Volume 42 Issue 4
Apr.  2023
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Wen Yang, Wenjia Hu, Bin Chen, Hongjian Tan, Shangke Su, Like Ding, Peng Dong, Weiwei Yu, Jianguo Du. Impact of climate change on potential habitat distribution of Sciaenidae in the coastal waters of China[J]. Acta Oceanologica Sinica, 2023, 42(4): 59-71. doi: 10.1007/s13131-022-2053-x
Citation: Wen Yang, Wenjia Hu, Bin Chen, Hongjian Tan, Shangke Su, Like Ding, Peng Dong, Weiwei Yu, Jianguo Du. Impact of climate change on potential habitat distribution of Sciaenidae in the coastal waters of China[J]. Acta Oceanologica Sinica, 2023, 42(4): 59-71. doi: 10.1007/s13131-022-2053-x

Impact of climate change on potential habitat distribution of Sciaenidae in the coastal waters of China

doi: 10.1007/s13131-022-2053-x
Funds:  The Xiamen Youth Innovation Fund under contract No. 3502Z20206096; the National Key Research and Development Program of China under contract No. 2019YFE0124700; the National Natural Science Foundation of China under contract Nos 42176153, 41906127, and 42076163; the National Program on Global Change and Air-Sea Interaction under contract No. HR01-200701.
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  • Corresponding author: dujianguo@tio.org.cn
  • Received Date: 2022-03-30
  • Accepted Date: 2022-06-08
  • Available Online: 2023-02-01
  • Publish Date: 2023-04-25
  • Climate change has affected and will continue to affect the spatial distribution patterns of marine organisms. To understand the impact of climate change on the distribution patterns and species richness of the Sciaenidae in China’s coastal waters, the maximum entropy model was used to combine six environmental factors and predict the potential distribution of 12 major species of Sciaenidae by 2050s under Representative Concentration Pathways (RCPs) 2.6 and 8.5. The results showed that the average area under the receiver operating characteristic curve of the model was 0.917, indicating that the model predictions were accurate and reliable. The main driving factors affecting the potential distribution of these fishes were dissolved oxygen, salinity, and sea surface temperature (SST). There was an overall northward shift in the potential habitat areas of these fishes under the two climate scenarios. The total potential habitat areas of Larimichthys polyactis, Pennahia argentata, and Pennahia pawak decreased under both climate scenarios, while the total habitat area of Johnius belengerii, Pennahia anea, Miichthys miiuy, Collichthys lucidus, and Collichthys niveatus increased, suggesting that these might be loser and winner species, respectively. The expansion rate, contraction rate, degree of centroid change, and species richness in the potential habitats were generally more significant under RCP8.5 than RCP2.6. The mean shift rates of the potential distribution were 41.50 km/(10 a) and 29.20 km/(10 a) under RCP8.5 and RCP2.6, respectively. The changes in Sciaenidae species richness under climate change were bounded by the Changjiang River Estuary waters, with obvious north-south differences. Some waters with increased species richness may become refuges for Sciaenidae fishes under climate change. The richness and habitat area change rate of some aquatic germplasm resources will decrease, meanings that these reserves are more sensitive to climate change, and more attention should be paid to the potential challenges and opportunities for fishery managers. This study may provide a scientific basis for the management and conservation of Sciaenidae in China under climate change.
