Keywords: digestibility, fecal crude protein, near infrared reflectance spectroscopy, sheep, tropical grass

Comparison of fecal crude protein and fecal near-infrared reflectance spectroscopy to predict digestibility of fresh grass consumed by sheep

Audrey Fanchone, Harry Archimède, Maryline Boval

ABSTRACT: Organic matter digestibility (OMD), an essential criterion for the evaluation of the nutrition of ruminants, cannot be measured easily at pasture. Therefore, the objective of this study was to test and compare 2 methods of OMD prediction based on the fecal CP content (CPf) or near infrared reflectance spectroscopy (NIRS) applied to feces. First, published equations derived from fecal N (Eq. 1 CP , n = 40) and from fecal NIRS (Eq. 1 NIRS , n = 84) were used to predict OMD of an independent validation data set from which in vivo OMD, ranging from 58 to 74%, was measured for 4 regrowth stages of Digitaria decumbens. Second, to establish equations usable in grazing situations and to improve the efficiency of the predictions, new equations were calculated from a large data set (n = 174) using CPf (Eq. 2 CP ) or fecal NIRS (Eq. 2 NIRS ). By applying the CPf method, Eq. 2 CPf (OMD, % = 88.4 -263.9/CPf, % of OM; residual SD = 2.92, r2 = 0.63) showed similar statistical parameters (P < 0.01) when compared with Eq. 1 CP (OMD, % = 86.6 -266.2/CPf, % of OM; residual SD = 2.95, r 2 = 0.79). When using fecal NIRS, Eq. 2 NIRS showed decreased SE of calibration (SEC = 1.48) and of cross-validation (SECV = 1.75) and greater coefficient of determination of crossvalidation (R 2 CV = 0.85) than the previously published Eq. 1 NIRS (SEC = 1.78, SECV = 2.02, R 2 CV = 0.77). The validation of the 4 equations on the validation data set was satisfactory overall with an average difference between the predicted and the observed OMD ranging from 0.98 to 2.79 percentage units. The Eq. 2 NIRS was nevertheless the most precise with a decreased residual SD of 2.53 and also the most accurate, because the SD of the average difference between predicted and observed OMD was the lowest. Therefore, fecal NIRS provided the most reliable estimates of OMD and is thus a useful tool to predict OMD at pasture. However, an adequate number of reference data are required to establish good calibration. Indeed, better calibration statistics were obtained by increasing the data set from 84 (Eq. 1 NIRS ) to 174 (Eq. 2 NIRS ). In contrast, using fecal N on a set of 84 or 174 points did not improve the prediction. Both methods are useful for predicting OMD at pasture in certain circumstances, using fecal NIRS when a large data set (n = 84 and n = 174) is available and fecal CP with smaller data sets (n = 40).

INTRODUCTION

Digestibility of OM is one of the most important characteristics used to evaluate feed nutritional quality. For grazing animals, OM digestibility (OMD) cannot be determined directly, unlike for stall-fed animals, where direct determination by quantitative measurements of ingested forage and fecal excretion can be accomplished. Therefore, several indirect assessment methods have been developed from forage or fecal samples. Methods based on forage samples such as in vitro or in sacco degradability of hand-plucked herbage may introduce bias in digestibility estimation because hand-plucked herbage may not be representative of the herbage grazed because of diet selection by grazing animals [START_REF] Baumont | How forage characteristics influence behaviour and intake in small ruminants: A review[END_REF][START_REF] Schlegel | Grazing methods and stocking rates for direct-seeded alfalfa pastures: II. Pasture quality and diet selection[END_REF]. Methods based on esophageal fistula samples have then been used to overcome the inaccuracy of hand-plucked samples (Le [START_REF] Du | Animal-based techniques for estimating herbage intake[END_REF]. However, these methods require the surgical alteration of experimental animals, which is impractical in production situations and can be undesirable from an animal welfare point of view.

Methods to predict OMD based on fecal profiling, including regression with fecal CP (CPf) content [START_REF] Wehausen | Fecal measures of diet quality in wild and domestic ruminants[END_REF][START_REF] Boval | The ability of faecal nitrogen to predict digestibility for goats and sheep fed with tropical herbage[END_REF] and near infrared reflectance spectroscopy (NIRS) applied to feces (Coates, Comparison of fecal crude protein and fecal near-infrared reflectance spectroscopy to predict digestibility of fresh grass consumed by sheep 1 A. Fanchone, H. Archimède, and M. Boval 2 INRA, UR143, Unité de Recherches Zootechniques, 97170 Petit-Bourg Guadeloupe, French West Indies 1999; [START_REF] Landau | Monitoring nutrition in small ruminants with the aid of near infrared reflectance spectroscopy (NIRS) technology: A review[END_REF], have provided consistent estimates of OMD. Therefore, the aim of this study was to examine the potential of fecal indices based on fecal CP or fecal NIRS to predict OMD in grazing situations. A 2-step procedure was employed. First, existing published equations derived from fecal CP [START_REF] Boval | The ability of faecal nitrogen to predict digestibility for goats and sheep fed with tropical herbage[END_REF] and from fecal NIRS [START_REF] Fanchone | Faecal indices based on near infrared spectroscopy to assess intake, in vivo digestibility and chemical composition of herbage ingested by sheep (crude protein, fibres and lignin content)[END_REF] were used to predict OMD of a small independent validation data set. Second, a larger calibration data set was created to further assess the applicability of these 2 fecal-based methods to predict OMD in a variety of Pangola grass pastures.

MATERIALS AND METHODS

Care and use of animals were performed according to the Certificate of Authorization to Experiment on Living Animals issued by the French Ministry of Agriculture, Fishing, and Feeding.

Validation Data Set

The validation data set (VDS, n = 23) came from an independent trial carried out in 1996 at the animal experimental station of the Institut National de la Recherche Agronomique (INRA) in the French West Indies (Guadeloupe, latitude 16°16´ N, longitude 61°30´ W). This trial was designed to evaluate variations in nutritive values of Pangola grass (Digitaria decumbens) according to various stages of regrowth [START_REF] Archimède | Effect of regrowth age on intake and digestion of Digitaria decumbens consumed by black-belly sheep[END_REF]. This data set was retained for validation because of its large range in values for OMD. Six adult Martinik rams (40.8 ± 0.6 kg of BW) were fed 14-, 28-, 42-, and 56-d-old fresh regrowth of Pangola grass during 4 successive experimental periods. The regrowth stages of 14, 28, 42, and 56 d were used during periods 1, 2, 3, and 4, respectively. The plots intended to be used at 14, 28, 42, and 56 d of regrowth were divided into 15, 30, 30, and 30 subplots respectively. The first of the 15, 30, 30, and 30 subplots had been cut 15, 29, 43, and 57 d before the beginning of the experimental period 1, 2, 3, and 4, respectively. One subplot was cut per day, so that each subplot had 1 d more than the subplot cut the day before and 1 d less than the subplot cut the following day. Consequently, the regrowth stage of the subplot intended to be harvested daily was exactly 14, 28, 42, and 56 d in period 1, 2, 3, and 4, respectively. For the 4 stages of regrowth (14, 28, 42, and 56 d), the concentration (% of DM) of OM was 84, 89, 90, and 88;CP was 13.0, 7.9, 7.2, and 5.7;NDF was 74, 78, 79, and 79;and ADF was 38, 43, 44, and 44, respectively (Archimède et al., 2000). In the 56-d treatment, 1 ram having a very low intake level (30% less than the average intake of the group) was removed. Each experimental period consisted of 14 d of adaptation to the diet, followed by 5 d of intake and total-tract digestibility measurements. The grass was cut daily, early in the morning, and chopped (to a 5-cm length) before being offered. The amount of forage provided was 1.15 × animal voluntary intake estimated during the adaptation period. Digestibility was calculated per animal by weighing the daily amounts of forage offered, the refusals, and feces excreted. Dry matter contents of fresh forage and refusals were determined daily by drying for 72 h at 60°C [START_REF] Cochran | Measurement of in-vivo forage digestion by ruminants[END_REF]. A representative subsample of feces excreted was obtained by pooling 10% of the daily amount of feces excreted per animal. Subsamples of feces were stored at -20°C until DM content determination. Dry matter content of fecal subsamples was determined in similar conditions as described previously for fresh forage and refusals. Samples were ground to a 0.75-mm particle size using a cross beater mill SK 100 (Retsch, Haan, Germany). Ground samples were then stored in closed plastic containers before chemical analyses. Organic matter content of forage and fecal samples was measured after an 8-h pyrolysis at 550°C to estimate OMD according to the reference procedure of [START_REF] Cochran | Measurement of in-vivo forage digestion by ruminants[END_REF]. Nitrogen concentration of feces was determined using the Dumas method [START_REF] Aoac | Official Methods of Analysis[END_REF]. Crude protein content of feces was calculated by multiplying the N concentration by 6.25. Approximately 2.5 g of ground fecal sample was packed in a ring-cup sample cell with a near infrared, transparent, quartz cover glass [START_REF] Foss | WinISI II training handbook[END_REF]. Cells were scanned 32 times using a scanning reflectance monocromator (NIRSystem 6500 Inc., Silver Springs, MD). Reflectance energy [log (1/R), where R = reflectance] was measured and averaged over the 32 scans. The average spectra of absorbance were recorded at 2-nm intervals over the wavelength range 700 to 1,100 and 1,100 to 2,500 nm. Only the near infrared region was used for calibration.

