, 2009), food processing ( Shahidi & Kamil, 2001) and pharmacolog

, 2009), food processing ( Shahidi & Kamil, 2001) and pharmacology ( Jónsdóttir, Bjarnason, & Gudmundsdóttir, 2004). The silver mojarra (Diapterus rhombeus) is a marine finfish from the northeastern

Brazilian coast, of economic and ecological importance that can be used to extract proteases for biotechnological applications. This fish Epigenetics inhibitor belongs to the family Gerreidae and is found in coastal estuaries throughout the tropical waters of the Atlantic Ocean ( Austin, 1973). According to the Brazilian Environmental Agency IBAMA (2008), 2080 tons of mojarras were captured in northeastern Brazil in 2006, which generated an estimated annual discharge of about 100 tons of viscera. Therefore, the investigation into enzymes present in this type of byproduct may help optimise the use of these resources, by adding value to these industrial

segments. The aim of the present study was to purify a trypsin from the digestive tract of the silver mojarra and characterise its physical and biochemical properties, such as the effect of temperature, pH, ions, inhibitors, substrate concentration and NH2-terminal amino acid sequence. Specimens of D. rhombeus were obtained from a fishing community in Itapissuma, Pernambuco, DNA Damage inhibitor Brazil. Fish were packed in ice and transported to the laboratory. Average weight and length was 350 ± 20 g and 28 ± 2 cm, respectively. The intestine and pyloric caeca of ten fish (about 30 g) were removed and stored in a freezer at −25 °C until analysis. Fish intestines and pyloric caeca were mixed together and homogenised at a concentration of 40 mg ml−1 (w.v−1) of tissue in a solution of 0.01 M Tris–HCl, pH 8.0, with 0.9% NaCl, using a tissue homogeniser (Bondine Electric Company, Chicago, IL) at 300 rpm for 60 s. The homogenate was then centrifuged (Herolab Unicen MR Centrifuge, Germany) at 10,000g for 25 min at 4 °C for the removal of insoluble

particles. The supernatant (enzyme extract) was collected and stored in a freezer at −25 °C for subsequent use in the purification mafosfamide steps. Enzyme activity was measured using BApNA (Nα-benzoyl-l-arginine-p-nitroanilide) prepared with dimethylsulphoxide (DMSO), as substrate specific for trypsin. The assay was carried out by mixing 30 μl of sample with 140 μl of 0.1 M Tris–HCl, pH 8.0 and 30 μl of 8 mM BApNA (final concentration of 1.2 mM) for 10 min at 25 °C. The formation of p-nitroaniline (product) was measured at 405 nm with a microplate reader (Bio-Rad X-Mark spectrophotometer, California, USA). A blank control was prepared by replacing sample with 0.1 M Tris–HCl, pH 8.0 (Souza, Amaral, Santo, Carvalho, & Bezerra, 2007). One unit (U) of enzyme activity was defined as the amount of enzyme capable of hydrolysing 1 μmol of BApNA per min under the established conditions, using a molar coefficient of 9100 mM−1 cm−1.

It is interesting to maintain a high relative content of trans-C1

It is interesting to maintain a high relative content of trans-C18:1 as it participates in CLA production in the human ( Butler et al., 2011 and Gnädig et al., 2003) and acts as an intermediate fatty acid in the biohydrogenation pathway ( Bergamo et al., 2003). During storage of the fermented products, the trans-C18:1 concentration remained stable,

whatever the kind of milk and starters used. Finally, after 7 days storage at 4 °C, it was higher in organic fermented milks (3.3 ± 0.03%) than in conventional milks (2.2 ± 0.03%). During fermentation, CLA relative content significantly increased (P < 0.05), at different levels in organic (17%) and conventional (12%) milks ( Fig. 1B). This was explained by Ekinci et al. (2008), who indicated that enzymatic reactions occurred in the biohydrogenation pathway, thus increasing CLA level during the production of fermented products. Similar results were reported PF-06463922 by Oliveira et selleck al. (2009) in fermented milks, whereas no change was observed in probiotic fermented products made with conventional milk, as reported by Van de Guchte et al. (2006). As these authors used different strains, this behaviour was thus strain-dependent. The difference between conventional and organic fermented milks found in our study was considered as significant (P < 0.05).

