FamilyTreeDNA Globetrekker Program and Landscape Archaeology

In previous stories, I have relied upon the use of specific online programs or tools that map genetic genealogy with geography. Specifically, one of those heuristic tools I have utilized is the Globetrekker^TM program that was created by FamilyTreeDNA to map the estmated migratory path of my YDNA ancestors to my most recent (as of the date of this story) ancestral haplogroup G-Y132505 – recognized by various genetic genealogical organziations. ( see video below).

Just to ensure we are speaking with understood terms, a haplogroup is a genetic grouping of people who share a common ancestor, identified by specific DNA markers (mutations) in the non-recombining parts of our DNA. In this context the YDNA for paternal lineage, tracing ancestral migration and origins. These markers act like unique signatures, showing branches on the human family tree and revealing deep ancestral paths across time and continents. [1]

Illustration One: Globetrekker Video of the Migratory Path for YDNA ancestors of the Most Recent Common Ancestor of Haplogroup G-Y132505

Source:The migration route to of YDNA haplogroups to most recent ancester of haplogroup G-Y132505, Globetrekker, FamilyTreeDNA, Accessed 16 Jan 2026

To provide historical context and complimentary information to the Globetrekker animated YDNA migratory path in illustration one, I have also utilized the results of archaeological research by a group of archaeologists that employ a mutlidisciplinary approach to identify and explain the persistence of travel corridors in one portion of this migratory path: the Late Roman era and the ‘dark ages’ of the early medieval era.

The Globetrekker program provides a specific outline of my patrilineal migration path, while landscape archaeological studies document historically persistent places, and movement corridors that supply the fine‑grained, time‑specific spatial frameworks needed to interpret those migratory paths in real historical landscapes. Used together, they let you move from an abstract geographical Y‑DNA trajectory to concrete hypotheses about which river valleys, trackways, settlement hubs, and settlement zones specific YDNA lineages likely used or avoided in particular periods. For those that think in graphical terms, I offer a venn diagram in illustration two below.

Illustration Two: The Methodological Overlapp between the Use of Globetrekker and Landscape Archaeological Research

The focus of this story is discussing, in greater detail, the utility and integrative nature of using Globetrekker, the genetic genealogical mapping tool, with the research findings associated with landscape archaelogy when weaving family stories about YDNA migration in the ‘dark ages’ in an area we now call the Netherlands. Using this phylogeographical tool and the unique blend of landscape archaeological research has given me an appreciation of what roughly 95 or so generations of my YDNA lineage experienced in their migration in the late Roman and Early mediaval eras.

What is Globetrekker^TM

The mix of genes and geography is the most potent recipe for studying human history. Phylogeography has attempted that feat since the 1980s, and we are taking it one step further with Globetrekker! How did your ancestors trek across the globe? [2]

Phylogeography is the study of how genealogical lineages are distributed across geographic space through time, using genetic data to infer the historical processes that generate patterns of variation. It explicitly links phylogenetics and population genetics with biogeography, focusing on how climatic or geological change structure genetic lineages within and among closely related populations and species. [3]

Table One: Breakdown of What is Phylogeography

Phylogenetics	The study of evolutionary relationships between organisms, aiming to reconstruct their shared ancestry and evolutionary history, primarily using DNA/RNA sequences [4] or physical traits. [5]
Population Genetics	The study of genetic variation within and between populations, focusing on how allele frequencies (a variant of a gene) change over time due to forces like natural selection, genetic drift, mutation, and migration. [6]
Biogeography	The scientific study of how and why plants, animals, and ecosystems are distributed across Earth’s surface. [7]

Modern statistical phylogeography usually considers genome-wide (population) spread, whereas the Globetrekker platform utilizes the test results of Big Y DNA customers, solely for exploring patrilineal history.

Globetrekker is a specialized mapping tool originally developed by FamilyTreeDNA (FTDNA) as an exclusive feature for their Big Y-DNA test customers. It visualizes ancestral migration paths on a global scale, tracing paternal lineage journeys from “Y-Adam” (the earliest common paternal ancestor, approximately 200,000 years ago) to the most recent known locations of direct paternal ancestors. [8]

Globetrekker employs ‘advanced phylogenetic algorithms’ that factor in geographical topography, historical sea levels, land elevations, and ice age glaciation patterns to determine likely ancestral migration routes. The tool also incorporates user-provided information regarding the earliest known ancestors (EKAs) to pinpoint the migratory patterns. [9]

The developers of Globetrekker specifically adapted the use of least cost paths (LCPs) and least cost corridors (LCCs) as probabilistic migration zones, including a tiered 95, 96.6 and 98.3 percent corridor scheme from landscape genetics research. The method takes the inferred locations of successive haplogroups and connects them with LCPs, computed over a ‘cost surface’ built from slope, distance to land, coastal routing, sea currents, and glacial boundaries. Around each LCP, it builds LCCs that represent areas that are 95%, 96.6%, and 98.3% likely to contain the ‘true’ path.

Corridor paths are derived from LCP and LCC modeling, adapted from landscape genetics methods published in Heredity, the official journal of the Genetics Society. The algorithm uses environmental data and ancient geography to estimate ancestral movement across time. [10]

Earlier phylogeography tools largely used ‘centroids’ (a geometric center, or “balance point,” representing the average position of all its points of tester locations and straight or smoothed “as‑the‑crow‑flies” lines between them). Globetrekker instead uses a cost-based movement model from landscape genetics to reflect realistic movement constraints. The explicitly probabilistic corridor bands (rather than a single deterministic line) are the key innovation taken from landscape genetics, providing confidence-style envelopes around each inferred migration segment instead of just mapping one route.

GlobeTrekker identifies each ancestral haplogroup’s probable position and then connects them using these ‘cost-efficient routes’ that consider:

Slope steepness (to avoid rugged terrain);
Distance to land (favoring coastlines);
Ocean current direction and strength (penalizing movement against currents); and
Past topography and sea levels, including exposed Ice Age land bridges and glacial boundaries. [11]

In a FamilyTreeDNA blog article, Paul Maier, a population geneticist for FamilyTreeDNA argues that combining phylogenetic structure, curated environmental reconstructions, least‑cost path/corridor methods from landscape genetics, and time‑aware spacing between haplogroups transforms Globetrekker from a simple “dot map” into a probabilistic reconstruction of human movement constrained by both genetics and landscape. [12]

Paul Maier

Maier emphasizes that the Globetrekker outputs are still model‑based estimates. The least‑cost paths and the three‑tier least‑cost corridors provide a graded ‘confidence envelope’. They rely on simplified assumptions about what constituted “cost” for past humans and may need future tweaking as scholarship on mobility improves. He concludes that Globetrekker currently represents the latest advance in Y‑DNA research at FTDNA by integrating their Big Y age estimates (their most comprehensive YDNA test) [13] , Discover™ ancient DNA reports (unique YDNA summary reports) [14] , and landscape genetics.

