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Assessment of Aquatic Macroinvertebrate Sampling Methods for Nonregulatory Water Quality Programs
Author(s) -
McCarty Elizabeth,
Nichols Rebecca,
McCreadie John,
Grant Jerome
Publication year - 2019
Publication title -
journal of environmental quality
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.888
H-Index - 171
eISSN - 1537-2537
pISSN - 0047-2425
DOI - 10.2134/jeq2019.01.0024
Subject(s) - species evenness , species richness , sampling (signal processing) , dominance (genetics) , water quality , environmental science , abundance (ecology) , ecology , biodiversity , water framework directive , sorting , hydrology (agriculture) , biology , computer science , geology , geotechnical engineering , filter (signal processing) , computer vision , biochemistry , gene , programming language
Many land management water quality programs must assess water quality using aquatic macroinvertebrates for nonregulatory purposes but conduct these assessments using regulatory protocols. The costs of providing data using regulatory protocols can be financially burdensome for these programs. Macroinvertebrate water quality monitoring in Great Smoky Mountians National Park in the United States is assessed using six sampling methods (kicknet, Dnet, rockwash, sand, leafpack, and visual samples). Data for this study were collected from nine wadeable streams flowing through high‐gradient mountainous forests. Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa were identified to the lowest taxonomic unit as was practical. Comparisons were made among different sampling methods to determine if nonregulatory programs can obtain similar data with fewer collection methods. Richness, abundance, Shannon diversity, evenness, and dominance were compared among each of the sampling methods. Effort ratio (abundance/richness) was also compared. Methods producing high‐diversity samples were then combined and compared with the current six‐method protocol. All comparisons were made using an ANOVA and general linear model ( P < 0.05). Using combinations of kicknet–visual or rock wash–Dnet–visual samples resulted in similar richness, Shannon diversity, evenness, and dominance compared with all methods, while having lower abundance and effort ratios. Reducing sampling methods will reduce time invested in field sampling, sorting, and identifications, which will reduce program costs for nonregulatory management programs. Core Ideas Aquatic macroinvertebrate nonregulatory sampling methods can be reduced. Rockwash–Dnet–visual or kicknet–visual samples have similar diversity to all methods. Reducing sampling methods will save field, sorting, and identification time. Programs can get similar nonregulatory water quality data for less money and effort.