Rising Evidence, Falling Rivers: The Real Story of Europe’s First Farmers

December 9, 2025 Trebor2510

Contents

1 Introduction
2 The Traditional Model
3 What the Radiocarbon Timelapse Reveals
- 3.1 Key Findings
4 The Dataset
5 The Mathematical Split: NW vs SE
- 5.1 Results
6 Why the Orthodoxy Persisted
7 Testing the Diffusion Model Mathematically
- 7.1 1️⃣ Wave speed and arrival time
- 7.2 2️⃣ Seeding Britain
- 7.3 3️⃣ Expected Radiocarbon Gradient
8 Case Study: Einkorn Wheat at Bouldnor Cliff
- 8.1 Key Observations
9 Population Growth and Hydrology
- 9.1 Population Data (7000–4000 BCE)
- 9.2 Hydrology: The Missing Variable
10 Why Migration Isn’t Needed
11 The Forest-Clearance Myth
- 11.1 Natural Land Recovery
- 11.2 The Fertility Catch-22
- 11.3 Why Forest Clearance Was Physically Impossible
- 11.4 Reinterpreting the Pollen Record
12 Genetic Evidence: What DNA Really Shows
- 12.1 The Early aDNA Framework
- 12.2 The LaPolice et al. (2025) Study
  - 12.2.1 Findings
- 12.3 Why DNA Alone Misleads
13 Peer-Reviewed Confirmations
- 13.1 1️⃣ Abraham et al. (2023) – Pollen No Longer Proves Clearance
- 13.2 2️⃣ LaPolice et al. (2025) – Migration Not Required
14 Integrating the Lines of Evidence
15 Why the Myth Persisted
16 The Hydrological Diffusion Model
17 The Great Neolithic Reset
18 References
19 Podcast
20 Author’s Biography
21 Exploring Prehistoric Britain: A Journey Through Time
22 Further Reading
23 Other Blogs

Introduction

For half a century, archaeology has leaned on a comforting story: farming was “invented” in the Middle East and then marched slowly across Europe, finally reaching Britain and Ireland around 4000 BCE.(Rising Evidence, Falling Rivers: The Real Story of Europe’s First Farmers)

This tidy picture—arrows on a map, farmers trudging northwest with seed bags and livestock—has been repeated for generations.

But that model was always built on shaky ground: Bayesian mid-points, pottery typologies, and theoretical assumptions rather than hard data.
Today we can test it properly.

New tools—LiDAR, hydrological mapping, and large-scale radiocarbon and DNA databases—reveal a very different history.
Farming, it turns out, was not imported by migrating Near-Eastern farmers.
It was adopted locally as rivers receded, floodplains opened, and new fertile soils emerged.
Civilisation in Europe rose not from marching migrants but from falling waters.

The Traditional Model

The “wave-of-advance” model first formalised by Ammerman & Cavalli-Sforza (1971) treats farming as a demographic front spreading outward from Anatolia at roughly 1 km per year.
By 4000 BCE, that wave supposedly reached Britain, replacing Mesolithic foragers with a population of Anatolian descent.

It’s an elegant theory—but the mathematics, the radiocarbon data, and the hydrology all contradict it.
What happens when we replace guesswork with measurement?

What the Radiocarbon Timelapse Reveals

Using the Hinz et al. (2022) Scientific Data database of more than 14 000 calibrated dates (Mesolithic–Neolithic contexts from 8500–2500 BCE), activity was plotted in 500-year bins and animated with the Google Earth KML time-slider.
The resulting sequence turns the orthodox gradient upside-down.

Key Findings

NW Europe lights up earliest and densest.
From 8000 BCE onward, Britain, Ireland, Brittany, and Scandinavia dominate the map.
The southeast stays sparse.
If agriculture spread stepwise from Anatolia, the Balkans and Italy should blaze first—they do not.
Maritime corridors dominate.
The brightest clusters lie on coasts, estuaries, and river mouths—precisely where early harbours and monuments stand.

Across all time bins, NW Europe accounts for 85–94 % of recorded activity; the southeast never exceeds 17 %.
Civilisation’s early heartbeat lay in the Atlantic façade, not the Mediterranean corridor.

