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Lookup NU author(s): Dr Fabrice StephensonORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2021 The AuthorsRobust design of Marine Protected Areas in ocean environments is often challenging due to inadequate knowledge of biodiversity patterns, reflecting difficulties in the prediction of species distributions from sampling data that are often sparse or inadequate. Models that combine species and environmental data, such as Gradient Forests (GF), provide one analytical approach to this problem, efficiently combining available information to produce spatial models of species turnover throughout an area of interest. Spatial estimates of species turnover can then be classified to estimate spatial patterns in species composition; however, the performance of GF-based classifications within a conservation planning context has not previously been evaluated. Here we assess the utility for conservation planning (using the software Zonation) of a GF-based hierarchical classification that summarises spatial patterns in demersal fish composition in the oceans around New Zealand. Progressively more complex Zonation analyses assessed the effects of (i) varying the number of classification groups, (ii) adding information describing species turnover, and (iii) adding information describing spatial variation in demersal fish species richness. The best-performing GF-based conservation ranking used layers describing the distributions of 30 classification groups, demersal fish species turnover between these groups, and species richness. Conservation outcomes from this ranking were only marginally less efficient than those from a more conventional ranking that used 217 individual species distribution layers (7% less efficient). This indicates that GF-based classifications may provide a practical alternative for marine conservation planning. Additional advantages arise from the greater ease with which a single classification layer summarising complex biodiversity patterns can facilitate decision-making in participatory stakeholder processes.
Author(s): Stephenson F, Leathwick JR, Geange S, Moilanen A, Pitcher CR, Lundquist CJ
Publication type: Article
Publication status: Published
Journal: Ocean and Coastal Management
Year: 2021
Volume: 212
Online publication date: 19/08/2021
Acceptance date: 16/08/2021
Date deposited: 23/11/2023
ISSN (print): 1873-524X
ISSN (electronic): 0964-5691
Publisher: Elsevier Ltd
URL: https://doi.org/10.1016/j.ocecoaman.2021.105855
DOI: 10.1016/j.ocecoaman.2021.105855
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