Jennifer Harris-Hellal

Michel Grimaldi

Evelyne Garnier-Zarli

Dr Noureddine Bousserrhine
email: bousserrhine@univ-paris12.fr

Iron oxide and mercury biogeochemistry in tropical soils

Keywords: mercury, iron oxides, chemical reduction, ferri-reducing bacteria, French Guyana

Iron oxy(hydr)oxides (oxides) are important mercury sinks in tropical oxisols and the geochemistry of these two elements are thus closely entwined. We hypothesized that bacterial Fe-oxide reduction in anoxic conditions could be a significant mechanism for mobilizing associated Hg. Iron oxide and mercury solubilisation in presence of two chemical reducers (ascorbate and dithionite, dissolving amorphous and amorphous plus well crystallized Feoxides, respectively) was compared to their solubilisation in presence of autochthonous ferrireducing bacteria. This work was carried out on two soil profiles from a small catchment basin in French Guyana, an oxisol (O) from a well drained slope and a water-saturated hydromorphic soil (H).

The chemical reductions showed that in the oxisol 20 and 48 % of total Hg (Hg T ) was associated to amorphous and well crystallized iron oxides, respectively. However, in the hydromorphic soil, no Hg seemed to be associated to amorphous iron oxides while the well crystallized fraction contained less than 9 % of Hg T . Chemical Fe-oxide reduction showed that Hg solubility was correlated to Fe reduction in the oxisol, demonstrating a relationship between the geochemistry of these two metals.

During bacterial growth, while bacterial iron reduction solubilised up to 3.2 mg Fe g -1 soil in the oxisol sample, Hg T remained unchanged. No mercury was detected in the culture medium either. However, chemical analysis showed a decrease of the amounts of Hg associated to amorphous and well crystallized Fe-oxides after 14 days of incubation, underlining the potential for iron-reducing bacteria to modify mercury distribution in soil.

Introduction

Amazonian soils have been accumulating atmospheric mercury (Hg) for several millions of years and register natural background levels of Hg up to ten times those found in temperate soils [START_REF] Carmouze | Le mercure en Amazonie, rôle de l'homme et de l'environnement, risques sanitaires[END_REF]. On top of that, human activities, and in particular gold mining, have contributed to raising the levels of Hg in these regions. Indeed, it has been estimated that around 5 000 tons of Hg have been dumped in the whole Amazonian area since the beginning of the gold rush towards the end of the 19 th century [START_REF] Nriagu | Mercury pollution from the past mining of gold and silver in the Americas[END_REF].

In pristine soils of the Amazonian basin, high mercury concentrations have been measured in Fe-oxide rich oxisols that contain little organic matter. Conversely, in hydromorphic soils that contain little Fe, lower Hg concentrations have been measured.

Several studies have identified relationships between Hg and Fe contents in soils [START_REF] Roulet | Geochemistry of mercury in pristine and flooded ferralitic soils of a tropical rain forest in French Guyana, south America[END_REF][START_REF] Roulet | The geochemistry of mercury in central Amazonian soils developed on the Alter-do-Chao formation of the lower Tapajos River Valley, Para state, Brazil[END_REF][START_REF] Roulet | Le mercure dans les sols d'Amazonie in Le mercure en Amazonie[END_REF] and it is now generally accepted that in organic-poor soils, such as oxisols, Fe-oxides play an important role in adsorbing Hg. Thus, the geochemistry of these two elements may be strongly linked. This explains the lower amounts of Hg measured in hydromorphic soils in which most of the iron has been reduced and exported, along with the mercury, via the aquifer.

The Hg adsorbed to Fe-oxides has little risk of being exported from the well drained oxisols, except via natural surface erosion and soil transformation. However, modern gold mining and deforestation expose soils to sunlight and rain and the excavation of the goldcontaining soils causes previously immobile mercury to encounter conditions that (i) favour its erosion and transport in watersheds [START_REF] Oliveira (de) | Soils as an Important Sink for Mercury in the Amazon[END_REF][START_REF] Lacerda | The effects of land use change on mercury distribution in soils of Alta Floresta, Southern Amazon[END_REF]Béliveau et al., 2009) and (ii) create disorganized hydromorphic areas where all the geochemical conditions necessary to favour methylation are brought together [START_REF] Guedron | Impact de l'exploitation minière en Guyane française sur les flux de mercure vers les écosystèmes aquatiques[END_REF]. Indeed, Hg methylation is generally considered to occur in anoxic soils and sediments [START_REF] Mehra | Iron oxide removal from soils and clays by a dithionite-citrate system buffered with sodium bicarbonate[END_REF], mainly by microbial methylation of inorganic Hg [START_REF] Gadd | Microbial formation and transformation of organometallic and organometalloid compounds[END_REF][START_REF] King | Mercury removal, methylmercury formation, and sulfate-reducing bacteria profiles in wetland mesocosms[END_REF]. Once methylated, methylmercury (MeHg) can be transported via the aquifer or by soil water runoff or erosion, to streams and rivers [START_REF] Mehra | Iron oxide removal from soils and clays by a dithionite-citrate system buffered with sodium bicarbonate[END_REF]Wasserman et al., 2003). Once in the water system, MeHg is readily accumulated along the food chain and can become an environmental and sanitary hazard as it can be consumed by local fish-eating populations [START_REF] Veiga | Mercury in the Amazon: A comprehensive Review with special Emphasis on Bioaccumulation and Bioindicators[END_REF].

Although geochemical conditions and erosion are a well recognized means of remobilizing Hg, little attention has been given to soil microbial communities, although their activity could play an important role in Hg distribution and speciation. Indeed, in natural environments, and in particular in the tropics, microbial Fe-reduction is a major factor in the mobilization of Fe [START_REF] Stemmler | Microbial activity as a major factor in the mobilization of iron in the humid tropics[END_REF]. Ferri-reducing bacteria reduce Fe in anoxic conditions by using it either as a major final electron accepter in anaerobic respiration or as a minor electron accepter during fermentation metabolism. During this process, it has been demonstrated that heavy metals adsorbed to iron oxides can be mobilized. (Addy et al., 1976;[START_REF] Schwertmann | Properties of iron oxides in some New Caledonian oxisols[END_REF][START_REF] Francis | Anaerobic Microbial Remobilization of Toxic Metals Coprecipitated with Iron Oxide[END_REF][START_REF] Lovley | Dissimilatory Metal Reduction[END_REF][START_REF] Trolard | Trace metals in natural iron oxides from laterites: A study using selective kinetic extraction[END_REF][START_REF] Bousserrhine | Bacterial and chemical reductive dissolution of Mn, Co, Cr and Al substituted goethites[END_REF][START_REF] Quantin | Oxide weathering and trace metal release by bacterial reduction in a New Caledonia Ferralsol[END_REF][START_REF] Quantin | Redistribution of Metals in a New Caledonia Ferralsol After Microbial Weathering[END_REF][START_REF] Cornell | The iron oxides[END_REF][START_REF] Garrido | Bio-geochemical mechanisms influencing the stability of As-bearing iron oxides[END_REF][START_REF] Bradl | Adsorption of heavy metal ions on soils and soils constituents[END_REF][START_REF] Neaman | Improved methods for selective dissolution of manganese oxides from soils and rocks[END_REF][START_REF] Noubactep | Release of coprecipitated uranium from iron oxides[END_REF][START_REF] Cooper | Interactions between Microbial Iron Reduction and Metal Geochemistry: Effect of Redox Cycling on Transition Metal Speciation in Iron Bearing Sediments[END_REF]. However, although bacterial Fe reduction is frequently mentioned as being an important factor of heavy metal mobilization, to our knowledge, there is no available data on the impact of this reductive dissolution on Hg mobility.

The aim of this study was to evaluate and compare the impact of chemical and microbial Fe-oxide reduction on the mobilization and distribution of associated Hg in tropical ferralitic soils. The chemical reducers used were ascorbate and dithionite that extract amorphous (Fe Asc ) and amorphous plus well crystallized (Fe CBD ) Fe-oxides, respectively.

Microbial reduction was carried out with autochthonous soil bacteria. The soils studied were an oxisol (O) and a hydromorphic soil (H) from a small catchment basin in French Guyana of which the downstream flats were gold-mined towards the end of the 19 th century and again in the middle of the 20 th century. Thus, high Hg concentrations could be found locally.

Material and methods

Sample collection

Soil samples were collected in December 2005 from the catchment basin of the Combat creek (1 km 2 ), situated at approximately 10 km from the village of Cacao in French Guyana (52°23'W, 4°35'N). Soil profiles up to 1 m deep were sampled with a metal auger, and each 10 cm layer was immediately sealed in sterile hermetic polyethylene bags. Two soil profiles were considered in this study: an oxisol (O) collected from a well drained slope and a hydromorphic soil (H) from the toeslope. These soils did not appear to have been directly affected by gold-mining as a logical continuity in vertical variations was observed; for example organic matter getting scarce with depth.

Soil preparation and characterization

The collected samples were air dried at 25°C, sieved at 2 mm and hermetically sealed at 4°C until use. Initial analyses were carried out on all samples by the National Institute of Agronomic Research (INRA, Arras, France). They consisted in the determination of 5 granulometric fractions without decarbonation (NF X 31-107), organic carbon (C) and total nitrogen (N) (NF ISO 10694 and NF ISO 13878), and total Fe (NF EN ISO 11885). Finally, pH was measured in water with a 1:2.5 ratio soil: solution (NF ISO 10390).