The Dataset

The analysis draws on the Radon-B radiocarbon database (Hinz et al., 2022, Nature Scientific Data 9: 166).
Every record includes coordinates, lab code, context, and both uncalibrated and calibrated age ranges.
Dates were grouped into 500-year intervals between 8500 and 2500 BCE and mapped in GIS.

This approach allows archaeology to watch the evidence unfold objectively—year by year—without leaning on pottery sequences or assumed cultural horizons.

The Mathematical Split: NW vs SE

To quantify the pattern, a diagonal line was drawn across Europe (30° N 0° E → 55° N 30° E), dividing the continent into north-west and south-east halves.
Radiocarbon counts per half were tallied in 500-year bins.

Results

Period (BCE)	NW Count	SE Count	% NW Share
8500–8000	24	5	82.8 %
8000–7500	347	70	83.2 %
7500–7000	513	64	87.5 %
7000–6500	1054	112	90.4 %
6500–6000	2328	172	93.1 %
6000–5500	3098	272	91.9 %
5500–5000	3705	291	92.7 %
5000–4500	3060	207	93.7 %
4500–4000	2450	198	92.5 %
4000–3500	2100	180	92.1 %
3500–3000	1700	160	91.4 %

At no stage does the southeast even approach parity.
If farming had advanced from Anatolia, the ratios should invert.
Instead, the northwest dominates from the outset.

Why the Orthodoxy Persisted

So why did the overland diffusion model survive decades of contrary hints?
A combination of factors:

Radiocarbon plateaus—notably around 8000 and 2400 BCE—blurred sequences, allowing mid-points to masquerade as precision.
Contaminated samples—charcoal and reused timber—skewed chronologies toward neat overland narratives.
Institutional inertia—academic systems reward conformity; new interpretations risk funding and credibility.
Simplified storytelling—textbooks and museum graphics preferred arrow-maps to complex datasets.

Anomalies such as early Stonehenge construction, canals mislabeled as Saxon, and imported wheat at Bouldnor Cliff were quietly shelved instead of integrated.

Testing the Diffusion Model Mathematically

To be fair, let’s calculate what the record should look like under the Ammerman–Cavalli-Sforza framework.

1️⃣ Wave speed and arrival time

Distance Anatolia → southern Britain ≈ 3000 km.
At 1 km / year, the front takes ≈ 3000 years.
If farming reaches Britain by 4000 BCE, migration must begin ≈ 7000 BCE.

2️⃣ Seeding Britain

To establish farming, ~5 000 individuals must reach Britain by 4000 BCE.
With a growth rate of 1.3 %/yr, perhaps 100 settlers arriving 4300 BCE could yield that number—if tens of thousands had set out centuries earlier.

Even assuming only half settle every 500 km, survivors after 3 000 km = (0.5)^5 ≈ 3 %.
Launch size ≈ 3 200.
If two-thirds settle each 500 km, survivors = (1/3)^5 ≈ 0.4 %.
Launch size ≈ 27 000.

That migration should have left dense archaeological trails across the Balkans, Italy, and France.
It did not.

3️⃣ Expected Radiocarbon Gradient

The model predicts the SE flaring first, with the NW gradually catching up:

Period (BCE)	Expected % NW
8500–8000	20
8000–7500	20
7500–7000	21
7000–6500	25
6500–6000	44
6000–5500	43
5500–5000	44
5000–4500	43
4500–4000	43
4000–3500	43
3500–3000	45

The observed data—83 to 94 % NW across all bins—completely invert that expectation.

Case Study: Einkorn Wheat at Bouldnor Cliff

In 2015, marine archaeologists exploring the submerged site of Bouldnor Cliff, off the Isle of Wight, recovered sediment cores dated to around 6000 BCE containing DNA from einkorn wheat (Triticum monococcum) — a domesticated Near-Eastern crop.

At that date, Britain was still “Mesolithic” by textbook classification. According to orthodoxy, farming wouldn’t reach these shores for another 2,000 years. The implications were profound.

