Merrall, Eve S; Green, Jonathan A; Robinson, Leonie A; Butler, Adam; Wood, Matt J; Newell, Mark A; Black, Julie; ... Horswill, Catharine; + view all Merrall, Eve S; Green, Jonathan A; Robinson, Leonie A; Butler, Adam; Wood, Matt J; Newell, Mark A; Black, Julie; Daunt, Francis; Horswill, Catharine; - view fewer (2024) Incorporating density-dependent regulation into impact assessments for seabirds. Journal of Applied Ecology 10.1111/1365-2664.14750. (In press).

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Abstract

1. Many industries are required to perform population viability analysis (PVA) during the consenting process for new developments to establish potential impacts on protected populations. However, these assessments rarely account for densitydependent regulation of demographic rates. Excluding density-dependent regulation from PVA-based impact assessments is often assumed to provide a maximum estimate of impact and therefore offer a precautionary approach to assessment. However, there is also concern that this practice may unnecessarily impede the development of important industries, such as offshore renewable energy. 2. In this study, we assess density-dependent regulation of breeding success in 31 populations of seabird. We then quantify the strength and form of this regulation using eight different formulations. Finally, we use PVA to examine how each formulation influences the recreation of observed dynamics (i.e. model validation), as well as the predicted absolute and relative population response to an extrinsic threat (i.e. model projection). 3. We found evidence of both negative (n= 3) and positive (n= 5) regulation of seabird breeding success. In populations exhibiting negative regulation, excluding density-dependent regulation from PVA-based impact assessment allowed uncontrolled population growth, such that model outcomes became biologically implausible. By contrast, in populations exhibiting positive regulation, excluding density-dependent regulation provided an appropriate reconstruction of observed dynamics, but population decline was underestimated in some populations. We find that multiple formulations of density dependence perform comparably at the detection, validation and projection stages of analysis. However, we tentatively recommend using a log-linear or Weibull distribution to describe density-dependent regulation of seabird breeding success in impact assessments to balance accuracy with caution. Finally, we show that relative PVA metrics of impact assessment cannot necessarily be used to overcome PVA misspecification by assuming density independence in positively regulated populations. 4. Synthesis and applications: We suggest that a density-dependent approach when performing PVA-based assessments for seabird populations will prevent biologically unrealistic, unconstrained population growth and therefore ensure meaningful PVA metrics in populations experiencing negative regulation. It will also maintain a precautionary approach for populations experiencing positive regulation, crucial when estimating impacts for these more vulnerable populations. These conclusions have immediate international application within the consenting processes for marine industries.

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