2021, Vol. 28 
2. 大连海洋大学，设施渔业教育部重点实验室，辽宁 大连 116023
3. 默多克大学哈里巴特勒研究所可持续水生生态系统中心，西澳大利亚 珀斯 6150
4. 默多克大学，环境和保护科学，西澳大利亚 珀斯 6150
2. Key Laboratory of Environment Controlled Aquaculture, Ministry of Education, Dalian Ocean University, Dalian 116023, China
3. Centre for Sustainable Aquatic Ecosystems, Harry Butler Institute, Murdoch University, Perth, Western 6150, Australia
4. Environmental and Conservation Sciences, Murdoch University, Perth, Western 6150, Australia
20世纪以来，由于人类活动加剧和全球环境变化，海洋生态系统面临着前所未有的威胁，近海生境退化和生物资源衰退问题日渐突出。为有效保护近海生态环境，实现基于生态系统的管理，需要在大空间尺度上广泛评估海洋生物多样性状况。在生物栖息地范围内的采样应符合生态保护理念，基于对无破坏性海洋生物监测技术在生物栖息地的应用需求，从20世纪60年代开始，水下目视调查技术(underwater visual census, UVC)一直是监测浅水(<40 m)海域生物群落的主要手段[1], UVC在估算鱼类数量和多样性方面的优劣性已被相关研究所讨论[2-4], 其主要局限性在于需要潜水员水下监测，无法在较深海域进行评估。随着摄像机生产成本的降低和海量信息存储设备的快速发展，一系列水下视频调查技术逐渐得以研发与应用[5], 可有效弥补传统UVC 调查技术的不足。
诱饵式远程水下视频技术(baited remote underwater video, BRUV)是一种基于饵料诱集鱼类并进行视频录制，分析提取视频数据用于评估鱼类相对丰度和分析物种行为的监测技术[6]。主要由摄像机、防水外壳、诱饵臂、装有饵料的网袋或容器，以及抗腐蚀框架等组成(图1, 图2), 根据摄像机数量可分为单摄像机的BRUV (Mono- BRUV)和双摄像机的立体BRUV (Stereo-BRUV)。Mono- BRUV通常利用安装在诱饵臂后方的单一摄像机对诱饵视野进行拍摄(图 1), 而Stereo- BRUV则由面对诱饵两侧特定角度的双摄像机组成，经过校准后起到立体摄影效果。相比Mono- BRUV, Stereo-BRUV除了分析鱼类相对丰度外，还可精确测量鱼的体长信息[7-8], 而Stereo-BRUV用于精确测量鱼体体长的核心组件是位于诱饵袋上方的同步二极管，即环绕圆周闪烁的LED灯(图2), 研究人员在观看两个视频进行鱼体体长校准时，通过观察两组灯光的闪烁是否一致，来确保视频同步播放，进而可进行鱼体体长的估算。与Stereo- BRUV相比，Mono-BRUV的结构较为轻便，体积小，成本也相对较低，在野外调查时部署方便；而Stereo-BRUV体积大，成本相对较高，占用大量的船体空间，使用小型船只开展多个站点的调查时会增加时间成本，相比而言，Mono-BRUV在野外调查的适用性更强。BRUV作为一种成本较低的非破坏性调查技术，对所研究海域的生态系统不会产生破坏，同时该技术可应用于潜水通常无法到达的深度(>40 m)进行调查，不仅具有强大的安全优势，且可储存相关视频记录，重复分析视频数据。BRUV技术已广泛用于人为影响(捕捞、气候变化、石油或天然气平台、人工鱼礁)下的鱼类多样性的监测评价中，另外在研究观察鱼类特定行为，如鱼类对噪声回放的行为变化等也有相关应用[9]。
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图1 单摄像机的BRUV结构示意图 Fig. 1 Structure diagram of mono-BRUV |
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图2 立体BRUV结构示意图 Fig. 2 Structure diagram of stereo-BRUV |
