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  • 1
    Publication Date: 2024-01-30
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Marine heatwaves are known to have a detrimental impact on marine ecosystems, yet predicting when and where they will occur remains a challenge. Here, using a large ensemble of initialized predictions from an Earth System Model, we demonstrate skill in predictions of summer marine heatwaves over large marine ecosystems in the Arabian Sea seven months ahead. Retrospective forecasts of summer (June to August) marine heatwaves initialized in the preceding winter (November) outperform predictions based on observed frequencies. These predictions benefit from initialization during winters of medium to strong El Niño conditions, which have an impact on marine heatwave characteristics in the Arabian Sea. Our probabilistic predictions target spatial characteristics of marine heatwaves that are specifically useful for fisheries management, as we demonstrate using an example of Indian oil sardine (〈italic〉Sardinella longiceps〈/italic〉).〈/p〉
    Description: Plain Language Summary: Marine heatwaves (MHWs) are prolonged extreme events associated with exceptionally high ocean water temperatures. Such events impose heat stress on marine life, and thus predicting such events is beneficial for management applications. In this work we show that the occurrence of MHWs in summer in the Arabian Sea can be skilfully predicted seven month in advance. Our prediction system benefits from the information of sea surface temperature anomalies in the eastern Pacific Ocean in the preceding winter, among other aspects. Our predictions suggest potential for using climate information in fisheries management in this region.〈/p〉
    Description: Key Points: 〈list list-type="bullet"〉 〈list-item〉 〈p xml:lang="en"〉Summer marine heatwaves in the Arabian Sea are predictable seven months in advance〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉The prediction skill in summer is mainly associated with a preceding El Niño event in winter〈/p〉〈/list-item〉 〈list-item〉 〈p xml:lang="en"〉Probabilistic predictions of Arabian Sea area under heatwave can be tailored to benefit fisheries〈/p〉〈/list-item〉 〈/list〉 〈/p〉
    Description: DFG
    Description: Universität Hamburg http://dx.doi.org/10.13039/501100005711
    Description: Cedars‐Sinai Medical Center http://dx.doi.org/10.13039/100013015
    Description: Marine Institute http://dx.doi.org/10.13039/501100001627
    Description: Copernicus Climate Change Service
    Description: Aigéin, Aeráid, agus athrú Atlantaigh
    Description: EU
    Description: http://dx.doi.org/10.7289/V5SQ8XB5
    Description: http://hdl.handle.net/hdl:21.14106/f2fdc61b13828ed5284f4e4ab41e63f8a84c6e52
    Description: http://hdl.handle.net/hdl:21.14106/27e73ed39cd59d2033e018a494e342383db53a0b
    Keywords: ddc:551.46 ; Arabian Sea ; marine heatwaves
    Language: English
    Type: doc-type:article
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  • 2
    Publication Date: 2024-02-07
    Description: Understanding the drivers behind fluctuations in fish populations remains a key objective in fishery science. Our predictive capacity to explain these fluctuations is still relatively low, due to the amalgam of interacting bottom-up and top-down factors, which vary across time and space among and within populations. Gaining a mechanistic understanding of these recruitment drivers requires a holistic approach, combining field, experimental and modelling efforts. Here, we use the Western Baltic Spring-Spawning (WBSS) herring (Clupea harengus) to exemplify the power of this holistic approach and the high complexity of the recruitment drivers (and their interactions). Since the early 2000s, low recruitment levels have promoted intense research on this stock. Our literature synthesis suggests that the major drivers are habitat compression of the spawning beds (due to eutrophication and coastal modification mainly) and warming, which indirectly leads to changes in spawning phenology, prey abundance and predation pressure. Other factors include increased intensity of extreme climate events and new predators in the system. Four main knowledge gaps were identified related to life-cycle migration and habitat use, population structure and demographics, life-stage specific impact of multi-stressors, and predator–prey interactions. Specific research topics within these areas are proposed, as well as the priority to support a sustainable management of the stock. Given that the Baltic Sea is severely impacted by warming, eutrophication and altered precipitation, WBSS herring could be a harbinger of potential effects of changing environmental drivers to the recruitment of small pelagic fishes in other coastal areas in the world.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
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