Chemical iron reduction

Chemical iron reduction was followed over time on homogenised samples of the 70-80 cm deep horizon of O and H using ascorbate and dithionite to reduce amorphous (Fe Asc ) and well crystallized Fe-oxides (Fe CBD ), respectively. These samples were chosen firstly because of their depth which induced low organic matter contents, thus increasing the possibilities of interactions between mercury and mineral elements, and secondly for their total iron and mercury contents which made them representative of their soil type (i.e. oxisol or hydromorphic soil). Amorphous Fe-oxides were extracted using a modified application of the ascorbate method as described by [START_REF] Ferdelman | The distribution of sulfur, iron, manganese, copper and uranium in a salt marsh sediment core as determined by a sequentiel extraction method[END_REF]. Briefly, 10 g of sodium citrate (Na 3 C 6 H 5 O 7 ) and 10 g of sodium bicarbonate (NaHCO 3 ) were added to 200 ml of ultra pure water that was deionised by bubbling with filtered nitrogen, before adding 4 g of ascorbic acid, for a final pH of 8. One gram of soil (dry weight, dw) was placed in a 30 ml polypropylene centrifugation tube (Nalgene, France) with 10 ml of reagent and agitated at room temperature. This temperature was chosen in order to avoid Hg volatilization.

Crystallized Fe-oxides were extracted using the Carbonate, Bicarbonate, Dithionite (CBD) method of [START_REF] Mehra | Iron oxide removal from soils and clays by a dithionite-citrate system buffered with sodium bicarbonate[END_REF], modified by [START_REF] Jeanroy | Differentiel dissolution of hematite and goetite and its implication on soil yellowing[END_REF]. Briefly, 0.2 g soil (dw) was placed in a centrifuge tube with 20 ml of reagent (78.4 g l -1 sodium citrate and 9.8 g l -1 sodium bicarbonate in ultra pure water) for a 1/100 soil weight/reagent ratio. Sodium dithionite was added at a ½ ration soil weight/dithionite (0.4 g tube -1 ), the tubes were agitated and incubated under agitation at room temperature.

During the ascorbate extraction, triplicate samples were harvested after 6, 12, 24, 48, 72 and 120 hours of extraction, and during the dithionite extraction, triplicate samples were harvested after 2, 4, 8, 12, 24, 48 and 96 hours of extraction. Samples were immediately centrifuged at 5000 x g for ten minutes at 4°C. The pellets were resuspended in 2 ml of ultra pure water, centrifuged a second time and both supernatants were pooled. The supernatant was then filtered (0.45 µm acid rinsed filtered, Minisart SRP 25, Sartorius) and acidified (pH 1) with HCl (37 %) to prevent metal precipitation and preserved at 4°C until analysis. The remaining soil pellet was air dried and crushed to < 100 µm and also conserved at 4°C until further analyses.

Chemical extracts were analyzed for Hg and Fe, as described below. Moreover, Fe Asc and Fe CBD were also extracted from the 50-60 and 90-100 cm deep horizons of soils O and H, with an extraction time of 72 h. This extraction time was chosen after the extraction kinetics demonstrated that the maximum amount of iron was extracted after 72 hours.

Microbial iron reduction

As chemical extractions showed (see results), significant quantities of Hg and Fe were leached only in the Fe-rich oxisol (O), thus, only this soil was investigated in bacterial iron reduction experiments. The three depths used correspond to different soil colours, described according to the Munsell Soil Colour Charts (2000). At 50-60 cm, the soil was dark yellowish brown (10YR4/6), at 70-80 cm it started evolving towards a heterogenic dark brown and red colour, and at 90-100 cm, it was clearly double phased with brownish-yellow and red volumes (5YR5/6 and 10R4/8). Microbial iron reduction was followed in soil microcosms set up in sterile hermetic 250 ml glass plasma bottles (BioBlock, France). Microcosms consisted in 5 g of each soil sample and 100 ml of modified Bromfield medium [START_REF] Bousserrhine | Etude de paramètres de la réduction bactérienne du fer et application à la déferrification de minéraux industriels[END_REF], of the following composition for one litre of MilliQ® water; MgSO 4 .7H 2 O (0.5 g); K 2 HPO 4 (0.5 g);

(NH 4 ) 2 SO 4 (1 g), yeast extract (0.15 g) and glucose (1 g). Each soil sample was prepared in triplicates. Anoxic conditions were initiated by flushing microcosms with N 2 for 10 min.

Incubations were carried out in the dark at 28°C for 14 days without shaking except prior to sampling.

During the incubation, several parameters were measured in the culture medium: carbon mineralization, glucose consumption, Fe(II) production and Hg solubilisation. At the end of the incubation, the microcosm medium was recovered and analyzed for Hg and Fe, and total Hg was measured in the soil. Moreover, the soil was subjected to Fe Asc and Fe CBD selective extractions as described previously.

Mercury analysis

Total Hg (Hg T ), in soils and in chemical extracts, was analyzed with an Automatic Mercury Analyzer (AMA 254, Courtage Analyses, France), detection limit 0.01 ng. Soil samples were crushed in an agate mortar to < 100 µm. About 100 mg were then placed in the AMA 254 and analyzed. In brief, the sample is heated to 550°C and all products of decomposition, including mercury, are carried by a stream of oxygen through a catalytic tube where Hg T is transformed into elementary mercury (Hg°) which then readily adsorbs to a gold-trap. The fixed mercury is then released by heating the gold-trap at 450°C and the mercury quantified by atomic adsorption spectrometry. Concentrations of standard reference materiel (MESS-3) did not exceed the range of concentrations announced (0.091 ± 0.008 µg g -1 ). Extraction supernatants were analyzed using the same method by analyzing 400 µl of each sample. All liquid samples were previously filtered (< 0.45 µm Teflon filters, Minisart SRP 25, Sartorius) and acidified to pH 1 (HCl, 37 % Suprapur).

Total dissolved Hg (Hg D ) in bacterial microcosm medium was analyzed by Cold Vapor Atomic Fluorescence Spectrophotometer (CVAFS), detection limit 17 pg, as described by [START_REF] Cossa | Dosage du mercure et du monomethylmercure dans les organismes et les sédiments marins, Méthodes d'analyse en milieu marin -Ifremer editions[END_REF]. All liquid samples were previously filtered (< 0.45 µm Teflon filters, Minisart SRP 25, Sartorius) and acidified to pH 1 (HCl, 37 % Suprapur). Briefly, the sample is mineralized with BrCl 2 , and reduced to elemental mercury (Hg°) with stannous chloride (SnCl 2 ). A bubbling system then causes the elemental mercury to be caught on a gold trap before being measured using a 2500 CVAFS Mercury detector (TEKRAN, Canada).

Concentrations of standard reference material (ORMS3) did not exceed the range of concentrations announced (12.6 ± 1.1 pg g -1 ).

Iron analysis

Chemical extracts and microcosm medium were analyzed after filtration (0.45 µm acidwashed membrane filter, Minisart SRP 25, Sartorius) and acidification at pH 1 with HCl (37 %) by ICP-AES (Vista MPX, Varian) for total Fe. Standards were prepared from an ICM 240 (Promochem, VWR) solution.

Reduced Fe (Fe II ), was also measured in the medium at regular intervals (after 1, 2, 3, 4, 9 and 14 days of incubation) using a colorimetrical method with orthophenanthrolinechlorydrate. Briefly 0.1 to 1 ml of filtered samples (0.45 µl acid rinsed filters, Minisart SRP 25, Sartorius) were put in a 25 ml graduated glass vial with 1 ml of orthophenanthroline (0.5 %) and completed to 25 ml with MilliQ water. After 10 min the absorbance was read at 490 nm. Readings were compared to a standard curve established with dissolved anhydrous ferrous sulphate (Fe(NH 4 ) 2 (SO 4 ) 2 .6H 2 O).

Bacterial metabolism

During the incubations, carbon mineralization was followed by measuring CO 2 evolution daily in the microcosm's atmosphere with an infrared spectrophotometer (Berly 100, Cosma).

Glucose concentration in microcosms was measured daily in samples of microcosm medium with a D-Glucose enzymatic test (Boehringer Mannheim, France). Samples were filtered (0.45 µm, Minisart, Sartorius) prior to analysis.

Sulphate reduction was followed by measuring sulphide (S 2-) formation in the culture medium. This was carried out using a kit (Spectroquant, Merck), analogue to NF ISO 10530. This kit measures sulphide concentrations in a range of 0.02 to 1.5 mg S 2-l -1 . Samples were filtered (0.45 µm, Minisart, Sartorius) prior to analysis.

Finally, redox potential and pH were measured in microcosms at the beginning and the end of the incubation with Eh/pH electrodes (Metrohm, France).

Statistical analysis

Homogeneity of variances was checked using a Bartlett's test and normality using a Shapiro-Wilk's test. When variances were not homogeneous between replicates, real standard deviations (SD) were presented in the figures; otherwise, the overall SD was calculated and displayed as the interval associated to each sample mean. Our data (CO 2 and iron solubilisation) did not follow a normal distribution (P-value < 0.05), thus, a Friedman non parametrical test for paired data was run for each soil depth to identify the effect of time on data distribution, and a Kruskal-Wallis non parametrical test and a multicomparaison test were run to identify differences between soil depths. The results for CO 2 and Fe solubilisation identified an effect of time (i.e. increase during the experiment) and no differences between soil depths (P Fe = 0.643 and P CO2 = 0.617).

