Similar results are reported for Mugil cephalus ( Guizani, Rolle,

Similar results are reported for Mugil cephalus ( Guizani, Rolle, Marshall, & Wei, 1991) and S. s. caerulea ( Castillo-Yáñes et al., 2005), both with an optimal temperature of 50 °C, and for C. macropomum, with an optimal temperature of 60 °C. The high optimal temperature may be due to the fact that D. rhombeus lives in warm waters, whereas most species analysed thus far live in cold waters. With regard to thermostability, the trypsin from the fish cited proved also to be sensitive to temperatures above 45 °C, which is similar to the results found in the present study ( Fig. CDK and cancer 2D). Kishimura et al. (2008) reported a direct correlation between the temperature of the habitat and

the thermal stability of fish trypsin. The effects of metal ions (1 mM) on the activity of trypsin from D. rhombeus are displayed in Table 1. Enzyme activity was higher than the control (100%) when incubated in the

presence of K+ (34%), Li+ (46%) and Ca2+ (83%). Calcium was shown to be a positive effector for D. rhombeus trypsin. In fact, this ion is known as a classic activator for mammal trypsins. However, Bezerra et al. (2005) and Souza et al. (2007) found that trypsin from the Nile Bcl 2 inhibitor tilapia and spotted goatfish were inhibited by calcium. These results suggest that there are differences in calcium dependence amongst the trypsins from mammal and some fish. The activity of trypsin from the Nile tilapia and spotted goatfish was also inhibited in the presence of Mn2+ and Ba2+, but trypsin isolated from the species analysed in the present study exhibited no traces of enzyme inhibition with these ions. Fe2+, Cd2+, Cu2+ and Al3+ decreased enzyme activity by about 20–35%, whereas Hg2+ and Zn2+ inhibited trypsin activity Thiamine-diphosphate kinase by 53% and 71%, respectively. However, these inhibition values are less expressive than those described for the spotted goatfish. In the presence of Pb2+, there was total inactivation of the trypsin purified from D. rhombeus. Ions such as Cd2+ and Hg2+ are known to act on sulfhydryl residues in proteins ( Aranishi

et al., 1998) and, according to Bezerra et al. (2005), inhibition caused by these metal ions suggests the importance of sulfhydryl residues to the catalytic action of this peptidase. This relevance was also reinforced by the inhibition (approximately 35%) of the D. rhombeus trypsin activity by 2-mercaptoethanol. Moreover, the influence of metals ions or other inhibitory compounds over trypsin activity has been employed as a means to detect xenobiotics in a solution containing commercially available trypsin ( Šafařik et al., 2002). The influence of some synthetic inhibitors on the activity of the enzyme purified from the viscera of the D. rhombeus is displayed in Table 1. The trypsin from D. rhombeus was completely inhibited in the presence of TLCK. Similar results are reported for the Nile tilapia ( Bezerra et al., 2005), bluefish ( Klomklao et al.

The vesicle suspension was titrated potentiometrically with NaOH

The vesicle suspension was titrated potentiometrically with NaOH (0.1 M, pH 9.8) and the pH readings were carried out after a 5 min with a potentiometer (Digmed DM20), and simultaneously monitored by UV–Vis spectrum scanning from 700 to 400 nm, to evaluate the effect of pH on the chromic phase transition of the vesicles. LBH589 nmr HCl (0.1 M, pH

0.98) was also used to assess chromic response at pH values <4.0. The analyses were performed at 21 ± 2 °C. Solutions that simulate the concentration of some components of milk were added individually to the PCDA/DMPC vesicle suspension according to Table 1. The effect of each solution individually on vesicle chromism was monitored by UV–Vis scanning from 700 to 400 nm; at first, 5 min after the addition of solutions of the simulants; next, at intervals of two or four days for a period of 12 days, at 21 ± 2 °C. In the same away we also evaluated the effect of fat, obtained by centrifugation of raw milk, according to the method suggested by R-Biopharm

Rhône Ltd., and direct addition of UHT milk. The concentrations of the solutions that simulated the components of milk were generally prepared according to the theoretical concentrations (total average) suggested by Walstra, Wouters, and Geurts (2006): carbohydrates–lactose (4.9%); salt–Na (48 mg/100 g), K (143 mg/100 g), Ca (117 mg/100 g), Mg (11 mg/100 g), citrate (175 mg/100 g), proteins–casein (26 g/kg), β-lactoglobulin (3.2 g/kg) and α-lactalbumin (1.2 g/kg). In cases of colour change, from blue to red, the colorimetric response (CR) was calculated as a semi-quantitative selleck parameter of the change of chromic properties, according to the following equation (Okada, Peng, Spevak, & Charych, 1998): equation(1) CR(%)=100×Bo-B1Bowhere B C-X-C chemokine receptor type 7 (CXCR-7) = (Ablue/(Ablue + Ared)); Ablue = absorbance at 640 nm and Ared = absorbance at 540 nm; Bo and Bi values calculated before and after colour change, respectively.

