(untitled) (Zoological Records and Reviews, 2025)
Accurate wildlife population estimation is foundational to conservation planning, harvest management, and biodiversity monitoring. The diversity of available methods – ranging from traditional mark-recapture and distance sampling to modern spatial capture-recapture (SCR), N-mixture models, integrated population models (IPM), and close-kin mark-recapture (CKMR) – creates substantial challenges in method selection, application, and result interpretation. This review synthesises advances in wildlife population estimation from 216 primary studies published 2010-2024, with a focus on European vertebrate conservation contexts. We compare seven major estimation framework categories across six performance dimensions (accuracy, precision, cost, invasiveness, scalability, and model assumptions). Integrated population models show the most consistent performance advantages in precision (mean CV 0.14 vs. 0.28 for single-method approaches). Spatial capture-recapture eliminates density estimation bias from undefined sampling area. Close-kin mark-recapture provides unbiased abundance estimates without individual marking. N-mixture models require careful assumption checking that is frequently inadequate in published applications. These findings provide a critical evaluation framework for method selection and reporting standards in wildlife population studies supporting EU Habitats Directive Article 17 conservation status assessments.