The CLA relative concentration was higher in organic fermented milks (1.2 ± 0.01%) than in conventional fermented milks (0.8 ± 0.01%) ( Fig. 1B), in accord with previous results ( Oliveira et al., 2009). This higher CLA relative content in organic fermented products was the result of both initial CLA percentage in milk and changes

during fermentation. In addition to these results, CLA relative concentration did not significantly vary in fermented milks according to the co-cultures. This result indicates that tuclazepam B. lactis HN019 had no effect on CLA relative content, and that the variations observed during fermentation could be ascribed to S. thermophilus or L. bulgaricus, as suggested by Lin (2003). Finally, the CLA percentage slightly decreased during cold storage of three of the fermented milks (P < 0.05), that may be related to the activation of reduction steps in the biohydrogenation pathway ( Kim & Liu, 2002). However, by considering the conventional fermented milk with yogurt starters and bifidobacteria, a significant increase of relative CLA content was observed. Fig. 1C shows that, during fermentation, ALA level did not vary significantly in organic milk (0.5 ± 0.02%), for the two kinds of culture. In contrast, a significant decrease (P < 0.05) was noted during fermentation and storage of conventional milk products (from 0.38 ± 0.02% to 0.30 ± 0.02%). These results are not in agreement with those of Van de Guchte et al.

Seventeen compounds were identified in the fractions of extracts

Seventeen compounds were identified in the fractions of extracts from the stem and leaves of T. triangulare by spectrometric data analysis and chromatographic procedures. Besides the mixture of steroids (1–4), the new acrylamide, 3-(N-acryloyl, N-pentadecanoyl) propanoic acid (5), allantoin (6), malic acid (7), asparagine (10) and a mixture of glucopyranosyl steroids (8–9) were isolated from the stem extracts. In the dichloromethane and methanolic extracts from the leaves, seven phaeophytins (11–17)

were identified, including four new compounds named (151S, 17R, 18R)-Ficuschlorin D acid (31,32-didehydro-7-oxo-173-O-phytyl-rhodochlorin-15-acetic acid, 13), (17R, 18R)-phaeophytin b-151-hydroxy or 152,153-acetyl-131-carboxilic acid (14) named Talichlorin selleck compound A, and (151S, 17R, 18R)-phaeophytin b peroxylactone or (151S, 17R, 18R)-hydroperoxy-Ficuschlorin D (16), together with twelve known compounds, including four phaeophytins

(11, 12, 15 and 17), as well as allantoin (6), malic acid (7) and JNJ-26481585 mouse the mixture of glucopyranosyl steroids (8 and 9). The IR, UV, 1D and 2D 1H and 13C NMR, and mass spectra analysis, including GC–MS and HPLC–MS techniques, were used to identify the compounds ( Fig. 1). The absolute configurations of phaeophytins 12 (132R, 17R, 18R)-132-hydroxyphaeophytin a, 13 and 16 (as presented above), 15 (151S, 17R, 18R)-31,32-didehydro-151-hydroxyrhodochlorin-15-acetic acid δ-lactone-152-methyl-173-phytyl ester and 17 (17R, 18R)-purpurin 18-phytyl ester were defined by CD spectra data analysis and applying the quadrant rule ( Crabbé, 1974) to the planar tetrapyrrole system, as described below. The steroids mixture was identified by 1H and 13C NMR spectra analysis, and each component selleck chemicals llc in this mixture was defined by mass-spectra analysis, corresponding to each peak detected by GC–MS, followed by comparison with the literature equipment library (Nist 08). Campesterol (1, Ret. Time 19.517), sitosterol (2, Ret. Time 20.067), stigmasterol (3, Ret. Time 20.311), and scotenol (4, Ret. Time 21.416) were identified (Fig. 1). Compound 5 was isolated as a white amorphous solid. The 1H NMR (1D and 2D) spectra exhibited

