Non-target impacts of fungicide disturbance on phyllosphere yeasts in conventional and no-till management

Abstract

Fungicides reduce fungal pathogen populations and are essential to food security. Understanding the impacts of fungicides on crop microbiomes is vital to minimizing unintended consequences while maintaining their use for plant protection. However, fungicide disturbance of plant microbiomes has received limited attention, and has not been examined in different agricultural management systems. We used amplicon sequencing of fungi and prokaryotes in maize and soybean microbiomes before and after foliar fungicide application in leaves and roots from plots under long-term no-till and conventional tillage management. We examined fungicide disturbance and resilience, which revealed consistent non-target effects and greater resiliency under no-till management. Fungicides lowered pathogen abundance in maize and soybean and decreased the abundance of Tremellomycetes yeasts, especially Bulleribasidiaceae, including core microbiome members. Fungicide application reduced network complexity in the soybean phyllosphere, which revealed altered co-occurrence patterns between yeast species of Bulleribasidiaceae, and Sphingomonas and Hymenobacter in fungicide treated plots. Results indicate that foliar fungicides lower pathogen and non-target fungal abundance and may impact prokaryotes indirectly. Treatment effects were confined to the phyllosphere and did not impact belowground microbial communities. Overall, these results demonstrate the resilience of no-till management to fungicide disturbance, a potential novel ecosystem service provided by no-till agriculture.

Fig. 1. Effects of fungicides on fungal leaf composition in maize and soybean.

A separate analysis was conducted for soybean (a) 0- (b) 13- or (c) 33-days post fungicide (dpf) application or maize (d) 0- (e) 9- or (f) 34-dpf since there was a significant interaction between dpf and fungicide. Constrained analysis of principal coordinates (CAP) analyses was constrained by the effect of fungicide while partialling out the effect of management. The percentage of total variation due to fungicide is expressed above the plot. The significance was determined based on 1000 permutations.

Fig. 2. Fungicides alter soybean network complexity.

A microbial co-occurrence network was constructed using taxa with a mean relative abundance greater than 1⁻⁵ and present in greater than 5 % of samples. Subnetworks were generated for each sample based on the OTUs present within those samples, and each point represents a subnetwork. a Network complexity (i.e., linkage density) and (b) number of edges were then calculated for each subnetwork. Comparisons are based on Wilcox ranked sign tests for soybean conventional management and no-till. An asterisks indicate the level of significance; * = p ≤ 0.05, ** = p ≤ 0.01, *** = p ≤ 0.001. Comparisons for maize are shown in Fig. S5.

Fig. 3. Management scheme alters the recovery dynamics of phyllosphere fungi following fungicide treatment.

The composition of fungal operational taxonomic units (OTUs) that were significantly different in abundance, as indicated with analysis of compositions of microbiomes (ANCOM) analysis (n = 12). a Composition of fOTUs whose abundance was significantly different following a fungicide disturbance. Bars below zero indicate the fOTU decreased in abundance, whereas bars above zero indicate the fOTU increased in abundance. b Recovery of fungi in soybean leaf samples in conventional (conv.) or no-till management. All fungi recovered in maize leaf samples. c Composition of fOTUs within the Tremellomycetes whose abundance was significantly altered following a fungicide disturbance. d Recovery dynamics of Tremellomycetes fOTUs following a fungicide disturbance in conv. or no-till. All Tremellomycete fungi recovered in maize. e Soybean or (f) maize plots subjected to a fungicide treatment compared to non-sprayed control plots. g Abundance occupancy relationship with the recovery dynamics of the Bulleribasidiaceae fOTUs significantly affected by the fungicide treatment. All Bulleribasidiaceae fOTUs recovered in maize. A full list of core fungi and prokaryotes for soybean or maize leaves are found in Table S8. An asterisks indicate the level of significance; * = p ≤ 0.05, ** = p ≤ 0.01, *** = p ≤ 0.001.

Fig. 4. Indirect effects of fungicides on prokaryotic communities from altered Bulleribasidiaceae diversity on soybean leaves.

Relationship of observed versus predicted Bulleribasidiaceae richness in conventional (a) or no-till (c) from random forest models using prokaryote OTU abundance in fungicide treated plots. The most important (P < 0.05) prokaryote OTUs for random forest model accuracy in fungicide treated conventional (b) or no-till (d). The cumulative mean edge weight calculated from each sub-network of a meta-network of Bulleribasidiaceae edges between Sphinogomonas, Hymenobacter, or Methylobacterium OTUs and alterations to co-occurrence strength with and without fungicides under (e) conventional and (f) no-till crop management. Parallel analysis was not conducted with maize due to the lack of evidence to alteration of network structure and complexity (Fig. S5).