诱饵视频的使用报道最早可追溯到20世纪90年代中期[10]。近年来BRUV技术得到了快速发展，对此笔者采用关键词“BRUV” “bited video”检索了2006年1月至2020年3月期间Google Scholar, Scopus, Web of Science 3个数据库中所发表的与BRUV相关的文献资料信息，排除掉其中的综述、书籍、会议摘要和组织机构报告，以及没有具体使用BRUV或与诱饵视频无关的文献记录，无法获得全文的文献信息也排除掉，最终共检索到278篇与BRUV相关的文献，分析表明BRUV的发文数量近年来呈现不断增加的趋势(图3)。从各地区的发文数量来看，大洋洲的文献最多，其次是北美洲和欧洲，而亚洲、南美洲、非洲的相关研究较少(表1)。澳大利亚、美国、英国等国家已将BRUV技术广泛运用于珊瑚礁、岩礁等生境的鱼类群落评估和行为研究中[9,11-12]。国内在运用水下视频监测技术开展渔业方面的应用研究已有个别报道，但主要是使用潜水操作的立体式视频技术(dive operated stereo-video, Stereo-DOV)评估许氏平鲉(Sebastes schlegeli)种群结构和丰度[13], 通过定性(拍照)或定量(摄录)的水下摄像方式评估厚壳贻贝(Mytilus coruscus)栖息范围和密度并探究其分布的自然规律[14], 以及使用鱼探仪辅以水下摄影和潜水取样方式对礁区的生物群落进行综合观测[15]等，尚未检索到与BRUV相关的研究报道。
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图3 诱饵式远程水下视频系统(BRUV)研究论文发表年份和数量分布2020年数量仅统计3个月(1月至3月). Fig. 3 Publication year and quantity of research papers about baited remote underwater video (BRUV)Data of 2020 only cover three months (from January to March). |
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表1 诱饵式远程水下视频系统(BRUV)研究论文第一作者的大洲和国家的分布情况 Tab. 1 Continents and countries of the first author of baited remote underwater video (BRUV) research papers |
海洋牧场作为一种生态健康、环境友好、资源养护型的渔业生产方式，近年来在我国得到高度重视和快速发展[16-18], 而人工鱼礁是海洋牧场构建过程中生境修复的关键设施[19]。根据对生物资源的影响程度，目前对于人工鱼礁区鱼类与无脊椎动物的调查方法可分为破坏性调查和非破坏性调查[20]。传统的破坏性调查渔具主要有：刺网类、拖网类、笼壶类和钓具等[20]。刺网类在鱼礁区调查时有缠绕到礁石的风险，易形成幽灵渔具，对礁区渔业资源造成二次破坏。拖网类调查一般位于礁区周边海域，会对稳定的底栖生态环境产生扰动，另外对趋礁性鱼类采样困难；笼壶类和钓具对目标生物的选择性较强。上述传统渔具调查方法虽能获得人工鱼礁区的相关生物资源信息，但对资源和生境也会产生一定的破坏。传统的非破坏性调查方法如潜水目视等方法，因礁体遮挡、鱼类对潜水员的应急反应等原因，无法实现对生物资源的精准监测[21]。采用声学手段调查所获得的物种数据需通过其他互补技术加以识别，且由于鱼礁对声波的遮蔽作用，使得声学方法对底栖生物特别是鱼礁内生物监测效果有限[15]。我国海洋牧场的监测技术近年来发展迅速，但对生物资源的精细化监测仍显不足[18], 尚未形成规范有效的牧场生物资源调查监测体系[21]。基于资源无损监测分析的BRUV技术，克服了对喜好栖息于礁体内部及附近的趋礁性鱼类的采样限制，同时避免了对海洋渔业资源的破坏，有利于对海洋生态系统的保护。本研究从栖息地类型、平均部署水深、饵料种类与重量、部署时间、BRUV摄像角度、使用的相机品牌、BRUV与其他监测方法的对比与结合、视频提取采用的度量指标等多个方面对提取的278篇文献进行梳理归纳，总结分析了BRUV的研究进展，旨在为国内利用BRUV技术开展资源调查与评估工作提供技术参考，为我国无破坏性海洋生物调查技术的发展和海洋牧场资源养护与增殖效果的监测评估提供技术保障。
