Periphyton and phytoplankton samples were collected and analyzed from 393 locations in three midcontinent
(US) great rivers: the Upper Mississippi, Missouri and Ohio. From the 410 taxa identified, 303
taxa were common enough for multivariate analyses. Algae assemblages were quantified by multiple
metrics including biovolume (based on algal shape formulae and cell measurements), relative
biovolume, cell density, relative cell density, entity density (based on numbers of colonies, filaments or
free-living cells), and relative entity density. Relationships between algal metrics and both water quality
(e.g., nutrients, ionic properties, physicochemical parameters) and landscape-scale stressor data (e.g.,
proportions watershed with agriculture and urban development, impoundment, pollution pointsources)
were examined using multivariate analyses. Overall, algal metrics were more closely related to
water quality than to landscape stressors. Phytoplankton cell density was the best indicator of water
quality with 45% of the variance in the taxonomic data explained. Wesuspect that relationships between
periphyton and water quality were weaker because water grab samples did not reflect the prevailing
conditions to which the periphyton had been exposed. Phytoplankton also had a slightly stronger
relationship to landscape-scale stressor data than did periphyton. Biovolume metrics were the best
periphytic indicators of water quality and stressors. Absolute algal metrics, especially cell density,
consistently had stronger relationships to water quality and stressors than relative (percentage-based)
metrics.
Periphyton and phytoplankton samples were collected and analyzed from 393 locations in three midcontinent(US) great rivers: the Upper Mississippi, Missouri and Ohio. From the 410 taxa identified, 303taxa were common enough for multivariate analyses. Algae assemblages were quantified by multiplemetrics including biovolume (based on algal shape formulae and cell measurements), relativebiovolume, cell density, relative cell density, entity density (based on numbers of colonies, filaments orfree-living cells), and relative entity density. Relationships between algal metrics and both water quality(e.g., nutrients, ionic properties, physicochemical parameters) and landscape-scale stressor data (e.g.,proportions watershed with agriculture and urban development, impoundment, pollution pointsources)were examined using multivariate analyses. Overall, algal metrics were more closely related towater quality than to landscape stressors. Phytoplankton cell density was the best indicator of waterquality with 45% of the variance in the taxonomic data explained. Wesuspect that relationships betweenperiphyton and water quality were weaker because water grab samples did not reflect the prevailingconditions to which the periphyton had been exposed. Phytoplankton also had a slightly strongerrelationship to landscape-scale stressor data than did periphyton. Biovolume metrics were the bestperiphytic indicators of water quality and stressors. Absolute algal metrics, especially cell density,consistently had stronger relationships to water quality and stressors than relative (percentage-based)metrics.
การแปล กรุณารอสักครู่..
