More on WARP Data (Part One)

As readers of this blog know, my colleagues and I on the Western Argolid Regional Project have been working our way through the data that the project produced over its three main field seasons. This (virtual) study season focused on producing some reports that would start to describe the survey area in general ways. These reports will help us in the future as we attempt to unpack the character of more specific artifact scatters and distribution patterns. They’ll also contribute to address some “big picture” questions in survey methods and methodologies. I’ve already blogged a bit on my work over the last few weeks (here, here, and here). This week’s installment will likely be my last and the most general.

Six things that I learned this WARP study season.

1. Densities and Visibility. Like most intensive surveys we counted the total number of sherds and tile fragments in each survey unit. These numbers alone don’t tell us much about the past, but they do provide insights into artifact recovery rates across the entire survey area. For example, we know that surface visibility and the quantity of artifacts in the plow zone are likely independent variables. The question then becomes whether the areas with higher artifact densities represent the quantity of material in the plow zone or simply zones where we have higher visibility (or geomorphological processes took place that revealed past surfaces). As I blogged about a few weeks ago, for our survey area lower visibility tended to mean lower densities in a fairly consistent way. This indicates that across the entire survey zone lower visibility areas are as likely to have significant quantities of artifacts as higher visibility areas (and vice versa). In other words, it suggests that the two variables are independent. We might see a different trend if the two variables were related. For example, if ancient settlements tended to appear more frequently in fields that were currently abandoned and overgrown, we might see unusual spikes in artifact densities at lower surface visibilities and lower densities – either proportionately or in absolute terms – with greater visibility.  

Another measure for this considers the variability of artifact densities at different levels of visibilities. A number of scholars have noted that as visibilities decrease our ability to consistently recover artifacts becomes more random. This may be the case in some environments, but at WARP, the variability present across visibilities (measured by the standard deviation divided by the mean) does not pattern consistently and if anything appears to slightly increase as visibility increases. 

VarVis

Background disturbance is another factor that archaeologists have recognized as impacting artifact recovery rates (as I’ve blogged about before). Background disturbance describes the amount of distracting material on the surface that complicates artifact recovery. In general, we did not notice background disturbance having a significant impact on artifact recovery rates at WARP in general. That said, when consider variability in artifact densities per visibility split out by background disturbance (which we recorded as light, moderate, and heavy) we can see that variability decreases with higher densities, but the pattern is not a particular strong one. It is telling, however, that variability increases with visibility in units with moderate and light artifact densities.

VarBGD

While the patterns here are not particularly compelling, I think they do hint at how background disturbances shape recovery rates even if the story they tell is not a dramatic one.

2. Hidden Landscapes. Survey archaeologist have long worried about hidden landscapes, a phrase coined by John Bintliff, Phil Howard and Anthony Snodgrass in an influential late 1999s article. While this article introduces a whole range of reasons for landscapes being hidden – from geomorphology to the fragility of ceramics fired at lower temperatures at certain periods – in crunching the WARP data, I concerned myself with just one or two factors. The main factor that I fretted about was the possibility that contemporary land use which shapes not only recovery rates (through factors like surface visibility and plowing; units that remain under cultivation, for example, tend to have better surface visibility and to receive the kind of attention that increases the amount of subsurface contexts visible to field walkers), but as importantly shaped access to fields. Overgrown fields, steep slopes or units inaccessible via field road, walking paths, or undergraduate clambering may well hide landscapes that survey projects could systematically overlook. At this point in our project, there is no chance of us going back to field to survey steep slopes or dense thickets of maquis, but we can look at the data to see if there are hints that certain periods were more common in certain kinds of fields or, better still, whether they appeared somehow out of sync with predominant densities across the survey area. Again, overall artifact densities do not necessarily suggest certain units saw more activity throughout the past than others, but suggest the happy confluence of field conditions and surface material.

To do this analysis, I ranked the units in our survey area by artifact density according to equal intervals. The lowest density unit was 1 and the highest was 5. I think looked at any period of under 1100 years (and these constitute “narrow” periods from WARP) and ordered them according to average density rank. The idea was to determine whether certain periods appeared consistently in fields where artifact recovery rates produced low densities. I recognize that this is not the only method to suss out whether certain periods were more hidden than others, but it offered at least a preliminary way to consider the problem at scale across our survey area.

For Bintliff and co. there was a thought that certain prehistoric periods might be hidden in their landscapes in Boeotia. On WARP, however, it appears that prehistoric periods – even rather narrow ones such as Late Helladic IIIA-B – tend to appear most consistently in units with the highest artifact densities suggesting the confluence of recovery rates and material in the plow zone revealed a significant assemblage of pre-historic material. Of course, this can’t tell us what we didn’t find, but it is suggestive when compared to material from the Medieval period, the Venetian/Ottoman period, and the Early Modern period. This material tended to appear in units with lower average densities and lower average visibilities suggesting that contemporary land use, access, and surface visibility might be working to obscure the Late Medieval and post-Medieval landscape in the survey area. The densely overgrown Medieval site near the village of Sterna which produced Late Medieval through Venetian material despite may be a useful example of an area where our survey might not consistently explore. The site stood above the highest cultivated fields in the Inachos valley and was densely overgrown in vines, trees, and weeds. Artifact densities was spotty owing to the difficult surface visibility and it seems probable that artifact densities if not otherwise compromised would have been significant. That said, the site near Sterna did produce some standing architecture, a series of (you guessed it!) cisterns, and stood at a strategic location where the Inachos river valley narrowed before opening out into the wider Lyrkeia valley. In other words, there are certain characteristics of the site that encouraged us to explore it in greater detail despite the limited visibility and challenging landscape. To my mind, this mitigates to some extent against the idea that the absence of certain landforms and situations have led to the underrepresentation of Late Medieval to Early Modern material, but this hypothesis will, of course, require greater testing.

Stay tuned for more tomorrow!

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