Counting Microliths: A Reliable Method to Assess Mesolithic Land Use? in This Debate the Authors Tackle a Problem Fundamental to Researchers and Resource Managers in the Mesolithic Period: What Sort of Prehistory Do Flint Scatters Represent?
Crombe, Philippe, Sergant, Joris, Robinson, Erick, Antiquity
Surface scatter assemblages form the majority of the Mesolithic archaeological record in many regions throughout Europe. A central challenge for research is the use of these scatters in the determination of how land was used. Land use models require data with a high enough resolution to map the variability of social organisation through time over specific ecological zones. Can low resolution surface data on their own give this result?
In a recent paper Vanmontfort (2008) proposed a new method for modelling Mesolithic land use for regions where almost the entire archaeological record is comprised of surface assemblages. Vanmontfort counts individual microlith types (2008:152) in order to model the diachronic variability of Mesolithic land use between different regions. His method claims to reveal the 'behavioural changes' that lead to regional variability in 'exploitation intensity' throughout the 4000-year period of the Mesolithic. The model supports his conclusion that on their eventual arrival in the middle Belgian loess belt, Linearbandkeramik (LBK) farmers exuded 'conflict-avoiding attitudes' by settling in areas that were either uninhabited, or marginally inhabited, by Late Mesolithic foraging societies. Interestingly, this model directly contradicts the one recently published in this journal by Golitko and Keeley (2007), in which the Neolithisation of north-west Europe was interpreted as one of the most violent periods in prehistory.
Our critique addresses three specific assumptions:
1. Available datasets are random samples of each study region
2. Individual microlith types fit within uniform chronological sequences throughout the entire Rhein-Meuse-Scheldt cultural distribution
3. Microlith counts correspond with site-based and technological assessments of interregional land use variability.
Vanmontfort (2008: 150) considers differences in research and survey activity, taphonomy and sample size as 'complicating factors to keep in mind' because they 'play the same role for all periods or phases in a given region'. He claims that the method is immune to biasing factors because it takes a broader inter-regional scale of analysis (Vanmontfort 2008: 156).
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This could not be further from the truth, particularly in the three regions of the loess belt where the LBK first settled (i.e. Hainaut, Hesbaye and the Kleine Gete) (Figure 1). Differences in research activity and methodologies can cause major biases both within and between different regions. One of the authors (PC) carried out intensive research in the north-western part of Hainaut in the late 1980s and noticed that amateur fieldwalkers focused mainly on sandy outcrops of hilltops and plateaux in the loess region, and largely ignored river valleys (Crombe 1989). While no valley sites are currently known from Hainaut, they surely existed and are awaiting future research. For example, in the Hageland region, which is environmentally most similar to Hainaut, Vanmontfort (2008: Table 4) reports 60 per cent of all collected microliths as coming from river valleys. In central Hainaut, fieldwalkers have focused on sandy soils, which have yielded a high density of sites. However, excluding the 25[km.sup.2] survey of the LBK cluster, the loamy areas of Hainaut have received much less attention thus far (Van Assche 2005: 47-8). Taphonomic factors must be considered seriously, especially in regions with hilly topography (e.g. Hainaut). Hillwash erosion may have sealed valley and slope sites. It is very likely that in the hilly landscape of the middle Scheldt Basin many sites are buried beneath colluvial deposits, like the site of Rebecq-Le Spinoi mentioned by Vanmontfort (2008:150). In fact, the diachronic exploitation trend reconstructed by Vanmontfort for the Hainaut region (Vanmontfort 2008: Figure 3), and its subsequent deviation from all other studied regions, proves the significant hindrance of these methodological issues for a comparative regional analysis. …