Developing updated predictive models for benthic taxa and communities across Chatham Rise and Campbell Plateau using photographic survey data / F. Stephenson, D.A. Bowden, B. Finucci, O.F. Anderson, A.A. Rowden.

By: Stephenson, F. (Fabrice).
Contributor(s): Bowden, David A. National Institute of Water and Atmospheric Research (NIWA), New Zealand | Finucci, B. (Brit). National Institute of Water and Atmospheric Research (NIWA), New Zealand | Anderson, Owen F. National Institute of Water and Atmospheric Research (NIWA), New Zealand | Rowden, A. A. (Ashley Alun). National Institute of Water and Atmospheric Research (NIWA), New Zealand | Fisheries New Zealand (Government agency).
Material type: materialTypeLabelBookSeries: New Zealand aquatic environment and biodiversity report: no. 276Publisher: Wellington, New Zealand : Fisheries New Zealand, Tini a Tangaroa, 2021Description: 1 online resource (82 pages).ISBN: 9781991019912.Other title: Predictive models for benthic taxa using photographic data [Running title].Subject(s): FISHERIES | NEW ZEALANDOnline resources: AEBR 276 Fisheries Infosite | NIWA document server Summary: A quantitative dataset of benthic invertebrate occurrences from photographic surveys was used to predict distributions of individual taxa and communities across the south-eastern sector of New Zealand’s Exclusive Economic Zone. Several methods were used to model distributions of individual taxa and whole communities. Most individual models had at least some explanatory and predictive power, while community classifications showed potential for use in environmental management.
List(s) this item appears in: New Zealand Aquatic Environment and Biodiversity Report
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"November 2021."

AEBR-276-Preditive-Models-For-Benthic-Taxa-Using-Photographic-Data-4214

A quantitative dataset of benthic invertebrate occurrences from photographic surveys was used to predict distributions of individual taxa and communities across the south-eastern sector of New Zealand’s Exclusive Economic Zone. Several methods were used to model distributions of individual taxa and whole communities. Most individual models had at least some explanatory and predictive power, while community classifications showed potential for use in environmental management.

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