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How long should we ignore imperfect detection of species in the marine environment when modelling their distribution?


Monk, J, How long should we ignore imperfect detection of species in the marine environment when modelling their distribution?, Fish and Fisheries, 15, (2) pp. 352-358. ISSN 1467-2960 (2014) [Refereed Article]

Copyright Statement

Copyright 2013 John Wiley & Sons Ltd

DOI: doi:10.1111/faf.12039


The application of the ‘ecosystem approach’ to marine conservation management demands knowledge of the distribution patterns of the target species or communities. This information is commonly obtained from species distribution models (SDMs). This article explores an important but rarely acknowledged assumption in these models: almost all species may be present, but simply not detected by the particular survey method. However, nearly all of these SDM approaches neglect this important characteristic. This leads to the violation of a fundamental assumption of these models, which presuppose the detection of a species is equal to one (i.e. at each survey locality, a species is perfectly detected). In this article, the concept of imperfect detection is discussed, how it potentially influences the prediction of species' distributions is examined, and some statistical methods that could be used to incorporate the detection probability of species in estimates of their distribution are suggested. The approaches discussed here could improve the collection and interpretation of marine biological survey data and provide a coherent way to incorporate detection probability estimates in the modelling of species distributions. This will ultimately lead to an unbiased and more rigorous understanding of the distribution of species in the marine environment.

Item Details

Item Type:Refereed Article
Keywords:marine fishes, imperfect detection, species distribution
Research Division:Agricultural, Veterinary and Food Sciences
Research Group:Fisheries sciences
Research Field:Aquaculture and fisheries stock assessment
Objective Division:Environmental Management
Objective Group:Marine systems and management
Objective Field:Marine biodiversity
UTAS Author:Monk, J (Dr Jacquomo Monk)
ID Code:99551
Year Published:2014
Web of Science® Times Cited:51
Deposited By:IMAS Research and Education Centre
Deposited On:2015-03-27
Last Modified:2017-11-04

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