Publication Date

8-2023

Date of Final Oral Examination (Defense)

6-20-2023

Type of Culminating Activity

Dissertation

Degree Title

Doctor of Philosophy in Ecology, Evolution, and Behavior

Department

Biology

Major Advisor

Vicken Hillis, Ph.D.

Advisor

Matthew A. Williamson, Ph.D.

Advisor

Kelly Hopping, Ph.D.

Advisor

Kathryn E. Demps, Ph.D.

Abstract

This body of work leverages a variety of quantitative and theoretical approaches to advance our understanding of why individuals adopt community-based conservation behaviors, the impacts those decisions have on natural resources and human wellbeing, and how these insights can be used for practical conservation planning. The first chapter makes a theoretical contribution by fitting data produced from a stylized, agent-based simulation of conservation adoption over time with a set of probabilistic differential equations derived from the theory of diffusion of innovations and cultural evolutionary theory broadly. We use these methods to demonstrate that such a statistical approach can provide accurate inference and prediction around the rates and degree of behavioral adoption within a population even when behavioral uptake is contingent on dynamic feedback processes between human behavior, social learning, and environmental change. The second chapter introduces approximate Bayesian computation as a method for linking hypothesized causal processes in complex land systems with observed changes in the mosaic of land cover. This chapter uses the small-scale agricultural production system in Pemba Island, Tanzania as a case study, identifying that soil degradation is likely the primary driver of agricultural expansion into nearby coral rag forests. The third chapter relies on an extensive data collection campaign in 43 communities across Pemba to measure individuals’ perceptions of mangrove cover change and risk of mangrove theft, and to assess their impact on individuals’ conservation behaviors and preferences. The results of this study indicate that perceptions of mangrove decline drive individual adoption of conservation behaviors and preferences only if they believe that the resultant gains in mangrove cover will not be stolen by outsiders. Conversely, individuals who believe their community mangrove forests are at high risk of theft actually decrease their support for forest conservation in response to perceived forest decline. Lastly, the fourth chapter explores the alignment and misalignment between individual perceptions of mangrove cover change in Pemba and remotely sensed observations of cover change over the same time period. We qualitatively examine the reasons for mismatches in the two data sources and propose a numerical optimization method for considering both sources of information in systematic conservation planning. Together, these studies contribute to the advancement of both theory and methods in studying human behavior within complex social-ecological systems, primarily in small-scale fishing and agricultural communities. Overall, the research presented underscores the importance of understanding human behavior for effectively implementing conservation strategies, and provides valuable insights for informing future conservation planning and interventions.

DOI

https://doi.org/10.18122/td.2099.boisestate

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