A Bayesian Analysis of Landscape Disturbance and the Ecosystem Enhancement of Q'eqchi' Maya Swidden Agriculture
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Publisher:The Ohio State University
Series/Report no.:The Ohio State University. Department of Anthropology Honors Theses; 2021
In this paper we ask whether forest clearing patterns and the regrowth associated with swidden cultivation exhibits patterns of disturbance that enhance ecosystem productivity. Analyzing high-resolution, multispectral imagery and ground-truthed data collected in 2018 from two villages in southern Belize, we test the Intermediate Disturbance Hypothesis (IDH) by relating spatial metrics of landscape fragmentation to diversity and abundance of tree species. The analysis workflow outlined in this paper makes use of high-performance computing (HPC) to overcome constraints of scale, data size, and algorithmic complexity. This effectively cuts the time to process data and produce statistical results by two orders of magnitude, enabling us to use more complex algorithms, to analyze larger high-precision datasets, and to rapidly iterate our analyses. Preliminary modeling results produced by this analysis qualitatively reveal significant differentiation between anthropogenic disturbances expanding from the village centers and the primary forest and provide tentative quantitative support for the claim that Q'eqchi' forest clearing and swidden cultivation enhances forest biodiversity in southern Belize, especially at large spatial scales of analysis.
Academic Major: Data Analytics
Funded by the National Science Foundation (NSF#1818597, NSF#1553875).
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