Regression analyses were carried out between Hg and Fe solubilised during the chemical Fe extractions and between CO 2 evolution and Fe solubilisation in the microcosms.

The R² and P-value are given in the corresponding paragraphs and significant correlations are presented graphically.

Student t tests were run on the molar ratios calculated between Fe and Hg, in the iron oxide CBD and ascorbate extractions, at the beginning and the end of microcosm incubations (Fig. 6), to determine whether differences were significant.

Extraction and incubation quality assurance and control (QA/QC)

To avoid contamination, all materials used in this work were acid-washed twice with HNO 3 (5 %), then rinsed several times with Milli-Q® water before use.

The extraction reagents (ascorbate and CBD) were prepared in Milli-Q® water and analysed for Hg contents as blanks. On average we measured 0.089 ng Hg g -1 ± 0.003 in the ascorbate and 0.223 ng Hg g -1 ± 0.007 in the dithionite. These values are very low compared to the amounts measured in the samples.

Blank microcosms containing sterile Bromfield medium were incubated in the same conditions as the soil containing ones and analysed for CO 2 evolution, Fe(II), Fe T and Hg T .

Whereas these tests were negative for CO 2 and Fe, we measured 0.87 ± 0.3 pg Hg l -1 medium.

Results

Soil characteristics

Table 1 presents soil texture and organic carbon contents in three depths of each soil profile.

The oxisol (O) was very rich in clay, up to 75 % with quantities of fine silt and coarse sand ranging from 5 to 15 %. The texture triangle defines this soil as clay. The hydromorphic soil (H) was not as rich in clay (< 35 %), its dominant component being silt (~ 45 %), followed by sand (up to 40 %). The texture triangle describes this soil as a fine clay-loam soil. Organic carbon contents were low and decreased with depth in both soils.

Fe T and Hg T soil contents were very different in O and H (Table 2). Quantities of Fe T were up to 10 times higher in O compared to H and ranged from 198.1 mg Fe g -1 soil in the 50-60 cm horizon, to 290.6 mg Fe g -1 soil in the 90-100 cm horizon. In H, the maximum Fe T was found at 70-80 cm: 20.7 mg g -1 soil, it was of 13.4 and 8.4 mg Fe g -1 soil in the 50-60 and the 90-100 cm horizons, respectively. Hg T decreased slightly with depth in O, from 294.1 ng Hg g -1 soil in the 50-60 cm horizon, to 248.7 ng Hg g -1 soil in the 90-100 cm one. In H, Hg T was on average 134 ng Hg g -1 soil in the first two horizons and then increased to 338.6 ng Hg g -1 soil in the 90-100 cm one.

Insert Table 1

The selective extractions carried out before kinetic reductions (Table 2) showed a good repeatability. In O, the percentage of Fe Asc /Fe T decreased with depth from 6.9 to 1.7 %, as did the percentage Hg Asc /Hg T (19.8 to 8.5). Also in O, CBD extracted up to 77.3 % of Fe T , and 48 % of Hg T . Although significant quantities of Hg were leached with Fe Asc and Fe CBD extractions, no significant correlation was observed between the two elements.

In H, the ascorbate extraction yielded up to 14 % of Fe T , however, Hg Asc was not detectable (nd) by AMA 254 in the extractant (Table 2). The CBD extracted 100 % of Fe T in the 90-100 cm horizon and up to 9 % of Hg T in the 70-80 cm horizon. No significant correlations were observed between Fe and Hg in H.

Insert Table 2

Kinetics of chemical iron oxide reduction

The kinetics of chemical Fe-oxide reduction by ascorbate and CBD are presented in Fig. 1. The citrate in CBD acts as a complexant and prevents Al, Fe or other metals from precipitating. In O, Hg and Fe were leached simultaneously over time with both ascorbate and CBD. During ascorbate extraction, the maximum of Hg Asc and Fe Asc were leached after 48 hours, while during CBD extraction, Hg CBD was leached faster (12 h) than Fe CBD (48 h). In H, on the contrary, no Hg Asc was detected along with Fe Asc , but Hg CBD appeared to be leached simultaneously to Fe CBD in this soil, although values were a lot smaller than in O.

Insert Fig. 1

Regression analyses were run between Hg and Fe leached during Fe chemical extractions when possible. Results demonstrate a clear correlation (R² = 0.84, P = 0.003) between Fe and Hg extracted with dithionite and a less significant correlation (R² = 0.51, P = 0.070) for ascorbate (Fig. 2). In H on the other hand, the relation between Fe and Hg for dithionite gave a R² = 0.21 and could not be calculated for ascorbate as Hg was not detectable.

Insert Fig. 2

Microbial iron oxide reduction

Carbon mineralization (Fig. 3) increased considerably during the first 4 days of incubation in all three horizons (Friedman test, P < 0.001), before slowing down. The amount of C mineralized at the end of the experiments was 5.1 ± 0.3 mg g -1 soil on average and no significant differences were given between soil depths (Kruskal Wallis test, P = 0.617).

Glucose was totally consumed after four days (Fig. 3). The amount of carbon that evolved in the form of CO 2 in the microcosm atmosphere represented 72 % of the carbon provided by the glucose.

Insert Fig. 3 The redox potential (Eh), decreased rapidly (data not shown) and the Eh measured at the end of the incubations was -190 ± 47 mV on average in all microcosms. The pH increased during incubations in all three soils from 4.7 ± 0.25 to 5.3 ± 0.25.

The formation of sulphides was detected from day 8 onwards, and at the end of the incubation we measured on average 80 µg S 2-g -1 soil in the microcosm medium (data not shown).

Insert Fig. 4

During the incubation, total dissolved Fe (Fe D ) increased in the microcosm medium (Fig. 4). Slightly more Fe was solubilised in the 90-100 cm horizon; 3.5 mg Fe g -1 soil, compared to the 50-60 and 70-80 cm horizons; 3 mg Fe g -1 soil at the end of the incubation but overall differences were not significant (Kruskal-Wallis test, P = 0.643). These solubilised quantities represent 2.1; 1.5; and 1.8 % of Fe CBD or 21, 42 and 70 % of Fe Asc in the 50-60, 70-80 and 90-100 cm horizons respectively. A colorimetric test with Orthophenantroline analysis indicated that all of this Fe was in the form of Fe II (data not shown), confirming that Fe solubilisation was due to bacterial reduction. Moreover, a significant polynomial correlation was calculated between Fe solubilisation in the inoculation medium and CO 2 evolution (Fig. 5).

Insert Fig. 5

According to the chemical reduction of iron, the solubilisation of 2.1, 1.5 and 1.8 % of Fe CBD should have led to the solubilisation of at least 2.4, 1.6 and 1.3 ng Hg g -1 soil, and the solubilisation of 21, 42 and 70 % of Fe Asc to the solubilisation of 12.8, 14.6 and 15.1 ng Hg g -1 soil in the 50-60, 70-80 and 90-100 cm horizons, respectively. However, dissolved Hg (Hg D ) was very low and constant throughout the experiment, averaging 8.6 ± 2.3 ng g -1 soil, as was the total mercury in the solid phase.

The amount of Hg (nmol) extracted per µmol Fe in the ascorbate and CBD fractions before and after the incubation is presented in Fig. 6. Results showed that Hg was much more concentrated in the amorphous fraction (up to 14 nmol Hg µmol -1 Fe) than in the CBD fraction (< 0.25 nmol Hg µmol -1 Fe). After the incubation, these ratios had significantly decreased (Student t tests) in the 50-60 and 70-80 cm horizons for the ascorbate extractions (P < 0.05) but not in the 90-100 cm horizon (P = 0.077). They had also significantly decreased in all the horizons in the CBD extraction (P < 0.05).

Insert Fig 6 Discussion

The aim of this study was to compare chemical and microbial reduction of iron oxides in tropical ferrallitic soils of French Guyana, and to evaluate its impact on mercury release. It is a well accepted fact that Fe-oxides are sinks for various major and trace metals including Al, Mn, Cr, Ni, Cd, Zn, Co, Pb and U, and that bacterial Fe-reduction contributes to re-mobilizing these metals [START_REF] Schwertmann | Solubility and dissolution of iron oxides[END_REF][START_REF] Bousserrhine | Effect of aluminium substitution on ferri-reducing bacterial activity and dissolution of goethites[END_REF][START_REF] Bousserrhine | Bacterial and chemical reductive dissolution of Mn, Co, Cr and Al substituted goethites[END_REF][START_REF] Quantin | Oxide weathering and trace metal release by bacterial reduction in a New Caledonia Ferralsol[END_REF][START_REF] Dominik | Limitations to the reductive dissolution of Al-substituted goethites by Clostridium butyricum[END_REF][START_REF] Quantin | Redistribution of Metals in a New Caledonia Ferralsol After Microbial Weathering[END_REF][START_REF] Stemmler | Microbial activity as a major factor in the mobilization of iron in the humid tropics[END_REF][START_REF] Cooper | Effects of sediment iron mineral composition on microbially mediated changes in divalent metal speciation: Importance of ferrihydrite[END_REF][START_REF] Noubactep | Release of coprecipitated uranium from iron oxides[END_REF][START_REF] Cooper | Interactions between Microbial Iron Reduction and Metal Geochemistry: Effect of Redox Cycling on Transition Metal Speciation in Iron Bearing Sediments[END_REF]. It is also more and more accepted that Fe-oxides play an important role in the geochemistry of Hg, especially in iron-rich tropical soils [START_REF] Roulet | Geochemistry of mercury in pristine and flooded ferralitic soils of a tropical rain forest in French Guyana, south America[END_REF][START_REF] Roulet | The geochemistry of mercury in central Amazonian soils developed on the Alter-do-Chao formation of the lower Tapajos River Valley, Para state, Brazil[END_REF][START_REF] Grimaldi | Sources, stocks et transferts dans les sols et sédiments[END_REF].

