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. 2024 Dec 3;10(12):836.
doi: 10.3390/jof10120836.

Bedrock-Dependent Effects of Climate Change on Terricolous Lichens Along Elevational Gradients in the Alps

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Bedrock-Dependent Effects of Climate Change on Terricolous Lichens Along Elevational Gradients in the Alps

Chiara Vallese et al. J Fungi (Basel). .

Abstract

In this study, we focused on the bedrock-dependent effects of climate change on terricolous lichen communities along elevational gradients in the Alps. In particular, we contrasted between carbonatic and siliceous bedrock, hypothesizing more favourable conditions on siliceous than on carbonatic bedrock, where dryer conditions may exacerbate the effects of climate change. To test this hypothesis, we compared terricolous lichen diversity patterns between the two bedrock types in terms of (1) species richness, (2) beta-diversity, (3) proportion of cryophilous species, and (4) functional diversity, also testing the effect of the elevational gradient as a proxy for expected climate warming. Our results indicate that the most cold-adapted part of the terricolus lichen biota of the Alps could be especially threatened in the near future, mainly on carbonatic bedrock. Actually, contrasting diversity patterns were found between carbonatic and siliceous bedrock, clearly revealing a bedrock-dependent effect of climate change on terricolous lichens of the Alps. As hypothesized, siliceous bedrock hosts a richer lichen biota than carbonatic bedrock, reflecting a general richness pattern at the national level. In general, siliceous bedrock seems to be less prone to rapid pauperization of its lichen biota, providing more suitable climatic refugia that can mitigate the effects of climate warming on terricolous lichens.

Keywords: Dolomites; Rhaetian Alps; beta-diversity; climate change; cryophylous species; functional diversity; species richness; terricolous lichens.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Location of the study area with a conceptualization of the sampling design. We selected 6 transects on carbonatic and 6 on siliceous bedrock. Each elevational transect was split into 100 m belts. In each belt, lichens were recorded in 4 randomly selected rectangular (40 × 50 cm) plots. This figure was assembled using Adobe Illustrator 2024.
Figure 2
Figure 2
(a) Species richness of lichens on carbonatic and siliceous bedrock. (b) The relationship between lichen species richness and elevation [m]. The lines show the predicted species richness values, with 95% confidence intervals (bands) according to the linear models. Points represent the observed data. Points represent the observed data. Round points and the solid line represent carbonatic bedrock, while triangles and the dashed line represent siliceous bedrock.
Figure 3
Figure 3
Relationship between the three facets of beta diversity and elevational difference [m] on carbonatic ((a) blue regression line) and siliceous ((b) red regression line) bedrock. The three facets of beta diversity were total beta diversity (βtot), its partition in species replacement (βrepl), and richness difference (βrich).
Figure 4
Figure 4
(a) Proportion of cryophilous lichen species on carbonatic and siliceous bedrock. Functional traits investigated were growth form, photobiont type, and type of reproduction. Functional diversity was quantified as the mean species pairwise dissimilarity (MPD) based on the occurrence of the species in each elevational belt. (b) Relationship between the proportion of cryophilous species and elevation [m]. Lines show the predicted proportion of cryophilous species values with 95% confidence intervals (bands) according to the linear models. Points represent the observed data. Round points and the solid line represent carbonatic substrata, while triangles and the dashed line represent siliceous substrata.
Figure 5
Figure 5
(a) Functional diversity on carbonatic and siliceous bedrock. (b) The relationship between functional diversity and elevation [m]. Lines show the predicted functional diversity values with 95% confidence intervals (bands) according to the linear models. Points represent the observed data. Round points and the solid line represent carbonatic bedrock, while triangles and the dashed line represent siliceous bedrock.

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