Neolithic transition in Europe: the radiocarbon record revisited. (Research).

Neolithic transition in Europe: the radiocarbon record revisited. (Research). Introduction There is a long tradition of using radiocarbon dates to map thespread of farming and the arrival of Neolithic cultures across Europe.Clark (1965) was the first to do this, plotting only the earliestsettlements in each territory; he noted "the need, in view of theelement of uncertainty inherent in individual determinations, to disposeof To determine the fate of; to exercise the power of control over; to fix the condition, application, employment, etc. of; to direct or assign for a use.See also: Dispose samples numerous enough to yield convincing patterns" (1965:66).He was able to discern a pattern of spread into Europe along the Danubefrom an origin in the South East, with a long delay before farmingreached the North European Plain, south Scandinavia, and other places inwestern Europe Western EuropeThe countries of western Europe, especially those that are allied with the United States and Canada in the North Atlantic Treaty Organization (established 1949 and usually known as NATO). from the Alps to northern Britain and Ireland (ibid.:67). Ammerman and Cavalli-Sforza (1971) used regression methods todescribe the average rate at which farming spread. They also used thecorrelation coefficient Correlation CoefficientA measure that determines the degree to which two variable's movements are associated.The correlation coefficient is calculated as: (r) to assess the extent to which regional ratesof spread differed from that overall average. They reported an averagediffusion rate from an assumed origin in Jericho of about 1 km/year, andfound a high value for r (0.89) in their sample of 53 Neolithicsites--suggesting that this rate was quite representative of the processgenerally. However, they also noted evidence for regional variation inrates (from 0.7 km/year in the Balkans, to 5.6 km/year for theBandkeramik culture). Subsequently, they used spatial interpolation interpolationIn mathematics, estimation of a value between two known data points. A simple example is calculating the mean (see mean, median, and mode) of two population counts made 10 years apart to estimate the population in the fifth year. methods to generate isochron maps that plotted the mean rates of spreadof farming (and of the disappearance of hunting and gathering) in twodimensions (Ammerman & Cavalli-Sforza 1984). They conjectured thatthe pattern observed may have been produced, not by cultural diffusion In anthropology, cultural diffusion refers to the spread of ideas, inventions, or patterns of behavior to different societies (Wintrop 1991:82)Since cultures have never been completely isolated from each other, diffusion has happened throughout history, and continues on (the adoption of cultural traits), but by a gradual process of spatialpopulation expansion and replacement. They found support for this `demicdiffusion' model in a synthetic gene map, generated from the SE-NWgradient in the first Principal Component of variation in allele allele(əlēl`): see genetics. alleleAny one of two or more alternative forms of a gene that may occur alternatively at a given site on a chromosome. frequencies of modern Europeans. In their monograph, they reported thatsuch a cline (trend) in gene frequencies was expected where farming hadspread by demic diffusion. The steepness of the cline was modelled as afunction of the rate of reproductive mixing with hunter-gatherers; whenthis rate was very low, the cline would be relatively flat, such thatgene pools near the origin of the diffusion would contain about 90% ofinitial farmers' genes, and gene pools at the periphery wouldcontain 75% of them. Subsequent work has transformed this simple picture. It has beenshown mathematically that identical travelling waves for the spread offarming can be generated by demic expansion, demic diffusion, or bytrait adoption-diffusion (Aoki, Shida & Shigesada 1996).Archaeologists have pointed to the very different rates of the spread offarming in different regions of Europe Europe is often divided into regions due to geographical, cultural or historical criteria. Some common divisions are as follows. Directional divisionsGroupings by compass directions are the hardest to define in Europe, since (among other issues) the pure geographical criteria , and have challenged the use ofsynthetic gene maps to validate the demic diffusion model (since suchmaps contain no information about the chronology of dispersals). Themethodology of generating synthetic gene maps has also been challenged,since it can potentially produce clines even in spatially random data(Sokal, Oden & Thomson 1999). Furthermore, it is now recognized thatgenuine clines