1 BRUV技术应用的栖息地类型及水深分布近20年来，BRUV技术已被国外研究人员广泛应用于全球多种栖息地和水深范围的资源调查与评估中。
1.1 栖息地类型目前BRUV应用的研究绝大部分都集中在海洋生态系统(占97%), 淡水生态系统的研究极少(占3%)[22-27]。在海洋生态系统中，珊瑚礁、岩礁作为鱼类主要的栖息场所，具有重要的研究意义和保护价值。在BRUV的应用研究中，最常见的栖息地调查类型也是珊瑚礁和岩礁(共占45%, 图4), 另外包括珊瑚礁与岩礁在内的多种自然生境构成的近岸海洋景观也占有相对较高比例(占20%)。部分研究将BRUV用于人工鱼礁[28]、波浪能源设施[29]、油气平台[30-31]、海底管道[32]、海上风电场[33]等人造生境的调查，而海草[34-35]、潮间带[36-37]等其他栖息地类型的相关研究较少(占10%)。BRUV的调查研究主要集中在温带与热带海域，但近年来在北极地区也有应用[38], 为研究极地海洋生态系统提供了重要手段。
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图4 诱饵式远程水下视频系统(BRUV)研究的栖息地及水深分布[39-45]人造生境包括：波浪能源设施、油气平台、海底管道、海上风电场等；其他栖息地包括：海草床、潮间带等. Fig. 4 Habitat and water depth distribution of baited remote underwater video (BRUV) studies[39-45]Artificial habitat includes: wave energy development facility, oil and gas platforms, subsea pipeline, offshore windfarms, etc. Other habitats include: seagrass beds, intertidal zones, etc. |
BRUV部署的平均水深大多集中在0~40 m之间(占67%, 图4)的浅海地区，原因可能在于浅海地区的部署成本较低，视频技术在有自然光照的水域中效果出色，黑暗环境中使用BRUV需补充灯光，成本较高且部署更加困难[39]。其他水深范围内也有相应的分布，统计中诱饵视频技术应用的最深海域范围可达到9729 m的超深渊带(hadal zone)[40]。之前因为传统采样技术的限制，与浅海珊瑚礁相比，30~150 m的中光层珊瑚礁生态系统(mesophotic coral ecosystems, MCEs) 文献记录较少，随着BRUV技术的不断进步与普及，人们已开始陆续涉足这一未知领域的研究[41-45]。
2 BRUV采用的诱饵诱饵是BRUV系统中的重要组成部分，关于有无饵料(BRUV与RUV)之间的效果比较已经有了明确的结论，有饵料能获得更大的鱼类丰度与多样性，可提供更好的统计效果[46-47]。其中，饵料类型和用量可能会对BRUV的监测结果造成影响。目前，关于BRUV研究报道中所使用的饵料类型和用量存在一定的差异，在未来的研究中，考虑效果及成本的基础上饵料类型和用量应该标准化，从而更好地推广和普及BRUV的应用。
2.1 饵料类型饵料种类是影响BRUV监测效果的一个关键变量。Dorman等[48]对沙丁鱼(Sardinops sagax)、猫粮、鹰嘴豆泥蔬菜混合物(falafel mix) 3种不同的饵料组以及无饵料组进行对比，发现3种不同饵料对珊瑚礁鱼类群落结构的监测结果无显著的差异，但猫粮消耗迅速，无法满足60 min的部署时间；鹰嘴豆泥蔬菜混合物是混合饵料，在BRUV部署时容易造成视野模糊，影响视频分析；沙丁鱼饵料消耗的时间长，具有持久性，价格便宜，使用效果较好。而有无饵料之间的监测结果显示，统计的鱼类组成存在显著差异，也证实了BRUV与RUV对比实验的结果。Wraith等[49]也开展过相似研究，使用了沙丁鱼、鲍(Haliotis spp.)以及海胆(Centrostephanus rodgersii) 3种不同的饵料进行对比实验，其中海胆的效果最差，故其推荐使用像沙丁鱼这样的油性鱼类作为饵料，对于吸引肉食性鱼类会起到很好的效果。Walsh等[50]使用了沙丁鱼、澳大利亚鲑(Arripis trutta)和贻贝(Mytilus edulis)进行对比，结果也认为沙丁鱼是一种有效的饵料类型。混合饵料的类型(动物混合饵料，植物混合饵料)也有相关的比较研究[51]。总体而言，沙丁鱼是BRUV监测过程中效果比较理想的饵料。