He anticipates iterative refinement as more samples, better environmental data, and improved ideas about human movement become available. A key operational takeaway is that the accuracy of Globetrekker depends heavily on users supplying correct, internally consistent Earliest Known Ancestor (EKA) countries and coordinates. These EKAs represent ‘leaf‑level’ new haplogroup branches, anchors of the haplogroup tree, that drive the entire bottom‑up placement of ancestral nodes.

Maier describes a four‑step workflow. In laymen’s terms, what this four step workflow entails is (1) build the old world map your ancestors actually faced, (2) clean the data so only believable, consistent locations remain, (3) estimate where each ancestor probably lived on that changing map, and (4) draw the easiest likely routes between those places using “path of least resistance” rules. [15]

The method first reconstructs past coastlines, land bridges, ice sheets, and ocean conditions so that migrations are modeled on the world as it looked thousands of years ago, not today. It also distinguishes between overland, coastal, and open‑ocean travel, favoring routes that hug coasts or land when that fits known historical patterns.

The second stage involves cleaning up the data. The samples of YDNA that obviously do not fit history (for example, a European Y‑line placed in colonial‑era America) or whose coordinates contradict the reported country are removed or corrected. YDNA branches where the few samples are scattered across continents, or where a single odd sample would distort the pattern, are collapsed so outliers do not drag the inferred migration unrealistically.

In the third stage, the method works up the phylogenetic tree, starting from known Y700 test results of YDNA users’ EKA locations and documented ancient samples, then placing each ancestral common ancestor asociated with haplogroup branches roughly in the middle of its closest descendant branches, while giving more weight to better and nearer‑in‑time data. It then adjusts these positions so they stay on plausible land at the right time, smooths away zig‑zags caused by outliers, and spaces ancestors according to their genetic ages so older ancestors are not forced to sit right next to modern descendants.

Once ancestral points are set, in the fourth stage the software connects them with “least‑cost paths,” which are the easiest routes given terrain steepness, distance from land for coastal travel, and ocean currents for sea travel. Around each path it builds “corridors” showing broader zones that are still quite likely, giving a visual band of plausible movement rather than a single razor‑thin line.

Whew, easier said than done.

The Lowlands in the Dark Ages in ‘an Interdisciplinary Light’

This subheading in this story is derived from a published study by Esther Jansma and associates entitled, “The Dark Age of the Lowlands in an interdisciplinary light: people, landscape and climate in The Netherlands between AD 300 and 1000“.

I thought it was an eye catching title for an interesting but perhaps dense research paper that I thought was an amazing article. It is a catchy literary or rhetorical use of placing contrasting elements (“dark ages” and “in an interdisciplinary light”) in close proximity to highlight their differences and to create an interesting effect. “Dark Ages” is a discriptive term that has been used to describe an historical era that we lack of knowledge of. “Interdisciplinary light” is a metaphor for knowledge, understanding, or illumination across academic disciplines. [16]

The title implies that the research “illuminates” a period previously considered “dark” or poorly documented. The research reported in the paper does indeed provide an innovative scientific and historical approach to shed light on human interaction with the environment, in the area we call the Netherlands in the early Medieval era. The research is part and reflective of a larger innovative interdisciplinary research effort that focused on the ‘dark ages’ in the lowlands. The research from this project and from scholars using related interdisciplinary approaches have increased my understanding of historical facts and my ability to document and make sense of my research on the migratory path of the Griff(is)(es)(ith) YDNA genetic lineage in this time period.

The “Dark Ages” is a misleading label for a complex era of upheaval and transformation, not just a mysterious era as implied by the name. The “Dark Ages” typically refers to Europe’s Early Middle Ages, roughly 476 CE to 1000 CE. It is a time perod where not much is available in written form. It is a period following the fall of Rome marked by societal decline, warfare, and fragmentation.

However, the dark ages is now seen by historians as an oversimplification, as this era also saw the rise of christian monasticism, significant cultural growth, agricultural innovations, and the emergence of foundations of later medieval society. The term itself originated from Renaissance scholars who contrasted it unfavorably with antiquity. [17]

During roughly 400–800, the Netherlands region shifted from a Roman frontier zone with towns, taxation and a military‐fiscal economy to a patchwork of largely rural, low-density agrarian societies under shifting Frankish and Frisian political control, with new elites, emerging Christian institutions, and long-distance trade hubs like Dorestad emerging by the late seventh to eighth centuries. Rather than a uniform “dark age,” it was a period of demographic contraction and reoccupation, environmental stress and adaptation, and gradual consolidation of Merovingian and then Carolingian social structures of lordship and ecclesiastical power. [18]

As discussed in a mult-part story, a genetic YDNA ancestor of the Griff(is)(es)(ith) line lived at the end of the Roman era or perhaps the late iron age / early medieval times, the ‘dark ages’, in an area that is now known as the Netherlands. This ancestor was the most recent common ancestor of the haplogroup G-Z6748. He was born approximately 668 CE.

The dark ages coincided with dramatic land-use changes in many parts of post-Roman Europe. [19] This collapse coincided with a period of severe river-network changes due to increased sedimentation and flooding in the Meuse Rhine River watershed area. [20] During the Dark Ages in the Netherlands, coastal areas faced intense environmental change from human-induced peatland drainage (causing land subsidence and increased flooding) and natural sea-level rise, transforming peat bogs into tidal zones and salt marshes, leading to widespread inundation, drowned settlements, and a shift towards a more maritime landscape. [21]

Severe depopulation also took place and trade networks collapsed. Various aspects of the previous Iron-Age cultural landscape re-emerged. Researchers utilizing this multidisciplinary approach highlight the value of integrating archaeological, geoscientific, and modeling approaches to test hypotheses about past population dynamics and their consequences for historical landscapes. [22] As identified by van Lanen and Groenewoudt, several sub‑regions experienced the late/post‑Roman decline with markedly different timing and severity, especially when comparing the coastal belt, the central river area, and the higher coversand zones inland. [23]

The Dark Ages (Early Middle Ages) in the Netherlands, marked by Roman collapse and decliining population shifts, created a foundation for the remaining population base to create a growing structure of stable local male lineages due to the persistence of patrilocal groups and limited geographical male movement, leading to strong regional YDNA structures. The Dark Ages established the basis for distinct male lineages in the Netherlands, but it was later medieval and early modern processes that fully developed the complex regional YDNA patterns that we see today. [24]

The Research Program ‘Dark Ages in an Interdisciplinary Light‘

The research mentioned above by Esther Jansma and associates explore the Late Roman to Early Medieval period in the Netherlands by combining research methodologies from archaeology, dendrochronology (tree-ring dating), palaeoecology, geography, and climate science to understand human-landscape interaction. The research was the result of collaborative efforts by researchers from a number of different academic disciplines and part of a larger funded research project. This project integrates diverse archaeological datasets (e.g., wood analysis, pottery distribution, elevation models) to create an holistic understanding of the Dutch Lowlands, demonstrating how environmental factors, climate shifts, and human decisions shaped this historical era.

The work of Jansma and associates was part of a larger research program with a common theme. The research program, ‘The Dark Age of the Lowlands in an interdisciplinary light’, was funded by The Netherlands Organization for Scientific Research (NWO, 2012-2017) and managed at the department of Physical Geography at Utrecht University, Netherlands.