in gene frequencies can be produced by populationreplacement with successive founder effects (cf. Barbujani et al. 1995),or by demic diffusion with acculturation acculturation,culture changes resulting from contact among various societies over time. Contact may have distinct results, such as the borrowing of certain traits by one culture from another, or the relative fusion of separate cultures. (cf. Rendine et al. 1996), orby gradients in duration of natural selection when the selectionpressures are initiated by adoption of a new economic strategy, ratherthan by population replacement (Fix 1996, 1997). Some recent genetic studies have found distinctive European mtDNAmatrilineages that have an apparently Upper Palaeolithic or Mesolithiccommon ancestor; it has been estimated by Richards et al. (1996, 1998,2000) that female immigrant farmers contributed only about 20% of themodern European mitochondrial mitochondrialpertaining to mitochondria.mitochondrial RNAsa unique set of tRNAs, mRNAs, rRNAs, transcribed from mitochondrial DNA by a mitochondrial-specific RNA polymerase, that account for about 4% of the total cell RNA that gene pool. A similar conclusion has beenreached with respect to male genetic contributions as measured fromY-chromosome markers (Semino et al. 2000). Thus, much recent geneticwork indicates that, at the continental scale, farming spread intoEurope by a mixture of demic expansion, demic diffusion, and traitadoption-diffusion, with adoption-diffusion as the predominantmechanism. However, other studies suggest that both female and maleimmigrant farmers may have contributed more significantly to the modernEuropean gene pool (~45% of modern Y-chromosomal variation, Rosser etal. 2000; see also for mtDNA: Simoni et al. 2000, and for nuclear genesand classic protein markers: Barbujani and Bertorelle 2001). Moreover,Chikhi et al. (2002) have shown that it is not straightforward to makeinferences from percentages of genes in modern populations to relativeproportions of bearers of genes in the remote past. The link between thetwo has to be modelled mathematically. Chikhi et al.'s resultssuggest that when this is done demic diffusion provides the bestexplanation of present-day patterns. Bentley et al. (2003) synthesiseChikhi's approach with new archaeological evidence for sex-biaseddispersal. Meanwhile, new archaeological models of the transition fromforaging to farming have been proposed which allow a more sensitiveinterpretation of the radiocarbon data. Bogucki (e.g Bogucki &Grigiel 1993) has proposed a two stage (pioneer/established) model ofdemic diffusion in North Central Europe Central Europe is the region lying between the variously and vaguely defined areas of Eastern and Western Europe. In addition, Northern, Southern and Southeastern Europe may variously delimit or overlap into Central Europe. . Zvelebil and collaborators(1991, 1996, 2000) have proposed a three-phase model of the transition(availability, substitution, and consolidation) in which the local andregional rate of spread becomes a measure of the absolute duration ofthese successive transitional phases. It is now widely recognized thatthere may have been significant regional variation in the relativeimportance of demic expansion, demic diffusion, and of traitadoption-diffusion as the mechanisms of spread (see e.g. Arias 1999,Gronenborn 1999). At the same time disagreements continue over thenature of the processes responsible for some of the most important EarlyNeolithic phenomena, especially the spread of the Central EuropeanLinearbandkeramik and the Mediterranean Impressed Ware. One recentdiagram of the regional variation in mechanisms of spread is reproducedin Figure 1 (from Zvelebil & Lillie 2000). [FIGURE 1 OMITTED] It is clear that the time is ripe for a re-evaluation both of theradiocarbon record, and of its potential as a test-bed for alternativemodels of the demography of the Neolithic transition. In this paper wereport our preliminary findings. Methods The basis of our re-evaluation was the collection of a spatialdatabase A spatial database is a database that is optimized to store and query data related to objects in space, including points, lines and polygons. While typical databases can understand various numeric and character types of data, additional functionality needs to be added for databases of radiocarbon dates for the later Mesolithic and earlyNeolithic of Europe, roughly 9000-5000 BP; this time frame covers therange from the later Mesolithic in southeast Europe to the earlierNeolithic in northern and northwest Europe. In addition information wascollected about the contexts of the dates, the material dated andeconomic and cultural associations. Europe was defined as the area tothe west of a line from the Black Sea to the eastern