ArticlePeerJ2026
Substrate affinities of slime moulds (Eumycetozoa) and their potential as indicators of forest microhabitat conditions.
Article in PeerJ, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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
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