Maria-Fernanda Romero-Sarmiento

Armelle Riboulleau
email: armelle.riboulleau@univ-lille1.fr

Marco Vecoli

Gerard J M Versteegh

Fatima Laggoun-Défarge

Aliphatic and aromatic biomarkers from Carboniferous coal deposits at Dunbar (East Lothian, Scotland): Palaeobotanical and palaeoenvironmental significance

Keywords: land plant biomarkers, terrestrial terpenoids, combustion derived-PAH, Lower Carboniferous coals, megaspores

Carboniferous (Viséan) coals from Dunbar, East Lothian, Scotland, contain well-preserved miospore and megaspore assemblages suggesting a lycopod-dominated forest ecosystem with some ferns, sphenopsids and pteridosperms. The low rank of the coals and the well defined microflora permit assessment of the palaeoenvironmental significance of lipid biomarkers during Early Carboniferous times. Rock-Eval, petrographic, and lipid analyses indicate a fully terrestrial depositional environment. Although we also present and discuss a wide diversity of other lipid biomarkers (alkanes, hopanoids, steroids), we focus on the terrestrial-derived biomarkers. Combustion-derived PAHs pyrene, fluoranthene, benzo[a]anthracene, chrysene and triphenylene indicate the occurrence of forest fires in the study areas during Early Carboniferous times. Alkyldibenzofurans derive from lichen-biomass. Retene, cadalene, simonellite, tetrahydroretene and kaurane are poorly specific and can derive from a variety of early Palaeozoic land plants.

Abietane, phyllocladane, ent-beyerane and 4β(H)-eudesmane, as well as bisnorsimonellite, diaromatic totarane, diaromatic sempervirane and 2methylretene, however, as yet had only been reported from conifers, which do not appear in the fossil record until the Late Carboniferous.

Within the lower Carboniferous forest ecosystem, arborescent lycopsids and pteridosperms are proposed as alternative sources for these compounds.

Introduction

Biomarkers are molecular compounds which can be extracted from crude oils, coals and all kinds of sedimentary rocks [START_REF] Tissot | Petroleum Formation and Occurrence[END_REF]. Biomarkers have numerous biological origins, and their occurrence can be related to a specific source, giving information of the type of fauna/flora present in the environment, or to depositional conditions, such as salinity or temperature [START_REF] Peters | The Biomarker Guide: Interpreting molecular fossils in petroleum and ancient sediments[END_REF]. For these reasons, biomarkers are regularly used in palaeoenvironmental studies (e.g. [START_REF] Olcott | The utility of lipid biomarkers as paleoenvironmental indicators[END_REF][START_REF] Eglinton | Molecular proxies for paleoclimatology[END_REF]. Recent applications of biomarkers aim at tracing the evolution of life. In archean rocks, biomarkers give information on the timing and evolution of early forms of life (e.g. [START_REF] Brocks | Archean molecular fossils and the early rise of Eukaryotes[END_REF][START_REF] Brocks | A reconstruction of Archean biological diversity based on molecular fossils from the 2.78 to 2.45 billion-year-old Mount Bruce Supergroup, Hamersley Basin, Western Australia[END_REF][START_REF] Brocks | Biomarker evidence for green and purple sulphur bacteria in a stratified Palaeoproterozoic sea[END_REF][START_REF] Ventura | Molecular evidence of Late Archean archaea and the presence of a subsurface hydrothermal biosphere[END_REF][START_REF] Eigenbrode | Methylhopane biomarker hydrocarbons in Hamersley Province sediments provide evidence for Neoarchean aerobiosis[END_REF][START_REF] Waldbauer | Late Archean molecular fossils from the Transvaal Supergroup record the antiquity of microbial diversity and aerobiosis[END_REF], while in more recent rocks and sediments, biomarkers help determining taxonomic relationships between taxa (e.g. [START_REF] Arouri | Biological affinities of Neoproterozoic acritarchs from Australia: microscopic and chemical characterisation Organic[END_REF][START_REF] Talyzina | Affinities of Early Cambrian acritarchs studied by using microscopy, fluorescence flow cytometry and biomarkers[END_REF]. In the last decades, chemotaxonomic applications have been particularly developed for the study of flora associated with amber and coal deposits mostly of Mesozoic to recent age (e.g. [START_REF] Simoneit | Cyclic terpenoids of contemporary resinous plant detritus and of fossil woods, ambers and coals[END_REF][START_REF] Otto | Sesqui-and diterpenoid biomarkers preserved in Taxodium-rich Oligocene Oxbow Lake Clays, Weisselster basin, Germany[END_REF][START_REF] Otto | Terpenoid composition of three fossil resins from Cretaceous and Tertiary conifers. Review of Palaeobotany and Palynology 120[END_REF][START_REF] Bechtel | Influence of floral assemblage, facies and diagenesis on petrography and organic geochemistry of the Eocene Bourgas coal and the Miocene Maritza-East lignite (Bulgaria)[END_REF][START_REF] Stefanova | Molecular indicators for coal-forming vegetation of the Miocene Chukurovo lignite[END_REF] based on extractible biomarkers were developed in the 70's (Niklas, 1976a,b;[START_REF] Niklas | Chemotaxonomy of some problematic palaeozoic plants[END_REF][START_REF] Niklas | Evidence for lignin-like constituents in early silurian (llandoverian) plant fossils[END_REF] but have been relatively limited in more recent years (Schultze and Michaelis, 1990;[START_REF] Fleck | Palaeoenvironmental assessment of Westphalian fluvio-lacustrine deposits of Lorraine (France) using a combination of organic geochemistry and sedimentology[END_REF][START_REF] Auras | Aromatized arborane/fernane hydrocarbons as biomarkers for Cordaites[END_REF], despite the interest of Palaeozoic plants regarding the evolution of terrestrial life.

The aim of this study is to identify and characterise aliphatic and aromatic biomarkers for Lower Carboniferous plants preserved in coals and to relate these biomarkers to specific plant taxa in order to apply chemotaxonomy to Palaeozoic land plants. Biomarker analyses were performed on four Lower Carboniferous (Viséan) coal samples from Dunbar, East Lothian, Scotland. Though megafossils are absent from these coals, their palynological content is rich and comprises abundant miospore and megaspore assemblages [START_REF] Spinner | Megaspore assemblages from Viséan deposits at Dunbar, East Lothian, Scotland[END_REF][START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF]. This gives us an opportunity to correlate the identified biomarkers with the occurrence of land plant palynomorphs and possibly to terrestrial plant groups or families.

Geological setting and previous studies

The Midland Valley of Scotland is a rift valley bounded by Highland Boundary and Southern Uplands Faults on the North and the South, respectively (Fig. 1; [START_REF] Murchison | Igneous activity and organic maturation in the Midland Valley of Scotland[END_REF][START_REF] Underhill | Controls on structural styles, basin development and petroleum prospectivity in the Midland Valley of Scotland[END_REF]. This sedimentary basin evolved in response to crustal extension and especially contains Devonian to Carboniferous sediments and some igneous rocks [START_REF] Murchison | Igneous activity and organic maturation in the Midland Valley of Scotland[END_REF][START_REF] George | Effect of igneous intrusion on the organic geochemistry of a siltstone and an oil shale horizon in the Midland Valley of Scotland[END_REF][START_REF] Underhill | Controls on structural styles, basin development and petroleum prospectivity in the Midland Valley of Scotland[END_REF]. The Carboniferous rocks in the Midland Valley of Scotland are only well exposed along coastlines [START_REF] Murchison | Igneous activity and organic maturation in the Midland Valley of Scotland[END_REF]. Coal samples were collected from two outcrop sections located at Dunbar, East Lothian, on the east coast of southern Scotland, some 40 km East of Edinburgh (Fig. 1). These sections show a group of alternating Lower Carboniferous (Viséan) limestones, shales, sandstones and coals (Fig. 2. ;[START_REF] Spinner | Megaspore assemblages from Viséan deposits at Dunbar, East Lothian, Scotland[END_REF][START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF].

SKT coal samples were collected around the bay near Skateraw Harbour, approximately 6.4 km south-east of Dunbar, whereas WS coals were taken from rock successions exposed in White Sand Bay (Fig. 1). Both localities are clearly exposed on a geological map permanently exhibited just above the shoreline. In stratigraphic order, the lower seam is located immediately above the Middle Longcraig Limestone: samples WS-2 and WS-3 (Fig. 2); the upper one (samples SKT-E and SKT-D) occurs stratigraphically below the Chapel Point Limestone (Fig. 2). WS samples are equivalent to the Longcraig coal seam described by [START_REF] Spinner | Megaspore assemblages from Viséan deposits at Dunbar, East Lothian, Scotland[END_REF]. In contrast, SKT coals are more comparable to the sample horizon SC2 detailed by [START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF]. In order to investigate the possible vertical stratigraphic variations, two samples were obtained from each coal seam (Fig. 2).

Accordingly, WS coals are separated by approximately 30 cm while SKT samples by 15 cm. A fluvio-deltaic environment has been assigned to these Carboniferous coals, which contain mainly land-plant derived organic matter [START_REF] George | Effect of igneous intrusion on the organic geochemistry of a siltstone and an oil shale horizon in the Midland Valley of Scotland[END_REF]. After deposition, these shallow-water deltaic deposits were mainly influenced by burial history and extensive volcanic, sill and dyke activities [START_REF] Murchison | Igneous activity and organic maturation in the Midland Valley of Scotland[END_REF].

The sampled outcrop successions were previously studied palynologically [START_REF] Spinner | Megaspore assemblages from Viséan deposits at Dunbar, East Lothian, Scotland[END_REF][START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF]. Additional palynological analyses were performed for each of the collected samples for the present study. The WS coal interval is characterized by abundant and well-preserved megaspores such as [START_REF] Spinner | Megaspore assemblages from Viséan deposits at Dunbar, East Lothian, Scotland[END_REF]: and Densosporites spp. [START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF]. All megaspore specimens recognized in the WS horizon (e.g. Lagenicula subpilosa, Setosisporites and Zonalesporites fusinatus) range through the SKT coal interval but Zonalesporites is less abundant [START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF]. This upper interval also shows a notable diversity of miospores represented by Lycospora pusilla, Calamospora, Densosporites and Cingulizonates cf. capistratus (Hoffmeister, Staplin and Mallow) Staplin and Jansonius in Smith and Butterworth, 1967 (Spinner and Clayton, based flora reconstruction suggests that the vegetation consisted of large arborescent lycopsids with long leaves together with some diminutive forms [START_REF] Spinner | Megaspore assemblages from Viséan deposits at Dunbar, East Lothian, Scotland[END_REF].

Zonalesporites

Analytical methods

Experimental procedures

The four coal samples (Fig. 2) were studied by Rock-Eval pyrolysis and biomarker analysis. Rock-Eval pyrolysis was performed on 100 mg of ground rock with an Oil Show Analyser device at the University of Paris 6 (France), using the conventional temperature program described in [START_REF] Espitalié | La pyrolyse Rock-Eval et ses applications[END_REF]. The pyrolysis oven temperature was programmed with 25°/min from 300°C (held 3 min) to 650°C (held 3 min). However, due to the poor estimation of the total organic carbon (TOC) content of coals by Rock-Eval analysis [START_REF] Espitalié | La pyrolyse Rock-Eval et ses applications[END_REF], their TOC content was additionally determined on 100 mg of powdered decarbonated sample using a LECO carbon analyser at the same university (Paris 6, France). The hydrogen index (HI) was calculated using the Rock-Eval S 2 and the LECO TOC values.