Baltic. It became clear in the course of the project that, despite thelarge sums of money which have been spent over the years on radiocarbondating in Europe, the state of public availability of the dates, theircontext and associations and details which enable users to judge thereliability of dates is in general very poor. Thus, no claim is madethat the database is in any sense complete. To achieve this would take amajor collaborative European exercise over many years. A total of justover 2600 samples were eventually included in the database. Thisinvolved the exclusion of dates about which there were grounds forsuspicion in terms of their reliability and associations. Much of theinformation for this was obtained from Gob (1990) but similar judgementswere also made about other dates on the basis of internal evidence fromtheir sources. Again, we would not claim to avoided errors of bothinclusion and exclusion, for the reasons just mentioned, but since ourinterest is in identifying continent-wide patterns on the basis of largenumbers of observations we do not believe that these affect ourconclusions. The database consists of four main tables apart from thereferences. They are described in Table 1, where shortcomings are alsonoted. The database is available through the UK Archaeology Data Service(http://www.ads.ahds.ac.uk). Analytical approaches Two sets of analyses were carried out using the database: a set ofspatial analyses for the whole of Europe examining the extent to whichthe subsequent accumulation of dates supported or modified the patternssuggested by Clark (1965) and by Ammerman and Cavalli-Sforza (1971,1984); and a further set of analyses by country to look at the relationbetween Mesolithic and Neolithic dates and the light this might throw ondemographic models for the transition. Spatial analyses A set of 508 Neolithic sites and 207 Mesolithic sites was used inthese analyses. The classification of dates as Mesolithic or Neolithicwas on the basis of conventional cultural assignment. While in principleit is important to distinguish the spatial and chronologicaldistribution of different elements of the Neolithic `package', inpractice it is not currently possible to do this given the quality ofthe available information. Nevertheless, we feel that accepting theconventional cultural distinctions gives us a valid initial view of thesituation. A single date was taken for all distinct sites in each of thetwo categories for which latitude./ longitude, co-ordinates wereavailable; at sites where there are multiple radiocarbon dates, only theearliest Neolithic date and/or the most recent Mesolithic date wereused. For the initial analysis, the visualization techniques weresimilar to those used by Clark (1965) and Ammerman & Cavalli-Sforza(1971, 1984). Following Clark (1965), the 508 Neolithic dates were grouped intotemporal categories at 1200-year intervals (in uncalibrated years BC).Following Ammerman & Cavalli-Sforza (1971, 1984), a major axis major axisn.The longer of the two lines about which an ellipse is symmetrical; the axis that passes through both focuses of an ellipse.Noun 1. regression analysis In statistics, a mathematical method of modeling the relationships among three or more variables. It is used to predict the value of one variable given the values of the others. For example, a model might estimate sales based on age and gender. was undertaken of the date of early farming sitescompared with their distance from a nominal origin at Jericho. Neolithicdates (in uncalibrated years BP) were imported into a Grass GIS GRASS (Geographic Resources Analysis Support System) is an open source, Free Software Geographical information system (GIS) with raster, topological vector, image processing, and graphics production functionality that operates on various platforms through a graphical user interface package,and contour lines fitted to the data at 500 year intervals. Theprocedure was first used to produce an isochron map using Ammerman andCavalli-Sforza's data (Figure 2) and then, using the new data-base,for Mesolithic sites (Figure 6) and Neolithic sites (Figure 7). [FIGURES 2, 6-7 OMITTED] We also undertook other map visualizations and statistical analyses(Russell & Steele in press, see also Glass et al. 1999). First, weexperimented with geographically-weighted regression (Fotheringham,Brunsdon & Charlton 2000, 2001), a technique which allows us todetect local variation in trends in large-scale spatial datasets, byweighting each control datum The singular form of data; for example, one datum. It is rarely used, and data, its plural form, is commonly used for both singular and plural. in a regression analysis inversely to itsdistance from a specified point location. A second new method of analysis uses ranges of calibrated