Words wield immense power. They help to shape realities, tell stories, and encompass deeper values and intentions on behalf of their users. Buzzwords are imprecise, trendy – and often-frustrating – words that are encountered in daily life. They frame problems, evoke emotional responses, and signal moral values. In this dissertation, I study buzzword use within the field of environmental conservation to better untangle the inherent tension they have long produced: do buzzwords help or hurt collective conservation efforts? Using a mixed methods approach, this dissertation provides descriptive and causal empirical evidence on many of the untested assumptions regarding the behavior, use, and impacts of buzzwords on conservation decision making. First, through a series of expert interviews with conservation professionals, I develop an empirically informed definition and understanding of buzzwords that builds upon the scholarly literature. It identifies eight defining characteristics, elaborates on the nuances of their use, life cycle, and context dependence, and sets forth a series of testable hypotheses on the relationship between buzzwords, trust, and perceptions. Second, I take this empirically informed understanding and employ a large-scale text analysis to interrogate the mainstream conservation discourse. I produce a list of buzzwords used across institutions (e.g., academia, NGOs) in the past five years and link them to predominant conservation frames, comparing the ways in which different institutions relate to and discuss conservation concepts. This analysis validates many long-held paradigms and ubiquitous buzzwords found in conservation such as sustainability and biodiversity, while identifying a more recently emerging framing of inclusive conservation. Third, I experimentally test a set of hypotheses on the effects that buzzwords have on decision making, as moderated through trust. This study finds evidence of a greenwashing effect, whereby buzzwords may produce marginal benefits to less trustworthy organizations through increases in credibility and group identity alignment, but do not outweigh the benefits of being trustworthy in the first place. In the face of many current global challenges requiring cooperation and collective action – such as climate change and environmental degradation – it is imperative to better understand the ways in which communication and framing (including buzzwords) influence decision making.

Coffee leaf rust (CLR) is an aggressive disease that has caused devastating production losses around the world. While coffee productivity under shade conditions has been simulated in sufficient detail, explicit modeling of the interactions between shading levels, microclimate, coffee plant physiology, and CLR progression remains largely unexplored, despite the recognized influence of shade on CLR epidemics. This dissertation introduces a new model, SpatialRust, as an initial approximation to an integrative simulation framework where farm design and management strategies can be linked to coffee production and CLR epidemic outcomes. SpatialRust considers stylized processes describing the dynamics of shade trees, coffee plants, and CLR and their interactions within a spatially explicit context. The dissertation then presents three experiments conducted using SpatialRust simulations. The first experiment investigates the role of shading as a mitigation tool for CLR outbreaks. It demonstrates that shade can effectively mitigate CLR epidemics when the conditions are otherwise conducive to a major CLR epidemic. Additionally, the experiment reveals complex effects of different shade management approaches, underscoring the potential value of future empirical studies that consider temporal and spatial shade dynamics in relation to CLR outcomes. The second experiment focuses on the financial balance of farms and examines how farmer preferences and needs influence farm management strategies. The findings indicate that incorporating CLR mitigation as part of the strategy's goals leads to positive long-term farm performance, even when planning for the short term. In the third experiment, the scope of the simulations is expanded to include neighboring coffee farms. The results demonstrate that the strategies adopted by immediate neighbors can affect the performance of individual farms, emphasizing the importance of considering the broader coffee-growing landscape context. This work shows that the integration of farm management practices and the resulting shading effects into a spatially explicit framework can provide valuable insights into the dynamics of CLR epidemics and how they respond to farmers' decisions.