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  • Andrews S, Leroux S J, Fortin M J. 2020. Modelling the spatial–temporal distributions and associated determining factors of a keystone pelagic fish. ICES Journal of Marine Science, 77(7–8): 2776–2789
    Assis J, Tyberghein L, Bosch S, et al. 2018. Bio-ORACLE v2.0: extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3): 277–284. doi: 10.1111/geb.12693
    Bindoff N L, Cheung W W L, Kairo J G, et al. 2019. Changing ocean, marine ecosystems, and dependent communities. In: Pörtner H O, Roberts D C, Masson-Delmotte V, et al., eds. IPCC Special Report on the Ocean and Cryosphere in a Changing Climate. Geneva: Intergovernmental Panel on Climate Change, 477–587
    Bohorquez J J, Xue Guifang, Frankstone T, et al. 2021. China’s little-known efforts to protect its marine ecosystems safeguard some habitats but omit others. Science Advances, 7(46): eabj1569. doi: 10.1126/sciadv.abj1569
    Brown J L. 2014. SDMtoolbox: a python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses. Methods in Ecology and Evolution, 5(7): 694–700. doi: 10.1111/2041-210X.12200
    Burrows M T, Schoeman D S, Buckley L B, et al. 2011. The pace of shifting climate in marine and terrestrial ecosystems. Science, 334(6056): 652–655. doi: 10.1126/science.1210288
    Burrows M T, Schoeman D S, Richardson A J, et al. 2014. Geographical limits to species-range shifts are suggested by climate velocity. Nature, 507(7493): 492–495. doi: 10.1038/nature12976
    Chen Peng, Chen Xinjun. 2016. Analysis of habitat distribution of Argentine shortfin squid (Illex argentinus) in the Southwest Atlantic Ocean using maximum entropy model. Journal of Fisheries of China (in Chinese), 40(6): 893–902
    Chen Shuang, Guo Ai, Chen Xinjun. 2019. Distribution forecasting of habitat of chub mackerel (Scomber japonicus) during the climate change in the coastal waters. Journal of Fisheries of China (in Chinese), 43(3): 593–604
    Chen Yunlong, Shan Xiujuan, Ovando D, et al. 2021a. Predicting current and future global distribution of black rockfish (Sebastes schlegelii) under changing climate. Ecological Indicators, 128: 107799. doi: 10.1016/j.ecolind.2021.107799
    Chen Jinghui, Wang Xuefang, Tian Siquan, et al. 2021b. A review of the development of fishery resources monitoring in the Yangtze River Estuary and its adjacent waters. Resources and Environment in the Yangtze Basin (in Chinese), 30(1): 122–136
    Cheung W W L, Brodeur R D, Okey T A, et al. 2015. Projecting future changes in distributions of pelagic fish species of Northeast Pacific shelf seas. Progress in Oceanography, 130: 19–31. doi: 10.1016/j.pocean.2014.09.003
    Cheung W W L, Lam V W Y, Sarmiento J L, et al. 2009. Projecting global marine biodiversity impacts under climate change scenarios. Fish and Fisheries, 10(3): 235–251. doi: 10.1111/j.1467-2979.2008.00315.x
    Chinese Offshore Investigation, Assessment Project Office of the State Oceanic Administration. 2006. Technical Specifications for Marine Biological and Ecological Investigation for Chinese Offshore Investigation and Assessment Project (in Chinese). Beijing: China Ocean Press
    Costa M D P, Wilson K A, Dyer P J, et al. 2021. Potential future climate-induced shifts in marine fish larvae and harvested fish communities in the subtropical southwestern Atlantic Ocean. Climatic Change, 165(3–4): 66
    Du Jianguo, Cheung W W L, Chen Bin, et al. 2012. Progress and prospect of climate change and marine biodiversity. Biodiversity Sceince (in Chinese), 20(6): 745–754
    Dufresne J L, Foujols M A, Denvil S, et al. 2013. Climate change projections using the IPSL-CM5 earth system model: from CMIP3 to CMIP5. Climate Dynamics, 40(9–10): 2123–2165
    Dunne J P, John J G, Adcroft A J, et al. 2012. GFDL’s ESM2 global coupled climate–carbon earth system models. Part I: physical formulation and baseline simulation characteristics. Journal of Climate, 25(19): 6646–6665. doi: 10.1175/JCLI-D-11-00560.1