“The program focuses on spatial developments in the Low Countries during a period of severe pan-European economic and demographic change: the Late Roman Period and the Early Middle Ages (AD 300- 1000). Physical-geographical and palaeoenvironmental data from coastal-deltaic lowlands and more inland regions in the Netherlands indicate marked landform and land-use changes as well as climatic variability during this time interval.” [25]

Illustration Three: Research Areas of the Interdisciplinary Program

The project received core project funding for roughly six to seven years. NWO lists the project within the 2012–2019 window. The 2012–2017 bracket mentioned in Jansma et. al’s. paper captures the main funding phase. It directly generated at least eight peer ‑ reviewed scientific articles, four substantial book‑chapter–type product contributions listed by NWO, and underpinned at least three PhD projects (although these theses are not enumerated individually on the public NWO and Utrecht portals). [26]

What Defines this Mutlidisciplinary Approach in Studying the Dark Ages in the Lowlands?

These studies involve overlapping research traditions. They are often framed explicitly as contributions to a broader “landscape‑archaeological” and “connectivity/persistence” program for the Dutch delta in the first millennium CE.

Researchers such as Van Lanen, Groenewoudt, Spek and Jansma, among others, work firmly within landscape archaeology, combining palaeogeography, geomorphology, soils and hydrology with archaeological data to reconstruct “total” cultural landscapes through time.

“Landscape archaeology can be defined as the interdisciplinary investigation of the long-term relationship between people and their environment . . . . Probably the greatest benefit of a landscape-archaeological approach is the way it shifts the focus from a “single-site” perspective to much larger areas that are more closely matched to the physical scale at which human societies operate. Such an approach is inevitably multidisciplinary. Landscape-archaeological approaches have in common that the (dynamics of) the historical landscape as a whole is being investigated as a single, complex “site.” “Landscape” within this context is defined at a basic level, being “an area, as perceived by people, whose character is the result of the action and interaction of natural and/or human factors”.” [27]

Methodologically this aligns with a wider international trend in settlement and landscape archaeology that uses Geographic Inforation Systems (GIS) based modelling [28] to study accessibility, route networks and off‑site activity areas, but the Dutch work is unusually systematic in its national-scale application and depth. This places their studies within a wider school of archaeological research on long‑term network stability and path dependence in cultural landscapes, but with a strong Dutch delta variant that treats route networks, settlements, demography and land use as dynamically interacting subsystems.

Their publications explicitly frame “connectivity” (degree of interlinkage between places) and “persistence” (long‑term re‑use of locations and corridors) as key analytical concepts, drawing on Sarah Schlanger’s notion of “persistent places” and embedding them in what is referred to as a ‘multi‑proxy modelling framework‘.

Sarah Schlanger used “persistent place” to describe locations that are repeatedly used over the long-term occupation of a region, and that link isolated finds with more substantial archaeological sites in a single landscape-use system. Schlanger defines persistent places as localities “that were repeatedly used during long-term occupations of regions,” neither reducible to formal archaeological sites nor to passive landscape features but emerging from the conjunction of particular behaviors with particular locations. [29]

“I propose to treat both the isolated (archaeological) finds and the sites together and to employ them as tools for studying the use of a landscape occupied by prehistoric horticulturalists. The concept I use to link sites and isolated finds to landscapes is the concept of the “persistent place,” a place that is used repeatedly during the long-term occupation of a region.” [30]

Persistent places may be associated with:

Unique environmental or topographic qualities that attract recurrent use (e.g. marsh edges, access routes, vantage points);
Cultural constructions such as hearths, shelters, storage features, or house ruins that focus and structure later reoccupation.; and/ or
Accumulations produced by repeated visits and use that are not dependent on built features but on the continued presence of cultural material in the landscape.

These places are archaeologically visible as spots where occupations, activities, and material deposition recur over extended periods to tme, producing multicomponent assemblages or dense accumulations within a wider settlement system. Schlanger also emphasizes that entire landscapes can function as persistent places when patterns of reoccupation, abandonment, and return maintain enduring relationships between people and particular tracts of land across centuries.

A multi-proxy modeling framework integrates diverse, indirect natural records (proxies like tree rings, ice cores, sediments) to reconstruct past environments, using statistical or computational models to combine their complementary ‘signals’, quantify uncertainties, and gain a more robust understanding of past climate or other conditions than any single proxy could provide alone. This framework moves beyond simple cross-checking, using advanced techniques to blend data, model uncertainties consistently, and reveal complex climate histories.

A well-known example is the multi‑proxy route‑modelling framework developed by Van Lanen and colleagues for reconstructing Roman and early medieval transport networks in the Netherlands. Van Lanen et al. combine several data types in a single GIS‑based modelling framework. The framework integrates environmental friction surfaces (soil, relief, hydrology), archaeological settlement and burial distributions, and shipping‑related finds to generate and validate route networks for different time slices (e.g. 100, 500, 900 CE). [31]

These researchers utilize a research approach that integrates layers of archaeological settlement data, geomorphological maps, soil and groundwater data and tree ring data within Geographic Information Systems (GIS) models, to understand the long-distance transport routes and their dynamics during the first millennium CE in the Dutch river delta (see illustration four).

Illustration Four: An Example of a Flowchart of route-persistence calculations based on integrating various historical data sets

This interdisciplinary approach produces predictive models to reconstruct past movement corridors and assess their persistence through time. Route persistence is studied to explain long‑term settlement foci, land‑use patterns, and “persistent places” in cultural landscapes.

How the Methodological Approaches Associated with Globetrekker and Landscape Archaeology Compliment Each Other

Globetrekker provides a statistically smoothed, large‑scale reconstruction of patrilineal migration paths, while landscape‑archaeological work on connectivity, persistence places, and corridors can supply the fine‑grained, time‑specific spatial frameworks needed to interpret those paths in real historical landscapes. Used together, they let you move from an abstract Y‑DNA trajectory to concrete hypotheses about which river valleys, trackways, hubs, and settlement zones specific lineages likely used or avoided in particular periods.

Landscape‑archaeological models reconstruct route networks and “hypothetical movement corridors” from palaeogeography, soils, elevation, groundwater and other geoscientific data, then test them against settlements, burials, shipwrecks, etc. Persistence analysis identifies long‑term stable “persistent areas” and route segments that remain in use across multiple time periods, often clustering around later historic towns and acting as long‑term attractors for movement and settlement.

Globetrekker’s broad phylogeographic path can be overlaid onto modeled corridor networks to see which persistent corridors and hubs are most compatible with a given haplogroup’s inferred movements in each time slice. Conversely, where corridor models predict strong, long‑lived route networks but relevant haplogroups show limited crossing, that mismatch can highlight demographic boundaries, cultural frontiers, or asymmetric connectivity not obvious from archaeology alone.

