https://dx.doi.org/10.1016/j.jasrep.2017.05.033">
 

Title

Analyzing landform patterns in the monumental landscape of the northern Great Lakes, 1200–1600 CE

Abstract

Monuments create permanent and predictable contexts and so they offered a particularly powerful way for past societies to reconfigure their landscapes in response to variable social and ecological factors. We examine the monumental landscape of the Late Precontact (ca. 1200–1600 CE) northern Great Lakes using a longstanding tool of landscape archaeology, Geographic Information Systems (GIS). In line with the growing recognition of the need to move beyond point-to-point GIS analyses to realize dynamic insights into past landscapes, we turned to multivariate total landscape geospatial modeling increasingly common in ecology. Specifically, we used a total landscape model of landforms—a compound, stable, and archaeologically relevant measure of landscape heterogeneity. We conducted a multi-scalar computation of Shannon's equitability to assess landform diversity in terms of both abundance and evenness and examined the positioning of monumental earthwork enclosures across north-central Michigan in relation to this measure. We found enclosures were non-randomly located in areas with high landform abundance and evenness, a nuanced positioning that patterned regionally but also relied on detailed, local socioecological knowledge. The positioning of earthwork enclosures in areas of increased landform diversity was one way indigenous communities crafted a monumental landscape to navigate the restricted social, economic, and ideological setting of Late Precontact (ca. 1200–1600 CE). Our study offers one example of the ways archaeologists can harness the power of geospatial technologies to gain insight into the variegated landscapes people inhabited in the past—places that were composed of ecology, other peoples, non-human beings and the constant flow of interactions between them.

Publication Date

6-1-2018

Journal Title

Journal of Archaeological Science: Reports

Publisher

Elsevier

Digital Object Identifier (DOI)

https://dx.doi.org/10.1016/j.jasrep.2017.05.033

Document Type

Article

Rights

© 2017 Elsevier Ltd. All rights reserved.

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