Calibration Data Set

A large data set (LDS, n = 174) was made from 4 digestibility trials carried out in stalls from 1997 to 2000. All trials were conducted at the animal experimental station at INRA in Guadeloupe (French West Indies). The effects tested through the different trials were mainly the leaf-stem proportion of the ration, the regrowth stage of the herbage, or the physiological stage of the animals (H. Archimède, unpublished data). In all trials, adult Martinik rams (45.1 ± 0.31 kg of BW) were fed fresh Pangola.

Determination of OM content of forage and feces, estimation of in vivo OMD, calculation of CPf, as well as recording of the absorbance spectra of fecal samples were as described previously for the VDS.

Calculations and Statistical Analysis

Existing predicting equations of OMD, derived from CPf (Eq. 1 CP ;[START_REF] Boval | The ability of faecal nitrogen to predict digestibility for goats and sheep fed with tropical herbage[END_REF] and from fecal NIRS (Eq. 1 NIRS ;[START_REF] Fanchone | Faecal indices based on near infrared spectroscopy to assess intake, in vivo digestibility and chemical composition of herbage ingested by sheep (crude protein, fibres and lignin content)[END_REF], were used to predict OMD of the VDS. New equations, based on CPf (Eq. 2 CP ) or fecal NIRS (Eq. 2 NIRS ), were developed from the LDS and were used to predict OMD of the VDS. The equation Eq. 2 CP was calculated according to a hyperbolic model (OMD = a -b/CPf) as proposed by [START_REF] Boval | The ability of faecal nitrogen to predict digestibility for goats and sheep fed with tropical herbage[END_REF], because it has been observed to be more precise than linear or quadratic models. The MIXED procedure (SAS Inst. Inc., Cary, NC) was used to account for the fixed effects of experiment (4 experiments) and the random effect of rams within each experiment (4 to 6 rams per experiment). The stage of regrowth was added as a covariate. The intercept and the slope of Eq. 2 CP were compared with that of Eq. 1 CP using the Neyman-Pearson test.

Before calibration, absorbance spectra of the LDS were transformed using standard normal variate and detrend scatter correction and 2 mathematical pretreatments: 1.4.4. and 2.5.5. using ISI software (Infrasoft International, Port Matilda, PA), where the first number is the order of derivatization of spectral data, the second number is the gap over which the derivative is to be calculated, and the third number is the smoothing factor. The mathematical treatment 2.5.5. yielded superior calibration statistics, namely reduced SE of calibration (SEC), decreased SE of cross-validation (SECV), greater multiple coefficient of determination (R 2 ), and greater R 2 of cross-validation (R 2 CV ), and this treatment was retained rather than treatment 1.4.4. The SEC represents the variability in the difference between predicted values and reference values when the equation was developed from the calibration data set. The SECV represents the variability in the difference between predicted and reference values when the equation is applied sequentially to subsets of data from the calibration data set [START_REF] Landau | Monitoring nutrition in small ruminants with the aid of near infrared reflectance spectroscopy (NIRS) technology: A review[END_REF]. Cross-validation is often employed when an independent validation set is unavailable or when removal of samples from a calibration set results in too few samples for effective equation development. Briefly, this process involves removing a certain number of samples during the calibration procedure; for example, 25%, and predicting these with the remaining 75%. This step is then repeated until all have served as validation samples. Cross-validations were based on splitting the sample population into 6 groups to select the optimum number of terms (i.e., principal components or eigenvectors) without over-fitting. The combined SE for each of these steps is the SECV. The equation Eq. 2 NIRS to predict OMD was derived by processing pretreated fecal spectra of the LDS using modified, partial, least squares regression (ISI, 1999) because this technique has proven superior to other methods (principal component regression or stepwise multiple linear regression) in earlier research [START_REF] Shenk | Population definition, sample selection, and calibration procedures for near infrared reflectance spectroscopy[END_REF][START_REF] Park | The use of near infrared reflectance spectroscopy on dried samples to predict biological parameters of grass silage[END_REF][START_REF] Park | The use of near infrared reflectance spectroscopy (NIRS) on undried samples of grass silage to predict chemical composition and digestibility parameters[END_REF].

The predicted values of OMD for the VDS, starting from the 4 equations described above (Eq. 1 CP , Eq. 1 NIRS , Eq. 2 CP , and Eq. 2 NIRS ), were compared with the observed values. The precision of estimation was evaluated from the absolute difference (Dpo) between the predicted OMD and the observed OMD. Factorial analyses of variance was computed to determine the influ-ence on Dpo of the main factors of variation in the VDS [START_REF] Archimède | Effect of regrowth age on intake and digestion of Digitaria decumbens consumed by black-belly sheep[END_REF], the regrowth stage (14, 28, 42, and 56 d), and animals using the GLM procedure (SAS Inst. Inc.). The SECV of the fecal NIRS equations and the SD of the different equations were compared using a Fisher test.

RESULTS

In the VDS, OMD and CPf variation (about 26 and 84%, respectively) was mainly due to regrowth stage of the grass used in the study (Figure 1; Table 1). In this set of data, OMD and CPf varied over a broader range (15 and 9%, respectively) compared with the data used to establish Eq. 1 CP (which varied by 12 and 6% for OMD and CPf, respectively). In addition, variation in OMD and CPf in the VDS was less than in the other 2 data sets used to establish Eq. 1 NIRS and Eq. 2 NIRS . The LDS used to establish Eq. 2 NIRS presented the most significant variation for the 2 variables (a range of approximately 28% for OMD and 12% for CPf).

For CP equations, experiment, animal, and stage of regrowth were not significant (P > 0.10) for the equation Eq. 2 CP (P > 0.10; Table 2). The a and b values of Eq. 2 CP were not significantly different (P > 0.05) from those of the equation Eq. 1 CP based on the Neyman-Pearson test. Similar residual SD were achieved for both equations (P > 0.05), whereas r 2 was less for Eq. 2 CP . For fecal NIRS equations derived from the LDS, better calibration and cross-validation statistics (decreased SEC and SECV, P < 0.05; greater R 2 and R 2 cv; Table 3) were obtained for Eq. 2 NIRS than for Eq. 1 NIRS .

Using CPf equations to predict OMD from the VDS, we obtained a residual SD numerically greater for Eq. 1 CP compared with Eq. 2 CP (Table 4; Figure 2). The differences between the observed and predicted values were numerically less with Eq. 1 CP compared with Eq. 2 CP . Similarly, the SD of the difference was proportionally larger for Eq. 1 CP compared with Eq. 2 CP . The ef- fects of regrowth stage and animal were significant (P < 0.05) on the Dpo (Table 4) for the 2 equations Eq. 1 CP and Eq. 2 CP . Using fecal NIRS to predict OMD of the VDS, we obtained a greater residual SD with Eq. 1 NIRS compared with Eq. 2 NIRS (P < 0.09; Table 4 and Figure 3). For Eq. 1 NIRS , the mean difference between predicted OMD and observed OMD was decreased compared with Eq. 2 NIRS , but the SD was proportionally greater with Eq. 1 NIRS compared with Eq. 2 NIRS (Table 4). The effect of both stage of regrowth and animal was highly significant (P = 0.02 and P = 0.003 for the effect of stage of regrowth and animal, respectively) for Eq. 1 NIRS , whereas only the animal effect was significant on Dpo for the Eq. 2 NIRS (P = 0.009). Considering the SECV of Eq. 2 NIRS (Table 3) and the numerically less SD of the equation predicting OMD by using Eq. 2 NIRS , this equation is more precise.

DISCUSSION

Fecal CP Equations

Fecal CP equations allow precise prediction of in vivo OMD. Residual SD obtained using Eq. 2 CP was numerically less than the residual SD obtained with other methods aimed at predicting in vivo OMD from forage (from 3.2 to 5.1%, [START_REF] Kitessa | Comparison of methods used to predict the in vivo digestibility in ruminants[END_REF]; from 2.4 to 5.0%, [START_REF] Gosselink | Prediction of forage digestibility in ruminants using in situ and in vitro techniques[END_REF] and slightly greater than those of CPf equations using hyperbolic models (2.5%, [START_REF] Boval | Evaluation des indicateurs fécaux pour prédire la digestibilité et les quantités ingérées de dichantium sp par de bovins créoles[END_REF] or exponential models (2.7%, [START_REF] Lukas | Relationship between fecal crude protein concentration and diet organic matter digestibility[END_REF]. By increasing the range of OMD and CPf using the LDS, we expected to increase the predictive ability of Eq. 2 CP compared with the published Eq. 1 CP of [START_REF] Boval | The ability of faecal nitrogen to predict digestibility for goats and sheep fed with tropical herbage[END_REF] but that was not the case. The values of a and b were not significantly different between the 2 fecal CP equations. The similarity between the 2 CPf equations may be explained by the hyperbolic model retained to derive the 2 equations. This model is assumed to describe the biological relationship between OMD and CPf, as described by [START_REF] Lancaster | Estimation of digestibility of grazed pasture from faeces nitrogen[END_REF], and can be used outside of its range of establishment [START_REF] Lancaster | Estimation of digestibility of grazed pasture from faeces nitrogen[END_REF][START_REF] Wehausen | Fecal measures of diet quality in wild and domestic ruminants[END_REF][START_REF] Boval | The ability of faecal nitrogen to predict digestibility for goats and sheep fed with tropical herbage[END_REF]. Thus, although the range of variation of data from [START_REF] Boval | The ability of faecal nitrogen to predict digestibility for goats and sheep fed with tropical herbage[END_REF] is less than the range of the LDS, Eq. 1 CP was capable of adequately describing this biological relationship, giving valid a and b values throughout the entire range of OMD and CPf in the VDS. Hence, the similarity of our 2 equations based on CPf means that it is not absolutely necessary to develop local equations for Pangola grass, in a fixed range of variation, as reported by Le [START_REF] Du | Animal-based techniques for estimating herbage intake[END_REF] and [START_REF] Armstrong | The prediction of the in vivo digestibility of the diet of sheep and cattle grazing indigenous hill plant communities by in vitro digestion, faecal nitrogen concentration or "indigestible" acid-detergent fibre[END_REF]. In fact, different researchers employed linear or quadratic models, which tended to overestimate the OMD for increased values of CPf, whereas the hyperbolic or exponential models used by [START_REF] Wehausen | Fecal measures of diet quality in wild and domestic ruminants[END_REF], [START_REF] Boval | Evaluation des indicateurs fécaux pour prédire la digestibilité et les quantités ingérées de dichantium sp par de bovins créoles[END_REF][START_REF] Lukas | Relationship between fecal crude protein concentration and diet organic matter digestibility[END_REF] better explain the biological relationship between OMD and CPf. Thus, equations established under a fixed range can have a wider range of application, and methods based on CPf may be more powerful than expected.