From Generic Paths to Specific Corridors

Corridor models can ‘dissect’ Globetrekker’s smoothed line into concrete options for consideration. For example, the findings of land archaeological studies can help determine whether a patrilineal trajectory into a basin is more consistent with a specific river system, interfluve ridgeway, or coastal lowland, given friction surfaces and known route persistence. This allows for the targeted assessment of archaeological fndings once a Globetrekker path intersects a persistence zone. One can focus on settlements, cemeteries, and land‑use systems in that zone to see whether demographic signals align with the Y‑DNA branch’s age and geography.

Integrating Time, Scale, and Uncertainty

Landscape models operate in ‘temporal windows’ (e.g. Roman, early medieval, early modern) with explicit environmental boundary conditions, while Globetrekker provides genetic based ‘temporal anchors’ for each branch. Aligning the two tightens chronological hypotheses for when specific corridors became important for a migration. Because Globetrekker includes spatial “hotspots” and uncertainty bands, overlapping those with areas of modeled ‘accessibility’ and ‘long‑term route persistence’ helps distinguish our historically informed inferences from speculative ones, improving how genealogical users read the maps.

A Comparison of the Terms Used by Globetrekker and Landscape Archaeology

Globetrekker and Roman/early‑medieval route‑persistence studies use overlapping but differently framed vocabularies for movement and connectivity; many terms map cleanly onto each other if treated as probabilistic models of paths and corridors through constraining landscapes.

The table below pairs key terms and highlights how each field conceptualizes routes, uncertainty, and long‑term stability.

Table Two: Comparison of Similar Terminology

Concept focus	Globetrekker term	Route‑persistence / land‑archaeology term
Basic movement line	Migration path / ancestral path: LCP‑based line connecting ancestral haplogroup locations over time. [32]	Route / path / road segment: modeled or attested line of movement between nodes (settlements, crossings). [33]
Probabilistic zone	Least Cost Corridor (LCC) with 95–98.3% “corridor levels” expressing likelihood the true path lies within. [34]	Route zone / movement corridor: network friction derived bands of high accessibility predicting likely route orientations. [35]
Movement cost surface	Friction layers from slope, distance to land, currents, land/sea masks used to compute LCPs between haplogroup points. [36]	Network‑friction surface / cost surface combining palaeogeography, soils, elevation, groundwater, etc., to model accessibility. [37]
Spatial uncertainty	Hotspot: spatial uncertainty envelope around a haplogroup’s “Mean Path Intersect” location. [38]	Uncertainty band / model error: spatial tolerance where modeled route zones are checked against observed infrastructure/ finds. [39]
Temporal anchors	TMRCA‑based time slices and animated migration through chronologically ordered haplogroup nodes. [40]	Periodized networks (Roman, early‑medieval, early‑modern) compared across time windows to study change and continuity. [41]
Multi‑period stability	(Not a formal label, but visually implied) overlapping paths for many lineages through similar corridors over time. [42]	Route persistence / route‑network stability: quantified degree to which route‑zone sections recur across periods (e.g. AD 100–1600). [43]
Preferred options	Most likely corridor / most likely path determined by combined LCP + corridor modeling and filtering. [44]	Best travel options: multi‑proxy modeled Roman and early‑medieval routes that maximize accessibility and match archaeological evidence.[45]
Spatial nodes	Implicit ancestral location nodes where haplogroups are time‑stamped and paths turn or branch. [46]	Nodes / hubs / crossings / persistent places: intersections of major routes, river crossings, and long‑lived focal points of movement. [47]
Model validation	Internal checks on Earliest Known Ancestor (EKA) consistency, comparison with ancient DNA points and geography; corridors treated as confidence envelopes. [48]	Validation with infrastructure and finds: percent of known Roman/ early ‑ medieval roads and isolated finds falling inside modeled route zones. [49]

Globetrekker’s vocabulary centers on phylogeographic inference and statistical confidence (the most recent common ancestor [TMRCA], hotspots, LCP/LCC corridors, likelihood levels) because its primary goal is to model lineage trajectories from genetic data under environmental constraints.

Roman/early‑medieval route‑persistence work focuses on accessibility, stability, and ‘multi‑proxy’ validation (network friction, route zones, persistence, best travel options) because it aims to reconstruct and quantify real route networks across periods using environmental data plus archaeological observations.

The Ability to Understand the Longue Durée of Genetic Migration through the Landscape Archaeological View

Similar to the advantages of combining traditional genealogical research with genetic genealogy to understand different time perods of genealogical research, the ablity to combine the results from the Globetrekker tool with landscape oriented archaeology greatly enhances our ability to understand the ‘Longue Durée” period of our genetic genalolgy. [50]

Landscape archaeological approaches developed for the “Dark Age” / first millennium AD in the Netherlands have been applied to other regions and to many different periods, from the Palaeolithic to the High Middle Ages and beyond. For example, in the Southern Baltic lowlands, high‑resolution reconstructions of how a major medieval trade route (via Marchionis) shaped erosion, vegetation and agrarian regimes over centuries, combining cores, pollen and archaeological data. [51] Also. in the early medieval Wessex (England) area, Langlands’ work models road networks and communications using charter boundary clauses, toponymy, topography and archaeological evidence, explicitly framed as a landscape approach to routes and movement. [52] These are methodologically very close to the Dutch “Dark Age” connectivity and persistence studies, just in different historical and documentary contexts.

Within the Netherlands the same approach has been pushed both backwards and forwards in time. Fokkens and his successors’ work on a “living landscape” in the Neolithic Iron Age uses large datasets of settlements, burials and deposits to reconstruct Bronze and Iron Age cultural landscapes at multiple scales. [53] Historical land‑use research in Drenthe and other sandy upolands links prehistoric barrows, Celtic fields, medieval fields and later agrarian systems into a single diachronic landscape narrative. [54] Vos and others trace reclamation, peat ingressions and flooding in late Iron Age – Medieval wetlands from the Late Iron Age through ca. 1000 CE, explicitly as coupled physical and social landscape change. [55] So the “Dark Age” program is one phase within a much longer Dutch landscape‑archaeological tradition.

Beyond the Low Countries and early medieval Europe, landscape archaeology has been adapted to different time periods. For example, palaeolithic work on the Middle Palaeolithic in the Netherlands situates Neanderthal sites within loess plateaus, ice‑pushed ridges and glacial geomorphology, treating the landscape template as central aspect to interpreting the past. [56] Another example is a study of medieval road operation in the southern Baltic and other regions tieing route maintenance, erosion and vegetation to changing economic and political regimes at landscape scale. [57] There are also methodological overviews that explicitly present landscape‑factor case studies as templates or inspirations for other archaeological projects, underlining that the approach is not period‑bound. [58]

In practice, the same toolbox—palaeoenvironmental reconstruction, spatial modelling, settlement pattern analysis, and route/mobility modelling—is now used from deep prehistory to the late medieval period and in many different regions; what changes are the temporal resolution, available proxies and the historical questions being posed.

