Three‐dimensional conservation planning of fish biodiversity metrics to achieve the deep‐sea 30×30 conservation target

Author:

Mathon Laetitia12ORCID,Baletaud Florian134,Lebourges‐Dhaussy Anne5,Lecellier Gaël1,Menkes Christophe1,Bachelier Céline6,Bonneville Claire1,Dejean Tony7,Dumas Mahé1,Fiat Sylvie1,Grelet Jacques8,Habasque Jérémie5,Manel Stéphanie2,Mannocci Laura3ORCID,Mouillot David3,Peran Maëlis15,Roudaut Gildas5,Sidobre Christine1,Varillon David6,Vigliola Laurent1

Affiliation:

1. ENTROPIE, IRD, CNRS, Ifremer, Université de la Réunion Université de la Nouvelle‐Calédonie Nouméa New Caledonia

2. CEFE, Univ. Montpellier, CNRS EPHE‐PSL University, IRD Montpellier France

3. MARBEC Univ. Montpellier, CNRS, Ifremer IRD Montpellier France

4. Soproner, groupe GINGER Nouméa New Caledonia

5. LEMAR, Univ. Brest, CNRS, IRD, Ifremer Plouzané France

6. UAR IMAGO, IRD Nouméa New Caledonia

7. SPYGEN Le Bourget‐du‐Lac France

8. IMAGO, UAR191, IRD DR‐Ouest Plouzané France

Abstract

AbstractAccelerating rate of human impact and environmental change severely affects marine biodiversity and increases the urgency to implement the Convention on Biological Diversity (CBD) 30×30 plan for conserving 30% of sea areas by 2030. However, area‐based conservation targets are complex to identify in a 3‐dimensional (3D) ocean where deep‐sea features such as seamounts have been seldom studied mostly due to challenging methodologies to implement at great depths. Yet, the use of emerging technologies, such as environmental DNA combined with modern modeling frameworks, could help address the problem. We collected environmental DNA, echosounder acoustic, and video data at 15 seamounts and deep island slopes across the Coral Sea. We modeled 7 fish community metrics and the abundances of 45 individual species and molecular operational taxonomic units (MOTUs) in benthic and pelagic waters (down to 600‐m deep) with boosted regression trees and generalized joint attribute models to describe biodiversity on seamounts and deep slopes and identify 3D protection solutions for achieving the CBD area target in New Caledonia (1.4 million km2). We prioritized the identified conservation units in a 3D space, based on various biodiversity targets, to meet the goal of protecting at least 30% of the spatial domain, with a focus on areas with high biodiversity. The relationship between biodiversity protection targets and the spatial area protected by the solution was linear. The scenario protecting 30% of each biodiversity metric preserved almost 30% of the considered spatial domain and accounted for the 3D distribution of biodiversity. Our study paves the way for the use of combined data collection methodologies to improve biodiversity estimates in 3D structured marine environments for the selection of conservation areas and for the use of biodiversity targets to achieve area‐based international targets.

Funder

Agence Nationale de la Recherche

Publisher

Wiley

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