The Experts below are selected from a list of 31479 Experts worldwide ranked by ideXlab platform
Donald D. Davis - One of the best experts on this subject based on the ideXlab platform.
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staghorn sumac rhus typhina a new bioindicator to detect phytotoxic levels of ambient ozone in the eastern united states
Northeastern Naturalist, 2019Co-Authors: Lauren K Seiler, Dennis R Decoteau, Richard P Marini, Donald D. DavisAbstract:In our air pollution studies at The Pennsylvania State University, we have successfully used Prunus serotina (Black Cherry), Asclepias syriaca (Common Milkweed), Apocynum androsaemifolium (Spreading Dogbane), and Ailanthus altissima (Tree-of-Heaven) as ozone-sensitive Bioindicators to detect phytotoxic levels of ambient ozone. However, ambient ozone concentrations have decreased in our study area, and we are seeking a more sensitive bioindicator species. We observed significant levels of ambient ozone-induced leaf injury (stipple) on native Rhus typhina (Staghorn Sumac) within a field in a central Pennsylvania, suggesting that this species might serve as a new and highly sensitive ozone bioindicator. Therefore, we conducted a preliminary survey to determine the incidence and severity of ozone-induced stipple on Staghorn Sumac. In the same location, we concurrently evaluated the level of foliar stipple on the ozone-sensitive bioindicator species listed above. Staghorn Sumac developed significantly greater ozone-induced symptoms than the other Bioindicators and has potential to serve as a bioindicator to detect phytotoxic levels of ambient ozone in the eastern US.
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Spatial and temporal patterns of bioindicator mercury in pennsylvania oak forest.
Journal of Environmental Quality, 2013Co-Authors: James R. Mcclenahen, Russell J. Hutnik, Donald D. DavisAbstract:We monitored spatial and temporal patterns of total Hg in forest Bioindicators to assess possible local, regional, and global changes in atmospheric Hg deposition. Total Hg concentrations were monitored in leaves and fresh litterfall of northern red oak (Quercus rubra L.), on an epiphytic moss (Dicranum montanum Hedw.) on northern red oak stems, and in surface soil organic matter (Oₑ and Oₐ horizons) in Pennsylvania oak-dominated forests. Variously configured plots were used to monitor Hg deposition near local coal-fired generating stations and an industrial city and along an extended regional transect. Linearly decreasing temporal trends in Hg concentrations occurred in leaves, litterfall, moss, and soil Oₑ and Oₐ. Mean annual Hg concentrations were often greater near local emissions sources compared with remote areas, especially in the initial monitoring period. Decreasing time trends for different impact areas tended to converge due to greater rates of Hg decrease where initial bioindicator Hg levels were higher. Fresh litter and soil Oₑ showed the greatest overall potential as Hg Bioindicators. We conclude that Hg deposition has been significantly decreasing over time throughout the study area as a result of locally and regionally declining Hg emissions. Reductions in Hg emissions are likely a co-benefit of the 1990 Clean Air Act regulations and changing industrial activities. Recent leveling of several bioindicator Hg time trends may foretell a shift in Hg depositional patterns. Mercury monitoring studies such as this fulfill a need for documenting local and regional effects of emissions reduction.
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Spatial and temporal patterns of bioindicator mercury in pennsylvania oak forest.
Journal of environmental quality, 2013Co-Authors: James R. Mcclenahen, Russell J. Hutnik, Donald D. DavisAbstract:We monitored spatial and temporal patterns of total Hg in forest Bioindicators to assess possible local, regional, and global changes in atmospheric Hg deposition. Total Hg concentrations were monitored in leaves and fresh litterfall of northern red oak ( L.), on an epiphytic moss ( Hedw.) on northern red oak stems, and in surface soil organic matter (O and O horizons) in Pennsylvania oak-dominated forests. Variously configured plots were used to monitor Hg deposition near local coal-fired generating stations and an industrial city and along an extended regional transect. Linearly decreasing temporal trends in Hg concentrations occurred in leaves, litterfall, moss, and soil O and O. Mean annual Hg concentrations were often greater near local emissions sources compared with remote areas, especially in the initial monitoring period. Decreasing time trends for different impact areas tended to converge due to greater rates of Hg decrease where initial bioindicator Hg levels were higher. Fresh litter and soil O showed the greatest overall potential as Hg Bioindicators. We conclude that Hg deposition has been significantly decreasing over time throughout the study area as a result of locally and regionally declining Hg emissions. Reductions in Hg emissions are likely a co-benefit of the 1990 Clean Air Act regulations and changing industrial activities. Recent leveling of several bioindicator Hg time trends may foretell a shift in Hg depositional patterns. Mercury monitoring studies such as this fulfill a need for documenting local and regional effects of emissions reduction.