Sources:

Feature image: The story banner consists of a number of ‘Network-friction maps’, characteristic of the ‘Landscape Archaeological approach’, from left to right: (1) Areas in the Netherlands where landscape changes occur between AD 100 and 800. (2) Network-friction map AD 800 for water: areas with almost no network friction (accessible regions) have been designated as suitable areas for potential water routes. (3) Network-friction map AD 800 for land: light gray depicts areas with almost no network friction (accessible regions), which must have been suitable for potential routes. Dark gray grid cells depict areas with landscape obstacles (inaccessible regions). (4) Maps four and five represent land and water routes in 100 AD and 800 AD

Sources of the maps can be found in:

van Lanen, Rowin J., Menne C. Kosian, Bert J. Groenewoudt and Esther Jansma, Finding a Way: Modeling Landscape Prerequisites for Roman and Early-Medieval Routes in the Netherlands, Geoarchaeology: An International Journal 00 (2015) 1–23 pp. 200 – 222, https://www.academia.edu/11879781/Van_Lanen_et_al_2015_Finding_a_way_Modeling_Landscape_Prerequisites_for_Roman_and_Early_Medieval_Routes_in_the_Netherlands

van Lanen, Rowin J. and Bert J. Groenewoudt, Theo Spek, Esther Jansma, Route persistence. Modelling and quantifying historical route-network stability from the Roman period to early-modern times (AD 100–1600): a case study from the Netherlands, Archaeol Anthropol Sci (2018) 10:1037–1052 DOI 10.1007/s12520-016-0431-z , https://www.researchgate.net/publication/310757823_Route_persistence_Modelling_and_quantifying_historical_route-network_stability_from_the_Roman_period_to_early-modern_times_AD_100-1600_a_case_study_from_the_Netherlands

[1] Haplogroup, Wikiepdia, This page was last edited on 7 January 2026, https://en.wikipedia.org/wiki/Haplogroup

[2] Runfeldt, Goran, Globetrekker, Part 1: A New FamilyTreeDNA Discover™ Report That Puts Big Y on the Map, 31, Jul 2023, FamilyTreeDNA Blog, https://blog.familytreedna.com/globetrekker-discover-report/

See also:

Maier, Paul, Part 2: Advancing the Science of Phylogeography, 15 Aug 2023, FamilyTreeDNA Blog, https://blog.familytreedna.com/globetrekker-analysis/

Vilar, Miguel, Globetrekker, Part 3: We Are Making History, 26 Sep 2023, FamilyTreeDNA Blog, https://blog.familytreedna.com/globetrekker-history/

[3] Phylogeography, Wikipedia, This page was last edited on 3 October 2025, https://en.wikipedia.org/wiki/Phylogeography

Phylogeography, International Society of Genetic Genalogy Wiki, This page was last edited on 29 July 2021, https://isogg.org/wiki/Phylogeography

Avise, John C., The history and purview of phylogeography: a personal reflection, Molecular Ecology (1998) 7, 371–379, https://escholarship.org/content/qt1hv4f8vk/qt1hv4f8vk.pdf

[4] DNA/RNA sequences are the specific order of nucleotide bases (A, T/U, C, G) that make up a DNA or RNA molecule, essentially the genetic alphabet that carries instructions for building and operating living organisms, with DNA sequencing determining this order for DNA and RNA sequencing for RNA, revealing gene activity and functions.

Alberts B, Johnson A, Lewis J, et al. Molecular Biology of the Cell. 4th edition. New York: Garland Science; 2002. From DNA to RNA. Available from: https://www.ncbi.nlm.nih.gov/books/NBK26887/

[5] Phylogenetics, Wikipedia, This page was last edited on 12 January 2026, https://en.wikipedia.org/wiki/Phylogenetics

[6] Population Genetics, Wkipedia, This page was last edited on 31 December 2025, https://en.wikipedia.org/wiki/Population_genetics

[7] Biogeography, Wikipedia, This page was last edited on 15 January 2026, https://en.wikipedia.org/wiki/Biogeography

[8] Estes, Roberta, Globetrekker – A New Feature for Big Y Customers From FamilyTreeDNA, 4 Aug 2023, DNAeXplained-Genetic Genealogy, https://dna-explained.com/2023/08/04/globetrekker-a-new-feature-for-big-y-customers-from-familytreedna/

Runfeldt, Goran, Globetrekker, Part 1: A New FamilyTreeDNA Discover™ Report That Puts Big Y on the Map, 31, Jul 2023, FamilyTreeDNA Blog, https://blog.familytreedna.com/globetrekker-discover-report

[9] Estes, Roberta, Globetrekker – A New Feature for Big Y Customers From FamilyTreeDNA, 4 Aug 2023, DNAeXplained-Genetic Genealogy, https://dna-explained.com/2023/08/04/globetrekker-a-new-feature-for-big-y-customers-from-familytreedna/

Runfeldt, Goran, Globetrekker, Part 1: A New FamilyTreeDNA Discover™ Report That Puts Big Y on the Map, 31, Jul 2023, FamilyTreeDNA Blog, https://blog.familytreedna.com/globetrekker-discover-report

Maier, Paul, Part 2: Advancing the Science of Phylogeography, 15 Aug 2023, FamilyTreeDNA Blog, https://blog.familytreedna.com/globetrekker-analysis/

[10] Journal Information, Heredity, https://www.nature.com/hdy/journal-information

Maier, Paul, Part 2: Advancing the Science of Phylogeography, 15 Aug 2023, FamilyTreeDNA Blog, https://blog.familytreedna.com/globetrekker-analysis/

[11] Maier, Paul, Part 2: Advancing the Science of Phylogeography, 15 Aug 2023, FamilyTreeDNA Blog, https://blog.familytreedna.com/globetrekker-analysis/

[12] Maier, Paul, Part 2: Advancing the Science of Phylogeography, 15 Aug 2023, FamilyTreeDNA Blog, https://blog.familytreedna.com/globetrekker-analysis/

[13] The FTDNA Big Y‑700 (often just called “Y700”) is FamilyTreeDNA’s most comprehensive Y‑chromosome test for genetic males. It is designed to characterize a man’s paternal line using both Short Tandem Repeats (STRs)and high‑coverage Single Nucleotide Polymorphism (SNP) sequencing. It aims to identify a test taker’s most precise Y‑DNA haplogroup by sequencing a large, SNP‑rich region of the Y chromosome and identifying both known and novel SNPs.

It is optimized for deep paternal lineage reconstruction, building out branches of the Y‑chromosome phylogenetic tree and refining time to the most recent common ancestor (TMRCA) estimates between men on the same line. Next‑generation sequencing targets roughly 20–25 million Y chromosome base pairs in the phylogenetically useful regions of the Y chromosome, reporting hundreds to thousands of known Single Nucleotide Polymorphism (SNPs) plus previously unknown variants unique to the tester. It also includes the full Y‑111 Short Tandem Repeats (STRs) panel plus at least approxmately 589 additional STR markers, giving a total of 700 plus Y‑STRs, which improves resolution for more recent paternal relationships compared with traditional Y37/Y67/Y111 STR marker tests.

