Impact assessments of wind farms on seabird populations that overlook existing drivers of demographic change should be treated with caution

• Main Authors: Horswill, C, Miller, JAO, Wood, MJ
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2022
• Subjects: 41 Environmental Sciences; 31 Biological Sciences; 3103 Ecology; 7 Affordable and Clean Energy; Black-legged Kittiwake; rissa tridactyla
• Online Access: https://www.repository.cam.ac.uk/handle/1810/334958; https://doi.org/10.17863/CAM.82396

Funder: Research England; Id: http://dx.doi.org/10.13039/501100013589 Funder: UK Joint Nature Conservation Committee (DEFRA)’s Seabird Monitoring Programme; Id: http://dx.doi.org/10.13039/501100000277 <jats:title>Abstract</jats:title><jats:p>Population viability analyses (PVA) are now routinely used during the consenting process for offshore wind energy developments to assess potential impacts to vulnerable species, such as seabirds. These models are typically based on mean vital rates, such as survival and fecundity, with some level of environmental stochasticity (i.e., temporal variation). However, many species of seabird are experiencing population decline due to temporal (i.e., directional) trends in their vital rates. We assess the prevalence of temporal trends in rates of fecundity for a sentinel species of seabird, the black‐legged kittiwake <jats:italic>Rissa tridactyla</jats:italic>, and examine how accounting for these relationships affects the predictive accuracy of PVA, as well as the projected population response to an extrinsic threat. We found that temporal trends in kittiwake rates of fecundity are widespread, and that including these trends in PVA assessments dramatically influences the projected rate of population decline. We advocate that model validation become a prerequisite step in seabird PVA assessments to identify potential biases influencing the projected population response. We also argue that environmental factors driving current population dynamics need to be incorporated in PVA impact assessments as potential “worst‐case” scenarios. These findings have immediate application for improving and reducing uncertainty in impact assessments conducted as part of the consenting process for offshore wind energy developments.</jats:p>