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Abstract Agriculture is one of the most fundamental ways in which human societies interact with the environment. The form and function of agriculture have important socio-political implications in terms of yields, labor requirements, variability and resilience, and elite control. Hawai‘i has been used as a model system for the discussion of coupled human and natural systems, and how the uneven distribution of agricultural opportunities has manifested in the political ecology. However, consideration of agriculture has emphasized forms with physical infrastructure documented through archaeology and have not included arboricultural forms that were extensive among Pacific Islands. We leverage existing, independent data sets to build and validate spatial models of two intensities of arboriculture across the Hawaiian archipelago: Agroforestry and Novel Forest. Model validation demonstrates good accuracy that includes both expected and unexpected sources of errors. Results of the models demonstrate that arboricultural techniques accounted for ~70% of the agricultural potential by area and ~40% of the agricultural potential by yield. Unlike existing agricultural forms modeled, such as flooded wetland terrace cultivation and rainfed field production, which have strong distributional patterns based on the age of the islands, arboricultural potential is well distributed across all the islands. The extent, distribution, and characteristics of arboricultural methods provide important augmentation of the current narrative of production dynamics and distribution, and the political ecology, of pre-contact Hawai‘i. 

Abstract 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 Stone and earthen architecture is nearly ubiquitous in the archaeological record of Pacific islands. The construction of this architecture is tied to a range of socio-political processes, and the temporal patterning of these features is useful for understanding the rate at which populations grew, innovation occurred, and social inequality emerged. Unfortunately, this temporal patterning is poorly understood for many areas of the region, including the Sāmoan archipelago. Here, we describe a project directed toward establishing a robust chronology for the construction of these earthen and stone terraces and linear mounds on Ta‘ū Island. Using recent methodological improvements, we highlight the tempo at which different architectural types were constructed on the island and the implications for understanding demographic expansion and changing land tenure practices in the last 1500 years. This research suggests the construction of architecture was largely confined to the 2nd millennium AD with a small number of terraces plausibly built in the 1st millennium AD. This temporal patterning suggests that a reconfiguration of settlement patterns occurred within West Polynesia as people there moved into other regions of Oceania.