Frontiers in Plant Science · 2014 · 68 citations · 30 references
AgriculturePlant BiologyPlant SciencesMicrobial EcologyPlant EcologyPlant-microbe InteractionsAbiotic Stress ToleranceBlight DiseasesCrop Stress EcologyCrop-environment InteractionsPlant-pathogen InteractionsStress PhenotypingAbiotic StressAlpha DiversityBiotic StressIntergenic Spacer VariationNitrogen Fertilization EffectsNitrogen Fertilizer ManagementPhyllosphere Microbial DiversityPlant Functional Traits After Disturbance
Plant leaves are inhabited by a diverse group of microorganisms that are important contributors to optimal growth. Biotic and abiotic effects on plant growth are usually studied in controlled settings examining response to variation in single factors and in field settings with large numbers of variables. Multi-factor experiments with combinations of stresses bridge this gap, increasing our understanding of the genotype-environment-phenotype functional map for the host plant and the affiliated epiphytic community. The maize inbred B73 was exposed to single and combination abiotic and the biotic stress treatments: low nitrogen fertilizer and high levels of infection with southern leaf blight (causal agent Cochliobolus heterostrophus). Microbial epiphyte samples were collected at the vegetative early-season phase and species composition was determined using 16S ribosomal intergenic spacer analysis. Plant traits and level of southern leaf blight disease were measured late-season. Bacterial diversity was different among stress treatment groups (P < 0.001). Lower species richness-alpha diversity-was correlated with increased severity of southern leaf blight disease when disease pressure was high. Nitrogen fertilization intensified the decline in bacterial alpha diversity. While no single bacterial ribotype was consistently associated with disease severity, small sets of ribotypes were good predictors of disease levels. Difference in leaf bacterial-epiphyte diversity early in the season were correlated with plant disease severity, supporting further tests of microbial epiphyte-disease correlations for use in predicting disease progression.
30
R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
A new method for non‐parametric multivariate analysis of variance
Marti J. Anderson · Austral Ecology · 2001 · 13.3K citations