A flexible framework for species-based regional cumulative effects assessments to support offshore wind energy planning and management

Offshore wind energy development (OWED) is pivotal for renewable energy transition and climate resiliency. However, OWED activities may negatively affect wildlife, contributing to cumulative effects (CE) from human activities and natural processes. Cumulative effects assessments (CEAs) are vital for informed planning and management of OWED activities during regional assessment, site selection, and site evaluation phases. To reduce impacts on wildlife, OWEDs should be sited in areas that avoid or minimize CE. We present a flexible, species-based framework to assess CE from OWED activities and other pressures, supporting decision-making in early planning phases. The framework uses a species-based approach, applicable to various wildlife receptors (i.e., species or populations), and adapts to available information on ecology, socioeconomics, and pressures. The analytical strategy uses a CE metric to indicate the presence or magnitude of effects from all pressures on receptors. Spatially explicit optimization methods identify OWED site configurations that minimize a CE metric. The framework accommodates alternative pressure scenarios that include foreseeable future human activities and natural processes and can explore the sensitivity of the results to uncertain parameters. Given sufficient spatial information on receptor density, pressure magnitude, and cause-effect pathways, the spatial optimization algorithm can find solutions that minimize species- or population-level impacts from CE. If this ideal standard cannot be achieved due to information gaps, alternative metrics may be used to inform the immediate decision-making process. This framework offers a practical approach for balancing renewable energy goals with wildlife conservation, even when information is incomplete. • Step-by-step framework for cumulative effects assessment on any wildlife species or population. • Regional approach adaptable to diverse species and pressure data types. • Spatial optimization identifies offshore wind site configurations minimizing impacts. • Accommodates alternative scenarios, exploring sensitivity to uncertain parameters. • Standardized metrics enable consistent and comparable cumulative effects assessments.