University of Oulu

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, Ecological Indicators, Volume 121, 2021, 106986, ISSN 1470-160X, https://doi.org/10.1016/j.ecolind.2020.106986

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

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Author: Jyväsjärvi, Jussi1; Lehosmaa, Kaisa1; Aroviita, Jukka2;
Organizations: 1University of Oulu, Ecology and Genetics Research Unit, P.O. Box 3000, FI-90014, Finland
2Finnish Environment Institute, Freshwater Centre, P.O. Box 413, FI-90014 Oulu, Finland
3University of Oulu, Water, Energy and Environmental Engineering Research Unit, P.O. Box 4300, FI-90014, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.9 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202103298697
Language: English
Published: Elsevier, 2021
Publish Date: 2021-03-29
Description:

Abstract

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.

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Series: Ecological indicators
ISSN: 1470-160X
ISSN-E: 1872-7034
ISSN-L: 1470-160X
Volume: 121
Article number: 106986
DOI: 10.1016/j.ecolind.2020.106986
OADOI: https://oadoi.org/10.1016/j.ecolind.2020.106986
Type of Publication: A1 Journal article – refereed
Field of Science: 1181 Ecology, evolutionary biology
1172 Environmental sciences
Subjects:
Funding: This study was funded by the Academy of Finland (projects 128377 and 263597), University of Oulu (Kvantum), Maj and Tor Nessling foundation, the MARS project (7th EU Framework Program, Theme 6 Contract No.: 603378) and Maa- ja vesitekniikan tuki ry., Ministry of Agriculture and Forestry of Finland and BIOWATER Nordic Centre of Excellence.
Academy of Finland Grant Number: 128377
Detailed Information: 128377 (Academy of Finland Funding decision)
Copyright information: © 2020 Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
  https://creativecommons.org/licenses/by-nc-nd/4.0/