The prediction could be improved by using additional predictors, although [START_REF] Boval | The ability of faecal nitrogen to predict digestibility for goats and sheep fed with tropical herbage[END_REF] and [START_REF] Lukas | Relationship between fecal crude protein concentration and diet organic matter digestibility[END_REF] explored, unsuccessfully, the fiber content of the herbage or feces and the CP content of herbage. Another possible improvement would be to better describe the biological relationship between OMD and CPf. Fecal CP is composed of 2 fractions: 1) the undigested dietary protein and 2) the metabolic fecal protein, including bacterial and endogenous protein [START_REF] Lancaster | Estimation of digestibility of grazed pasture from faeces nitrogen[END_REF][START_REF] Wehausen | Fecal measures of diet quality in wild and domestic ruminants[END_REF][START_REF] Ferri | In vivo digestibility of kleingrass from fecal nitrogen excretion[END_REF]. These Table 1. Descriptive statistics for OM digestibility (OMD) and fecal CP (CPf) in the validation data set, the data set of [START_REF] Boval | The ability of faecal nitrogen to predict digestibility for goats and sheep fed with tropical herbage[END_REF], the data set of [START_REF] Fanchone | Faecal indices based on near infrared spectroscopy to assess intake, in vivo digestibility and chemical composition of herbage ingested by sheep (crude protein, fibres and lignin content)[END_REF] Fecal indices methods to assess digestibility authors state that the biological relationship between OMD and CPf is linked to the metabolic fecal protein fraction. However, the opinions are divided concerning the respective role of bacterial and endogenous fractions and even on the proportion of these fractions in metabolic fecal protein. Therefore, an evaluation of the various sources of CPf and their respective relationship with OMD should improve the ability to predict OMD via fecal-based calibrations. Further experiments are required to better understand the relationship between the different CPf fractions.

Fecal NIRS Equations

The prediction of OMD by fecal NIRS using the LDS was as expected and confirmed the potential of this indirect method to assess in vivo OMD for grazing animals. Contrary to CPf equations, the precision of fecal NIRS equations increased by using a larger data set. The Eq. 2 NIRS calculated from the LDS was more precise than Eq. 1 NIRS derived from a smaller data set. Enlarging the data set increased variability in spectral proper-ties, which led to an increase in precision of prediction. In addition, using the LDS expanded the prediction potential of the equation, particularly for low OMD values (<0.60). For NIRS to be used successfully, it is essential that the sample and reference data cover all sources of variation likely to be encountered in routine analysis [START_REF] Kitessa | Comparison of methods used to predict the in vivo digestibility in ruminants[END_REF]. Statistics of calibration for Eq. 2 NIRS were thus better than those previously published. Indeed, SEC of 2.26 and 2.2, and R2 of 0.94 and 0.72 were reported, respectively, by [START_REF] Krachounov | Application of near infrared spectroscopy (NIRS) in the analysis of feces from sheep for estimation of forage digestibility and energy feeding value[END_REF] for sheep fed an array of forage, and [START_REF] Boval | Faecal near infrared reflectance spectroscopy (NIRS) to assess chemical composition, in vivo digestibility and intake of tropical grass by creole cattle[END_REF] for cattle fed tropical grasses.

Validation

The 2 CPf equations provided good estimates of in vivo OMD of the VDS. The precision of prediction using Eq. 1 CP or Eq. 2 CP on the VDS were close, although Eq. 2 CP presented a slightly smaller residual SD. The variation of the difference between predicted and observed values was less for Eq. 1 CP compared with Eq. 2 CP , indicating a more robust prediction. However, both CPf equations overestimated the decreased values of OMD measured for 42 and 56 d of regrowth. If studies agreed on the existence of a biological relationship between OMD and CPf, they also agreed on the fact that undigested dietary protein adversely affects this relationship [START_REF] Lukas | Relationship between fecal crude protein concentration and diet organic matter digestibility[END_REF][START_REF] Schlecht | Estimating the digestibility of sahelian roughages from faecal crude protein concentration of cattle and small ruminants[END_REF]. When digestion of dietary CP is constrained, the undigested dietary protein fraction of CPf increases and induces an artificial increase in the OMD prediction.

Particularly, tropical forages are known to be resistant to digestion because they mature rapidly. High fiber content of tropical forage may restrict CP digestion in the rumen leading to an increase of undigested dietary protein. For example, [START_REF] Archimède | Effect of regrowth age on intake and digestion of Digitaria decumbens consumed by black-belly sheep[END_REF] reported a decrease in the apparent total-tract CP digestibility from 0.67 to 0.32 for 14-and 56-d regrowth of Pangola grass, respectively. This decreased CP digestibility for more mature forage can generate increased fractions of undigested dietary protein in feces and an overestimate of the prediction of OMD by the CPf method. Fecal NIRS equations provided more rewarding estimates of in vivo OMD of the VDS than CPf equations. The Eq. 2 NIRS had the least residual SD of the 4 equations tested and appears to be more precise. This equation was also the most reliable because the Dpo varied to a lesser extent than in the Eq. 1 NIRS and CPf equations, and only the effect of animal was significant on Dpo. For the other models, both animal and stage of regrowth had a significant effect on Dpo. After increasing the variability in spectral properties and reference data by using the LDS, the entire range of variation of the VDS was covered, resulting in a gain in precision and reli- OMD Eq. 2CP = OMD predicted by the fecal CP equation Eq. 2 CP derived using the large data set: OMD = 88.4 -263.9/CPf. 5 OMD Eq. 1NIRS = OMD predicted by the equation Eq. 1 NIRS of [START_REF] Fanchone | Faecal indices based on near infrared spectroscopy to assess intake, in vivo digestibility and chemical composition of herbage ingested by sheep (crude protein, fibres and lignin content)[END_REF]. 6 OMD Eq. 2NIRS = OMD predicted by the equation Eq. 2 NIRS derived using the large data set. ability of prediction. The main advantage of the NIRS compared with the CPf technique is its ability to take indirectly into account several predictors in the calibration process, which improves the predictive ability. Although the CPf method takes into account only one chemical component of feces to derive an equation, the NIRS technique provides 700 absorbances of light in wavelengths ranging between 1,100 and 2,500 nm, each one a potential indicator of diet characteristics. Therefore, the NIRS technique can retain absorbances related to CPf, as well as spectral absorbance values for other constituents associated with OMD of the diet. Thus, fecal NIRS takes into account the microbial and endogenous fractions of CPf that are correlated to OMD.

Furthermore, other advantages of the NIRS technique compared with CPf are speed and repeatability of prediction, and the fact that it does not require repeated chemical analyses except for calibration [START_REF] Stuth | Direct and indirect means of predicting forage quality through near infrared reflectance spectroscopy[END_REF]. In addition, NIRS calibration permits the estimation of several constituents from the scan of a single sample [START_REF] Stuth | Direct and indirect means of predicting forage quality through near infrared reflectance spectroscopy[END_REF]. The main limitation of this approach is the difficulty of obtaining a sufficient number of samples, with values measured in vivo, to develop calibration equations [START_REF] Deaville | Near-infrared (NIR) spectroscopy: An alternative approach for the estimation of forage quality and voluntary intake. Page 301[END_REF]. Nevertheless, this drawback is also shared by the CPf method. However, given the similarity between Eq. 1 CP and Eq. 2 CP for the VDS, it appears possible to achieve satisfactory predictions with a small set of data. It is necessary, however, that this small data set covers a range of sufficient variation of CPf and that a suitable model, such as hyperbolic or exponential, is used [START_REF] Lukas | Relationship between fecal crude protein concentration and diet organic matter digestibility[END_REF]. When using NIRS, in contrast to the CPf method, the data set used by [START_REF] Boval | The ability of faecal nitrogen to predict digestibility for goats and sheep fed with tropical herbage[END_REF] may not allow for consistent calibration because of a narrow range of spectral properties. Also, even if the NIRS has many advantages, the method of CPf can be useful with a small data set to derive reliable predictive equations of OMD. In fact, each of the 2 methods can be useful to estimate digestibility of pasture in different contexts.

