| Literature DB >> 32531093 |
Lisa A Levin1, Chih-Lin Wei2, Daniel C Dunn3, Diva J Amon4, Oliver S Ashford1, William W L Cheung5, Ana Colaço6, Carlos Dominguez-Carrió6, Elva G Escobar7, Harriet R Harden-Davies8, Jeffrey C Drazen9, Khaira Ismail10, Daniel O B Jones11, David E Johnson12, Jennifer T Le1, Franck Lejzerowicz13, Satoshi Mitarai14, Telmo Morato6, Sandor Mulsow15, Paul V R Snelgrove16, Andrew K Sweetman17, Moriaki Yasuhara18.
Abstract
Climate change manifestation in the ocean, through warming, oxygen loss, increasing acidification, and changing particulate organic carbon flux (one metric of altered food supply), is projected to affect most deep-ocean ecosystems concomitantly with increasing direct human disturbance. Climate drivers will alter deep-sea biodiversity and associated ecosystem services, and may interact with disturbance from resource extraction activities or even climate geoengineering. We suggest that to ensure the effective management of increasing use of the deep ocean (e.g., for bottom fishing, oil and gas extraction, and deep-seabed mining), environmental management and developing regulations must consider climate change. Strategic planning, impact assessment and monitoring, spatial management, application of the precautionary approach, and full-cost accounting of extraction activities should embrace climate consciousness. Coupled climate and biological modeling approaches applied in the water and on the seafloor can help accomplish this goal. For example, Earth-System Model projections of climate-change parameters at the seafloor reveal heterogeneity in projected climate hazard and time of emergence (beyond natural variability) in regions targeted for deep-seabed mining. Models that combine climate-induced changes in ocean circulation with particle tracking predict altered transport of early life stages (larvae) under climate change. Habitat suitability models can help assess the consequences of altered larval dispersal, predict climate refugia, and identify vulnerable regions for multiple species under climate change. Engaging the deep observing community can support the necessary data provisioning to mainstream climate into the development of environmental management plans. To illustrate this approach, we focus on deep-seabed mining and the International Seabed Authority, whose mandates include regulation of all mineral-related activities in international waters and protecting the marine environment from the harmful effects of mining. However, achieving deep-ocean sustainability under the UN Sustainable Development Goals will require integration of climate consideration across all policy sectors.Entities:
Keywords: biodiversity maintenance; bottom fishing; climate projections; conservation; deep ocean; deep-seabed mining; environmental management; habitat suitability modeling; larval connectivity modeling
Year: 2020 PMID: 32531093 PMCID: PMC7496832 DOI: 10.1111/gcb.15223
Source DB: PubMed Journal: Glob Chang Biol ISSN: 1354-1013 Impact factor: 10.863
FIGURE 1Climate projections for the RCP 8.5 scenario for the global seafloor and two regions targeted for deep‐seabed mining, the Clarion Clipperton Zone (CCZ; left panels) and the northern Mid‐Atlantic Ridge (MAR right panels). (a) Time of Emergence: the year when future variability exceeds historical variability for all climate changes in temperature, oxygen, pH, and food supply (i.e., annual standard deviation between 1951 and 2000). (b) Cumulative negative climate hazard refers to the changes in warming, oxygen loss, acidification, and declining food supply (POC flux) relative to the historical variability by 2041–2060. (c) Cumulative negative climate hazard by 2081–2100. The gray polygons in the global map show the extent of the CCZ and MAR, respectively. Projections for the CCZ (left bottom panel in a–c) suggest strong regional variations among exploration contracts (brown), reserve areas (green), and areas of particular environmental interest (APEIs—gray), which are designated no‐mining zones in the CCZ. The right sub‐panels show the exploration contracts (brown) and ridge (gray) within a 150‐mile MAR buffer zone
