[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2170":3,"related-2170":96},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":24,"tags":26,"primary_topic":9,"secondary_topics":32,"classification":33,"search_phrases":61,"slug":64,"view_count":22,"doi":65,"paper":66,"created_at":95},2170,"Predicting the suitable habitat distribution of greater amberjack using the MaxEnt model with fishery and remote sensing data in the surrounding waters of Taiwan","https:\u002F\u002Fdoi.org\u002F10.1038\u002Fs41598-026-60453-6","Abstract The increasing availability of satellite-derived remotely sensed oceanographic data offers significant potential for evaluating changes in habitat suitability driven by oceanographic phenomena and for informing scientific management strategies, particularly when coupled with maximum entropy (MaxEnt) methods. Oceanographic variables, including sea surface temperature (SST), sea surface salinity (SSS), sea surface height (SSH), sea surface chlorophyll-a concentration (CHL), mixed layer depth (MLD), and eddy kinetic energy (EKE), alongside fishery data from Taiwanese fishing vessels, were collected for the period 2014–2019. The MaxEnt model is a widely employed method for predicting species’ geographical distributions by analyzing species occurrence data in relation to environmental variables. Our results indicated that the annual response curves of habitat suitability were significantly influenced by environmental factors. Specifically, optimal environmental conditions for high habitat suitability were identified as SST > 24 °C, SSS \u003C 35 PSU, SSH between 0.41 and 0.64 m, CHL > 0.22 mg\u002Fm 3 , MLD is between 10 and 17 m, and EKE \u003C 0.007 m 2 \u002Fs 2 . The MaxEnt models exhibited strong predictive performance across all seasons and overall, as evidenced by receiver operating characteristic curve (AUC) values exceeding 0.8 and true skill statistics (TSS) values above 0.7, thereby confirming their accuracy in predicting greater amberjack presence, a reference for future conservation and management priorities.","摘要 卫星遥感海洋学数据的日益普及，为评估海洋学现象驱动的栖息地适宜性变化以及为科学管理策略提供依据带来了巨大潜力，尤其是与最大熵（MaxEnt）方法相结合时。本研究收集了2014—2019年期间的海洋学变量，包括海表温度（SST）、海表盐度（SSS）、海表高度（SSH）、海表叶绿素-a浓度（CHL）、混合层深度（MLD）和涡动能（EKE），以及来自台湾渔船的渔业数据。MaxEnt模型是一种广泛使用的方法，通过分析物种出现数据与环境变量之间的关系来预测物种的地理分布。我们的结果表明，栖息地适宜性的年际响应曲线受到环境因素的显著影响。具体而言，高栖息地适宜性的最优环境条件为：SST > 24 °C，SSS \u003C 35 PSU，SSH在0.41至0.64 m之间，CHL > 0.22 mg\u002Fm³，MLD在10至17 m之间，EKE \u003C 0.007 m²\u002Fs²。