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Palaeoenvironmental data indicate that the climate of south-western Madagascar has changed repeatedly over the past millennium. Combined with sociopolitical challenges such as warfare and slave raiding, communities continually had to mitigate against risk. Here, the authors apply social network analysis to pottery assemblages from sites on the Velondriake coast to identify intercommunity connectivity and changes over time. The results indicate both continuity of densely connected networks and change in their spatial extent and structure. These network shifts coincided with periods of socio-political and environmental perturbation attested in palaeoclimate data and oral histories. Communities responded to socio-political and environmental risk by reconfiguring social connections and migrating to areas of greater resource availability or political security. Keywords: Madagascar, Velondriake, settlement patterns, social network analysis, ceramics, mobility, risk, Introduction As the contemporary climate crisis intensifies, deepening our understanding of the interactions between climate and human social networks is increasingly important (Pisor & Jones 2021). Environmental archaeologists have, for [...]

Many communities in southwestern Madagascar rely on a mix of foraging, fishing, farming, and herding, with cattle central to local cultures, rituals, and intergenerational wealth transfer. Today these livelihoods are critically threatened by the intensifying effects of climate change and biodiversity loss. Improved understanding of ancient community-environment dynamics can help identify pathways to livelihood sustainability. Multidisciplinary approaches have great potential to improve our understanding of human-environment interactions across spatio-temporal scales. We combine archaeological survey data, oral history interviews, and high-resolution multispectral PlanetScope imagery to explore 400 years of human-environment interaction in the Namonte Basin. Our analysis reveals that settlement and land-use led to significant changes in the region's ecology, both during periods of occupation and after settlement abandonment. Human activity over this period may have stabilized vegetative systems, whereby seasonal changes in vegetative health were reduced compared to surrounding locations. These ecological legacies may have buffered communities against unpredictable climate challenges. [ABSTRACT FROM AUTHOR]

This rapid communication describes a lithic blade that was recently recovered during excavations in the Velondriake Marine Protected Area in southwest Madagascar. This represents the only recorded archaeological lithic blade recovered from southwest Madagascar. The blade was recovered in situ at a depth of 1.66 m, a deposit dating to between 750 and 1200 BP at site G134, adjacent to the modern village of Antsaragnasoa. While similar in material choice (translucent-brown chert) and morphology (parallel-sided blade) to other lithics recovered at the northern sites of Ambohiposa and Lakaton'i Anja, it is significantly larger than other recorded lithics on Madagascar. More research is required but this finding suggests that lithic technology may have been more widespread on the island, particularly among coastal communities, than previously thought. [ABSTRACT FROM AUTHOR]

Communities in resource-poor areas face health, food production, sustainability, and overall survival challenges. Consequently, they are commonly featured in global debates surrounding societal collapse. Rapa Nui (Easter Island) is often used as an example of how overexploitation of limited resources resulted in a catastrophic population collapse. A vital component of this narrative is that the rapid rise and fall of pre-contact Rapanui population growth rates was driven by the construction and overexploitation of once extensive rock gardens. However, the extent of island-wide rock gardening, while key for understanding food systems and demography, must be better understood. Here, we use shortwave infrared (SWIR) satellite imagery and machine learning to generate an islandwide estimate of rock gardening and reevaluate previous population size models for Rapa Nui. We show that the extent of this agricultural infrastructure is substantially less than previously claimed and likely could not have supported the large population sizes that have been assumed. [ABSTRACT FROM AUTHOR]

Critical data concerning key developments in global human history now lie submerged on continental shelves where investigations confront significant challenges. Whereas underwater excavations and surveys are expensive and weather dependent and require specialized training and equipment, remote sensing methods can improve chances for success offshore. A refinement in one method, a semi‐automated analysis protocol that can help to identify Pleistocene and Holocene era archaeological deposits in bathymetric LiDAR datasets, is presented here. This method employs contour mapping to identify potential archaeological features in shallow water environments in Apalachee Bay, Florida. This method successfully re‐identified multiple previously recorded archaeological sites in the study region and detected at least four previously undocumented archaeological sites. These results suggest that this procedure can expand on methods to identify and record submerged archaeological deposits in sediment‐starved, shallow‐water environments. [ABSTRACT FROM AUTHOR]