For biomarker analyses, rock fragments were extracted with dichloromethane (DCM) during 24 h in the refrigerator, in order to remove possible contamination on the sample surface. After this first extraction, the rock fragments were crushed to enable extraction of the lipids preserved inside the rock. Approximately 30 g of pulverised samples were extracted with a mixture of methanol (MeOH) and dichloromethane (DCM) (1/2, v/v) for 24 h with extensive stirring. This second extract was dried by means of roto-evaporation and partly resolubilized in cyclohexane. The cyclohexane-soluble fraction (maltenes) was further separated by column chromatography.

The apolar fraction was recovered from the maltenes by elution with cyclohexane on an activated silica column. Subsequent elution with a mixture of cyclohexane -DCM (2/1, v/v) recovered the aromatic fraction after which the polar fraction was recovered by elution with a mixture DCM -MeOH (2/1, v/v).

Gas chromatography -mass spectrometry (GC-MS)

The aliphatic and aromatic fractions were analysed by gas chromatography -mass spectrometry (GC-MS) using a ThermoFinnigan Trace GC 2000 coupled to a ThermoFinnigan DSQ mass spectrometer.

The column used was a DB5ht (30 m length, 0.25 mm internal diameter, 0.1 µm film thickness). The oven temperature was programmed as follows 100 °C for 1 minute, 100 °C -310°C at a rate of 4 °C/min followed by an isothermal period of 16.5 min at 310 °C.

Helium was used as carrier gas. The mass spectrometer was operated in the EI mode at electron energy of 70 eV. Samples were analysed in full scan (m/z 50 -700; scan rate 1000 amu/s; scan speed 1.49/s, scan time 0.67 s). The organic compounds were identified by comparison of their mass spectra and retention times with available published data.

Organic petrography

Maceral analyses and random vitrinite reflectance measurements (expressed in %) were carried out on embedded grain sections of two coal samples (WS-3 and SKT-E) with a MPVIII Leica microscope using an oil immersion objective (50 X) and following the procedures described in ICCP (1975). Qualitative fluorescence analyses were also performed using a blue light.

Results

Bulk OM characteristics

Bulk organic parameters obtained by Rock-Eval and LECO analyses (Table 1) show that the TOC values for these coal samples range between 60.8 and 71.9%. HI and T max values vary between 144 to 218 mg HC/g TOC and 423 to 428°C, respectively (Fig. 3). The average T max is 426 °C. Based on the constructed HI vs. T max diagram (Fig. 3; [START_REF] Espitalié | La pyrolyse Rock-Eval et ses applications[END_REF], coal samples plot in the Type II -III kerogen region.

Maceral composition and vitrinite reflectance

The maceral composition of the two samples is very similar (Table 2). The two coals are dominated by vitrinite (47-49%), mostly corresponding to telocollinite (Table2; Fig. 4A). Exinite is the second most abundant maceral group (24-26%). It mostly corresponds to microspores and ornamental macrospores (17-20%) with a yellow to yellow-brownish fluorescence, and leaf cuticles with a bright yellow fluorescence (Fig. 4B). Resinous secretions presenting a bright yellow fluorescence also are observed in both samples (Fig. 4C). Although inertinite is the less abundant maceral, it nevertheless represents a substantial fraction of the organic matter (18-20%). This maceral group is dominated by semi-fusinite and fusinite. These macerals correspond to plant material which is partially or totally, respectively, charred or oxidized. Pyrofusinite, distinguished from fusinite by the presence of devolatilisation vacuoles which indicate combustion at high temperature (Fig. 4D), also is present in significant proportion (5%; Table 2).

Vitrinite random reflectance values are 0.44% and 0.45% for SKT-E and WS-3, respectively. These values show that the samples are both subbituminous A coals and represent the beginning of the bituminization interval.

Aliphatic hydrocarbons

Total aliphatic hydrocarbons

The total ion currents (TIC) of the aliphatic fractions of the coal extracts (Fig. 5) are dominated by a series of n-alkanes ranging from C 13 to C 30 . The distribution of n-alkanes is relatively similar in all four samples and the most abundant are n-C 27 and n-C 29 (Fig. 6). Long chain C 23 -C 33 n-alkanes are characterized by an odd-over-even predominance with a maximum at n-C 27 (Fig. 6). The carbon preference index (CPI) ranges between 1.65 and 1.93 (Table 1). Series of C 14 to C 21 acyclic isoprenoids dominated by norpristane (C 18 ), pristane (Pr; C 19 ) and phytane (Ph; C 20 ), were also detected (Fig. 6). Pr is the most abundant compound in all the samples except SKT-D, where the n-C 27 alkane is more abundant (Fig. 5). The Pr/Ph ranges from 7.33 to 14.67 (Table 1). The Pr/n-C 17 is more than 1, whereas the Ph/n-C 18 is inferior to 1 (Table 1; Fig. 7). Branched alkanes without odd or even chain length predominance were also recognized in low abundance (Fig. 6).

Steranes, hopanes, bicyclic alkanes and several diterpanoids were clearly detected in the aliphatic fractions (Fig. 5).

Hopanoids

Series of αβ-hopanes were detected in all the samples by monitoring the m/z 191 ion (Fig. 8). These compounds are dominated by 17α(H),21β(H)-hopanes (22R and 22S epimers) from C 27 to C 33 , with a maximum at C 29 or C 30 hopanes (Fig. 8).

Series of βα-moretanes (17β(H),21α(H)-moretanes) were also detected ranging from C 27 to C 32 , with a maximum at C 30 (Fig. 8). C 29 ββ-hopane was present in all the samples (Fig. 8). Tricyclic terpanes and gammacerane were not observed.

Steroids

Steranes and diasteranes were detected in all the samples using the characteristic fragment at m/z 217 (Fig. 9). Steranes are more abundant than diasteranes and the distribution of these compounds is similar in all the samples (Fig. 9). Steranes are dominated by the C 29 5α(H),14α(H),17α(H)-20R regular sterane (C 29 ααα-sterane; Fig. 9 and 10), followed by an important contribution of the αββ isomer (Fig. 9).

Diasteranes are dominated by C 29 βα-diasteranes. However, series of C 27 to C 29 αβ-diasteranes and C 27 to C 29 αββ-steranes were also recognized in all the samples (Fig. 9). Additionally, short chain steroids were also detected in low amounts. SKT coals show a marked contribution of short chain C 19 -C 20 steroids in comparison with WS samples (Fig. 9).

Bicyclic alkanes

Seventeen bicyclic alkanes ranging from C 14 to C 16 carbon atoms have been identified in the aliphatic extracts of the Scottish coals, using the expanded m/z 109 + 123 + 179 + 193 fragmentograms (Fig. 11).

Peak assignments for the identified bicyclic alkanes are summarized in Table 3. Based on comparisons with the previously reported mass spectra and the retention times, 4β(H)-eudesmane; 8β(H)-drimane; 8β(H)-and 8α(H)-homodrimanes were clearly detected (Fig. 11;[START_REF] Noble | A geochemical study of bicyclic alkanes and diterpenoid hydrocarbons in crude oils, sediments and coals[END_REF][START_REF] Noble | Configurational isomerization in sedimentary bicyclic alkanes[END_REF]. These compounds are not present as the major constituents of the aliphatic fractions (Fig. 5); however, they have been found in relative significant proportion (Fig. 11). Most of other identified bicyclic alkanes have been previously observed in coal extracts [START_REF] Noble | A geochemical study of bicyclic alkanes and diterpenoid hydrocarbons in crude oils, sediments and coals[END_REF][START_REF] Noble | Configurational isomerization in sedimentary bicyclic alkanes[END_REF].

The distribution of bicyclic alkanes is relatively similar in all four coals and the most abundant are C 14 bicyclic alkanes (Fig. 11; e.g.

Peaks b and c

). 8β(H)-homodrimane (Fig. 11; Peak p) is present in significant proportion in most samples except SKT-D, while the relative abundance of peak h allows differentiate WS coals from SKT samples.

The relative abundance of 4β(H)-eudesmane and 8β(H)-drimane is similar in all samples (Fig. 11; Peaks i and k; respectively).

Tricyclic and tetracyclic diterpenoids

The partial m/z 109 + 123 + 193 + 233 fragmentograms from the aliphatic fractions of Lower Carboniferous coals reveal the presence of eighteen tricyclic and tetracyclic diterpenoid hydrocarbons (Fig. 12).

Peak assignments for identified aliphatic diterpenoids are shown in Table 4. The tetracyclic diterpenoids (C 20 H 34 ) ent-beyerane (Peak XII), 16β(H)-phyllocladane (Peak XIII), ent-16α(H)-kaurane (Peak XV), 16α(H)phyllocladane (Peak XVI) and ent-16β(H)-kaurane (Peak XVII) were mainly recognized, by comparison with the published mass spectra of authentic compounds [START_REF] Noble | A geochemical study of bicyclic alkanes and diterpenoid hydrocarbons in crude oils, sediments and coals[END_REF][START_REF] Otto | Sesqui-and diterpenoid biomarkers preserved in Taxodium-rich Oligocene Oxbow Lake Clays, Weisselster basin, Germany[END_REF]also in Noble et al., 1985;[START_REF] Philp | Fossil Fuel Biomarkers Applications and Spectra[END_REF][START_REF] Schulze | Structure and origin of terpenoid hydrocarbons in some German coals[END_REF].

The peak labelled II has a mass spectrum characterized by a strong fragment at m/z 233 (Fig. 12A). Based on its fragmentation pattern, compound II was tentatively identified as a C 18 tricyclic hydrocarbon (Fig. 12). This latter compound is particularly abundant in SKT samples, as are C 19 and C 20 steranes, it could therefore be related to short chain steroids. To our knowledge, the molecular structures for most of the C 18 -C 19 diterpenoids identified in this study, have not been previously established (see mass spectra in the appendix).

In most samples, the tetracyclic diterpenoid distribution is dominated by kaurane and phyllocladane. Kaurane isomers, however, are slightly more abundant in SKT samples while phyllocladanes are more predominant in WS coals (Fig. 12). ent-Beyarane shows a relatively similar contribution in all samples, and generally is present in low amounts in comparison to the other C 20 diterpenoids.

The only tricyclic diterpenoid identified is abietane (Peak XIV; Fig. 12). It is present in relatively low abundance in all four samples. Its contribution is however more significant in WS coals (Fig. 12).