MaxEnt模型在所有季节及总体上均表现出较强的预测性能，受试者工作特征曲线（AUC）值超过0.8，真实技巧统计量（TSS）值高于0.7，从而证实了其预测高体鰤出现的准确性，为未来的保护和管理优先事项提供了参考。",null,"Scientific Reports","2026-09-09T00:00:00Z","论文",10,false,72,{"impact":17,"substance":18,"depth":19,"authority":20,"freshness":21,"relevant":22,"comment":23},12,21,17,14,8,1,"利用遥感与渔业数据构建MaxEnt栖息地模型，方法扎实、结论具体，对渔业资源管理与海洋生态保护有参考价值，但属区域性与学科细分研究，公共影响有限。",[25],{"name":10,"url":6},[27,28,29,30,31],"海洋牧场","渔业遥感","栖息地预测","渔业资源管理","MaxEnt模型",[],{"status":34,"locked":14,"version":35,"method":36,"evidence":37},"needs_review","2026-10-22.2","rules",{"candidates":38,"agricultural_evidence":14,"reason":60},[39,48,55],{"code":40,"score":41,"supported":42,"title":43,"abstract":45,"tags":47},"I3",11,true,[44],"remote sensing",[46],"遥感",[],{"code":49,"score":50,"supported":42,"title":51,"abstract":52,"tags":54},"D",3,[],[53],"渔业",[],{"code":56,"score":22,"supported":14,"title":57,"abstract":58,"tags":59},"D2",[],[],[27],"农业相关性需要复核",[62,63],"渔业资源管理 栖息地预测 海洋牧场 渔业遥感","渔业资源管理 栖息地预测","渔业资源管理栖息地预测海洋牧场渔业遥感-2170","10.1038\u002Fs41598-026-60453-6",{"doi":65,"openalex_id":67,"authors":68,"venue":10,"cited_by_count":86,"oa_url":87,"card":88,"direction":92,"ingested_from":94},"W7212047677",[69,72,75,78,80,83],{"name":70,"orcid":71},"Mubarak Mammel","https:\u002F\u002Forcid.org\u002F0000-0002-5546-2531",{"name":73,"orcid":74},"Baker Matovu","https:\u002F\u002Forcid.org\u002F0000-0002-1814-5705",{"name":76,"orcid":77},"Sajna Beegum","https:\u002F\u002Forcid.org\u002F0009-0009-7526-5015",{"name":79,"orcid":9},"Abdul Azeez Pokkathappada",{"name":81,"orcid":82},"Ming‐An Lee","https:\u002F\u002Forcid.org\u002F0000-0001-6970-7643",{"name":84,"orcid":85},"Li-Chi Cheng","https:\u002F\u002Forcid.org\u002F0000-0002-4624-994X",0,"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fs41598-026-60453-6.pdf",{"tldr":89,"method":90,"finding":91,"direction":92,"opportunity":93},"用MaxEnt结合遥感与渔业数据预测台湾周边高体鰤适宜栖息地分布。","MaxEnt模型，2014–2019年SST、SSS、SSH、CHL、MLD、E","高适宜区条件为SST>24°C、SSS\u003C35、SSH 0.41–0.64m、CHL>0.22mg\u002Fm","农业遥感与作物表型","可将该遥感+MaxEnt框架迁移至近海养殖选址与渔业资源管理，并引入气候变化情景预测栖息地迁移。","openalex","2026-09-11T23:30:31.565418Z",{"total":97,"page":22,"page_size":97,"items":98},6,[99,158,197,267,332,387],{"id":100,"title":101,"url":102,"summary":103,"summary_zh":9,"content":104,"source_name":105,"source_url":9,"published_at":106,"category":107,"cover_url":9,"hotness":13,"is_selected":14,"score":108,"score_detail":109,"sources":115,"tags":117,"primary_topic":123,"secondary_topics":127,"classification":128,"search_phrases":153,"slug":156,"view_count":86,"doi":9,"paper":9,"created_at":157},5027,"农业农村部与海南省委省政府举行工作会谈","https:\u002F\u002Fwww.moa.gov.cn\u002Fxw\u002Fzwdt\u002F202610\u002Ft20261014_6488570.htm","10月13日,农业农村部与海南省委省政府举行工作会谈。农业农村部党组书记、部长张柱,海南省委书记冯飞,省委副书记、省长刘小明出席。农业农村部将与海南协同推进崖州湾国家实验室、'南繁硅谷'、国家热带农业科学中心建设,打造农业科技创新高地;支持海南做大做强热带乡村特色产业,加快建设现代化海洋牧场;深入学习运用'千万工程'经验,因地制宜建设宜居宜业和美乡村。