Publication details.

Paper

Year:2019
Author(s):Guillermo Follana-Berná, Miquel Palmer, Andrea Campos-Candela, Pablo Arechavala-Lopez, Carlos Diaz-Gil, Josep Alós, Ignacio A. Catalan, Salvador Balle, Josep Coll, Gabriel Morey, Francisco Verger, Amalia Grau
Title:Estimating the density of resident coastal fish using underwater cameras: accounting for individual detectability
Journal:MARINE ECOLOGY PROGRESS SERIES
ISSN:0171-8630
Volume:615
Pages:177-188
D.O.I.:10.3354/meps12926
Web:https://www.int-res.com/abstracts/meps/v615/p177-188/
Abstract:Technological advances in underwater video recording are providing novel opportu- nities for monitoring wild fish. Although extracting data from videos is often challenging, accurate and precise estimates of density for animals whose normal activities are restricted to a bounded area or home range can be obtained from counts averaged across a relatively low number of video frames. However, this method requires that individual detectability (PID, the probability of detect- ing a given animal provided that it is actually within the area surveyed by a camera) be known. Here we propose a Bayesian implementation for estimating PID after combining counts from cam- eras with counts from any other reference method. The proposed framework was demonstrated with a case study of Serranus scriba, a widely distributed and resident coastal fish. Density and PID were calculated after combining fish counts from unbaited remote underwater video (RUV) and underwater visual censuses (UVC) as reference methods. The relevance of the proposed frame- work is that after estimating PID, fish density can be estimated accurately and precisely at the UVC scale (or at the scale of the preferred reference method) using RUV only. This method is further validated using computer simulations based on empirical data. We provide a simulation tool kit for comparing the expected precision attainable for different sampling effort and for species with different levels of PID. Overall, the proposed method may contribute to substantially enlarge the spatio-temporal scope of density monitoring programmes for many resident fish.

Related staff

  • Ignacio A. Catalán Alemany
  • Miguel Palmer Vidal
  • Guillermo Follana Berna
  • Josep Alós Crespí
  • Salvador Balle Monjo
  • Pablo Arechavala López
  • Related departments

  • Marine Ecology
  • Related projects

  • PHENOFISH CTA 137.1
  • Related research groups

  • Marine Ecosystems Dynamics