Public trust and knowledge in the context of emerging climate-adaptive forestry policies.

Effective governance of public forests depends, in part, on public support for changes in forest management, particularly those responding to changes in socio-ecological conditions driven by climate change. Trust in managing authorities and knowledge about forest management have proven influential in shaping public support for policy across different forest managemen contexts. However, little is known about the relationship between public trust and knowledge as it relates to policy support for emerging management strategies for climate adaptation in forests. We use the example of genomics-based assisted migration (within and outside of natural range) in British Columbia's (BC) forests to examine the relative roles of and interactions between trust in different forestry actors and knowledge of forestry in shaping public support for this new and potentially controversial management alternative. Our results, based on an online survey (n = 1953 BC residents), reveal low public trust in governments and the forest industry combined with low levels of public knowledge about forest management. We find that individuals who are more trusting of decision-makers and other important forestry actors hold higher levels of support for assisted migration. Higher levels of forestry knowledge are linked with support for assisted migration within native range, whereas no knowledge effect is observed for assisted migration outside of native range. We discuss the implications of these observations and provide recommendations to more fully engage with the challenges of low levels of trust and knowledge in this context.

Farmers' Risk-Based Decision Making Under Pervasive Uncertainty: Cognitive Thresholds and Hazy Hedging.

Researchers in judgment and decision making have long debunked the idea that we are economically rational optimizers. However, problematic assumptions of rationality remain common in studies of agricultural economics and climate change adaptation, especially those that involve quantitative models. Recent movement toward more complex agent-based modeling provides an opportunity to reconsider the empirical basis for farmer decision making. Here, we reconceptualize farmer decision making from the ground up, using an in situ mental models approach to analyze weather and climate risk management. We assess how large-scale commercial grain farmers in South Africa (n = 90) coordinate decisions about weather, climate variability, and climate change with those around other environmental, agronomic, economic, political, and personal risks that they manage every day. Contrary to common simplifying assumptions, we show that these farmers tend to satisfice rather than optimize as they face intractable and multifaceted uncertainty; they make imperfect use of limited information; they are differently averse to different risks; they make decisions on multiple time horizons; they are cautious in responding to changing conditions; and their diverse risk perceptions contribute to important differences in individual behaviors. We find that they use two important nonoptimizing strategies, which we call cognitive thresholds and hazy hedging, to make practical decisions under pervasive uncertainty. These strategies, evident in farmers' simultaneous use of conservation agriculture and livestock to manage weather risks, are the messy in situ performance of naturalistic decision-making techniques. These results may inform continued research on such behavioral tendencies in narrower lab- and modeling-based studies.