For all tests, a descriptive analysis was carried out for the behaviour of the samples. The experiments were prepared with at least three replicates. The PCDA/DMPC vesicles presented no colour transition, no aggregates formation and the same behaviour (spectrum indicative of the blue-phase PDA with an absorption maximum at ≈635 nm) when subjected to temperatures of 5, 12, 20 and 25 °C for a period of 60 days. However, storage at temperatures of 20 and 25 °C for 60 days led to change in the vesicles’ colour intensity, with absorbance values of approximately half those of their initial value (time 0). Possible changes in the vesicle structure, which were not sufficient to change colour from blue to red, promoted the decrease in blue colour intensity at 20 and 25 °C. These data indicate that the vesicles were stable for 60 days under storage at 5 and 12 °C. Fig. 1 represents the absorption spectrum obtained for storage at 25 °C to illustrate the behaviour exhibited by the vesicles during this evaluation.

, 1998a) TFA used to be present in products containing vegetable

, 1998a). TFA used to be present in products containing vegetable-based spreads containing partially hydrogenated oils, such as bakery products (cakes and Dabrafenib price cookies), but also in potato chips and popcorn as reported in the 1998 TRANSFAIR study ( Aro et al., 1998b and van Erp-Baart et al., 1998). Natural TFA, occurring in low amounts in dairy products, can be found in bakery products. Today the TFA level varies, depending on ingredients, and differs among countries. In the TRANSFAIR study, Sweden was reported to be the country with the highest intake of total fat derived from bakery products, contributing

with 13% of total fat ( van Erp-Baart et al., 1998). Currently, the food items with the highest contribution to the total fat intake in Sweden are fats and oils (23%), meat and meat products (21%), milk and dairy products (21%). Bakery products contribute with 9% ( NFA., 2012). High intake of TFA has been associated with increased risk of coronary

heart disease (CHD), sudden death, diabetes mellitus and increased markers for systematic inflammation (Mozaffarian et al., 2006). The TFA found in partially hydrogenated oils has been associated with increased risk of CHD and appears to be more potent than SFA in the development of Palbociclib molecular weight CHD (FAO., 2010). Due to the health risk of TFA, the FAO/WHO recommend a maximum intake of TFA of 1% of energy intake (E%), from both ruminant and industrially-produced sources (FAO, 2010). The current Nordic Nutrition Recommendations recommend a limitation of both SFA and TFA, emphasizing that TFA should be limited as much as possible (NNR., 2014). In Denmark, TFA has been regulated and national legislation allows a maximum of 2% TFA of total fat in products containing non-dairy fat. In the United States and Canada, mandatory labelling of TFA content was introduced in 2003 (Krettek, Thorpenberg, & Bondjers, 2008). In Sweden and the EU, labelling of products containing industrial hydrogenated vegetable oils is mandatory (European Union.,

2011). In this project, levels of FA in selected products on the Swedish market in 2001, 2006 Ponatinib price and 2007 were determined and compared with data from 1995-97 reported in the Swedish part of the TRANSFAIR study (Becker, 1998). Sweet bakery products, cakes, biscuits and cookies, were sampled, since the main fat source in these products is industrially processed fat and oil (van Erp-Baart et al., 1998). The aim was to obtain an overview of TFA levels in the products on the Swedish market and to follow trends in FA composition over time. In order to support decision making for consumers and to evaluate the need for legislations, or not, there is a need to study the FA-profiles of a range of products, that have previously been major contributors to the total TFA intake.