The land plant-and combustion-derived polycyclic aromatic hydrocarbons

Among the polycyclic aromatic hydrocarbons (PAHs), two particular groups have been recognized in these Scottish coals (Fig. 13; Table 5). The first one includes the land-plant-derived PAHs retene (87), cadalene (33), simonellite (74), bisnorsimonellite (57), tetrahydroretene (70), diaromatic totarane (76), diaromatic sempervirane (90) and 2methylretene (94) whereas the second group comprises the combustionderived PAHs pyrene (75), fluoranthene (71), benzo[a]anthracene (96), chrysene and triphenylene (97) (Fig. 13;[START_REF] Philp | Fossil Fuel Biomarkers Applications and Spectra[END_REF][START_REF] Ellis | Formation of isohexyl alkylaromatic hydrocarbons from aromatization-rearrangement of terpenoids in the sedimentary environment: A new class of biomarker[END_REF][START_REF] Otto | Sesqui-and diterpenoid biomarkers preserved in Taxodium-rich Oligocene Oxbow Lake Clays, Weisselster basin, Germany[END_REF]Jiang et al., 1998 and references therein;[START_REF] Van Aarssen | Higher plant biomarkers reflect palaeovegetation changes during Jurassic times[END_REF][START_REF] Otto | Chemosystematics and diagenesis of terpenoids in fossil conifer species and sediment from the Eocene Zeitz Formation, Saxony, Germany[END_REF]Bastow et al., 2001, Tuo and[START_REF] Tuo | Saturated and aromatic diterpenoids and triterpenoids in Eocene coals and mudstones from China[END_REF]. Simonellite (74), diaromatic totarane (76) and diaromatic sempervirane (90) (see also the expanded m/z 237 chromatograms; Fig. 20) were clearly identified by their mass spectra but the elution pattern slightly differs from one presented in [START_REF] Tuo | Saturated and aromatic diterpenoids and triterpenoids in Eocene coals and mudstones from China[END_REF]. Following the same principles as by [START_REF] Tuo | Saturated and aromatic diterpenoids and triterpenoids in Eocene coals and mudstones from China[END_REF], another family of diaromatic tricyclic hydrocarbons was detected in the aromatic fractions (Fig. 20). These new, supposedly also diaromatic hydrocarbons (Tre 1 and Tre 2 ) have very similar mass spectra to tetrahydroretene, exhibiting a base peak at m/z 223 and a molecular ion at m/z 238 (Fig. 20). Based on their mass spectra and elution times, comparison with the distribution of the established diaromatic tricyclic hydrocarbons simonellite, diaromatic totarane and diaromatic sempervirane [START_REF] Otto | Sesqui-and diterpenoid biomarkers preserved in Taxodium-rich Oligocene Oxbow Lake Clays, Weisselster basin, Germany[END_REF][START_REF] Otto | Chemosystematics and diagenesis of terpenoids in fossil conifer species and sediment from the Eocene Zeitz Formation, Saxony, Germany[END_REF][START_REF] Tuo | Saturated and aromatic diterpenoids and triterpenoids in Eocene coals and mudstones from China[END_REF], and the identification of diaromatic totarane and sempervirane in our coals, these compounds were tentatively identified as tetrahydroretene isomers, based on the totarane and sempervirane skeletons, respectively. Compound Tre 1 could be the 1-methyl-1,2,3,4-tetrahydro-8-isopropylphenanthrene (totarane-derived) and Tre 2 the 1-methyl-1,2,3,4-tetrahydro-6-isopropylphenanthrene (sempervirane-derived; Fig. 20). Their molecular structures are also proposed in Figure 20.

Discussion

Thermal maturity

According to LECO results, the TOC values for these Scottish samples are typical for coals (60.8 and 71.9%; Table 1). Based on such values of TOC, the average T max (426 °C) from Rock-Eval analyses, as well as the vitrinite reflectance (0.45 %), the rank of the studied coals is of subbituminous A, i.e. an immature stage of thermal evolution (Fig. 3). This interpretation is supported by molecular thermal maturity indicators from the aliphatic and aromatic fractions. First, the CPI is high (>1) due to odd predominance (Table 1; [START_REF] Bray | Distribution of n-paraffins as a clue to recognition of source beds[END_REF].

Second, the thermally unstable C 29 ββ hopane is observed in all samples (Fig. 8; [START_REF] Seifert | The effect of thermal stress on source rock quality as measured by hopane stereochemistry[END_REF]. Third, the high thermal maturity markers in sediments 18α-22,29,30-trisnorneohopane (Ts) and αββsteranes (Fig. 9) are absent or very low in abundance (Seifert andMoldowan, 1978, 1986). This is further attested by the aromatic hydrocarbon distribution of MN, EN, DMN, TMN, TeMN and MP isomers again indicating that the coals are immature (Table 6; [START_REF] Radke | Aromatic components of coal: relation of distribution pattern to rank[END_REF][START_REF] Radke | Maturity parameters based on aromatic hydrocarbons: influence of the organic matter type[END_REF][START_REF] Alexander | The effects of thermal maturity on distribution of dimethylnaphthalenes and trimethylnaphthalenes in some ancient sediments and petroleums[END_REF][START_REF] Van Aarssen | Distributions of methylated naphthalenes in crude oils: indicators of maturity, biodegradation and mixing[END_REF]. For instance, the TeMN compounds show the predominance of 1,2,5,6-and 1,2,3,5-TeMN over the 1,3,6,7-TeMN (Fig. 16; [START_REF] Van Aarssen | Distributions of methylated naphthalenes in crude oils: indicators of maturity, biodegradation and mixing[END_REF].

The distribution of methyl-and ethyl-naphthalene homologues with 2-MN and 2-EN dominating is typical for immature samples (Fig. 14; Table 6; [START_REF] Radke | Aromatic components of coal: relation of distribution pattern to rank[END_REF]. The alkylphenanthrenes 9-MP and 1-MP are highly abundant, with 9-MP being predominant (Fig. 17) is another feature of immature samples [START_REF] Radke | Aromatic components of coal: relation of distribution pattern to rank[END_REF]. It is interesting to note, however, that depending on the maturity index either WS or SKT samples may be considered to be the more mature. WS samples are more mature with DNR, TNR1 and TNR2 while SKT samples are more mature with TMNr, TeMNr, MPI 1 and MPI 2 (Table 6). This feature probably reflects the control exerted by the source of the organic matter and depositional environment on these compounds at low maturity degree.

Biomarker distributions and palaeoenvironmental conditions

Like most coals, the investigated ones are typically terrestrial. This is evidenced by petrographic examination (Table 2, Fig. 4), palynology [START_REF] Spinner | Megaspore assemblages from Viséan deposits at Dunbar, East Lothian, Scotland[END_REF][START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF], and biomarker distributions. In addition to the typical odd numbered long-chain nalkanes [START_REF] Eglinton | Leaf epicuticular waxes[END_REF], several aliphatic and aromatic compounds generally used as terrestrial biomarkers have been detected in our Carboniferous coals (Table 7).

The Carboniferous sedimentary rocks in the Midland Valley of Scotland consist of cyclical sequences of coals, oil shales, limestones, shales, mudstones, siltstones and sandstones [START_REF] Murchison | Igneous activity and organic maturation in the Midland Valley of Scotland[END_REF][START_REF] George | Effect of igneous intrusion on the organic geochemistry of a siltstone and an oil shale horizon in the Midland Valley of Scotland[END_REF]. Coals are usually deposited in swampy terrestrial environments such as deltas and regions with poor drainage.

Accordingly, a variety of depositional environments, all relatively shallow-water and predominantly deltaic, has been assigned to these Carboniferous rocks [START_REF] Murchison | Igneous activity and organic maturation in the Midland Valley of Scotland[END_REF]). In the case of a deltaic environment (such as in our case) marine intrusions may occur which may be evidenced by means of palynomorphs and lipid biomarkers. Since organic particles of marine origin, i.e. alginite and marine palynomorphs, and marine biomarkers (e.g. cheilantanes) are absent, the (low proportion of) short chain n-alkanes in our coals (Fig. 6) must be considered to be of bacterial rather than marine origin.

Other arguments for a purely terrestrial depositional environment are the high Pr/Ph (Table 1) and Pr/n-C 17 vs. Ph/n-C 18 ratios (Fig. 7; [START_REF] Hunt | Petroleum Geochemistry and Geology[END_REF]. These ratios characterize the Scottish coals as Type III OM which is usually derived from terrestrial plants [START_REF] Peters | The Biomarker Guide: Interpreting molecular fossils in petroleum and ancient sediments[END_REF] deposited under oxidizing conditions, and in particular, the WS coal level (Fig. 7).

A bacterial contribution to the OM is further evidenced by the occurrence of branched alkanes (Fig. 6; e.g. [START_REF] Shiea | Mid-chain branched monoand dimethyl alkanes in hot spring cyanobacterial mats: a direct biogenic source for branched alkanes in ancient sediments?[END_REF], hopanoids (Figs. 5 and 8;[START_REF] Otto | Terpenoid composition of three fossil resins from Cretaceous and Tertiary conifers. Review of Palaeobotany and Palynology 120[END_REF] and bicyclic alkanes of the drimane and homodrimane series (Fig. 11; [START_REF] Noble | A geochemical study of bicyclic alkanes and diterpenoid hydrocarbons in crude oils, sediments and coals[END_REF][START_REF] Noble | Configurational isomerization in sedimentary bicyclic alkanes[END_REF]. Aromatic hydrocarbons often associated to a microbial source include 1,2,3,5,6-pentamethylnaphthalene (1,2,3,5,6-PMN; Fig. 13; Table 5; [START_REF] Bastow | Pentamethylnaphthalenes and related compounds in sedimentary organic matter[END_REF] and1,3,6,7-tetramethylnaphthalene (1,3,6,7-TeMN; Fig. 16; e.g. [START_REF] Jiang | Polycyclic aromatic hydrocarbons in ancient sediments and their relationships to palaeoclimate[END_REF].

Steroids have also been used to differentiate depositional settings [START_REF] Peters | The Biomarker Guide[END_REF]. [START_REF] Huang | Sterols as ecological indicators[END_REF] proposed a useful ternary diagram to identify the source of the OM which can be constructed by the distribution of C 27 , C 28 and C 29 sterols (Fig. 10).

Based on their results, the dominant source of C 27 sterols is zooplankton, C 28 sterols are generally components of phytoplankton and C 29 sterols are mainly derived from terrestrial plants. There are many exceptions on these rules; for instance, C 29 sterols are also found in marine diatoms and dinoflagellates (e.g. [START_REF] Rampen | A comprehensive study of sterols in marine diatoms (Bacillariophyta): Implications for their use as tracers for diatom productivity[END_REF].

Nevertheless, the method seemed reliable for other Palaeozoic (Middle Devonian) coals which have a high predominance of C 29 steranes (e.g. [START_REF] Fowler | Hydrocarbon potential of Middle and Upper Devonian coals from Melville Island, Arctic Canada[END_REF][START_REF] Kashirtsev | Terpanes and steranes in coals of different genetic types in Siberia[END_REF]. Considering this, the dominance of C 29 relative to C 27 steranes in these coals further evidences their terrestrial origin (Table 1; Fig. 9). Consistent with the shallow-water environment proposed for Scottish coals [START_REF] Murchison | Igneous activity and organic maturation in the Midland Valley of Scotland[END_REF], the steroids plot in a transitional estuarine-bay environment (Fig. 10). It is interesting to note that short chain C 19 -C 20 steroids are abundant in SKT coals (Fig. 9). Although these compounds are not commonly described from coals, they have been reported in a Devonian liptobiolith [START_REF] Kashirtsev | Terpanes and steranes in coals of different genetic types in Siberia[END_REF]. The relative abundance of these C 19 -C 20 steroids may be characteristic for some primitive coals, suggesting that they could be more specific biomarkers of early plants.

