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"Over the last decades, Roman wood in various shapes and sizes has been excavated in the region of the continental north-western provinces of the Roman empire. However, it is often unclear whether wood has been transported. Most dendrochronological provenance studies rely on simple comparisons between tree-ring series based on a single similarity measure. In addition, most fail to consider the complex system of relations that is the result of the variables that influence tree-ring patterns. Network analysis is a solution to this problem, because it allows to both visualize and analyze the complex (provenance) relations of tree-ring series as a whole. A network makes it impossible to ignore existing (statistical) relations between tree-ring series. Although networks can be build using any (combination of) similarity measure(s), in this study a combination of the Synchronous Growth Changes (SGC), its related probability of exceedance (p), correlation (r) and overlap define the edges. This paper focusses on networks with site chronologies as nodes, although networks can also be constructed using individual tree-ring series or a combination with site chronologies. A combination of these can also help to refine the (archaeological) interpretation. The location of any tree-ring series in a network reflects its provenance. Material that is placed closer together in the network has similar growth patterns and is generally from the same region. Therefore, network communities reflect wood that has a similar provenance. If tree-ring material was found on different spatial locations, but in close proximity in the network, this indicates that wood has been moved. To determine which wood has been transported, a combination of archaeological and spatial arguments is used. The method is sound, simple and gives insight in the complexity of all tree-ring relations in a simple diagram. The resulting patterns show that most wood was obtained in the region where it was used, but that transport of wood in the Roman period did take place. Three scales are defined to describe the Roman wood economy: local, provincial and imperial. While transport of wood over long distances is attested for both military and civilian sites (provincial and imperial scale), it seems that wood that was transported beyond the provincial borders was only used in civilian sites (imperial scale). The combination of network science, dendrochronology and archaeology is a powerful method to understand patterns in the Roman timber economy."
From https://journal.caa-international.org/articles/10.5334/jcaa.79#additional-file
Construction
"Networks were created with dendrochronological material as nodes and the edges defined by a combination of noverlap, r, SGC and p of the pair-wise comparison of the dendrochronological material. These were stored in the database and selected for network creation. Since all relations are reciprocal the network is undirected, and duplicate edges have been removed. The networks were created using various levels of testing (as defined by Daly 2007b), resulting in nodes as: Site chronologies, Site chronologies and trees, Trees"
"In this paper I will focus on the network of the first level of testing, with each node representing a single site chronology. The edges are based on the comparison of both the C and M chronologies. The other levels are often needed for the (archaeological) interpretation of the network. Initially the edges were selected from the database using r ≥ 0,5, SGC ≥ 70% with p ≤ 0,0001 and noverlap ≥ 50 for each pair-wise comparison. Previous research has shown that wood from the same region often show similarities well above these values (Visser 2006; Vorst 2005). To test these values the combination of thresholds for creating edges was varied, leading to four network-types:
r ≥ 0,5, SGC ≥ 70% with p ≤ 0,0001 and noverlap ≥ 50; r ≥ 0,5, SGC ≥ 70% and noverlap ≥ 50; r ≥ 0,5, any SGC with p ≤ 0,0001 and noverlap ≥ 50; A merged network of 2 and 3. The resulting networks are described using standard variables, such as the number of nodes (N), the number of edges (E), the number of components and the diameter of the network (δ). The average degree (K) describes the degree to which the nodes in the network are connected"
https://dataverse.nl/dataverse/dccd