See:

Introduction to the Big Y-700 Test, FamilyTreeDNa Help Cener, https://help.familytreedna.com/hc/en-us/articles/4414479800463-Introduction-to-the-Big-Y-700-Test#h_01HXCWFG501Z529S362GNK3P34

Big Y-700: The Forefront Of Y Chromosome Testing, 7 Jun 2019, FamilyTreeDNA Blog, https://blog.familytreedna.com/human-y-chromosome-testing-milestones/

Estes, Roberta, The Big Y-700 Test Marries Science to Genealogy, 11 Jul 2024, DNAeXplained, https://dna-explained.com/2024/07/11/the-big-y-700-test-marries-science-to-genealogy/

[14] FamilyTreeDNA Discover™ ancient DNA reports are curated summaries that link your tested haplogroups (Y-DNA or mtDNA) to sequenced ancient individuals from archaeological contexts and to modeled ancient populations, with estimated timeframes and shared ancestry depths. They are designed as interpretive tools for context and hypothesis-building, not as direct genealogical matches in the usual family-history sense.

Discover’s ancient reports take published ancient DNA datasets and map them onto FTDNA’s Y- and mtDNA haplotree and autosomal reference panels, so your results can be compared to ancient individuals or populations that share a haplogroup or autosomal profile with your test kit.

The system then provides age estimates on most recent common ancestors asoociated with haplogroups (TMRCA), geographic and cultural metadata, and short narrative summaries to place those ancient connections in historical context.

For Y-DNA, Discover links a test kit’s haplogroup (especially Big Y–derived subclades) to ancient male individuals carrying the same or ancestral Y-haplogroups, and places them on the Discover haplogroup maps and time tree. Individuals who manage test kits are provided information onhaplogroup age estimates, approximate formation times for branches, locations of ancient samples (often shown as icons on maps or trees), and sometimes short context paragraphs about key sites or cultural phases represented by those ancient men.

See:

Introducing FamilyTreeDNA Discover™, 15 Jul 2022, FamilyTreeDNA Blog, https://blog.familytreedna.com/introducing-familytreedna-discover/

Vilar, Miguel G., Unlocking Our Ancestry: The Fascinating Science of Ancient DNA Analysis, 2 Sep 2022, FamilyTreeDNA Blog, https://blog.familytreedna.com/what-is-adna/

Vilar, Miguel G., What’s New in Ancient DNA and Ancient Discover™ Connections, 11 Jun 2024, FamilyTreeDNA Blog, https://blog.familytreedna.com/ancient-dna-research-ancient-discover-connections/

Estes, Roberta, FamilyTreeDNA Discover™ Launches – Including Y DNA Haplogroup Ages, 22 Jun 2022, DNAeXplained, https://dna-explained.com/2022/06/30/familytreedna-discover-launches-including-y-dna-haplogroup-ages/

Using the mtDNA Discover™ Ancient Connections Report, FamilyTreeDNa Help Center, https://help.familytreedna.com/hc/en-us/articles/12750396320399-Using-the-mtDNA-Discover-Ancient-Connections-Report

Vilar, Miguel, What’s New in Ancient DNA and Ancient Discover™ Connections, 11 Jun 2024, FamilyTreeDNA Blog, https://blog.familytreedna.com/ancient-dna-research-ancient-discover-connections/

Rowe-Schurwanz, Katy, Interpreting Your Recent and Ancient Origin Results, 7 Sep 2024, FamiyTreeDNA Blog, https://blog.familytreedna.com/recent-and-ancient-origin-results/

[15] Maier, Paul, Part 2: Advancing the Science of Phylogeography, 15 Aug 2023, FamilyTreeDNA Blog, https://blog.familytreedna.com/globetrekker-analysis/

[16] Esther Jansma, with Marjolein Gouw-Bouman, Rowin Van Lanen, Harm Jan Pierik, Kim Mikkel Cohen, Bert J. Groenewoudt, Wim Hoek, Esther Stouthamer, Hans Middlekoop, The Dark Age of the Lowlands in an interdisciplinary light: people, landscape and climate in The Netherlands between AD 300 and 1000, European Jourrnal of Postclassicalarchaelogigies (4) May 2014, 471-476, https://www.researchgate.net/publication/265096511_The_Dark_Age_of_the_Lowlands_in_an_interdisciplinary_light_people_landscape_and_climate_in_The_Netherlands_between_AD_300_and_1000

[17] Dark Ages (historiography) Wikipedia, This page was last edited on 17 December 2025, https://en.wikipedia.org/wiki/Dark_Ages_(historiography)

Britannica Editors. “Migration period”. Encyclopedia Britannica, 23 Mar. 2018, https://www.britannica.com/event/Dark-Ages .

[18] Wickham, Chris, Framing the Early Middle Ages: Europe and the Mediterranean, 400—800 (Oxford, 2005; online edn, Oxford Academic, 3 Oct. 2011), https://doi.org/10.1093/acprof:oso/9780199264490.001.0001

W.A. van Es & W.J.H. Verwers, Early Medieval settlements along the Rhine: precursors and contemporaries of Dorestad, Journal of Archaeology in the Low Countries, 2-1 (May 2010), https://jalc.nl/cgi/t/text/get-pdfcfad.pdf?c=jalc%3Bidno%3D0201a01

Bavel, Bas van, ‘The Emergence of a Regional Framework in the Early and High Middle Ages: Land and Occupation’, Manors and Markets: Economy and Society in the Low Countries 500-1600 (Oxford, 2010; online edn, Oxford Academic, 1 May 2010), https://doi.org/10.1093/acprof:oso/9780199278664.003.0002

[19] Cheyette, F.L., The disappearance of the ancient landscape and the climatic anomaly of the early Middle Ages: a question to be pursued, “Early Medieval Europe”, 16(2), 2008, pp. 127-165. https://www.academia.edu/395947/The_Disappearance_of_the_Ancient_Landscape_and_the_Climatic_Anomaly_of_the_Early_Middle_Ages_a_Question_to_Be_Pursued

[20] E. Stouthamer, E.. and H.J.A. Berendsen, Factors Controlling the Holocene Avulsion History of the Rhine-Meuse Delta (The Netherlands), “Journal of Sedimentary Research”, 70(5), 2000, pp. 1051-1064. https://www.researchgate.net/publication/250082489_Factors_Controlling_the_Holocene_Avulsion_History_of_the_Rhine-Meuse_Delta_The_Netherlands

Toonen, W.H.J. , A Holocene flood record of the Lower Rhine, PhD thesis Utrecht University, Utrecht Studies in Earth Sciences, 41, Utrecht. 2000\\13, https://www.researchgate.net/publication/299524556_The_influence_of_hydroclimatic_variability_on_flood_frequency_in_the_Lower_Rhine

Erkens, G., , Sediment dynamics in the Rhine catchment – Quantification of fluvial response to climate change and human impact, “Netherlands Geographical Studies”, 2009.