signals with an ABC system with δH 6.14 (dd, J1 = 12 and 16 Hz, H-2′), 6.06 (dd, J1 = 8 and J2 = 12 Hz, Ha-3′), 5.53 (dd, J1 = 8 and J2 = 16 Hz, Hb-3′) and a A2B2 system with δH 3.75 (t, J = 8 Hz, H-3), 2.62 (t, J = 8 Hz, H-2). The 13C (BBD and DEPT) and HMQC spectrum analysis allowed the identification of the corresponding connected carbons with δC: 135.2(CH-2′), 123.8 (CH2-3′), 59.3 (CH2-3), 40.0 (CH2-2) for both systems. The additional analysis of the 13C and HMBC NMR spectra allowed the identification of carbonyl groups [δC 181.8 (C-1) 173.8 (C-1′)] and enabled the completion of the systems of an acrylamide and the 3-amino-propanoic acid. Other signals at δH 2.14 (t, J = 8 Hz, H-2″), 1.61(brs, H-3″), 1.29 (m), 0.

No statistical differences were observed, with regard to the live

8.2 ± 2.9, 30.4 ± 3.0, and 29.1 ± 3.4, respectively; p < 0.05). No statistical differences were observed, with regard to the liver function tests, between the normal, alcohol, control, KRG, urushiol, and probiotics groups (p > 0.05; Table 2). The following results were found (stated as the normal, control, probiotics,

KRG, and urushiol groups vs. the alcohol group): aspartate aminotransferase (186.1 ± 60.1 U/L, 186.3 ± 79.8 U/L, 174.0 ± 45.6 U/L, 182.5 ± 55.8 U/L, and 164.3 ± 62.8 U/L, respectively, vs. 191.2 ± 57.0 U/L); alanine aminotransferase (30.7 ± 24.9 U/L, 33.1 ± 24.8 U/L, 41.1 ± 12.0 U/L, 41.2 ± 14.9 U/L, and 31.2 ± 4.8 U/L, respectively, vs. 35.3 ± 11.3 U/L); and gamma-glutamyl transferase Erastin cell line (8.1 ± 4.1 U/L, 8.0 ± 5.9 U/L, 7.8 ± 4.6 U/L, 8.5 ± 3.0 U/L, and 9.2 ± 4.8 U/L, respectively, vs. 7.4 ± 3.9 U/L). Thus, treatment with probiotics, KRG, or urushiol did not ameliorate the results of the serum liver function test. Serum cytokines,

TNF-α, and IL-1β level analyses revealed Osimertinib that the probiotics, KRG, and urushiol groups did not differ from the alcohol group (p > 0.05). Although the serum TNF-α levels in the probiotics and urushiol groups, as well as the IL-1β levels in the urushiol group, were lower than those in the alcohol group, these results were not significant. TNF-α level of the liver tissue in the KRG group was 379.9 ± 201.5 pg/mL, which was significantly lower than that in the alcohol group (687.4 ± 110.5 pg/mL; p < 0.05). IL-1β levels of the liver tissue in the probiotics (37.33 ± 18.48 pg/mL; p < 0.05) and KRG (26.18 ± 7.17 pg/mL; p < 0.01) groups were decreased compared with those in the alcohol group (65.21 ± 3.91 pg/mL; Fig. 2). KRG reduced proinflammatory cytokines. Western blot recognition of the protein in the liver tissue homogenate is summarized in Fig. 3. The Western blot analysis revealed positive

bands of appropriate sizes for each protein studied. TLR-4 and GAPDH antibodies Cepharanthine were detected as single bands at 95 kDa and 37 kDa, respectively. Treatment with probiotics, KRG, and urushiol was associated with reduced TLR-4 levels in the liver tissue compared with those in the alcohol group. Liver tissue TLR-4 levels were 0.33 ± 0.070 ng/mL (p < 0.001) in the probiotics group, 0.37 ± 0.063 ng/mL (p < 0.01) in the KRG group, and 0.39 ± 0.12 ng/mL (p < 0.05) in the urushiol group, but 0.88 ± 0.31 ng/mL in the alcohol group ( Fig. 3). In the alcohol group, four mice exhibited Grade 0 steatosis, four exhibited Grade 1 steatosis, and two exhibited Grade 2 steatosis (p < 0.01 vs. normal group). In the KRG group, eight mice exhibited Grade 0 steatosis, one exhibited Grade 1 steatosis, and one exhibited Grade 2 steatosis (p < 0.05 vs.

