Evaluation of Plecoptera (Insecta) community composition using multivariate technics in a biodiversity hotspot View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2017-02-07

AUTHORS

N. Kazanci, G. Turkmen, P. Ekingen, O. Basoren

ABSTRACT

Eastern Black Sea Region of Turkey is a sub-ecoregion of the Caucasus Ecoregion, and its Plecoptera fauna is similar to fauna of Caucasus with unique endemic species of the region. The Caucasus Ecoregion is one of the “WWF Global 200 Ecoregions,” and it is also included in the list of top 25 hotspots in the World. Running water ecosystems of Eastern Black Sea sub-ecoregion are the most sensitive to land use change and global climate change. High-altitude aquatic ecosystems are more strongly threatened by global climate change in the region. Plecoptera constitute the most important part of the biodiversity of running waters in the region. Among the benthic macroinvertebrate taxa, Plecoptera is the best indicator of ecological conditions of running waters. The influence of environmental variables on the distribution of twenty Plecoptera species in running water ecosystems (headwaters, crenon, epirhithron, metarhithron) was assessed using canonical correspondence analysis. Sampling was carried out in 2009 and 2011. Eleven end groups were generated from the TWINSPAN analysis. Isoperla rhododendri, Isoperla grammatica, Protonemura bifida, Protonemura eumontana and Perla caucasica were closely related to pH, dissolved oxygen and riparian vegetation. Brachyptera transcaucasica transcaucasica, Nemoura martynovia, Nemoura taurica and Protonemura eumontana were related to Mg and Cu. The results show that the Plecoptera assemblage composition was affected by DO, pH, EC, temperature, nitrite, Ca, Mg, Fe, Cu, Zn, Al, riparian vegetation, altitude and stream width. More... »

PAGES

1307-1316

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s13762-017-1245-y

DOI

http://dx.doi.org/10.1007/s13762-017-1245-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1083698833


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