datesrather than point values. Ammerman & Cavalli-Sforza's andClark's methodologies used uncalibrated dates and treated thedate's modal value Noun 1. modal value - the most frequent value of a random variablemodestatistics - a branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parameters as a point value. The irregular shape of many ofthe calibrated probability distributions of radiocarbon dates makesstatistical treatment that requires point values problematic (Figure 3).Most commonly this is overcome by treating the modal value of theradiocarbon probability distribution Probability distributionA function that describes all the values a random variable can take and the probability associated with each. Also called a probability function.probability distributionas a point value and using weightedregression to minimize the influence of dates with a large associatederror (e.g. Glass et al. 1999). We wanted to assess how problematic theuse of the modal value might be, particularly in instances when thecalibrated radiocarbon distribution deviates from a normal distribution(for example, Figure 3). To do this dates were calibrated in OxCal3(Ramsey 1999). The area under the calibration curve In analytical chemistry, a calibration curve is a general method for determining the concentration of a substance in an unknown sample by comparing the unknown to a set of standard samples of known concentration. was used tocalculate the probability that a site was occupied within a giveninterval of the calibrated date range. The probability that a site wasoccupied at successive 100-year intervals is reflected by the rise andfall in the area of the circle that marks a site's location. Boththe late Mesolithic and the early Neolithic dates were used in theanalysis. [FIGURE 3 OMITTED] In the second set of analyses dates were categorised by country, togive a broad regional breakdown, and the summed calibrated probabilitiesof the dates were obtained, with Mesolithic and Neolithic datesdistinguished from one another. The rationale for this is the assumptionthat fluctuations through time in the summed probabilities should give ageneral indication of fluctuations in settlement intensity. The factthat the absolute numbers of Mesolithic dates are in general much lowerthan for the Neolithic may or may not give an indication of the relativeintensity of settlement in the two periods given the different types ofarcheological evidence which generally characterise them. However, evenif this is not the case, the fluctuations within each period within agiven broad region should be interpretable in this way, so long as thenumber of dated sites is not too small. Results Spatial analyses Clark's map of the changing distribution of early farmingsites is closely mirrored when the expanded database of Neolithic sitesis analysed (Figure 4). Sites are older close to the origin in the NearEast and they become increasingly younger with movement in a north-westdirection from this origin. Ammerman & Cavalli-Sforza's (1971,1984) major regression analysis of rates of spread from an assumedorigin at Jericho was repeated with the new database (using 510radiocarbon determinations) (Figure 5), yielding the major axisequation: [y.sub.date] = (-0.77 [+ or -] 0.03) [x.sub.distance] + (8240 [+ or-] 110). [FIGURES 4-5 OMITTED] This suggests that the overall rate of spread is ~1.3 km/year andthat the mean notional departure time from Jericho was ~8240 [+ or -]110 yrs BP (uncal.). In this case, linear regression Linear regressionA statistical technique for fitting a straight line to a set of data points. of the twovariables produces a correlation coefficient, r = 0.73. In other words Adv. 1. in other words - otherwise stated; "in other words, we are broke"put differently ,with the larger data set now available the mean rate of spread issimilar to that observed by Ammerman & Cavalli-Sforza, although thedispersion around that rate is somewhat greater. It is important to note that calibrating the radiocarbon valuesderived from in this major axis model would give us a mean originationtime in Jericho of about 10 400 cal BP for European Neolithicpopulations. If we approximate a confidence range for this date bytaking estimates from linear regression models for dates on distance andfor distance on dates (cf. Draper 1992), we derive a range for the meanNear Eastern origination time of 9200-12 400 cal BP. Such estimates fitquite well with observed dates for the end of the Natufian (c. 10 200BP, Belfer-Cohen 1991, which becomes c. 12 000 cal BP aftercalibration). This is interesting when we consider that current debateabout European genetic origins contrasts a possible major dispersal at11-14 000 cal BP (variously described as `Mesolithic' by Sykes,1999 and as `Late Upper Palaeolithic' by Richards et al., 2000),with one at 8500 cal BP (described as `Neolithic' by Sykes, 1999).In other words, one effect of calibration is that the mtDNA signaturesof these two events appear less well-resolved than some geneticistssuggest. Some of the mtDNA variation currently attributed to the lateglacial recolonization Re`col`o`ni`za´tionn. 