海南将充分发挥自由贸易港政策优势,加快'南繁硅谷'建设,高质量打造'蓝色粮仓',大力发展农产品精深加工,扎实推进乡村建设、乡村治理。","本网讯　10月13日，农业农村部与海南省委省政府举行工作会谈。农业农村部党组书记、部长张柱，海南省委书记冯飞，省委副书记、省长刘小明出席会谈。\n\n张柱表示，海南省委省政府坚持把“三农”工作摆在重中之重位置，谋深抓实南繁种业，着力巩固拓展脱贫攻坚成果，大力发展热带特色高效农业，持续深化农村改革，取得一系列新进展新成效。农业农村部将认真贯彻落实习近平总书记关于“三农”工作的重要论述和对海南工作的重要讲话重要指示精神，与海南协同推进崖州湾国家实验室、“南繁硅谷”、国家热带农业科学中心建设，打造农业科技创新高地。支持海南做大做强热带乡村特色产业，加快建设现代化海洋牧场，抓实抓细农业安全生产各项工作。毫不松懈抓好常态化帮扶，提升监测帮扶体系效能，牢牢守住不发生规模性返贫致贫底线。深入学习运用“千万工程”经验，因地制宜建设宜居宜业和美乡村，努力提升乡村基础设施完备度、公共服务便利度、人居环境舒适度。希望部省进一步深化合作，共同推进乡村全面振兴。\n\n冯飞、刘小明感谢农业农村部对海南“三农”工作的大力支持，表示海南将深入贯彻落实习近平总书记对海南工作的重要指示精神，充分发挥自由贸易港政策优势，立足海南特色资源禀赋，进一步加快“南繁硅谷”建设，发挥好崖州湾国家实验室作用，积极打造种业创新策源地，推进热带特色高效农业发展，高质量打造“蓝色粮仓”，大力发展农产品精深加工。切实抓好巩固拓展脱贫攻坚成果考核评估发现问题整改，认真落实常态化帮扶政策，持续抓好产业就业帮扶工作，扎实推进乡村建设、乡村治理，努力推动海南乡村全面振兴迈上新台阶。\n\n农业农村部党组成员、副部长麦尔丹•木盖提，党组成员、副部长潘文博，国家首席兽医师（官）陶怀颖，海南省副省长杨国强出席会谈。","农业农村部新闻办公室 2026 年 10 月 14 日","2026-10-14T00:33:00Z","政策",80,{"impact":110,"substance":111,"depth":20,"authority":112,"freshness":113,"relevant":22,"comment":114},26,18,15,7,"部省高层会谈明确南繁种业、海洋牧场与和美乡村合作方向，政策信号明确但以表态为主，适合进入每日精选。",[116],{"name":105,"url":102},[118,119,27,120,121,122],"种业振兴","千万工程","热带特色农业","南繁硅谷","部省合作",{"code":56,"slug":124,"name":125,"path":126,"parent_code":49},"offshore-aquaculture","深远海养殖与海洋牧场","\u002Ftopic\u002Faquaculture\u002Foffshore-aquaculture",[],{"status":129,"locked":14,"version":35,"method":36,"evidence":130},"classified",{"candidates":131,"agricultural_evidence":42},[132,137,143,148],{"code":56,"score":133,"supported":42,"title":134,"abstract":135,"tags":136},4,[],[27],[27],{"code":138,"score":50,"supported":42,"title":139,"abstract":140,"tags":142},"G5",[],[141],"乡村治理",[],{"code":144,"score":22,"supported":14,"title":145,"abstract":146,"tags":147},"F1",[],[],[118],{"code":149,"score":22,"supported":14,"title":150,"abstract":151,"tags":152},"G4",[],[],[119],[154,155],"农业农村部 海南 工作会谈","崖州湾国家实验室 南繁硅谷","农业农村部海南工作会谈-5027","2026-10-16T00:13:02.714121Z",{"id":159,"title":160,"url":161,"summary":162,"summary_zh":9,"content":163,"source_name":164,"source_url":9,"published_at":165,"category":107,"cover_url":9,"hotness":13,"is_selected":14,"score":108,"score_detail":166,"sources":172,"tags":174,"primary_topic":179,"secondary_topics":180,"classification":181,"search_phrases":192,"slug":195,"view_count":86,"doi":9,"paper":9,"created_at":196},4248,"农业农村部、财政部联合发文明确十五五渔业发展支持政策","https:\u002F\u002Fepaper.nfncb.cn\u002Fnfnc\u002Fcontent\u002F20261001\u002FArticel07001JQ.htm","两部委联合发布通知，明确十五五期间继续实施渔业发展支持政策，按照大稳定小调整原则，不再新增海洋牧场建设项目、不再实施深远海养殖装备建设，已批在建项目2027年底前收尾。