    Guisan A, Thuiller W. 2005. Predicting species distribution: offering more than simple habitat models. Ecology Letters, 8(9): 993–1009. doi: 10.1111/j.1461-0248.2005.00792.x
    Guisan A, Zimmermann N E. 2000. Predictive habitat distribution models in ecology. Ecological Modelling, 135(2–3): 147–186
    Han Qingpeng, Shan Xiujuan, Wan Rong, et al. 2019. Spatiotemporal distribution and the estimated abundance indices of Larimichthys polyactis in winter in the Yellow Sea based on geostatistical delta-generalized linear mixed models. Journal of Fisheries of China (in Chinese), 43(7): 1603–1614
    Hastings R A, Rutterford L A, Freer J J, et al. 2020. Climate change drives poleward increases and equatorward declines in marine species. Current Biology, 30(8): 1572–1577. doi: 10.1016/j.cub.2020.02.043
    Hu Wenjia, Du Jianguo, Su Shangke, et al. 2022. Effects of climate change in the seas of China: predicted changes in the distribution of fish species and diversity. Ecological Indicators, 134: 108489. doi: 10.1016/j.ecolind.2021.108489
    Jiang Mei, Shen Xinqiang, Chen Lianfang. 2006. Relationship between with abundance distribution of fish eggs, larvae and environmental factors in the Changjiang Estuary and vicinity waters in spring. Marine Enviromental Science (in Chinese), 25(2): 37–39, 44
    Jones M C, Cheung W W L. 2015. Multi-model ensemble projections of climate change effects on global marine biodiversity. ICES Journal of Marine Science, 72(3): 741–752. doi: 10.1093/icesjms/fsu172
    Kang Bin, Pecl G T, Lin Longshan, et al. 2021. Climate change impacts on China’s marine ecosystems. Reviews in Fish Biology and Fisheries, 31(3): 599–629. doi: 10.1007/s11160-021-09668-6
    Kass J M, Muscarella R, Galante P J, et al. 2021. ENMeval 2.0: redesigned for customizable and reproducible modeling of species’ niches and distributions. Methods in Ecology and Evolution, 12(9): 1602–1608. doi: 10.1111/2041-210X.13628
    Kumar S, Graham J, West A M, et al. 2014. Using district-level occurrences in MaxEnt for predicting the invasion potential of an exotic insect pest in India. Computers and Electronics in Agriculture, 103: 55–62. doi: 10.1016/j.compag.2014.02.007
    Lenoir S, Beaugrand G, Lecuyer É. 2011. Modelled spatial distribution of marine fish and projected modifications in the North Atlantic Ocean. Global Change Biology, 17(1): 115–129. doi: 10.1111/j.1365-2486.2010.02229.x
    Lenoir J, Bertrand R, Comte L, et al. 2020. Species better track climate warming in the oceans than on land. Nature Ecology & Evolution, 4(8): 1044–1059. doi: 10.1038/s41559-020-1198-2
    Liang Jie, Peng Yuhui, Zhu Ziqian, et al. 2021. Impacts of changing climate on the distribution of migratory birds in China: habitat change and population centroid shift. Ecological Indicators, 127: 107729. doi: 10.1016/j.ecolind.2021.107729
    Liu Ruiyu. 2008. Checklist of Marine Biota of China Seas (in Chinese). Beijing: Science Press
    Liu Xiaoxiao, Wang Jin, Xu Binduo, et al. 2017. Impacts of fishing pressure and climate change on catches of small yellow croaker in the Yellow Sea and the Bohai Sea. Periodical of Ocean University of China (in Chinese), 47(8): 58–64
    Liu Zunlei, Yang Linlin, Yuan Xingwei, et al. 2020. Overwintering distribution and its environmental determinants of small yellow croaker based on ensemble habitat suitability modeling. Chinese Journal of Applied Ecology (in Chinese), 31(6): 2076–2086
    Lotze H K, Tittensor D P, Bryndum-Buchholz A, et al. 2019. Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change. Proceedings of the National Academy of Sciences of the United States of America, 116(26): 12907–12912. doi: 10.1073/pnas.1900194116
    Ma Jin, Huang Jinling, Chen Jinhui, et al. 2020. Analysis of spatiotemporal fish density distribution and its influential factors based on Generalized Additive Model (GAM) in the Yangtze River Estuary. Journal of Fisheries of China (in Chinese), 44(6): 936–946
