Human settlement of the Caribbean represents the only example in the Americas of peoples colonizing islands that were not visible from surrounding mainland areas or other islands. Unfortunately, many interpretive models have relied on radiocarbon determinations that do not meet standard criteria for reporting because they lack critical information or sufficient provenience, often leading to specious interpretations. We have collated 2484 radiocarbon determinations, assigned them to classes based on chronometric hygiene criteria, and constructed Bayesian colonization models of the acceptable determinations to examine patterns of initial settlement. Colonization estimates for 26 islands indicate that (i) the region was settled in two major population dispersals that likely originated from South America; (ii) colonists reached islands in the northern Antilles before the southern islands; and (iii) the results support the southward route hypothesis and refute the “stepping-stone model.”
Explaining the processes underlying the emergence of monument construction is a major theme in contemporary anthropological archaeology, and recent studies have employed spatially-explicit modeling to explain these patterns. Rapa Nui (Easter Island, Chile) is famous for its elaborate ritual architecture, particularly numerous monumental platforms (ahu) and statuary (moai). To date, however, we lack explicit modeling to explain spatial and temporal aspects of monument construction. Here, we use spatially-explicit point-process modeling to explore the potential relations between ahu construction locations and subsistence resources, namely, rock mulch agricultural gardens, marine resources, and freshwater sources—the three most critical resources on Rapa Nui. Through these analyses, we demonstrate the central importance of coastal freshwater seeps for precontact populations. Our results suggest that ahu locations are most parsimoniously explained by distance from freshwater sources, in particular coastal seeps, with important implications for community formation and inter-community competition in precontact times.
Rapa Nui (Easter Island, Chile) presents a quintessential case where the tempo of investment in monumentality is central to debates regarding societal collapse, with the common narrative positing that statue platform (ahu) construction ceased sometime around AD 1600 following an ecological, cultural, and demographic catastrophe. This narrative remains especially popular in fields outside archaeology that treat collapse as historical fact and use Rapa Nui as a model for collapse more generally. Resolving the tempo of "collapse" events, however, is often fraught with ambiguity given a lack of formal modeling, uncritical use of radiocarbon estimates, and inattention to information embedded in stratigraphic features. Here, we use a Bayesian model-based approach to examine the tempo of events associated with arguments about collapse on Rapa Nui. We integrate radiocarbon dates, relative architectural stratigraphy, and ethnohistoric accounts to quantify the onset, rate, and end of monument construction as a means of testing the collapse hypothesis. We demonstrate that ahu construction began soon after colonization and increased rapidly, sometime between the early-14th and mid-15th centuries AD, with a steady rate of construction events that continued beyond European contact in 1722. Our results demonstrate a lack of evidence for a pre-contact 'collapse' and instead offer strong support for a new emerging model of resilient communities that continued their long-term traditions despite the impacts of European arrival. Methodologically, our model-based approach to testing hypotheses regarding the chronology of collapse can be extended to other case studies around the world where similar debates remain difficult to resolve.
Landscape archaeology has a long history of using predictive models to improve our knowledge of extant archaeological features around the world. Important advancements in spatial statistics, however, have been slow to enter archaeological predictive modeling. Point process models (PPMs), in particular, offer a powerful solution to explicitly model both first- and second-order properties of a point pattern. Here, we use PPMs to refine a recently developed remote sensing-based predictive algorithm applied to the archaeological record of Madagascar’s southwestern coast. This initial remote sensing model resulted in an 80% true positive rate, rapidly expanding our understanding of the archaeological record of this region. Despite the model’s success rate, it yielded a substantial number (~20%) of false positive results. In this paper, we develop a series of PPMs to improve the accuracy of this model in predicting the location of archaeological deposits in southwest Madagascar. We illustrate how PPMs, traditional ecological knowledge, remote sensing, and fieldwork can be used iteratively to improve the accuracy of predictive models and enhance interpretations of the archaeological record. We use an explicit behavioral ecology theoretical framework to formulate and test hypotheses utilizing spatial modeling methods. Our modeling process can be replicated by archaeologists around the world to assist in fieldwork logistics and planning.
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