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Small-scale variability of benthic macroinvertebrates distribution and its effects on biological monitoring

Published online by Cambridge University Press:  21 August 2014

Alex Laini ,
Alessio Vorti ,
Rossano Bolpagni  and
Pierluigi Viaroli
Alex Laini*
Affiliation:
Department of Life Sciences, University of Parma, Viale G.P. Usberti 33/A – 43124 Parma, Italy
Alessio Vorti
Affiliation:
Department of Life Sciences, University of Parma, Viale G.P. Usberti 33/A – 43124 Parma, Italy
Rossano Bolpagni
Affiliation:
Department of Life Sciences, University of Parma, Viale G.P. Usberti 33/A – 43124 Parma, Italy
Pierluigi Viaroli
Affiliation:
Department of Life Sciences, University of Parma, Viale G.P. Usberti 33/A – 43124 Parma, Italy
*
*Corresponding author: [email protected]
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Abstract

The within-site patchy distribution of organisms represents a natural source of variability that can bias the precision of biotic indices. This study aims to evaluate the spatial distribution of benthic macroinvertebrates and its effects on the biotic index used in Italy for assessing the ecological status of rivers. Two main issues were considered: the sampling design and the minimum number of replicates which are necessary to achieve a given precision level. To this purpose, 30 surber replicates were taken, instead of the ten required for the application of the index, in a homogeneous reach of a mid-sized perennial river (Trebbia River, Northern Italy). The percentile confidence interval (p.c.i.) of the index was calculated from 1000 possible communities with the resampling method and the bootstrap procedure. The 95% p.c.i. varied from 0.195 to 0.227, which is great considering that the index ranges from 0 to 1. The metrics based on abundance data were especially affected by the heterogeneous distribution of organisms. The resulting precision of the index increased only partially when doubling the sampling effort.

Keywords

Macroinvertebratesmultimetric indexWater Framework Directiveuncertaintymicrodistribution
Type
Research Article
Information
Annales de Limnologie - International Journal of Limnology , Volume 50 , Issue 3 , 2014 , pp. 211 - 216
Copyright
© EDP Sciences, 2014