The occurrence of the combustion-derived PAHs pyrene, fluoranthene, benzo[a]anthracene, chrysene and triphenylene (Fig. 13) can be related to the significant presence of the fusinite group, most particularly pyrofusinite, in the organic matter. Charred or fusinized plant debris have been frequently reported in coals from the Midland Valley of Scotland [START_REF] Murchison | Igneous activity and organic maturation in the Midland Valley of Scotland[END_REF][START_REF] Scott | The nature and influence of fire in Carboniferous ecosystems[END_REF][START_REF] Falcon-Lang | Fire ecology of the Carboniferous tropical zone[END_REF] and combustion-derived PAHs have been observed in coal extracts [START_REF] Murchison | Igneous activity and organic maturation in the Midland Valley of Scotland[END_REF]. These compounds and macerals testify that fire events took place contemporarily with coal deposition. Fire events in coals are often related to lightning, but in the case of the Midland Valley of Scotland, volcanic activity also appears as a major cause of wildfires [START_REF] Murchison | Igneous activity and organic maturation in the Midland Valley of Scotland[END_REF][START_REF] Scott | The nature and influence of fire in Carboniferous ecosystems[END_REF][START_REF] Falcon-Lang | Fire ecology of the Carboniferous tropical zone[END_REF].

Linking biomarkers, palynology and palaeobotany

On the basis of the diverse palynomorph assemblages described by [START_REF] Spinner | Megaspore assemblages from Viséan deposits at Dunbar, East Lothian, Scotland[END_REF] and [START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF], a relatively detailed reconstruction of the flora giving rise to the SKT and WS coals can be provided, though more details are available for SKT coals than for WS coals. In WS coals, megaspores are dominated by Zonalesporites and/or Setosisporites, followed by Lagenicula [START_REF] Spinner | Megaspore assemblages from Viséan deposits at Dunbar, East Lothian, Scotland[END_REF]. Cystosporites are also present in minor proportion. In SKT coal, dominant megaspores are Lagenicula and Setosisporites followed by ?Bacutriletes and Zonalesporites [START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF]. Miospores assemblages are generally dominated by Lycospora, Calamospora and Densosporites [START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF]. Cingulizonates miospores should also be abundant in SKT coal. The megaspore Zonalesporites as well as the miospores Densosporites and Cingulizonates were mostly produced by Bodeodendron/Sporangiostrobus (recently identified as equivalent to Omphalophloios) which was a sub-arborescent lycopsid belonging to the Isoetales group [START_REF] Wagner | A late Stephanian forest swamp with Sporangiostrobus fossilized by volcanic ash fall in the Puertollano Basin, central Spain[END_REF][START_REF] Taylor | Paleobotany: The Biology and Evolution of Fossil Plants[END_REF]Opluštil et al., 2010).

Bacutriletes miospores were produced by herbaceous and subarborescent lycopsids among which Bodeodendron/Sporangiostrobus [START_REF] Eble | Lower and lower Middle Pennsylvanian coal palynofloras, southwestern Virginia[END_REF]. Setosisporites megaspores mainly derived from Bothrodendron (e.g. Phillips, 1979). Lagenicula megaspores and some Lycospora miospores were produced by Paralycopodites (also known as Anabathra; [START_REF] Dimichele | Paleobotanical and paleoecological constraints on models of peat formation in the Late Carboniferous of Euramerica[END_REF]. Finally, Cystosporites megaspores and some Lycospora miospores were produced by Lepidodendron (DiMichele and Phillips, 1994). Bothrodendron, Paralycopodites and Lepidodendron were arborescent lycopsids and belonged to the Lepidodendrales group [START_REF] Taylor | Paleobotany: The Biology and Evolution of Fossil Plants[END_REF]. It must be noted that these different plants are mostly documented from the Late Carboniferous and afterwards, though the corresponding spores appeared earlier, sometimes in the Devonian [START_REF] Glasspool | Ultrastructure and affinity of Lower Carboniferous megaspores from the Moscow Basin, Russia[END_REF]Opluštil et al., 2010). The plants from which these spores derived in Viséan coals are not firmly identified, but it is highly probable that they correspond to several groups or families of lycopsids [START_REF] Glasspool | Ultrastructure and affinity of Lower Carboniferous megaspores from the Moscow Basin, Russia[END_REF], in particular to Isoetales and Lepidodendrales which already existed during the Viséan [START_REF] Taylor | Paleobotany: The Biology and Evolution of Fossil Plants[END_REF]. Accordingly, though the same lycopsids were present in both coal levels, WS coals vegetation is marked by a higher contribution of Isoetales (Bodeodendron-like) while Lepidodendrales, and in particular Paralycopodites-like plants, were more abundant in the vegetation of SKT coals. In addition to these dominant plants, the miospore assemblages [START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF] document the presence of a notable contribution of Calamites sphenopsids and of small ferns, in particular Botryopteridaceae and Zygopteridaceae. Marattialean tree ferns and the arborescent lycopsid Sigillariaceae are also indicated, as well as Lyginopteridacean pteridosperms documented by the presence of the spore Schulzospora [START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF]. Lycopsids were abundant spore producers (DiMichele and Phillips, 1994) and the abundance of spores observed in the organic matter (Table 2; Fig. 4) supports a significant contribution of lycopsids to our Scottish coals. By its diversity and dominance of lycopsids, this floral assemblage appears relatively comparable to the anatomically preserved floras of Glenarbuck and Pettycur in Scotland [START_REF] Scott | Distribution of anatomicallypreserved floras in the Lower Carboniferous in Western Europe[END_REF], which are of Viséan age but slightly older than our studied coals. It is notable that although there are some Viséan records of Cordaites (e.g. [START_REF] Wang | The cordaitean fossil plants from Cathaysian area in China[END_REF], Cordaites remains were not reported from Glenarbuck and Pettycur [START_REF] Scott | Distribution of anatomicallypreserved floras in the Lower Carboniferous in Western Europe[END_REF] nor Cordaite spores (e.g. Florinites) in the palynofacies from our Scottish coals [START_REF] Spinner | Megaspore assemblages from Viséan deposits at Dunbar, East Lothian, Scotland[END_REF][START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF].

The relatively similar lycopsid-dominated floras observed in SKT and WS coals [START_REF] Spinner | Megaspore assemblages from Viséan deposits at Dunbar, East Lothian, Scotland[END_REF][START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF] are consistent with the relatively similar biomarker content observed in both coals. Some aromatic biomarkers detected in this study can be related to specific plant taxa (Table 7). For instance, the presence of alkyldibenzofurans (MDBFs) indicates lichen input (Fig. 13; [START_REF] Radke | Alkyldibenzofurans in terrestrial rocks: Influence of organic facies and maturation[END_REF]. Although lichen fossils or specific lichen spores have not been reported in Scottish coals [START_REF] Spinner | Megaspore assemblages from Viséan deposits at Dunbar, East Lothian, Scotland[END_REF][START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF], it can be safely assumed that Euramerican Coal Measure forests were a good potential habitat for lichens. Among the less specific biomarkers, the detected combustion-derived PAHs cannot be associated to specific kind of plants (Oros and Simoneit 2000a,b;[START_REF] Oros | Identification and emission factors of molecular tracers in organic aerosols from biomass burning: Part 3. Grasses[END_REF][START_REF] Iinuma | Source characterization of biomass burning particles: The combustion of selected European conifers, African hardwood, savanna grass, and German and Indonesian peat[END_REF]. It is also the case for 1,6dimethylnaphthalene (1,6-DMN; Fig. 14), 1,2,5-trimethylnaphthalene (1,2,5-TMN; Fig. 15), pimanthrene (1,7-DMP; Fig. 16) and cadalene, which can be produced by aromatization of several different terpenoid structures and/or which precursors are widespread among terrestrial plants (Table 7). Ionene is a degradation product of β-carotene [START_REF] Day | Ionene: a thermal degradation product of β-carotene[END_REF]. It is often observed in coal extracts (e.g. [START_REF] Wang | Organic geochemistry and coal petrology of Tertiary brown coal in the Zhoujing mine, Baise Basin, South China[END_REF], but also can be produced from thermal degradation of marine and lacustrine sediments [START_REF] Day | Ionene: a thermal degradation product of β-carotene[END_REF][START_REF] Achari | Identification of ionene and other carotenoid degradation products from the pyrolysis of sporopollenins derived from some pollen exines, a spore coal and the Green River shale[END_REF]. 4β(H)-eudesmane is another non-specific land plant biomarker. This compound has been rarely observed in Palaeozoic coals [START_REF] Del Río | Composition and origin of the aliphatic extractable hydrocarbons in the Puertollano (Spain) oil shale[END_REF][START_REF] Dzou | Maturation effects on absolute biomarker concentration in a suite of coals and associated vitrinite concentrates[END_REF] and is considered to derive from evolved land plants such as angiosperms and gymnosperms (e.g. conifers; [START_REF] Noble | A geochemical study of bicyclic alkanes and diterpenoid hydrocarbons in crude oils, sediments and coals[END_REF]. However, bicyclic alkanes with an eudesmane skeleton have been also identified in recent bryophytes [START_REF] Asakawa | Chemosystematics of the Hepaticae[END_REF]. Its oldest reported occurrence in sediments, to our knowledge, is Middle Pennsylvanian [START_REF] Dzou | Maturation effects on absolute biomarker concentration in a suite of coals and associated vitrinite concentrates[END_REF].