Furthermore, FT-IR spectroscopy techniques could be applied for h

Furthermore, FT-IR spectroscopy techniques could be applied for high-throughput screening and metabolic evaluation of new cultivars or elite lines in conventional breeding programs. All contributing authors declare no conflicts of interest. This work was supported Z-VAD-FMK solubility dmso by a grant (NRF-2011-0030880 to S.W.K) from the National Research Foundation of Korea and a grant (PJ008329

to S.W.K.) from the Next-Generation BioGreen 21 Program of the Rural Development Administration of Korea. “
“Ginseng has been considered one of the most valuable medicinal herbs in oriental countries for the past 2,000 yr, and now it is widely used as an alternative medicine and health food [1]. At present, ginseng production is pegged at approximately 8,000 tons/yr; traditional

therapeutic herbs are consumed in 35 countries around the world, and its global market was estimated to be about $2,000 million (US dollars) [2]. Most of this production is limited to two genera of ginseng (Panax ginseng and Panax quinquefolius), and four countries—South Korea, China, Canada, and the United States—are the world’s biggest ginseng producers. The roots of P. ginseng (Korean ginseng) and P. quinquefolius (American ginseng), two closely related herbal species belonging to the Panax genus, are two of the most commonly used medicinal herbs. However, aside from its wide use as traditional medicine, ginseng is also used for other purposes. Therefore, discrimination

this website and differentiation between these two herbal genera are of importance in terms of food safety and pharmaceutical value. As the characteristics, morphology, and chemical compositions of P. ginseng and P. quinquefolius are very similar, use of traditional methods based on morphological and physicochemical characteristics enough for identification of these two genera is rather problematic. The study of the currently known most reliable method is based on chromatographic separation of isomeric compounds of ginsenoside Rf and 24(R)-pseudoginsenoside F11, two potential markers present in P. ginseng and P. quinquefolius [3], [4] and [5]. In recent years, attempts have been made to solve this problem using metabolomics [6]. Metabolomics is a relatively new field of “omics” research concerned with the high-throughput identification and quantification of small-molecule metabolites in the metabolome. It has emerged as an important tool in many disciplines such as human diseases and nutrition, drug discovery, and plant physiology [7], [8], [9], [10], [11] and [12]. The metabolome of an organism is a compilation of all of its metabolites. Metabolites are small molecules; polymeric biomolecules, such as polysaccharides, lignin, peptides, proteins, DNA, and RNA, are excluded from this category. For this reason, metabolomics is called “a snapshot of an organism,” showing which compounds are present and in what quantities at a given time point.

“Leaf area as photosynthetically active area is one of

“Leaf area as photosynthetically active area is one of

the main drivers for tree growth and thus an important tree characteristic for tree growth studies. For silvicultural purposes trees have to be considered as parts of stands, and individual tree growth has to be investigated in relation to stand structure. Thus, O’Hara (1988) Gefitinib cost used the area for individual trees as a measure of site occupancy. Leaf area in relation to stand parameters, e.g., ground area potentially available (APA), which could be named as individual tree leaf area index, but also leaf area in relation to stemwood increment which is described as growth efficiency (Waring, 1983) are important research issues. However, leaf area is hard to determine precisely and non-destructively. For leaf area index determination of stands various optical instruments like LAI-2000 (Li-Cor) or SunScan (Delta-T) are available. But these instruments are limited by the complexity of the canopy structure and improvement in accuracy is still needed (Moser et al., 1995, Chen et al., 1997, Pokorny and Marek, 2000 and Pokorny et al., 2004). Another

