Improved access to multibeam sonar and underwater video technology is enabling scientists to use spatially-explicit, predictive modelling to improve our understanding of marine ecosystems. With the growing number of modelling approaches available, knowledge of the relative performance of different models in the marine environment is required. Habitat suitability of 5 demersal fish taxa in Discovery Bay, south-east Australia, were modelled using 10 presence-only algorithms: BIOCLIM, DOMAIN, ENFA (distance geometric mean [GM], distance harmonic mean [HM], median [M], area-adjusted median [Ma], median + extremum [Me], area-adjusted median + extremum [Mae] and minimum distance [Min]), and MAXENT. Model performance was assessed using kappa and area under curve (AUC) of the receiver operator characteristic. The influence of spatial range (area of occupancy) and environmental niches (marginality and tolerance) on modelling performance were also tested. MAXENT generally performed best, followed by ENFA-GM and -HM, DOMAIN, BIOCLIM, ENFA-M, -Min, -Ma, -Mae and -Me algorithms. Fish with clearly definable niches (i.e. high marginality) were most accurately modelled. Generally, Euclidean distance to nearest reef, HSI-b (backscatter), rugosity and maximum curvature were the most important variables in determining suitable habitat for the 5 demersal fish taxa investigated. This comparative study encourages ongoing use of presence-only approaches, particularly MAXENT, in modelling suitable habitat for demersal marine fishes.

Item Type:	Refereed Article
Keywords:	demersal fish, species distribution model, habitat suitability, sonar, towed video
Research Division:	Agricultural and Veterinary Sciences
Research Group:	Fisheries Sciences
Research Field:	Aquatic Ecosystem Studies and Stock Assessment
Objective Division:	Environment
Objective Group:	Flora, Fauna and Biodiversity
Objective Field:	Marine Flora, Fauna and Biodiversity
UTAS Author:	Monk, J (Dr Jacquomo Monk)
ID Code:	99555
Year Published:	2010
Web of Science® Times Cited:	37
Deposited By:	IMAS Research and Education Centre
Deposited On:	2015-03-27
Last Modified:	2015-04-21
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