However, although re-mobilization of Hg by Fe-oxide reduction has often been suggested, to our knowledge, there is no data that demonstrates it.

A kinetic approach of the reduction of Fe-oxides by chemical and microbial processes was used to determine the potential solubilisation of Fe and Hg in tropical ferrallitic soils of French Guyana. The results enabled us to estimate the amounts of Hg associated to amorphous and well crystallized Fe-oxides, which can potentially be mobilized in anaerobic conditions by ferri-reducing bacteria.

Soil characteristics and Fe and Hg distribution

Both soils under study, O and H, were very different from a textural point of view and concerning Fe T and Hg T contents. O is an oxisol, containing a lot of clay and iron oxides, as reported for these types of soils [START_REF] Boulet | Géochimie des paysages : le rôle des couvertures pédologiques[END_REF], whereas the hydromorphic soil contained little clay and Fe, but more sand and silt, due to soil transformations in anoxic conditions and the export of fine particles [START_REF] Boulet | Géochimie des paysages : le rôle des couvertures pédologiques[END_REF][START_REF] Tessier | Mercury mobilization in soil from a rainfall event in a Tropical forest (French Guyana)[END_REF]. The Hg concentrations measured in the oxisol were in the range of concentrations previously reported in French Guyana; 240-320 ng g -1 soil [START_REF] Roulet | Geochemistry of mercury in pristine and flooded ferralitic soils of a tropical rain forest in French Guyana, south America[END_REF]. In pristine hydromorphic soils, these authors measured Hg contents in a range of 50-100 ng g -1 soil which is lower than those measured in the present study (133-338 ng g -1 soil). This suggests that although soil horizons were not apparently disturbed, past gold-mining had contaminated these soils. Indeed, [START_REF] Guedron | Impact de l'exploitation minière en Guyane française sur les flux de mercure vers les écosystèmes aquatiques[END_REF] found droplets of metallic Hg in hydromorphic soils from the same catchment basin as in this study that most probably came from past gold-mining.

In the oxisol, O, the maximum Fe CBD yielded by selective extractions was 77 % of Fe T .

The remaining iron is most probably resistant goethite or hard Fe nodules [START_REF] Trolard | Trace metals in natural iron oxides from laterites: A study using selective kinetic extraction[END_REF]. Fe Asc represented less than 7 % of Fe T in all the studied depths of the O soil profiles, and decreased with depth, indicating an increase in iron crystallinity [START_REF] Fritsch | Transformation of haematite and Al-poor goethite to Al-rich goethite and associated yellowing in a ferralitic clay soil profile of the middle Amazon Basin (Manaus,Brazil)[END_REF].

In the hydromorphic soil, H, on the contrary, up to 100 % of Fe T was extracted with CBD, but not systematically. The presence of hard nodules in the soil profile indicates that free iron has re-precipitated, probably during the dry seasons when soils are partially oxygenated. Fe Asc was slightly higher than in O (up to 14 %), and no relations were observed with depth. In this blue-grey coloured soil, nearly all the iron oxides have been reduced and exported, leaving only hard iron concretions.

Hg was only significantly leached during selective extractions of iron forms in O, where Hg CBD and Hg Asc represented up to 48 and 19 % of Hg T , respectively. However, there wasn't a significant correlation between Fe Asc , Fe CBD and Hg T . Although they didn't measure Hg CBD , [START_REF] Roulet | Geochemistry of mercury in pristine and flooded ferralitic soils of a tropical rain forest in French Guyana, south America[END_REF] did not observe any correlations between Fe CBD and Hg T in soils of French Guyana, either. These authors concluded that although Fe-oxides play an important role in Hg absorption, they do not solely control Hg retention in these soils.

Hg was significantly associated to iron oxides in the oxisol

Iron oxide dissolution is controlled by crystallinity and surface area [START_REF] Trolard | Trace metals in natural iron oxides from laterites: A study using selective kinetic extraction[END_REF][START_REF] Cornell | The iron oxides[END_REF]. Moreover, several studies have demonstrated that high Al substitution in Fe-oxides decreases their solubility [START_REF] Rajot | Dissolution des oxydes de fer (hématite et goethite) d'un sol ferrallitique des Llanos de Colombie par des bactéries ferri-réductrices[END_REF][START_REF] Bousserrhine | Effect of aluminium substitution on ferri-reducing bacterial activity and dissolution of goethites[END_REF][START_REF] Bousserrhine | Bacterial and chemical reductive dissolution of Mn, Co, Cr and Al substituted goethites[END_REF]. During the chemical Fe-oxide reduction, Fe was continuously dissolved to a maximum as observed by other authors [START_REF] Bousserrhine | Etude de paramètres de la réduction bactérienne du fer et application à la déferrification de minéraux industriels[END_REF][START_REF] Trolard | Trace metals in natural iron oxides from laterites: A study using selective kinetic extraction[END_REF]. Our results did not enable us to distinguish different iron oxides by variations in the rates of dissolution as the dissolution curves were smooth; this has also been pointed out by [START_REF] Trolard | Trace metals in natural iron oxides from laterites: A study using selective kinetic extraction[END_REF]. The curves of Hg release, during chemical Fe-oxide reduction, were similar to Fe release, especially in the CBD fraction of the oxisol. Although no significant correlation was previously calculated between Hg T and Fe CBD , the regression analysis carried out between Hg CBD and Fe CBD demonstrated a clear relationship between the two metal fractions (R²=0.84).

In the hydromorphic soil, H, little Fe or Hg was solubilised in the CBD or the ascorbate fraction and no significant relationships could be established between the two metals. However, total mercury concentrations in this soil went up to 338 ng g -1 soil in the deepest sample (90-100 cm), which suggests that there could be other important mercury adsorbing phases, other than iron oxides and organic matter.

In the oxisol, O, the percentages of Hg T in the extraction fractions were higher for CBD than for ascorbate, although the ratio nmol Hg / µmol Fe was much higher in the amorphous Fe-oxide fraction, thus suggesting that it is only the small amount of amorphous Fe-oxides that limits their Hg adsorption. Indeed amorphous Fe-oxides have the largest surface areas and are reputed to be more efficient adsorbents for trace elements than well crystallized oxides [START_REF] Cornell | The iron oxides[END_REF].

Bacterial iron reduction was related to carbon mineralisation

Due to the first results obtained with the chemical Fe-oxide reduction, bacterial Fereduction was only carried out in soils from the oxisol profile. The three horizons studied (50-60, 70-80 and 90-100 cm) were chosen because of the variations in colour, and thus theoretically their different contents in Fe-oxide types, e.g. goethite and hematite. These depths also differed in their carbon contents which could influence microbial density and activity. Thus, we tried to cover the vertical differentiation of our soil profile.

Although soil characteristics varied with depth, this did not interfere on carbon mineralisation, induced by the addition of glucose, or iron solubilisation as they were no significant differences between horizons (P Fe = 0.643 and P CO2 = 0.617). Eh decreased rapidly in all microcosms and all of the dissolved Fe was ferrous Fe (Fe II ) indicating that Fe was dissolved by a reduction process. The correlation between Fe solubilisation and carbon mineralization indicated that reduction was biologically mediated [START_REF] Lovley | Organic Matter Mineralization with Reduction of Ferric Iron in Anaerobic Sediments[END_REF][START_REF] Bousserrhine | Bacterial and chemical reductive dissolution of Mn, Co, Cr and Al substituted goethites[END_REF]. All of the glucose was consumed after 3 days incubation and up to 72 % of the provided carbon was transformed into CO 2 . This also corresponded to a decrease in soil respiration and Fe II production, thus suggesting that in the present study, available carbon was the limiting factor, in which case we have possibly underestimated the potential bacterial Fe-oxide reduction in these soils. Another limiting factor could be the accessibility of reducible iron as suggested by [START_REF] Stemmler | Microbial activity as a major factor in the mobilization of iron in the humid tropics[END_REF]. Indeed, while in the case of chemical CBD extractions, a citrate buffer prevented metal precipitation in the solution, in natural conditions, however, soluble aluminium and iron can re-precipitate on the surfaces of iron oxides and prevent their reduction by bacteria [START_REF] Dominik | Limitations to the reductive dissolution of Al-substituted goethites by Clostridium butyricum[END_REF].

Bacterial iron reduction influenced Hg distribution in soils

According to the chemical extractions, the bacterial reduction of 3 mg g -1 soil in the 50-60 and 70-80 cm horizons and of 3.5 mg g -1 in the 90-100 cm horizon could have led to the solubilisation of 2.4, 1.6 and 1.3 ng Hg g -1 soil if we consider the CBD fraction (amorphous plus well crystallised oxides) or to the solubilisation of 12.8, 14.6 and 15.1 ng Hg g -1 soil if we just consider the amorphous fraction. However, although we have observed the solubilisation of other trace metals such as Ni and Cr (unpublished data), in the present experiment we did not measure an increase of Hg D in the microcosm medium, or a decrease of Hg T in the solid phase.