[21] Pierik HJ. Landscape changes and human–landscape interaction during the first millennium AD in the Netherlands. Netherlands Journal of Geosciences, Volume 100, e11. https://doi.org/10.1017/njg.2021.8

[22] Rowin J van Lanen and Bert Groenewoudt, Counting heads: Post-Roman population decline in the Rhine-Meuse delta (the Netherlands) and the need for more evidence-based reconstructions, in Niall Brady & Claudia Theune, eds, Settlement Change Across Medieval Europe: Old paradigms and New Vistas, , 2019, Ruralia XII, Leiden; Sidestone, 2019, https://www.academia.edu/40523376/Counting_heads_Post_Roman_population_decline_in_the_Rhine_Meuse_delta_the_Netherlands_and_the_need_for_more_evidence_based_reconstructions

Groenewoudt, Bert and Rowin J. van Lanen, Diverging decline. Reconstructing and validating (post-)Roman population trends (AD 0-1000) in the Rhine-Meuse delta (the Netherlands), Post Classicial Studies PCA 8 (2018) ISSN: 2039-7895 (pp. 189-218), https://www.researchgate.net/publication/327867127_Diverging_decline_Reconstructing_and_validating_post-Roman_population_trends_AD_0-1000_in_the_Rhine-Meuse_delta_the_Netherlands

Louwe Kooljmans, L.P., 1995, Prehistory or paradise? Prehistory as a reference for modern nature development, the Dutch case, Rifts Geologische Dienst, NR52 1995 pp. 415-424. https://www.academia.edu/92961347/Prehistory_or_Paradise_Prehistory_as_a_Reference_for_Modern_Nature_Development_the_Dutch_Case

Van Beek, R., and Groenewoudt, B.J. An Odyssey along the River Vecht in the Dutch-German border area. A Regional Analysis of Roman-period Sites in Germania Magna, Germania 89:157-190, 2011, https://www.researchgate.net/publication/259801460_Beek_R_vanBJ_Groenewoudt_2013_An_Odyssey_along_the_River_Vecht_in_the_Dutch-German_border_area_A_Regional_Analysis_of_Roman-period_Sites_in_Germania_Magna_Germania_89_2011_157-190

C. Wickman, C., Rethinking the structure of the early medieval economy, in J.R. Davis and M. McCormick (eds), The Long Morning of Medieval Europe, Burlington, Ashgate, 2008 , pp. 19-31.

Cheyette, F.L., The disappearance of the ancient landscape and the climatic anomaly of the early Middle Ages: a question to be pursued, “Early Medieval Europe”, 16(2), 2008, pp. 127-165. https://www.academia.edu/395947/The_Disappearance_of_the_Ancient_Landscape_and_the_Climatic_Anomaly_of_the_Early_Middle_Ages_a_Question_to_Be_Pursued

Willemsen, Annemariekeet and Hanneke Kik(eds) Dorestad in an International Framework. New Research on Centres of Trade and Coinage in Carolingian Times, Proceedings of the First ‘Dorestad Congress’, Leiden: Brepols Publishers, 2010.

Jansma, Esther, Rowin J. van Lanen, Harm Jan Pierik, Traveling through a River Delta: A Landscape-Archaelogical Recnstruction of River Development and Long-Distance Connections in the Netherlands During the First Millennium AD , Medieval Settlement Research 32 (2017), 35–39, https://www.academia.edu/35074210/Jansma_E_R_J_Van_Lanen_and_H_J_Pierik_2017_Travelling_through_a_river_delta_a_landscape_archaeological_reconstruction_of_river_development_and_long_distance_connections_in_the_Netherlands_during_the_first_millennium_AD_Medieval_Settlement_Research_32_35_39?nav_from=916b9486-c089-4cb3-b728-d0bdf8be8f1a

van Lanen, Rowin J., and Ham Jan Pierik, Calculating connectivity patterns in delta landscapes: Modelling Roman and early-medieval route networks and their stability in dynamic lowlands, Quaternary International xxx (2017) 1e20, 1-20, https://www.academia.edu/34741700/Van_Lanen_and_Pierik_2017_Calculating_connectivity_patterns_in_delta_landscapes_Modelling_Roman_and_early_medieval_route_networks_and_their_stability_in_dynamic_lowlands?nav_from=6a13d473-5ea5-4a1f-9e16-bf3867387aa2

[23] van Lanen, Rowan J. and Bert Groenewoudt, Counting heads: Post-Roman population decline in the Rhine-Meuse delta (the Netherlands) and the need for more evidence-based reconstructions, in Niall Brady & Claudia Theune, eds, Settlement Change Across Medieval Europe: Old paradigms and New Vistas, , 2019, Ruralia XII, Leiden; Sidestone, 2019, https://www.academia.edu/40523376/Counting_heads_Post_Roman_population_decline_in_the_Rhine_Meuse_delta_the_Netherlands_and_the_need_for_more_evidence_based_reconstructions

[24] Altena, E., Smeding, R., van der Gaag, K.J. et al. The Dutch Y-chromosomal landscape. Eur J Hum Genet 28, 287–299 (2020). https://doi.org/10.1038/s41431-019-0496-0

[25] Esther Jansma, with Marjolein Gouw-Bouman, Rowin Van Lanen, Harm Jan Pierik, Kim Mikkel Cohen, Bert J. Groenewoudt, Wim Hoek, Esther Stouthamer, Hans Middlekoop, The Dark Age of the Lowlands in an interdisciplinary light: people, landscape and climate in The Netherlands between AD 300 and 1000, European Jourrnal of Postclassicalarchaelogies (4) May 2014, 471-476, https://www.researchgate.net/publication/265096511_The_Dark_Age_of_the_Lowlands_in_an_interdisciplinary_light_people_landscape_and_climate_in_The_Netherlands_between_AD_300_and_1000

[26] Peer‑reviewed journal articles:

Doesburg, J. et al. 2016, “Roman and early‑medieval long‑distance transport routes in north‑western Europe: Modelling frequent‑travel zones using a dendroarchaeological approach.” Journal of Archaeological Science: Reports 6, 120–137.
DOI: 10.1016/j.jasrep.2016.01.01910.1016/j.jasrep.2016.01.019

Gouw‑Bouman, M.T.I.J. et al. 2014, “The Dark Age of the Lowlands in an interdisciplinary light: People, landscape and climate in The Netherlands between AD 300 and 1000.” Post‑Classical Archaeologies 4, 471–476. Stable link (open PDF):
https://www.academia.edu/26380319/The_Dark_Age_of_the_Lowlands_in_an_interdisciplinary_light_people_landscape_and_climate_in_The_Netherlands_between_AD_300_and_1000

Van Lanen, R.J. et al. 2015, “Best travel options: Modelling Roman and early‑medieval routes in the Netherlands using a multi‑proxy approach.” Journal of Archaeological Science: Reports 3, 144–159. DOI: 10.1016/j.jasrep.2015.05.02610.1016/j.jasrep.2015.05.026 , https://www.academia.edu/145412081/Best_travel_options_Modelling_Roman_and_early_medieval_routes_in_the_Netherlands_using_a_multi_proxy_approach

Van Lanen, R.J. et al. 2015, “Finding a Way: Modeling Landscape Prerequisites for Roman and Early‑Medieval Routes in the Netherlands.” Geoarchaeology 30, 200–222.
DOI: 10.1002/gea.2151010.1002/gea.21510

