Fungal assemblages in predictive stream bioassessment: A cross-taxon comparison along multiple stressor gradients

Degradation of freshwater ecosystems requires efficient tools for assessing the ecological status of freshwater biota and identifying potential cause(s) for their biological degradation. While diatoms and macroinvertebrates are widely used in stream bioassessment, the potential utility of microbial...

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Autores principales:	Jussi Jyväsjärvi, Kaisa Lehosmaa, Jukka Aroviita, Jarno Turunen, Maria Rajakallio, Hannu Marttila, Mikko Tolkkinen, Heikki Mykrä, Timo Muotka
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Aquatic fungi Bioassessment Diatoms Leaf decomposition Macroinvertebrates Predictive modelling Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/3f5d73e7926a4b0ea7fe8f5e497859a8
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spelling	oai:doaj.org-article:3f5d73e7926a4b0ea7fe8f5e497859a82021-12-01T04:31:46ZFungal assemblages in predictive stream bioassessment: A cross-taxon comparison along multiple stressor gradients1470-160X10.1016/j.ecolind.2020.106986https://doaj.org/article/3f5d73e7926a4b0ea7fe8f5e497859a82021-02-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X20309250https://doaj.org/toc/1470-160XDegradation of freshwater ecosystems requires efficient tools for assessing the ecological status of freshwater biota and identifying potential cause(s) for their biological degradation. While diatoms and macroinvertebrates are widely used in stream bioassessment, the potential utility of microbial communities has not been fully harnessed. Using data from 113 Finnish streams, we assessed the performance of aquatic leaf-associated fungal decomposers, relative to benthic macroinvertebrates and diatoms, in modelling-based bioassessment. We built multi-taxon niche -type predictive models for fungal assemblages by using genus-based and sequence-based identification levels. We then compared the models’ precision and accuracy in the prediction of reference conditions (number of native taxa) to corresponding models for macroinvertebrates and diatoms. Genus-based fungal model nearly equalled the accuracy and precision of our best model (macroinvertebrates), whereas the sequence-based model was less accurate and tended to overestimate the number of taxa. However, when the models were applied to streams disturbed by anthropogenic stressors (nutrient enrichment, sedimentation and acidification), alone or in combination, the sequence-based fungal assemblages were more sensitive than other taxonomic groups, especially when multiple stressors were present. Microbial leaf decomposition rates were elevated in sediment-stressed streams whereas decomposition attributable to leaf-shredding macroinvertebrates was accelerated by nutrients and decelerated by sedimentation. Comparison of leaf decomposition results to model output suggested that leaf decomposition rates do not detect effectively the presence of multiple simultaneous disturbances. The rapid development of global microbial database may soon enable species-level identification of leaf-associated fungi, facilitating a more precise and accurate modelling of reference conditions in streams using fungal communities. This development, combined with the sensitivity of aquatic fungi in detecting the presence of multiple human disturbances, makes leaf-associated fungal assemblages an indispensable addition in a stream ecologist’s toolbox.Jussi JyväsjärviKaisa LehosmaaJukka AroviitaJarno TurunenMaria RajakallioHannu MarttilaMikko TolkkinenHeikki MykräTimo MuotkaElsevierarticleAquatic fungiBioassessmentDiatomsLeaf decompositionMacroinvertebratesPredictive modellingEcologyQH540-549.5ENEcological Indicators, Vol 121, Iss , Pp 106986- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Aquatic fungi Bioassessment Diatoms Leaf decomposition Macroinvertebrates Predictive modelling Ecology QH540-549.5
spellingShingle	Aquatic fungi Bioassessment Diatoms Leaf decomposition Macroinvertebrates Predictive modelling Ecology QH540-549.5 Jussi Jyväsjärvi Kaisa Lehosmaa Jukka Aroviita Jarno Turunen Maria Rajakallio Hannu Marttila Mikko Tolkkinen Heikki Mykrä Timo Muotka Fungal assemblages in predictive stream bioassessment: A cross-taxon comparison along multiple stressor gradients
description	Degradation of freshwater ecosystems requires efficient tools for assessing the ecological status of freshwater biota and identifying potential cause(s) for their biological degradation. While diatoms and macroinvertebrates are widely used in stream bioassessment, the potential utility of microbial communities has not been fully harnessed. Using data from 113 Finnish streams, we assessed the performance of aquatic leaf-associated fungal decomposers, relative to benthic macroinvertebrates and diatoms, in modelling-based bioassessment. We built multi-taxon niche -type predictive models for fungal assemblages by using genus-based and sequence-based identification levels. We then compared the models’ precision and accuracy in the prediction of reference conditions (number of native taxa) to corresponding models for macroinvertebrates and diatoms. Genus-based fungal model nearly equalled the accuracy and precision of our best model (macroinvertebrates), whereas the sequence-based model was less accurate and tended to overestimate the number of taxa. However, when the models were applied to streams disturbed by anthropogenic stressors (nutrient enrichment, sedimentation and acidification), alone or in combination, the sequence-based fungal assemblages were more sensitive than other taxonomic groups, especially when multiple stressors were present. Microbial leaf decomposition rates were elevated in sediment-stressed streams whereas decomposition attributable to leaf-shredding macroinvertebrates was accelerated by nutrients and decelerated by sedimentation. Comparison of leaf decomposition results to model output suggested that leaf decomposition rates do not detect effectively the presence of multiple simultaneous disturbances. The rapid development of global microbial database may soon enable species-level identification of leaf-associated fungi, facilitating a more precise and accurate modelling of reference conditions in streams using fungal communities. This development, combined with the sensitivity of aquatic fungi in detecting the presence of multiple human disturbances, makes leaf-associated fungal assemblages an indispensable addition in a stream ecologist’s toolbox.
format	article
author	Jussi Jyväsjärvi Kaisa Lehosmaa Jukka Aroviita Jarno Turunen Maria Rajakallio Hannu Marttila Mikko Tolkkinen Heikki Mykrä Timo Muotka
author_facet	Jussi Jyväsjärvi Kaisa Lehosmaa Jukka Aroviita Jarno Turunen Maria Rajakallio Hannu Marttila Mikko Tolkkinen Heikki Mykrä Timo Muotka
author_sort	Jussi Jyväsjärvi
title	Fungal assemblages in predictive stream bioassessment: A cross-taxon comparison along multiple stressor gradients
title_short	Fungal assemblages in predictive stream bioassessment: A cross-taxon comparison along multiple stressor gradients
title_full	Fungal assemblages in predictive stream bioassessment: A cross-taxon comparison along multiple stressor gradients
title_fullStr	Fungal assemblages in predictive stream bioassessment: A cross-taxon comparison along multiple stressor gradients
title_full_unstemmed	Fungal assemblages in predictive stream bioassessment: A cross-taxon comparison along multiple stressor gradients
title_sort	fungal assemblages in predictive stream bioassessment: a cross-taxon comparison along multiple stressor gradients
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/3f5d73e7926a4b0ea7fe8f5e497859a8
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Fungal assemblages in predictive stream bioassessment: A cross-taxon comparison along multiple stressor gradients

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