The gap between experts, farmers and non-farmers on perceived environmental vulnerability and the influence of values and beliefs.

Science has played a mixed role in guiding conservation and sustainability-oriented decision-making by individuals, policymakers, institutions, and governments. Not all science-based conservation and sustainability initiatives that address issues facing humanity and ecosystems and global problems have gained public support. Conservation decisions and policy prescriptions are and may be based on perceptions about and experiences with the environment, local land use, and ecosystems that may not align with or be grounded in science or evidence from experts in the field. Values, beliefs, and perceptions associated with nature play a critical role in how individuals view biodiversity conservation, sustainability, and natural resource management. This study first examines the gap between experts (scientists and other field experts) and the public (farmers and non-farmers) about the state of water and land resources, wildlife and associated habitats, and aquatic biodiversity in the Smoky Hill River Watershed in western Kansas. Second, the study examines the role that values and beliefs play in shaping environmental perceptions for farmers and non-farmers. Analysis confirms that a gap between experts and farmers/non-farmers does exist, especially with respect to the state of the Ogallala Aquifer, playas, rivers and streams, lakes and reservoirs, native grasslands, wildlife habitats, farmland, native fish populations, and wildlife species. Ordered-logistic regression analyses, meanwhile, indicate that farmer and non-farmer perceptions about the state of the local environment are influenced by traditional and self-interested values, as well as environmental values and beliefs, but less so by religiosity and political ideology. Despite broad takeaways, results exhibited heterogeneity across the farmer and non-farmer subpopulations. If environmental professionals cannot align ecological data, stakeholders' values/perceptions, and policies, then the existing body of technical research and management on sustainability in natural and social sciences may be of little value.

U.S. agricultural university students' mental well-being and resilience during the first wave of COVID-19: Discordant expectations and experiences across genders.

The coronavirus disease 2019 (COVID-19) pandemic's first wave led to declining mental health and life satisfaction outcomes for college students, especially women. While women in undergraduate agricultural programs outperformed men academically prior to and during the pandemic, the achievement may have come at personal cost, especially for those women with fewer personal and environmental resiliency resources. Our research objective was to expand on personal, social, and environmental factors linked with lower mental health and life satisfaction scores for students in agriculture during the pandemic. We measured the influence of such factors across gender-based mental health and life satisfaction outcomes. Our data were collected from 2030 students using an on-line survey across six land-grant university college of agriculture in agriculturally as many distinct regions of the United States. We estimated OLS and Ordered Probit models of their mental health and life satisfaction self-assessments. Our findings reveal students' mental health and life satisfaction were reduced due to a paucity of personal (e.g., less future orientation or graduate school aspirations, food and housing insecurity, and personal health risks) and environmental (e.g., lower quality on-line learning experiences, isolation, family health risk, discrimination experiences) resiliency resources. Our results suggest women were more likely than men to be adversely affected by reduced resiliency resources. These findings suggest university emergency response policies need to address students' needs for housing and food security, on-line course development and delivery, tele health and mental health resources, broad social inclusion and diversity to decrease risk of female attrition and support all students in agricultural degree programs.

Local environment and individuals' beliefs: The dynamics shaping public support for sustainability policy in an agricultural landscape.

Agricultural landscapes are the leading edge in the advancement of sustainability and climate change adaptation. The purpose of this study is to endogenize culture as shaped by natural-cultural feedback into individuals' decision-making processes on sustainability policy support. We present an agent-based model in which an adaptive cultural decision-rule quantifies the probability of an agent deciding to support a wildlife area policy for the Smoky Hill River Watershed (SHRW) in Kansas, USA. By using an ABM to examine the watershed as a coupled natural and human system, we learned that agents would adopt a new behavior, voting for the policy, if the cultural conditions were right, with high levels of beliefs and norms for freshwater and its biota. Our results indicate that individuals in the SHRW are not engaged in caring for fish, plants, and bird richness in their rivers and playas with few individuals supporting the policy in the naïve cultural setting (8.9 % of simulated population). However, enough agents would support the policy under a lower cultural threshold (40.7 % of simulated population). Our results show that sustainability policies need to account for the local culture to gain support, and if a policy is culturally meaningful, it does not need to be cheap. For an agricultural landscape, such as those commonly found in the Central Great Plains, this study presents new levers for policymakers on the conditions needed to help assemble popular support for sustainability policies.

Consumer Reactions to E. Coli and Antibiotic Residue Recalls: Utility Maximization vs. Regret Minimization.

Food safety remains a major issue to many consumers. Previous studies examining the economic impact of food safety recalls have focused on Class I recalls. Antibiotic residue in meat products, a Class II recall, has increased in consumer importance yet little is known about how much research and development expenditure should be allocated to reduce antibiotic residue pre- and post-harvest. This study compares demand elasticities and the decrease in willingness to pay in response to either an E. coli (Class I) or antibiotic residue (Class II) recall. We compare and contrast two competing behavioral frameworks, Random Utility and Regret Minimizing. Modeling behavior using the random regret framework is found to be more powerful for assessing consumer responses. In addition, we explore if different groups of consumers exist that either maximize utility or minimize regret. Consumer devaluations of E. coli (Class I) are 40-65% larger than antibiotic residue (Class II). Approximately 60% of consumers are identified as regret minimizers and 40% were identified as utility maximizers. While industry response and government policy recommendations differed conditional on modeling framework, the regret minimizing framework required smaller price discounts than regret minimizing to maintain the same level of market share.

