The bean method as a tool to measure sensitive behavior

Conservationists need to measure human behavior to guide decisions and evaluate their impact. However, activities can be misreported and reporting accuracy may change following conservation interventions, making it hard to verify any apparent changes. Techniques for asking sensitive questions are increasingly integrated into survey designs to improve data quality, but some can be costly or hard for nonexperts to implement. We demonstrate a straightforward, low-cost approach, the bean method in which respondents give anonymous answers by adding a colored bean to a jar to denote a yes or no response. We applied the bean method to measure wild-meat hunting and trading over 2 years at a conservation-project (hunting reduction) site in Gola Forest, Liberia. We extended the technique to accommodate questions about hunting and meat-selling frequency. We compared responses given using the bean method and direct questioning for groups that did and did not participate in conservation interventions. Results from the bean method corresponded to those from direct questioning, and there was no indication of change in question sensitivity following conservation interventions. Estimates from both methods indicated that wild-meat trading decreased in project and nonproject households (from 36% to 20%) and that hunting decreased in 1 project group (38–28%). Where inconsistent answers were given (2–6% of respondents), differences were in both directions and were most likely attributable to measurement error. The bean method was quick and straightforward to administer in a low-literacy setting. We showed how it can be modified for answers of more than 2 categories and consider it a valuable tool that could be adapted for a wide range of conservation settings.     

Conducting conservation social science surveys online

The coronavirus (COVID-19) pandemic is affecting the environment and conservation research in fundamental ways. Many conservation social scientists are now administering survey questionnaires online, but they must do so while ensuring rigor in data collection. Further, they must address a suite of unique challenges, such as the increasing use of mobile devices by participants and avoiding bots or other survey fraud. We reviewed recent literature on online survey methods to examine the state of the field related to online data collection and dissemination. We illustrate the review with examples of key methodological decisions made during a recent national study of people who feed wild birds, in which survey respondents were recruited through an online panel and a sample generated via a project participant list. Conducting surveys online affords new opportunities for participant recruitment, design, and pilot testing. For instance, online survey panels can provide quick access to large and diverse samples of people. Based on the literature review and our own experiences, we suggest that to ensure high-quality online surveys one should account for potential sampling and nonresponse error, design survey instruments for use on multiple devices, test the instrument, and use multiple protocols to identify data quality problems. We also suggest that research funders, journal editors, and policy makers can all play a role in ensuring high-quality survey data are used to inform effective conservation programs and policies.     

安全信息认知通用模型构建及其启示

为了揭示复杂系统内安全信息传播的机理与故障模式和发展新的安全模型,以安全信息认知过程为主线,以安全信息失真或不对称为问题,构建了1个包含7个关键事件、6个时间状态、5级信息失真和4级信息传播的安全信息认知通用理论模型,阐述了模型的内涵、特点、用途分类和故障诊断分析途径,并由模型推导出1组安全科学基础理论新概念,同时也建立了1种新的安全信息系统分析与控制的方法论。结果表明,该模型对事故致因机理分析、行为安全管理、系统安全设计和事故防控等的具有重要的理论和实际意义。     

Practical guide to coproduction in conservation science

We considered a series of conservation-related research projects on the island of Pemba, Tanzania, to reflect on the broad significance of Beier et al.’s recommendations for linking conservation science with practical conservation outcomes. The implementation of just some of their suggestions can advance a successful coproduction of actionable science by small research teams. Key elements include, first, scientists and managers working together in the field to ensure feedback in real time; second, questions jointly identified by managers and researchers to facilitate engaged collaboration; third, conducting research at multiple sites, thereby broadening managers’ abilities to reach multiple stakeholders; and fourth, establishing a multidisciplinary team because most of the concerns of local managers require input from multiple disciplines.     

The legacy of lead pollution: (dis)trust in science and the debate over Superfund

Lead contamination is a significant health hazard in communities around the world, but this environmental toxin often remains unknown to residents living near hazardous sites. This research investigates a unique case where residents were informed of lead contamination but rejected official and scientific narratives regarding environmental risks. The case study involves a decommissioned smelter in Colorado. Drawing from data collected over three years, the researchers examine how officials and experts communicated the severity of environmental health hazards. Despite these efforts, residents opposed the Environmental Protection Agency’s attempts to place the site on the National Priorities List for federal cleanup. The government’s framing of science and environmental risk failed to resonate with homeowners, despite the known and significant scientific evidence confirming environmental health hazards, and residents’ perceptions of lead contamination were mitigated by material concerns, including property values and community stigma. Implications for future research on lead contamination, environmental risk, and trust in science are discussed.     