在统计的饵料种类中，最常见的饵料类型是澳大利亚沙丁鱼(Sardinops sagax)(占64%, 图5), 其他种类的沙丁鱼(Sardinella brasiliensis、Sardinella aurita、Sardinops neopilchardus等)也常被用作BRUV的饵料。大西洋鲭(Scomber scombrus)(占8%)是仅次于沙丁鱼的饵料类型，该鱼种是产于北美洲和欧洲的大西洋沿岸的鲭属鱼种，在美国、英国等BRUV的研究中也经常将其作为饵料使用。其他报道的鱼类饵料类型(占17%)还包括秋刀鱼(Cololabris saira)[44-46]、鲻(Mugil cephalus)[52]以及鲣(Katsuwonus pelamis)[41]等。此外，几种油性鱼类之间的混合饵料也有一定的使用比例(占6%)[53-54]。
2.2 饵料用量在BRUV饵料的用量上，研究人员使用最多的饵料重量范围是801~1000 g (占38%, 图5), 大部分研究使用的饵料重量为1000 g, 其次较高的饵料用量范围为501~800 g (占27%, 800 g最常见), 另外还有部分研究的饵料重量使用范围在301~ 500 g (占16%, 主要用量是500 g)和小于300 g (占16%)。大于1000 g饵料用量范围(仅占3%)的研究相对较少。关于饵料的重量是否会造成监测鱼类群落结构的差异这一疑问，目前已有研究报道[55], 该研究使用0 g、200 g、1000 g、2000 g 4种不同重量的饵料用量，测试其对鱼类群落结构监测的影响[55], 饵料存在的情况下，鱼类相对丰度显著增加，而3种饵料重量之间对鱼类群落结构影响的差异不大，该研究还认为，在鱼类特别丰富的地区，如热带珊瑚礁，需要更多的饵料防止大量的鱼类摄食而消耗殆尽。
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图5 诱饵式远程水下视频系统(BRUV)研究使用的饵料类型及重量分布[48-55]其他鱼类包括：秋刀鱼、鲻、鲣等；混合饵料包括：油性鱼类混合饵料、植物混合饵料；其他饵料包括：猫粮、鹰嘴豆泥蔬菜混合物、玉米、鲍等. Fig. 5 Types of bait used in baited remote underwater video (BRUV) studies and their weight distribution[48-55]Other fish includes: pacific saury, mullet, skipjack tuna, etc. Mixed bait includes: oily fish mixed and plant mixed. Other bait includes: cat food, falafel mix, corn, abalone, etc. |
在使用BRUV开展调查时，过长的水下投放时间不仅需要耗费更多的电池供能，而且还增加了野外工作时间成本和后期视频数据处理时间；而水下监测时间不足可能导致监测结果不能有效代表样本特征，影响生物多样性监测评估结果，因此，需要确定合理的BRUV水下部署时间以提高采样效率，保证数据整体监测质量。