way to determine stand leaf area index is to use the individual tree leaf area. Hence, different approaches to estimate individual tree leaf area in an indirect way were and are investigated. Such investigations aim at strong relations of leaf area to other tree characteristics. Based on the pipe model of Shinozaki et al. (1964), selleck chemicals which supposed that a given leaf area is supplied GPX6 with water from a respective quantity of conducting pipes, mainly sapwood area (e.g., Waring et al., 1982, Bancalari et al., 1987 and Meadows and Hodges, 2002), early sapwood area (Eckmüllner and Sterba, 2000), and diameter at breast height (e.g., Gholz et al., 1979 and Baldwin, 1989) are used as estimators for leaf area or leaf biomass. A few studies deal with estimating leaf area with allometric functions based on different other

tree characteristics (e.g., Pereira et al., 1997 and Kenefic and Seymore, 1999). The majority of studies dealing with indirect leaf area estimation describe sapwood area as the most accurate estimator for leaf area (e.g., Long et al., 1981, O’Hara and Valappil, 1995 and Meadows and Hodges, 2002). But to get continuously information about leaf area and related characteristics, e.g., growth efficiency, and their development over time, the determination via sapwood area is not feasible, because from the same trees cores cannot be taken every 5 or 10 years over a long term. Additionally, it is well known that the relationship between leaf area and sapwood area, even within species, is not constant. Differences could be shown between sites, crown classes, stand density, and age (Long et al.

The Journal regrets this error “
“Due to an oversight, the

The Journal regrets this error. “
“Due to an oversight, the authors omitted follow-up data from the article titled, “Squamous Odontogenic Tumor-like Proliferations in Radicular Cysts: A Clinicopathologic Study of Forty-two Cases,”" by Rinku M. Parmar, Robert B. Brannon, and Craig B. Fowler, Veliparib manufacturer which was published in J Endod 2011;37:623–6. In the article, this data should follow the section, “Histopathologic Features.” The missing text appears below. Follow-up information was available for 11 cases. The range of follow-up was 1 month to 10 years, and the average length of follow-up was 2.5 years. There were no recurrences or unexpected clinical

behavior reported among the 11 cases with follow-up. “
“Microbial control is paramount in clinical endodontics 1 and 2.

Among the treatment steps, chemomechanical procedures play a pivotal role in eliminating or reducing bacterial populations from the main root canal, but the disinfecting effects of instruments and irrigants may be somewhat hampered in cases with complex anatomy. A clear example includes the cross-sectional root canal configuration, which has been classified as round, oval, long oval, flattened, or irregular (3). Oval, long oval, and flattened canals are those presenting a ratio between the maximum and minimum cross-sectional diameter of less than 2:1, 2 to 4:1, and greater than 4:1, respectively (3). Numerous studies have reported that hand and rotary instrumentation of

E7080 oval-shaped canals leaves unprepared buccal and lingual extensions or recesses 4, 5, 6, 7, 8 and 9, which can harbor remnants of necrotic pulp tissue and bacterial biofilms. Moreover, recesses can be packed with dentin debris generated and pushed therein by rotating instruments (10). Residual biofilms and infected debris can serve as a potential source of ADP ribosylation factor persistent infection and treatment failure (11). Some approaches have been suggested to deal with the problem of cleaning and disinfecting oval canals. Ultrasonic instrumentation (12) and a combination of rotary nickel-titanium (NiTi) instruments and hand instrumentation with a modified Hedström file were reported to improve the preparation (13), but no technique completely cleaned oval-shaped canals. A histologic study (8) reported that preparation with hand Hedström files and another two techniques (anatomic endodontic technology and rotary NiTi instruments) failed to completely prepare and clean oval canals. Another recent study (7) evaluated the prepared surface areas of oval-shaped canals using four different instrumentation techniques: Hedström files in circumferential filing, ProTaper NiTi rotaries considering the oval canal as 1 canal, ProTaper considering buccal and lingual aspects of the oval canal as 2 individual canals, and ProTaper in a circumferential filing motion.