The diterpenoids ent-beyerane, abietane, ent-kaurane and phyllocladane have been previously described in Carboniferous (e.g. [START_REF] Schulze | Structure and origin of terpenoid hydrocarbons in some German coals[END_REF][START_REF] Fleck | Palaeoenvironmental assessment of Westphalian fluvio-lacustrine deposits of Lorraine (France) using a combination of organic geochemistry and sedimentology[END_REF]; among others) and Permian coals (e.g. [START_REF] Noble | A geochemical study of bicyclic alkanes and diterpenoid hydrocarbons in crude oils, sediments and coals[END_REF][START_REF] Noble | Tetracyclic diterpenoid hydrocarbons in some Australian coals, sediments and crude oils[END_REF]. Abietane precursors occur in all conifer families [START_REF] Otto | Sesqui-, di-and triterpenoids as chemosystematic markers in extant conifers -A review[END_REF][START_REF] Cox | Oxygenated di-and tricyclic diterpenoids of southern hemisphere conifers[END_REF] and this compound has been recently described in the pyrolysate of Late Carboniferous amber [START_REF] Bray | Identification of Carboniferous (320 Million Years Old) Class Ic Amber[END_REF]. Kaurane skeletons have been observed in different kinds of plants, and in particular bryophytes (e.g. [START_REF] Noble | A geochemical study of bicyclic alkanes and diterpenoid hydrocarbons in crude oils, sediments and coals[END_REF][START_REF] Chopra | Biology of Bryophytes[END_REF][START_REF] Asakawa | Chemosystematics of the Hepaticae[END_REF]. The occurrence of this component in very early terrestrial OM (e.g. [START_REF] Sheng | Tetracyclic terpanes enriched in Devonian cuticle humic coals[END_REF][START_REF] Disnar | Biological origin of tetra-cyclic diterpanes, n-alkanes and other biomarkers found in Lower Carboniferous Gondwana coals (Niger)[END_REF][START_REF] Kashirtsev | Terpanes and steranes in coals of different genetic types in Siberia[END_REF][START_REF] Romero-Sarmiento | Occurrence of retene in upper Silurian -Lower Devonian sediments from North Africa: Origin and implications[END_REF] can be therefore related to bryophytes, which represent the earliest land plants. Phyllocladane and ent-beyerane have been mostly associated to all conifer families except Pinaceae (e.g. [START_REF] Noble | A geochemical study of bicyclic alkanes and diterpenoid hydrocarbons in crude oils, sediments and coals[END_REF][START_REF] Schulze | Structure and origin of terpenoid hydrocarbons in some German coals[END_REF]; among others). However, the oldest recorded occurrences of phyllocladane and ent-beyerane are Serpukhovian [START_REF] Fabianska | Gas chromatography-mass spectrometry in geochemical investigation of organic matter of the Grodziec Beds (Upper Carboniferous), Upper Silesian Coal Basin, Poland[END_REF][START_REF] Izart | Stratigraphic distribution of macerals and biomarkers in the Donets Basin: Implications for paleoecology, paleoclimatology and eustacy[END_REF] and Middle Devonian [START_REF] Sheng | Tetracyclic terpanes enriched in Devonian cuticle humic coals[END_REF][START_REF] Kashirtsev | Terpanes and steranes in coals of different genetic types in Siberia[END_REF], respectively. The occurrence of these compounds in Carboniferous sediments that predated the evolution of conifers has been related to the Voltziales (e.g. [START_REF] Schulze | Structure and origin of terpenoid hydrocarbons in some German coals[END_REF] and/or the close relatives Cordaites (e.g. Disnar and Harouna, 1994 and references therein), while in Devonian coals, these compounds were related to pteridophytes [START_REF] Sheng | Tetracyclic terpanes enriched in Devonian cuticle humic coals[END_REF].

The relative abundance of tricyclic and tetracyclic diterpenoids in coals is affected by the palaeobotanical and palaeoenvironmental conditions and consequently, by the available type of vegetation (e.g. [START_REF] Schulze | Structure and origin of terpenoid hydrocarbons in some German coals[END_REF][START_REF] Fleck | Palaeoenvironmental assessment of Westphalian fluvio-lacustrine deposits of Lorraine (France) using a combination of organic geochemistry and sedimentology[END_REF]. In Permian coals, the dominance of tetracyclic diterpenoids, and in particular phyllocladane and kaurane isomers has been related to the pteridosperm Glossopteris, while a predominance of tricyclic terpanes (e.g. isopimarane, rimuane, fichtellite) can particularly indicate a Medullosan pteridosperm input [START_REF] Noble | A geochemical study of bicyclic alkanes and diterpenoid hydrocarbons in crude oils, sediments and coals[END_REF]. A predominance of kaurane has been also observed in Late Carboniferous rocks [START_REF] Fabianska | Gas chromatography-mass spectrometry in geochemical investigation of organic matter of the Grodziec Beds (Upper Carboniferous), Upper Silesian Coal Basin, Poland[END_REF] whereas phyllocladane isomers are more predominant in Lower Carboniferous rocks (Viséan; [START_REF] Disnar | Biological origin of tetra-cyclic diterpanes, n-alkanes and other biomarkers found in Lower Carboniferous Gondwana coals (Niger)[END_REF].

Following the observations of [START_REF] Noble | A geochemical study of bicyclic alkanes and diterpenoid hydrocarbons in crude oils, sediments and coals[END_REF], the abundance of tetracyclic phyllocladanes and kauranes compared to the tricyclic abietane in our coals (Fig. 12) would point to a contribution of non-Medullosan pteridosperms. This is consistent with the spore content of these coals [START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF], and the described megaflora of Glenarbuck and Pettycur [START_REF] Scott | Distribution of anatomicallypreserved floras in the Lower Carboniferous in Western Europe[END_REF]. In addition, the abundance of ent-beyerane compared to ent-kaurane has been linked to a considerable contribution of Cordaites in late Carboniferous coals from France and Germany (e.g. [START_REF] Schulze | Structure and origin of terpenoid hydrocarbons in some German coals[END_REF][START_REF] Vliex | Aromatized arborane/fernane hydrocarbons as molecular indicators of floral changes in Upper Carboniferous/Lower Permian strata of the Saar-Nahe Basin, southwestern Germany[END_REF][START_REF] Fleck | Palaeoenvironmental assessment of Westphalian fluvio-lacustrine deposits of Lorraine (France) using a combination of organic geochemistry and sedimentology[END_REF][START_REF] Auras | Aromatized arborane/fernane hydrocarbons as biomarkers for Cordaites[END_REF]. According to these previous studies, the low abundance of ent-beyerane in the Scottish coals can therefore indicate the absence of Cordaites input. This agrees with an absence of Cordaites contribution in the palynological record [START_REF] Spinner | Megaspore assemblages from Viséan deposits at Dunbar, East Lothian, Scotland[END_REF][START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF][START_REF] Scott | Distribution of anatomicallypreserved floras in the Lower Carboniferous in Western Europe[END_REF], and the absence of the arborane/fernane derivatives MATH, MAPH DAPH1 and DAPH2 which have been recently suggested to be of Cordaites origin [START_REF] Auras | Aromatized arborane/fernane hydrocarbons as biomarkers for Cordaites[END_REF].

Similarly, abietane, retene, tetrahydroretene, bisnorsimonellite and simonellite (Figs. 13 and20) have been widely accepted as conifer biomarkers [START_REF] Van Aarssen | Higher plant biomarkers reflect palaeovegetation changes during Jurassic times[END_REF][START_REF] Hautevelle | Vascular plant biomarkers as proxies for palaeoflora and palaeoclimatic changes at the Dogger/Malm transition of the Paris Basin (France)[END_REF]. Actually, abietic acid, the major constituent of conifer resin, has been often considered as the biological precursor for retene and its related aromatic compounds [START_REF] Van Aarssen | Higher plant biomarkers reflect palaeovegetation changes during Jurassic times[END_REF][START_REF] Hautevelle | Vascular plant biomarkers as proxies for palaeoflora and palaeoclimatic changes at the Dogger/Malm transition of the Paris Basin (France)[END_REF].

However, most of these compounds, except abietane and bisnorsimonellite, have been recently identified in upper Silurian to lower Devonian sediments and are supposedly associated with early Palaeozoic bryophytes [START_REF] Romero-Sarmiento | Occurrence of retene in upper Silurian -Lower Devonian sediments from North Africa: Origin and implications[END_REF]. Following [START_REF] Ellis | Formation of isohexyl alkylaromatic hydrocarbons from aromatization-rearrangement of terpenoids in the sedimentary environment: A new class of biomarker[END_REF], the higher abundance of alkylphenanthrene compounds compared to isohexylalkylnaphthalenes in the Scottish coals (Fig 13 and19) could indicate a resin acid source. The presence of resinite macerals in both analysed samples (Fig. 4), though in low abundance, gives support to this interpretation. The hypothesis that abietic acid synthesis had already evolved in early land plants, prior to the emergence of true conifers [START_REF] Romero-Sarmiento | Occurrence of retene in upper Silurian -Lower Devonian sediments from North Africa: Origin and implications[END_REF] gains therefore support with this observation. Similarly, [START_REF] Bray | Identification of Carboniferous (320 Million Years Old) Class Ic Amber[END_REF] concluded that biosynthetic mechanisms specific to angiosperms had already appeared in the Late Carboniferous, far before the emergence of true angiosperms. 2-Methylretene is commonly associated with retene; it is only known from Permian and younger sediments and considered a conifer biomarker [START_REF] Bastow | 2methylretene in sedimentary material: a new higher plant biomarker[END_REF]. The diaromatic tricyclic totarane and sempervirane also typically co-occur with retene and related hydrocarbons. These biomarkers typically derive from a restricted number of conifer families: mostly Podocarpaceae and Cupressaceae [START_REF] Otto | Sesqui-, di-and triterpenoids as chemosystematic markers in extant conifers -A review[END_REF][START_REF] Cox | Oxygenated di-and tricyclic diterpenoids of southern hemisphere conifers[END_REF], though the totarane skeleton has been also observed in some angiosperms (e.g. [START_REF] Pinto | A new diterpene with a totarane skeleton from Vellozia flavicans[END_REF][START_REF] Clarkson | In vitro antiplasmodial activity of abietane and totarane diterpenes isolated from Harpagophytum procumbens (devil's claw)[END_REF] and a bryophyte (e.g. [START_REF] Wu | A Cyclic Peroxide of Clerodenoic Acid from the Taiwanese Liverwort Schistochila acuminata[END_REF].

In summary, most of the aliphatic and aromatic terrestrial biomarkers observed in the Scottish coals have been related to conifer families (Table 6). The oldest report of conifer megafossils is in the Late Carboniferous (Westphalian B/Late Bashkirian; [START_REF] Scott | The earliest conifer[END_REF] and the oldest occurrence of conifer-related saccate pollens is Early Bashkirian [START_REF] Zhou | Earliest pollen-dominated microfloras from the early Late Carboniferous of the Tian Shan Mountains, NW China: their significance for the origin of conifers and palaeophytogeography[END_REF], so that our coals predate the evolution of conifers. Other precursor(s) must therefore be proposed to explain the presence of "conifer biomarkers" in the Viséan Scottish coals. Cordaites are closely related to conifers and have been previously proposed as a source of supposedly typical conifer biomarkers (e.g. [START_REF] Disnar | Biological origin of tetra-cyclic diterpanes, n-alkanes and other biomarkers found in Lower Carboniferous Gondwana coals (Niger)[END_REF].

However, no data support the presence of Cordaites in the flora that contributed to our Scottish coals. An alternative origin for these compounds therefore must be found within the Viséan Scottish flora which was dominated by arborescent or sub-arborescent lycopsids (Lepidodendrales and Isoetales) with a contribution from ferns, sphenopsids and lyginopteridacean pteridosperms. Most of these groups of plants are extinct [START_REF] Taylor | Paleobotany: The Biology and Evolution of Fossil Plants[END_REF], so that direct comparison with present-day plants is not possible. Pteridosperms are the closest relatives to conifers identified in the Scottish Viséan coals [START_REF] Taylor | Paleobotany: The Biology and Evolution of Fossil Plants[END_REF], and therefore could have provided the "conifer biomarkers".