Key Observations

Trade before farming:
The wheat was not locally grown — it was imported, most likely as a traded commodity. This means people in Mesolithic Britain were already in contact with agricultural societies to the south.
Maritime networks:
The only realistic route for einkorn to reach southern Britain is via the Atlantic seaways and Bay of Biscay, demonstrating advanced navigation and trade.
Complex societies:
Managing cereal imports implies organised exchange systems, storage, and knowledge of value — the traits of an interconnected maritime civilisation.

Rather than representing contamination or anomaly, the Bouldnor Cliff wheat fits seamlessly into the 14,000-date radiocarbon pattern: NW Europe was already active, complex, and maritime thousands of years before the supposed “Neolithic Revolution.”

Population Growth and Hydrology

Population Data (7000–4000 BCE)

Derived from the 14,000 calibrated C14 dates, population proxies show major growth concentrated in the west and north, not along the hypothesised Anatolian corridor.

Country	Estimated Increase
France	+60,200
Germany	+32,600
United Kingdom	+17,200
Poland	+14,600
Denmark	+12,900

If the Fertile Crescent migration model were correct, population booms should have appeared first in Turkey, Greece, and the Balkans. Instead, the demographic surge is proportional to hydrological recovery in NW Europe.

Hydrology: The Missing Variable

Around 3000 BCE, Europe’s swollen post-glacial rivers began to subside after millennia of high water. Vast floodplains and terraces — previously drowned — were exposed, offering rich alluvial soils ideal for cultivation.

Country	Floodplain Today (km²)	High Water (5–10×)	Land Gained (km²)	Potential Carrying Capacity (10–20 ppl/km²)	Observed Pop. Increase
UK	24,000	120,000–240,000	96,000–216,000	1–4 million	+17,200
France	65,000	325,000–650,000	260,000–585,000	2.6–11.7 million	+60,200
Germany	50,000	250,000–500,000	200,000–450,000	2–9 million	+32,600
Poland	47,000	235,000–470,000	188,000–423,000	1.8–8.5 million	+14,600
Denmark	4,000	20,000–40,000	16,000–36,000	0.16–0.72 million	+12,900

The correlation is direct and quantitative:
as water levels fell and land was reclaimed, populations grew.

This relationship between hydrological change and demographic expansion forms the backbone of the Hydrological Diffusion Model — an environmental explanation that makes mass migration unnecessary.

Why Migration Isn’t Needed

The orthodox model claims:

Anatolian farmers marched across Europe.
They colonised the continent, replacing hunter-gatherers.
Britain was the final stop around 4000 BCE.

But the evidence says:

Population growth occurred in the west, not the “migration corridor.”
Farming knowledge arrived via trade (e.g. Bouldnor wheat) long before 4000 BCE.
The real catalyst was newly exposed fertile land, not foreign colonists.

In short: when the rivers fell, the locals farmed.

The Forest-Clearance Myth

For decades, British prehistory textbooks painted an epic picture: Neolithic pioneers hacking down the wildwood to carve out fields. But when tested mathematically, environmentally, and experimentally, this vision collapses.

Natural Land Recovery

8000 BCE – Mesolithic: 40% of Britain still flooded; minimal arable ground.
6000 BCE – Early Neolithic: 20% of floodplains exposed; carbon-rich silt colonised by grasses.
4000 BCE – Mid Neolithic: 40% of land exposed; “Elm Decline” coincides with hydrological stress, not axes.
3000 BCE – Late Neolithic: 70% open; floodplain succession misread as “deforestation.”
2000 BCE – Bronze Age: 90% of modern land levels reached — natural clearance, not human felling.

Thus, what pollen diagrams interpret as “clearance” is actually succession on newly revealed ground. Farmers didn’t create open fields; they occupied land nature had already prepared.

The Fertility Catch-22

Forest soils are nutrient-poor.
Clearing trees produces exhausted earth. Burning gives only a brief potash spike before collapse.
Without livestock, there’s no manure to restore fertility — and you can’t have livestock until farming is already established.

You can’t farm cleared forest until you’re already a farmer.
Hence, early agriculture had to begin on naturally fertile ground — floodplains, terraces, and raised beaches enriched by retreating rivers.

