本研究尝试采用我国已有的季风气候区底栖动物观测值(O)/期望值(E)比值模型,在无足够数量参照样点的情况下,建立淮河流域O/E指数健康评价指标体系,评价淮河流域典型水体底栖动物物种组成完整性现状.于2014年夏季(8月)和秋季(11月)分别...本研究尝试采用我国已有的季风气候区底栖动物观测值(O)/期望值(E)比值模型,在无足够数量参照样点的情况下,建立淮河流域O/E指数健康评价指标体系,评价淮河流域典型水体底栖动物物种组成完整性现状.于2014年夏季(8月)和秋季(11月)分别调查了淮河流域20和25个典型水体的底栖动物和水质指标.O/E模型评价结果表明,监测点位在PC(Probabilities of Capture)>0和PC≥0.5条件下,夏季和秋季的物种期望丰富度分别约为25和9.所有25个点位中,仅1个点位为健康,其余为一般或较差;模型控制自然梯度后O/E0和O/E50值均没有显著的季节性差异(p=0.565和0.229).环境胁迫因子(TN、EC、CODCr和p H)和土地覆盖数据(水体比例、湿地比例、裸地比例、森林比例和草地比例)对秋季O/E50和O/E50-null的解释量高于夏季,TN是能够解释淮河流域典型水体夏季O/E指数变异最多的环境因子,p H和CODCr是能够解释秋季O/E指数变异最多的环境因子.研究表明,在缺少有效参照点位构建评价指标体系的情况下,在淮河流域应用已经构建的季风气候区底栖动物O/E指数模型进行健康评价是比较可靠的方法.展开更多
Freshwater ecosystems are threatened by flow regulation,sedimentation,habitat degradation,non-native species,and water pollution.These disturbances have led to global losses of biodiversity and habitats.Therefore,it i...Freshwater ecosystems are threatened by flow regulation,sedimentation,habitat degradation,non-native species,and water pollution.These disturbances have led to global losses of biodiversity and habitats.Therefore,it is essential to evaluate the ecological condition of freshwater ecosystems to promote effective management practices.Quantitative predictive models based on multivariate analyses of taxa richness are recognized ecological tools that can facilitate the monitoring and managing of freshwater ecosystems worldwide.However,few studies have used this approach to assess tropical rivers and streams.By evaluating predictive models,we can assess their usefulness for determining water-body taxonomic richness.We built a RIVPACS-type model based on macroinvertebrate assemblages(MINASPACS),for spatially extensive taxa richness assessments of Minas Gerais state streams,southeast Brazil.As a second objective,we assessed the sensitivity of the MINASPACS to human-induced disturbances affecting Minas Gerais streams through the relative risk(RR)approach.The MINASPACS model was trained with biological and environmental data from 78 reference sites and showed good accuracy(R^(2)>0.6,SD O/E=0.16).We found that percent of urban infrastructure,percent of catchment anthropogenic land use,Turbidity,Total Nitrogen,and Total Phosphorus represented significant risks to the taxa richness of Minas Gerais streams.Because of its accuracy,sensitivity,and use of map-level predictor variables,our model provides a clear,simple,and defensible measure of stream macroinvertebrate taxa richness across diverse biomes.展开更多
文摘本研究尝试采用我国已有的季风气候区底栖动物观测值(O)/期望值(E)比值模型,在无足够数量参照样点的情况下,建立淮河流域O/E指数健康评价指标体系,评价淮河流域典型水体底栖动物物种组成完整性现状.于2014年夏季(8月)和秋季(11月)分别调查了淮河流域20和25个典型水体的底栖动物和水质指标.O/E模型评价结果表明,监测点位在PC(Probabilities of Capture)>0和PC≥0.5条件下,夏季和秋季的物种期望丰富度分别约为25和9.所有25个点位中,仅1个点位为健康,其余为一般或较差;模型控制自然梯度后O/E0和O/E50值均没有显著的季节性差异(p=0.565和0.229).环境胁迫因子(TN、EC、CODCr和p H)和土地覆盖数据(水体比例、湿地比例、裸地比例、森林比例和草地比例)对秋季O/E50和O/E50-null的解释量高于夏季,TN是能够解释淮河流域典型水体夏季O/E指数变异最多的环境因子,p H和CODCr是能够解释秋季O/E指数变异最多的环境因子.研究表明,在缺少有效参照点位构建评价指标体系的情况下,在淮河流域应用已经构建的季风气候区底栖动物O/E指数模型进行健康评价是比较可靠的方法.
基金supported by Companhia Energética de Minas Gerais(CEMIG)through Programa Cemig-Peixe Vivo,Programa de Pesquisa e Desenvolvimento Aneel(Cemig GT-479,GT-487,GT-550,GT-599)Cemig/Fapemig(APQ-01961-15,APQ-00261-22,and CRA 3147)+5 种基金Fundação de Amparo á Pesquisa do Estado de Minas Gerais–FAPEMIG(APQ-01432-17 and APQ-261-22)Conselho Nacional de Desenvolvimento Científico e Tecnológico(CNPq 311002/2023-4 to DRM,and 304060/2020-8 to MC)MC is a Resident Professor at the Institute of Advanced Transdisciplinary Studies(IEAT/UFMG)Fundação para a Ciência e Tecnologia through MARE strategic project(UIDB/04292/2020)Associate Laboratory ARNET Project(LA/P/0069/2020)CEEC principal investigator to MJF,Coordenação de Aperfeiçoamento de Pessoal de Nível Superior(CAPES)Finance Code 001,Fulbright-Brazil to RMH,and Projeto Manuelzão/UFMG.
文摘Freshwater ecosystems are threatened by flow regulation,sedimentation,habitat degradation,non-native species,and water pollution.These disturbances have led to global losses of biodiversity and habitats.Therefore,it is essential to evaluate the ecological condition of freshwater ecosystems to promote effective management practices.Quantitative predictive models based on multivariate analyses of taxa richness are recognized ecological tools that can facilitate the monitoring and managing of freshwater ecosystems worldwide.However,few studies have used this approach to assess tropical rivers and streams.By evaluating predictive models,we can assess their usefulness for determining water-body taxonomic richness.We built a RIVPACS-type model based on macroinvertebrate assemblages(MINASPACS),for spatially extensive taxa richness assessments of Minas Gerais state streams,southeast Brazil.As a second objective,we assessed the sensitivity of the MINASPACS to human-induced disturbances affecting Minas Gerais streams through the relative risk(RR)approach.The MINASPACS model was trained with biological and environmental data from 78 reference sites and showed good accuracy(R^(2)>0.6,SD O/E=0.16).We found that percent of urban infrastructure,percent of catchment anthropogenic land use,Turbidity,Total Nitrogen,and Total Phosphorus represented significant risks to the taxa richness of Minas Gerais streams.Because of its accuracy,sensitivity,and use of map-level predictor variables,our model provides a clear,simple,and defensible measure of stream macroinvertebrate taxa richness across diverse biomes.