1. A second or renewed colonization. of Europe may in fact derive from Neolithic demicdiffusion! The isochron maps compiled to show the distribution of the lastforaging and first farming sites in Europe (Figures 6 and 7) also shareparallels with Ammerman & Cavalli-Sforza's isochron maps. Thedelay in the expansion into the Alpine area shows up clearly in thenewly compiled isochron map of the early Neolithic (Figure 7). Theoverall expansion northwestwards from a near eastern origin ismaintained, although the isochrons are less regularly spaced suggestinga much greater variance in the rate of spread of early farmers into thedifferent areas of Europe. But we must recognize the methodologicallimitations of this technique. Interpolation error will be large inregions with sparse or no sites to use as control points, and theinterpolation has been continuous across sea as well as land (althoughthe sea has subsequently been masked off). This technique thereforerisks giving a misleadingly coherent impression of the spatial structureof any such dataset. In Figure 8 we have plotted results of a locally-weighted lineartrend analysis for the ages of early Neolithic sites, for each of aregular grid A regular grid is a tessellation of the Euclidean plane by congruent rectangles or a space-filling tessellation of rectilinear parallelepipeds. Grids of this type appear on graph paper and may be used in finite element analysis. of points. It is a convention that vector field In mathematics a vector field is a construction in vector calculus which associates a vector to every point in a (locally) Euclidean space.Vector fields are often used in physics to model, for example, the speed and direction of a moving fluid throughout space, or the diagramsshould plot values on a regular grid in this way. We have used projectedco-ordinates, and we have only used the earliest sites in each 60km-by-60 km cell of a sampling grid. The orientations of the arrows showthe direction in which sites get younger. The lengths of the arrowsscale to the rate of spread. The colours of the arrows indicate thestrength of the locally-weighted linear trend (where red is awell-fitting model, and blue is a poorly-fitting model). What thistechnique shows us is that we can only pick up significant regionaltrends in regions where our dataset is full, rather than sparse. Thistechnique therefore combines the best elements of the previous two (asused by Ammerman and Cavalli-Sforza), but avoids their weaknesses. Wecan observe local variation in rate and direction of diffusion, and itsstatistical strength. We do not need to assume any single origin, and wecan see the regions where the model fits well and the regions where itfits badly. [FIGURE 8 OMITTED] However, this too is an oversimplification o��ver��sim��pli��fy?v. o��ver��sim��pli��fied, o��ver��sim��pli��fy��ing, o��ver��sim��pli��fiesv.tr.To simplify to the point of causing misrepresentation, misconception, or error.v.intr. . When the whole of thecalibrated date distribution is used to show spread, rather than themodal value of the uncalibrated date, the pattern of spread is far lessobvious. The value in this approach is twofold: it emphasises theprobabilistic nature of radiocarbon dates, and it enables us to see theextent of co-occurrence of Mesolithic and Neolithic sites within aregion. Neither of these aspects of the chronology of the transition canbe easily visualised using regression techniques or spatialinterpolation methods. Regional analyses The results of this procedure for countries with a reasonablenumber of dates are shown in Figures 9 and 10. It should be noted thatthe probability distributions of the Mesolithic and Neolithic dates areseparately normalised to the same height and do not reflect thedifferent numbers of samples used. It is also important to emphasisethat the end cut off date of the Neolithic dates is relativelyarbitrary. Within any given region, dates were included that wereassociated with cultures regarded as characteristic of the local earlierNeolithic. Subdividing the dates by country is a very rough and readyway of obtaining a regionalisation Regionalisation refers to the tendency to form regions or the process of doing so. In geography, the process of delineating the Earth into regions. In globalization discourse, a world that becomes less interconnected, with a stronger regional focus. and summed date probabilities a verycoarse measure of occupation, but