Lidar datasets have been crucial for documenting the scale and nature of human ecosystem engineering and land use. Automated analysis methods, which have been rising in popularity and efficiency, allow for systematic evaluations of vast landscapes. Here, we use a Mask R‐CNN deep learning model to evaluate terracing—artificially flattened areas surrounded by steeper slopes—on islands in American Sāmoa. Mask R‐CNN is notable for its ability to simultaneously perform detection and segmentation tasks related to object recognition, thereby providing robust datasets of both geographic locations of terracing features and their spatial morphometry. Using training datasets from across American Sāmoa, we train this model to recognize terracing features and then apply it to the island of Tutuila to undertake an island‐wide survey for terrace locations, distributions and morphologies. We demonstrate that this model is effective (F1 = 0.718), but limitations are also documented that relate to the quality of the lidar data and the size of terracing features. Our data show that the islands of American Sāmoa display shared patterns of terracing, but the nature of these patterns are distinct on Tutuila compared with the Manu'a island group. These patterns speak to the different interior configurations of the islands. This study demonstrates how deep learning provides a better understanding of landscape construction and behavioural patterning on Tutuila and has the capacity to expand our understanding of these processes on other islands beyond our case study. [ABSTRACT FROM AUTHOR]

Climate change and anthropogenic activities are actively destroying the archaeological record. The dramatic disappearance of archaeological landscapes becomes particularly problematic when they are also unrecorded. Hidden from view and eroding, these disappearing landscapes likely hold answers to important anthropological questions. As such, disappearing landscapes present a major challenge for twenty-first century archaeology. Left unchecked, this phenomenon will increase the severity of bias in our knowledge of the past. In this paper we use a case study from Pinckney Island in the American Southeast to illustrate how the problem of hidden and disappearing landscapes can be addressed through multi-scalar surveys. Specifically, by combining aerial LiDAR, pedestrian survey, and micro-artifact approaches, the identification of hidden and disappearing cultural materials (including permanent settlements and ephemeral artifact scatters) can be alleviated. [ABSTRACT FROM AUTHOR]

Environmental archaeological enquiry has a long and vibrant history. Many of the same questions have persisted in archaeological dialogues over the past century. In particular, the effects of environmental change on demographic patterns, health, and societal stability are among the most pervasive questions being addressed by anthropological research. These studies have limitations, however. For example, evaluations of the complex relationships between environmental variables and human responses are only just beginning to emerge in anthropological literature. This goal requires high-resolution paleoclimate datasets and the use of quantitative modelling rooted in evolutionary and complex systems theory. This paper serves as a broad review of advances in environmental archaeological enquiry associated with environmental change and human response. I argue that the future of archaeological questions concerning human-environmental connection requires a re-evaluation of causality and the incorporation of complex systems approaches to address human responses to external pressures. [ABSTRACT FROM AUTHOR]

The study of precontact anthropogenic mounded features—earthen mounds, shell heaps, and shell rings—in the American Southeast is stymied by the spotty distribution of systematic surveys across the region. Many extant, yet unidentified, archaeological mound features continue to evade detection due to the heavily forested canopies that occupy large areas of the region, making pedestrian surveys difficult and preventing aerial observation. Object-based image analysis (OBIA) is a tool for analyzing light and radar (lidar) data and offers an inexpensive opportunity to address this challenge. Using publicly available lidar data from Beaufort County, South Carolina, and an OBIA approach that incorporates morphometric classification and statistical template matching, we systematically identify over 160 previously undetected mound features. This result improves our overall knowledge of settlement patterns by providing systematic knowledge about past landscapes. [ABSTRACT FROM AUTHOR]

Object‐based image analysis (OBIA) is a method of assessing remote sensing data that uses morphometric and spectral parameters simultaneously to identify features in remote sensing imagery. Over the past 10–15 years, OBIA methods have been introduced to detect archaeological features. Improvements in accuracy have been attained by using a greater number of morphometric variables and multiple scales of analysis. This article highlights the developments that have occurred in the application of OBIA within archaeology and argues that OBIA is both a useful and necessary tool for archaeological research. Additionally, I discuss future research paths using this method. Some of the suggestions put forth here include: pushing for multifaceted research designs utilizing OBIA and manual interpretation, using OBIA methods for directly studying landscape settlement patterns, and increasing data sharing of methods between researchers. [ABSTRACT FROM AUTHOR]