Nevertheless, when selective extractions were performed on the soil samples after microbial incubations, the amounts of mercury associated to Fe Asc and Fe CBD had decreased significantly, even more than the theoretical amounts that should have been mobilized by iron reduction (in comparison to chemical reduction). This Hg could then have re-precipitated on metabolites or formed organo-mercurial complexes, or more likely, due to the presence of sulphates in Bromfield medium, and their reduction to sulphides towards the end of the incubation, Hg could have re-precipitated in the form of HgS. Indeed, for [S 2-] > 1.8 mg g -1 soil; all dissolved Hg forms HgS. However, in laboratory conditions, bacterial iron reduction carried out on pure goethite have shown that 100 % of Fe CBD can be reduced by ferri-reducing bacteria [START_REF] Bousserrhine | Bacterial and chemical reductive dissolution of Mn, Co, Cr and Al substituted goethites[END_REF]. If this were the case in the oxisol used in this study then in the right conditions and with a sufficient source of carbon, we can imagine that kilograms of mercury could rapidly be remobilized in the watersheds.

Conclusion

Our results demonstrate that a significant amount of Hg is adsorbed to Fe-oxides in the Ferich oxisol used in this study. During the chemical reduction of iron oxides, mercury was significantly leached from the soils, whereas mercury solubilisation was not detected during the microbially-mediated iron reduction. However, during the later, the distribution of Hg on amorphous and well crystallized iron oxides was modified. Further work would enable to (i) assess the dynamics of Hg associated to Fe oxides in soils, in relation to soil pedogenesis and water table fluctuations (ii) estimate the amounts of Fe and Hg that can be mobilized by bacteria in natural conditions, i.e. without glucose or Bromfield medium, and (iii) identify the micro-organisms present in the soils, and their potential to transform the available Hg. Hg mobility in cultivated tropical soils one year after slash-and-burn of the primary

  Addy, S. K., Presley, B. J. and Ewing, M. (1976) Distribution of manganese, iron and other trace elements in a core from the Northwest Atlantic. Journal of Sedimentary Research 46(4): 813-818. Béliveau, A., Lucotte, M., Davidson, R., do Canto Lopes, L. O. and Paquet, S. (2009) Early

 Wasserman, J. C., Hacon, S. and Wasserman, M. A. (2003)Biogeochemistry of Mercury in the Amazonian Environment. Ambio 32(5): 336-342.


Marilena Oita
email: marilena.oita@telecom-paristech.fr

Pierre Senellart
email: pierre.senellart@telecom-paristech.fr

Archiving Data Objects using Web Feeds *

Keywords: Algorithms, Experimentation Web archiving, data object, Web feed, Web page dynamics

Web feeds, either in RSS or Atom XML-based formats, are evolving descriptive documents that characterize a dynamic hub of a Web site and help subscribers keep up with what is the most recent Web content of interest. In this paper, we show how Web feeds can be useful instruments for information extraction and Web page change detection. Web pages referenced by feed items are usually blog posts or news articles, data with a dynamic (then ephemeral) nature and which is clustered topically in a feed channel. We monitor Web channels and extract from the associated Web pages the text and references corresponding to Web articles. The result is enriched with the timestamp and additional metadata mined from the feed, and encapsulated in a 'data object'. The data object will be in particular information devoided of all the template elements or advertisements. These irrelevant elements, generically called boileplate, are not only consuming time and space from the crawler's point of view, but also hinder the data analysis process. We first make some statistics on a set of Web feeds, by crawling them for a period of time and observing their temporal aspects. Then we present the algorithm used for article extraction, algorithm that uses the feed semantics (more specifically the description and title of feed items) in order to identify the DOM node in the HTML page that contains the article. The data objects constructed in this way can be used as a semantic overlay collection for an archive or in the context of an incremental crawl, making it more efficient by detecting change at data object level. Experiments on the extraction technique are done in order to validate our approach, with good results even in cases when other techniques fail. We finally discuss useful applications based on the extraction and change detection of Web objects.

INTRODUCTION

Web archiving [START_REF] Masanès | Web Archiving[END_REF] is the process of repeatedly collecting the content of parts of the World Wide Web, to ensure its preservation and to allow access to information even after it disappears from the Web. A Web archiving crawler follows the same basic steps as a search engine crawler does to construct indexes for Web pages. However, an archive crawler does not drop indexes to old versions when new ones are discovered, but instead stores and references versions in time. The final result is a collection of Web pages that can be browsed off-line and, in ideal settings, can as well be temporally and semantically queried.

Performing a coherent crawl of sites that are updating their supply of information very rapidly it is not an easy task. The common choice of crawling in snapshots, i.e., crawling the entire collection at distant (but frequent enough) intervals of time, can be quite expensive in terms of network bandwidth, and in the end, both redundant for some zones of the site, and incomplete for other zones that are more dynamic. Additionally, as running an integral crawl takes time and in the meanwhile the resource might change, it raises issues of temporal incoherence of a given snapshot [START_REF] Spaniol | Catch me if you can. Temporal coherence of Web archives[END_REF].

What 'frequent enough' means is also to be clarified when one decides to perform an incremental crawl instead, which is better adapted to sites that have temporally heterogeneous parts in their structure. An incremental crawler will crawl once a full version of the site and, from that point, supposing the existence of a trigger that informs the crawler which content of a site has been added or updated, it will crawl only the modified content and store it as a delta data structure. The difficulty of performing an incremental crawl is essentially to determine this dynamics (how often new Web pages are added or current ones are modified), and to make this change detection effective, knowing that there are a lot of factors that can negatively influence the detection process.

Our contribution is related to techniques that can be used to improve this detection process, in the particular case where the Web pages that need to be crawled have RSS or Atom feeds attached.

The traditional way of detecting changes between two successive versions of a Web page is to perform a comparison on content, using a similarity metrics, varying from hashing and content signatures to edit distances for flexibility. Whatever the way the change is detected, the importance of this change (regarding the types of content of a Web page) is not evaluated. Nevertheless, it is crucial to understand whether changes are relevant to the main content of the page from a semantic point of view, since, in some applications, changes that only impact boilerplate [START_REF] Kholschutter | Boilerplate detection using shallow text features[END_REF] parts of the page, such as menus, presentation templates, or advertisements, might be safely ignored.

Web feeds have been poorly studied, yet are a rapidly evolving phenomenon. We draw attention to the fact that they can be used as instruments in the analysis of a Web site before and during the crawl. In addition to being a way to advertise content, Web feeds are also used to classify sources of information and their types of content by search engines. In a nutshell, from Web feeds important aspects of a dynamic website can be extracted and exploited in the context of a Web crawl in order to make it more aware of the information it treats.

The nature of a feed is: informative: it synthesizes what and when fresh information is published by a channel;

descriptive: it describes what kind of new resources are added, with the title, description, and other possible tag elements.

We aim at extracting, with the help of feeds, structured data from Web pages. The basic intuition behind our approach is that an item of a channel matches a data object in a Web page. Therefore, the metadata that we can get about the item in the feed can be used to recognize and extract the data object in the Web page.

The notion of data object has different interpretations in computer science; in order to clarify its signification, in our context a data object is an instance of a resource referenced by a feed, and which has some special metadata associated, similarly to [START_REF] Knight | Data without meaning: Establishing the significant properties of digital research[END_REF] and [START_REF] De Sompel | Resource harvesting within the oai-pmh framework[END_REF]. The concept itself of data object it is a compound one, and from this point of view, can be explained as a 'logical document'(we would say semantic), in contrast with a 'hypertext document'(HTML page) [START_REF] Dmitriev | As we may perveive: Inferring logical documents from hypertext[END_REF].

Even if the object is often a Web article, it can also be a dictionary entry, a comment, a forum message, a video, a status, and any other kind of resources that are uniquely associated with Web feed items. Direct approaches to identifying the main content of a Web page, such as taking the elements that contain the largest amount of information from the HTML code after cleaning (baseline), studying the density of the text in specific regions of the page [START_REF] Kholschutter | Boilerplate detection using shallow text features[END_REF], or even identifying the most prominent visual areas of the page [START_REF] Yu | Improving pseudo-relevance feedback in web information retrieval using web page segmentation[END_REF], are becoming obsolete as the manner of encoding becomes more complex and the notion itself of Web article evolves. Data objects can correspond to small portions of a Web page, can be simple or compound, can contain multimedia and even good JavaScript that should be exploited. Depending on the context, we can have one or multiple data objects per page and the difference between them can be done either by using machine-readable semantics, or using human heuristics.

We leverage the semantics that is brought by Web feeds to dynamic Web pages. Written in a XML-like form, with standard elements, feeds can be used to capture some important aspects of the information that we want to extract. We get from the structure of a feed item, using classical information retrieval techniques, a semantic descriptor of the object that will be used as an input for the extraction algorithm. Next, we identify the zone in a Web page that contains the content of the data object and extract it by means of semantic density analysis. Having extracted the content in time and an important part of its properties, complex queries can be run, from the temporal and semantic point of view.

We present in the next section some related work, and describe in Section 3 the results of our studies on Web feeds done in order to determine the value of these feeds in the Web archiving process. We explain in Section 4 how the semantics revealed by specific elements in a feed can be used to extract data objects. In Section 5, experiments relative to the extraction of data objects are shown. We conclude by outlining the importance of extracted data objects in the context of applications.