, 2007) If error cannot

be avoided (e g , if all availab

, 2007). If error cannot

be avoided (e.g., if all available samples were obtained post-fast), it is important to assess accuracy of exposure characterization by calculating sensitivities and specificities (Jurek et al., 2006). Sensitivity LY294002 concentration is the probability of correctly classifying an individual as having high level of exposure, if that person truly belongs in the high exposure category. Specificity is the probability of correctly assigning low exposure to a participant who truly has a low level of exposure. Estimates of sensitivity and specificity may be calculated for a single urine sample, using multiple samples per subject as gold standard, since the true sensitivity and specificity for many measures JQ1 mouse is unknown. This can be achieved by randomly selecting a single sample from among each individual’s repeated samples collected over the study (as demonstrated for phthalates in Adibi et al., 2008). In a recent systematic review of the epidemiology literature on phthalates and associations with obesity, diabetes, and cardiovascular disease, Goodman et al. (2014) found that of 26 available studies, all but three relied on a single

measure of phthalates. Similarly, in a systematic review of BPA and obesity, diabetes, and cardiovascular disease, LaKind et al. (2014) found that of 45 available studies, all but four relied on a single measure of BPA. Yet the intra-individual variability for BPA is large (with ICCs ranging from 0.10 to 0.35) (Lassen et al., 2013 and Teitelbaum et al., 2008), and multiple measures of exposure are needed to describe a person’s long-term exposure. The ICCs for phthalates have been reported to be higher than for BPA (e.g., ICC values range

from 0.18 to 0.61 for mono-ethyl phthalate, from 0.21 to 0.51 for mono-isobutyl phthalate, and from 0.08 to 0.27 for mono-(2-ethylhexyl) phthalate [reviewed in Goodman et al., 2014]), but intra-person variability Methamphetamine is still large. Recently, Attfield et al. (2014), in a study of variability of urinary pesticide measures in children, observed that a study with only a small number of samples from each study participant “…may lead to a high probability of exposure misclassification by incorrect quantile assignment and offer little assurance for correctly classifying the exposure into a specific category. The above considerations permit dividing the available body of literature into the following tiers (Table 1). Tier 1 includes studies in which exposure assessment is based on sufficient number of samples per individual to estimate exposure over the appropriate duration, or through the use of adequate long-term sampling (e.g., multiple 24-hour urine collections). To be included in Tier 1, studies should assess error by calculating measures of accuracy (e.g., sensitivity and specificity) and reliability (e.g., ICC). It is possible that for some chemicals, one sample may be sufficient to fully characterize exposure.

2 and Fig  3) Considering these results,

2 and Fig. 3). Considering these results, XAV-939 manufacturer we inferred that the significant FT-IR spectral variations in this study were directly related to changes in major metabolites (sugars and amino acids) and secondary metabolites (aromatic compounds) of ginseng leaves. The overall

metabolic variations between cultivation ages were much greater than those within cultivars. PLS-DA was able to discriminate ginseng cultivars within the same cultivation age groups (Fig. 5). These results show that FT-IR combined with multivariate analysis could be used as a reliable tool for metabolic discrimination of ginseng cultivars. Recently, a novel method combining high performance liquid chromatography fingerprint and simultaneous quantitative analysis of multiple components was developed for quality evaluation of medicinal plants [54] and [55] or cultivar discrimination [53]. However, these chemical fingerprinting protocols require complex sample preparation as well as metabolite analysis. In this regard, FT-IR could be easily applied without these complexities. To verify the practical

applicability of PLS-DA for the discrimination of cultivation ages and cultivars of ginseng, we conducted a cross-validation test (Table 1). In this, 96.15% of the group cases were correctly classified. The average accuracy for the cross-validation test (×10) was 94.8%, which was statistically significant (p = 0.00625). These results clearly show that cultivation ages and cultivars were simultaneously discriminated

through PLS modeling with high accuracies. Kim et al Selleckchem BMS-734016 [56] reported that age discrimination of ginseng roots is possible using NMR or Liquid chromatography-mass spectrometry (LC/MS). However, in this study, we showed that it was possible to discriminate cultivation ages and cultivars using multivariate analysis of FT-IR spectra from ginseng leaf samples. We also observed that cultivation age-dependent metabolic changes were many much greater than cultivar-dependent ones in ginseng leaf. These results imply that aging-related metabolites in the roots are transported to the aerial part of ginseng. In conclusion, this study showed that FT-IR combined with multivariate analysis was capable of discerning metabolic differences in ginseng leaf in a cultivation age-dependent or cultivar-dependent manner. Moreover, we showed that quantitative and qualitative modifications of polysaccharide and amide regions of FT-IR spectra from ginseng leaves have the potential to act as metabolic markers for discriminating among different ginseng cultivars and cultivation ages. Similar to the suggestion of Di Donna et al [53] and Schulz and Baranska [44], such metabolic markers could be applied to characterize different cultivars or chemotypes among the same species.