Economic elasticities of input substitution using data envelopment analysis.

The use of elasticities of substitution between inputs is a standard method for addressing the effect of a change in the mix of inputs used for production from a technical or cost standpoint. Most estimation methods use parametric production or cost functions or frontiers to estimate these elasticities. A potentially useful nonparametric alternative is data envelopment analysis (DEA). The purpose of this paper is to derive elasticities of input substitution for both technical and cost frontiers using DEA, extending the use of this approach in the field of economics and associated fields. The paper provides derivations for both Hicksian (production and cost frontier) and Morishima (cost frontier) elasticities of input substitution, as well as a parsimonious method for estimating them using DEA. The derivations are presented using an agricultural example form Kansas, USA.

Evaluating environmental change and behavioral decision-making for sustainability policy using an agent-based model: A case study for the Smoky Hill River Watershed, Kansas.

Sustainability has been at the forefront of the environmental research agenda of the integrated anthroposphere, hydrosphere, and biosphere since the last century and will continue to be critically important for future environmental science. However, linking humans and the environment through effective policy remains a major challenge for sustainability research and practice. Here we address this gap using an agent-based model (ABM) for a coupled natural and human systems in the Smoky Hill River Watershed (SHRW), Kansas, USA. For this freshwater-dependent agricultural watershed with a highly variable flow regime influenced by human-induced land-use and climate change, we tested the support for an environmental policy designed to conserve and protect fish biodiversity in the SHRW. We develop a proof of concept interdisciplinary ABM that integrates field data on hydrology, ecology (fish richness), social-psychology (value-belief-norm) and economics, to simulate human agents' decisions to support environmental policy. The mechanism to link human behaviors to environmental changes is the social-psychological sequence identified by the value-belief-norm framework and is informed by hydrological and fish ecology models. Our results indicate that (1) cultural factors influence the decision to support the policy; (2) a mechanism modifying social-psychological factors can influence the decision-making process; (3) there is resistance to environmental policy in the SHRW, even under potentially extreme climate conditions; and (4) the best opportunities for policy acceptance were found immediately after extreme environmental events. The modeling approach presented herein explicitly links biophysical and social science has broad generality for sustainability problems.

Spatial dynamics in the classroom: Does seating choice matter?

This study examines peer and seating effects on overall class performance and exams from a spatial perspective for principles of economics courses at a major Land Grand institution in the Midwest. Both spatial and student specific factors were identified that impact performance. The spatial relationships in the classroom were explored to determine if students' peers and seating choice affect their performance. Endogenous spatial peer effects were only found to impact performance on the first exam. Other findings found gender, being an economics major, sitting in the back of the class, and the year the class was taken all impacted overall exam and class performance.

A primer on marginal effects--Part I: Theory and formulae.

Marginal analysis evaluates changes in an objective function associated with a unit change in a relevant variable. The primary statistic of marginal analysis is the marginal effect (ME). The ME facilitates the examination of outcomes for defined patient profiles while measuring the change in original units (e.g., costs, probabilities). The ME has a long history in economics; however, it is not widely used in health services research despite its flexibility and ability to provide unique insights. This paper, the first in a two-part series, introduces and illustrates the calculation of the ME for a variety of regression models often used in health services research. Part One includes a review of prior studies discussing MEs, followed by derivation of ME formulas for various regression models including linear, logistic, multinomial logit model (MLM), generalized linear model (GLM) for continuous data, GLM for count data, two-part model, sample selection (two-stage) model, and parametric survival model. Prior theoretical papers in health services research reported the derivation and interpretation of ME primarily for the linear and logistic models, with less emphasis on count models, survival models, MLM, two-part models, and sample selection models. These additional models are relevant for health services research studies examining costs and utilization. Part Two of the series will focus on the methods for estimating and interpreting the ME in applied research. The illustration, discussion, and application of ME in this two-part series support the conduct of future studies applying the marginal concept.

Economic linkages to changing landscapes.

Many economic processes are intertwined with landscape change. A large number of individual economic decisions shape the landscape, and in turn the changes in the landscape shape economic decisions. This article describes key research questions about the economics of landscape change and reviews the state of research knowledge. The rich and varied economic-landscape interactions are an active area of research by economists, geographers, and others. Because the interactions are numerous and complex, disentangling the causal relationships in any given landscape system is a formidable research challenge. Limited data with mismatched temporal and spatial scales present further obstacles. Nevertheless, the growing body of economic research on these topics is advancing and shares fundamental challenges, as well as data and methods, with work in other disciplines.