    Melo-Merino S M, Reyes-Bonilla H, Lira-Noriega A. 2020. Ecological niche models and species distribution models in marine environments: a literature review and spatial analysis of evidence. Ecological Modelling, 415: 108837. doi: 10.1016/j.ecolmodel.2019.108837
    Morley J W, Selden R L, Latour R J, et al. 2018. Projecting shifts in thermal habitat for 686 species on the North American continental shelf. PLoS ONE, 13(5): e0196127. doi: 10.1371/journal.pone.0196127
    Muscarella R, Galante P J, Soley-Guardia M, et al. 2020. ENMeval: automated runs and evaluations of ecological niche models. https://mran.microsoft.com/snapshot/2020-12-31/web/packages/ENMeval/index.html[2020-09-12]
    Pachauri R K, Allen M R, Barros V R, et al. 2014. Climate change 2014: Synthesis report. Contribution of Working Groups I, II, and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Geneva: IPCC
    Pei Rude, Ma Qiuyun, Tian Siquan, et al. 2021. Growth, maturity and mortality of Johnius distinctus and J. belangerii in offshore waters of southern Zhejiang Province. South China Fisheries Science (in Chinese), 17(6): 39–47
    Perry A L, Low P J, Ellis J R, et al. 2005. Climate change and distribution shifts in marine fishes. Science, 308(5730): 1912–1915. doi: 10.1126/science.1111322
    Petatán-Ramírez D, Whitehead D A, Guerrero-Izquierdo T, et al. 2020. Habitat suitability of Rhincodon typus in three localities of the Gulf of California: environmental drivers of seasonal aggregations. Journal of Fish Biology, 97(4): 1177–1186. doi: 10.1111/jfb.14496
    Phillips S J, Dudík M. 2008. Modeling of species distributions with MAXENT: new extensions and a comprehensive evaluation. Ecography, 31(2): 161–175. doi: 10.1111/j.0906-7590.2008.5203.x
    Radosavljevic A, Anderson R P. 2014. Making better MAXENT models of species distributions: complexity, overfitting and evaluation. Journal of Biogeography, 41(4): 629–643. doi: 10.1111/jbi.12227
    Segurado P, Araujo M B. 2004. An evaluation of methods for modelling species distributions. Journal of Biogeography, 31(10): 1555–1568. doi: 10.1111/j.1365-2699.2004.01076.x
    Shen Shichang, Huang Liangmin, Wang Jiaqiao, et al. 2020. A preliminary study on the biological characteristics of Johnius belengerii inhabiting Xiamen Sea Are. Transactions of Oceanology and Limnology (in Chinese), 42(1): 129–135
    Sheng Qiang, Ru Huijun, Li Yunfeng, et al. 2019. The distribution pattern of national aquatic germplasm reserves in China. Journal of Fisheries of China (in Chinese), 43(1): 62–80
    Silva C, Leiva F, Lastra J. 2019. Predicting the current and future suitable habitat distributions of the anchovy (Engraulis ringens) using the Maxent model in the coastal areas off central-northern Chile. Fisheries Oceanography, 28(2): 171–182. doi: 10.1111/fog.12400
    State Oceanic Administration. 2016. Atlas of China’s Coastal Seas: Marine Life and Ecology (in Chinese). Beijing: China Ocean Press, 2016
    Tabor K, Williams J W. 2010. Globally downscaled climate projections for assessing the conservation impacts of climate change. Ecological Applications, 20(2): 554–565. doi: 10.1890/09-0173.1
    Tan Hongjian, Cai Rongshuo, Huo Yunlong, et al. 2020. Projections of changes in marine environment in coastal China seas over the 21st century based on CMIP5 models. Journal of Oceanology and Limnology, 38(6): 1676–1691. doi: 10.1007/s00343-019-9134-5
    Thuiller W, Guéguen M, Renaud J, et al. 2019. Uncertainty in ensembles of global biodiversity scenarios. Nature Communications, 10(1): 1446. doi: 10.1038/s41467-019-09519-w
    Tyberghein L, Verbruggen H, Pauly K, et al. 2012. Bio-ORACLE: a global environmental dataset for marine species distribution modelling. Global Ecology and Biogeography, 21(2): 272–281. doi: 10.1111/j.1466-8238.2011.00656.x
    Wang Miao, Hong Bo, Zhang Yuping, et al. 2016. Spring and summer fish community structure in northern Hangzhou Bay. Journal of Hydroecology (in Chinese), 37(5): 75–81
