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Spatial scales of interactions among bacteria and between bacteria and the leaf surface.

ABSTRACT: Microbial life on plant leaves is characterized by a multitude of interactions between leaf colonizers and their environment. While the existence of many of these interactions has been confirmed, their spatial scale or reach often remained unknown. In this study, we applied spatial point pattern analysis to 244 distribution patterns of Pantoea agglomerans and Pseudomonas syringae on bean leaves. The results showed that bacterial colonizers of leaves interact with their environment at different spatial scales. Interactions among bacteria were often confined to small spatial scales up to 5-20 ?m, compared to interactions between bacteria and leaf surface structures such as trichomes which could be observed in excess of 100 ?m. Spatial point-pattern analyses prove a comprehensive tool to determine the different spatial scales of bacterial interactions on plant leaves and will help microbiologists to better understand the interplay between these interactions.

SUBMITTER: Esser DS

PROVIDER: S-EPMC4399446 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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Spatial scales of interactions among bacteria and between bacteria and the leaf surface.

Esser Daniel S DS Leveau Johan H J JH Meyer Katrin M KM Wiegand Kerstin K

FEMS microbiology ecology 20141224 3

Microbial life on plant leaves is characterized by a multitude of interactions between leaf colonizers and their environment. While the existence of many of these interactions has been confirmed, their spatial scale or reach often remained unknown. In this study, we applied spatial point pattern analysis to 244 distribution patterns of Pantoea agglomerans and Pseudomonas syringae on bean leaves. The results showed that bacterial colonizers of leaves interact with their environment at different s ...[more]

PMID: 25764562

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Project description:Even with increasing interest in the ecological importance of intraspecific trait variation (ITV) for better understanding ecological processes, few studies have quantified ITV in seedlings and assessed constraints imposed by trade-offs and correlations among individual-level leaf traits. Estimating the amount and role of ITV in seedlings is important to understand tree recruitment and long-term forest dynamics. We measured ten different size, economics, and whole leaf traits (lamina and petiole) for more than 2,800 seedlings (height ≥ 10 cm and diameter at breast height < 1 cm) in 283 seedling plots and then quantified the amount of ITV and trait correlations across two biological (intraspecific and interspecific) and spatial (within and among plots) scales. Finally, we explored the effects of trait variance and sample size on the strength of trait correlations. We found about 40% (6%-63%) variation in leaf-level traits was explained by ITV across all traits. Lamina and petiole traits were correlated across biological and spatial scales, whereas leaf size traits (e.g., lamina area) were weakly correlated with economics traits (e.g., specific lamina area); lamina mass ratio was strongly related to the petiole length. Trait correlations varied among species, plots, and different scales but there was no evidence that the strength of trait relationships was stronger at broader than finer biological and spatial scales. While larger trait variance increased the strength of correlations, the sample size was the most important factor that was negatively related to the strength of trait correlations. Our results showed that a large amount of trait variation was explained by ITV, which highlighted the importance of considering ITV when using trait-based approaches in seedling ecology. In addition, sample size was an important factor that influenced the strength of trait correlations, which suggests that comparing trait correlations across studies should consider the differences in sample size.

Dataset Information

Spatial scales of interactions among bacteria and between bacteria and the leaf surface.

Publications

Spatial scales of interactions among bacteria and between bacteria and the leaf surface.

Similar Datasets

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