perhaps the most striking feature ofthe country-by-country patterns shown in Figures 9 and 10 is how veryvaried they are, and this variation has potential significance for therelevance of the models of `neolithisation' in the differentregions. [FIGURE 9-10 OMITTED] We shall look separately at regions which Zvelebil & Lillie(2000, cf Figure 1) characterise as experiencing significant demicdiffusion (Figure 9), and regions which they characterise asexperiencing predominantly trait adoption-diffusion (Figure 10).Overall, we have the impression from these probability plots that inregions of predicted demic diffusion the appearance of an earlyNeolithic population was relatively abrupt: that is, there is no long"fat negative tail" to these summed distributions. Secondly,in regions of predicted demic diffusion, Mesolithic dates tend either todisappear well ahead of the establishment of early Neolithic occupation,or to continue at a fairly constant rate well after it. By contrast, inareas of predicted trait adoption-diffusion we do see such long fatnegative tails to the early Neolithic distributions, implying a moregradual rate of increase in Neolithic settlement density. In suchregions, the Mesolithic radiocarbon record tends to tail off graduallywith significant overlap with that of the early Neolithic. We can nowmake some more specific, but still impressionistic im��pres��sion��is��tic?adj.1. Of, relating to, or practicing impressionism.2. Of, relating to, or predicated on impression as opposed to reason or fact: impressionistic memories of early childhood. suggestions aboutthese pooled radiocarbon records. Regions predicted to have experienced demic diffusion The pattern for Greece does not contradict the view that we aredealing with the expansion of new populations from Anatolia rather thanan indigenous Neolithic development. However, the number of Mesolithicdates is still small and it remains unclear how much the current stateof affairs reflects lack of work rather than lack of settlement. In the former Yugoslavia the Mesolithic dates come from a verysmall number of sites, dominated by Lepenski Vir Lepenski Vir is an important Mesolithic archaeological site located in Serbia in the central Balkan peninsula. It consists of one large settlement with around ten satellite villages. , indicating a need forcaution. Nonetheless, what emerges is a Neolithic represented by theStar evo culture which appears very suddenly at around 8000 cal. BP,most probably as a result of populations expanding from Greece, and aMesolithic which carries on in such locations as the Iron Gates gorgesor the mountains of Montenegro, overlapping and interacting with thenewly arrived Neolithic colonists. Italy has a rather firmer foundation and at first sight looks moreambivalent in terms of its possible implications for`neolithisation' processes since there is a later Mesolithicconcentration of dates immediately prior to and overlapping with theearliest Neolithic ones. However, an examination of the geographicallocation of the sites concerned reveals that all the late Mesolithicsites are in northern Italy Northern Italy comprises of two areas belonging to NUTS level 1: North-West (Nord-Ovest): Aosta Valley, Piedmont, Lombardy, Liguria North-East (Nord-Est): Friuli-Venezia Giulia, Veneto, Trentino-Alto Adige/S��dtirol, Emilia-Romagna while virtually all the earliest Neolithicdates come from the south, suggesting that in this region at least theearliest Neolithic is likely to represent colonisation. In Germany there is a marked decline Mesolithic occupation before8000 cal. BP and the body of the Neolithic distribution begins verysharply at around 7400 cal. BP, associated with the appearance of theLinearbandkeramik (LBK LBK Lubbock (Texas)LBK Linearbandkeramik (European Archaeological Culture)LBK Landing Barge, Kitchen (US Navy)LBK Lutherske BekjennelseskirkeLBK Location-Based Key ). This would seem to suggest a decline inMesolithic occupation after 8000 cal. BP and hardly fits in with thesuggestion that the German LBK represents an indigenous adoption ofNeolithic culture and economy. On the contrary, it seems to confirm theidea of the LBK as an expanding, colonising population moving into anarea which was relatively thinly occupied. However, the probablepresence of Mesolithic groups with distinctive La Hoguette La Hoguette is a commune of the Calvados d��partement in the Basse-Normandie r��gion in France. Its postal code is 14700. The INSEE code is 14332. Archeology pottery inthe west of the area should be noted (see e.g. Jochim 2000, Figure 7.5).The recent work of Price et al. (2001; see also Bentley et al. 2002),involving strontium strontium(strŏn`shēəm)[from Strontian, a Scottish town], a metallic chemical element; symbol Sr; at. no. 38; at. wt. 87.62; m.p. 