Ten grams of each honey sample were taken, diluted in tepid water

Ten grams of each honey sample were taken, diluted in tepid water and 95% ethanol, centrifuged, de-hydrated with anhydrous acetic acid, submitted to the acetolysis method with acetic anhydride and sulfuric acid (9:1) and successively centrifuged (Erdtman, 1960). After the acetolysis process, slides containing glycerinated gelatin were prepared for the mounting of the pollen grains, which were later examined and identified by optical microscopy. The frequency classes were established from counting at least 300 pollen grains for each honey sample. The classification was based upon

the following criteria: predominant pollen type (DP, >45%), secondary pollen type (SP, 16–45%), important minor pollen (IMP, 3–15%) and minor pollen (MP, <3%). The identification of pollen types found in each sample was based on Alpelisib mouse pollen catalogues and comparison with the slide collection of the pollen libraries from the Federal University of the West of the Pará (PUFOPA) and the State University of the Santana

Fair (PUEFS). The determination of total phenolic content of the honey samples and the ethyl acetate fractions (EtOAct) was conducted www.selleckchem.com/products/LY294002.html by the colorimetric Folin–Ciocalteu method (Slinkard & Singleton, 1977). A 300-μL aliquot of methanol extract (5 mg mL−1 in MeOH) was transferred to a test tube containing 60 μL of the Folin–Ciocalteu reagent and 2.46 μL of distilled water. The mixture was stirred for 1 min before 180 μL of Na2CO3 (15%) were added. The contents were stirred for an additional 0.30 min to obtain a final extract concentration of 0.2 mg mL−1. The samples were kept in the dark for 2 h prior to analysis using a UV–Vis spectrophotometer at 760 nm. The total phenolic content (TFC) was determined EGFR antibody inhibitor by interpolation of the sample absorbance against a calibration curve built with gallic acid standards (0.001–0.015 mg mL−1

in ethanol) and expressed as milligrams of gallic acid equivalents per gram of extract (mg GAE/g). All the analyses were performed in triplicate. The ABTS test was performed according to the methodology reported by Re et al. (1999). The cation radical ABTS + was synthesised by the reaction of a 7 mM ABTS solution with a 2.45 mM potassium persulfate solution. The mixture was kept at 23 °C in the dark for 16 h. Afterwards, the ABTS + solution was diluted with ethanol until an absorbance (A) of 0.7 at 734 nm was achieved in a UV–Vis spectrophotometer. Aliquots of 2.7 mL from the ABTS + solution were added, immediately after being prepared, to the sample solutions diluted in methanol (MeOH) to reach final concentrations between 0.1 and 0.5 mg mL−1. After 10 min, the percentage inhibition of absorbance at 734 nm was calculated for each concentration, relative to the blank absorbance (ethanol).

There are a number of emerging rapid non-destructive methods for

There are a number of emerging rapid non-destructive methods for chemical grouping of foods such as the direct injection mass spectrometric techniques (DIMS), atmospheric pressure chemical ionisation mass spectrometry (APCI-MS) (Davies, Linforth, Wilkinson, NLG919 Smart, & Cook, 2011), proton transfer reaction mass spectrometry (PTR-MS) (Biasioli, Yeretzian, Gasperi, & Mark, 2011) and selected ion flow tube mass spectrometry (SIFT-MS) (Langford et al., 2012) have gained the attention of the researchers working in the field

for classification and authenticity, due to their ability to perform real time non-invasive analysis with high sensitivity and limited sample pre-treatment. PTR in combination with a time-of-flight mass spectrometer (PTR-ToF-MS) have been extensively used for classification studies of a broad range of food products including PDO cheese, olive oil and dry cured hams, intact fruits and their derivatives (Aprea et al., 2006, Biasioli et al., 2003, Cappellin et al., 2012, Del Pulgar et al., 2011 and Galle et al., 2011). In these cases, classification typically uses the data matrix resulting

from the entire mass spectrum (spectral fingerprint) and statistical treatment to identify clusters, trends or correlations, appropriate data mining techniques may C59 wnt include partial least squares discriminant analysis (PLS-DA), K-nearest neighbours (KNN), soft independent modelling of class analogies (SIMCA) (Fisk, Virdie, Kenny, & Ullrich, 2010) support vector machine (SVM) and random forest (RF) (Cappellin et al., 2012). Whist direct injection mass spectrometric techniques are rapid and information rich, gas phase chemometric classification approaches should always take into consideration