RELATED WORK

Web archiving, seen as a necessity or duty, is acquiring a lot of importance lately due to the volatile nature of the Web, and more specifically due to the value that the lost information could have for future generations. Internet Archive [11] is one of the initiators of the Web archive movement. There exist many other actors that actively run crawls as part of their heritage preservation mission, and efforts are done to converge into a unified, global Web archive collection [START_REF] Van De Sompel | Extracting structured data from Web pages[END_REF]. Though Web feeds are typically indexed as other kinds of Web documents by archive crawlers, limited effort has been made on exploiting their specificity in the archiving process. ArchivePress, a blog-archiving project [START_REF] Pennock | ArchivePress: A really simple solution to archiving blog content[END_REF] has been developing a Wordpress plugin that archives posts using Web feeds. The principal drawback is that only the content that can be delivered by the RSS feed is captured. In effect, an RSS feed can have a full coverage of the article and its media files, but this case is quite rare because a feed is often just a way of advertising content. In contrast, we harness the feed clues with the goal to extract the actual information associated. Additionally, we do not limit ourselves to a blogging platform, or blogging in particular.

When studying the dynamics of Web pages, there are two perspectives: the change can come from the publishing of new content or from the modifications that occur in the existing pages. To avoid excessive overload on servers of Web sites that provide timely content, [START_REF] Sia | Efficient monitoring algorithm for fast news alerts[END_REF] proposes an adaptative aggregator approach. An inhomogeneous Poisson model on Web feeds is used in order to learn the posting patterns in blogs and predict the optimal recheck for new content. In the context of an incremental crawl, we have the same problem; our statistics on the temporal aspects of feeds are done with the aim of stating their value in the process of learning the publishing strategy. In order to model the behavior of Web sites over time and crawl them more efficiently, other studies have been focusing on the understanding of the dynamics of Web pages [START_REF] Fetterly | A large-scale study of the evolution of web pages[END_REF][START_REF] Adar | The web changes everything: Understanding the dynamics of web content[END_REF][START_REF] Ntoulas | What's new on the web? the evolution of the web from a search engine perspective[END_REF]: how fast the Web content changes and what is the nature of these changes, the implications on the structure and the correlation with the topic of pages.

There are tentatives to automatically adapt the crawl to the predicted rate of change: [START_REF] Ii | Application of kalman filters to identify unexpected change in blogs[END_REF] uses a textual vector space model to identify the patterns of the page and to train Kalman filters. In the end, the change is the event that does not match the prediction. However, the hypothesis on the system linearity and the incompleteness of the vector space model represent possible drawbacks. To detect and store only the modified content of a Web page, the open-source Heritrix archive crawler [START_REF] Sigurðsson | Incremental crawling with Heritrix[END_REF] uses heuristics and regular expressions to filter irrelevant changes. In the attempt to fairly estimate the Web page change rate, a more formal model of prediction is studied by Cho and Garcia-Molina in [START_REF] Cho | The evolution of the Web and implications for an incremental crawler[END_REF], where the authors study whether changes of a Web page follow a (homogeneous) Poisson process. However, accurately identifying the change rate is stated by both approaches as a challenge. We motivate the extraction of data objects within this issue. Once the acquisition of data objects is done in a timely manner, a measure of similarity can be applied on the contents or on the properties of data objects. Supposing they have acquired two successive versions of a Web page by using some technique for detecting change, Pehlivan, Ben Saad, and Gançarski [START_REF] Pehlivan | A novel Web archiving approach based on visual pages analysis[END_REF] focus on detecting the changes that have occurred in the new version, based on the old one. For that purpose, the VIPS [START_REF] Yu | Improving pseudo-relevance feedback in web information retrieval using web page segmentation[END_REF] algorithm is used to identify semantically related parts of a Web page, which are compared in order to detect structural and content changes. Heuristics on the visual appearance of a Web page are made to group together content that seems to have similar importance in the page. These heuristics do not exhaustively cover the problem, and the algorithm is computationally expensive. Our approach is more restrictive, as we need to pass through the feed; in the same time, it can be more effective: by identifying only "important" semantic zones in the Web page, we can focus our attention on changes that are relevant, with less effort.

A Web article identified using the feed item's title and description has to be extracted from the HTML code of the associated Web page. Much work has been done on unsupervised extraction of structured data from Web pages; many of these are based on MDR [START_REF] Liu | Mining data records in Web pages[END_REF], ExAlg [START_REF] Arasu | Extracting structured data from Web pages[END_REF] or RoadRunner [START_REF] Crescenzi | Roadrunner: Towards automatic data extraction from large Web sites[END_REF].

Basically, these methods try to automatically generate a wrapper by inferring a grammar for the HTML code that contains the data of interest (generally called data records), in such a way that it does not rely on any a priori knowledge about the target pages and their contents. Usually, various pages that have the same template are needed in order to compare them in pairs and discover shared patterns and code regularities. These regularities are emphasized either by studying the similarities and dissimilarities between pages [START_REF] Crescenzi | Roadrunner: Towards automatic data extraction from large Web sites[END_REF], or by constructing classes of equivalence [START_REF] Arasu | Extracting structured data from Web pages[END_REF]. As opposed to the previous works, MDR [START_REF] Liu | Mining data records in Web pages[END_REF] considers the DOM tree structure of the HTML page, and identifies the data region by finding the generalized node that contains the largest number of children presenting the same patterns according to a similarity measure. Even though we are concentrating our attention on sites that contain Web articles, that are not necessarily consecutive in the way they appear in the Web page, we have a similar problem of extracting structured data (possibly of a more complex and isolated nature than in these approaches) and, as described in Section 4, we use Two other approaches to the problem of extracting the main article from a Web page have been proposed recently by Kholschutter, Fankhauser, and Nejdi [START_REF] Kholschutter | Boilerplate detection using shallow text features[END_REF] and Pasternack and Roth [START_REF] Pasternack | Extracting article text from the web with maximum subsequence segmentation[END_REF]. While [START_REF] Kholschutter | Boilerplate detection using shallow text features[END_REF] uses the text density on the Web page to identify the article, [START_REF] Pasternack | Extracting article text from the web with maximum subsequence segmentation[END_REF] uses a subsequence text segmentation technique to achieve the same result. Our algorithm of data object extraction uses, similarly to MDR, some heuristics on the HTML code in order to identify the region where the article might be found, but in contrast with all enumerated approaches, we use the semantics retrieved from the feed to extract the data objects. This is obviously possible only for pages which are linked to a Web feed. In Section 5, we compare our results to those of the Boilerpipe [START_REF] Kholschutter | Boilerplate detection using shallow text features[END_REF] algorithm, seen as a baseline of what can be done without exploiting Web feed information. To our knowledge, there is no previous work that leverages semantic information (that may come from a Web feed or from any other source) to extract the relevant part of the Web page, in a general and unsupervised manner.

WEB FEEDS: STATISTICS AND TRENDS

In order to affirm the value of feeds as analysis tools in the process of Web change detection, we have crawled over a period of a little more than one month, twice a day, a number of 400 Web feeds with all associated Web pages. We first describe how these feeds were selected and then report some statistics of interest of our dataset.

Acquisition

The set of feeds was collected from the Web by passing in large part through a feed search engine called Search4RSS [START_REF]Search4RSS feed search engine[END_REF]. This search engine returns a number of feeds and associated channel pages for a given keyword. We scraped the way the interface returns the results as records and put all URLs parsed in a file list to be further analyzed.

The keywords chosen in order to probe the search interface are names of domains: art, biology, environment, medicine, science and universe. We have used Wordnet in order to get hyponyms of these words (for example for art, a hyponym is photography) and constructed a bag of terms representing subdomains.

These bags of terms were used to automatically probe the Search4RSS interface and to construct, for each domain, a list of feed URLs. Semantics of terms permitted us to focus the search for feeds and to identify Web pages that were treating a certain subject. The reflection in the media of domains of interest can be observed through the eyes of feeds captured in this way, which usually present some specific patterns and characteristics.

The purpose of this semi-automatic selection was to get an insight into the diversity of feeds, in terms of formats, update patterns, and varied structures of the corresponding Web pages. Additionally, to ensure coverage of common blog platforms as well as the more news-oriented results returned by Search4RSS, a number of blog sites were manually selected from a list of "best blogs" [START_REF]Blogger's choice awards[END_REF]. We obtained thus a list of about 400 sites that were systematically crawled (this number ensures coverage of the variety of Web feeds, while remaining manageable without any involved archiving infrastructure). At the end of the crawling period, we noticed that some of the feeds had not been updated at all, some others had disappeared, and some could not be parsed. Filtering them out, we obtained an archive of 340 active feeds and their associated pages.

A Web feed refers to a primary Web page, the channel, which is usually either the home page of the site, or a hub from which we can find links to information presented in the form of Web articles. The rest of the feed describes individual feed items corresponding to new or updated articles. For each domain, for each followed site, we have stored the feed and the resources associated, mainly the channel page, and the Web pages that were referred to by each item. In order not to lose new items that could be added in the feed, these crawls were performed twice a day (in addition to the crawls of the same feeds run daily by European Web Archive).

Web feed characteristics

For the feed analysis, we have used Eddie [START_REF]Eddie java feed parser[END_REF], a feed parsing library for Java, based on a SAX-based parser capable of parsing even (some of) the real-world ill-formed XML. Eddie supports the standard RSS, Atom, and RDF formats for feeds. The FeedData structure returned by this parser can be exploited to extract all kinds of useful information about the channel and its composing items. In particular, for the channel, metadata like language, tagline, description and title; as well for each item, plus author and categories in which the article is classed.

