为了应对近海渔业资源日益衰退的问题,为实施基于空间的渔业管理提供必要信息,以江苏南部海域小黄鱼为研究对象,根据2019—2022年在该海域进行的季节性渔业资源综合调查,结合5个生物和非生物因子,采用组合物种分布模型(Ensemble species...为了应对近海渔业资源日益衰退的问题,为实施基于空间的渔业管理提供必要信息,以江苏南部海域小黄鱼为研究对象,根据2019—2022年在该海域进行的季节性渔业资源综合调查,结合5个生物和非生物因子,采用组合物种分布模型(Ensemble species distribution model,ESDM),研究了该海域小黄鱼的空间分布特征及其主要影响因素。结果显示,相较于单一物种分布模型,组合物种分布模型具有更高的AUC值(春季:0.995±0.002;秋季:0.985±0.001)和TSS值(春季:0.935±0.038;秋季:0.903±0.029)。在春季,底层水温和底层盐度的重要性水平最高(0.40和0.38),而在秋季叶绿素a和饵料生物丰度对小黄鱼空间分布的影响较大,其重要性分别为0.53和0.46。春季小黄鱼主要分布在近岸浅海区域,整体呈条带状分布;秋季小黄鱼则主要分布于水深较深的远岸水域,且适宜分布的海域范围要大于春季,整体呈块状分布。此外,小黄鱼的空间分布特征亦呈现出明显的年际差异,例如在2021年,其适宜栖息地面积明显小于其他年份,分布范围也仅限于局部区域。研究表明,组合物种分布模型具有更优的预测性能,能够更好地反映小黄鱼的栖息分布特征及其影响因素;不同季节小黄鱼的适生区及影响因素各有差异。本研究可为揭示该海域小黄鱼的时空分布特征及其变化规律提供理论依据,为实施基于空间的渔业管理和保护区选划提供基础资料。展开更多
Ocean environmental information is very important to supporting the fishermen in fishing and satellite remote sensing technology can provide it in large scale and in near real-time. Ocean fishery locations are always ...Ocean environmental information is very important to supporting the fishermen in fishing and satellite remote sensing technology can provide it in large scale and in near real-time. Ocean fishery locations are always far away beyond the coverage of the satellite data received by a land-based satellite receiving station. A nice idea is to install the satellite ground station on a fishing boat. When the boat moves to a fishery location, the station can receive the satellite data to cover the fishery areas. One satellite remote sensing system was once installed in a fishing boat and served fishing in the North Pacific fishery areas when the boat stayed there. The system can provide some oceanic environmental charts such as sea surface temperature (SST) and relevant derived products which are in most popular use in fishery industry. The accuracy of SST is the most important and affects the performance of the operational system, which is found to be dissatisfactory. Many factors affect the accuracy of SST and it is difficult to increase the accuracy by SST retrieval algorithms and clouds detection technology. A new technology of temperature error control is developed to detect the abnormity of satellite-measured SST. The performance of the technology is evaluated to change the temperature bias from -3.04 to 0.05 ℃ and the root mean square (RMS) from 5.71 to 1.75℃. It is suitable for employing in an operational satellite-measured SST system and improves the performance of the system in fishery applications. The system has been running for 3 a and proved to be very useful in fishing. It can help to locate the candidates of the fishery areas and monitor the typhoon which is very dangerous to the safety of fishing boats.展开更多
文摘为了应对近海渔业资源日益衰退的问题,为实施基于空间的渔业管理提供必要信息,以江苏南部海域小黄鱼为研究对象,根据2019—2022年在该海域进行的季节性渔业资源综合调查,结合5个生物和非生物因子,采用组合物种分布模型(Ensemble species distribution model,ESDM),研究了该海域小黄鱼的空间分布特征及其主要影响因素。结果显示,相较于单一物种分布模型,组合物种分布模型具有更高的AUC值(春季:0.995±0.002;秋季:0.985±0.001)和TSS值(春季:0.935±0.038;秋季:0.903±0.029)。在春季,底层水温和底层盐度的重要性水平最高(0.40和0.38),而在秋季叶绿素a和饵料生物丰度对小黄鱼空间分布的影响较大,其重要性分别为0.53和0.46。春季小黄鱼主要分布在近岸浅海区域,整体呈条带状分布;秋季小黄鱼则主要分布于水深较深的远岸水域,且适宜分布的海域范围要大于春季,整体呈块状分布。此外,小黄鱼的空间分布特征亦呈现出明显的年际差异,例如在2021年,其适宜栖息地面积明显小于其他年份,分布范围也仅限于局部区域。研究表明,组合物种分布模型具有更优的预测性能,能够更好地反映小黄鱼的栖息分布特征及其影响因素;不同季节小黄鱼的适生区及影响因素各有差异。本研究可为揭示该海域小黄鱼的时空分布特征及其变化规律提供理论依据,为实施基于空间的渔业管理和保护区选划提供基础资料。
文摘Ocean environmental information is very important to supporting the fishermen in fishing and satellite remote sensing technology can provide it in large scale and in near real-time. Ocean fishery locations are always far away beyond the coverage of the satellite data received by a land-based satellite receiving station. A nice idea is to install the satellite ground station on a fishing boat. When the boat moves to a fishery location, the station can receive the satellite data to cover the fishery areas. One satellite remote sensing system was once installed in a fishing boat and served fishing in the North Pacific fishery areas when the boat stayed there. The system can provide some oceanic environmental charts such as sea surface temperature (SST) and relevant derived products which are in most popular use in fishery industry. The accuracy of SST is the most important and affects the performance of the operational system, which is found to be dissatisfactory. Many factors affect the accuracy of SST and it is difficult to increase the accuracy by SST retrieval algorithms and clouds detection technology. A new technology of temperature error control is developed to detect the abnormity of satellite-measured SST. The performance of the technology is evaluated to change the temperature bias from -3.04 to 0.05 ℃ and the root mean square (RMS) from 5.71 to 1.75℃. It is suitable for employing in an operational satellite-measured SST system and improves the performance of the system in fishery applications. The system has been running for 3 a and proved to be very useful in fishing. It can help to locate the candidates of the fishery areas and monitor the typhoon which is very dangerous to the safety of fishing boats.