the availability of volatile compounds in the gas-phase and the equilibrium concentration difference between the product and its gas phase. The chemical potential of a volatile component is dependent Methane monooxygenase firstly on the physicochemical properties of the analyte, the physical structure of the matrix (Yang et al., 2012 and Yu et al., 2012), the presence of multiple phases (Fernández-Vázquez et al., 2013 and Fisk et al., 2011) and chemical composition of the product being analysed (Fisk, Boyer, & Linforth, 2012). It is therefore important to consider that modifications to the product non-volatile composition may have a significant impact on the aroma profile and therefore where appropriate, standardisations should be applied.

Samples were then fixed on stubs and coated with a thin

Samples were then fixed on stubs and coated with a thin Vemurafenib manufacturer gold layer using a cool sputter-coater (Blazers SCD 005, Liechtenstein). The chitosan crosslinked with the chelating agent 8-hydroxyquinoline-5-sulphonic acid and glutaraldehyde and the microspheres were

obtained according to a procedure described in the literature (Vitali et al., 2008). The sensor was constructed as follows: 30 mg (15% w/w) of chitosan microspheres and 130 mg (65% w/w) of graphite powder were mixed in a small mortar for 20 min to form a homogeneous mixture and 40 mg (20% w/w) of Nujol was then added followed by mixing for another 20 min. The resulting modified carbon paste was tightly packed into a syringe and a copper wire was introduced into the other end for electrical contact. A bare carbon paste electrode (CPE), used for comparison purposes, was prepared as previously described, using GDC-0199 manufacturer only graphite powder and Nujol in the proportion of 65:35% w/w (Oliveira, Fernandes, & Vieira, 2006).

In a typical procedure for electrochemical measurements, 10.0 mL of the acetate buffer solution (pH 6.0) was transferred to a clean dry cell and successive additions of standard or sample solutions of Cu(II) were added by micropipette. The voltammetric procedure consisted of pre-concentration (accumulation), stripping (detection), and electrode regeneration steps. During the pre-concentration step, the electrode was immersed in the cell containing the supporting electrolyte and the metallic ion

solution. A negative controlled potential (−0.1 to −0.7 V) was applied to the sensor for a specified time (0–300 s). The solution was stirred using a magnetic stirring bar. Stripping voltammetry was then Exoribonuclease performed in the same cell with a sweeping square wave potential toward the positive direction (from −0.3 to 0.1 V), at frequencies of (f) 1.0–50 Hz, pulse amplitudes (a) of 10–50 mV and scan increments (ΔEs) of 1.0–10 mV, after successive additions of the analyte. The electrode cleaning step was performed by applying a positive potential under stirring. No de-aeration of solutions was required in any step. The sample and blank solutions were prepared following previously described procedures (Onianwa, Adetola, Iwegbue, Ojo, & Tella, 1999). Briefly, three samples of instant coffee (A, B and C) were obtained from local supermarkets in Florianópolis (Santa Catarina, Brazil). For the sample preparation, 1.0 g of instant coffee was weighed in triplicate in porcelain crucibles and mineralised in a muffle furnace at 550 °C for 20 h. The mineralisation step is necessary in order to eliminate the organic compounds present in the coffee sample, which can act as complexing agents for many metals (including Cu(II)) and can thus affect the results if present in the sample. The residue was dissolved with 0.2 mL of 1.0 mol L−1 nitric acid and diluted to 3.0 mL with acetate buffer solution (0.1 mol L−1, pH 6.0).

For example, we could not account for differences in chemical exp

For example, we could not account for differences in chemical exposure between different types

of fish and between fish captured from wild fisheries selleck or harvested in fish farms. In addition, only current dietary habits were assessed, which could differ from dietary habits in the past that would also have contributed to the body burden at time of study. Due to these limitations, we may not have been able to detect endocrine disrupting effects of dietary sources of persistent chemical exposures. We also assessed associations between the DR CALUX® measurements and other potential determinants for internal exposure to persistent endocrine disrupting chemicals, including age, BMI, weight loss, and living within a city centre, but the effect estimates were inconclusive (Supplemental Table 2). We did, however, identify a positive association between plasma androgenic activity and the internal dioxin TEQ values over a small range (Table 5). An inverse association between CALUX® TEQs and total and free testosterone in male serum has been reported (Dhooge et al., 2006), as well as between CALUX® TEQs and AEQs in fetal plasma after MTBE extraction (R = − 0.7)