This study has shown that CPf content is a reliable index to predict in vivo OMD for sheep. The hyperbolic model first proposed by [START_REF] Lancaster | Estimation of digestibility of grazed pasture from faeces nitrogen[END_REF] is of interest because it describes a biological relationship between OMD and CPf that allows reliable estimates using an independent data set with values outside the range of the originally modeled data. However, NIRS applied to fecal samples allows better estimation of in vivo OMD than the CPf method because it can take into account more indicators of digestibility [START_REF] Andrès | Nutritive evaluation of forages by near infrared reflectance spectroscopy[END_REF]. An increase of variability of the reference data improved the precision of the estimated fecal NIRS equation. Varying the forage species, the agronomic treatment of tropical grass, or extending our data set to cool-season forages should be explored to widen the predictive potential of our fecal NIRS equation and to further increase the precision of prediction. When a small data set of reference data (n ≈ 40) is available, a hyperbolic equation based on CPf can be suitable to predict the OMD of grazing animals.

Figure 1 .

 1 Figure 1. Evolution of OM digestibility (OMD) with fecal CP (CPf) content (% of OM) for sheep fed with Pangola grass at various stages of regrowth (14, 28, 42, and 56 d) in the validation data set: OMD = 48.4 + 1.26 CPf, r 2 = 0.64.

Figure 2 .

 2 Figure 2. Observed and predicted OM digestibility (OMD) by fecal CP equations of Boval et al. (2003, OMD = -34.1 + 1.47 OMD Eq. 1CP , and r 2 = 0.63) or derived using a large data set (LDS; n = 174, OMD = -21.2 + 1.27 OMD Eq. 2CP , and r 2 = 0.63).

Figure 3 .

 3 Figure 3. Observed and predicted OM digestibility (OMD) by fecal near infrared reflectance spectroscopy (NIRS) equations of Fanchone et al. (2007, OMD = 21.7 + 0.665 OMD Eq. 1NIRS , and r 2 = 0.66) or derived using a large data set (LDS; n = 174, OMD = 2.59 + 0.928 OMD Eq. 2NIRS , and r 2 = 0.68).

  , and the large data set

			OMD, %		CPf, % of OM
	Data set	n	Mean ± SD	Range	Mean ± SD	Range
	Validation data set	23	66.6 ± 4.6	58.3 to 73.6	14.5 ± 2.9	11.1 to 20.4
	1 Eq. 1 CP Eq. 1 NIRS 2	40 84	63.0 ± 1.8 68.7 ± 7.4	59.0 to 71.0 59.9 to 82.3	11.7 ± 0.4 14.3 ± 2.6	9.8 to 16.0 10.0 to 20.3
	Large data set	174	67.1 ± 4.9	53.9 to 82.3	12.8 ± 2.6	7.9 to 20.3
	1 Eq. 1 CP = equation of Boval et al. (2003): OMD = 86.6 -266.2/CPf. 2 Eq. 1 NIRS = fecal near infrared reflectance spectroscopy equation of Fanchone et al. (2007).

Table 2 .

 2 Predictive regressions of OM digestibility (OMD, %) from fecal CP content per unit of OM (CPf, % of OM), calculated for sheep fed Digitaria decumbens

	Item	n	Equation	Residual SD	r 2
	Eq. 1 CP 1 Eq. 2 CP 2	40 174	OMD = 86.6 (±7.3) -266.2 (±83.1) / CPf OMD = 88.4 (±4.72) -263.9 (±64.4) / CPf	2.95 2.92	0.79 0.63

1 Equation of

[START_REF] Boval | The ability of faecal nitrogen to predict digestibility for goats and sheep fed with tropical herbage[END_REF]

.

2 Fecal CP equation derived using the large data set.

Table 3 .

 3 Descriptive statistics of the fecal near infrared reflectance spectroscopy (NIRS) equations to predict OM digestibility (OMD, %)

						Statistic 1
	Item		n	Mean	SD	SEC	R 2	SECV	R 2 cv
	Eq. 1 NIRS Eq. 2 NIRS	2 3	84 174	68.8 67.0	4.12 4.48	1.78 1.48	0.81 0.89	2.02 1.75	0.77 0.85

Table 4 .

 4 Relationships between OM digestibility observed (OMD, %) in an independent validation set and predicted OMD, using 4 different equations, based on fecal CP (CPf; Eq. 1 CP and Eq. 2 CP ) or fecal near infrared reflectance spectroscopy (Eq. 1 NIRS and Eq. 2 NIRS )

					P-value 2
	Prediction of OMD	Residual SD	Dpo 1	SD	RS	A
	3 OMD = 0.959 × OMD Eq. 2CP OMD = 0.97 × OMD Eq. 1CP OMD = 0.983 × OMD Eq. 1NIRS 4 5 OMD = 0.965 × OMD Eq. 2NIRS 6	3.04 2.80 3.15 2.53	1.65 2.79 0.98 2.40	3.02 2.79 3.21 2.55	0.01 0.04 0.002 0.45	0.01 0.009 0.003 0.009
	1 Dpo = difference between predicted and observed OMD.
	2 Factorial ANOVA of Dpo, including the effects of regrowth stage (RS) and animal (A).
	3 OMD Eq. 1CP = OMD predicted by the equation Eq. 1 CP of Boval et al. (2003): OMD = 86.6 -266.2/CPf.

4

at INRA Institut National de la Recherche Agronomique on August 13, 2013 www.journalofanimalscience.org Downloaded from

We thank the Region Guadeloupe and the European Social Funds for funding this study and D. Renaudeau (Institut National de la Recherche Agronomique, Guadeloupe, French West Indies) for critical evaluation of the manuscript.

Corresponding author: maryline.boval@antilles.inra.fr ReceivedDecember 20, 2007. Accepted August 29, 2008.

SEC = SE of calibration; SECV = SE of cross-validation; R

cv = coefficient of cross-validation. 2 Eq. 1 NIRS : Equation of[START_REF] Fanchone | Faecal indices based on near infrared spectroscopy to assess intake, in vivo digestibility and chemical composition of herbage ingested by sheep (crude protein, fibres and lignin content)[END_REF].

Eq. 2 NIRS : Fecal NIRS equation derived using the large data set.Fanchone et al.


L Foan

C Sablayrolles
email: caroline.sablayrolles@ensiacet.fr

V Simon

D Elustondo

E Lasheras
email: elasheras@unav.es

L González
email: lgonzale2@alumni.unav.es

A Ederra
email: aederra@unav.es

J M Santamaría

Reconstructing historical trends of PAH deposition in a remote area of Spain using moss material from a herbarium

Keywords: Atmospheric deposition, Biomonitoring, Herbarium moss, PAH, N, C isotope signatures

Herbarium mosses from 1879-1881, 1973-1975 and 2006-2007 were used to investigate the historical changes of atmospheric deposition of polycyclic aromatic hydrocarbons (PAHs) at a remote site located in Northern Spain. Natural abundance of nitrogen and carbon isotopes was also measured in order to assess the evolution of emissions from anthropogenic sources.

Nitrogen concentrations,  13 C,  15 N and PAH levels were significantly higher in 19 th century 5 samples with respect to the present century samples. Moreover, PAH distribution varied over the centuries, following a tendency of light PAH enrichment. The carbon, nitrogen and PAH levels measured in the mosses tally with the historic evolution of anthropogenic emissions in the area, mainly influenced by changes of economic activities, domestic heating and road traffic density. Mosses provided by herbaria seem to offer the possibility to study long-term temporal 10 evolution of atmospheric PAH deposition.

Introduction 15

Air quality is generally monitored by physico-chemical detectors supplying numerical information. However, these direct measures face problems such as low sample representativeness, analytical difficulties (trace levels), cost and maintenance of equipments. Biological monitoring is an alternative consisting in an integrative 20 technique able to assess the environment contamination based on studies of living organisms exposed to pollution episodes. Because of their capacity to act as efficient interceptors and accumulators of chemicals, plants are used widely as passive biomonitors in urban and rural environments (Garrec and Van Haluwyn, 2002), the most common being persistent trees (Lehndorff and Schwark, 2009a, b), lichens (Blasco 25 et al., 2008) and mosses (Migaszewski et al., 2009).

Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019

3 Bryophytes in particular have been employed over the past decades as biomonitors for the assessment of airborne pollutant deposition, including heavy metals (Harmens et al., 2007;Rühling and Tyler, 1969;Tyler, 1990), radionuclides (Sawidis et al., 2009;Sumerling, 1985), persistent organic pollutants [START_REF] Carlberg | Atmospheric deposition of organic 15 micropollutants in Norway studied by means of moss and lichen analysis[END_REF]Migaszewski et al., 2009) and nitrogen (Poikolainen et al., 2009;Solga et al., 2006;5 Wilson et al., 2008). Characteristics of mosses make them excellent subjects for biomonitoring. Their lack of root system as well as their well-developed cuticle forces them to obtain most of their nutrient supply from the atmosphere. Moreover, their high cationic exchange capacity and surface area to volume ratio favours the accumulation of great amounts of pollutants (Gerdol et al., 2002). 10

Persistent organic pollutants (POPs) remain in the center of scientific attention due to their slow rates of degradation, their toxicity and potential for both long-range transport and bioaccumulation in living organisms (Holoubek et al., 2007). Polycyclic aromatic hydrocarbons (PAHs) are a group of persistant organic pollutants formed by incomplete combustion of organic material through pyrolysis and pyrosynthesis 15 mechnisms (Kiss et al., 2001) and emitted into the atmosphere from both anthropogenic and natural sources (Simonich and Hites, 1995). Anthropogenic sources are generally referred to sources that produce energy such as domestic heating, traffic exhaust, incinerators and natural gas (Mastral et al., 2003). Some of the PAHs are also produced commercially. Acenaphtene, acenaphtylene and anthracene may be used in dye, 20 explosive and fiber production, and in pharmaceutical industry (Hawley, 1987). Natural sources are usually volcanic eruptions and biomass burning. Several PAHs are hazardous to living organisms due to their mutagenic, carcinogenic, teratogenic, immunosuppressive and/or neurotoxic properties (Garuszka, 2000) and eight PAHs are Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019 4 classified by US EPA (1997) as possible human carcinogens. Therefore it is important to monitor and regulate the occurrence of PAHs in ambient air.

