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      Heat sensitivity of mariculture species in China

      1 , 1 , 1 , 2 , 1 , 2 , 1 , 2
      ICES Journal of Marine Science
      Oxford University Press (OUP)

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          Abstract

          China's mariculture is an indispensable part of the world's aquaculture and helps address food security issues in China and around the globe. However, this industry is facing a grand challenge from global warming. Therefore, it is urgent to assess the sensitivity of the main mariculture species and production modes to the increasing temperature. Here, we first extracted the coastal temperature data from 1465 grid cells (0.25 × 0.25 arcdegree) in the mariculture regions, and then compiled an upper thermal limit as well as culturing modes dataset of forty-two commercially important mariculture species. With these two datasets, we calculated the thermal safety margin (TSM) for each species across its aquaculture regions. Our results showed that several species with low TSMs were particularly sensitive to the current conditions and future warming, and some culturing regions face catastrophic consequences caused by high temperature and potential heatwaves. It is also noted that several mariculture modes like pond farming and mudflat ranching were more vulnerable compared to other mariculture modes. In summary, China's mariculture industry is sensitive to global warming at present and in the future. Our present study also provided tools to assess the risks in mariculture production and suggested solutions for future mitigation and adaptations.

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            Thermal-safety margins and the necessity of thermoregulatory behavior across latitude and elevation.

            Physiological thermal-tolerance limits of terrestrial ectotherms often exceed local air temperatures, implying a high degree of thermal safety (an excess of warm or cold thermal tolerance). However, air temperatures can be very different from the equilibrium body temperature of an individual ectotherm. Here, we compile thermal-tolerance limits of ectotherms across a wide range of latitudes and elevations and compare these thermal limits both to air and to operative body temperatures (theoretically equilibrated body temperatures) of small ectothermic animals during the warmest and coldest times of the year. We show that extreme operative body temperatures in exposed habitats match or exceed the physiological thermal limits of most ectotherms. Therefore, contrary to previous findings using air temperatures, most ectotherms do not have a physiological thermal-safety margin. They must therefore rely on behavior to avoid overheating during the warmest times, especially in the lowland tropics. Likewise, species living at temperate latitudes and in alpine habitats must retreat to avoid lethal cold exposure. Behavioral plasticity of habitat use and the energetic consequences of thermal retreats are therefore critical aspects of species' vulnerability to climate warming and extreme events.
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              Marine heatwaves under global warming

              Marine heatwaves (MHWs) are periods of extreme warm sea surface temperature that persist for days to months1 and can extend up to thousands of kilometres2. Some of the recently observed marine heatwaves revealed the high vulnerability of marine ecosystems3-11 and fisheries12-14 to such extreme climate events. Yet our knowledge about past occurrences15 and the future progression of MHWs is very limited. Here we use satellite observations and a suite of Earth system model simulations to show that MHWs have already become longer-lasting and more frequent, extensive and intense in the past few decades, and that this trend will accelerate under further global warming. Between 1982 and 2016, we detect a doubling in the number of MHW days, and this number is projected to further increase on average by a factor of 16 for global warming of 1.5 degrees Celsius relative to preindustrial levels and by a factor of 23 for global warming of 2.0 degrees Celsius. However, current national policies for the reduction of global carbon emissions are predicted to result in global warming of about 3.5 degrees Celsius by the end of the twenty-first century16, for which models project an average increase in the probability of MHWs by a factor of 41. At this level of warming, MHWs have an average spatial extent that is 21 times bigger than in preindustrial times, last on average 112 days and reach maximum sea surface temperature anomaly intensities of 2.5 degrees Celsius. The largest changes are projected to occur in the western tropical Pacific and Arctic oceans. Today, 87 per cent of MHWs are attributable to human-induced warming, with this ratio increasing to nearly 100 per cent under any global warming scenario exceeding 2 degrees Celsius. Our results suggest that MHWs will become very frequent and extreme under global warming, probably pushing marine organisms and ecosystems to the limits of their resilience and even beyond, which could cause irreversible changes.
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                Author and article information

                Contributors
                Journal
                ICES Journal of Marine Science
                Oxford University Press (OUP)
                1054-3139
                1095-9289
                November 2021
                October 27 2021
                August 31 2021
                November 2021
                October 27 2021
                August 31 2021
                : 78
                : 8
                : 2922-2930
                Affiliations
                [1 ]Key Laboratory of Mariculture of Ministry of Education, College of Fisheries, Ocean University of China, 266003 Qingdao, China
                [2 ]Function Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, 266237 Qingdao, China
                Article
                10.1093/icesjms/fsab168
                fb2fbd3f-16b4-47bb-9ea3-cab8eca9c8ab
                © 2021

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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