769°C;; b.p. 1,384°C;; sp. gr. 2.6 at 20°C;; valence +2. isotope analysis Isotope analysis is the identification of isotopic signature, the distribution of certain stable isotopes and chemical elements within chemical compounds. This can be applied to a food web to make it possible to draw direct inferences regarding diet, trophic level, and subsistence. of LBK skeletons, suggests bothpopulation immigration immigration,entrance of a person (an alien) into a new country for the purpose of establishing permanent residence. Motives for immigration, like those for migration generally, are often economic, although religious or political factors may be very important. and some degree of mixing with neighbouringgroups, possibly foragers. In the case of Belgium a continuous low level of Mesolithicoccupation is suggested, continuing in parallel with the earlyNeolithic, but examination of the coordinates of these later Mesolithicsites indicates that they are located significantly further west thantheir early Neolithic contemporaries. The Neolithic begins quiteabruptly at 5400 cal. BC with the earliest Bandkeramik settlements. Regions predicted to have experienced trait adoption-diffusion The pattern for France once again shows a series of Mesolithicfluctuations but its most striking feature is the very gradual increasein the number of Neolithic dates through time. A low Mesolithic levelleading up to 7500 cal. BP gives way to a gradually rising intensity ofNeolithic occupation. Two-thirds of the very earliest Neolithic dates,ie., those where the beginning of the 1 [sigma] calibrated range goesback before 7000 cal. BP, are from the southern half of France andassociated with Cardial and related cultures, while the remaining thirdare northern French LBK-related dates. There would appear to be strongevidence here for the early indigenous adoption of Neolithic attributesby Mesolithic populations in France, at least in its southern half. Inthis respect the radiocarbon evidence supports the inferences made fromthe presence of sherds of west European La Hoguette pottery in early LBKsites (see again, Jochim 2000). The number of French dates issufficiently large In mathematics, the phrase sufficiently large is used in contexts such as: is true for sufficiently large to examine this geographical issue more closely, bydividing the French dates into a southern and a northern set at 47degrees latitude to see if there is any difference in the pattern on`neolithisation' between that in the south derived from theMediterranean Impressed Ware route and that in the north, where therewas strong LBK influence (Figure 10). Perhaps surprisingly, the patternseems to be the same in both northern and southern France, correspondingto the overall pattern noted above of gradually rising Neolithicoccupation, but with a 400 year delay in the northern half; in southernFrance the 95% confidence interval confidence interval,n a statistical device used to determine the range within which an acceptable datum would fall. Confidence intervals are usually expressed in percentages, typically 95% or 99%. for the Neolithic dates begins atc.7800 cal. BP, while in northern France it is c.7400 cal. BP. However,the northern French pattern does not suggest a sudden LBK impact, suchas we see elsewhere. The picture for Britain is more ambivalent in that there is adecline in the summed Mesolithic probabilities prior to the rise of theNeolithic but in the light of the other patterns, it seems at presentmore convincing to see it as pointing towards indigenous adoption ratherthan than colonisation. This seems even more likely to be the case forIreland, where the main Mesolithic peak is immediately prior to thebeginning of the Neolithic, followed apparently by a very suddentransition. However, as Woodman (2000) makes clear, the picture remainsvery unclear. Concluding remarks Discussion of the spread of agriculture in Europe has beenpolarised in recent years. Proponents of demic diffusion have becomeincreasingly embattled in the face both of archaeological arguments forregional variation in mechanism, and of genetic evidence favouring acombination of demic diffusion and adoption-diffusion in a populationwhich largely retained its local, late Palaeolithic genetic composition,although recently they have been fighting back. Our initial analysis ofthe new radiocarbon database confirms the robustness of the spatialpatterns described by Clark and by Ammerman & Cavalli-Sforza.However, the existence of a clear correlation between date of earliestoccurrence and distance from an assumed source is quite as compatiblewith a wave of advance of a cultural trait through a pre-existingpopulation, as it is with a wave of population replacement. Thegradients in gene frequencies plotted in synthetic gene