目前文献报道显示，60 min (占48%, 图6)是BRUV研究中最常用的部署时间，其次是30 min (占22%), 部署时间不足30 min的研究最少(占4%)。Santana-Garcon等[56]认为，2 h的部署时间适合评估中上层鱼类群落结构。Gladstone等[57]分别采用30 min、60 min和90 min的部署时间对河口区域的海草床和无植被底泥中的鱼类进行独立采样，发现60~90 min是河口地区最适合的采样时间。在具有礁石的栖息地中，Harasti等[58]研究表明，设置30 min的BRUV足以比较海洋保护区与捕捞区之间关键渔业物种的相对丰度和鱼类群落结构。Misa等[59]发现，15~30 min的BRUV布置时间可对夏威夷底栖鱼类进行有效的采样。而对于评估一些隐蔽或稀有物种，可能需要长达几个小时的录制时间[53]。因此在使用BRUV进行调查时，应具体根据栖息地特征和监测目标种制定合理的部署时间，已有研究建议根据物种数和丰度累积曲线到达恒定值来确定BRUV最适布放时间[60]。
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图6 诱饵式远程水下视频系统(BRUV)研究的部署时间分布[56-60] Fig. 6 Deployment setting time used in baited remote underwater video (BRUV) studies[56-60] |
BRUV的摄像机视角通常有水平向前和视角向下两种布局(图7), 摄像机视角向下的优点是可以通过固定的标尺测量鱼的体长，然而却只能通过摄像机从上方观察鱼的背部识别种类，影响鉴别效果。两种摄像机视角方向的设置也会影响鱼类数量的观察结果，Langlois等[61]研究表明，在法国新喀里多尼亚海洋保护区的珊瑚礁生境中，使用水平视角的摄像机记录了14个物种，而视角向下的摄像机只记录了4个物种，作者推测可能是由于摄像机下方空间有限，一些主要的趋礁性鱼类不易进入俯视摄像机下的视野。Cundy等[62]将视角水平向前的Stereo-BRUV和视角向下的Mono- BRUV对比采样效果及优缺点，在监测总物种数、总个体数以及重点物种的相对丰度和体长等方面的测试中前向视角优于向下视角。前向视角的摄像机设置可得到更大的视野，从侧面识别鱼类物种更容易，因此摄像机水平向前视角的设置广泛应用于BRUV的研究中。
10-1359-14-F007.jpg "点击查看原图") |
图7 向下视角的诱饵式远程水下视频系统(BRUV)结构示意图 Fig. 7 Structure diagram of downward-bait used in baited remote underwater video (BRUV) |
BRUV逐渐流行起来的一个关键原因得益于摄像机产品图像质量的提高和价格的下降。其中，GoPro摄像机因价格便宜、便于携带和易于使用等优点，适用于多种环境且可保证视频录制的质量，是BRUV研究人员在调查中广泛选择的摄像机品牌(占34%, 图8)。Phillips[63]曾专门详细介绍了GoPro的滤镜、防水壳、电池等配件以及如何使用GoPro进行捕获、编辑视频和查看水下图像。但是，廉价的动作摄像机(如GoPro)通常不适用于弱光环境[64], 而Sony与Canon摄像机尽管价格较高，但在深水低光照条件下，却可提供较好的视频录制效果。在相机品牌的选择方面，Sony (占28%)是仅次于GoPro的相机品牌，主要使用的型号是Sony HDR-CX系列。Canon相机品牌的使用量排在第三(占13%), Canon Legria HFG系列也是常用的相机型号。
10-1359-14-F008.jpg "点击查看原图") |
图8 诱饵式远程水下视频系统(BRUV)研究使用的相机品牌类型分布[63-64] Fig. 8 Video camera brands used in baited remote underwater video (BRUV) studies[63-64] |
BRUV常用于与不同调查方法进行比较，以评估该技术的优势及局限性，通过与其他监测技术结合优势互补，从而达到全面精细监测评估的目标。
