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Are we predicting the actual or apparent distribution of temperate marine fishes?

Monk, Jacquomo, Ierodiaconou, Daniel, Harvey, Euan, Rattray, Alex and Versace, Vincent L. 2012, Are we predicting the actual or apparent distribution of temperate marine fishes?, PLoS One, vol. 7, no. 4, pp. 1-11, doi: 10.1371/journal.pone.0034558.

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Title Are we predicting the actual or apparent distribution of temperate marine fishes?
Author(s) Monk, JacquomoORCID iD for Monk, Jacquomo orcid.org/0000-0002-1874-0619
Ierodiaconou, DanielORCID iD for Ierodiaconou, Daniel orcid.org/0000-0002-7832-4801
Harvey, Euan
Rattray, Alex
Versace, Vincent L.ORCID iD for Versace, Vincent L. orcid.org/0000-0002-8514-1763
Journal name PLoS One
Volume number 7
Issue number 4
Article ID e34558
Start page 1
End page 11
Total pages 11
Publisher Public Library of Science
Place of publication San Francisco, Calif.
Publication date 2012-04-19
ISSN 1932-6203
Keyword(s) animals
area under curve
computer simulation
conservation of natural resources
data collection
ecosystem
fishes
biological models
oceans and seas
ROC curve
video recording
Summary Planning for resilience is the focus of many marine conservation programs and initiatives. These efforts aim to inform conservation strategies for marine regions to ensure they have inbuilt capacity to retain biological diversity and ecological function in the face of global environmental change – particularly changes in climate and resource exploitation. In the absence of direct biological and ecological information for many marine species, scientists are increasingly using spatially-explicit, predictive-modeling approaches. Through the improved access to multibeam sonar and underwater video technology these models provide spatial predictions of the most suitable regions for an organism at resolutions previously not possible. However, sensible-looking, well-performing models can provide very different predictions of distribution depending on which occurrence dataset is used. To examine this, we construct species distribution models for nine temperate marine sedentary fishes for a 25.7 km2 study region off the coast of southeastern Australia. We use generalized linear model (GLM), generalized additive model (GAM) and maximum entropy (MAXENT) to build models based on co-located occurrence datasets derived from two underwater video methods (i.e. baited and towed video) and fine-scale multibeam sonar based seafloor habitat variables. Overall, this study found that the choice of modeling approach did not considerably influence the prediction of distributions based on the same occurrence dataset. However, greater dissimilarity between model predictions was observed across the nine fish taxa when the two occurrence datasets were compared (relative to models based on the same dataset). Based on these results it is difficult to draw any general trends in regards to which video method provides more reliable occurrence datasets. Nonetheless, we suggest predictions reflecting the species apparent distribution (i.e. a combination of species distribution and the probability of detecting it). Consequently, we also encourage researchers and marine managers to carefully interpret model predictions.
Language eng
DOI 10.1371/journal.pone.0034558
Field of Research 070499 Fisheries Sciences not elsewhere classified
Socio Economic Objective 960808 Marine Flora, Fauna and Biodiversity
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2012, The Authors
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30046908

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Citation counts: TR Web of Science Citation Count  Cited 13 times in TR Web of Science
Scopus Citation Count Cited 16 times in Scopus
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Created: Mon, 13 Aug 2012, 12:40:24 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.