of this task. In particular, our best run achieves the top position in terms of the Fscore. Indeed, even when other participants outperform our method in terms H-measure, our method remains in the top three positions when evaluated with this metric. The remainder of this paper includes a brief introduction to continuous vector space models in Section 2, our intent mining strategy based on vectors in Section 3, results are presented in Section 4, and finally, discussion and conclusions are presented in Sections 5 and 6.

CONTINUOUS VECTOR SPACE MOD-ELS

Recent ways to represent words are getting a lot of attention in NLP and IR communities. Indeed, the possibility of representing words with vectors is not new [START_REF] Hinton | Distributed representations[END_REF]. Some previous works have used decompositional methods to represent words as vectors [START_REF] Lund | Producing high-dimensional semantic spaces from lexical co-occurrence[END_REF]. But, some of the difficulties of these kind of studies are that they demand high computational power to achieve good performance in their representations. However, in [START_REF] Mikolov | Distributed representations of words and phrases and their compositionality[END_REF] the authors have shown that adequate representations of words could be achieved with limited resources over large datasets. Their method relies in recursive and non-recursive neural networks. The idea is that continuous words could help to define the vectorial representation in a similar way that n-grams models can successfully define semantic relationships between words. Indeed, the use of neural networks is motivated by their strong capability to solve the underlying mathematical problem. When a certain level of convergence is achieved, the vectorial representation for each word is obtained from the hidden layer in the neural network. The good results obtained by this method as well as their new operation possibilities make it an interesting way to explore.

One of the most cited example is related with word relationships. In [START_REF] Mikolov | Distributed representations of words and phrases and their compositionality[END_REF], it is shown that their model is capable of discovering semantic relationships such as "Queen is to Woman as King is to Man". Their results strongly support this idea. Note that, if a vectorial representation is available, the vector of each word could be used to verify this situation. In the mentioned example, the case is validated due to the fact that over the full vocabulary, vector queen Vqueen is the most similar vector to the resulting vector after a basic mathematical operation: V king -Vman + Vwoman. This method offers new ways to operate when comparison between words are needed. As far as we know, this paper is a first attempt to use these new kinds of representations in an intent mining experiment.

INTENT MINING USING CONTINUOUS VECTOR SPACE MODELS

In this work, we explore a continuous vector space models representation in the IMine Subtopic mining subtask. For that purpose, we utilize an existing vectors database of thousands of words built from a huge collection. This database is publicly available on the Web as well as the needed code to operate them 2 . An overall description of our algorithm is presented in Figure 1 and some of their intermediary phases are described below.

Mapping Subtopics to Vectors

In this phase, given a list of candidate subtopics we perform string matching to identify their vectorial representation for each subtopic. In that order, each string candidate is tokenized using a space as a separator and each token is searched in the vector database. If the token is found, then the vector is considered to represent the final string. When more than one token are found in the vector database the remaining vector is the sum along with their predecessors.

Intent Diversification with Vectors

The underlying idea consists in partial extractions of topics from the original query string. Using their respective vectorial representations, we first identify from a list of string candidates the most similar intent with respect to the query string. Note that this most similar candidate must cover the most reliable intent from the query. For the second intent, we subtract from the query the first intent and the most similar candidate to the difference is selected. Note that, the resulting vector from the subtraction expresses the remaining concepts not covered in the first intent and partially covered in the second intent. In an iterative process, the remaining intents are extracted using this subtraction strategy. Finally, the second level is built adding the most relevant string with respect to the first level.

Submitted runs

In order to evaluate our algorithm with different configurations, we submitted a total of four runs. The main differences are in the use of original candidate labels (S candidates ) or the modified version (S candidates ). Another parameter that could be explored is the assigning method for the second level. We experiment with soft assigning and hard assigning. In the instance of the soft assigning, a total of ten strings are assigned to the second level of all the intents in the first level. In the case of hard assigning, a string in the second level is assigned to a unique intent in the first level. Our runs are identified as:

• HULTECH-S-E-1A: uses the modified version for first level and soft subtopics assigning.

• HULTECH-S-E-2A: uses the modified version for first level and hard subtopics assigning.

• HULTECH-S-E-3A: uses the original version for first level and soft subtopics assigning.

• HULTECH-S-E-4A: uses the original version for first level and hard subtopics assigning.

