Multispecies ecological models have been used for predicting the effects of fishing activity and evaluating the performance of management strategies. Size-spectrum models are one type of physiologically-structured eco...Multispecies ecological models have been used for predicting the effects of fishing activity and evaluating the performance of management strategies. Size-spectrum models are one type of physiologically-structured ecological model that provide a feasible approach to describing fish communities in terms of individual dietary variation and ontogenetic niche shift. Despite the potential of ecological models in improving our understanding of ecosystems, their application is usually limited for data-poor fisheries. As a first step in implementing ecosystem-based fisheries management（EBFM）, this study built a size-spectrum model for the fish community in the Haizhou Bay, China. We describe data collection procedures and model parameterization to facilitate the implementation of such size-spectrum models for future studies of data-poor ecosystems. The effects of fishing on the ecosystem were exemplified with a range of fishing effort and were monitored with a set of ecological indicators. Total community biomass, biodiversity index, W-statistic, LFI（Large fish index）, Mean W（mean body weight） and Slope（slope of community size spectra） showed a strong non-linear pattern in response to fishing pressure, and largest fishing effort did not generate the most drastic responses in certain scenarios. We emphasize the value and feasibility of developing size-spectrum models to capture ecological dynamics and suggest limitations as well as potential for model improvement. This study aims to promote a wide use of this type of model in support of EBFM.展开更多
国家教育数字化战略转型带动了智慧课堂交互行为数据大规模、系统化的采集,当前在采集的数据基础上所进行的分析依据是统计性的经验性分析方法。如何根据课堂交互行为数据建立标准分数常模,并对相关维度数据进行分级应用,是目前国家教...国家教育数字化战略转型带动了智慧课堂交互行为数据大规模、系统化的采集,当前在采集的数据基础上所进行的分析依据是统计性的经验性分析方法。如何根据课堂交互行为数据建立标准分数常模,并对相关维度数据进行分级应用,是目前国家教育数字化亟待探索的数据驱动智慧课堂交互分析方法。为此,从课堂交互行为数据基础出发,基于改进型弗兰德斯互动分析系统(iFIAS),选取iFIAS系统平台的358节有效课堂和292380条有效数据,形成了课堂交互行为分析标准分数常模的计算方法,并构建了“1个总体,4个主维度,14个子维度”的标准分数常模分级应用框架,得出iFIAS课堂交互行为数据标准分数常模计算结果。最后,应用该方法对一堂小学四年级数学课“认识三角形和四边形”和一堂初中一年级英语课“Do You Think You Will Have Your Own Robot?”进行课堂交互行为量化分析,通过比较发现数据驱动的智慧课堂的特点及其内在关联,并从“标准分数常模、三值内在逻辑关系、课堂特点、无学科限定、常模漂移”五个方面讨论了常模分析结果。展开更多
基金The Special Fund for Agriscientific Research in the Public Interest under contract No.201303050the Fundamental Research Funds for the Central Universities under contract Nos 201022001 and 201262004
文摘Multispecies ecological models have been used for predicting the effects of fishing activity and evaluating the performance of management strategies. Size-spectrum models are one type of physiologically-structured ecological model that provide a feasible approach to describing fish communities in terms of individual dietary variation and ontogenetic niche shift. Despite the potential of ecological models in improving our understanding of ecosystems, their application is usually limited for data-poor fisheries. As a first step in implementing ecosystem-based fisheries management（EBFM）, this study built a size-spectrum model for the fish community in the Haizhou Bay, China. We describe data collection procedures and model parameterization to facilitate the implementation of such size-spectrum models for future studies of data-poor ecosystems. The effects of fishing on the ecosystem were exemplified with a range of fishing effort and were monitored with a set of ecological indicators. Total community biomass, biodiversity index, W-statistic, LFI（Large fish index）, Mean W（mean body weight） and Slope（slope of community size spectra） showed a strong non-linear pattern in response to fishing pressure, and largest fishing effort did not generate the most drastic responses in certain scenarios. We emphasize the value and feasibility of developing size-spectrum models to capture ecological dynamics and suggest limitations as well as potential for model improvement. This study aims to promote a wide use of this type of model in support of EBFM.
文摘国家教育数字化战略转型带动了智慧课堂交互行为数据大规模、系统化的采集,当前在采集的数据基础上所进行的分析依据是统计性的经验性分析方法。如何根据课堂交互行为数据建立标准分数常模,并对相关维度数据进行分级应用,是目前国家教育数字化亟待探索的数据驱动智慧课堂交互分析方法。为此,从课堂交互行为数据基础出发,基于改进型弗兰德斯互动分析系统(iFIAS),选取iFIAS系统平台的358节有效课堂和292380条有效数据,形成了课堂交互行为分析标准分数常模的计算方法,并构建了“1个总体,4个主维度,14个子维度”的标准分数常模分级应用框架,得出iFIAS课堂交互行为数据标准分数常模计算结果。最后,应用该方法对一堂小学四年级数学课“认识三角形和四边形”和一堂初中一年级英语课“Do You Think You Will Have Your Own Robot?”进行课堂交互行为量化分析,通过比较发现数据驱动的智慧课堂的特点及其内在关联,并从“标准分数常模、三值内在逻辑关系、课堂特点、无学科限定、常模漂移”五个方面讨论了常模分析结果。