Minimum and maximum values of time of emergence and cumulative negative climate hazard under climate scenarios RCP 8.5 and 2.6 for four climate drivers (temperature, O2, pH, and POC flux) in the global ocean, Clarion Clipperton Zone (CCZ), and Mid‐Atlantic Ridge (MAR)
| Area | RCP 8.5 | RCP 2.6 | ||
|---|---|---|---|---|
| Min | Max | Min | Max | |
| Time of emergence for all four climate drivers | ||||
| Global | 2023 | >2100 | 2022 | >2100 |
| CCZ | 2028 | >2100 | 2033 | >2100 |
| MAR | 2031 | >2100 | 2036 | >2100 |
| Cumulative negative climate hazard by 2041–2060 | ||||
| Global | 0.0 | 67.4 | 0.0 | 63.6 |
| CCZ | 6.3 | 38.5 | 6.0 | 36.6 |
| MAR | 8.9 | 24.9 | 8.7 | 20.7 |
| Cumulative negative climate hazard by 2081–2100 | ||||
| Global | 0.0 | 148.2 | 0.7 | 113.1 |
| CCZ | 13.5 | 105.1 | 12.7 | 102.4 |
| MAR | 14.8 | 45.7 | 11.2 | 39.1 |
FIGURE 2Global warming causes losses and increases of potential larval transport among hydrothermal vents in the Southwestern Pacific Ocean. (a) Transport frequencies (how often source and destination vent fields can be connected by ocean circulation) are computed under the RCP 8.5 scenario from years 2090 to 2099, normalized by the preindustrial control case. Enhanced transport (>100% increases in transport frequencies) is indicated with red lines, while reduced transport (<50% reductions) is indicated with blue lines. (b) White lines indicate lost transport (potential larval transport present in the preindustrial control case that vanishes under the RCP 8.5 scenario). Transport frequencies from all active vent fields in the western Pacific Ocean were assessed using a regional ocean modeling system nested within the CMIP5 coupled global climate models. We set dispersal depth to 1,000 m below the sea surface. Transport time is set to 180 days, a period long enough to cover larval development times of marine species under the mean water temperature of 5°C at 1,000 m (O'Connor et al., 2007)
FIGURE 3Forecasted cumulative climate refugia areas (sensu Keppel & Wardell‐Johnson, 2012) under future (2081–2100) environmental conditions under RCP 8.5 for (a) six cold‐water corals: 1. Lophelia pertusa (recently reclassified as Desmophyllum pertusum), 2. Madrepora oculata, 3. Desmophyllum dianthus, 4. Acanthogorgia armata, 5. Acanella arbuscula, 6. Paragorgia arborea and (b) six deep‐water commercially important fishes: 1. Helicolenus dactylopterus, 2. Sebastes mentella, 3. Gadus morhua, 4. Hippoglossoides platessoides, 5. Reinhardtius hippoglossoides, 6. Coryphaenoides rupestris) in the North Atlantic Ocean. Areas were identified from binary maps built with an ensemble modeling approach and the maximum sensitivity and specificity thresholds (MSS). The model outputs used to build Figure3 were published in Morato et al. (2020) 'Areas were identified from binary maps built with an ensemble modeling approach and the maximum sensitivity and specificity threshold (MSS)'
International reports or fora addressing or considering climate change relevant to the deep ocean
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UNFCCC: The Intergovernmental Panel on Climate Change (IPCC) Special Report on the Ocean and Cryosphere in a Changing Climate inextricably links climate change and the deep ocean (Bindoff et al., Sectoral marine resource interests Food and Agriculture Organization (fisheries) International Maritime Organization (shipping) International Seabed Authority (mining) International Cable Protection Committee (sub‐sea cables) Biodiversity protection interests Convention on Biological Diversity (CBD) Post‐2020 Global Biodiversity Framework Negotiations for a new international legally binding instrument on conservation and sustainable use of marine biological diversity of areas beyond national jurisdiction (BBNJ) Intergovernmental Science‐Policy Platform on Biodiversity and Ecosystem Services (IPBES) The Convention on the Conservation of Antarctic Marine Living Resources (CCAMLR) Scientific research plans UN Decade of Ocean Science for Sustainable Development Global Ocean Observing System Deep Ocean Observing Strategy |