maps can also beexplained by multiple mechanisms, of which demic expansion is only one. We conjecture that regional differences in the importance of demicand of adoption diffusion may reflect both underlying differences in therelative fertility and population density of local foraging and farminggroups, and underlying differences in the readiness of foragers toconvert to farming. As a first exploration of the demographic picture,we have plotted summed radiocarbon distributions by region, taking theseas very approximate measures of occupancy by foraging and farmingcommunities. We have proposed that in areas where demic diffusion ispredicted to have occurred, a more abrupt transition may be visible.However, the underlying causes of such abruptness (if it is indeed agenuine pattern) remain to be investigated. The environmental factorsdifferentiating regions of probable demic diffusion from those ofprobable adoption-diffusion also need to be examined in terms of theirimplications for forager and farmer demography. Our intention here is tostimulate further work on the large-scale patterns and processes, not toinhibit it by reinforcing that polarisation of debate which is tendingto cause stagnation StagnationA period of little or no growth in the economy. Economic growth of less than 2-3% is considered stagnation. Sometimes used to describe low trading volume or inactive trading in securities.Notes:A good example of stagnation was the U.S. economy in the 1970s. .Table 1. Structure of the radiocarbon database. The database isconstructed in Microsoft Access. The sources used includepublications, radiocarbon lab databases and other relevant data setsfrom universities or archaeological bodies. Full details are givenwith the database. Site co-ordinates in latitude and longitude wereobtained from the sources which provided the dates. British and Irishsites were reported in the relevant OS grids, and therefore had to beconverted to WGS84 in order to be incorporated in the database. Forthe calibration of the dates OxCal 3beta.2 was used, which providesthe 93 calibration curve.Table Name Table Fields CommentSample sample ID, date BP, error, Information not complete calibrated dates BC in some fields as lab earliest and latest 1 and 2 information rarely sigma, kind of lab (AMS or mentioned in publications conventional), treatment, or databases delta [sup.13]C correction, material, comments, date of process, source, lab code, submittersSite sample ID, site name, site The `site type' field could ID, area, country, cultural not be completed in many ID, site type, latitude, cases as the relevant longitude, comments, information was not period, references, available. Latitude and association longitude could not be obtained for about 250 sites. The `period' field states the temporal characterisation (in archaeological conventional terms) of the relevant site by the archaeologist in charge. The `references' field has information that was provided by the sources used. Gob (1990) provided comments on the quality of the association between sample and purported context for those dates he included and such information was obtained from other sources wherever possible.Site phase Sample ID, site phase, Only rarely could relevant absence or presence of information be added in pottery, domesticated the table, as the site animals and plants and reports are generally the human remains. only source for this kind of information.Context Sample ID, context, context Again site reports are type necessary for the type of context, as well as for the completion of the `site phase' and `context' fields. The `Site Phase' and `Context' tables should be used together as there is no consistency in the way the two terms have been used in the data sources Acknowledgements We wish to thank the UK Arts and Humanities Research Board forfunding the database collection element of this work, which was carriedout by Marina Gkiasta. 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Marina Gkiasta (1), Thembi Russell (2), Stephen Shennan (1[dagger]) and James Steele (2) (1) Institute of Archaeology The Institute of Archaeology is an academic department of University College London (UCL), in the United Kingdom. The Institute is located in a separate building at the north end of Gordon Square, Bloomsbury. , 31-34 Gordon Square, London WC1H OPY OPY Overall Process Yield ,England. (2) Department of Archaeology, University of Southampton In the most recent RAE assessment (2001), it has the only engineering faculty in the country to receive the highest rating (5*) across all disciplines.[3] According to The Times Higher Education Supplement ,Highfield, Southampton SO17 1BJ, England. ([dagger]) (s.shennan@ucl.ac.uk) Received 9 January 2003; Accepted 9 January 2003; Revised 9 January2003.