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Aleksey Y. Sheshukov

Publications and source records attributed to Aleksey Y. Sheshukov.

5 recordsLinked to original sources

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

Agricultural landscapes are the bleeding-edge in the advancement of sustainability and climate change adaptation. Our study focuses on how individual support for sustainability policy is shaped in coupled natural and human systems. We present an agent-based model in which a cultural decision-rule quantifies the probability that a stakeholder decides to support an easement policy for a region in the Central Great Plains, USA. Our model defines a cultural threshold used to assess how culturally meaningful the policy is for each stakeholder. The individual cultural threshold is estimated using the value-belief-norm framework and is modified by perceived changes in the environment. Results demonstrated that few stakeholders support the policy in the average cultural setting (8.9%). However, enough stakeholders would support the policy under a lower cultural threshold (40.7%). Our results indicate that sustainability policies do not need to be cheap if they are culturally meaningful.

Kansas

Understanding the central Great Plains as a coupled climatic-hydrological-human system: Lessons learned in operationalizing interdisciplinary collaboration

This chapter discusses an interdisciplinary and transdisciplinary project to understand the interactions of agriculture, climate, and water resources in the Central Great Plains as a coupled natural-human system. We focus on the Smoky Hills Watershed in Kansas, where we gathered socioeconomic, hydrological, and climatic data, along with ecological data on fish species. The project involved substantial stakeholder engagement, which was complicated by post-truth attitudes about climate science and environmental regulation by some groups. We discuss the challenges of team management, stakeholder engagement, and data integration for modeling, notably the incorporation of stakeholder support for environmental policy in the context of extreme climatic events. We conclude by offering a framework for good collaborative practice to manage the complications of crossing boundaries in transdisciplinary research and outreach.

Kansas

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.

Kansas

Opinion: Endogenizing culture in sustainability science research and policy

Integrating the analysis of natural and social systems to achieve sustainability has been an international scientific goal for years ( 1 , 2 ). However, full integration has proven challenging, especially in regard to the role of culture ( 3 ), which is often missing from the complex sustainability equation. To enact policies and practices that can achieve sustainability, researchers and policymakers must do a better job of accounting for culture, difficult though this task may be. The concept of culture is complex, with hundreds of definitions that for years have generated disagreement among social scientists ( 4 ). Understood at the most basic level, culture constitutes shared values, beliefs, and norms through which people “see,” interpret, or give meaning to ideas, actions, and environments. Culture is often used synonymously with “worldviews” or “cosmologies” ( 5 , 6 ) to explain the patterned ways of assigning meanings and interpretations among individuals within groups. Used in this way, culture has been found to have only limited empirical support as an explanation of human risk perception ( 7 , 8 ) and environmentalism ( 9 ).

Proceedings of the National Academy of Sciences of

The Index of Biological Integrity and the bootstrap revisited: an example from Minnesota streams

Multimetric indices, such as the Index of Biological Integrity (IBI), are increasingly used by management agencies to determine whether surface water quality is impaired. However, important questions about the variability of these indices have not been thoroughly addressed in the scientific literature. In this study, we used a bootstrap approach to quantify variability associated with fish IBIs developed for streams in two Minnesota river basins. We further placed this variability into a management context by comparing it to impairment thresholds currently used in water quality determinations for Minnesota streams. We found that 95% confidence intervals ranged as high as 40 points for IBIs scored on a 0–100 point scale. However, on average, 90% of IBI scores calculated from bootstrap replicate samples for a given stream site yielded the same impairment status as the original IBI score. We suggest that sampling variability in IBI scores is related to both the number of fish and the number of rare taxa in a field collection. A comparison of the effects of different scoring methods on IBI variability indicates that a continuous scoring method may reduce the amount of bias in IBI scores.

Minnesota