RESULTS

The complete information of the IMine results can be found in [START_REF] Liu | Overview of the ntcir-11 imine task[END_REF]. For evaluation a set of metrics are used including: H-score, F -score, S-score and finally a combination of them called H-measure. Indeed, H-score measures the quality of the hierarchical structure and evaluates if there is concordance between the second-level and the first-level, F -score measures the quality of the first-level subtopic and S-score measures the quality of the second-level subtopic. Finally, H-measure is defined as:

H-measure = H-score × (α × F -score + β × S-score) (1)
where α + β is equal to one and both paraleters are fixed to 0.5. The top three performing runs (including all participants sorted by H-measure) and our other submissions are presented in Table 1. Note that, we get a higher performance in terms of F -score but it is not the same case when compared with the others participants in terms of H-score and S-score. A significant difference is clear between our best run (0.3596) and the top one (0.9190) in terms of H-score. This difference is not very relevant in terms of S-score.

Q a Web query string, S candidates the set of N strings candidates, K level1 the expected number of intents in level 1, K level2 the expected number of intents in level 2, D = {token1, ..., tokenm} a dictionary of tokens and V = {vector1, ..., vectorm} the set of vectors that correspond to D.

Step 1 : Initialization VQ.

The Q string is mapped to a vectorial representation. A tokenization process is applied (tokenization(Q) = {Qt1, ..., Qtq}), then each token Qti is searched over D and their respective vector from V is extracted. Final vectorial representation of Q correspond to the sum of all the extracted vectors (VQ).

Step 2 : Initialization V candidates . Each string from S candidates is mapped to a vectorial representation. A tokenization process is applied (tokenization(S j candidates ) = {S j t1 , ..., S j tq }), then each token S j ti is searched over D and their respective vector from V is extracted. Final vectorial representation of S j candidates correspond to the sum of all the extracted vectors (V j candidates ). If any of the tokens if not found in D, a new string is defined extracting the non-found tokens from the original string (S candidates ).

Step 3 : First level computation.

Define S level1 = ∅. For l : 1 to K level1 , do: Add to S level1 the associate S candidates string to V j candidates which is not included in S level1 that maximize:

Cosine(VQ -|V level1 | 1 V level1 , V j candidates ).
Step 4 : Second level computation.

For l : 1 to K level1 , do: Define S l level2 = ∅. For m : 1 to K level2 , do: Add to S l level2 the associate S candidates string to V j candidates which is not included in S l level2 that maximize: Cosine(V l level1 , V j candidates ).

Return :

Finally, first level are the strings in S level1 and second level are the associated strings in S level2 .

DISCUSSION

First, it is relevant to remark that our algorithm is constrained by the string candidates used as input. In our experiments, we have used only the query suggestions provided by the organizer. This string candidate set includes query suggestions from Bing, Google, Sogou, Yahoo! and Baidu. For many queries the number of candidates is around 20 and in some extreme cases the set of candidates only includes 16 strings3 . Unfortunately, our experiments were limited by these candidates, so that clearly explains our under performance in terms of H-score that penalize the inconsistent relations between the first and second level. In future work, we plan to include other string candidates to increase the number of intents in the second level when the hard assigning is used. In that case the performance is better than with soft assigning, but it is not as good when compared with the other participants. This situation is due to the low number of candidates. In many cases our second level submission includes less than the maximum of ten intents allowed for the task.

CONCLUSIONS

This paper presents a novel strategy for intent mining and diversification using continuous vector space models. Results show that our proposal outperforms others participants in terms of F -score and achieves the third position

2

  https://code.google.com/p/word2vec/ [Last access: 15/09/2014.].

Figure 1 :

 1 Figure 1: The Vectorial based Intent Mining algorithm.

Table 1 :

 1 Top three runs and our remaining submissions ordered by H-measure. In bold the best result (including others participants).

		Position H-score F -score S-score H-measure
	KUIDL-S-E-1A	1st	0.9190 0.5670	0.5964	0.5509
	THUSAM-S-E-1A	2nd	0.8065	0.5179	0.4835	0.4257
	HULTECH-S-E-2A 3rd	0.3596	0.7184 0.3977	0.1562
	HULTECH-S-E-4A 4th	0.3055	0.6496	0.3981	0.1384
	HULTECH-S-E-1A 10th	0.1703	0.7184	0.5754	0.0888
	HULTECH-S-E-3A 11th	0.1703	0.7184	0.5754	0.0888

Further information of the complete challenge and participants results could be found in[START_REF] Liu | Overview of the ntcir-11 imine task[END_REF].

This situation occurs with the query id 56. when compared in terms of H-measure. We propose the integration of more adequate string candidates for the mining task in order to improve the obtained performance in terms of S-score.