3), modelled available water capacity (AWC) and location of tree

3), modelled available water capacity (AWC) and location of tree in slope position (in sinkhole, out of sinkhole). Tree age and competition intensity were included as additional explanatory variables for height and radial growth of dominant silver fir trees, respectively. Models were compared using partial F-tests and Akaike’s Information Linsitinib Criterion (AIC). To define groups of trees with similar soil conditions, we applied a cluster analysis (Ward clustering method, Manhattan distance) considering the mean thickness of the soil horizons around each individual tree. Based on the resulting dendrograms,

three groups of trees with similar soil conditions were distinguished ( Fig. 3). We used an analysis of covariance (ANCOVA) to detect differences in the SBAI between soil associations SA and landforms (grouping factor) while controlling for

the effect of competition (a continuous covariate), which is considered a ‘nuisance’ parameter. Soil probing (n = 780) around each tree revealed different development of soils in the Trametinib manufacturer studied area. Shallow soils with depths up to 20 cm were prevalent. Only organic O horizon on parent material was found in 13% of soil probing. Leptosol (profile O–A–C) were found in 44% of the soil probing. Deeper soils with well-developed cambic Bw horizon (Cambisol) or eluvial E horizon in combination with the Bt horizon, (Luvisol) represented 36% and 7% of the soil cores, respectively. The latter, were most often found at the bottom of sinkholes. At least two different soil profile development were found per tree: in 18 cases two soil development stages; in 33 cases three soil development stages and in 14 cases four soil development stages ( Fig. 4). The prevailing thickness of the O and A horizons were 0–5

and 0–10 cm, respectively ( Fig. 2). The cambic, eluvial and illuvial horizons were up to 80 cm thick, with median values of 20 cm, 22 cm and 28 cm, respectively. Surface rock outcrops were estimated to be up to 30%. In general, the soils were silty clay with negligible amounts of sand, neutral pH, high cation exchange capacity and high base saturation (Table Atorvastatin 2 and Table 3). In the A and Bw horizons of Leptosol and Cambisol, the base saturation (BS) was greater than 99%. Cation exchange capacity (CEC) was highest in the A horizons as a consequence of both high organic matter and high clay content. Eluvial – illuvial processes resulted in decreased pH, organic matter and clay content and base saturation in the A and E horizons of leached soils (Luvisols). Conversely, the highest amount of clay was measured in the Bt horizon. The C/N ratio in the mineral soil was favourable for N mineralisation because it was less than 20 in almost all cases (Table 2). In the organic horizons, the C/N ratio decreased with an increasing degree of decomposition from 41.8 in the litter Ol to 18.3 in the humified Oh horizon (Table 2). Modelled available water content (see 2.

, 2012, Gane et al , 2013 and Matthews and Lancaster, 2012) have

, 2012, Gane et al., 2013 and Matthews and Lancaster, 2012) have been developed and show increased viral clearance rates. However, genotype-dependent differences in drug sensitivity and viral resistance highlight the need for additional drugs for future Cilengitide combination therapy. The HCV encoded viroporin p7 is an attractive target for therapeutic intervention since it is essential for viral assembly and egress (Tedbury et al., 2011 and Wozniak et al., 2010). However, clinical trials of p7 inhibitors, including the adamantane-derivatives amantadine and rimantadine,

have showed limited efficacy at concentrations that can be achieved in man, consistent with in vitro observations ( Fong et al., 1999, Griffin et al., 2008, Jubin et al., 2000, Steinmann et al., 2007a and Steinmann et al., 2007b). A recent study by OuYang et al., elucidated an NMR structure of HCV p7 strain EUH1480 (GT5A) and predicted the amantadine binding domain. Both amantadine and rimantadine

are suggested to hinder the p7 channel from opening by restricting movement of helical segments in the p7 hexamer. The authors report variations in the adamantane-binding pocket which may explain the broad range of responses to inhibitors reported for diverse HCV genotypes ( OuYang et al., 2013). The majority of in vitro studies on p7 inhibitors have characterised the effect of compounds on virus assembly and the infectivity of secreted click here particles. Cobimetinib in vivo However, these studies did not address the ability of HCV to transmit via cell-to-cell contacts, a dominant route of