From the palynological content, pteridosperms were not dominant in the flora of the studied coals [START_REF] Spinner | Megaspore assemblages from Viséan deposits at Dunbar, East Lothian, Scotland[END_REF][START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF]; a palynological bias is possible, so that pteridosperm biomass would be underestimated in the palynological content (e.g. Phillips et al., 1985;[START_REF] Dimitrova | Palynology of late Westphalian-early Stephanian coal-bearing deposits in the eastern South Wales Coalfield[END_REF]. Pteridosperms, in particular, produced resin [START_REF] Taylor | Paleobotany: The Biology and Evolution of Fossil Plants[END_REF] and could be at the origin of the resinous secretions observed in our coal samples (Fig. 4C).

Lyginopteridacean pteridosperms probably appeared in the latest Devonian [START_REF] Taylor | Paleobotany: The Biology and Evolution of Fossil Plants[END_REF] but were preceded in the Middle Devonian by progymnosperms, which could therefore be considered for the origin of the "conifer biomarkers" observed in middle Devonian coals [START_REF] Sheng | Tetracyclic terpanes enriched in Devonian cuticle humic coals[END_REF][START_REF] Kashirtsev | Terpanes and steranes in coals of different genetic types in Siberia[END_REF]. Progymnosperms, however, were neither described in Chinese nor in Russian Middle Devonian coals [START_REF] Volkova | Nature and composition of the Devonian coals of Russia[END_REF][START_REF] Yi | The Xichong flora of Yunnan, China: diversity in late Mid Devonian plant assemblages[END_REF]. An alternative source for the "conifer biomarkers" are the arborescent lycopsids (Lepidodendrales) since palynologically, these plants dominated the Scottish flora [START_REF] Spinner | Megaspore assemblages from Viséan deposits at Dunbar, East Lothian, Scotland[END_REF][START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF]. Lepidodendrales already existed during the Devonian [START_REF] Taylor | Paleobotany: The Biology and Evolution of Fossil Plants[END_REF] and a recent palaeobotanical study showed that the Middle Devonian Chinese coals were dominated by Lepidodendrales and Protolepidodendrales [START_REF] Yi | The Xichong flora of Yunnan, China: diversity in late Mid Devonian plant assemblages[END_REF]. From these observations, arborescent lycopsids appear as another likely source for the so-called typical conifer biomarkers.

Conclusions

Numerous land-plant biomarkers have been identified in the aliphatic and aromatic fraction of the extracts of Early Carboniferous coals from Scotland. Among these compounds, several have been classically considered to be conifer-derived. However, micro and macrofossil evidence for conifers does not go further back than the Upper Carboniferous while palynological and palaeobotanical data indicate that these coals mainly derive from arborescent lycopsid (Lepidodendrales)-dominated forest. This discrepancy between the lipid and other fossil records leads to the following hypotheses:

1. Conifers had evolved already in the Early Carboniferous and this has now been evidenced with lipids.

2. The metabolic pathways giving rise to the observed biomarkers had evolved already in the Early Carboniferous in plants which are related to the conifers.

3. The identified biomarkers are derived from terrestrial plants which are not closely related to the conifers. This implies the evolution of a separate, possibly extinct, or as yet unidentified metabolic pathway for these and associated products.

An argument for hypothesis 3 is that retene, simonellite and tetrahydroretene -which are generally related to conifers -could also derive from the degradation of kaurane-type compounds synthesised by the early bryophytes. The Lower Carboniferous Scottish coals can be related to a flora dominated by arborescent lycopsids in conjunction with some ferns, sphenopsids and pteridosperms. Among these plants which are presently extinct, pteridosperms, which are relatively closely related to conifers, and arborescent lycopsids, which are not related to conifers, appear as the best possible sources for the "typical conifer" biomarkers. Therefore hypotheses 2 and 3 seem the most likely at present. F. R-S. acknowledges receipt of a scholarship (No. E07D402105VE) from the Programme Alβan. G. J. M.V. benefited from a position as invited professor at the Université Lille 1 (France) and a Heisenberg Stipend by the German Science Foundation (DFG). The authors are grateful to François Baudin (Université Paris 6) for performing the Rock-Eval and LECO analyses and to Brigitte Meyer-Berthaud (CNRS-UMR0931 AMAP) for helpful discussions in palaeobotany. This is a contribution to the ANR project "Global Perspectives on the Terrestrialization Process". The editor Finn Surlyk, Jørgen A. Bojesen-Koefoed, and an anonymous reviewer are acknowledged for constructive comments on the manuscript. [START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF][START_REF] Underhill | Controls on structural styles, basin development and petroleum prospectivity in the Midland Valley of Scotland[END_REF].

Figure captions

Fig. 2. The outcrop geological succession showing alternating

Carboniferous limestones, shales, sandstones and coals (modified from [START_REF] Spinner | Viséan spore assemblages from Skateraw, East Lothian, Scotland[END_REF]. 5.

Table captions

Table 1 Bulk and molecular geochemical parameters from Scottish coals.

Table 2

Petrographic composition and vitrinite reflectance.

Table 3

Bicyclic alkanes identified.

Table 4

Diterpenoid hydrocarbons identified.

Table 5

Aromatic hydrocarbons identified.

Table 6

Maturity indicators from aromatic fractions of Carboniferous coal samples.

Table 7

List of target saturated and aromatic land plant biomarkers and their origin.

Appendix

Mass spectra of unknown compounds (Peak assignments in Tables 2 and3).

Edinburgh

  fusinatus Spinner 1969, Lagenicula subpilosa (Ibrahim) forma major Dijkstra ex Chaloner 1954 and Setosisporites (Ibrahim) Potonié and Kremp 1954 emend. Spinner 1969. Miospores are less abundant in this lower interval and are dominated by the following taxa: Lycospora pusilla (Ibrahim) Somers 1972 with Calamospora spp.

Fig. 1 .

 1 Fig. 1. Simplified geologic map showing the outcrop sample positions at

Fig. 3 .

 3 Fig. 3. Plot of HI vs. T max values for Scottish coals (diagram from

Fig. 4 .

 4 Fig. 4. Photomicrographs of macerals. A) WS-3, reflected natural light.

Fig. 5 .Fig. 6 .

 56 Fig. 5. Total ion current chromatograms of the aliphatic fraction from

Fig. 7 .

 7 Fig. 7. Plot of Pr/n-C 17 vs. Ph/n-C 18 for Scottish coals (diagram from

Fig. 8 .

 8 Fig. 8. Mass chromatograms m/z 191 of aliphatic fractions from coal

Fig. 9 .

 9 Fig. 9. Mass chromatograms m/z 217 of aliphatic fractions from coal

Fig. 10 .

 10 Fig. 10. Steroids ternary plot. The contributions of C 27 , C 28 and C 29 steranes were calculated using the peak height of ααα (20R) and αββ

Fig. 11 .Fig. 12 .

 1112 Fig. 11. Partial m/z 109 + 123 + 179 + 193 mass fragmentograms

Fig. 13 .

 13 Fig. 13. Total ion current chromatograms of aromatic fraction from

Fig. 14 .

 14 Fig. 14. Partial m/z 142+156 mass fragmentograms showing the

Fig. 15 .

 15 Fig. 15. Partial m/z 170 mass fragmentograms showing the

Fig. 16 .

 16 Fig. 16. Partial m/z 184 mass fragmentograms showing the

Fig. 17 .

 17 Fig. 17. Partial m/z 178+192 mass fragmentograms showing the

Fig. 18 .

 18 Fig. 18. Partial m/z 206 mass fragmentograms showing the

Fig. 19 .Fig. 20 .

 1920 Fig. 19. Partial m/z 155 + 169 + 183 mass fragmentograms showing a

Fig. 4 .

 4 Fig. 4. Photomicrographs of macerals A) WS-3, reflected natural light. Vitrinite particles : telocollinite (Vt) and desmocollinite (Vd). B) Same zone as A, blue light fluorescence emphasizing exinite particles: fluorescing spores (S) and cuticles (C). C) SKT-E, blue light fluorescence. Exinite particles: fluorescing spores (S) and resinite (R) filling conducting canals in a vitrinite particle. D) WS-3, reflected natural light. Pyrofusinite (P) and spores (S) in a vitrinite (V) groundmass.

Horizon SC2 (Spinner and Clayton, 1973)

		STRATIGRAPHY
		250000 Barness East Limestone Geological members	300000 Succession Samples	350000
	U.K Midland Valley of Scotland	H i g h l a n d B o u n d a r y F a u l t Chapel Point Limestone
					700000
		Upper Skateraw Limestone			Dunbar
		Glasgow Middle Skateraw Limestone
					Skateraw Bay
					White Sand Bay
		Lower Skateraw Limestone
					650000
		Upper Longcraig Limestone	0	N	200 Km
			Sampling location
	S o u t h e r n U p l a n d s F a u l t Middle Longcraig Limestone	Carboniferous Carboniferous volcanic rocks Bashkirian -Kasimovian Serpukhovian Tournaisian -Visean Late Devonian Ordovician -Early Devonian 600000 Permian

21,022,0 23,0 24,0Retention Time (mins)

29,0 30,0 31,0 32,0Retention Time (mins)

Acknowledgements

The authors acknowledge financial support from the "ECLIPSE II and INSU 2009 -Terrestrialization" grant from the INSU department of CNRS. Thanks are extended to Dr. Charles Wellman (Department of Animal and Plant Sciences, University of Sheffield, U.K.) for guidance and assistance to M.V. during field work; this latter was funded by an exchange grant from "EGIDE Programme d'Actions Intégrées francobritanniques ALLIANCE" of the British Council and the Ministère des Affaires Étrangères of France, which is also gratefully acknowledged. M-


Mohamed-Hedi Karray

Zakaria Maamar
email: zakaria.maamar@zu.ac.ae

Towards a Self-Healing Approach to Sustain Web Services Reliability

Keywords: Web service, reliability, self-healing, case-based reasoning, AOP. I

Web service technology expands the role of the Web from a simple data carrier to a service provider. To sustain this role, some issues such as reliability continue to hurdle Web services widespread use, and thus need to be addressed. Autonomic computing seems offering solutions to the specific issue of reliability. These solutions let Web services self-heal in response to the errors that are detected and then fixed. Self-healing is simply defined as the capacity of a system to restore itself to a normal state without human intervention. In this paper, we design and implement a selfhealing approach to achieve Web services reliability. Two steps are identified in this approach: (1) model a Web service using two behaviors known as operational and control; and

(2) monitor the execution of a Web service using a control interface that sits between these two behaviors. This control interface is implemented in compliance with the principles of aspect-oriented programming and case-based reasoning.