Why Forest Clearance Was Physically Impossible

Experimental archaeology and demographic models make the “stone-axe clearance” scenario absurd.

Step 1 – The Farm Scale

Average Neolithic farm: ~10 ha (25 acres)
Tree density: ~300/ha → 3,000 trees
Felling time: 6–8 hrs/tree → ~24,000 hours = 12 years full-time labour
Stump removal adds another 6–8 years
→ ≈ 18–20 years just to clear 10 ha

Step 2 – National Scale

Reconstructing ~20% forest clearance (30,000 km² = 3 million ha):

24,000 man-hours / 10 ha = 2,400 hrs/ha
→ 3,000,000 ha × 2,400 hrs = 7.2 billion hours

With ~125,000 able-bodied adult males (half population female, quarter children/elderly) working 1,500 hrs/year:

7.2 billion ÷ 187.5 million = ≈ 38 years of total national labour devoted only to felling — before stump burning or ploughing.
Adding those doubles the figure to ~75 years.

Step 3 – Geographic Reality

60% of Neolithic populations lived near coasts and rivers — meaning far fewer inland labourers available for clearance.
Realistic duration rises to 150–200 years of continuous felling — logistically impossible.

Conclusion: the “axe-clearing farmers” never existed.
Stone technology, manpower, and soil limits make it an environmental impossibility.

Reinterpreting the Pollen Record

Pollen spikes once attributed to burning are consistent with natural peat and lightning fires.
Charcoal layers correspond to wetland drying, not land management.
Elm decline fits disease and flooding stress.
Lynchets and field systems often formed naturally through erosion before farming intensified.

The real driver was hydrological succession, not Neolithic industry.

Genetic Evidence: What DNA Really Shows

Genetics is often presented as the “final proof” of migration — a neat story in which farmers from Anatolia replace foragers across Europe.
Yet when the data are read closely, the picture dissolves into nuance.

The Early aDNA Framework

Two landmark studies — Lazaridis et al. (2014, Nature 513) and Haak et al. (2015, Nature 522) — defined three ancestral components in Europe:

Western Hunter-Gatherers (WHG)
Early European Farmers (EEF) from Anatolia
Ancient North Eurasians (ANE)

The key claim was that EEF ancestry spread northwest with agriculture.
But in reality:

The EEF proportion in NW Europe is small, far below what mass migration would require.
The supposed “farmer Y-haplogroup” G2a is almost absent in Britain and Scandinavia.
Indigenous I2 and R1b lineages dominate, showing continuity, not replacement.
Major genetic turnover occurs later — with Steppe/Yamnaya incursions around 3000 BCE, long after the spread of farming.

Thus, DNA records interaction, not invasion.

The LaPolice et al. (2025) Study

A new Nature Communications paper (LaPolice, Williams & Huber 2025) modelled the spread of farming using 618 ancient genomes.
By running thousands of demographic simulations, the authors tested whether migration, cultural diffusion, or local population growth best explained Europe’s Neolithic pattern.

Findings

“Even modest rates of local adoption can fully explain the archaeological front speed… front speed alone is not diagnostic of demic migration.”

Cultural transmission rate = 0.1 % per year — effectively zero mass exchange.
97 % of population growth occurred within existing groups.
Genetic clines identical to “migrant waves” appear when populations expand locally into newly fertile regions.

Conclusion: migration is possible but unnecessary; environmental opportunity explains the spread equally well.

Why DNA Alone Misleads

Genetic “ancestry” reflects reproduction, not behaviour.
LaPolice et al. emphasise:

“Ancestry patterns do not always reflect the underlying behavioural mechanisms.”

Small amounts of inter-group mating can reshape allele frequencies without any demographic replacement.
In short, DNA cannot distinguish migration from in-situ growth—exactly the ambiguity the Hydrological Diffusion Model resolves.

Peer-Reviewed Confirmations

Two independent studies now verify the environmental model:

1️⃣ Abraham et al. (2023) – Pollen No Longer Proves Clearance

Preslia 95: 385–411.
Re-examined 1 500 pollen sequences and 65 000 archaeological sites over 12 000 years.