viral transmission for several HCV genotypes ( Brimacombe et al., 2011, Catanese et al., 2013, Meredith et al., 2013 and Timpe et al., 2008). We therefore assessed the efficacy of several known p7 inhibitors to prevent HCV cell-to-cell transmission, including the amantadine-derivative Rimantadine, the long alkyl-chain iminosugar NN-DNJ ( StGelais et al., 2007 and Wozniak et al., 2010) and the small molecule inhibitor BIT225 ( Luscombe et al., 2010). We previously reported that diverse strains of HCV can transmit effectively via the cell-to-cell route, with J6/JFH (GT2A/2A) showing a distinct preference for cell-to-cell infection, while SA13/JFH (GT5A/2A) transmitted with equal efficiency by either route ( Brimacombe et al., 2011 and Meredith et al., 2013). Furthermore, HCV SA13/JFH is the only published infectious GT5 strain and has a closely related sequence to EUH1480, the subject of the recent p7 NMR study ( OuYang et al., 2013). To determine the sensitivity of HCV J6/JFH and SA13/JFH to p7 inhibitors BIT225, NN-DNJ and rimantadine, infected Huh-7.5 cells were treated overnight with increasing concentrations of compound. The drug was removed by repeated washing, conditioned media was collected over a 2 h period and infectivity measured.

In such circumstances, they may develop the illusion that they ar

In such circumstances, they may develop the illusion that they are becoming better at the task and able to persuade others that this is so. In the financial domain, this would have clear implications for people’s selection of investment strategies. This research was supported by a scholarship awarded by the Responsible Gambling Fund to Juemin Xu. We thank Peter Ayton for Protease Inhibitor Library cell assay invaluable comments on earlier drafts of the manuscript. “
“The processing of a word in a sentence is affected by a range of linguistic properties, across many tasks and experimental

paradigms, but how does the cognitive system change the way it responds to these properties in different tasks? Two hallmark effects derive from the frequency of a word to be ABT263 processed (high frequency words are processed more quickly than low frequency words) and the predictability of a word in its sentence context (more predictable words are processed more quickly than less predictable words; see Kutas and Federmeier, 2011, Rayner, 1998 and Rayner, 2009 for reviews). While frequency

and predictability effects are robust and well documented, the magnitudes of these effects vary across tasks and paradigms (even when equating the magnitude of the frequency or predictability manipulation). The fact that these effects change across tasks suggests that the way in which people approach a task can modulate the extent to which they are sensitive to specific linguistic properties of the words they read (even when held constant across tasks). In the present study, we investigated this cognitive flexibility in reading for comprehension and proofreading. While still poorly understood, proofreading is a useful task for elucidating how cognitive processing changes along with task demands because ADAM7 of its similarity to reading for comprehension in

terms of stimuli and response measure. The only differences in experimental design between these two tasks are the instructions and the inclusion of sentences that contain an error. Thus, we can study how processing of sentences without errors changes when people are asked to process them in different ways: checking for errors or reading for understanding. In the remainder of this introduction, we briefly discuss frequency effects and predictability effects and existing evidence regarding how they change magnitude across tasks, then turn to theoretical and empirical aspects of proofreading and discuss the goals and design of the present study.

For multivariate analysis, data were z-score standardized and Euc

For multivariate analysis, data were z-score standardized and Euclidean distance matrices produced for each

parameter group. Permutational Multivariate Analysis of Variance (MANOVA) was used with GC# and site location as factors to determine if each category differed by stream and up and downstream of golf course facilities. Significant multivariate interactions were examined by trajectory analysis where the magnitude and direction of change for each stream and site location pair was explored ( Collyer and Adams, 2007). When interactions between stream and site location were not significant, multivariate post hoc tests Selisistat in vivo were run to determine which streams differed. Multivariate categories for each sampling location were visualized with principle components analysis as biplots of components 1 and 2. Mantel and partial mantel tests and two block partial least squares were used to examine multivariate correlation between parameter groups. All statistical analyses were carried out in R 2.14.1 with the assistance of vegan and geomoph packages. Watershed area ranged for each sampling point from 10 to 93 km2. Anthropogenic land use (e.g., agriculture, development, tree plantations, etc.) ranged 48–78% among stream riparian zones (Table