Feed type. Let us first look at the types of feed formats that we encountered in our dataset. As shown on Table 1, most feeds use the 2.0 dialect of RSS, while a minority use Atom or RDF. RSS 0.91 was only used once among the 340 feeds, and RSS 1.0 never at all, which might suggest the coming obsolescence of these two feed formats. However, it is quite possible that these numbers are also biased by the use of Search4RSS as our main source for feeds.

Number of items.

We have looked at the number of items that were presented in a given feed. Indeed, though it is theoretically possible for a feed to refer to all previously published items, it is rarely done so to limit the size of the resulting Web feed. In effect, most feeds are truncated and present only the k most recent items for a given k. We show in Figure 1 a histogram of the number of items per feed in the dataset. Roughly 75% of the feeds present information about less than 30 items at a time. The other peaks observed in As we shall see, there is a minority of feeds with a higher update frequency than that, for which some of the updates were missed in our crawl (basically, these feeds needed to be crawled more often than twice a day).

Temporal information. In the RSS specification (and similarly in other feed formats) temporal information can be given through the elements lastBuildDate, ttl, and updateFrequency for the channel, and pubDate and lastModified for items.

From our experiments, we have observed that although pub-Date is an optional element, it is present in the vast majority of feeds. This is not the case for the other types of timerelated elements mentioned above, though lastBuildDate can be somehow inferred as the publication date of the most recent item. This observation is important as it shows that feeds can be used to determine when new data is added to a channel and of help in the task of change detection. By doing the analysis of a feed for a period of time, we can identify patterns in the publishing strategy and automatically adapt the crawl to it.

Update intervals.

We have collected all publication dates corresponding to the items appearing during the period of experiments; as an item has one publication date, the number of publication dates is equal to that of items. We are interested in the range of update intervals between two publications, as well as indications whether a feed has a regular publishing strategy. In Figure 2, we present the median update interval between two publications of each feed as a cumulative plot (in green, in the middle). Note that the x-axis has logarithmic scale. Figure 2 shows for instance that 20% of the feeds have a median update interval of less than an hour, and that around 10% of the feeds have a median update interval of exactly one day, which corresponds to feeds having regular, automatic, updates, every day. Globally, it is important to note that there is no typical update interval, and that, even disregarding extreme cases, it can range to less than a hour to more than a week. Figure 2 also shows other quantities of the update interval of each feed, which helps to see the diversity of update patterns for a given feed: thus, even though 60% of the feeds have a median update interval of a day or less, less than 10% of them always have at least an update per day, and more than 90% of them have at least had a daily update in the period of observation. There is actually a big gap between the median update interval values and minimum and maximum values, which makes difficult to predict the next update of a given feed.

We show in Table 2 some other statistics on update intervals at domain level. For each domain, the average mean update interval is given, as is the pooled standard deviation of update intervals, which is the statistically-founded way to summarize the deviation of the union of series of numbers. As can be seen, there are huge variations among domains, another indication of the absence of typical update interval. We also note here the very high standard deviations in some domains 1 , especially since a given domain can represent Web sites of very different natures (news items, blogs, wiki entries, etc.). In the art domain, for instance, we have observed that there are several sites that publish small articles about paintings or photographs of the order of 100 entries per day. So the notion of item varies from a specialized article, that might contain a lot of text (as it is the case for news), to an article exclusively composed of images or videos. The more structurally homogeneous category of "popular" blogs has a more reasonable deviation of update intervals.

We conclude here the study of the dataset, that reflects in a 1 Note that it is not impossible for a standard deviation to be much greater than a mean value, it just means that there are a few values much greater than the mean in the distribution. certain measure the status-quo and diversity of Web feeds, to turn to the discussion to our technique of Web data objects extraction.

DATA OBJECT EXTRACTION

We describe in this section our algorithm for finding the data object in a given Web page, object that corresponds to a Web feed item.

Gathering semantic information

We first construct a semantic context from feed items, that will serve to extract the corresponding object. Feed items have three compulsory elements: link, title and description.

Link. The link gives us the URL of the Web page in which the data object resides.

Title.

A feed item is required to have a title, which is usually a short text meant to characterize the content of an article.

Description. Most of the time, the description does not contain the whole content of the article, but only the first few lines of it, encoded in HTML for presentation purposes, with a link at the end (like "Read more. . . ") to the original Web page. In other cases, the description contains only a sentence, which summarizes the article rather than containing the first lines of it. Whatever the precise case, we can extract some reliable semantics about the article by exploiting this description.

We start by retrieving all textual content from the title and description; the HTML code of the description is stripped, only text is kept. The resulting sequences of words are transformed into two kinds of semantic entities: concepts and n-grams.

To obtain the concepts, we tokenize and stem the words, sort the resulting lexemes according to their frequency (seen as a measure of their importance) and keep only outstanding ones. In a sense, a concept will resemble a tag, being a term that describes a data object. The words coming from concepts can indeed be used as keywords to look for in a Web page, in order to identify the data object region, but can frequently digress the attention to other zones that are also rich in concepts, like the ones that contain comments or categories for a given Web article. This is the reason why we turned our focus to n-grams. A n-gram represents in our context a sequence of n terms, taken as they appear, from the title and the description. The choice for n is a compromise between false positives and false negatives in the extraction process and it is further discussed.

Extraction

We present here a bottom-up algorithm that, given a feed, it identifies the items and for each feed item finds the wrapper element of the data object by matching n-grams against the textual content of the leaf nodes extracted from the HTML Web page. This algorithm is summarized in Algorithm 1. We extract all leaf nodes of the page and, for each, establish its semantic density.

Definition 2. The semantic density of a conceptual node is defined as the number of matched concepts (or n-grams), divided by the length of the textual content of the respective node.

We classify the conceptual nodes according to the closest ancestor that is a block-level element. An effective heuristic is actually to take the closest ancestor that is a div element, since we have observed in our experiments that a data object is almost always confined in a div element. After this analysis, we are able to say which are the conceptual nodes that share the same ancestor. The list of ancestors will give us the semantic zones of the page, modeled at code level by semantic nodes.

Definition 3. A semantic node is the lowest block-level common ancestor of a set of conceptual nodes.

In order to clarify which of the semantic nodes represents the wrapper of the article, we calculate the following semantic density measure for each and take the node that has the largest value for it.

Definition 4. The wrapper node of the data object is the semantic node that contains the largest number of dense conceptual nodes.

In the previous description, we have allowed the use of either concepts or n-grams for finding conceptual nodes and computing semantic density. When matching with terms that correspond to concepts, the number of semantic zones will increase, while doing the matching with n-grams will visibly decrease this number. This happens because n-grams are more significant than concepts, relative to the article's content. Nevertheless, in certain cases, the choice of n-grams is too restrictive. This happens quite rarely, when the description is rather summarizing the article with different words, than representing the first lines of it. Consequently, in order to detect this kind of cases where n-grams are not an option, we introduce the notion of semantic node consistency.

Definition 5. A node is semantically consistent if its text contains a large proportion of the concepts acquired from the item's title and description.

We say a "large" proportion (in practice, ≥ 0.5) of concepts because it is not necessary to check for the presence of all in order to assert a wrapper node. On the other hand, when the candidate ancestor node does not contain half of the existing concepts, we might suspect that it is not the wrapper of the article. If this happens, we conclude that the n-grams were not effective due to imperfection of the semantic acquisition assumptions, and therefore we diminish the value of n in n-grams and repeat the method of getting the wrapper node. In our experiments, we started with n = 3 (the aim is to acquire an approprite number of significant ngrams) which gave best results, and, in case of failure, directly tried matching with concepts. In general, data objects (news articles, blog posts) have comments associated. We want to make a clear difference between the comments of an article and the article itself because:

1. from a conceptual point of view, the information of interest in an article is not the same as comments about it 2. the crawl of the article should be separated from the crawl of the comments: if each time a comment is added, the article is considered to be changed, a new crawl is needed and the resulting object can be very redundant in comparison with its previous version; instead, the article should have a reference to its comments, tracked separately and synchronized on update 3. usually, the webmaster takes care to add in the feed the URL that can be used to track comments, but when it is not the case, we can still identify the zone of comments by using heuristics in our algorithm

An example

To illustrate, we will take the example of a Web page, which is partially presented in Figure 3. The Web page will be cleaned and well-formatted using HtmlCleaner. This step is necessary in order to reliably select leaf nodes from the DOM tree of the page (and keep for futher analysis only those that contain at least one semantic term).

We observe that the title of the article is present in the feed item, as well as the first two lines of text, which are encoded in the feed description. There is also a timestamp that corresponds to the publication date. The tag <content:encoded> is not an element which appears very often, therefore we do not make assumptions about its usefulness in our algorithm.

In Figure 4 we observe that the title of the article is also present in the zone of comments and on the right, where are presented some of the most recent articles of the Web site. The title only is not sufficient as a hint: we also need the item's description. Some random examples of n-grams from the description are "delightful aspects"(n=2), "being a scientist"(n=3), "This morning the New"(n=4). In general, the n-grams have a smaller chance to be masively clustered in other zones of the Web page. More the sequences are large, more rapid will be to identify the article. On the contrary, if the description of the article is very short or a reformulation of the idea, using the concepts is a better choice. In this particular example, the algorithm identifies the article even using only "This morning the New". This happens because "This morning the New" is a unique n-gram in the Web page. Using only "delightful aspects" or "being a scientist" will not identify the article, as these n-grams appear also in the first comment (Figure 6, div/ol/li/div/p). Therefore, we cannot make the assumption that the sequences are unique or that we can make them unique, so we take various samples from the title and description. For explaining the principle of the algorithm, let's assume that the process of matching n-grams returns the two semantic nodes illustrated in Figure 5 and Figure 6 (in practice, for this Web page the algorithm returns three possible semantic nodes, that have actually a more complex structure). As we can see, the leaf nodes in the first DOM subtree (Figure 5) are richer in concepts than those in the second one (Figure 6). We then select the first node as it is the most significant regarding our semantic density measure.