To further investigate the quantitative importance of different sources of deposition, the use of stable isotopes at natural abundance levels in mosses provides a powerful approach for understanding environmental interactions. Isotopic composition 5 of elements, such as carbon and nitrogen, changes in predictable ways during their course through the biosphere, which makes them ideal tracers of the pathways and origins of these elements (Liu et al., 2008;Solga et al., 2005).

Mosses preserved in herbaria should be highly suitable for determining environmental conditions in past times since mosses are largely dependent on the 10 atmosphere for their nutrition. It is safe to assume that the concentrations in the herbarium moss samples correlate with atmospheric inputs in the corresponding periods provided that disruptive factors such as soil particles and leaching processes, contamination during sampling and certain preservatives or storage conditions can be excluded (Ross, 1990). 15

Naturally growing mosses have been extensively employed for studying spatial variations of atmospheric PAHs (Migaszewski et al., 2009) and temporal variations of these pollutants over periods of 10 years at the most (Holuoubek et al., 2007) Bertiz has oceanic climate, with an average annual temperature of 13.7-15 ºC, not very hot summers, mild winters and not much difference between the average monthly maximum and minimum temperatures. This is due to the influence of the Biscay Bay, only several kilometres away. The rainfall is one of the highest in Navarra, with an annual average of about 1800 mm distributed all over the year, especially 15 between October and May.

The vegetation mainly consists in a beech forest (Fagus sylvatica L.), although there are some patches of oak woods (Quercus robur L.) and a few pastures.

Due to its ecological richness, the Señorío de Bertiz was declared as a Natural Park during March 1984 (92/43/CEE Directive) and has become since part of the Natura 20 2000 Network.

Herbarium specimens

Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. ( 2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019

6

The following species of bryophytes were studied: Dicranum scoparium Hedw., Hypnum cupressiforme Hedw., Thamnobryum alopecurum Hedw. Gangulee and Thuidium tamariscinum Hedw. Schimp. The mosses had been conserved in the Herbarium PAMP of the University of Navarra, which contains specimens of bryophytes collected in the Natural Park of Bertiz since 1879. Samples were separated 5 into three periods: 1879-1881(Lacoizqueta, 1885), 1973-1975(Fuertes & Álvarez, 1982) and 2006-2007. A total of 28 specimens of the species mentioned above were found in the herbarium.

Leaves or stem tips were taken from a similar terminal position on each specimen using plastic tweezers. Any extraneous material was removed. After that, the 10 unwashed samples were oven-dried at 30ºC to constant weight (dry weight) and finally ground to a fine powder in a mill.

Elemental analysis and isotopic determination 15

Moss samples were analysed for their carbon and nitrogen content and their respective isotopic signatures ( 13 C and  15 N). Tissue C and N contents (%, dry weight) were determined by an elemental analyzer (EA1108, Carlo Erba, Milano, Italy) with an analytical precision of 0.1%. The calibration was performed using atropine (ThermoQuest Italia, Milan, Italy). Stable C and N isotopic ratios were measured with 20 an isotope ratio mass spectrometer (CONFLO II interface, Thermo Finnigan MAT, Bremen, Germany) operating in continuous flow mode. The calibrations were performed using interspersed international isotopic standards of carbon and nitrogen (IAEA, Vienna, Austria). Isotope data are reported as  13 C and  15 N values, which represent relative difference expressed in per mil (‰) between the isotopic composition of the sample and that of a standard (Pee Dee Belemnite (PDB) for carbon and atmospheric N 2 for nitrogen):

 13 C (‰ vs V-PDB) = 1000 1 tan           dard s sample R R  15 N (‰ vs at-air) = 1000 1 tan           dard s sample R R 5
where R sample represents the isotope ratio ( 13 C/ 12 C) or ( 15 N/ 14 N) and R standard the isotope ratio for the standard. The accuracy of the measurements was  0.15‰ for  13 C and  0.3‰ for  15 N. The extractions were performed with a Soxtec System HT2 (Tecator, France). 10

Polycyclic Aromatic

Cellulose thimbles were filled with approximately 1 g of spiked moss, anhydrous sodium sulfate and Florisil (U.S. Silica Company, USA). The extract was concentrated with a rotary evaporator at 30°C (Rotavapor, Büchi, Switzerland), then by nitrogen flow (Alpha 1, Air Liquide, France). A clean-up procedure was carried out with normal phase Florisil SPE cartridges (Supelclean LC-Florisil SPE 1g, Supelco, France) placed on a 15 Supelco manifold. After solvent exchange, the samples were filtered and an internal standard was added. The extracts were stored at -20°C.

The global recoveries of the extraction/purification procedure extend from 25 to 71 % with an average of 54 % for light PAHs (ACE to PYR) and from 27 to 79 % with an average of 60 % for heavy PAHs (B(a)A to IND). 20

HPLC-FLD analysis

The PAH analyses were performed on reversed-phase high-performance liquid chromatograph DIONEX RF 2000 (Pump P680 HPLC) (Dionex, USA) equipped with a C18 column Supelcosil TM LC-PAH (250 mm X 4.6 mm X 5 µm) and a precolumn ( 20Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019 mm X 4.6 mm X 5 µm) (Supelco, France) and a fluorescence detector (DIONEX RF 2000, Dionex, USA) at a flow rate of 1.5 mL/min with a water/acetonitrile elution gradient. The details of the analytical parameters are given in table 1.

The linearity range for the PAH analysis extends from 0 to 58 ng/L with regression coefficients from 0.9992 (B(k)F) to 0.9999 (ANT and B(a)A). 5

To study the repeatability of the analysis, a standard solution containing low PAH concentrations (2 ng/mL) was injected 10 times. The standard deviation, determined for each PAH (from 3% for ACE to 14% for PHE), appeared to be lower than 20%.

The reproducibility of the method was tested by repeating 7 times the entire 10 extraction-purification-analysis procedure on a recent moss sample (collected during October 2008). The results are shown in figure 2. The standard deviation determined for each PAH was lower than 20% except for ACE, FLR, D(ah)A and B(ghi)P with a maximum of 81% for ACE.

Limits of detection (LOD) and limits of quantification (LOQ) were determined 15 by studying the chromatogram obtained with a 2 ng/mL standard solution. The LOD was calculated as equal to 3 times the background and the QL as 10 times the background (Tranchant, 1995). The limits of quantification appear in table 1.

Finally, the accuracy of the analytic procedure was verified by applying the whole extraction-purification-analysis procedure 5 times to a reference material of 20 organic contamination (IAEA-140OC Fucus (35 g) from ANALAB) which contains 9 of the 13 researched PAHs. All determined concentrations entered the reference concentrations 95% confidence interval, except for PYR, overestimated because of interferences with other reference molecules (PCBs or pesticides).

Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. ( 2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019 10

Statistical analysis

One way analysis of variance (ANOVA) was performed to determine the effects of the factors time and species on the variables. For examining associations between the 5 different variables Pearson's correlation coefficients were calculated. The statistical analysis was conducted by using SPSS 15.0 (SPSS Science, Chicago, USA) and XLSTAT 2008 (Addinsoft, Paris, France).

Results 10

Elemental analysis and isotopic determination

Nitrogen and carbon concentrations

Tissue nitrogen concentrations in the herbarium specimens ranged between 0.8 15 % and 1.8 %. Nitrogen concentrations were significantly higher (p < 0.05) in 19 th century with respect to the present century (Figure 3).

The moss Thamnobryum alopecurum exhibited the highest nitrogen concentrations, showing significative differences (p < 0.05) with the other species.

Concerning carbon, concentrations ranged between 30.9% and 43.9% and in this 20 case values did not show significant differences between species or along the centuries.

Nitrogen and carbon isotope signatures

Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. ( 2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019

11 Mean  13 C and  15 N values for the moss species studied ranged between -30.5‰ and -25.1‰ and between -9.3‰ and 0.6‰ respectively. The average  13 C showed a significant (p < 0.05) decrease along the three studied centuries, while in the case of  15 N only mosses collected in the 19 th century exhibited values significantly higher (p < 0.05) than those collected in the 21 st century (Figure 4). 5 No significant differences were observed in  13 C values between the four studied moss species. However, in the case of  15 N significant differences were detected between Dicranum scoparium and Thamnobryum alopecurum, species that respectively showed the lowest and highest  15 N values. 10

PAH levels

Except for antracene and dibenzo(ah)antracene levels which remained low, all PAH concentrations significantly decreased in the mosses between 1879-1881 and 1973-1975 (p < 0.01). Solely levels of the heavy PAHs benzo(b)fluoranthene, 15 benzo(k)fluoranthene, benzo(a)pyrene, benzo(g,h,i)perylene and indeno(c,d)pyrene significantly decreased between 1973-1975 and 2006-2007 (p < 0.01) (Table 2).

As a consequence, total PAH levels decreased significantly between the 19 th and 20 th century (p < 0.01) but not between the 20 th and 21 st century. The average total of the 13 PAHs was 172 ng/g (dry weight) in the current century samples against 1219 20 ng/g (dry weight) in the 130 year old samples.

