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

Wen Yang Wenjia Hu Bin Chen Hongjian Tan Shangke Su Like Ding Peng Dong Weiwei Yu Jianguo Du

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

doi: 10.1007/s13131-022-2053-x

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

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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  • Figure  1.  Study area and occurrence records of 12 Sciaenidae species in the coastal waters of China.

    Figure  2.  Permutation importance of environment variables in sciaenidae distribution.

    Figure  3.  Prediction of current habitat distribution and future habitat distribution for the 2041–2060 period based on the RCP2.6 and RCP8.5 climate change scenarios.

    Figure  4.  Changes of potential Sciaenidae habitats under the RCP2.6 and RCP8.5 climate scenarios.

    Figure  5.  Centroid shift rates of potential Sciaenidae habitats under different future climate change scenarios.

    Figure  6.  Species richness changes of Sciaenidae under different future climate change scenarios. The black and red framed areas are the Larimichthys polyactis national aquatic germplasm reserves.

    Table  1.   Details of 12 fish species

    GenusSpeciesSurvey data (2004−2009)Global data in study area (2004−2009)
    LarimichthysLarimichthys crocea18339
    LarimichthysLarimichthys polyactis40110
    NibeaNibea albiflora772
    JohniusJohnius grypotus342
    JohniusJohnius belengerii1825
    PennahiaPennahia argentata20112
    PennahiaPennahia macrocephalus956
    PennahiaPennahia pawak7613
    PennahiaPennahia anea12043
    CollichthysCollichthys niveatus352
    CollichthysCollichthys lucidus19611
    MiichthysMiichthys miiuy1561
    下载: 导出CSV

    Table  2.   List of environmental variables for the maximum entropy (MaxEnt) model

    VariableSource (current scenario)Source (future scenarios, 2050s)UnitInitial resolution
    Sea surface temperatureNASA MODIS-Aqua L3 productsNASA MODIS-Aqua L3 products, IPSL: https://esgf-node.ipsl.upmc.fr/projects/cmip6-ipsl/, GFDL: https://www.gfdl.noaa.gov/1 km
    Salinitywww.bio-oracle.orgwww.bio-oracle.org, IPSL: https://esgf-node.ipsl. upmc.fr/projects/cmip6-ipsl/, GFDL: https://www.gfdl.noaa.gov/10 km
    Dissolved oxygenwww.bio-oracle.orgwww.bio-oracle.org, IPSL: https://esgf-node.ipsl. upmc.fr/projects/cmip6-ipsl/, GFDL: https://www.gfdl.noaa.gov/mol/m310 km
    Current velocitywww.bio-oracle.orgwww.bio-oracle.orgm/s10 km
    Bathymetrywww.noaa.gov/https://www.noaa.gov/m2 km
    Distance from landwww.globalfishingwatch.comwww.globalfishingwatch.comm1 km
    下载: 导出CSV

    Table  3.   The area under the curve (AUC) values of the maximum entropy (MaxEnt) models

    SpeciesMean value of AUCStandard deviation
    Larimichthys crocea0.9090.027
    Larimichthys polyactis0.8980.012
    Johnius grypotus0.8890.051
    Johnius belengerii0.8940.018
    Pennahia anea0.9670.012
    Pennahia argentata0.8600.022
    Pennahia macrocephalus0.9080.026
    Pennahia pawak0.9640.012
    Nibea albiflora0.8820.042
    Miichthys miiuy0.9500.021
    Collichthys lucidus0.9220.019
    Collichthys niveatus0.9640.024
    下载: 导出CSV

    Table  4.   Spatial pattern changes in potential Sciaenidae habitats under different future climate change scenarios

    CurrentRCP2.6 scenario
    The total area/km2The total area/km2Rate of change/%Expansion area/km2Rate of expansion/%Stability area/km2Contraction area/km2Rate of contraction/%
    Larimichthys crocea152799.37152344.99–0.3017638.5811.54134706.4118092.9611.84
    Larimichthys polyactis263894.87281568.346.7031606.4411.98249961.9013932.975.28
    Johnius grypotus377112.31391667.463.8636606.169.71355061.3122051.015.85
    Johnius belengerii249780.74348187.6339.40103448.9241.42244738.715042.032.02
    Pennahia anea66919.2479876.6219.3620773.9831.0459102.647816.6011.68
    Pennahia argentata413733.32401618.63–2.9355031.7413.30346586.8967146.4316.23
    Pennahia macrocephalus215773.19152440.02–29.3510417.434.83142022.5973750.6034.18
    Pennahia pawak112929.3786448.11–23.457571.596.7078876.5334052.8430.15
    Nibea albiflora293061.36275219.02–6.0929985.0410.23245233.9847827.3816.32
    Miichthys miiuy62502.8997658.1656.2540436.5264.7057221.645281.258.45
    Collichthys lucidus205666.85269987.4831.2783678.0040.69186309.4819357.379.41
    Collichthys niveatus46941.9265053.4438.5821891.3846.6443162.063779.858.05
    CurrentRCP8.5 scenario
    The total area/km2The total area/km2Rate of change/%Expansion area/km2Rate of expansion/%Stability area/km2Contraction area/km2Rate of contraction/%
    Larimichthys crocea152799.37145773.49–4.6025559.1216.73120214.3732585.0021.33
    Larimichthys polyactis263894.87253112.89–4.0922008.698.34231104.2132790.6612.43
    Johnius grypotus377112.31320600.11–14.998837.482.34311762.6365349.6817.33
    Johnius belengerii249780.74344062.5337.75104544.0541.85239518.4810262.264.11
    Pennahia anea66919.2487944.9131.4233061.6649.4154883.2512035.9917.99
    Pennahia argentata413733.32337727.88–18.3763755.6215.41273972.25139761.0633.78
    Pennahia macrocephalus215773.19238367.6710.4758280.7427.01180086.9435686.2516.54
    Pennahia pawak112929.3779443.02–29.6519620.2017.3759822.8253106.5547.03
    Nibea albiflora293061.36322457.4510.0373018.7424.92249438.7143617.8214.88
    Miichthys miiuy62502.8990946.3645.5141622.4766.5949323.8913179.0021.09
    Collichthys lucidus205666.85270594.0731.57104380.7150.75166213.3639453.4819.18
    Collichthys niveatus46941.9281962.1874.6040628.0586.5541334.135607.7911.95
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    Table  5.   Centroid shifts of potential Sciaenidae habitats under different future climate change scenarios