(Pedersen et al., 2010). Selleckchem Alectinib Pliskova and colleagues measured a reduced estrogenic activity in male serum extracts containing high levels of PCBs, which seemed to be associated with a decline in endogenous estradiol (Pliskova et al., 2005). In our study, plasma TEQs were not associated with reduced estrogenic activity in total plasma, but this could also be due to the lower exposure levels. Estrogenic and/or androgenic plasma activities seemed to be increased in men occupationally exposed to disinfectants, Sucrase pesticides, welding or soldering, and vehicle exhaust fumes. These exposures occurred in very diverse occupational settings and often involved mixtures of different substances. As co-exposure to other chemical groups was very common, it was difficult to attribute differences in estrogenic or androgenic activities to specific exposures. In general, multivariable analyses with adjustment for co-exposures did not drastically change the effect estimates. However, reliable estimation of the independent effects of disinfectants, pesticides,

welding or soldering, exhaust fumes, and other occupational exposures, requires a larger population size that allows more specific exposure classification. We interpret the present findings as indications that various occupational exposures can alter estrogenic or androgenic activities and are therefore potentially relevant sources of endocrine disruptors. As pointed out, further research is needed to elucidate the effects of different sources of endocrine disruptors on the estrogenic and androgenic plasma activities in men. Including internal measurements of certain groups of chemicals such as dioxins in future research, could clarify their specific role in the estrogenic and androgenic activities found, especially if these chemicals have long half-lives of excretion.

60% Though our cores were by necessity taken from areas without

60%. Though our cores were by necessity taken from areas without smouldering, and after the flaming surface fire had been extinguished, smouldering was still underway when these samples were collected. In further lab experiments Benscoter et al. (2011) achieved successful peat combustion at moisture contents as high as 295% and observed smouldering continuing at higher moisture contents than those required for ignition. Both our and Benscoter et al.’s (2011) results therefore have implications for forecasting the selleck chemical potential maximum spread of smouldering wildfires. It is important that ignition and combustion limits are explored in greater detail

as they appear to be highly sensitive to fuel structure, fuel moisture and ignition mechanisms. Smouldering appeared to have occurred preferentially around the bases of trees and to have followed the root network, meeting those from the adjacent plants, thus propagating along the line of trees. Whether this was a result of peat being drier due to mounding from ploughing or due to the presence of the trees themselves was unclear as there was little peat left around tree bases leaving no Tyrosine Kinase Inhibitor Library or little evidence of the original micro-topography. However, a number of isolated trees on the

moorland area outside the forest had significant peat consumption around their bases matching the observations of Miyanishi and Johnson (2002). Our results suggest that it is important to investigate the extent to which plantation forestry on peat

soils, and associated ploughing, draining and ridging prior to planting, leads to peat desiccation Cediranib (AZD2171) and increased peat fire hazard. Smouldering was still occurring in isolated locations at the perimeter of the fire 33 days after the initial surface fire despite a number of days with rain. The fire spread was primarily through the peat and the propagation front formed a cavity beneath the damp moss/duff layer undercutting it by up to a metre. The heat produced by smouldering dried out the overlying material which subsequently ignited and burnt via smouldering or flaming combustion. This produced a pattern of fire spread characterised by gradual extension of the smouldering front below the duff, moss and litter followed by sudden ignitions and collapses of this surface material. This observed spread pattern compares favourably with changes in fuel moisture indices during and after the fire (Fig. 2). An initial period of high fire risk with conditions suitable for the spread of both surface flaming and subsurface smouldering combustion (high FFMC and high DC, Fig. 2) gave way to low FFMC (low fire danger) at the time of our visit. The DC however remained high, suggesting smouldering could continue, due to the long lag-time of this moisture code and the need for more substantial amounts of precipitation to re-wet subsurface fuel layers.

