ArticlePloS one2026
Complexity of leaf surface texture affects microbial colonization in temperate forest tree species.
Article in PloS one, 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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12 authors.
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Abstract
Throughout their life cycle, tree leaves are subject to colonization and degradation by microorganisms, including fungi, bacteria, and algae. These relationships co-evolved with chemical properties, leaf shape, and surface structures. Here we developed (i) a novel quantitative trait describing leaf surface texture complexity based on variables extracted from scanning electron microscopic images, resulting in a quantitative score of surface texture complexity on a tree species level. This complexity score was then used (ii) to test functional hypotheses, quantifying the contribution of leaf surface texture complexity in context of growth habitat preferences and colonization patterns by fungi and bacteria. We show that (iii) leaf surface texture complexity correlated with anatomical features such as stomatal density and leaf orientation as well as with Ellenberg temperature habitat indicator. Increasing leaf surface texture complexity was negatively correlated with leaf-associated fungal and bacterial specialists. Moreover, leaves with higher leaf surface texture complexity values showed reduced richness of colonization with plant pathogens (broad-leaved species) or lichenization (conifers), suggesting protection effects. Our results highlight leaf surface texture complexity as a previously underappreciated trait that may be a key to understanding microbial diversity between tree species and interaction patterns with leaf-associated microbes. This opens promising avenues for future research on plant-microbe co-evolution, trait-based ecosystem modeling, and the potential use of surface traits in forest management and disease resistance strategies.
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