Cohen, K.M., H.J. Pierik & E. Stouthamer 2016, “A new GIS approach for reconstructing and mapping dynamic late Holocene coastal‑plain palaeogeography.” Netherlands Journal of Geosciences 95, 51–78.
DOI: 10.1017/njg.2016.1010.1017/njg.2016.10

Jansma, E., H.J. Pierik & R.J. van Lanen 2017, “Travelling through a river delta: A landscape‑archaeological reconstruction of river development and long‑distance connections in the Netherlands during the first millennium AD.” Netherlands Journal of Geosciences 96, e3.
DOI: 10.1017/njg.2017.910.1017/njg.2017.9

Dinter, M. et al. 2017, “Late Holocene lowland fluvial archives and geoarchaeology: Utrecht’s case study of Rhine river abandonment under Roman and Medieval settlement.” Geomorphology 295, 227–243.
DOI: 10.1016/j.geomorph.2017.07.01910.1016/j.geomorph.2017.07.019

Groenewoudt, B.J. & R.J. van Lanen 2018, “Diverging decline. Reconstructing and validating (post‑)Roman population trends (AD 0–1000) in the Rhine–Meuse delta (the Netherlands).” Journal of Archaeological Science: Reports 20, 189–218.
DOI: 10.1016/j.jasrep.2018.04.01010.1016/j.jasrep.2018.04.010

Book / volume contributions

These chapter‑type items do not all carry DOIs; the most stable references are to the publisher or widely archived PDFs.

Jansma, E. et al. 2015, “The dendrochronology of Dorestad: placing early‑medieval structural timbers in a wider geographical context.” In: [Second Dorestad Congress volume], Turnhout (Brepols). Stable publisher series entry (Brepols “Dorestad” volume; no DOI given in catalogues).

Jansma, E. et al. 2016, “The dendrochronology of Dorestad: placing early‑medieval structural timbers in a wider geographical context – New research into early‑medieval communities and identities.” In: New Research into Early‑Medieval Communities and Identities, Turnhout (Brepols). No DOI listed; use series/publisher catalogue record as stable reference.

Kosian, M.C. et al. 2016, “Dorestad’s rise and fall: how the local landscape influenced the growth, prosperity and disappearance of an early‑medieval emporium.” In: [Dorestad‑related volume], Turnhout (Brepols). No DOI listed; use Brepols volume record.

Van Lanen, R.J. et al. 2019, “Counting heads: Post‑Roman population decline in the Rhine–Meuse delta (the Netherlands) and the need for more evidence‑based reconstructions.” In: Ruralia XII, Leiden (Sidestone Press). Stable link:
https://www.sidestone.com/books/ruralia-xii

Other scientific outputs

Nooren, C.A.M. et al. 2018, “Is the onset of the 6th century ‘dark age’ in Maya history related to explosive volcanism?” Quaternary Science Reviews 186, 1–12.
DOI: 10.1016/j.quascirev.2018.02.01710.1016/j.quascirev.2018.02.017

Riechelmann, D. et al. 2016, “Climate during the Roman and early‑medieval periods in North‑western Europe: a review of climate reconstructions from terrestrial archives.” Listed by NWO as conference review; an abstract rather than a full paper and no DOI is given in the project or author bibliographies.

Hoek, W.Z. et al. 2016, “Climate and environmental changes during the last 2000 years on Barentsøya and Edgeøya (E‑Svalbard).” Conference / project‑related output; no DOI recorded in UU publication lists, only meeting abstract reference.

Bilt, W. van der et al. 2016, “Short‑lived high‑amplitude cooling on Svalbard during the Dark Ages.” This work appears in palaeoclimate literature; the Quaternary Science Reviews article corresponding to this topic has DOI 10.1016/j.quascirev.2016.11.00110.1016/j.quascirev.2016.11.001, which is the stable identifier generally cited for this result.

Groenewoudt, B.J., R.J. van Lanen & H.J. Pierik 2019, “Bevolkingsaantallen berekenen – Kan dat, op basis van archeologische gegevens?” Popular‑scientific article (Dutch) without DOI; stable as print/HTML in the cited outlet only.

[27] van Lanen, Rowin J., Menne C. Kosian, Bert J. Groenewoudt and Esther Jansma, Finding a Way: Modeling Landscape Prerequisites for Roman and Early-Medieval Routes in the Netherlands, Geoarchaeology: An International Journal 00 (2015) page 2 , https://www.academia.edu/11879781/Van_Lanen_et_al_2015_Finding_a_way_Modeling_Landscape_Prerequisites_for_Roman_and_Early_Medieval_Routes_in_the_Netherlands

[28] GIS (Geographic Information System) is a computer-based system that captures, stores, analyzes, manages, and displays all forms of geographically referenced data, essentially linking location (where things are) with descriptive information (what they are like) to reveal patterns, relationships, and trends on maps

Geographic information system, Wikipedia, This page was last edited on 25 December 2025, https://en.wikipedia.org/wiki/Geographic_information_system

Sexton, Pamela Ann, What is a geographic information system (GIS)?, USGS, https://www.usgs.gov/faqs/what-a-geographic-information-system-gis

[29] Schlanger, S.H.. Recognizing Persistent Places in Anasazi Settlement Systems, pages 91-112, In: Rossignol, J., Wandsnider, L. (eds) Space, Time, and Archaeological Landscapes. Interdisciplinary Contributions to Archaeology. Springer, Boston, MA. 1992, https://doi.org/10.1007/978-1-4899-2450-6_5

[30] Schlanger, S.H.. Recognizing Persistent Places in Anasazi Settlement Systems, pages 91-112, In: Rossignol, J., Wandsnider, L. (eds) Space, Time, and Archaeological Landscapes. Interdisciplinary Contributions to Archaeology. Springer, Boston, MA. 1992, https://doi.org/10.1007/978-1-4899-2450-6_5

[31] Van Lanen, Rowin and Menne Kosian, Bert J. Groenewoudt, Theo Spek, Esther Jansma, Best travel options: Modelling Roman and early-medieval routes in the Netherlands using a multi-proxy approach, Journal of Archaeological Science: Reports, 2015/09/30, VL – 3, DO – 10.1016/j.jasrep.2015.05.02,
https://www.researchgate.net/publication/278332983_Best_travel_options_Modelling_Roman_and_early-medieval_routes_in_the_Netherlands_using_a_multi-proxy_approach

What is GlobetrekkerTM

The Lowlands in the Dark Ages in ‘an Interdisciplinary Light’

The Research Program ‘Dark Ages in an Interdisciplinary Light‘

What Defines this Mutlidisciplinary Approach in Studying the Dark Ages in the Lowlands?

How the Methodological Approaches Associated with Globetrekker and Landscape Archaeology Compliment Each Other

From Generic Paths to Specific Corridors

Integrating Time, Scale, and Uncertainty

A Comparison of the Terms Used by Globetrekker and Landscape Archaeology

The Ability to Understand the Longue Durée of Genetic Migration through the Landscape Archaeological View

Sources:

What is Globetrekker^TM