Conservation vs. Development in the Galápagos Islands, Ecuador: A Complex Systems Approach to the Study of Population-Environment Interactions in a Fragile Ecosystem

(A) PROJECT SUMMARY

The Galápagos Islands are part of the Republic of Ecuador, and are located in the Pacific Ocean approximately 1,000-km from mainland Ecuador. Nearly 97% of the total land area of the islands is designated as National Park, and the remaining 3% are a colonized zone with urban and farm areas. In the archipelago, three primary subsystems exist: Terrestrial Park, Marine Reserve, and Human Use Areas. These subsystems are interdependent, and any alteration of one subsystem has a profound effect on the others. Interactions among these sub-systems have immense consequences for resource conservation, development, and system dynamics. For instance, invasive plant species threaten native and endemic flora and fauna and cause a loss of biodiversity and ecological services, which are linked to human occupation, settlement patterns, farm abandonment, and alternate household livelihood strategies. Exotic species are, relative to the number of species they endanger, the least studied threat to biodiversity (Lawler et al. 2006). Our primary aim is to develop a data-informed, agent-based model that allows us to understand the implications of alternative conservation and development scenarios in the Galápagos Islands, with an emphasis on the three main populated islands of Santa Cruz, San Cristobal, and Isabela. To avoid having the model rest on rules and relationships that are not empirically grounded, there are additional specific aims to provide descriptive information on the (1) demographic system, (2) socio-economic system, (3) ecological system, and (4) the interrelationships and feedbacks among them. Complexity theory and Agent Based Models (ABMs) are used to integrate the endogenous and exogenous factors and their feedbacks among the three systems so that we can examine conservation vs. development scenarios. Complexity theory sees the complex nature of systems as emerging from nonlinearities due to interactions involving feedbacks occurring at lower levels of social and ecological organization within the system. ABMs are used to encompass the complex interactions within and among the ecological system, the physical system on which they depend, and the socio-economic systems with which they interact.

Intellectual Merit:

ABMs are used to improve our understanding of dynamic systems by considering the role of feedback mechanisms in the complex interplay between people and the environment. We integrate exogenous and endogenous drivers to represent a diverse set of forces and factors operating in the Galápagos Islands (i.e., demographic, socio-economic, and ecological systems) that together affect conservation and development in fundamental ways. Theoretically, we consider alternative approaches to population-environment interactions, including self-organized percolation, the inverse cascade model, an approach to complexity involving optimization, and highly optimized tolerance. In addition, human migration patterns, household livelihood strategies, and ecological dynamics, related to invasive plant species and biodiversity, are integrated to examine alternative scenarios of conservation vs. development.

Broader Impacts:

Environments throughout the world are besieged by the often competing agendas of conservation versus development. This project utilizes a set of integrated analytical and conceptual approaches to examine human-environment interactions within a spatially-explicit modeling environment. “What if” questions are posed and spatial simulations analyzed to consider plausible conservation vs. development scenarios. Our work has application to other geographic locales through questions that involve the complex interactions among people, place, and environment. Further, our work informs policy-makers and scientists about the role of spatially-explicit tools, approaches, and theories to link people and the environment in fragile ecosystems and through an integrated complex adaptive systems perspective.