New seabird modelling tool could 'transform' offshore wind planning

A new ‘first of its kind’ modelling tool for seabirds is twice as accurate as others available and could transform planning for offshore wind farms often stymied by conservation concerns, say researchers.

The new tool is 73% accurate on average, which “doubles on the predictive power” of other industry standard models, researchers from the University of Glasgow claimed.

The team used GPS tracking data from eight northern gannet colonies to verify their predictions, which they compared to other tools that were 41% and 31% accurate, both over- and underestimating colony exposure to offshore wind farms.

“Accurate estimation of the impacts of offshore wind farms and other stressors on seabirds can help us make more informed decisions about offshore wind farm plans and protect the species living around our coasts,” said PhD student Holly Niven, who was the lead author of a study published on the new tool.

The researchers, whose work was funded by the UK government, claim that their new tool “could be transformative” for planning offshore wind farms, with even the largest projects often frustrated by concerns over seabird populations.

Many seabird species nest in colonies on small pieces of land, including clusters of rocks off the coast, said the researchers. From there, they fly and forage around a local area at sea, a home range that can vary in size.

Because of these characteristic behaviours, central-place foragers such as seabirds are “particularly sensitive” to environmental stressors, including wind farms, which can have “severe impacts” on colony numbers and wellbeing.

The researchers claim that their new tool is the “first of its kind to accurately predict space use of seabird colonies without requiring extensive satellite tracking data, which is often not available.”

Current tools vary in accuracy and may lead to offshore wind farms being built in areas with “high bird density” or, conversely, being “inadvertently rejected based on overestimates of seabirds at sea.”

“Ironically, different environmentally positive activities such as wildlife conservation and our progress towards green energy can come into conflict with each other,” said Jason Matthiopoulos, professor of spatial and population ecology who supervised the study. “Resolving these conflicts relies on good data, but equally, on state-of-the-art computer modelling techniques.”

Jana Jeglinski, who also supervised the study, said that “many seabird colonies are located at remote islands or cliffs that make GPS tracking studies extremely challenging or even impossible.”

“Our method can predict biologically realistic home ranges and exposure for such inaccessible colonies and it can also forecast future home ranges given the size of a colony – this is important since offshore wind farm construction will drastically increase in the near future.”