在BRUV与其他非破坏性鱼类多样性调查技术进行比较方面，最常见的是BRUV与水下目视调查技术(underwater visual census, UVC)的比较[65-67]和与潜水操作视频技术(diver operated video, DOV)的比较[68-69], 以及3种调查技术之间的比较[70]。其他的比较还有BRUV、DOV与其他两种相对较新的技术——慢拖曳式立体视频技术(slow towed stereo-video, STV)、远程遥控潜水器(remotely operated vehicle, ROV)之间的比较分析[71]等。对于这些调查技术之间的优点及不足，Mallet等[5]对常用的水下视频技术进行了综述，分析了不同调查技术之间的互补性，对目前生物多样性监测和研究中存在的问题进行了讨论，研究认为，目前没有一种技术明显优于其他技术，在实际调查中，应根据具体的研究目的，选择合适的监测方法。拖曳式视频技术主要优势在于短时间内对大面积区域进行采样，可提高栖息地的空间覆盖率以及观察稀有物种的概率。DOV适合于较小尺度的研究，如监测珊瑚(gorgonians)和海藻栖息地(macroalgae)等鱼类丰度和物种多样性的研究，而BRUV特别适合监测活动能力强的肉食性鱼类，基于饵料对物种的吸引，它可以有效部署在鱼类稀少的地区。对于BRUV与传统网具调查方法采样效果的对比，包括与诱饵陷阱的对比[72-74]、与延绳捕鱼的对比[52,75]、与线钓的对比[76-77]以及与刺网的对比[78]等。这些研究表明，BRUV与传统网具调查方法采样的效果相比，是一种在评估鱼类多样性、种类组成以及相对丰度上非常有效的监测工具[5]。
BRUV与其他生物资源调查技术的互补可实现对生物资源更加全面的评估[71]。BRUV的监测结果中，肉食性鱼类比例与实际相比可能更大，而某些行为隐蔽、对肉食性鱼类产生躲避反应的物种比例较实际低，因此研究人员采用BRUV与其他方法结合互补的方式，以便更准确全面地评估鱼类群落结构，如BRUV与UVC[79-82]以及与DOV的结合[83-85]采样，能够弥补BRUV在监测草食性鱼类和行为隐蔽、对肉食性鱼类产生躲避反应的鱼类的不足。BRUV与ROV结合[86], 可监测到对潜水员产生应激反应的鱼类，进而全面了解评价整个生态系统的鱼类多样性，另外BRUV还可与自主水下载具(autonomous underwater vehicle, AUV)结合[87], 也是评估海洋生态系统鱼类群落结构完整性的重要方式。
6 监测分析指标视频数据的提取是有效链接水下视频监测影像，揭示鱼类多样性变化规律以及查明行为响应的关键纽带。目前，在BRUV提取视频数据过程中，对出现的相同种类的个体重复进行计数，可能会高估鱼类的数量，为了避免重复计数，大部分BRUV研究使用其记录期间，一个视频影像视野中所见到的某一个物种的个体最大数量(MaxN)的计数[88]。由于并非所有的鱼类都会进入相机视野，它们可能会游弋在摄像机的周围，因此MaxN的使用对鱼类相对丰度的估计相对保守，具有一定的偏差。为了调查固定视角产生的偏差，Whitmarsh等[89]在摄像机水平向前视角的BRUV基础上，在BRUV其他3个方向增加了3台摄像机，进行360°的环绕拍摄，其中面对诱饵的摄像机记录了最高的鱼类丰度，额外视角的摄像机只记录了不常见和害羞的物种(shy species), 对总体的物种丰富度影响较小。Sherman等[90]提出了一种用于BRUV数据提取分析的新指标方法，即通过识别和计数不同个体(MaxIND)来量化MaxN的准确性。也有相关的研究[91-92]通过MaxIND方法，分辨鱼类外观特征进行计数，该方法虽然能提供较好的准确性，但对全部个体进行识别非常耗时，而且该方法只适用于一些特征明显或稀有和濒危的物种的判定研究。总之，MaxN仍然是国际上最广泛使用的表征物种相对丰度的度量指标。除了提取鱼类相对丰度信息外，BRUV还可以基于影像信息进行鱼类行为分析，Phenix等[93]采用记录饵料袋被咬次数和袋子是否严重损坏来量化觅食活动率，评估大型肉食性鱼类的突发游泳、集群、在诱饵上停留等行为。Westlake等[94]记录了鲨鱼对固定在诱饵视频系统上磁铁的行为响应(吸引、背离或者无反应)。Silva等[23]通过观察鱼类行为与头部的朝向确定浮力以及Roberts等[9]监测鱼类对噪声回放的行为变化等。