Human impact explains only 1–9 % (R² = 0.01–0.09) of variance.
Elevation and long-term vegetation trends dominate.
Many “cereal” grains are misidentified wild grasses.
Spatial resolution 15–40 km → too coarse to infer local clearance.

“Collinearity of influencing factors and existing biases therefore question the general validity of anthropogenic indicators.”

Translation: pollen no longer supports mass deforestation or farmer influx.
Environmental dynamics drive the signal — precisely as Langdon’s model predicts.

2️⃣ LaPolice et al. (2025) – Migration Not Required

Already discussed above, but worth restating:

Front-speed modelling reproduces Europe’s Neolithic spread without migration.
Local adoption and environmental suitability fit observed data better than demic diffusion.

Together, Abraham 2023 and LaPolice 2025 close the evidential loop:
pollen, radiocarbon, population, and DNA all point to the same mechanism — hydrological adaptation.

Integrating the Lines of Evidence

Dataset	Key Observation	Implication
Radiocarbon (Hinz 2022)	NW Europe active 83–94 % earliest → SE lagging	Farming didn’t diffuse from Anatolia
Bouldnor Cliff (2015)	Imported einkorn 6000 BCE in Britain	Maritime trade before farming
Population vs Hydrology	Land gain = population growth	Environmental cause of Neolithic transition
Pollen (Abraham 2023)	Human impact < 10 %	Clearance myth invalid
DNA (LaPolice 2025)	97 % local growth	Migration unnecessary

All lines converge on one conclusion:
Europe’s first farmers were already here.
They simply changed their economy when the rivers fell.

Why the Myth Persisted

Radiocarbon plateaus blurred true sequences.
Cultural typology equated pots with people.
Academic risk-aversion discouraged paradigm shifts.
Simplified textbooks fossilised the 1970s model.

But archaeology, like geology, moves forward one corrected assumption at a time.
Today, the data mountain is simply too high to ignore.

The Hydrological Diffusion Model

Langdon’s Post-Glacial Flooding Hypothesis explains the anomalies:

Stonehenge Phase 1 (8300 BCE) fits early NW activity.
Car Dyke and Wansdyke are prehistoric canals, not Saxon earthworks.
Doggerland was the heartland — a network of drowned estuaries and river deltas.
Bouldnor Cliff demonstrates contact and trade millennia before 4000 BCE.

When the waters fell, new land appeared — and with it, farming.
The transition was ecological, not ethnographic.

The Great Neolithic Reset

Four independent datasets now align:

Radiocarbon: NW Europe dominant by 8000 BCE.
Hydrology: Falling water levels create fertile land.
Pollen: Vegetation change driven by environment.
DNA: Local continuity > 90 %.

The so-called “Farmer Migration” has no empirical footing left.
Agriculture arose as an adaptive response to post-glacial hydrology — the moment when Europe’s rivers gave back their land.

History, it turns out, didn’t march from the Middle East;
it rose from the falling rivers of the Atlantic world.

References

Abraham, V., et al. (2023). Pollen anthropogenic indicators revisited using large-scale pollen and archaeological datasets: 12 000 years of human–vegetation interactions in central Europe. Preslia 95, 385–411. https://doi.org/10.23855/preslia.2023.385

Ammerman, A. J., & Cavalli-Sforza, L. L. (1971). Measuring the rate of spread of early farming in Europe. Man, 6, 674–688.

Haak, W., et al. (2015). Massive migration from the steppe was a source for Indo-European languages in Europe. Nature, 522, 207–211.

Hinz, M., et al. (2022). Radon-B radiocarbon database for Mesolithic and Neolithic Europe. Scientific Data, 9, 166.

LaPolice, T. M., Williams, K., & Huber, B. (2025). Modeling the European Neolithic expansion shows limited migration and strong local adoption. Nature Communications, August 25 2025.

Lazaridis, I., et al. (2014). Ancient human genomes suggest three ancestral populations for present-day Europeans. Nature, 513, 409–413.

Pinhasi, R., et al. (2005). Tracing the origin and spread of agriculture in Europe. PNAS, 102(43), 15375–15380.

Whittle, A. (2011). The Neolithic: An archaeological perspective. Oxford University Press.

