Aggregation of species with similar ecological properties is one of the effective methods to simplify food web researches.However,species aggregation will affect not only the complexity of modeling process but also th...Aggregation of species with similar ecological properties is one of the effective methods to simplify food web researches.However,species aggregation will affect not only the complexity of modeling process but also the accuracy of models’outputs.Selection of aggregation methods and the number of trophospecies are the keys to study the simplification of food web.In this study,three aggregation methods,including taxonomic aggregation(TA),structural equivalence aggregation(SEA),and self-organizing maps(SOM),were analyzed and compared with the linear inverse model–Markov Chain Monte Carlo(LIM-MCMC)model.Impacts of aggregation methods and trophospecies number on food webs were evaluated based on the robustness and unitless of ecological net-work indices.Results showed that aggregation method of SEA performed better than the other two methods in estimating food web structure and function indices.The effects of aggregation methods were driven by the differences in species aggregation principles,which will alter food web structure and function through the redistribution of energy flow.According to the results of mean absolute percentage error(MAPE)which can be applied to evaluate the accuracy of the model,we found that MAPE in food web indices will increase with the reducing trophospecies number,and MAPE in food web function indices were smaller and more stable than those in food web structure indices.Therefore,trade-off between simplifying food webs and reflecting the status of ecosystem should be con-sidered in food web studies.These findings highlight the importance of aggregation methods and trophospecies number in the analy-sis of food web simplification.This study provided a framework to explore the extent to which food web models are affected by dif-ferent species aggregation,and will provide scientific basis for the construction of food webs.展开更多
为了解海州湾大泷六线鱼时空分布特征及其影响因素,根据2013—2019年秋季在海州湾开展的底拖网渔业资源调查和环境观测数据,构建了时空物种分布模型(spatio-temporal species distribution models),分析其分布与环境因子的关系,通过残...为了解海州湾大泷六线鱼时空分布特征及其影响因素,根据2013—2019年秋季在海州湾开展的底拖网渔业资源调查和环境观测数据,构建了时空物种分布模型(spatio-temporal species distribution models),分析其分布与环境因子的关系,通过残差分析比较其与广义加性模型的残差独立性和异质性,运用交叉验证检验模型预测性能,最终结合delta方法对其分布进行预测并计算栖息地适宜性指数(habitat suitability index,HSI)和资源分布重心。时空模型的偏差解释率为65.50%,模型分析表明,影响大泷六线鱼资源分布最主要的环境因子为水深(22.11%),其次为底层水温(12.98%),底层盐度(0.09%)的影响较小,水深与其分布存在正向相关性,底层水温与其分布存在负向相关性,底层盐度与其分布存在弱正向线性关系。时空模型的残差独立性和异质性较GAM更强,其交叉验证回归线斜率为0.90±0.38。模型预测结果表明,大泷六线鱼主要分布在34.5°N以北,120.0°E以东的海域,其栖息地适宜性指数的高值区域呈现逐年收缩的趋势,资源分布重心呈现向东北海域转移的趋势,这可能是气候变迁以及捕捞压力共同作用的结果。本研究解析了大泷六线鱼在海州湾的时空分布,对于深入了解大泷六线鱼的分布动态和科学的渔业管理具有重要意义。展开更多
为了解双斑蟳栖息分布规律,实验根据2011—2016年多个季度航次在海州湾进行的渔业资源和环境调查数据,采用广义线性模型(GLM)、广义可加模型(GAM)以及随机森林3种物种分布模型(SDMs)方法,结合AIC(akaike information criterion)准则、...为了解双斑蟳栖息分布规律,实验根据2011—2016年多个季度航次在海州湾进行的渔业资源和环境调查数据,采用广义线性模型(GLM)、广义可加模型(GAM)以及随机森林3种物种分布模型(SDMs)方法,结合AIC(akaike information criterion)准则、累积偏差解释率和交叉检验等评判指标筛选和构建了双斑蟳栖息分布模型,并分析了环境因子对双斑蟳分布的影响。结果显示,3种模型在解释因子与响应变量间的关系上基本一致;其中GAM在模型拟合上具有优势,而随机森林的预测性能明显高于传统的GLM和GAM。双斑蟳相对渔获量在年份和月份间的变异性最为显著,两个因子的解释率分别在18%和3.8%以上。水深和表层盐度对双斑蟳资源分布的影响较大,均与双斑蟳相对丰度呈正相关关系;双斑蟳分布总体呈现冬季相对较高,夏季东北部海域高、西南部低的特点,与海州湾水深分布特点基本一致。本研究还根据FVCOM(finite-volume coasta ocean model)模拟环境数据,利用随机森林分布模型估计了双斑蟳在海州湾海域2011年各个季节的空间分布,为渔业资源的开发和保护提供依据。展开更多
基金supported by the National Key R&D Program of China(Nos.2019YFD0901204,2019YFD 0901205).
文摘Aggregation of species with similar ecological properties is one of the effective methods to simplify food web researches.However,species aggregation will affect not only the complexity of modeling process but also the accuracy of models’outputs.Selection of aggregation methods and the number of trophospecies are the keys to study the simplification of food web.In this study,three aggregation methods,including taxonomic aggregation(TA),structural equivalence aggregation(SEA),and self-organizing maps(SOM),were analyzed and compared with the linear inverse model–Markov Chain Monte Carlo(LIM-MCMC)model.Impacts of aggregation methods and trophospecies number on food webs were evaluated based on the robustness and unitless of ecological net-work indices.Results showed that aggregation method of SEA performed better than the other two methods in estimating food web structure and function indices.The effects of aggregation methods were driven by the differences in species aggregation principles,which will alter food web structure and function through the redistribution of energy flow.According to the results of mean absolute percentage error(MAPE)which can be applied to evaluate the accuracy of the model,we found that MAPE in food web indices will increase with the reducing trophospecies number,and MAPE in food web function indices were smaller and more stable than those in food web structure indices.Therefore,trade-off between simplifying food webs and reflecting the status of ecosystem should be con-sidered in food web studies.These findings highlight the importance of aggregation methods and trophospecies number in the analy-sis of food web simplification.This study provided a framework to explore the extent to which food web models are affected by dif-ferent species aggregation,and will provide scientific basis for the construction of food webs.
文摘为了解海州湾大泷六线鱼时空分布特征及其影响因素,根据2013—2019年秋季在海州湾开展的底拖网渔业资源调查和环境观测数据,构建了时空物种分布模型(spatio-temporal species distribution models),分析其分布与环境因子的关系,通过残差分析比较其与广义加性模型的残差独立性和异质性,运用交叉验证检验模型预测性能,最终结合delta方法对其分布进行预测并计算栖息地适宜性指数(habitat suitability index,HSI)和资源分布重心。时空模型的偏差解释率为65.50%,模型分析表明,影响大泷六线鱼资源分布最主要的环境因子为水深(22.11%),其次为底层水温(12.98%),底层盐度(0.09%)的影响较小,水深与其分布存在正向相关性,底层水温与其分布存在负向相关性,底层盐度与其分布存在弱正向线性关系。时空模型的残差独立性和异质性较GAM更强,其交叉验证回归线斜率为0.90±0.38。模型预测结果表明,大泷六线鱼主要分布在34.5°N以北,120.0°E以东的海域,其栖息地适宜性指数的高值区域呈现逐年收缩的趋势,资源分布重心呈现向东北海域转移的趋势,这可能是气候变迁以及捕捞压力共同作用的结果。本研究解析了大泷六线鱼在海州湾的时空分布,对于深入了解大泷六线鱼的分布动态和科学的渔业管理具有重要意义。