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Incidence of ozone symptoms on vegetation within a National Wildlife Refuge in New Jersey, USA
Environmental Pollution, 2006Co-Authors: Donald D. Davis, Teodora OrendoviciAbstract:Abstract During 1993–1996 and 2001–2003, we evaluated the percentage of plants (incidence) exhibiting ozone-induced foliar symptoms on vegetation within a National Wildlife Refuge located along the Atlantic Ocean coast of New Jersey, USA. Incidence varied among plant species and years. Bioindicator plants most sensitive to ozone, across all years, included native common milkweed (Asclepias syriaca) and wild grape (Vitis spp.), as well as introduced tree-of-heaven (Ailanthus altissima). Less sensitive Bioindicators included Virginia creeper (Parthenocissus quinquefolia) and winged sumac (Rhus coppolina). Black cherry (Prunus serotina) and sassafras (Sassafras albidum) were least sensitive. The greatest incidence of ozone symptoms, across all plant species, occurred in 1996, followed by 2001 > 1995 > 1994 > 1993 > 2003 > 2002. A model was developed that showed a statistically significant relationship between incidence of ozone symptoms and the following parameters: plant species, Palmer Drought Severity Index, and the interaction of W126 × N100 measures of ambient ozone.
Otso Ovaskainen - One of the best experts on this subject based on the ideXlab platform.
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Long-term shifts in water quality show scale-dependent bioindicator responses across Russia – Insights from 40 year-long bioindicator monitoring program
Ecological Indicators, 2019Co-Authors: Otso Ovaskainen, Benjamin Weigel, Oleg Potyutko, Yury BuyvolovAbstract:Abstract Scale-related assessment strategies are important contributions to successful ecosystem management. With varying impact of environmental drivers from local to regional scales, a focal task is to understand scale-dependent responses when assessing the state of an ecosystem. In this study we use large-scale monitoring data, spanning 40 years and including four aquatic bioindicator groups (phytoplankton, zooplankton, periphyton, zoobenthos) to expose the long-term changes of water quality across Russia. We include four hierarchical spatial scales (region, basin, waterbody and observation point) to identify the relative importance of different spatio-temporal scales for the variation of each bioindicator and patterns of co-variation among the Bioindicators at different hierarchical levels. We analysed the data with Hierarchical Modelling of Species Communities (HMSC), an approach that belongs to the framework of joint species distribution models. We performed a cross validation to reveal the predictive power of modelled bioindicator variation, partitioned explained variance among the fixed effects (waterbody type, and influence of human population density) and the random effects (spatial and spatio-temporal variation at the four hierarchical scales), and examined the co-variation among Bioindicators at each spatio-temporal scale. We detected generally decreasing water quality across Russian freshwaters, yet with region and bioindicator specific trends. For all Bioindicators, the dominating part of the variation was attributed the largest (region) and smallest (observation point) hierarchical scales, the region particularly important for benthic and the observation point for pelagic Bioindicators. All Bioindicators captured the same spatial variation in water quality at the smallest scale of observation point, with phytoplankton, zooplankton and periphyton being associated positively to each other and negatively to zoobenthos. However, at larger spatial scales and at spatio-temporal scales, the associations among the Bioindicators became more complex, with phytoplankton and zooplankton showing opposite trends over time. Our study reveals the sensitivity of Bioindicators to spatial and temporal scales. While delivering unidirectional robust water quality assessments at the local scale, bioindicator co-variation is more complex over larger geographic scales and over time.
