Remote Sensing Reveals Lasting Legacies of Land-Use by Small-Scale Foraging Communities in the Southwestern Indian Ocean

Abstract

Archaeologists interested in the evolution of anthropogenic landscapes have productively adopted Niche Construction Theory (NCT), in order to assess long-term legacies of human-environment interactions. Applications of NCT have especially been used to elucidate co-evolutionary dynamics in agricultural and pastoral systems. Meanwhile, foraging and/or highly mobile small-scale communities, often thought of as less intensive in terms of land-use than agropastoral economies, have received less theoretical and analytical attention from a landscape perspective. Here we address this lacuna by contributing a novel remote sensing approach for investigating legacies of human-environment interaction on landscapes that have a long history of co-evolution with highly mobile foraging communities. Our study is centered on coastal southwest Madagascar, a region inhabited by foraging and fishing communities for close to two millennia. Despite significant environmental changes in southwest Madagascar’s environment following human settlement, including a wave of faunal extinctions, little is known about the scale, pace and nature of anthropogenic landscape modification. Archaeological deposits in this area generally bear ephemeral traces of past human activity and do not exhibit readily visible signatures of intensive land-use and landscape modification (e.g., agricultural modifications, monumental architecture, etc.). In this paper we use high-resolution satellite imagery and vegetative indices to reveal a legacy of human-landscape co-evolution by comparing the characteristics – vegetative productivity and geochemical properties – of archaeological sites to those of locations with no documented archaeological materials. Then, we use a random forest (RF) algorithm and spatial statistics to quantify the extent of archaeological activity and use this analysis to contextualize modern-day human-environment dynamics. Our results demonstrate that coastal foraging communities in southwest Madagascar over the past 1,000 years have extensively altered the landscape. Our study thus expands the temporal and spatial scales at which we can evaluate human-environment dynamics on Madagascar, providing new opportunities to study early periods of the island’s human history when mobile foraging communities were the dominant drivers of landscape change.

Influence of Late Holocene Climate Change and Human Land Use on Terrestrial and Aquatic Ecosystems in Southwest Madagascar

“…Results from this study suggest that the landscape transformation was the product of fire intensification, likely associated with the management of grasslands for introduced cattle (Bloesch, 1999;Kull, 2002;Davis and Douglass, 2021). High concentrations of charcoal particles are associated with the concomitant increase of Poaceae (∼65%) over time in the region.…”

Indigenous and Traditional Management Creates and Maintains the Diversity of Ecosystems of South American Tropical Savannas

“…The distribution of these practices among different human cultures is maintained today, and this may be related to the fact that humans, when successful niche constructors, inherit from their ancestors information about how to manage these environments, thus favoring more than one generation (Smith, 2011;Albuquerque et al, 2015;Coca et al, 2021). This makes explicit one of the principles of NCT, relocation, which affirms that practices can migrate with constructing organisms and be adopted by other populations when they meet in time and space (Davis and Douglass, 2021). Moreover, these common practices refute one of the current criticisms of NCT, because they are not merely singular human behaviors but behaviors that are regularly repeated at the population level (Spengler, 2021).…”

“…Domesticated landscapes are created by the conscious and unconscious processes of manipulating ecosystems and the plants that compose them, resulting in more productive environments suitable for humans (Terrell et al, 2003;Casas et al, 2017;Hecht, 2017;Clement et al, 2021). This feedback between practice and result is one of the differentials of NCT (Matthews et al, 2014;Huebert and Allen, 2020;Davis and Douglass, 2021).…”

Exploring the role of ecology and social organisation in agropastoral societies: A Bayesian network approach

“…This method has been previously applied in other research studies for designing conceptual models [ 55 , 56 ] but not as the machine learning method that it really is (at least that the authors are aware of). Other studies that have explored past socio-ecological systems from the machine learning approach have employed other algorithms, such as logistic regression [ 57 ], deep learning [ 58 ], support vector machine [ 19 ], random forest [ 59 ] or combined some of these algorithms [ 18 , 60 ].…”