Spatial correlation of macroinvertebrate assemblages in streams and the implications for bioassessment programs

Stream bioassessment using benthic macroinvertebrate assemblages is widely implemented by regulatory agencies, yet a critical question regarding spatial autocorrelation and sample independence remains: How much of a stream network does a point sample represent? Macroinvertebrate assemblages vary alo...

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Veröffentlicht in:Environmental monitoring and assessment 2021-06, Vol.193 (6), p.322-322, Article 322
Hauptverfasser: Shupryt, Michael P., Studinski, Jered M.
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Sprache:eng
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Zusammenfassung:Stream bioassessment using benthic macroinvertebrate assemblages is widely implemented by regulatory agencies, yet a critical question regarding spatial autocorrelation and sample independence remains: How much of a stream network does a point sample represent? Macroinvertebrate assemblages vary along a longitudinal gradient, likely due to a combination of natural and anthropogenic factors that alter water physiochemistry and habitat. A better understanding of how these gradients affect macroinvertebrate assemblage variance could prevent spatial over- and under-sampling within bioassessment efforts. This project investigated longitudinal patterns (10 s of km) of macroinvertebrate assemblages in 14 Wisconsin streams. Spatial autocorrelation was assessed using Moran’s I and other multivariate methods with an emphasis on estimating the distance at which assemblages no longer display spatial correlation. Within most streams, there was a linear, direct relationship between assemblage dissimilarity and longitudinal distance, with distance to independence (DTI) ranging from 1.7–13.5 km. DTI was most strongly affected by conductivity, which is often a surrogate for a suite of anthropogenic effects. With increasing conductivity, DTI increases, suggesting more homogenous assemblages in disturbed streams. Natural factors like watershed size, channel gradient, and riparian slope also affected DTI. Considering spatial correlation in monitoring designs could improve the efficiency and application of regulatory bioassessment programs.
ISSN:0167-6369
1573-2959
DOI:10.1007/s10661-021-09101-2