7 总结和展望 7.1 总结BRUV在国际上是一种广泛用于评估多种栖息地鱼类群落结构及其行为的无损调查技术。根据本研究结果，建议BRUV采用前向视角结构可得到更大的监测视野；轻巧且易于使用的GoPro相机更适合于光线充足的浅海海域(<40 m)调查；BRUV调查时饵料采用类似沙丁鱼的油性鱼类，有利于对肉食性鱼类的诱集；BRUV在大规模使用前，可通过试验性投放，观察物种数和丰度随时间增长的累积曲线变化情况，进而确定其合理的部署时间，底层BRUV的投放适宜时间多以60 min为宜，但取决于研究的具体情况；BRUV记录期间，所见到的某一个物种的个体最大数量(MaxN)是表征物种相对丰度时广泛使用的度量指标。BRUV具有成本低、操作方便、避免了潜水调查时鱼类对潜水员产生应激反应等优势，同时也有其局限性，通过与UVC、DOV等监测技术结合，可以达到优势互补全面精细监测鱼类生物多样性的目标。BRUV技术的成熟对我国无破坏性海洋生物监测技术的发展提供了方向，在海洋牧场精细化监测方面极具应用前景，国内有必要进一步开展BRUV在海洋牧场监测中的应用研究。
7.2 展望(1) BRUV技术的局限性仍需突破。BRUV在扩大应用的同时，也在不断地进行技术改进，包括为了评估濒危、稀有物种的特殊需求，研发了持续24 h的BRUV系统[95]以及深海相机[96], 但是在水体浑浊环境进行调查时，仍然存在很大的局限性。目前，改进BRUV提高水体能见度的研究已引起人们的重视[97], 研究人员尝试在BRUV系统引入液体光学透镜(clear liquid optical chamber, CLOC), 从而达到提高水体能见度的效果，但目前该技术在野外部署方面非常不便，调查成本也比较高。因此，未来开发操作简便、成本更低廉、部署容易并且能提高水体浑浊条件下评估能力的BRUV系统是主要研究目标。
(2) BRUV技术评估的能力仍需改善。在BRUV使用过程中，目前对监测物种的估计主要限于相对丰度和通过立体摄影测量鱼的体长，无法估计种群密度[98]。BRUV通过使用诱饵在其周围水体中释放化学刺激物来达到吸引和监测鱼类的目的，但饵料随着水流传播的距离以及饵料的影响范围都是未知的。目前已有研究开始关注流速变化对BRUV调查的影响[99], 并指出不同流速之间引起的饵料扩散面积变化显著影响了BRUV调查得出的结论，而关于饵料的影响范围和传播距离，仍然是需要解决的问题。
(3) BRUV技术在与其他新兴调查技术结合上可有效进行拓展。在非破坏性调查鱼类多样性技术上，环境DNA条形码技术[environmental DNA (eDNA) metabarcoding]是目前国际上较为前沿的一项评估技术手段[100-102], 目前，BRUV技术与eDNA技术结合评估鱼类生物多样性方面已有报道，Stat等[103]在西澳大利亚朱里恩湾海洋保护区的珊瑚礁和海草床生境，使用了BRUV与eDNA结合对海洋生物进行监测，结果表明，在评估鱼类群落结构上，eDNA是BRUV强大的辅助技术。此外，BRUV技术可与先进的声学技术结合，如利用声学遥测技术(acoustic telemetry)[104-105]监测鲨鱼的运动模式，结合BRUV监测其相对丰度和多样性等信息，可更好地查明鲨鱼种群特征以及它们对栖息地的利用。通过使用多波束测深系统[106-107]收集海底特征的高分辨率信息，帮助解释鱼类群落在不同空间的变化，实现BRUV与多波束测深系统的应用结合。未来随着海洋调查技术的快速发展，BRUV技术将会与更多的新兴调查技术结合形成多元化技术，对海洋生态系统的了解将会更加深入。
(4) BRUV技术的数据分析过程仍需优化。在BRUV视频数据提取过程中，需花费大量时间、人力对视频进行观察，识别和计数所有鱼类。深度学习和使用人工智能计算机系统可能有助于克服这一问题。在鱼类丰度计数方面，深度学习可以做到比人为计数更为准确[108], 已有相关研究采用运动分析软件检测视频片段中鱼类所在的部分，从而使研究人员快速分析并识别鱼类[109]。
(5) BRUV技术在我国海洋保护区(marine protected areas, MPAs)和海洋牧场生物资源精细化监测方面具有广泛的应用前景。BRUV技术可通过诱饵吸引潜在大型肉食性鱼类物种，对于监测评估我国MPAs内稀有、濒危物种，如鲨鱼和鳐类等种群相关信息具有重要应用前景。随着海洋牧场建设规模的扩大，人工生境与自然生境之间的连通性不断加强[20], 可将BRUV用于多尺度下海洋牧场生态系统的研究，探究鱼类种群在不同时空尺度下的变化规律其与相关生境间的关系。同时BRUV也可运用于海洋牧场海域岩礁生物行为的研究，掌握物种行为相关信息，提高对岩礁生物行为的认知水平。
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