EXPERIMENTS

In order to prove the validity of our approach for extracting data objects, we have fully implemented the system and performed experiments in order to evaluate its precision.

The experiments were done using the feeds collected as responses from the Search4RSS engine, the same dataset mentioned in Section 3. Recall that the dataset was quite diversified, in terms of structure and types of data objects.

For each feed, we have retrieved the channel data structure and applied the method of extraction for all its item components.

As a first test, we have tried to return the zone of the Web page associated with the item's title. This method was giving poor results, however, for several reasons: the title may not fully match due to encoding characters, or it may appear at several different places in the page (Figure 4). Additionally, given only the location of the title element, and its levels of imbrication in the HTML code blocks, it is not an easy task to identify the limits of the whole data object.

We compare now the performance of our algorithm, i.e., the precision of extracted data objects, to Boilerpipe [START_REF] Kholschutter | Boilerplate detection using shallow text features[END_REF] which constitutes a state-of-the-art method for identifying the main content of a page in the absence of extra semantic information. We stress that, as we use more information than Boilerpipe has access to, obtaining a better precision does not diminish the interest of this approach, which is more general.

We observed that our result is often more precise, because we are not simply considering the text density in the Web page, but rather its semantic coherence according to the feed item. There are cases where a node may contain a lot of text, but may be judged as worthless with respect to our semantic density measure. Moreover, note that when the Web page contains various consecutive articles, our method will make the difference between them and identify the specific article that corresponds to an item. In contrast, Boilerpipe will take the textual content of all the articles or just of the densest one, depending on the case.

The experiments were performed for 60 randomly selected sites from the dataset in the art domain (the first crawled), corresponding to a total of 1314 feed items. We manually checked the Web article, the result of our algorithm of extraction and that of Boilerpipe [START_REF] Kholschutter | Boilerplate detection using shallow text features[END_REF]. We only compare the textual result of the extraction because it is the output of the freely usable Boilerpipe implementation 2 . Our method actually extracts the whole content of the identified zone, including links and images.

Numerical results are given in Table 3. We consider an object as correctly extracted when its text is exactly that of the gold standard, obtained by manual annotation of the Web page. Partial matches are disregarded. The overall precision of the algorithm reaches the satisfactory number of around 79%, compared to the 62% precision obtained by Boilerpipe.

Finally, note that when our technique fails, the algorithm actually manages to identify a richer conceptual zone that the one of the data object, which is still relevant to the article, even though not strictly identifying with it.

DISCUSSION OF APPLICATIONS

We conclude this article by discussing a number of applications that can be integrated in the Web archiving process, 2 http://code.google.com/p/boilerpipe/ Perenniality of Web archives. Time is a particularly important factor of influence also for interpreting crawled content. While data might remain intact, the way we understand it and the rendering of it changes, mostly due to the fact that the language itself, the culture and the technological means of expression evolve. One of the most serious problems encountered in Web archiving is when the format of crawled data becomes obsolete or not generally used. The solutions given by the authors of [START_REF] Hunter | Implementing preservation strategies for complex multimedia objects[END_REF], [START_REF] Swaney | Dynamic Web file format transformations with grace[END_REF] and [START_REF] Strodl | Migrating content in warc files[END_REF] are software or hardware emulation, migrating content, or to include a proxy that will incorporate format translating capabilities and will do this dynamically, at user request or when the need is detected. While these works are trying to fight technology evolution, it is possible to take the opposite approach: adapt data to existing technology. In order to do this, one can imagine to encapsulate the relevant information of the crawled Web page, and to store the resulting object independently of the original encoding format. In this manner, the fact that technology evolves will not be anymore something to resist against, instead it will enhance the possibility of rendering the existing data in new ways, adapting the actual content to preferences. The extraction of data objects that we highlight in this paper is a first step towards storage of information freed from the specific way of encoding.

While it can be argued that for Web archiving the original form of a Web page matters, this is more related to the requirement of placing the actual data in its correct context. We note that our goal is not to try to change the current ways of storing the archived content, but for the cases in which it works (dynamic data with feed associated), some interesting overlay applications can be created for the people using the collection or for the archivists themselves. The extraction of data objects in the context of Web archiving is closely related to the semantic analysis of content in time and the possibility of providing value-added services. Indeed, what can very useful is to be able to run complex queries over the content, add interactivity and facilities to target consumers of the information presented as a Web archive.

Reconstruction of Web pages. Recall from Figure 2 that Web pages associated with Web feeds can have very lively dynamics, in some cases with update intervals of the order of the minute. In these conditions, it becomes unreasonable to try and capture every successive version of the corresponding channel Web page. However, since the Web feed keeps reference to a number of items (and, hopefully, a rather large number for such a lively channel), it is still possible to regularly crawl and archive it. In the cases where (most of) the content of each data object is stored in the Web feed, one application of the data extraction technique can be the reconstruction the Web page at a given point in time Moreover, using our algorithm (and possibly some heuristics), we can detect not only the DOM node that contains the article, but also other semantic nodes of the page: the ones that contain the comments, categories or tags. These zones can be mined for textual content and references, and stored independently of the template of the page (that consists basically of everything that remains after the extraction). A relation between the resulting components can be recreated or inferred using the semantics, and used to analyze these components. We could as reinvent the way information is rendered by mixing the objects (in mashups) to adapt to user preferences.

Figure 7 depicts the flow of a demonstration scenario pertaining to this reconstruction of Web pages from data objects, as described in [START_REF] Oita | Archivage du contenu éphémère du Web à l'aide des flux Web[END_REF].

Crawling and semantic exploitation of archives. Finally, we want to briefly recall two other applications, already mentioned earlier in this paper. Firstly, it is possible to use the data object extraction technique for change detection. Using a technique of temporal analysis on feeds similar to the one presented in this paper, we can determine the strategy of publishing of the channel that represents the dynamic part of the website. Having this awareness, we can adapt the rate of crawl to the approximated frequency. Moreover, for already crawled articles, we can detect if a new version has appeared in order to crawl it or not. This can be done by applying the algorithm of data object extraction on the crawled article and on the possibly new version of it (the current Web page). By comparing the resulting data objects referring to the same URL, we can see if a change in the text or references has occurred in the intervening period of time. Secondly, a Web archive that contains data objects (maybe in addition to Web pages) can be used by analysts more effectively than just an archive of Web pages. For instance, a linguist could focus on the new terms that appear in newspaper articles, without bothering about the terms that appear in the comments. Generally, the aim is to add exploitable meaning and temporality (at finer-grained levels) to collections of Web archives, that can become more expressive and adapted to user needs.

Figure 1 Figure 1 :

 11 Figure 1: Number of items per feed in the dataset

Figure 2 :

 2 Figure 2: Cumulated proportion of feeds with a given quartile value of interval between updates

Figure 3 :

 3 Figure 3: A typical Web article and its corresponding data item from the feed:

Figure 4 :Figure 5 : 1 Figure 6 :

 4516 Figure 4: An illustration of fact that the title alone is not enough to identify the zone of the Web article.

Figure 7 :

 7 Figure 7: Application for reconstructing Web pages from data objects

Table 1 : Dataset feed types Type Number Proportion

 1

	Atom	21	6.1%
	RDF	30	8.8%
	RSS 0.91	1	0.2%
	RSS 2.0	288	84.7%
	Total	340	100.0%
	somehow related techniques.

Table 2 : Feed statistics per domain

 2

	Domain	Number of feeds	Average mean update interval	Pooled standard derivation of update interval
	Art	87	12 days, 14 hours, 12 min	82 days, 6 hours, 32 min
	Biology	80	7 days,	13 min	8 days, 17 hours, 43 min
	Blogs	29		15 hours, 35 min	8 hours, 39 min
	Environment	7		19 hours, 49 min	4 days, 15 hours, 18 min
	Medicine	8	3 days, 19 hours, 16 min	1 day , 22 hours, 43 min
	Other	13	4 days, 16 hours, 48 min	4 days, 19 hours, 46 min
	Science	112	22 days, 12 hours, 45 min	14 days, 21 hours, 35 min
	Universe	4		4 hours, 44 min	7 hours, 5 min
	Total	340	12 days, 15 hours, 17 min	37 days, 16 hours, 49 min
	We first introduce the notion of conceptual node:
	Definition 1. A conceptual node is a leaf node (a node
	with no children) that contains in its textual content at least
	one concept (or n-gram) from the item's title and description.

Table 3 : Experimental results Method Correctly extracted Precision

 3

	Our technique	1038/1314	79.0%
	Boilerpipe	821/1314	62.5%
	and which use the data object extraction approach we pro-
	pose.

Acknowledgments. We would like to thank European Web Archive (especially, Julien Masanès, Gabriel Vasile and Radu Pop) for discussions about this topic and their help in obtaining the experimental dataset.

* This research was funded by the European Research Council grant Webdam FP7-ICT-226513. This work is licenced under an Attribution-NonCommercial -NoDerivs 2.