Data Management Dimensions of Social Water Science: The iUTAH Experience

Integrating social and hydrologic sciences for understanding water systems is challenged by data management complexities. Contemporary mandates for open science and data sharing necessitate better understanding of the implications of social science data types. In the context of an interdisciplinary water research program that endeavors to integrate and share social science and biophysical data, we highlight the array of data types and issues associated with social water science. We present a multi‐dimensional classification of social water science data that provides insight into data management considerations for each data type. Recommendations for cyberinfrastructure, planning, and policy are offered.     

Using citizen science in environmental justice: participation and decision-making in a Southern California waste facility siting conflict

Uses of science by environmental justice (EJ) activists reflect struggles to challenge professional scientific expertise, achieve fair outcomes, and effectively participate in decision-making processes. This qualitative research analyses the relationship between citizen science and EJ in a new waste facility siting conflict in urban Los Angeles, namely connections between citizen science and four dimensions of EJ: fair distribution, respect and recognition, participation in decision-making, and community capabilities. Citizen science is one tactic in EJ, yet little research investigates its role in a new facility siting conflict, particularly in relation to multi-faceted EJ goals. The research reveals opportunities for individual empowerment and community capacity building using citizen science, and a small measure of improved respect and recognition for participants who brought their own knowledge, research, and voices to the table. At the same time, the work identifies limitations on citizen science to improve local participatory procedures and decision-making, which also constricted the achievement of outcomes most desired by the EJ group: to prevent approval and construction of the new waste facility. This paper argues that uses of citizen science contributed to partial achievement of EJ goals, while hindered by governance processes that call for public participation yet shield decision-makers from substantive engagement with the volume or content of that participation.     

Risk and Responsibility in Public Engagement by Climate Scientists: Reconsidering Advocacy During the Trump Era

The election as US President of Donald J Trump, who denies the scientific consensus on climate change, raises questions about the role of scientists in public discourse. How far should scientists wade into the waters of advocacy before risking their credibility of fair arbiters of knowledge? The new study by Kotcher, Myers, Vraga, Stenhouse, and Maibach [2017. Does engagement in advocacy hurt the credibility of scientists? Results from a randomized national survey experiment. Environmental Communication. doi:10.1080/17524032.2016.1275736] is a reminder that scientists are among the most trusted people in public life and have some freedom to engage publicly without harming their reputation. However, with the power to influence public debate comes the responsibility to carefully consider the impact of statements and actions. This commentary discusses the challenges facing scientists at a time of great potential for public engagement, and for a gap between perceived and actual intent of public statements.     

Are all experiments created equal? A framework for analysis of the learning potential of policy experiments in environmental governance

Environmental changes are increasing the need to understand complex cross-scale feedbacks in social–ecological systems. However, consistent conceptualisation of learning associated with environmental governance is lacking, and research mainly centres on individual variables. This paper identifies a typology of such learning, and theorises about configurations of variables. Focusing on experimentation as an intervention geared towards learning, it proposes a definition of policy experiment. A theoretical framework is presented, summarising a typology of experiments based on learning-related variables embedded in design choices, and reflected in institutional rule aggregations. The framework facilitates systematic analysis of real-world cases and testing of hypotheses on the effects of different types of experiment on learning. A case study demonstrates application of the framework. Results suggest future research paths that include attention to additional relevant variables. The findings have relevance for scholars interested in experimentation and learning, and environmental policy-makers considering experimentation to assess policy innovations.     

Young adult conservation jobs and worker health

Decades of research studies demonstrate links between healthy environment, healthy lifestyles, and healthy people. This study evaluated the correlations between young adult conservation workers' perceived stress, personal effectiveness, and nature experience using quantitative and qualitative social science methods. The study cohort numbered nearly 300 individuals serving on small crews for an entire year, and were dispersed across Washington State (USA) to participate in conservation projects in rural to urban landscapes. Pre- and post-test surveys, using validated measures of perceived stress, health dimensions, and personal resiliency, were further informed by mid-year, field-based interviews. Overall, the young adults expressed fatigue with the physical work but were quite healthy when compared to national benchmarks. They indicated a reduction in perceived stress, and indicated social function influences based on the conservation work. Conclusions address the importance and implications of expanding this work opportunity to a more diverse cohort and future research needs.