Phenanthrene showed the highest PAH levels whatever the moss age. It appears to be the major compound as its accumulation accounted for 47% of the total PAHs The individual and total PAH levels measured in Bertiz moss did not vary significantly from one species to another. 15

Discussion

Isotopic signatures and atmospheric N, C sources 20

In contrast with other studies (Peñuelas and Filella, 2001;Solga et al., 2006;Wilson et al., 2008), N concentrations in mosses collected at Bertiz significantly decreased (P < 0,05) between the 19 th and 21 st century. A plausible explanation may be found in the 19 th century history of the Señorío de Bertiz. At that time, the use of wood 2002). All these activities emitted high amounts of NOx and consequently, it is very probable that a remote place such as Bertiz was more contaminated in the past than 5 nowadays. Taking into account that these activities decreased (wood burning) or disappeared (coal bunkers and foundries) at the end of the 19 th century, it seems logical that N concentrations are lower at present. Moreover, Peñuelas and Filella (2001) suggested that the decrease in foliar N from 1940-1950 to 1960-1970

observed in vascular plants and mosses collected in 10

Spain was the result of increased global CO 2 concentrations. Thus, the pattern of N decrease observed in this study could also be explained by growth dilution as a response to large increase of CO 2 availability.

The highest N concentrations found in Thamnobryum alopecurum may be explained by the different life-form of this bryophyte with respect to the others 15 [START_REF] Dierssen | Distribution, ecological amplitude and phytosociological characterization of European bryophytes[END_REF]Mägdefrau, 1982). Thamnobryum is a hygrophytic moss that grows on rocks by streams and rivers, just above mean water level. In consequence, the main water and nutrient source for this moss is groundwater, which is much more N enriched than rain water.

The other three moss species are mesophytic, growing on forest soils. In this 20 case, the main water source is precipitation, being Dicranum scoparium the species with lesser ability to retain water, fact that would explain the lower tissue N concentrations found in this moss. Regarding Thuidium tamariscinum and Hypnum cupressiforme, both

Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. ( 2010 (2006). 5

As mentioned above, the highest  15 N values were detected in Thamnobryum alopecurum, while Dicranum scoparium showed the most negative signatures. This behaviour may be also related to the opposite ecological life-forms of both species. It is known that N absorbed from rain is depleted in 15 N, while N taken from groundwater is enriched in the heavy isotope [START_REF] Asada | Nitrogen isotope signature variability in plant species from 10 open peatland[END_REF]Heaton et al., 1997). Thus, the 10 different water sources for both species would explain the  15 N values observed.

A clear trend towards 15 N depletion was observed, in agreement with Peñuelas and Estiarte (1997), who observed a  15 N decline in moss over the past century that was attributed to an increase over time of the uptake of anthropogenic N, which is depleted in 15 N. This pattern may be related with the increase of N inputs in the reduced form, 15 which is consistent with the gradual intensification of agriculture in the studied area.

Likewise, Turekian et al. (1998) have shown that the combustion of organic material as vegetation produce aerosol particulate material and ashes higher in  15 N than the source vegetation, material which can be retained by mosses. This could explain the significative higher values of  15 N recorded in Bertiz during the 19 th century, when 20 burning beech branches (coal bunkers) was a frequent activity in the forest, supporting the idea that N fractionation is a good indicator for the isotopic characterization of combustion-derived nitrogenous material.

Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. ( 2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019

In spite of the obtained results, it is obvious that the atmospheric concentrations of N have significantly increased all over the world since the Industrial Revolution. In fact, the Ellenberg ecological values calculated from 187 species of mosses collected in Bertiz since 1879, suggest an increasing trend for anthropogenic nitrogen in this area [START_REF] Ederra | One hundred and twenty years of bryology in Vertizarana valley (Navarra, North Spain)[END_REF]. This means that several factors, such as the local 5 influence of coal bunkers and foundries mentioned above, the increased growth and biomass production of mosses or the seasonal variations of N tissue concentrations, could mask the real increase of anthropogenic N deposition.

With respect to  13 C, values were in agreement with the range of C 3 plants (Liu et al., 2008). The observed decreasing tendency of  13 C through the time was consistent 10 with the depletion of 13 C detected in the atmosphere during the last centuries due to the increase of anthropogenic emissions, as well as the fractioning by mosses against the heavy isotope of carbon (Fletcher et al., 2006).

Temporal variations of PAH levels in the mosses 15

Bertiz mosses sampled in 2006-2007 presented total PAH levels of the same order as other background passive moss biomonitoring studies carried out during the past decade in Austria (Krommer et al., 2007;Zechmeister et al., 2006) and Czech Republic (Holoubek et al., 2007). The PAH distribution is also similar, with 20 phenanthrene, fluoranthene and pyrene as major contaminants. It appears that Holoubek et al. (2000,2007) measured a significant decrease of total PAH concentrations between mosses from 1988-1994 and 1996-2005, which 16

The significant decrease of individual PAH levels since 1879 (p < 0.01) can be explained by the evolution of the emissions in the area throughout the past centuries.

During the 19 th century, charcoal production with the coal bunkers located in the forest, charcoal burning in the local foundries and wood burning in stoves for domestic heating were activities that emitted significant amounts of PAHs as they involved biomass 5 burning under sub-optimum combustion conditions (Freeman and Catell, 1990). Thus, PAH emissions dropped significantly during the 20 th century due to the abandon of charcoal associated activities and to the evolution of domestic heating towards systems powered by oil or gas, which emit less PAHs. Indeed, Smith (1987) estimated that PAHs emission factors from wood combustion in small-space heating stoves exceed 10 those from furnace-oil combustion by a factor of 100 on an energy equivalent basis and for vehicles fitted with catalytic converters. The simultaneous limitation of these heavy PAHs may explain why their levels are significantly correlated (p < 0.01).

Phenanthrene, fluoranthene and pyrene, which levels were significantly correlated (p < 0.01), were the major contributors to PAH contamination in Bertiz mosses along the centuries. These compounds are important markers of wood 5 combustion (Khalili et al., 1995;Smith and Harrisson, 1998). Thus, the very high levels of each of these PAHs (> 200 ng/g, dry weight) in the 1879-1881 samples and their significant decrease in the 1973-1975 samples can be explained by the charcoal associated activities and the dominance of domestic heating with wood stoves in the area during the 19 th century. 10 However, in mosses from the 20 th and 21 st century, phenanthrene, fluoranthene and pyrene remained the major contributors to PAH contamination in Bertiz moss, probably due to the presence of local traffic, in particular because of the closeness of the Pamplona-Irun main road (N-121A). Indeed, these three compounds are markers of traffic emissions as diesel emission has a high factor loading for phenanthrene, 15 fluoranthene and pyrene and petrol emission for fluoranthene and pyrene (Duval and Frielander, 1981;Ho et al., 2002;Khalili et al., 1995;Masclet et al., 1986;Omar et al., 2002;Orlinski, 2002;Ravindra et al., 2006).

The fact that phenanthrene levels in moss increased relatively to fluoranthene and pyrene between the 20 th and 21 st century suggests that diesel-engined traffic is 20 predominant nowadays. Moreover, Marr et al. (1999) showed that light-duty vehicules contribute significantly to 4-and 5-benzene ring PAHs, whereas heavy-duty vehicules, which are diesel powered, are the dominant source of 3-benzene ring PAHs, i.e.phenanthrene, fluoranthene and pyrene. Thus, the high density of trucks that transits Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. ( 2010 [START_REF] Asada | Nitrogen isotope signature variability in plant species from 10 open peatland[END_REF]Niu et al., 2003).

Moreover, bryophytes can be contaminated by the soil, which can either emit particles or light volatile PAHs, and can lose PAHs through precipitation leaching (Steinnes et 10 al., 1992).

In the case of this study, the number of herbarium samples available was limited and the total quantity of each sample was low. Moreover, the only data available on the samples was their age. Hence, no inter-species variability was observed for PAHs. Yet moss morphology and growth conditions appear to have an influence on contaminant 15 accumulation in mosses as was shown for nitrogen stable isotopes in this study and for PAHs in other studies. For example Galuszka (2007) observed higher PAH accumulation in Hylocomium splendens than in Pleurozium schreberi moss species.

For a more thorough statistical interpretation, more information would be necessary on the exact sampling localisation, dating and meterological conditions as 20 well as the storage conditions (temperature, preservatives…).

Conclusion

Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. ( 2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019

This study has assessed the value of herbarium moss samples as biomonitors of atmospheric PAH deposition at a Spanish remote site. The high levels of PAHs, N and  15 N in 19 th century mosses of Bertiz Natural Park appear to be related with the historical production of charcoal for local foundries in coal bunkers located in the forest and to the exclusive use of wood stoves for domestic heating before the 20 th century. 5

The disappearance of the coal bunkers and foundries at the end of the 19 th century, associated with evolution of domestic heating towards less pollutant systems during the 20 th century, explain the significant PAH, N and 15 N depletion in the 1973-1975 mosses.

Between the 20 th and 21 st century mosses, PAH distribution changed noticeably with a tendency towards 3-ring PAH enrichment, due to political limitation of heavy PAH 10 emissions during the last 30 years and a regular increase of traffic in the area, in particular of heavy-duty vehicles, confirmed by significant  13 C decrease. Thus, in this study, knowledge of nitrogen and carbon signature in Bertiz mosses helped to identify the evolution of anthropogenic emissions in the area and furthermore explain the evolution of PAH deposition since the 19 th century. 15

Herbarium moss sample analysis meets certain limits due to low sample availability and poor data on sampling and storage. Thus, no evidence of PAH accumulation variability between species could be brought to light in this study. However, relevant information was obtained during this study on past PAH deposition at Bertiz and it consisted with the measured carbon and nitrogen signatures. Therefore, 20 herbarium moss samples appear to be an effective tool for reconstructing historical tendencies of atmospheric PAH deposition.

Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. ( 2010 Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. ( 2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. and emission (Em. ) wavelengths were chosen in function of the analyzed compounds.

The limits of quantification (LOQ) are expressed in mass of injected compound (pg). As 5 a rough guide, the average equivalent concentrations in moss (ng/g, dry weight) have been calculated (for 1 g of moss sample and with the average PAH recoveries). Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. ( 2010

  . The originality of the present study is to use herbarium moss samples to reconstruct temporal tendencies of PAH deposition over the last 125 years in a Natural Park located 20 in Navarra, North Spain. Moreover, we propose to investigate the historical changes of natural abundance of nitrogen and carbon isotopes in order to detect the evolution of emissions from anthropogenic sources. The temporal variations were measured with Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (2010

  Hydrocarbons 10 2.4.1. Chemicals and standards A standard mix containing acenaphtene (ACE), fluorene (FLR), phenanthrene (PHE), anthracene (ANT), fluoranthene (FTN), pyrene (PYR), benzo(a)anthracene (B(a)A), benzo(b)fluoranthene (B(b)F), benzo(k)fluoranthene (B(k)F), benzo(a)pyrene 15 (B(a)P), dibenzo(a,h)anthracene (D(ah)A), benzo(g,h,i)perylene (B(ghi)P) and indeno(c,d)pyrene (IND) at 10 µL/mL of acetonitrile was used for calibration (PAH Mix 9, Supelco, France). Deuterated PAHs were used as extraction standards (anthracene d 10 and benzo(a)pyrene d 12 at 300 ng/mL of acetonitrile) and as an internal standard (fluoranthene d 10 at 1000 ng/mL of acetonitrile) (Supelco, France). Anthracene 20 d 10 was chosen as a reference for the light PAH fraction (ACE to PYR) and benzo(a)pyrene d 12 for the heavy PAH fraction (B(a)A to IND).

  measured in the 2006-2007 samples and this percentage increased over time (24% and Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019 12 39% respectively in the 19 th and 20 th century samples). Fluoranthene and pyrene are the other major compounds measured in Bertiz mosses accounting for 33 to 39% of the total PAHs. Heavy PAHs (benzo(a)antracene to indeno(c,d)pyrene) accounted for approximately half of the total PAH levels in mosses of the 19 th century but appeared 5 to be minor compounds in the recent samples (12%) with individual concentrations of less than 6 ng/g (dry weight). Three groups of PAH levels appeared to be positively correlated (p < 0.01, R 2 = [0.913-0.978]): -acenaphtene and fluorene (2-benzene ring PAHs). 10 -phenanthrene, fluoranthene and pyrene (3-benzene ring PAHs). -benzo(a)anthracene, benzo(b)fluoranthene, benzo(k)fluoranthene, benzo(a)pyrene and indeno(c,d)pyrene (4-and 5-benzene ring PAHs).

  Rogge et al. (1993b) showed that gas home appliances have low total fine particulate organic carbon mass emission rates. The significative decrease of heavy PAHs between the 1973-1975 and 2006-2007 mosses (p < 0.01) can be put in relation with the political incitements to limit 15 POP emissions after the signature in 1982 of the Geneva Convention on Long-range Transboundary Air Pollution. In particular, the most toxic compounds, benzo(b)fluoranthene, benzo(k)flouranthene, benzo(a)pyrene and indeno(c,d)pyrene were regulated by the Aarhus Protocole (1998). Thus, their emissions were reduced by 56% in France between 1991 and 2007 (CITEPA, 2009) due to the control of industrial 20 emissions, the commercialization since 1990 of catalytic converters in transportation and the recent efficiency improvement of biomass combustion heating systems. Rogge et al. (1993a) showed for example that the total PAH emission rate was 25-fold lower Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019

  ). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019 20 This work was supported by the Communauté de Travail des Pyrénées / Communidad de Trabajo de los Pirineos (CTP). We thank Audrey Breton and Christine Raynaud from the LCA (Toulouse, France) for their technical and scientific support, as well as the University of Navarra (Pamplona, Spain) for giving us access to their 5 herbaria. Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019 21 Erdozáin, P., Mikelarena, F., 2002. Traditional iron industry and rural community -The administration of the municipal "ferrerías" of Lesaka and Extalar in 1750-1859. BIBLID 32, 491-515. Fletcher, B.J., Brentnall, S.J., Quick, W.P., Beerling, D.J., 2006. BRYOCARB: a process-based model of thallose liverwort carbon isotope fractionation in response to CO2, O2, light and temperature. Geochimica and Cosmochimica Acta 70, 5676-5691. 5 Freeman, D.J., Catell, F.C.R., 1990. Wood burning as a source of atmospheric polycyclic aromatic hydrocarbons. Environmental Science and Technology 24, 1581-1585. Fuertes, E., Álvarez, J., 1982. Aportaciones a la flora briológica española -El Señorio de Bertiz (Navarra) (Contributions to Spanish bryophyte flora -Señorio de Bertiz (Navarra)). Cryptogamie, Bryologie-Lichénologie 3 (2), 139-155. 10 Garrec, J.P., Van Haluwyn, C., 2002. Biosurveillance végétale de la qualité de l'air -Concepts, méthodes et applications (Air quality biomonitoring with plants -Concepts, methods and applications). Lavoisier, Paris, France, 117p. Galuszka, A., 2007. Distribution patterns of PAHs and trace elements in mosses Hylocomium splendens (Hedw.) B.S.G. and Pleurozium schreberi (Brid.) Mitt. From different forest communities: A case 15 study, south-central Poland. Chemosphere 67, 1415-1422. Garuszka, A., 2000. Toxic organic compounds in the environment. Prz Geol 48, 3681-3688. Gerdol, R., Bragazza, L., Marchesini, R., 2002. Element concentration in the forest moss Hylocomium splendens: variation associated with altitude, net primary production and soil chemistry. Environmental Pollution 116, 129-135. 20 Harmens, H., Norris, D.A., Koerber, G.R., Buse, A., Steinnes, E., Rühling, A., 2007. Temporal trends in the concentration of arsenic, chromium, copper, iron, nickel, vanadium and zinc in mosses across Europe between 1990 and 2000. Atmospheric Environment 41 (31), 6673-6687. Hawley, G.G., 1987. The Condensed Chemical Dictionary. Van Nostrand Reinhold Company, New York, .H.E., Spiro, B., Madeline, S., Robertson, C., 1997. Potential canopy influences on the isotopic composition of nitrogen and sulphur in atmospheric deposition. Oecologia 109, 600-607.

Figure captions Fig. 1 .

 captions1 Figure captions

Fig. 2 .

 2 Fig. 2. Means and standard deviations of polycyclic aromatic hydrocarbon

Fig. 3 .Fig. 4 .

 34 Fig. 3. Temporal variation of nitrogen concentrations (% dry weight) in mosses from

  ). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material.Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05with 100 mL of n-hexane 2 h "boiling mode" (thimble in the solvent) 1 h "rinsing mode" (thimble over the solvent) 20 µL of final extract Evaporation to 10 mL with a rotary evaporator then to 1 mL under a gentle N 2 stream -CONDITIONNING: 10 mL of n-hexane -SAMPLE DEPOSIT -ELUTION: 8 mL cyclohexane:DCM (60:40) 2-3 drops per second -SOLVENT EXCHANGE: Evaporation to 0.1 mL under a N 2 stream Completed to 1 mL with acetonitrile -FILTRATION: with PTFE filter syringes (ø 13 mm, 45 µm) -INTERNAL STANDARD: 100 µL added -MATERIAL: HPLC/FLD -CONDITIONS: 20 µL injection with a loop Acetonitrile/water gradient Flow: 1.5 mL/min Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05

  in aim to study the inter-species variability. This study will assess the value of herbarium mosses for reconstructing past PAH deposition trends.

		2. Experimental section
	5
		2.1. Study area
		The Natural Park of the "Señorío (Estate) de Bertiz" is located in the northwest
		of Navarra (Spain), near the French border. The Park occupies the eastern side of
	10	Bertizarana Valley, covering 2040 hectares.

). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019 5 four different mosses

  was the main procedure for heating houses and the accomplishment of coal bunkers inside the forest was very frequent, in order to obtain charcoal to feed the numerous existing foundries of the surrounding valleys (Erdozáin and Mikelarena,

Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (

2010

). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019 13 burning stoves

  a weft life-form that allows them to hold considerable quantities of rain water by capillarity action, thus showing intermediate N concentrations. Concerning  15 N, isotopic signatures measured in this study were substantially lower than values found by Peñuelas and Filella (2001), but similar to those registered by Liu et al. (2008) and Solga et al.

). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019 14 mosses have

  confirms the temporal trend of PAH depletion in Bertiz mosses.

Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (

2010

). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019

  France and Pamplona (Navarra's capital city) appears to be the main current PAH contamination source for Bertiz moss.

