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Article . 2026 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Substrate affinities of slime moulds (Eumycetozoa) and their potential as indicators of forest microhabitat conditions

Authors: Tomasz Pawłowicz; Tomasz Oszako;

Substrate affinities of slime moulds (Eumycetozoa) and their potential as indicators of forest microhabitat conditions

Abstract

Background Slime moulds (Eumycetozoa) inhabit moisture-buffered microhabitats such as bark, dead wood, bryophyte mats and litter. Their assemblages are expected to track fine-scale forest structure and may therefore provide tractable signals for bioindication of forest microhabitat conditions, which represent local components of forest ecosystem condition. However, their potential as substrate-associated forest bioindicators has rarely been evaluated using harmonised data and study designs that account for sampling effort. Methods A taxonomically standardised, georeferenced occurrence archive spanning forests in Central and Eastern Europe was used to quantify substrate affinities of slime moulds. The archive was also used to assess their suitability as ecological indicators of forest substrate (microhabitat) classes. Records were assigned to a consolidated 10-class substrate scheme representing forest substrate microhabitats where substrate descriptors were available. Analyses were restricted to these substrate (microhabitat) classes, which provided the analytical framework for all indicator assessments. Results After sample- size- and coverage-standardisation of substrate-level record counts, record-based diversity and evenness remained high and similar across substrates. However, assemblage composition differed consistently among corticolous (bark), lignicolous (dead wood), bryophilous (bryophyte mats) and other substrates. Effort-offset multi-species modelling quantified substrate-level contrasts, whereas effort-weighted IndVal statistics identified candidate indicator taxa, with the clearest signals for lignicolous and corticolous material. Species showed and interpretable elevational modes. In contrast, pH-associated patterns were evaluated using structured screening and should be interpreted cautiously. This screening nevertheless helps to delineate preliminary pH associations and to prioritise systematic co-measurement. Conclusions Effort-aware analyses supported consistent, substrate-associated differences in assemblage composition among forest substrate (microhabitat) classes, whereas sample-size- and coverage-standardised diversity and evenness remained broadly similar across substrates. The clearest indicator signals were recovered for lignicolous and corticolous material, with Cribraria piriformis , Amaurochaete atra and Arcyria ferruginea characterising lignicolous (dead wood) substrates and Paradiacheopsis and Calomyxa characterising corticolous (bark) substrates. Accordingly, substrate-resolved Eumycetozoa occurrences can inform effort-aware, regionally stratified bioassessment of forest microhabitat conditions in European forests. Given the near-absence of measured pH values in the archive, pH associations remain preliminary and systematic co-measurement of pH is a priority. Improved coverage of under-represented substrates is also required to strengthen operational Eumycetozoa-based bioindication.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Top 10%
Average
Average
gold