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Jacquomo Monk

Researcher at University of Tasmania

Publications -  60
Citations -  1274

Jacquomo Monk is an academic researcher from University of Tasmania. The author has contributed to research in topics: Marine protected area & Sampling (statistics). The author has an hindex of 19, co-authored 56 publications receiving 1010 citations. Previous affiliations of Jacquomo Monk include Hobart Corporation & Deakin University.

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Comparison of automated classification techniques for predicting benthic biological communities using hydroacoustics and video observations

TL;DR: This work uses towed video observations and seafloor complexity variables derived from multibeam echosounder bathymetry and backscatter to predict the distribution of 8 dominant benthic biological communities in a 54 km2 site, off the central coast of Victoria, Australia.
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Evaluation of Four Supervised Learning Methods for Benthic Habitat Mapping Using Backscatter from Multi-Beam Sonar

TL;DR: This study demonstrates the applicability of supervised learning techniques for benthic habitat characterization using angular backscatter response data from multibeam echo-sounder technology using four different supervised learning methods.
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Habitat suitability for marine fishes using presence-only modelling and multibeam sonar

TL;DR: In this article, a comparative study of presence-only approaches in modelling suitable habitat for demer-sal marine fishes is presented, with a focus on five demersal fish taxa.
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A field and video annotation guide for baited remote underwater stereo-video surveys of demersal fish assemblages

TL;DR: Barrow Island Gorgon Barrow Island Net Conservation Benefits Fund (NCBBSF) as discussed by the authors is an Australian Government's National Environmental Science Program (NESP) program.
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How long should we ignore imperfect detection of species in the marine environment when modelling their distribution

TL;DR: 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.