PRNT50 and DENV neutralization in THP-1 were carried out on the c

PRNT50 and DENV neutralization in THP-1 were carried out on the convalescent sera as described previously (Chan et al., 2011). In these experiments, DENV-1 (07K2402DK1), DENV-2 (ST), DENV-3 (05K802DK1) and DENV-4 (05K2270DK1) were used. To determine PRNT50 titers, serial 2-fold dilutions of the sera were incubated with 40 pfu of DENV at 37 °C for 1 h before adding to BHK-21. The serotype with the highest dilution that neutralized 50% of the plaque forming units was interpreted as causative

of the acute infection. Complete (100%) DENV neutralization in THP-1 was determined by incubating serial 2-fold dilutions of sera with DENV, before adding to THP-1 at a multiplicity selleck inhibitor of infection of 10. After 72 h incubation, plaque assay on BHK-21 was performed on the THP-1 culture supernatant. The serotype with the highest dilution that neutralized 100% of DENV was interpreted as causative of the acute infection. We also reacted

sera with DiD (1,1-dioctadecyl-3,3,3,3-tetramethylindodicarbocyanine, 4-chlorobenzenesulfonate salt)-labeled DENV (van der Schaar et al., 2007), at dilutions where 100% neutralization of DENV was seen in THP-1 and performed confocal immunofluorescence microscopy to assess for FcγR-mediated this website phagocytosis at 30 min post-inoculation (Fig. 1). Complete DENV neutralization with FcγR-mediated phagocytosis was taken as the serotype of the acute infection (Fig. 1). The RT-PCR findings in the respective acute sera were un-blinded only upon completion of the serological analyses. Of the 30 convalescent samples, only eight (26.7%) showed PRNT50 to a single serotype. Similarly, these eight sera displayed neutralizing titers to a single serotype in THP-1, all of which neutralized DENV in the presence of FcγR-mediated phagocytosis (Table 1). Among the remaining 22 convalescent sera, the highest PRNT50 titer was consistent with the serotype detected by RT-PCR in the acute sera in 15 cases (68.2%, 95% confidence interval (95% Phosphoglycerate kinase CI) 45.0–86.1%). In the 11 samples where the highest PRNT50 titer was at least 4-fold or higher than those of the other serotypes, the highest PRNT50 titer was consistent with the serotype of the

infection. However, in the other 11 of the samples that showed (i) identical titers to two serotypes or (ii) only 2-fold difference between the highest and the next highest titer, only 4 (36%) were consistent with the serotype of the infection (Table 1). Using the highest dilution that mediated 100% DENV neutralization in THP-1, only 13 out of the 22 cases correctly identified the serotype of infection (59.1%, 95% CI 36.4–79.3%) (Table 1). Confocal imaging, however, clarified the serotype of the acute infection, where 20 out of the 22 cases (90.9%, 95% CI 70.8–98.9%) showed complete DENV neutralization in the presence of FcγR-mediated phagocytosis (Table 1). Overall, the accuracy of PRNT50, 100% neutralization in THP-1 and confocal imaging were 76.7% (95% CI 57.7–90.1%), 70.0% (95% CI 50.6–85.3%) and 93.3% (95% CI 77.9–99.

One might wonder, for example, whether participants with superior

One might wonder, for example, whether participants with superior response inhibition performed better during retrieval practice and strengthened Rp+ items to a greater extent than individuals with inferior response inhibition. Although faster SSRTs did predict modestly better performance during retrieval practice (r = −.13, p = .34), as well as marginally selleck screening library greater benefits from retrieval practice on the final test (r = −.23, p = .08), the correlation between retrieval-induced forgetting and SSRT remained significant even when controlling for variance in these benefits.