    SpeciesCentroid latitudeDegree of northward shiftShifts distance/kmShifts rate/(km·(10 a)−1)
    CurrentRCP2.6RCP8.5RCP2.6RCP8.5RCP2.6RCP8.5RCP2.6RCP8.5
    Larimichthys crocea24.62°N25.52°N26.13°N0.90°1.51°108.59181.6624.6841.29
    Larimichthys polyactis35.80°N36.18°N36.40°N0.39°0.60°46.2072.5310.5016.48
    Johnius grypotus33.70°N34.37°N34.41°N0.68°0.71°81.0785.1818.4319.36
    Johnius belengerii32.74°N33.89°N34.07°N1.14°1.33°137.03159.3631.1436.22
    Pennahia anea22.14°N22.46°N23.23°N0.32°1.09°38.07130.988.6529.77
    Pennahia argentata29.05°N30.95°N31.83°N1.90°2.78°227.50334.0651.7075.92
    Pennahia macrocephalus23.51°N24.73°N24.87°N1.22°1.36°145.94163.6733.1737.20
    Pennahia pawak21.72°N22.05°N22.49°N0.32°0.77°38.6392.438.7821.01
    Nibea albiflora29.36°N30.92°N31.37°N1.57°2.02°187.92241.9842.7155.00
    Miichthys miiuy31.99°N33.50°N34.01°N1.50°0.51°180.52242.0041.0355.00
    Collichthys lucidus29.77°N32.32°N33.27°N2.54°3.49°305.25419.0869.3895.25
    Collichthys niveatus34.39°N34.77°N34.96°N0.37°0.57°44.9668.3010.2215.52
    Mean1.07°1.40°128.47182.6029.2041.50
    下载: 导出CSV

    Table  6.   Changes in marine-type aquatic germplasm reserves of the Sciaenidae under climate scenarios

    NameCurrentRCP2.6 scenarioRCP8.5 scenario
    Richness of SciaenidaeRichness of SciaenidaeShared speciesMean change rate of habitat area/%Richness of SciaenidaeShared speciesMean change rate of habitat area/%
    188812.48814.5
    257528.67528.6
    324250.03233.3
    4888–7.888–3.6
    5977–28.877–31.9
    699922.011992.6
    757528.67528.6
    877717.17710.4
    9888–6.697–11.1
    1044412.544137.5
    1135355.04343.8
    1266675.9666.7
    13575443.075251.4
    14888–8.877–14.3
    15676341.776341.7
    1646435.16435.1
    Note: 1: Ningde Guanjing Yellow Croaker Breeding National Aquatic Germplasm Reserve; 2: Haizhou Bay Razor Clam National Aquatic Germplasm Reserve; 3: Changdao Abalone and Sea Urchin National Aquatic Germplasm Reserve; 4: Jiangjia Shazhu Snail National Aquatic Germplasm Reserve; 5: Shangxiachuan Island Chinese Lobster National Aquatic Germplasm Reserve; 6: Donghai Largehead Hairtail National Aquatic Germplasm Reserve; 7: Qiansan Island National Aquatic Germplasm Reserve; 8: Lüsi Fishing Grounds Little Yellow Croaker and Butterfish National Aquatic Germplasm Reserve; 9: Xiangshan Japanese Spanish Mackerel National Aquatic Germplasm Reserve; 10: Changdao Scorpionfish National Aquatic Germplasm Reserve; 11: Qianliyan National Aquatic Germplasm Reserve; 12: Haizhou Bay Chinese Prawn Aquatic Germplasm Reserve; 13: Liaodong Bohai Bay Laizhou Bay National Aquatic Germplasm Reserve; 14: Rudong Razor Clam/Surf Clam National Aquatic Germplasm Reserve; 15: Rizhao Chinese Prawn National Aquatic Germplasm Reserve; 16: Shanhaiguan Coastal Area National Aquatic Germplasm Reserve.
    下载: 导出CSV
  • 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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出版历程
  • 收稿日期:  2022-03-30
  • 录用日期:  2022-06-08
  • 网络出版日期:  2023-02-01
  • 刊出日期:  2023-04-25

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