Stream diatom assemblages as environmental indicators - A cross-regional assessment

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http://hdl.handle.net/10138/340611

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Pajunen , V , Kahlert , M & Soininen , J 2020 , ' Stream diatom assemblages as environmental indicators - A cross-regional assessment ' , Ecological Indicators , vol. 113 , 106183 . https://doi.org/10.1016/j.ecolind.2020.106183

Title: Stream diatom assemblages as environmental indicators - A cross-regional assessment
Author: Pajunen, Virpi; Kahlert, Maria; Soininen, Janne
Contributor organization: Department of Geosciences and Geography
Helsinki Institute of Sustainability Science (HELSUS)
Date: 2020-06
Language: eng
Number of pages: 10
Belongs to series: Ecological Indicators
ISSN: 1470-160X
DOI: https://doi.org/10.1016/j.ecolind.2020.106183
URI: http://hdl.handle.net/10138/340611
Abstract: Ongoing climatic change and anthropogenic pressure highlight the importance of reliable assessment of the ecological status of freshwaters. Bioindicators are used widely in ecological assessments as biotic assemblages reflect the environmental conditions in current ecosystems. However, the robustness of bioindicators relies on the transferability of indices and models outside the regions they were derived from. We tested the reliability of stream diatom assemblages as indicators of water chemistry and climatic factors in a cross-regional assessment by developing a predictive model with diatom assemblage data from Sweden and using it to model stream conditions in Finland. The inference models and predictions were performed using the Boosted Regression Trees (BRT) method, separately in species and genus levels. The predictive performance of the calibration models in Sweden were good or moderate for both water chemistry and climatic variables, both at species and genus levels. The most important climatic (growing degree days, r(2) = 0.57) and water chemistry variables (pH, r(2) = 0.65; and total phosphorus (TP), r(2) = 0.52) could be inferred from diatom assemblages relatively well. However, predictive performances of the cross-regional models were low (r(2)
Subject: Bioindicators
Biomonitoring
Predictive modelling
Stream diatoms
BENTHIC DIATOMS
MONITORING EUTROPHICATION
NICHE CONSERVATISM
CLIMATE-CHANGE
COMMUNITIES
POPULATION
REGRESSION
ECOLOGY
RIVERS
1181 Ecology, evolutionary biology
Peer reviewed: Yes
Rights: cc_by_nc_nd
Usage restriction: openAccess
Self-archived version: acceptedVersion


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