, 2011 and PEN, 2013) Completed syntheses of the PEN data have n

, 2011 and PEN, 2013). Completed syntheses of the PEN data have not yet been published, but preliminary analyses provide results that are consistent with those of earlier NTFP studies (Table 1). There have been many studies investigating ancient forest management practices for indigenous food plants in parts of Latin America (e.g., Levis et al., 2012 and Peters, 2000) and Southeast Asia (e.g., Michon, 2005 and Wiersum, 1997), but relatively few in Africa Rigosertib nmr (although see, e.g., Leakey et al., 2004 and Maranz

and Wiesman, 2003). Ancient harvesting, managed regeneration and cultivation have, for example, led to genetic changes in many Amazonian fruit trees and palms (Clement, 1989). These include abiu (Pouteria caimito), Amazon tree grape (Pourouma cecropiifolia), araza (Eugenia stipitata), biriba (Rollinia mucosa), peach

palm (Bactris Etoposide order gasipaes) and sapota (Quararibea cordata). In Africa, rarer reports of changes in the characteristics of fruits attributed to ancient domestications include bush mango (Irvingia gabonensis and Irvingia wombolu) and safou (Dacryodes edulis) ( Leakey et al., 2004). Again, areca (Areca catechu), coconut (Cocos nucifera) and date (Phoenix dactylifera) are all palms for which changes in fruit size, in the proportion of useable product, and in the ability to be propagated, are attributed to long-past Parvulin human selections ( Clement, 1992), while an expanding list of global studies on ancient domestications includes many more food trees ( Clement, 2004). In perhaps the best studied case, in Amazonia, Amerindian populations declined after European colonial contact, which resulted in the erosion of the rich tree crop genetic heritage they had established (Clement, 1999). The effects of pre-Columbian forest management remain, however, including high density aggregations of useful trees close to ancient anthropogenic ‘dark earth’ soils (Clement and Junqueira, 2010) and in interfluvial regions (Levis et al., 2012), with Brazil nut (Bertholletia excelsa) being

the most famous example ( Shepard and Ramirez, 2011). A review of molecular genetic studies ( Clement et al., 2010) suggested that current centres of genetic diversity in fruit and nut trees are generally located in the centre of the Amazon Basin along the major white water rivers where large pre-Colombian human populations developed, while the periphery of the basin has had an important role in domestication origins. This suggests that subtle differences in the focus of management programmes for conservation and genetic improvement may be required in different geographic regions of the Amazon, and indicates the importance of germplasm exchange and dispersal during ancient domestication processes.

Buccal swabs from all donors

Buccal swabs from all donors OTX015 clinical trial (138 males, 102 females) that had been collected over the past year were used to generate a reference database. This donor pool consisted of current employees, employee family members and former employees.

The swabs were prepared using a slight modification of the GlobalFiler Express buccal swab protocol [16]. Briefly, 300–400 μL of Prep-N-Go™ Buffer (ThermoFisher Scientific) was added to 1.5 mL Eppendorf tubes. The cotton swab was inserted into the tube with buffer and incubated at 70 °C (vs. 90 °C) in a heating block for 15 min. The lysates were used to obtain an STR profile as described below. The human male fibroblast cell line HTB-157 (ATCC, Manassas, VA), designated 1000 M, was used to prepare positive control swabs. The human embryonic palatal mesenchymal (HEPM) cell line CRL-1486™ (ATCC, Manassas, VA), designated 1000 F, was used for the mixture study. Cell culture optimization Vemurafenib mw and scale up was performed under contract by Aragen Bioscience (Morgan Hill, CA), and cells were stored in 90% FBS, 10% DMSO at −80 °C. Cells were washed and resuspended twice in PBS buffer, quantified using a Scepter Handheld Automated Cell Counter (Millipore, Billerica, MA), and brought up to a working concentration between 200,000 and 10,000,000 cells/mL. 50 μL aliquots of the appropriate dilution of cells were added to swabs which were air dried at room temperature overnight. A

reference profile for 1000 F was obtained as described above for buccal swabs. The 1000 M cell line is the same as component eltoprazine F in the National Institute of Standards and Technology (NIST, Gaithersburg, MD) DNA Profiling Standard SRM 2391c and the certified profile from NIST was used as the reference for concordance. Blood samples in EDTA tubes from three different donors were purchased from Memorial Blood Center (Minneapolis, MN). Two-fold serial dilutions of blood from each donor (20–2.5 μL and 1 μL) were applied to swabs. To prepare these swabs, an aliquot of each blood dilution was pipetted onto a glass slide. Then, a swab wetted with sterile water was used to recover the diluted blood from the slide. The concentration of

