This thesis examined the complex socio-ecological dynamics in the Brazilian Amazon, focusing on the mechanisms that allow Amazonians to access natural resources along the gradient of urbanization. While Amazonian conservation and development policies have traditionally targeted rural areas, there is a growing need to consider the interconnectedness between urban, peri-urban (i.e. the area surrounding the urban center) and rural communities as the region urbanizes. The overall research question that guided this thesis research was "How does urbanization affect access to natural resources and how does access affect natural resource use?". We aimed to address key aspects of these relationships and the implications for sustainable development and conservation efforts. The first chapter explored the mechanisms by which rural, peri-urban, and urban populations in the Amazon access natural resources, focusing on the varied resources they use as food. Using the Theory of Access' framework and 33 semi-structured interviews with participants selected by snowball sampling in Manaus and Carauari (Amazonas, Brazil), we identified physical, knowledge, structural, social, and rights-based mechanisms as key to understanding resource access. The findings indicate that materiality (i.e. the presence and quality of a given resource), and knowledge were salient for rural and peri-urban people, who live in close proximity to natural resources, to establish access. Technology, such as mobile phones and internet access, further facilitated exchanges across the urbanization gradient. We also found out that the combination of mobility and social relations resulted in greater access to natural resources for those not living in physical proximity to such resources, for those not recognized as legitimate users, or for those that do not know how to extract natural resources. Across the gradient, people made use of social mechanisms and power to reinforce reciprocity among peers and access food. This study contributed to the advancement of the Access Theory by highlighting that people holding power, because of customary, social, institutional, political, and commercial power, accessed or controlled other people's access to natural resources, despite of legal constraints. By extending the notion of access to natural resources as bundles of diverse structural, knowledge, social, power, and rights-based mechanisms, novel policies can be designed to foster sustainable resource use while addressing power disparities for the development of the Brazilian Amazon. The second chapter examined the prevalence and quantity of wildmeat consumption, barter trade, and monetary trade across rural, peri-urban, and urban areas in the Brazilian Amazon. Through an indirect questioning technique, we surveyed 782 randomly selected households in Manaus and Carauari. We revealed substantial wildlife use throughout the urbanization gradient. In urban households, the rates of wildlife consumption, barter trade, and sale are significant (Manaus: 22%, 17%, 21%; Carauari: 57%, 30%, 7%, respectively), with higher market access in Manaus, the big city. Additionally, we found that wildlife trade occurred in both urban areas assessed, with an estimate of 21% (7-34%: Carauari) and 16% (6-26%: Manaus) of urban households trading wildmeat. Participation of peri-urban households in wildlife trade was high, especially close to Manaus. Results point to a need for inclusive wildlife policies, which regulate subsistence hunting, integrate fish and wildlife management within community-based conservation, implement measures to curtail illegal trade, and promote urban-rural development strategies. Together, these chapters highlight the importance of a collaborative and inclusive approach to conservation in the Amazon, recognizing the interconnectedness of rural and urban communities. To foster sustainable development, conservation strategies must prioritize equitable access to natural resources and promote the active participation of rural, peri-urban and urban inhabitants in shaping conservation outcomes. / Master of Science / In this study, we examined how people in the Brazilian Amazon access natural resources. Imagine living in a place with rich rainforests, rivers, and unique animals. Immersed in this forest matrix are one big city and several small towns where people have markets to obtain their food, commute to work and school in crowded roads, use mobile technologies such as internet and mobile banking. In this thesis, we studied how Amazonian people in different places get the food they eat, like animals, fish, açaí berries, and Brazil nuts. In order to do so, we asked people living in the rural and highly forested areas, in the areas within and around a small town, Carauari, and one big city, Manaus, how they were able to obtain these foods. We divided this study in two chapters, which are presented below: Chapter 1: How people obtain natural resources We talked to people in different parts of the Amazon, from rural villages to a big city, to understand how they get access to natural resources as food. We found that people who live close to the resources, such as those in the rural areas, can easily collect food. Others use their knowledge and social connections, sharing food with friends, family, and people they trust. Technology, such as mobile phones and the internet, also helps them exchange resources. People frequently move among the countryside and the city to access natural resources. Influential individuals, such as politicians, environmental agents, and merchants, can get natural resources whenever they want or easily control what others can access. Our findings highlight the importance of social relations, power, and technology in accessing natural resources and suggest new policies to promote fair and sustainable use in the Amazon. Chapter 2: Wildlife in the big city, in the small town, and in the rural areas We also looked at the amount of wild meat from birds, mammals, and river turtles and tortoises that people consumed, sold, or exchanged with others. Around a quarter of families in the big city, Manaus, and more than half of the families in the small town of Carauari consumed wild meat. We also found that they may share or sell them, especially in the surrounding areas of the big city, where the amount of people demanding wild meat can be high. This can be a problem for wildlife and for people if there is not enough meat for everyone to eat, share or trade. So, to create a sustainable pathway for wildlife and people, we suggested conservation policies that: promote the inclusion of city people in sustainable plans for wildlife, make the use of people's contribution in strategies to protect wildlife, and that ensure that everyone has what to eat as an ally of wildlife conservation. Conclusion: Working together for the Amazon Conserving the Amazon rainforest is a team effort. Rural and city communities are connected, and we must share resources fairly. By doing this, we can help the Amazon thrive while taking care of its people.

