Engagement takes a (fishing) village to manage a resource:Principles and practice of effective stakeholder engagement

Highlights • Qualitative study of stakeholder engagement strategies used in natural resource management. • We identify 22 outreach strategies, how they help practitioners achieve nine management goals, and how they can be measured using five metrics. • Inclusive and transparent engagement is critical for creating and implementing legitimate, salient, and credible policy

Designing a solution to enable agency-academic scientific collaboration for disasters

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecology and Society 22 (2017): 18, doi:10.5751/ES-09246-220218.As large-scale environmental disasters become increasingly frequent and more severe globally, people and organizations that prepare for and respond to these crises need efficient and effective ways to integrate sound science into their decision making. Experience has shown that integrating nongovernmental scientific expertise into disaster decision making can improve the quality of the response, and is most effective if the integration occurs before, during, and after a crisis, not just during a crisis. However, collaboration between academic, government, and industry scientists, decision makers, and responders is frequently difficult because of cultural differences, misaligned incentives, time pressures, and legal constraints. Our study addressed this challenge by using the Deep Change Method, a design methodology developed by Stanford ChangeLabs, which combines human-centered design, systems analysis, and behavioral psychology. We investigated underlying needs and motivations of government agency staff and academic scientists, mapped the root causes underlying the relationship failures between these two communities based on their experiences, and identified leverage points for shifting deeply rooted perceptions that impede collaboration. We found that building trust and creating mutual value between multiple stakeholders before crises occur is likely to increase the effectiveness of problem solving. We propose a solution, the Science Action Network, which is designed to address barriers to scientific collaboration by providing new mechanisms to build and improve trust and communication between government administrators and scientists, industry representatives, and academic scientists. The Science Action Network has the potential to ensure cross-disaster preparedness and science-based decision making through novel partnerships and scientific coordination.The authors thank the David and Lucile Packard Foundation for a grant to undertake this project and enable participation of a wide range of participants and interviewees. We thank the Center for Ocean Solutions and ChangeLabs for their oversight and support

Data from: Characterizing driver-response relationships in marine pelagic ecosystems for improved ocean management

Scientists and resources managers often use methods and tools that assume ecosystem components respond linearly to environmental drivers and human stressor. However, a growing body of literature demonstrates that many relationships are non-linear, where small changes in a driver prompt a disproportionately large ecological response. Here we aim to provide a comprehensive assessment of the relationships between drivers and ecosystem components to identify where and when non-linearities are likely to occur. We focus our analyses on one of the best-studied marine systems, pelagic ecosystems, which allowed us to apply robust statistical techniques on a large pool of previously published studies. In this synthesis, we (1) conduct a wide literature review on single driver-response relationships in pelagic systems, (2) use statistical models to identify the degree of non-linearity in these relationships, and (3) assess whether general patterns exist in the strengths and shapes of non-linear relationships across drivers. Overall we found that non-linearities are common in pelagic ecosystems, comprising at least 52% of all driver-response relationships. This is likely an underestimate, as papers with higher quality data and analytical approaches reported non-linear relationships at a higher frequency - on average 11% more. Consequently, in the absence of evidence for a linear relationship, it is safer to assume a relationship is non-linear. Strong non-linearities can lead to greater ecological and socio-economic consequences if they are unknown (and/or unanticipated), but if known they may provide clear thresholds to inform management targets. In pelagic systems, strongly non-linear relationships are often driven by climate and trophodynamic variables, but are also associated with local stressors such as overfishing and pollution that can be more easily controlled by managers. Even when marine resource managers cannot influence ecosystem change, they can use information about threshold responses to guide how other stressors are managed and to adapt to new ocean conditions. As methods to detect and reduce uncertainty around threshold values improve, managers will be able to better understand and account for ubiquitous non-linear relationships

The challenges and opportunities in cumulative effects assessment

The cumulative effects of increasing human use of the ocean and coastal zone have contributed to a rapid decline in ocean and coastal resources. As a result, scientists are investigating how multiple, overlapping stressors accumulate in the environment and impact ecosystems. These investigations are the foundation for the development of new tools that account for and predict cumulative effects in order to more adequately prevent or mitigate negative effects. Despite scientific advances, legal requirements, and management guidance, those who conduct assessments including resource managers, agency staff, and consultants continue to struggle to thoroughly evaluate cumulative effects, particularly as part of the environmental assessment process. Even though 45 years have passed since the United States National Environmental Policy Act was enacted, which set a precedent for environmental assessment around the world, defining impacts, baseline, scale, and significance are still major challenges associated with assessing cumulative effects. In addition, we know little about how practitioners tackle these challenges or how assessment aligns with current scientific recommendations. To shed more light on these challenges and gaps, we-undertook a comparative study on how cumulative effects assessment (CEA) is conducted by practitioners operating under some of the most well-developed environmental laws around the globe: California, USA; British Columbia, Canada; Queensland, Australia; and New Zealand. We found that practitioners used a broad and varied, definition of impact for CEA, which led to differences in how baseline, scale, and significance were determined. We also found that practice and science are not closely aligned and, as such, we highlight opportunities for managers, policy makers, practitioners, and scientists to improve environmental assessment

Summary statistics and ancillary data of published single driver-response relationships in pelagic marine ecosystems

We created a database of published single driver-response relationships in marine pelagic ecosystems that were deemed significant based on p values ≤ 0.05 or were included in best-fit models identified through model selection. Multiple summary statistics were recorded (when available) in the database in an effort to explore variation in driver-response relationships in the present study and to be made available for researchers for future studies. The summary statistics include published or derived shapes of the relationships (linear, non-linear or specific functional forms), sample size, quantitative estimates of ecological thresholds, p values, R^2, deviance explained, correlation and regression coefficients, and model covariates (if multivariate model). In addition, we collected ancillary data on study characteristics to explore the variation in driver-response relationships and to identify the most robust papers with respect to statistical methods. The ancillary data in our database include ecosystem type (enclosed bay or sea, coastal pelagic, continental shelf and continental slope/oceanic), local region, ocean basin, large marine ecosystem, temporal scale of study, functional level (i.e., individual, population, community) and species trophic level (TL 1-4) of ecological response, primary productivity (mgC/mg2/day) and the statistical methods used by the authors. Estimates of species trophic level and primary productivity were obtained from the Sea Around Us Project (http://www.seaaroundus.org/). See Supplement Table S1 for additional description of data columns. The references in the database are cross-referenced with Table S1 Literature Cited.docx

Using ecological thresholds to inform resource management: current options and future possibilities

In the face of growing human impacts on ecosystems, scientists and managers recognize the need to better understand thresholds and nonlinear dynamics in ecological systems to help set management targets. However, our understanding of the factors that drive threshold dynamics, and when and how rapidly thresholds will be crossed is currently limited in many systems. In spite of these limitations, there are approaches available to practitioners today—including ecosystem monitoring, statistical methods to identify thresholds and indicators, and threshold-based adaptive management—that can be used to help avoid ecological thresholds or restore systems that have crossed them. We briefly review the current state of knowledge and then use real-world examples to demonstrate how resource managers can use available approaches to avoid crossing ecological thresholds. We also highlight new tools and indicators being developed that have the potential to enhance our ability to detect change, predict when a system is approaching an ecological threshold, or restore systems that have already crossed a tipping point