Indeed, the partial correlation observed between SSRT and RIF-Z controlling for both practice performance and practice benefits (r = −.29, p = .03) was quite similar to the non-partial correlation observed (r = −.31). Furthermore, for completeness, we repeated the regression analysis while controlling for practice performance and practice benefits, and the same pattern of results was observed.

Recall performance generally declines as a function of serial position in a test sequence. This output interference E7080 datasheet effect is another manifestation of retrieval-induced forgetting (Anderson et al., 1994). As such, we can also examine the relationship between SSRT and this effect of forgetting. In particular, in the category-plus-stem final test condition, we tested participants on the Rp− items before testing the Rp+ items to ensure that any impairment observed for Rp− items did not arise from the prior output of Rp+ items. Correspondingly, we tested half of

the Nrp items in the first half of the test, to use as a baseline for Rp− items, and the other half of the Nrp items in the second test half, to use as a baseline for Rp+ items. This arrangement provides ADP ribosylation factor a controlled manipulation of output position for Nrp items that allows us to estimate retrieval-induced forgetting at test. Specifically, as a result of testing Nrp− items first, the retrieval process engaged on those test trials should cause the retrieval-induced forgetting of the as-of-yet to-be-recalled Nrp+ items. Indeed, as would be predicted, Nrp+ items were recalled significantly less well than were Nrp− items, t(59) = 5.43, p < .001, d = −.70, thus demonstrating that Nrp+ items suffered retrieval-induced forgetting as the result of the earlier testing of Nrp− items. Using these data, an additional retrieval-induced forgetting score was calculated for each participant by subtracting Nrp+ recall from Nrp− recall, and then z-normalizing the scores within each counterbalancing condition. Importantly, individual differences in SSRT correlated significantly with this independent measure of retrieval-induced forgetting, with faster SSRTs (better inhibitory control) predicting larger test-based retrieval-induced forgetting effects, r = −.44, p < .001.

This includes quantifying the state of the environment prior to a

This includes quantifying the state of the environment prior to and during

a non-indigenous species invasion, and its recovery state following their eradication. This information is not generally available, particularly on oceanic islands with no long-term history of human occupation or scientific monitoring. In the absence of such information, a palaeoecological approach (the study of past environments) may be used. Palaeoecological methods have been extensively used around the world to examine the influence of humans on landscapes including lakes and rivers and their catchments. As a result, their value for providing a framework against which to assess ecosystem impacts and response and recovery is well recognised (see Bennion and Battarbee, 2007, Crutzen

see more and Stoermer, 2000, Froyd and Willis, 2008 and Smol, 2008 for examples and reviews). Palaeoecological methods have previously been applied on oceanic islands such as the Galapagos Islands, Hawai’i’ and the Azores showing that their highly diverse pre-Anthropocene landscapes were completely transformed with the arrival of humans and the introduction of non-indigenous species. This in turn caused a decline BGB324 in biodiversity and the extinction of many native species (Athens, 2009, Burney and Burney, 2007, Burney et al., 2001, Connor et al., 2012 and van Leeuwen et al., 2008). Lakes provide a particularly useful cAMP palaeoecological archive as their sediments accumulate in layers over time and integrate information from both the lake and its surrounding catchment (Smol, 2008). These layers of sediment may be dated and changes in

a lake and its surrounding environment studied over time using a range of biological and non-biological proxies. Anthropogenic impacts are often particularly well recorded (Smol and Stoermer, 2010) and lake sediments can therefore provide long-term data on the state of the catchment and lake prior to, during and after the introduction of an invasive species (Korosi et al., 2013). These data can include measures of changes in soil erosion rates, vegetation (Restrepo et al., 2012 and Sritrairat et al., 2012), and within-lake production (Bradbury et al., 2002 and Watchorn et al., 2011). This study presents a palaeoecological study of a lake in a heavily rabbit-impacted area on sub-Antarctic Macquarie Island (54°30′ S, 158°57′ E, 120 km2, Fig. 1). A sediment core collected from the bottom of Emerald Lake was analysed to assess changes in sedimentation rates, grain size distribution, geochemical properties and diatom composition over the last ca. 7200 years.