Social-ecological simulation in a indigenous land - ABM simulation of sustainability in Guyana
Research Background
Understanding pathways to environmental sustainability in tropical regions is a priority for conservation and development policies. Because drivers of environmental degradation often occur simultaneously, a holistic approach is needed. We analyzed environmental degradation on demarcated indigenous lands in Guyana, using a spatially explicit, agent-based simulation model representing human livelihoods, forest dynamics, and animal metapopulations.
Indigenous people of the Rupununi region of Amazonian Guyana interact with their natural environment through hunting and subsistence agriculture. To date the sustainability of indigenous livelihoods has been analyzed by modeling either hunting or forest clearing. Team of scientits, led by Prof Jose Fragoso, have collected extensive social and ecological dataset for 5 years (Luzar et al., 2011). Tak also conducted fieldwork to understand land-use practices in these communities.
Here we develop a holistic model framework with agent-based modeling (ABM) to examine interactions between demographic growth, hunting, subsistence agriculture, land cover change, and animal population in the Rupununi. We examined four plausible drivers of ecological degradation: conversion of land for agro–industrial use, erosion of hunting and dietary taboos, reduction in child mortality rates, and introduction of external food resources.
Research Objectives
We developed an agent-based model (ABM) in NetLogo using extensive datasets from over 9,000 individuals across 23 villages in the region. Each village was also characterized with land-cover maps derived from remote sensing. The simulations begin at the location of a given village, but prior to human settlement—meaning landscapes are initially pristine forests with maximum possible animal populations, as inferred from the most plausible ecological assumptions. Unknown parameters were calibrated through internal validation, using current observations of human population size, land-cover extent, and animal abundance. In this framework, we assumed that present-day human populations represent a social–ecological equilibrium, and thus focused on villages with more than 50 years of history and minimal external connections.
Results
We examined four plausible drivers of ecological degradation: conversion of land for agro–industrial use, erosion of hunting and dietary taboos, reduction in child mortality rates, and introduction of external food resources. Although social–ecological systems were resilient to internal changes, the introduction of external food resources resulted in large fluctuations in the system, leading to a deterioration in environmental sustainability. Our simulation model also revealed unexpected linkages within the system; for example, population growth rates of non-human animal species were related to the sustainability of human livelihoods. We highlight the value of simulation models as social–ecological experiments that can synthesize interdisciplinary knowledge bases and support policy development.