INTRODUCTION

We all agree that the Web is dynamic by nature; new services are offered, some services cease to exist without prior notice, new business opportunities arise, etc. This nature puts a lot of pressure on those who are in charge of developing business applications that should be loosely coupled and spread over enterprises' organizational boundaries. Making Web services the technology of choice upon which these applications could be built would require looking into some issues, with emphasis on reliability in this paper, that still hinder the acceptance of Web services. Reliability is the ability to perform independently of the current execution circumstances, which permits to guarantee business continuity. To address Web services reliability, several works are reported in the literature [START_REF] Erradi | A broker-based approach for improving Web services reliability Web Services[END_REF]. Recently, self-healing seems leading these solutions [START_REF] Sa | Towards Autonomic Web Services:Achieving Self-Healing Using Web Services[END_REF][START_REF] Ben Halima | Providing Predictive Self-Healing for Web Services: A QoS Monitoring and Analysis-based Approach[END_REF]. In information technology, "self-healing describes any device or system that has the ability to perceive that it is not operating correctly and, without human intervention, make the necessary adjustments to restore itself to normal operation" 1 .

In [START_REF] Sheng | Separating Operational and Control Behaviors: A New Approach to Web Services Modeling[END_REF], we started examining the reliability of Web services through the use of two behaviors, which we denoted by control and operational. Both behaviors are specifically used to specify the functioning of a Web service and comply with separation of concerns principle. By doing this, the development and maintenance of Web services is made simple. On the one hand, the operational behavior illustrates the business logic that underpins the 1 (www.bitpipe.com/tlist/Autonomic-Computing.html) functioning of a Web service, i.e., how the functionality of a Web service is achieved. On the other hand, the control behavior guides in a controlled way the progress of executing the operational behavior (i.e., business logic) by stating the actions to take and the constraints to put on this progress. In this paper, we capitalize on both behaviors to let Web services self-heal and hence, achieve the reliability of the business applications they implement. Mainly injecting self-healing mechanisms into Web services should help in discovering, diagnosing, and reacting to disruptions that affect Web services operation [START_REF] Papazoglou | Service-Oriented Computing: State of the Art and Research Challenges[END_REF]. We discuss how our self-healing Web services are developed and oversee the progress of both behaviors towards completion.

Enhancing a system with self-healing capacities could be based on internal or external mechanisms [START_REF] Garlan | Model-based Adaptation for Self-Healing Systems[END_REF]. The former refer to trapping errors (includes exceptions: we consider an exception as an exceptional error) when happened like modern programming languages (e.g., Java exceptions, assertion checking) and run-time libraries (e.g., timeouts for RPC) do. The latter refer to monitoring a system using some "outsider" components (e.g., monitoring, recovery, etc.) that determine when a system's behavior is acceptable and whether self-healing should be initiated or not.

Given the black box nature of a Web service, its implementation details are only known to those who took part in its development. Therefore, these persons would be in charge of developing the self-healing functionalities as well [START_REF] Koopman | Elements of the Self-Healing System Problem Space[END_REF]. Since the external components' features (monitoring, recovery, etc.) are more attractive and effective [START_REF] Garlan | Model-based Adaptation for Self-Healing Systems[END_REF][START_REF] Wile | An Externalized Infrastructure for Self-Healing Systems[END_REF], we adopt an hybrid approach that combines the benefits of both internal and external mechanisms, by first, separating the external features of self-healing (monitoring, recovery, etc.) from the execution of the Web service (which is not the case with, for instance, Java exceptions), and second, encapsulating these features into modules that run internally and in parallel with the execution of the operations of the Web service.

In this paper, we propose a self-healing approach that is built upon a set of dedicated modules that would support the reliability of Web services. These modules are part of a "control interface'' that ensures the monitoring of a Web service's behavior, the catching of errors, and the recovery from these errors. The design of this control interface complies with Aspect-Oriented Programming (AOP) and Case-Based Reasoning (CBR) to benefit from the dynamic weaving principles and previous similar recovery cases in order to use previously adapted solutions.

Section 2 presents some related work on Web services self-healing. Section 3 suggests a motivating example to highlight the run-time errors problem that hinder Web services execution Section 4 presents our approach to set up the control interface. Section 5 discusses our implementation. A brief discussion about the approach is presented in section 6. Finally, Section 7 concludes the paper and sets guidelines for future work.

II. RELATED WORK

To make Web services the technology of choice when developing critical applications, it is important to enhance them with mechanisms that guarantee continuity of operations despite failure. Self-healing is among these mechanisms and could fall into the research theme of reliability as reported in [START_REF] De Lemos | ICSE 2003 Workshop on Software Architectures for Dependable Systems and self-healing[END_REF]. We identify two categories of works on the topic, works that are based on models and works that based on intelligence and technology.

Concerning the first category, we find the work presented by Dabrowski et al. who use architectural models to characterize how different elements such as architecture, topology, consistency-maintenance mechanism, and failure-recovery strategy could contribute to self-healing during communication failure [START_REF] Dabrowski | Understanding Self-healing in Service-Discovery Systems[END_REF]. In this specific failure and using notification as a consistencymaintenance mechanism, the authors divided self-healing properties into recovery techniques and topology. In [START_REF] Ben Halima | Providing Predictive Self-Healing for Web Services: A QoS Monitoring and Analysis-based Approach[END_REF], Ben Halima et al. propose a self-healing framework that is capable of managing Web services-based distributed interactive applications. This framework focuses on QoS monitoring and uses models for QoS analysis. In fact, the framework considers the communication level monitoring while intercepting exchanged SOAP messages and extending them with QoS parameter values. Glosh et al. classify self-healing systems based on similarities or relationships between approaches, mechanisms, architectures and technologies applied in these systems. In this classification, the authors indicate that such systems use models, whether external or internal, to monitor behaviors so these systems can adapt themselves to the run-time environment [START_REF] Ghosh | Self-healing systems: survey and synthesis[END_REF].

Regarding the second category, Gurguis et al. present an approach to achieve the autonomic computing of Web services. They divide Web services into functional Web services providing computing functionalities over the Internet, and autonomic Web services encapsulating atomic attributes such as self-configuration, self-healing, and self-optimization [START_REF] Sa | Towards Autonomic Web Services:Achieving Self-Healing Using Web Services[END_REF]. Monatni and Anglano present a CBR approach for providing large-scale, distributed software systems with self-healing capabilities [START_REF] Montani | Achieving Self-Healing in Service Delivery Software Systems by Means of Case-Based Reasoning[END_REF]. However, the approach does not use structured knowledge such as models of the system behavior, thus easing its applicability to large-scale in complex software systems. Friese et al. present the design and implementation of a Robust Execution Layer that acts as a transparent, configurable add-on to any BPEL4WS execution engine to support self-healing business processes. The continuity of process execution is achieved through service replacement in case of communication failures [START_REF] Friese | Self-Healing Execution of Business Processes Based on a Peer-to-Peer Service Architecture[END_REF]. Baresi and Guinea identify and classify the major faults in service-oriented systems and draw some solutions that allow recovery strategies using pre and post-conditions for the required and provided operations based on service and process description via BPEL [START_REF] Baresi | Towards Selfhealing Service Compositions[END_REF]. As for us, our approach is in another context. Indeed, given the black box nature of the web services, knowing the service behaviors (i.e., control and operational) is essential.

The EU SHADOWS can be considered as an hybrid work classified into the two categories. It concentrates on self-healing of complex systems using a model base approach [19]. The project introduces pioneering technologies such as the automatic concurrent debugging and the data race detection to enable the systematic selfhealing of failures classes and an approach to the integration of several self-healing technologies into a common framework solution. In this approach a gamebased model-checking technique is used to the verification and the adaptation task: the system acts as a player in a hostile world. Based on this model, if anything goes wrong, the system adapts its behavior to accomplish its task in a different way. The system doesn't try to recover the confronted problem. In our approach, when the service catches any error, it tries to recover the error in the aim to not change its behavior.

III. MOTIVATING SCENARIO

We choose WeatherWS whose functionality is to return a 5-day weather-forecast report on a certain city. In [START_REF] Sheng | Separating Operational and Control Behaviors: A New Approach to Web Services Modeling[END_REF], we argue why this Web service is not simple and can be used to illustrate different types of errors.

We assume that WeatherWS requires two inputs: city name and date. At run-time, one of the following cases happens knowing that WeatherWS searches the city's name in a dedicated database: [START_REF] Erradi | A broker-based approach for improving Web services reliability Web Services[END_REF]The access to the database fails; (2)The city requested does not exist in the database; (3)The city requested exists in the database; WeatherWS submits a report to the user.

The execution of WeatherWS can be reflected using different states. We refer to these states as business and use them to form the operational behavior of a Web service. "City located", "weather collected", and "report delivered" are examples of business states in the operational behavior of WeatherWS. This latter passes from one state to another subject to first, completing the operations that are included in each state and second, satisfying the transitions that connect states. To follow up the execution progress of a Web service, we use the control behavior along with a specific set of states that are extracted from the field of transactional Web services.

To achieve self-healing Web services, we look into the interactions occurring between these two behaviors. Different types of failure could lead to self-healing such as bugs in the business logic and resource removal.

IV.

OUR PROPOSED SELF-HEALING APPROACH

Our proposed self-healing approach for Web services takes place over two steps: how to model the behaviors of a Web service, and how to set up the self-healing mechanisms in terms of operation safety and error recovery at run-time. The identification of these mechanisms is built upon the closed-loop of Garlan et al. in the control system paradigm [START_REF] Garlan | Model-based Adaptation for Self-Healing Systems[END_REF] which consists to monitoring, interpretation, resolution and adaptation.

A. Behavior modeling

A behavior illustrates the actions that a Web service takes in response to some event occurrence and condition satisfaction. In [START_REF] Sheng | Separating Operational and Control Behaviors: A New Approach to Web Services Modeling[END_REF], the operational behavior shows the business logic that underlies the functioning of a Web service, and the control behavior guides the execution progress of the business logic (i.e., operational behavior) of this Web service. As briefly reported in Section 2, the control behavior uses a set of states that are reported in the literature of transactional Web services [START_REF] Maamar | Policies for Context-driven Transactional Web Services[END_REF]. The complete list of these states is as follows: "activated'', "notactivated'', "done'', "aborted'', "suspended'', and "compensated''. The state chart diagrams is use to represent both behaviors.

In addition to the control and operational behaviors, Maamar et al. developed mechanisms that support the interactions between them. These mechanisms are used to convey details from one behavior to another and vice versa. For example, a message from the control to the operational behaviors carryies a temporal event that permits to trigger the execution of a Web service.

The use of state chart diagrams to model the control and operational behaviors shows what should happen at run-time but does not permit to follow up the execution progress at the operation level. In fact, questions like which operation was recently executed, what dependency exists between operations, and what operation failed cannot be tracked if state chart diagrams are used. Any self-healing exercise requires a clear access to the operations that were executed and the operations that encountered problems [START_REF] Carzaniga | Self-Healing by Means of Automatic Workarounds[END_REF]. To overcome this limitation of state chart diagrams, we decided to use activity charts to model the operations of a Web service.

After modeling both behaviors, the next step consists of mapping some states in the control behavior of a Web service onto other appropriate states in the operational behavior as discussed in [START_REF] Sheng | Separating Operational and Control Behaviors: A New Approach to Web Services Modeling[END_REF].