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References

Barnes, J.B., Vaughan, I.P. and Ormerod, S.J., 2013. Reappraising the effects of habitat structure on river macroinvertebrates. Freshw. Biol., 58, 2154–2167.CrossRefGoogle Scholar
Bournaud, M., Tachet, H., Berly, A. and Cellot, B., 1998. Importance of microhabitat characteristics in the macrobenthos microdistribution of a large river reach. Ann. Limnol. - Int. J. Lim., 34, 83–98.CrossRefGoogle Scholar
Boyero, L. and Bailey, R.C., 2001. Organization of macroinvertebrate communities at a hierarchy of spatial scales in a tropical stream. Hydrobiologia, 464, 219–225.CrossRefGoogle Scholar
Buffagni, A. and Erba, S., 2007. Macroinvertebrati acquatici e Direttiva 2000/60/EC (WFD) – Parte A. Metodo di campionamento per i fiumi guadabili. IRSA-CNR Notiziario dei Metodi Analitici, 1, 2–27.Google Scholar
Buffagni, A., Erba, S. and Pagnotta, R., 2008. Definizione dello Stato ecologico dei fiumi sulla base dei macroinvertebrati bentonici per la 200/60/EC (WFD): il sistema di classificazione MacrOper per il monitoraggio operativo. IRSA-CNR Notiziario dei Metodi Analitici, 1, 24–46.Google Scholar
Bray, J.R. and Curtis, J.T., 1957. An ordination of the upland forest communities of southern Wisconsin. Ecol. Monogr., 27, 325–349.CrossRefGoogle Scholar
Brooks, A.J., Haeusler, T.I.M., Reinfelds, I. and Williams, S., 2005. Hydraulic microhabitats and the distribution of macroinvertebrate assemblages in riffles. Freshw. Biol., 50, 331–344.CrossRefGoogle Scholar
Campaioli, S., Ghetti, P.F., Minelli, A. and Ruffo, S., 1994. Manuale per il riconoscimento dei macroinvertebrati delle acque dolci italiane Volume 1, Edizione del Museo di Storia Naturale di Trento, 357 p.
Campaioli, S., Ghetti, P.F., Minelli, A. and Ruffo, S., 1998. Manuale per il riconoscimento dei macroinvertebrati delle acque dolci italiane Volume 2, Edizione del Museo di Storia Naturale di Trento, 135 p.
Clarke, K.R., 1993. Non-parametric multivariate analyses of changes in community structure. Aust. J. Ecol., 18, 117–143.CrossRefGoogle Scholar
Clarke, R.T. and Hering, D., 2006. Errors and uncertainty in bioassessment methods – major results and conclusions from the STAR project and their application using STARBUGS. Hydrobiologia, 566, 433–439.CrossRefGoogle Scholar
Culp, J.M., Walde, S.J. and Davies, R.W., 1983. Relative importance of substrate particle size and detritus to stream benthic macroinvertebrate microdistribution. Can. J. Fish Aquat. Sci., 40, 1568–1574.CrossRefGoogle Scholar
Efron, B. and Tibshirani, R.J., 1993. An Introduction to the Bootstrap, Chapman & Hall, New York, 456 p.CrossRefGoogle Scholar
Fenoglio, S., Bo, T., Agosta, P. and Malacarne, G., 2005. Temporal and spatial patterns of coarse particulate organic matter and macroinvertebrate distribution in a low-order Apennine stream. J. Freshw. Ecol., 20, 539–547.CrossRefGoogle Scholar
Heino, J., Louhi, P. and Muotka, T., 2004. Identifying the scales of variability in stream macroinvertebrate abundance, functional composition and assemblage structure. Freshw. Biol., 49, 1230–1239.CrossRefGoogle Scholar
Lake, P.S., 2000. Disturbance, patchiness, and diversity in streams. J. N. Am. Benthol. Soc., 19, 573–592.CrossRefGoogle Scholar
Legendre, P. and Legendre, L., 1998. Numerical Ecology, (2nd edn), Elsevier Scientific, Amsterdam, 853 p.Google Scholar
Li, J., Herlihy, A., Gerth, W., Kaufmann, P., Gregory, S., Urquhart, S. and Larsen, D.P., 2001. Variability in stream macroinvertebrates at multiple spatial scales. Freshw. Biol., 46, 87–97.CrossRefGoogle Scholar
Niemi, G.J. and McDonald, M.E., 2004. Application of ecological indicators. Annu. Rev. Ecol. Evol. S., 35, 89–111.CrossRefGoogle Scholar
Oksanen, J., Guillaume Blanchet, F., Kindt, R., Legendre, P., Minchin, P.R., O'Hara, R.B., Simpson, G.L., Solymos, P., Henry, M., Stevens, H. and Wagner, H., 2013. vegan: Community Ecology Package. R package version 2.0–8. http://CRAN.R-project.org/package=vegan.
R Core Team, 2013. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.
Vlek, H.E., Šporka, F. and Krno, I., 2006. Influence of macroinvertebrates sample size in bioassessment of stream. Hydrobiologia, 566, 523–542.CrossRefGoogle Scholar
Woodward, G., 2009. Biodiversity, ecosystem functioning and food webs in freshwaters: assembling the jigsaw puzzle. Freshw. Biol., 54, 2171–2187.CrossRefGoogle Scholar
Woodward, G., Friberg, N. and Hildrew, A.G., 2010. Science and non-science in the biomonitoring and conservation of fresh waters. In: de Carlo, F. and Bassano, A. (ed.), Freshwater Ecosystems and Aquaculture Research, Nova Science, Hauppauge, NY, USA, 277–288.Google Scholar