Atlantic Offshore Wind Environmental Research Recommendations

Extract nocturnal flight activity from existing bird telemetry data to inform estimate of nocturnal collisions.

Collect baseline data that describes the distribution and abundance and animals offshore and how this changes throughout space and time

Identify baseline vocalization behavior

Measure pH, water clarity, and dissolved oxygen when conducting surveys from the surface to sea floor.

Characterize the ambient noise levels in the ocean for historic conditions, present day, and predicted future scenarios considering climate change.

Conduct modeling or sampling to better understand zooplankton distribution and shifts over time

Characterize the spatial distribution of habitat and oceanographic features through mapping, measurement, and sampling. This includes characterization and sampling of benthic and fish habitat as well as the physical and chemical features.

Explore recovery of the seafloor following construction-related disturbance at multiple OSW sites in relation to variables such as seabed properties, local hydrodynamics, and type of disturbance.

Evaluate relative threat of serious injury (PTS) from high-intensity noise exposure associated with OSW and non-OSW activities

Create an inventory of all ongoing tracking projects for seabirds and marine mammals to encourage a coordinated approach to making research results compatible, available and applicable in Marine Spatial Planning, particularly concerning OSW energy development.

Design an impact reduction decision support tool to assist in designing practicable mitigation strategies across different scenarios

Understand atmospheric effects associated with energy removal by wind turbines.

Assess whether the number of bats at risk of collisions at OSW farms is sufficient to influence population trajectories.

Determine what causes bat attraction to wind farms and how this relates to flight height, collision risk, and time spent at wind farms.

Assess the ecological function beneath cable protection (e.g., infilling or colonization of rock protection) for various protection measures and the effects of cables (e.g., EMF) associated with wind infrastructure

Identify how ecological drivers and environmental factors influence the distribution and movement of animals

Assess the benthic ecological impacts of infrastructure habitat on surrounding soft-sediment ecosystems, including biodiversity tradeoffs before construction and recovery after full removal of an offshore installation.

Determine how displacement and macro- to meso-avoidance of individual bird species is linked to the spatial configuration of turbines

Assess the effects of multiple OSW facilities on oceanographic processes (e.g., production of turbulence, currents, temperature, seasonal stratification, sediment scour) and coupling of the hydrodynamics with water quality and ecosystems, including nutrient cycling.

Assess how local biodiversity on OSW infrastructure contributes to regional diversity through movement of mobile organisms or larval dispersal.

Examine whether habitat changes from OSW development affect populations of managed species through temporary disruption of spawning behavior

Assess the physical effects of OSW infrastructure habitat on surrounding soft-sediment ecosystems to inform decommissioning considerations

Assess the potential for recovery, habituation, and adaptation to noise in relation to species mobility or other features, in order to help understand the duration/longevity of responses

Develop a centralized, transparent, replicable, ecosystem-based framework of information and methods for Cumulative Impact Assessments at large spatial/temporal scales that incorporates other stressors beyond OSW development (e.g., climate change).

Develop a PTS impact range calculation for marine mammals utilizing strategic literature review.

Develop a tool to support decision-making around the implementation of noise-related mitigation strategies as it relates to potential cumulative impacts to help accelerate permitting.

Improve analyses of avoidance including macro-avoidance of wind farms to micro-avoidance of turbines, including quantification of key parameters such as flight speed and height in relation to behavior.

Design methods to automatically count and identify species, including data collections from digital aerial surveys, drone imagery, and benthic surveys.

Develop an availability bias correction to improve abundance estimates for long-diving marine mammal species.

Develop better methods to measure bird collisions, including rates and the conditions contributing to variation in risk. Empirical data of collisions can be used to understand the relationship between estimated and realized risk.

Develop dose-response functions for species besides harbor seal and harbor porpoise to provide a method by which the behavioral responses of species can be predicted when exposed to varying levels of noise from impact pile-driving.

Quantify exposure and potential vulnerability at proposed development areas to inform siting and risk assessments, identify key gaps in knowledge, and ensure that research studies are focused on species of greatest potential risk.

Develop methods for a practical field system for rapid assessment of hearing sensitivity through the modification and validation of existing technology to inform the extent and consequences of auditory damage of marine mammals to impulsive sound.

Develop guidance to inform oceanographic, species effects, and population-level impacts research, including passive acoustic monitoring at the site- and regional scales, and baseline distribution surveys, as well as mitigation including best practices for underwater habitat restoration.

Develop better methods to assess the magnitude of cumulative effects across multiple OSW developments and/or across the ecosystem and other pressures, building from existing models and focusing on key processes and functions rather than species-specific stressors.

Develop apportioning methodologies and test against existing methods (e.g. GPS tracking data) to ensure apportioning of at-sea effects during the breeding season to the appropriate population/s.

Develop methods/models to better understand at-sea seabird distributions with robust estimates of uncertainty