    Wang Xuehui, Qiu Yongsong, Du Feiyan, et al. 2019. Roles of fishing and climate change in long-term fish species succession and population dynamics in the outer Beibu Gulf, South China Sea. Acta Oceanologica Sinica, 38(10): 1–8. doi: 10.1007/s13131-019-1484-5
    Wang Linlong, Zhang Zhixin, Lin Longshan, et al. 2021. Redistribution of the lizardfish Harpadon nehereus in coastal waters of China due to climate change. Hydrobiologia, 848(20): 4919–4932. doi: 10.1007/s10750-021-04682-y
    Worm B, Lotze H K. 2021. Marine biodiversity and climate change. In: Letcher T M, ed. Climate Change: Observed Impacts on Planet Earth. 3rd ed. Amsterdam: Elsevier, 445–464
    Xie Yangjie, Li Jun, Huang Liangmin, et al. 2012. Temporal and spatial variations of sciaenid fish resources in Fujian coastal waters in 2006 and 2007. Journal of Applied Oceanography (in Chinese), 31(3): 403–411
    Xu Zhaoli, Chen Jiajie. 2010. Analysis to population division and migratory routine of populations and migratory routines of Argyrosomus argentatus in the North China waters. Acta Ecologica Sinica (in Chinese), 30(23): 6442–6450
    Yang Wen, Hu Wenjia, Chen Bin, et al. 2022. The potential distribution of main Sciaenidae species in coastal China based on MaxEnt model. Chinese Journal of Ecology (in Chinese), 41(9): 1825–1834
    Yang Gang, Zhang Tao, Zhuang Ping, et al. 2014. Preliminary assessment of habitat of juvenile Collichthys lucidus in the Yangtze Estuary. Chinese Journal of Applied Ecology (in Chinese), 25(8): 2418–2424
    Yao Cuiluan, Somero G N. 2014. The impact of ocean warming on marine organisms. Chinese Science Bulletin, 59(5): 468–479
    Yu Dan, Chen Ming, Zhou Zhuocheng, et al. 2013. Global climate change will severely decrease potential distribution of the East Asian coldwater fish Rhynchocypris oxycephalus (Actinopterygii, Cyprinidae). Hydrobiologia, 700(1): 23–32. doi: 10.1007/s10750-012-1213-y
    Yuan Xingwei, Liu Zunlei, Cheng Jiahua, et al. 2017. Impact of climate change on nekton community structure and some commercial species in the offshore area of the northern East China Sea in winter. Acta Ecologica Sinica (in Chinese), 37(8): 2796–2808
    Zeng Jiawei, Lin Kun, Wang Xuefeng, et al. 2019. Fish community structure and its relationship with environmental factors in Leizhou Bay. Journal of Fishery Sciences of China (in Chinese), 26(1): 108–117. doi: 10.3724/SP.J.1118.2019.18378
    Zhang Jiarong. 2020. Research on the habitat distribution model of Albacore (Thunnus alalunga) in the South Pacific (in Chinese) [dissertation]. Shanghai: Shanghai Ocean University
    Zhang Zhixin, Mammola S, Xian Weiwei, et al. 2020a. Modelling the potential impacts of climate change on the distribution of ichthyoplankton in the Yangtze Estuary, China. Diversity and Distributions, 26(1): 126–137. doi: 10.1111/ddi.13002
    Zhang Xiaomin, Shi Yongchuang, Li Fan, et al. 2020b. Prediction of potential fishing ground for Pacific saury (Cololabis saira) based on MAXENT model. Journal of Shanghai Ocean University (in Chinese), 29(2): 280–286
    Zhang Zhixin, Xu Shengyong, Capinha C, et al. 2019. Using species distribution model to predict the impact of climate change on the potential distribution of Japanese whiting Sillago japonica. Ecological Indicators, 104: 333–340. doi: 10.1016/j.ecolind.2019.05.023
    Zhang Linlin, Zhou Yongdong, Jiang Rijin, et al. 2020c. Spatial niche of major fish species in spring in the coastal waters of central and southern Zhejiang Province, China. Chinese Journal of Applied Ecology (in Chinese), 31(2): 659–666
    Zhu Yugui, Zhang Zhixin, Reygondeau G, et al. 2020. Projecting changes in the distribution and maximum catch potential of warm water fishes under climate change scenarios in the Yellow Sea. Diversity and Distributions, 26(7): 806–817. doi: 10.1111/ddi.13032
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