The Alluvial Geoarchaeology of the Upper River Kennet in the Avebury Landscape: a Monumental Transformation of a Stable Landscape
Bibliographic record
Abstract
Geoarchaeological research as part of the AHRC funded Living with Monuments (LwM) project investigated the upper Kennet river system across the Avebury World Heritage landscape. The results demonstrate that in the early–mid-Holocene ( c. 9500–1000 bc ) there was very low erosion of disturbed soils into the floodplain, with floodplain deposits confined to a naturally forming bedload fluvial deposit aggrading in a shallow channel of inter-linked deeper pools. At the time of the Neolithic monument building in the 4th–early 3rd millennium bc , the river was wide and shallow with areas of presumed braid plain. Between c. 4000 and 1000 bc , a human induced signature of soil erosion became a minor component of fluvial sedimentation in the Kennet palaeo-channel but it was small scale and localised. This strongly suggests that there is little evidence of widespread woodland removal associated with Neolithic farming and monument building, despite the evidently large timber requirements for Neolithic sites like the West Kennet palisade enclosures. Consequently, there was relatively light human disturbance of the hinterland and valley slopes over the longue durée until the later Bronze Age/Early Iron Age, with a predominance of pasture over arable land. Rather than large Neolithic monument complexes being constructed within woodland clearings, representing ancestral and sacred spaces, the substantially much more open landscape provided a suitable landscape with areas of sarsen spreads potentially easily visible. During the period c. 3000–1000 bc , the sediment load within the channel slowly increased with alluvial deposition of increasingly humic silty clays across the valley floor. However, this only represents small-scale landscape disturbance. It is from the Late Bronze Age–Early Iron Age when the anthropogenic signal of human driven alluviation becomes dominant and overtakes the bedload fluvial signal across the floodplain, with localised colluvial deposits on the floodplain margins. Subsequently, the alluvial archive describes more extensive human impact across this landscape, including the disturbance of loessic-rich soils in the catchment. The deposition of floodplain wide alluvium continues throughout the Roman, medieval, and post-medieval periods, correlating with the development of a low-flow, single channel, with alluvial sediments describing a decreasing energy in the depositional environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".