Economic changes such as rising açaí prices and the availability of off-farm employment are transforming the landscape of the Amazonian várzea, subject to decision-making at the farming household level. Land use change results from complex human-environment interactions which can be addressed by an agent-based model. An agent-based model is a simulation model composed of autonomous interacting entities known as agents, built from the bottom-up. Coupled with cellular automata, which forms the agents’ environment, agent-based models are becoming an important tool of land use science, complementing traditional methods of induction and deduction. The decision-making methods employed by agent-based models in recent years have included optimization, imitation, heuristics, classifier systems and genetic algorithms, among others, but multiple methods have rarely been comparatively analyzed. A modular agent-based model is designed to allow the researcher to substitute alternative decision-making methods. For a smallholder farming community in Marajó Island near Ponta de Pedras, Pará, Brazil, 21 households are simulated over a 40-year period. In three major scenarios of increasing complexity, these households first face an environment where goods sell at a constant price throughout the simulated period and there are no outside employment opportunities. This is followed by a scenario of variable prices based on empirical data. The third scenario combines variable prices with limited employment opportunities, creating multi-sited households as members emigrate. In each scenario, populations of optimizing agents and heuristic agents are analyzed in parallel. While optimizing agents allocate land cells to maximize revenue using linear programming, fast and frugal heuristic agents use decision trees to quickly pare down feasible solutions and probabilistically select between alternatives weighted by expected revenue. Using distributed computing, the model is run through several parameter sweeps and results are recorded to a cenral database. Land use trajectories and sensitivity analyses highlight the relative biases of each decision-making method and illustrate cases where alternative methods lead to significantly divergent outcomes. A hybrid approach is recommended, employing alternative decision-making methods in parallel to illustrate inefficiencies exogenous and endogenous to the decision-maker, or allowing agents to select among multiple methods to mitigate bias and best represent their real-world analogues.

Economic changes such as rising açaí prices and the availability of off-farm employment are transforming the landscape of the Amazonian várzea, subject to decision-making at the farming household level. Land use change results from complex human-environment interactions which can be addressed by an agent-based model. An agent-based model is a simulation model composed of autonomous interacting entities known as agents, built from the bottom-up. Coupled with cellular automata, which forms the agents’ environment, agent-based models are becoming an important tool of land use science, complementing traditional methods of induction and deduction. The decision-making methods employed by agent-based models in recent years have included optimization, imitation, heuristics, classifier systems and genetic algorithms, among others, but multiple methods have rarely been comparatively analyzed. A modular agent-based model is designed to allow the researcher to substitute alternative decision-making methods. For a smallholder farming community in Marajó Island near Ponta de Pedras, Pará, Brazil, 21 households are simulated over a 40-year period. In three major scenarios of increasing complexity, these households first face an environment where goods sell at a constant price throughout the simulated period and there are no outside employment opportunities. This is followed by a scenario of variable prices based on empirical data. The third scenario combines variable prices with limited employment opportunities, creating multi-sited households as members emigrate. In each scenario, populations of optimizing agents and heuristic agents are analyzed in parallel. While optimizing agents allocate land cells to maximize revenue using linear programming, fast and frugal heuristic agents use decision trees to quickly pare down feasible solutions and probabilistically select between alternatives weighted by expected revenue. Using distributed computing, the model is run through several parameter sweeps and results are recorded to a cenral database. Land use trajectories and sensitivity analyses highlight the relative biases of each decision-making method and illustrate cases where alternative methods lead to significantly divergent outcomes. A hybrid approach is recommended, employing alternative decision-making methods in parallel to illustrate inefficiencies exogenous and endogenous to the decision-maker, or allowing agents to select among multiple methods to mitigate bias and best represent their real-world analogues.