	4.3. Limits of the method
	5
	Air quality passive biomonitoring, i.e. with specimens sampled in-situ, meets
	general disruptive factors due to species variability and to environmental conditions,
	particularly meteorological conditions and altitude (Liu

). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019 18 locally between

Table captions Table 1 .

 captions1 Ho, K.F., Lee, S.C., Chiu, G.M.Y., 2002. Characterization of selected volatile organic compounds, polycyclic aromatic hydrocarbons and carbonyl compounds at a roadside monitoring station.Xiao, H., Liu, C., Li, Y., Xiao, H., 2008. Stable carbon and nitrogen isotopes of the moss Haplocladium microphyllum in an urban and a background area (SW China): The role of Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019 Mastral, A.M., Lopez, J.M., Callén, M.S., Garcia, T., Murillo, R., Navarro, M.V., 2003. Spatial and temporal PAH concentrations in Zaragoza, Spain. Science of the Total Environment 397, 111-124. Migaszewski, Z.M., Gałuszka, A., Crock, J.G., Lamothe, P.J., Dołęgowska, S., 2009. Interspecies and 15 interregional comparisons of the chemistry of PAHs and trace elements in mosses Hylocomium splendens (Hedw.) B.S.G. and Pleurozium schreberi (Brid.) Mitt. From Poland and Alaska. Analytical parameters for PAH analysis by HPLC/FLD. Excitation (Exc. )

	5 10 15 20 25 5 10 20 25	Atmospheric Environment 36, 57-65. Holoubek, I., Klánová, J., Jarkovský, J., Kohoutek, J., 2007. Trends in background levels of persistent organic pollutants at Kosetice observatory, Czech Republic -Part II. Aquatic air and terrestrial environments 1996-2005. Journal of Environmental Monitoring 9, 564-571. Holoubek, I., Kořínek, P., Šeda, Z., Schneiderová, E., Holoubková, I., Pacl, A., Tříska, J., Cudlín, P., Čáslavský, J., 2000. The use of mosses and pine needles to detect persistent organic pollutants at local and regional scales. Environmental Pollution 109, 283-292. Khalili, N.R., Scheff, P.A., Holsen, T.M., 1995. PAH source fingerprints for coke ovens, diesel and gasoline engines, highway tunnels, and wood combustion emissions. Atmospheric Environment 29, 533-542. Kiss, G., Varga-Puchony, Z., Tolani, B., Varga, B., Gelencser, A., Krivacsy, Z., Hlavay, J., 2001. The seasonal changes in the concentration of polycyclic aromatic hydrocarbons in precipitation and aerosol near Lake Balaton, Hungary. Environmental Pollution 114, 55-61. Krommer, V., Zechmeister, H.G., Roder, I., Scharf, S., Hanus-Illnar A., 2007. Monitoring atmospheric pollutants in the biosphere reserve Wienerwald by a combined approach of biomonitoring methods and technical measurements. Chemosphere 67, 1956-1966. Lacoizqueta, J.M., 1885. Catálogo de las plantas que espontáneamente crecen en el Valle de Bertizarana (Catalogue of naturally growing plants in Bertizarana Valley). Anales de la Sociedad Española de Historia Natural 14, 187-346. Lehndorff E., Schwark L., 2009a. Biomonitoring airborne parent and alkylated three-ring PAHs in the Greater Cologne Conurbation. I: Temporal accumulation patterns. Environmental Pollution 157, 1323-1331. Lehndorff E., Schwark L., 2009b. Biomonitoring airborne parent and alkylated three-ring PAHs in the Greater Cologne Conurbation. II: Regional distribution patterns. Environmental Pollution 157, 1706-1713. (21), 5413-5423. Liu, X., Zhang, G., Jones, K.C., Li, X., Peng, X., Qi, S., 2005. Compositional fractionation of polycyclic aromatic hydrocarbons (PAHs) in mosses (Hypnum plumaeformae WILS.) from the northern slope of Nanling Mountains, South China. Atmospheric Environment 39, 5490-5499. Mägdefrau, K., 1982. Life forms of bryophytes. In: Smith AJE (ed.) Bryophyte ecology, pp. 45-58. London, New York: Chapman and Hall. Marr, L.C., Kirchstetter, T.W., Harley, R.A., Miguel, A.H., Hering, S.V., Hammond, S.K., 1999. Characterization of polycyclic aromatic hydrocarbons in motor vehicles fuels and exhaust emissions. Environmental Science and Technology 33, 3091-3099. Masclet, P., Mouvier, G., Nikolaou, K., 1986. Relative decay index and sources of polycyclic aromatic hydrocarbons. Atmospheric Environment 20, 439-446. Atmospheric Environment 43 (7), 1464-1473. Niu, J., Chen, J., Martens, D., Quan, X., Yang, F., Kettrup, A., Schramm, K.W., 2003. Photolysis of polycyclic aromatic hydrocarbons adsorbed on spruce [Picea abies (L.) Karst.] needles under sunlight irradiation. Environmental Pollution 123, 39-45. Omar, N.Y.M.J., Bin Abas, M.R., Ketuly, K.A., Tahir, N.M., 2002. Concentrations of PAHs in atmospheric particles (PM-10) and roadside soil particles collected in Kuala Lumpur, Malaysia. Atmospheric Environment 36, 247-254. Orliński R., 2002. Multipoint moss passive samplers assessment of urban airborne polycyclic aromatic hydrocarbons: concentrations profile and distribution along Warsaw main streets. Chemosphere Liu, X., environmental conditions and atmospheric nitrogen deposition. Atmospheric Environment 42 48, 181-186.

Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019 22 Peñuelas, J., Estiarte, M., 1997. Trends in plant carbon concentration and plant demand for N throughout this Century. Oecologia 109, 69-73. Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019 26

Table 2 .

 2 Means and ranges of PAH concentrations (ng/g dry weight) in mosses sampled in Bertiz Natural Park during the 19 th , 20 th and 21 st centuries. The table indicates the 10 individual PAH levels and the total PAH level (ΣPAHs) for each sampling period

  Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019

									Moss
	Time window Sampling period Time (min)	Exc.  (nm)	Em.  (nm) 1879 -1881	Compounds	Retention time (min) 1973 -1975	LOQ (pg)	average LOQ 2006-2007
									(ng/g DW)
	1 Observed compounds (ng/g) 8.0 Acenaphtene (ACE)		233	39.0 320 12.2 -62.4	ACE FLR	9.2 2.5 9.7 < 1.5 -3.3	22 52	2.2 5.3 < 1.5 -12.7 4.1
	2 Fluorene (FLR)	10.5		260	380 85.5	PHE	11.4 13.9	27	2.8 15.1
	3 Phenanthrene (PHE) 12.0		250	37.9 -143.2 375 298.8	ANT-d 10 ANT	< 10.4 -18.7 12.5 13.1 127.9	4	< 10.4 -21.3 0.4 81.1
	4 Anthracene (ANT) 13.8		365	118.9 -622.0 462 6.2	FTN-d 10 FTN	98.6 -174.3 14.3 14.9 4.7	28	26.9 -142.2 2.8 3.2
					2.9 -9.4		3.2 -9.6		1.2 -9.9
	5	15.6		275	380	PYR	16.4	13	1.3
	6 Fluoranthene (FTN) 18.0		270	300 252.2 145.5 -466.4	B(a)A	21.3 65.4 32.7 -123.0	15	38.1 1.4 10.2 -152.7
						B(b)F	26.5	6	0.6
	Pyrene (PYR)				220.9 127.4 -436.7	B(k)F	28.4 44.8 29.1 -66.4	3	18.5 0.3 6.8 -39.0
	7 Benzo(a)anthracene (B(a)A) 22.1		302	431 97.0	B(a)P-d 12	29.0 8.3		3.1
					66.9 -120.1	B(a)P	30.0 4.2 -11.9	12	1.1 < 1.2 -7.0
	Benzo(b)fluoranthene (B(b)F)		86.8	D(ah)A	32.3 18.8	7	3.0	0.6
	8	33.4		302	419 65.6 -95.5	B(ghi)P	33.9 9.3 -40.9	6	0.6 1.8 -5.5
	9 Benzo(k)fluoranthene (B(k)F) 34.8	300	500 40.6	IND	35.8 6.6	22	0.8	2.1
					29.6 -49.1		3.2 -14.3		< 0.5 -1.8
	Benzo(a)pyrene (B(a)P)			31.6		9.7		2.4
					28.5 -34.8		< 1.4 -17.8		< 1.4 -1.7
	Dibenzo(a,h)anthracene (D(ah)A)	3.6		1.8		4.2
					3.0 -4.6		< 1.3 -3.3		< 1.3 -7.8
	Benzo(g,h,i)perylene (B(ghi)P)	31.2		18.5		5.6
					21.7 -55.1		10.9 -35.3		2.0 -16.1
	Indeno(c,d)pyrene (IND)			25.2		9.9		2.0
					17.5 -35.0		5.8 -21.0		< 2.0 -2.5
	ΣPAHs				1218.6		328.2		171.8
					782.8 -2009.1		206.1 -464.6		86.0 -372.5
									28 29

Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (

2010

). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019

Acknowledgments

Version postprint

Comment citer ce document : Foan, L., Sablayrolles, C., Elustondo, D., Lasheras, E., Gonzalez, L., Ederra, A., Simon, V. (Auteur de correspondance), Santamaria, J. (2010). Reconstructing historical trends of polycyclic aromatic hydrocarbon deposition in a remote area of Spain using herbarium moss material. Atmospheric Environment, 44 (26), 3207-3214. , DOI : 10.1016/j.atmosenv.2010.05.019

24 Peñuelas, J., Filella, I., 2001. Herbaria century record of increasing eutrophication in Spanish terrestrial ecosystems. Global Change Biology 7, 427-433.

Poikolainen, J., Piispanen, J., Karhu, J., Kubin, E., 2009. Long-term changes in nitrogen deposition in Finland (1990Finland ( -2006) )