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long term shifts in water quality show scale dependent bioindicator responses across russia insights from 40 year long bioindicator monitoring program
Ecological Indicators, 2019Co-Authors: Benjamin Weigel, Oleg Potyutko, Otso Ovaskainen, Yury BuyvolovAbstract:Abstract Scale-related assessment strategies are important contributions to successful ecosystem management. With varying impact of environmental drivers from local to regional scales, a focal task is to understand scale-dependent responses when assessing the state of an ecosystem. In this study we use large-scale monitoring data, spanning 40 years and including four aquatic bioindicator groups (phytoplankton, zooplankton, periphyton, zoobenthos) to expose the long-term changes of water quality across Russia. We include four hierarchical spatial scales (region, basin, waterbody and observation point) to identify the relative importance of different spatio-temporal scales for the variation of each bioindicator and patterns of co-variation among the Bioindicators at different hierarchical levels. We analysed the data with Hierarchical Modelling of Species Communities (HMSC), an approach that belongs to the framework of joint species distribution models. We performed a cross validation to reveal the predictive power of modelled bioindicator variation, partitioned explained variance among the fixed effects (waterbody type, and influence of human population density) and the random effects (spatial and spatio-temporal variation at the four hierarchical scales), and examined the co-variation among Bioindicators at each spatio-temporal scale. We detected generally decreasing water quality across Russian freshwaters, yet with region and bioindicator specific trends. For all Bioindicators, the dominating part of the variation was attributed the largest (region) and smallest (observation point) hierarchical scales, the region particularly important for benthic and the observation point for pelagic Bioindicators. All Bioindicators captured the same spatial variation in water quality at the smallest scale of observation point, with phytoplankton, zooplankton and periphyton being associated positively to each other and negatively to zoobenthos. However, at larger spatial scales and at spatio-temporal scales, the associations among the Bioindicators became more complex, with phytoplankton and zooplankton showing opposite trends over time. Our study reveals the sensitivity of Bioindicators to spatial and temporal scales. While delivering unidirectional robust water quality assessments at the local scale, bioindicator co-variation is more complex over larger geographic scales and over time.
Yury Buyvolov - One of the best experts on this subject based on the ideXlab platform.
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Long-term shifts in water quality show scale-dependent bioindicator responses across Russia – Insights from 40 year-long bioindicator monitoring program
Ecological Indicators, 2019Co-Authors: Otso Ovaskainen, Benjamin Weigel, Oleg Potyutko, Yury BuyvolovAbstract:Abstract Scale-related assessment strategies are important contributions to successful ecosystem management. With varying impact of environmental drivers from local to regional scales, a focal task is to understand scale-dependent responses when assessing the state of an ecosystem. In this study we use large-scale monitoring data, spanning 40 years and including four aquatic bioindicator groups (phytoplankton, zooplankton, periphyton, zoobenthos) to expose the long-term changes of water quality across Russia. We include four hierarchical spatial scales (region, basin, waterbody and observation point) to identify the relative importance of different spatio-temporal scales for the variation of each bioindicator and patterns of co-variation among the Bioindicators at different hierarchical levels. We analysed the data with Hierarchical Modelling of Species Communities (HMSC), an approach that belongs to the framework of joint species distribution models. We performed a cross validation to reveal the predictive power of modelled bioindicator variation, partitioned explained variance among the fixed effects (waterbody type, and influence of human population density) and the random effects (spatial and spatio-temporal variation at the four hierarchical scales), and examined the co-variation among Bioindicators at each spatio-temporal scale. We detected generally decreasing water quality across Russian freshwaters, yet with region and bioindicator specific trends. For all Bioindicators, the dominating part of the variation was attributed the largest (region) and smallest (observation point) hierarchical scales, the region particularly important for benthic and the observation point for pelagic Bioindicators. All Bioindicators captured the same spatial variation in water quality at the smallest scale of observation point, with phytoplankton, zooplankton and periphyton being associated positively to each other and negatively to zoobenthos. However, at larger spatial scales and at spatio-temporal scales, the associations among the Bioindicators became more complex, with phytoplankton and zooplankton showing opposite trends over time. Our study reveals the sensitivity of Bioindicators to spatial and temporal scales. While delivering unidirectional robust water quality assessments at the local scale, bioindicator co-variation is more complex over larger geographic scales and over time.