重点包括加快推进耕海牧渔、提升现代渔业装备设施、完善渔业基础公共设施、推动渔业绿色循环发展、开展渔业资源调查养护。","֪ͨصҲͳһص㹤͹طƽĹҲصƽһǼӿƽ棬조ɫ֡غصнһҪؼСֺܶĺҵִ裻ִҵװʩˮƽչ洬Զ洬Լͨؿӻȫϵͳʩ豸¸죬ƶ䱸ˮƷӹرʵʩװҵʩչغ۾Զҵؽ裬۷ּƶҵɫѭչƽʩҵֳִʩǿչҵԴ͹ԼŻԶ洬ԼڿɳúҵԴ\n\n֪ͨͬʱطͳƶҵչѹʵ洬ȫΣƽؿӻȫϵͳ۰ȫ衢ˮƷȫȹƽԶ洬תˮֳɫչҵϢˮƷӹͨ߻յȡ","南方农村报 2026-10-01","2026-10-01T00:00:00Z",{"impact":167,"substance":168,"depth":169,"authority":170,"freshness":97,"relevant":22,"comment":171},27,22,16,9,"部委联合发布的十五五渔业支持政策，条款具体、产业影响面广，值得进入每日精选。",[173],{"name":164,"url":161},[27,175,176,177,178],"水产加工","深远海养殖","渔业政策","渔船装备",{"code":56,"slug":124,"name":125,"path":126,"parent_code":49},[],{"status":129,"locked":14,"version":35,"method":36,"evidence":182},{"candidates":183,"agricultural_evidence":42},[184,188],{"code":49,"score":41,"supported":42,"title":185,"abstract":186,"tags":187},[53],[53],[],{"code":56,"score":21,"supported":42,"title":189,"abstract":190,"tags":191},[],[176,27],[27,176],[193,194],"农业农村部 财政部 十五五 渔业","海洋牧场 深远海养殖 渔船改造","农业农村部财政部十五五渔业-4248","2026-10-06T00:04:59.276084Z",{"id":198,"title":199,"url":200,"summary":201,"summary_zh":202,"content":9,"source_name":203,"source_url":200,"published_at":165,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":204,"score_detail":205,"sources":207,"tags":209,"primary_topic":214,"secondary_topics":220,"classification":221,"search_phrases":243,"slug":246,"view_count":247,"doi":248,"paper":249,"created_at":266},3972,"Interpretable machine learning reveals threshold effects of blue mussel (Mytilus edulis) fouling on the hydrodynamic response of the marine aquaculture netting","https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.compag.2026.112492","Interpretable machine learning reveals threshold effects of blue mussel (Mytilus edulis) fouling on the hydrodynamic response of the marine aquaculture netting。Computers and Electronics in Agriculture","可解释机器学习揭示蓝贻贝（Mytilus edulis）污损对海水养殖网箱水动力响应的阈值效应。","Computers and Electronics in Agriculture",74,{"impact":17,"substance":18,"depth":111,"authority":20,"freshness":170,"relevant":22,"comment":206},"可解释机器学习揭示贻贝污损对养殖网衣水动力响应的阈值效应，方法新颖、结论可靠，对深远海养殖装备运维有参考价值，但属细分领域研究，影响面有限。",[208],{"name":203,"url":200},[210,211,212,27,213],"智慧农业","机器学习","水产养殖","养殖装备",{"code":215,"slug":216,"name":217,"path":218,"parent_code":219},"I2","agricultural-ai","农业AI与大模型","\u002Ftopic\u002Fdigital-agriculture\u002Fagricultural-ai","I",[],{"status":129,"locked":14,"version":35,"method":36,"evidence":222},{"candidates":223,"agricultural_evidence":42},[224,229,234,238],{"code":215,"score":112,"supported":42,"title":225,"abstract":227,"tags":228},[226],"machine learning",[211,226],[211],{"code":49,"score":17,"supported":42,"title":230,"abstract":232,"tags":233},[231],"aquaculture",[231],[212],{"code":56,"score":22,"supported":14,"title":235,"abstract":236,"tags":237},[],[],[27],{"code":239,"score":22,"supported":14,"title":240,"abstract":241,"tags":242},"I1",[],[],[210],[244,245],"紫贻贝 污损 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