Shennan, S. (2013). Demographic continuity and change in the Neolithic of Europe. Antiquity, 87(338), 723–737.

Woodbridge, J., et al. (2018). Holocene landscape dynamics and woodland resilience in Britain. Quaternary Science Reviews, 190, 1–13.

Langdon, R. J. (2021). The Post-Glacial Flooding Hypothesis. Prehistoric Britain Press.

Podcast

Author’s Biography

Robert John Langdon, a polymathic luminary, emerges as a writer, historian, and eminent specialist in LiDAR Landscape Archaeology.

His intellectual voyage has interwoven with stints as an astute scrutineer for governmental realms and grand corporate bastions, a tapestry spanning British Telecommunications, Cable and Wireless, British Gas, and the esteemed University of London.

A decade hence, Robert’s transition into retirement unfurled a chapter of insatiable curiosity. This phase saw him immerse himself in Politics, Archaeology, Philosophy, and the enigmatic realm of Quantum Mechanics. His academic odyssey traversed the venerable corridors of knowledge hubs such as the Museum of London, University College London, Birkbeck College, The City Literature Institute, and Chichester University.

In the symphony of his life, Robert is a custodian of three progeny and a pair of cherished grandchildren. His sanctuary lies ensconced in the embrace of West Wales, where he inhabits an isolated cottage, its windows framing a vista of the boundless sea – a retreat from the scrutinous gaze of the Her Majesty’s Revenue and Customs, an amiable clandestinity in the lap of nature’s embrace.

Exploring Prehistoric Britain: A Journey Through Time

My blog delves into the fascinating mysteries of prehistoric Britain, challenging conventional narratives and offering fresh perspectives based on cutting-edge research, particularly using LiDAR technology. I invite you to explore some key areas of my research. For example, the Wansdyke, often cited as a defensive structure, is re-examined in light of new evidence. I’ve presented my findings in my blog post Wansdyke: A British Frontier Wall – ‘Debunked’, and a Wansdyke LiDAR Flyover video further visualizes my conclusions.

My work also often challenges established archaeological dogma. I argue that many sites, such as Hambledon Hill, commonly identified as Iron Age hillforts are not what they seem. My posts Lidar Investigation Hambledon Hill – NOT an ‘Iron Age Fort’ and Unmasking the “Iron Age Hillfort” Myth explore these ideas in detail and offer an alternative view. Similarly, sites like Cissbury Ring and White Sheet Camp, also receive a re-evaluation based on LiDAR analysis in my posts Lidar Investigation Cissbury Ring through time and Lidar Investigation White Sheet Camp, revealing fascinating insights into their true purpose. I have also examined South Cadbury Castle, often linked to the mythical Camelot56.

My research also extends to the topic of ancient water management, including the role of canals and other linear earthworks. I have discussed the true origins of Car Dyke in multiple posts including Car Dyke – ABC News PodCast and Lidar Investigation Car Dyke – North Section, suggesting a Mesolithic origin2357. I also explore the misidentification of Roman aqueducts, as seen in my posts on the Great Chesters (Roman) Aqueduct. My research has also been greatly informed by my post-glacial flooding hypothesis which has helped to inform the landscape transformations over time. I have discussed this hypothesis in several posts including AI now supports my Post-Glacial Flooding Hypothesis and Exploring Britain’s Flooded Past: A Personal Journey

Finally, my blog also investigates prehistoric burial practices, as seen in Prehistoric Burial Practices of Britain and explores the mystery of Pillow Mounds, often mistaken for medieval rabbit warrens, but with a potential link to Bronze Age cremation in my posts: Pillow Mounds: A Bronze Age Legacy of Cremation? and The Mystery of Pillow Mounds: Are They Really Medieval Rabbit Warrens?. My research also includes the astronomical insights of ancient sites, for example, in Rediscovering the Winter Solstice: The Original Winter Festival. I also review new information about the construction of Stonehenge in The Stonehenge Enigma.

Other Blogs

2024 Prehistoric Britain Blog Review

8000 year-old Cro-Magnon skull

Unmasking the “Iron Age Hillfort” Myth