DNA in each blood sample was determined to calculate the amount being applied onto the swab at each dilution. DNA was extracted from 40 μL of blood from each donor using PrepFiler Forensic DNA Extraction kit (ThermoFisher Scientific) and the amount of DNA quantified in triplicate with Quantifiler Human DNA Quantification Kit (ThermoFisher Scientific) on a Applied Biosystems 7500 Real-Time PCR system v1.4 according to the manufacturer’s protocols [17] and [18]. The DNA Profiling Standard SRM 2391c, produced by NIST (Gaithersburg, MD), was used to test the accuracy of allele calls against NIST certified genotypes. For testing on the RapidHIT System, DNA from components A–D were added to the GlobalFiler Express STR reagents at 1–2 ng/20 μL.

9 mg/kg) and xylazine

(3 6 mg/kg) then inoculated intrana

9 mg/kg) and xylazine

(3.6 mg/kg) then inoculated intranasally with 500 μl (250 μl per nostril) PFI-2 ic50 of 100 TCID50 2009 influenza virus A/California/04/09 (A/Cal; H1N1). Solutions were prepared on the day of challenge and the titre of the virus confirmed by infectivity assay. Control groups were infected with virus or inoculated with saline. Rectal temperatures were measured daily. Ferrets were monitored twice-daily post-challenge throughout the course of the study for clinical signs of influenza infection (lack of activity, sneezing, nasal discharge, lack of appetite, weight loss and pyrexia). Clinical signs were scored as follows: loss of activity scored 0 for normal activity levels, 1 for reduced activity, and 2 if inactive; nasal discharge scored 0 for no discharge and 1 for a discharge; sneezing scored 0 for no sneezing, and 1 for sneezing; appetite was scored 0 for no loss of appetite, and 1 for loss of appetite. Nasal washes were collected from each ferret following ketamine and xylazine sedation (as above) at days 1–6 and then at days 8, 10 12 and 14 post-challenge. For each nasal wash, 2 ml of PBS were instilled by small multiple volumes into each nasal cavity with expectorate collected into a beaker. The study was terminated at 14 days post-challenge. 244 DI RNA was generated spontaneously during the transfection of 293T cells with plasmids to

make infectious GW-572016 mouse influenza A/PR/8/34 (Dimmock et al., 2008 and Subbarao et al., 2003). The haemagglutinin (HA) protein of the original 244/PR8 virus had a preference for cell receptors comprising α2,3-linked sialyl receptor sequences, so we reconstructed 244 DI virus with the HA protein of a PR8 virus that binds to both α2,6- and α2,3-linked sialyl receptors (Meng et al., 2010), so that DI RNA would be delivered to cells bearing both types of receptor, and thus protect against

infectious viruses which recognise either type of receptor as described previously (Meng et al., 2010). The resulting mixture of 244/PR8 DI virus and infectious helper A/PR8 virus was purified by pelleting through sucrose. Stocks were resuspended in PBS, standardized by haemagglutination SPTLC1 titration, and stored in liquid nitrogen. All DI virus stocks were tested for their ability to protect mice as described previously (Dimmock et al., 2008) prior to their use in ferrets (data not shown). Before inoculation into animals, helper virus infectivity was eliminated with a short burst (50 s) of UV irradiation at 253.7 nm (0.64 mW/cm2). This is referred to as ‘active DI virus’. The UV inactivation target is viral RNA, and UV has little effect on the DI RNA because of its small target size, 395 nt compared with 13,600 nt for infectious virus. The absence of infectivity after UV-irradiation was checked by infectivity assay (see Section 2.4) and by intranasal inoculation into mice (Dimmock et al., 2008).

10) Of the 404 sequence of dams, 73% are closer than 100 km to e

10). Of the 404 sequence of dams, 73% are closer than 100 km to each other. Results show that the 512 km

between the Garrison and Oahe Dam is not enough distance to consider these dams separately. We propose a conceptual model of how a sequence of interacting dams might impact river geomorphology (Fig. 11) based on our results. We call this morphologic sequence the Inter-Dam Sequence, and we present a simplified model based on the Upper Missouri River that could be easily adapted to other river reaches. Although the morphologic sequence is a useful conceptualization, there are clear limitations to these results. www.selleckchem.com/products/gsk1120212-jtp-74057.html This model is likely only applies to large PCI-32765 clinical trial dams on alluvial rivers. Dams on rivers that are controlled by bedrock or where morphologic adjustment is limited by vegetation or cohesive banks may respond completely different than the model presented here. Similarly, the downstream effects of small dams will likely attenuate

