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, 75 (4), 279-287

Using Stylized Agent-Based Models for Population-Environment Research: A Case Study From the Galápagos Islands

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Using Stylized Agent-Based Models for Population-Environment Research: A Case Study From the Galápagos Islands

Brian W Miller et al. Popul Environ.

Abstract

Agent Based Models (ABMs) are powerful tools for population-environment research but are subject to trade-offs between model complexity and abstraction. This study strikes a compromise between abstract and highly specified ABMs by designing a spatially explicit, stylized ABM and using it to explore policy scenarios in a setting that is facing substantial conservation and development challenges. Specifically, we present an ABM that reflects key Land Use / Land Cover (LULC) dynamics and livelihood decisions on Isabela Island in the Galápagos Archipelago of Ecuador. We implement the model using the NetLogo software platform, a free program that requires relatively little programming experience. The landscape is composed of a satellite-derived distribution of a problematic invasive species (common guava) and a stylized representation of the Galápagos National Park, the community of Puerto Villamil, the agricultural zone, and the marine area. The agent module is based on publicly available data and household interviews, and represents the primary livelihoods of the population in the Galápagos Islands - tourism, fisheries, and agriculture. We use the model to enact hypothetical agricultural subsidy scenarios aimed at controlling invasive guava and assess the resulting population and land cover dynamics. Findings suggest that spatially explicit, stylized ABMs have considerable utility, particularly during preliminary stages of research, as platforms for (1) sharpening conceptualizations of population-environment systems, (2) testing alternative scenarios, and (3) uncovering critical data gaps.

Figures

Fig. 1
Fig. 1
Map of the Galápagos Islands highlighting the study area on Isabela Island
Fig. 2
Fig. 2
Conceptual framework for modeling livelihood decisions and land use/land cover processes
Fig. 3
Fig. 3
Flowchart of the Isabela Livelihood and Land Use Model setup and operation. The shaded boxes indicate the sub-models that are illustrated in detail in Fig. 4
Fig. 4
Fig. 4
(a) Guava clearing and (b) livelihood choice sub-models. Livelihood options are limited by the availability of vacancies in the fishing and farming sectors, and switching is additionally constrained by a probabilistic control
Fig. 5
Fig. 5
Baseline model output for (a) the total and agricultural guava cover, and (b) the human population in each economic sector. Points designate the means of 1000 model runs for each time-step and lines designate the bounds of 95% of the values from these runs
Fig. 6
Fig. 6
Total guava cover (solid black symbols) and agricultural guava cover (hollow grey symbols) at time-step 50 under five separate reductions in the per hectare guava control cost (circles=$0; diamonds=$25; squares=$50; triangles=$75; points=$100). “Total Control Cost Subsidy (USD)” represents the sum of 50 years of subsidization

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