1). The multivariate landscape group was selleck chemical similar up and downstream of golf course facilities (Pillai’s Trace = 0.2, p = 0.914; Table 1; Fig. 2A). The landscape group significantly differed by stream (Pillai’s T = 16.9, p = 0.001). Post hoc comparison indicated that GC1 was only similar

to GC2 and GC5. The landscape of GC6 was Astemizole significantly different from GC2. The landscapes of GC2, GC3, and GC4 were similar ( Fig. 2A). Water quality among streams ranged from oligotrophic to eutrophic (Table 2). DOC ranged from 1.3 to 16.9 mg-C l−1 and was significantly lower downstream of golf courses (Wilcoxon’s paired test, p = 0.002; Fig. 3). SpCond, TDN, BACT, and BP were variable among sites but did not differ up and downstream of golf course facilities. TDP ranged from 4.1 to 44.1 μg-P l−1 and was significantly higher downstream of golf course facilities (Wilcoxon’s paired test, p = 0.023; Fig. 3). All together, the water quality group up and downstream of golf course facilities was similar (Pillai’s T = 0.2, p = 0.913), but significantly differed in water quality among streams (Pillai’s T = 14.3, p = 0.001; Fig. 2B). Post hoc comparison indicated that GC1 and GC2 were similar but significantly differed from the other streams, except between GC1 and GC5 which did not differ (p = 0.064). GC3, GC4, GC5, and GC6 had similar water quality. DOM ranged from strongly humic-like with features of terrestrial inputs (e.g., higher aromaticity (SUVA) and contributions of C2 and C3) to humic-like with features of microbial inputs (e.g.

yrs BC) the human presence in the Alpine region was too sparse to

yrs BC) the human presence in the Alpine region was too sparse to influence the natural climate- and vegetation-driven fire regime (Carcaillet et al., 2009; Fig. 2). During this first fire epoch Staurosporine sensu Pyne (2001), fires were ignited by lightning, as volcanoes in the Alps were already inactive, and the fire regime was characterized by long fire return intervals, e.g., 300–1000 yrs ( Tinner et al., 2005, Stähli et al., 2006 and Carcaillet et al., 2009). The shift to the second fire epoch sensu Pyne (2001) took place with the Mesolithic-Neolithic transition (6500–5500 cal. yrs BC; Fig.

2) when fire activity increased markedly throughout the Alps ( Tinner et al., 1999, Ali et al., 2005, Favilli et al., 2010, Kaltenrieder et al., 2010 and Colombaroli et al., 2013) as a consequence of an increase in the sedentary population and a corresponding use of fire for hunting and to clear vegetation for establishing settlements, pastures and crops ( Tinner et al., 2005 and Carcaillet et al., 2009). The anthropogenic signature of the second fire epoch is documented in the Alps from the Neolithic to the Iron age (5500–100 cal. yrs BC) by the positive correlation INCB024360 between charcoal particles and peaks in pollen

types indicative of human activities ( Tinner et al., 1999, Tinner et al., 2005, Kaltenrieder et al., 2010, Berthel et al., 2012 and Colombaroli et al., 2013). Despite the anthropogenic origin, the general level of fire activity highly depended on the climate conditions. Areas on the northern slopes of the Alps experienced charcoal influx values one order of magnitude lower than the fire-prone environments of the southern slopes ( Tinner et al., 2005). Similarly, phases of cold-humid climate coincided with periods of low fire activity in these areas ( Vannière et al., 2011). In the Alps, the human approach to fire use for land management has changed continuously according to the evolution

of the population and the resources and fires set by the dominant cultures alternating in the last 2000 years (Fig. 3). Consequently, the shift from the second to the third fire epoch sensu Pyne (2001) is not definite as they have coexisted up to the present, similarly to other European regions, e.g., Seijo and Gray (2012), and differently from other areas N-acetylglucosamine-1-phosphate transferase where it coincides with the advent of European colonization ( Russell-Smith et al., 2013 and Ryan et al., 2013). For example, the extensive use of fire that characterizes the second fire epoch completely changed in the Alpine areas conquered by the Romans starting at around 2000 cal. yrs BC. Under Roman control the territory and most forest resources were actively managed and also partially newly introduced (i.e., chestnut cultivation) and hence the use of fire was reduced proportionally ( Tinner et al., 1999, Conedera et al., 2004a and Favilli et al., 2010; Fig. 2). Consequently, during Roman Times, studies report a corresponding decrease in fire load throughout the Alps ( Blarquez et al.