Abstract
Analysis of the biological traits (BTA) that control how organisms interact with their environment has been used to identify environmental drivers or impacts across large-scales and to explain the importance of biodiversity loss. However, BTA could also be used within risk assessment frameworks or conservation planning by understanding the groups of traits that predict the sensitivity of observed habitats or communities to specific human activities. Deriving sensitivity from biological traits should extend sensitivity predictions to a variety of habitats, especially those in which it would be difficult to conduct experiments due to for example depth, risk to gear and human life and at scales larger than the normal scale of experiments. We used BTA on video transect data collected from a relatively pristine region of the seafloor to determine scales of natural spatial variability, the degree to which predictions of sensitivity are affected by underlying community compositions and the ability of the BTA to provide predictions that differ between three different stressors (extraction, sedimentation and suspended sediments). Three methods were used to assess sensitivity (weighted abundance, abundance of highly sensitive species and number of highly sensitive species). Regardless of method and spatial patterns occurring across the sampled area, BTA was able to distinguish differences in sensitivity at a site to different stressors. BTA also successfully separated differences in community composition from differences in sensitivity to stressors. Conversely, the three methods varied widely in their ability to detect simulated impacts. Differences between the methods reflected underlying processes, suggesting that use of multiple methods would be more informative for spatial planning and allocating conservation priorities than use of a single method. Our results suggest that BTA could be used as a first step in strategic prioritisation of protected areas and as an underlying layer for spatial planning. This article is protected by copyright. All rights reserved.
Original language | English (US) |
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Pages (from-to) | 142-151 |
Number of pages | 10 |
Journal | Conservation Biology |
Volume | 33 |
Issue number | 1 |
DOIs | |
State | Published - Sep 13 2018 |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledgements: The data analysed in this manuscript was provided by Chatham Rock Phosphate Ltd. Funding for this work was provided by two sources: Strategic Science Investment Funding of the Coasts and Oceans Centre (New Zealand National Institute of Water and Atmospheric Research) project COME1701; and the New Zealand Ministry of Business, Innovation and Employment (New Zealand's major source of public good research funding) project "Enabling Management of Offshore Mining" led by Dr Malcolm Clark NIWA. We also thank Malcolm for commenting on a draft of this manuscript.