The control and operational behaviors of a Web service are based on a finite set of sequences. In [START_REF] Sheng | Separating Operational and Control Behaviors: A New Approach to Web Services Modeling[END_REF], these sequences are called path and defined as follows: A path p i→j in a Web service behavior B is a finished sequence of states and transitions starting with state S i and finishing at state S j noted: p i→j = s i →(l i ) s i+1 →(l i+1 ) s i+2 . . .s j-1 →(l j-1 ) s j ; such that ∀k ∈ {i, j-1}:(s k , l k , k+1) ∈ T.

In the other hand, we define an execution scenario in a Web service as the association of a control state and a path in the operational behavior along with an execution priority defined by the developer of the Web service. This priority defines the recommended paths that need to be executed in order to satisfy a user's needs. Scenarios having the smallest value are considered as the more adequate to meet a user's expectations.

Also, a function Next was defined in [START_REF] Sheng | Separating Operational and Control Behaviors: A New Approach to Web Services Modeling[END_REF]. This function specifies in which control state the Web service must go after taking a final state in the operational path. We redefine this function to specify the control state that needs to be taken following the execution of a scenario.

Scenarios and Next function are used to oversee the progress of the execution of a Web service. Our selfhealing approach relies on the interactions that exist between behaviors and is built upon a control interface that drives these interactions.

B. Control Interface

Like any other program, Web services may be subject to events that could affect their normal execution progress. Our self-healing approach is based on a control interface (see Fig. 1) that contains the following modules: monitoring, interpretation, resolution, and adaptation. These modules support synchronization, verification, detection, and recovery.

In the control interface, the Mapping Module (MAM) is a repository of XML schemas and XML data that result from the mapping between the control and the operational behaviors. The MAM contains, also, additional elements such as matching paths, execution scenarios, and the results of the Next function. In addition, the MAM provides data regarding the expected behaviors during the execution of other modules to (i) instantiate the conversations between the two behaviors by the Conversation Management Module (CMM) or (ii) create recovery by the Error Recovery Module (ERM) in case of error.

In the control interface, the CMM instantiates, manages, and checks the conversational messages that are exchanged between the two behaviors. The CMM collects the scenario execution priority based on the current state in the control behavior of the Web service and initiates conversations with each state in the operational path that is included in this scenario. In this work we adapt the conversational messages that are reported by Maamar et al in [START_REF] Sheng | Separating Operational and Control Behaviors: A New Approach to Web Services Modeling[END_REF] like Sync, Success, Fail, Ack, just to cite some.

Through the management and monitoring of the different conversational messages that are exchanged, the CMM catches errors that interrupt the normal progress of the execution of a Web service. These errors are usually detected using Fail message. The CMM keeps track of different elements that help a Web service self-heal. These elements include (1) a component that instantiates conversations, (2) a list including all messages types, (3) details of messages related to the conversation in progress such as message Id, message origin, message destination, etc., and (4) log of the previous conversations. It should be noticed that there is a watchdog that monitors the messages of each conversation and raises alerts for the benefit of the CMM when it catches a failure message.

In the control interface, the Transition Management Module (TMM) comes into play before claiming the successful execution of a scenario. This claim depends on the operations to execute per state as well as the transitions that connect states. The TMM stores the intra-behavior transitions (i.e., transitions from one state to another in the same behavior) and all the information about the business operations (i.e., constraints, functioning description, implementation and execution). We define this information using pre-and post-conditions and constraints.

It should be noticed that the control interface does not address hardware failure problems that could affect client or server sides. Nevertheless, we designed the CI in a way that it records a Web service's execution states in case interruptions arise due to external events. We provided a buffer part of the TMM.

In the control interface, the ERM receives alerts of execution errors that CMM submits and takes corrective actions in response to these alerts. The implementation of these actions complies with the AOP principles [START_REF] Kiczales | Aspect-Oriented Programming[END_REF] by using the following three components: Aspects base, Patterns base, and Case base.

Aspects base. AOP is a paradigm that captures and modularizes concerns that split a software system into modules called Aspects. Aspects can be integrated into a system using dynamic weaving [START_REF] Bockisch | Virtual Machine Support for Dynamic Join points[END_REF]. An aspect contains different code fragments (advices) and location descriptions (pointcuts) to identify where code fragments should be plugged. Our use of AOP is motivated by the dynamic weaving of aspects. An aspect can be enabled and disabled at run-time. In our self-healing approach, we define a base that contains different types of aspects that could characterize the different errors during a Web service execution. These aspects are triggered by an aspect weaver that exists in the TMM when an error arises. We identify aspects with a triple (Name of the module including the aspect, Set of advices, Set of pointcuts).

Patterns base. It is a container of execution patterns for business operations. Each business operation is associated with a set of execution patterns. A pattern is used to decompose an operation into segments according to a certain semantics and implementation constraints. We define three types of patterns. Two are defined at design time (normal patterns and error patterns) and one at run time.

Case base. It contains cases of errors along with their solutions. Whenever the ERM receives an alert, it creates a new solution by assembling an error pattern with an aspect and records this case in the base if it does not already exist. A case is characterized by the 3-uplet <Sy, Con, R> where Sy presents sets of the problem symptoms and the "error patron"; Con is the case context, that means which aspect in which business operations; R is the carried out treatment i.e. resolution made.

When the ERM receives an alert, it recovers the execution scenario from the MAM as well as the details from the fail message that is related to the control state. This indicates that there is an execution problem that the CMM reports. First, the CMM starts to synchronize itself with the MAM and TMM to retrieve information related to the current scenario and the operations in the control state that is affected by this error. The ERM consults its base of patterns in order to compare the Log pattern received with "normal'' and "error'' patterns so that the aspect related to this error is detected. If the pattern is already in the database, the ERM consults its base cases to see if a similar error has already been treated and solved. If yes, the ERM sends a solution to the CMM and the TMM for deployment.

Otherwise, if it is not according to this pattern and the base of aspects, the ERM selects the associated aspect. Then the ERM sends the solution to the TMM module to apply it. In the case where the Log pattern does not exist in the error patterns list, the ERM adds this new pattern to the patterns base and sends an alert to the Web Service developer, asking its (new pattern) assignment to one or many aspect. After the application of the solution, the ERM updates its case base.

V. EXPERIMENTS

The feasibility of our self-healing approach was tested by implemenying the control interface. We used C # from .Net beta 2005 platform to program the different modules and XML to define behaviors, conversation messages, execution scenarios, patterns, and last but not least the manipulated data at run time.

Fig.2. Prototype architecture

Our experiments started by injecting errors to check the mechanisms for error detection and aspect activation. An example of error was an empty object (NULL) that was returned following the execution of "weather collection'' operation and then submitted to another operation namely "report delivery''. Our prototype catches, collects, and locates the error, identifies the appropriate error pattern, and finally determines the aspect that is associated with this error. All this happens without propagating the error to the client. We are now working on the injection of the set of advices related to aspects, to test the reaction of the web service behavior after this modification.

The prototype architecture as Fig. 2 presents is decomposed in two layers: "system layer" and "resource layer". The running system consists of two components: "service execution" and "control interface". An internally exchange for instantiation, monitoring and recovery (i.e. aspects injection) is made in the running system between the two components. The control interface is connected to the different XML data bases (Scenarios, Aspects, Patterns, Cases) managed by its modules.

VI. DISCUSSIONS

When it comes to self-healing, several requirements are suggested in the literature such as adaptability, dynamicity, and autonomy [START_REF] Mikic-Rakic | Architectural Style Requirements for Self-Healing Systems[END_REF]. We took into account these requirements while working on our approach to selfheal Web services. For example, the Web services adapt their course of actions in reaction to the errors that are detected. We, also, took into account other guidelines such as failure detection, fault diagnosis, fault healing, and validation [START_REF] Gorla | Towards Design for Self-healing, Fourth international workshop on Software quality assurance[END_REF]. The purpose of these guidelines is to attempt the completeness, soundness, and robustness of any self-healing approach. If one of these guidelines is not satisfied, the usability of the approach can be questioned. The externalization of self-healing mechanisms is generic in dealing with multiple Web services at once. This approach coupled with the black box nature of Web services increases the complexity of making them selfheal independently of any human assistance [START_REF] Montani | Achieving Self-Healing in Service Delivery Software Systems by Means of Case-Based Reasoning[END_REF], contrarily to the internal approach that is specified within the Web service itself. This approach relies on the knowledge of a Web service's behaviors. Although most of the aforementioned works adopt an external approach, we adopted an hybrid approach taking advantage of both approaches' benefits through the use of first, the closed loop that the external approach offers [START_REF] Garlan | Model-based Adaptation for Self-Healing Systems[END_REF] and second, the visibility and controllability elements that the internal approach offers [START_REF] Gorla | Towards Design for Self-healing, Fourth international workshop on Software quality assurance[END_REF]. Visibility is the ability to observe states, outputs, and resource usage during a Web service execution. Controllability is the ability to modify inputs and states during service running, to study different behaviors, and what-if situations. Hence, given the black box nature of a Web service, these two functionalities cannot be ensured only by an internal approach. To this purpose, our approach is based on modeling Web service behaviors. It implements a model-based approach, where models of a desired Web service behavior governs the self-healing process throughout the service design and implementation phase and the service deployment phase as used in the EU SHADOWS project [19]. We based our approach on two types of models: control/operational and fault. The control/operational model specifies the nominal behavior that must be satisfied by the Web service and provided by the Web service developers. This model ensures the behavior synchronization in order to facilitate the monitoring, control of states, and fault localization. The fault model specifies the types of faults that can be identified and repaired by our control interface. We specifically address fault types related to aspects, which were designed and implemented in a separated module in of this control interface.

In term of CBR, our approach differs from the work of Montani and Anglano in [START_REF] Montani | Achieving Self-Healing in Service Delivery Software Systems by Means of Case-Based Reasoning[END_REF]. These ones infer new cases from previous resolutions using similarity mechanisms. Contrarily, in our approach we verify if a case is resolved before any similarity reasoning is carried out. In the future, we aim at enhancing this part to handle the cases that require more than one repair action.

Regarding the effectiveness of our approach, we could not evaluate it in this paper which applies only the feasibility and implementation aspects. All other points such as the calculation of metrics will be addressed in future work.

VII. CONCLUSION

Self-healing is one of the important elements that could enhance the reliability of Web services [START_REF] Gorla | Towards Design for Self-healing, Fourth international workshop on Software quality assurance[END_REF]. In this paper, we examined self-healing Web services by first, describing their control and operational behaviors and second, implementing a control interface that oversees the performance of these Web services and takes corrective actions when necessary. This interface was implemented in compliance with the principles of aspect-oriented programming and case-based reasoning.

Our future work revolves around different aspects. Firstly, we will continue enhancing the prototype to conclude additional tests about WeatherWS, and more examples of real Web services will be developed to identify the failures that are not detected as expected. Secondly, we would like to make the control interface ``learn'' new patterns and study failure possibilities using proactive and predictive methods to predict when a failure would occur so that corrective actions are taken. Moreover, we plan to apply our proposed self-healing approach to the composition level by looking into the combination of the respective self-healing mechanisms of component Web services.

Fig. 1 .

 1 Fig.1. Self-healing architecture