over much shorter distances. However, this framework is a helpful advancement in our understanding of longitudinal responses to multiple dams. One of the greatest influences that humans have had on the fluvial landscape is the construction of dams. Despite significant advancements in the study of the downstream and upstream impacts of dams, they are often considered separately from each other. The Garrison and Oahe Dama on the Missouri River are used to demonstrate RAS p21 protein activator 1 that the effects of an upstream dam maintains significant geomorphic control over river morphology as the backwater effects of downstream reservoir begin to occur. The upstream–downstream interaction of multiple dams overlap to create a distinct morphologic sequence.

Five unique geomorphic gradational reaches were identified for the Garrison Reach, two of which are controlled solely by the upstream dam and three of which are controlled by the dam interaction termed: Dam Proximal, Dam-Attenuating, River-Dominated Interaction, Reservoir-Dominated Interaction, and Reservoir. A conceptual model was developed of a morphologic sequence of downstream dam impacts and dam interaction which can be adapted to other rivers. The current distribution of dams on the major rivers in the U.S. indicates that more than 80% of large rivers may have interacting between their dams. Given this widespread occurrence, we describe a generalized morphologic sequence termed the Inter-Dam Sequence and suggest it should be the focus of additional research. We would like to acknowledge project funding from the following sources: U.S. Army Corps of Engineers, ND State Water Commission, ND Department of Transportation, ND Game and Fish Department, ND Department of Health, City of Bismark, City of Mandan, Burleigh County WRB, Morton County WRB, and Lower Hart WRB.

e , Alroy, 2000 and Alroy,

2008), however, have called in

e., Alroy, 2000 and Alroy,

2008), however, have called into question whether all of these mass extinctions are truly outliers and substantially different from the continuum of extinctions that have been on-going for hundreds of millions of years. Multiple mass extinctions have occurred over the course of earth’s history, but they are relatively rare, poorly defined, and often played out over millions of years. The one exception is the Cretaceous-Paleogene extinction event (a.k.a. the K-T boundary event), when ∼76% of the world’s species went extinct within a few millennia (Renne et al., 2013). Most scientists implicate a large asteroid impact ca. 65.5 mya as the prime driver for this mass extinction, characterized by the disappearance of non-avian dinosaurs and the dawn of the age of mammals. The Big Five concept has become such an engrained part of the geologic and other sciences

that some scholars use the term “sixth extinction” to characterize Olaparib selleck products the current crisis of earth’s biological resources (e.g., Barnosky et al., 2011, Ceballos et al., 2010, Glavin, 2007 and Leakey and Lewin, 1995). Long before the formal proposal to define a new Anthropocene Epoch (Zalasiewicz et al., 2008), a variety of scientists identified post-industrial humans as the driving force behind the current and on-going mass extinction (e.g., Glavin, 2007 and Leakey and Lewin, 1995). Clearly we are currently living through a mass extinction event. Calculations suggest that the current rates of extinction are 100–1000 times natural background levels (Vitousek et al., 1997b and Wilson, 2002). Some biologists predict that the sixth extinction may result in a 50% loss of the remaining plants and animals on earth, which might trigger the collapse of some ecosystems,

the loss of food economies, the disappearance of medicinal and other resources, and the disruption of important cultural landscapes. The driving force of this biotic crisis can be directly tied to humans, and their propensity for unchecked population growth, pollution, over-harvesting, habitat alteration, and translocation of invasive species (Vitousek et al., 1997a and Vitousek Acyl CoA dehydrogenase et al., 1997b)—changes Smith and Zeder (2013; also see Smith, 2007) refer to as human niche construction. If we are living during the next great biotic crisis and it is directly tied to human agency, the question becomes when did this mass extinction process begin? Even those who have proposed to formally designate an Anthropocene Epoch beginning at the dawn of the Industrial Revolution (ca. AD 1800) or the nuclear era of the 1960s (e.g. Crutzen, 2002, Steffen et al., 2007, Steffen et al., 2011 and Zalasiewicz et al., 2008) acknowledge the evidence for widespread impacts of pre-industrial humans in archeological and historical records. They recognize a wide range of “pre-Anthropocene Events,” including the acceleration of plant and animal extinctions associated with human colonization of new landscapes (Steffen et al.