Adaptive management (AM) is a learning-based management approach that is used to reduce scientific uncertainty. AM has been identified as a tool to advance the wind energy industry, although its application in practice has been limited. AM has primarily been actively implemented in the United States, while other nations have applied some of the principles of AM. Many wind energy projects use the mitigation hierarchy or the precautionary principle to guide development, both of which focus on mitigating or avoiding project-related risks or impacts. Overall, AM allows wind energy projects to adapt monitoring and mitigation over time, leading to improved decision-making. The WREN nations have developed a white paper on AM that explores how AM principles are used by the wind energy industry in several nations, and identifies ways the process and its implementation may be improved.
Ten nations in Europe and North America collaborate on the WREN initiative under the International Energy Agency’s Wind Committee, to better understand and disseminate information on wind energy and wildlife interactions. WREN member nations have come together to publish their first white paper, on the topic of Adaptive Management (AM). Assessing Environmental Effects (WREN): Adaptive Management White Paper explores how AM principles are used by the wind energy industry in several nations, and identifies ways the process and its implementation may be improved. This white paper is the first in a series of papers to be published through WREN. A summary of the white paper can be found at the same site; a webinar on the topic is archived at: https://tethys.pnnl.gov/events/adaptive-management-wind-energy-industry.
The paper discusses AM use in practice and policy, which has been limited, and describes recent applications that have led to fundamental differences in the definition of AM, its application, and the projects or planning processes to which it might be applied. As a starting point, the AM paper adopts the US National Research Council definition, which focuses on: posing hypothesis-based questions for data collection; retaining a level of adaptability for monitoring and management actions throughout the process based on outcomes; enacting AM as an interactive process that provides feedback between the assessment of impacts on wildlife, wind energy project design and implementation, monitoring and evaluation of effects on wildlife; and ensuring that adjustment of management requirements are used to fully describe the AM process. AM can provide a myriad of benefits for wind energy developments and advancing the industry, as well as assisting regulators in applying environmental protections. However, there are also challenges associated with its implementation, which are discussed in the AM paper.
The paper explores AM applications to wind energy developments around the world, with additional focus given to United States (US) examples. Natural resource legislation, regulations, and guidelines for wind energy project management in some WREN member countries were found to include the explicit use of AM, while others apply some principles of AM. Several examples of AM principles used in WREN member countries are highlighted in the paper to showcase successful applications. One such example comes from wind farms located in the south of Spain where biomonitors are used for raptor flight to allow for real time shutdown of turbines, decreasing mortality due to blade collisions by 50% with a minimal reduction in energy productions. In the U.S., 16 wind energy AM plans were found to rely largely on predetermined mitigation triggers and actions. Additionally, US stakeholders were interviewed to determine their perceptions of the usefulness and application of AM to wind energy projects. Respondents generally acknowledged the regulatory benefits of acquiring added decision-making flexibility through AM in the face of unexpected impacts, but highlighted the effect that AM can have on project financing. They also commented on the confusion around a common definition and approach to applying AM, the high degree of variability among AM plans, and the lack of tools to direct preparation of AM plans as well as to enable impact reduction and mitigation.
Overall, the paper concludes that AM approaches should seek to leverage lessons learned from existing projects to inform future management decisions. This paper recommends that the AM guidance be improved to:
- Adopt a universal definition of AM that is coupled with an agreed-upon set of eligibility criteria and is consistent with the regulatory context in which it is being applied;
- Optimize the spatial and temporal scales over which AM is applied to reduce scientific uncertainty;
- Guide the application of AM by the need to minimize undue financial pressure on projects while ensuring that the natural resources of the nation or region are protected; and
- Establish formal processes and structures within national or regional regulatory bodies to make use of environmental impact data from existing projects to generate knowledge that can be applied to the planning and management of future projects.
Adaptive Management is a decision process that promotes flexible decision-making that can be adjusted in the face of uncertainties as outcomes from management actions and other events become better understood. Careful monitoring of these outcomes both advances scientific understanding and helps adjust policies or operations as part of an iterative learning process…” (NRC 2004; Williams et al. 2009).
Citations:
- NRC (National Research Council). 2004. Adaptive Management for Water Resources Planning, The National Academies Press. Washington, D.C.
- Williams, B.K., Szaro, R.C., and Shapiro, C.D. 2009. Adaptive Management: The U.S. Department of the Interior Technical Guide. Adaptive Management Working Group, U.S. Department of the Interior, Washington, D.C.