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long term shifts in water quality show scale dependent bioindicator responses across russia insights from 40 year long bioindicator monitoring program
Ecological Indicators, 2019Co-Authors: Benjamin Weigel, Oleg Potyutko, Otso Ovaskainen, Yury BuyvolovAbstract:Abstract Scale-related assessment strategies are important contributions to successful ecosystem management. With varying impact of environmental drivers from local to regional scales, a focal task is to understand scale-dependent responses when assessing the state of an ecosystem. In this study we use large-scale monitoring data, spanning 40 years and including four aquatic bioindicator groups (phytoplankton, zooplankton, periphyton, zoobenthos) to expose the long-term changes of water quality across Russia. We include four hierarchical spatial scales (region, basin, waterbody and observation point) to identify the relative importance of different spatio-temporal scales for the variation of each bioindicator and patterns of co-variation among the Bioindicators at different hierarchical levels. We analysed the data with Hierarchical Modelling of Species Communities (HMSC), an approach that belongs to the framework of joint species distribution models. We performed a cross validation to reveal the predictive power of modelled bioindicator variation, partitioned explained variance among the fixed effects (waterbody type, and influence of human population density) and the random effects (spatial and spatio-temporal variation at the four hierarchical scales), and examined the co-variation among Bioindicators at each spatio-temporal scale. We detected generally decreasing water quality across Russian freshwaters, yet with region and bioindicator specific trends. For all Bioindicators, the dominating part of the variation was attributed the largest (region) and smallest (observation point) hierarchical scales, the region particularly important for benthic and the observation point for pelagic Bioindicators. All Bioindicators captured the same spatial variation in water quality at the smallest scale of observation point, with phytoplankton, zooplankton and periphyton being associated positively to each other and negatively to zoobenthos. However, at larger spatial scales and at spatio-temporal scales, the associations among the Bioindicators became more complex, with phytoplankton and zooplankton showing opposite trends over time. Our study reveals the sensitivity of Bioindicators to spatial and temporal scales. While delivering unidirectional robust water quality assessments at the local scale, bioindicator co-variation is more complex over larger geographic scales and over time.
Kurt Nielsen - One of the best experts on this subject based on the ideXlab platform.
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Eelgrass as a Bioindicator Under the European Water Framework Directive
Water Resources Management, 2005Co-Authors: Dorte Krause-jensen, Tina Maria Greve, Kurt NielsenAbstract:Eelgrass is the most widespread plant in temperate coastal waters. It is regarded as a useful indicator of water quality because water clarity regulates its extension towards deeper waters, i.e. the depth limit. This study analyses the use of eelgrass depth limits as a bioindicator under the Water Framework Directive (WFD). The WFD demands that ecological status is classified by relating the actual level of Bioindicators to a so-called ‘reference level’, reflecting a situation of limited anthropogenic influence. The directive further demands that reference levels are defined for ‘water body types’ with similar hydromorphological characteristics, and that the classification thereby becomes ‘type-specific’.
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Eelgrass as a Bioindicator Under the European Water Framework Directive
Water Resources Management, 2005Co-Authors: Dorte Krause-jensen, Tina Maria Greve, Kurt NielsenAbstract:Eelgrass is the most widespread plant in temperate coastal waters. It is regarded as a useful indicator of water quality because water clarity regulates its extension towards deeper waters, i.e. the depth limit. This study analyses the use of eelgrass depth limits as a bioindicator under the Water Framework Directive (WFD). The WFD demands that ecological status is classified by relating the actual level of Bioindicators to a so-called ‘reference level’, reflecting a situation of limited anthropogenic influence. The directive further demands that reference levels are defined for ‘water body types’ with similar hydromorphological characteristics, and that the classification thereby becomes ‘type-specific’.
Britta Schaffelke - One of the best experts on this subject based on the ideXlab platform.
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a bioindicator system for water quality on inshore coral reefs of the great barrier reef
Marine Pollution Bulletin, 2012Co-Authors: Katharina Fabricius, Timothy F Cooper, Craig Humphrey, Glenn Death, Johnston Davidson, Helene Legrand, Angus Thompson, Sven Uthicke, Britta SchaffelkeAbstract:Abstract Responses of bioindicator candidates for water quality were quantified in two studies on inshore coral reefs of the Great Barrier Reef (GBR). In Study 1, 33 of the 38 investigated candidate indicators (including coral physiology, benthos composition, coral recruitment, macrobioeroder densities and FORAM index) showed significant relationships with a composite index of 13 water quality variables. These relationships were confirmed in Study 2 along four other water quality gradients (turbidity and chlorophyll). Changes in water quality led to multi-faceted shifts from phototrophic to heterotrophic benthic communities, and from diverse coral dominated communities to low-diversity communities dominated by macroalgae. Turbidity was the best predictor of biota; hence turbidity measurements remain essential to directly monitor water quality on the GBR, potentially complemented by our final calibrated 12 Bioindicators. In combination, this bioindicator system may be used to assess changes in water quality, especially where direct water quality data are unavailable.
