Compost-derived microbial dispersal in rangelands

The proposed study has two primary research objectives, A) determine how far compost derived microbial communities disperse beyond the primary application site, B) investigate whether this dispersal is beneficial to plant biomass and soil health.  

Plot Design: At three ranches with differing environmental conditions (Table 1), experimental plots were inoculated at ¼” depth with manure compost on sites with <5% slope in summer 2021 and 2022 and are 64 m2, with 16 m between plots. Plots were randomly assigned to compost (n = 3 for 2021, n = 3 for 2022) or control plots (n = 3). Existing data for these sites includes initial microbial composition of soils and compost, plant biomass and soil properties and sampling from 2022. As part of the existing Agriculture and Food Research Initiative grant 2021-67019-34249, we will measure the microbial community and plant/soil characteristics inside the plots in August-September 2023.  

Proposed Sampling Design: The space between plots will be used to sample multiple distances from existing plots in 2023. New 8 m long transects will be established parallel to the edge of the plot at distances of 1, 2, 4 and 7 m away from the plot (Figure 1). Transects will be placed on the most level side of the plots to minimize effects of water runoff spreading compost.  

Objective A1) Determine how far and how rapidly fungal and bacterial components of compost will disperse away from compost application sites.  

We will use Illumina sequencing to identify individual genera, and species (when possible), along a distance gradient. Sterilized soil cores will be used to collect 8 soil samples to a depth of 10 cm along each transect. Cores will be homogenized, and 25 mg will be used for DNA extraction via a standard soil extraction kit, following manufacturer protocols. Extractions will be sent for whole fungal and bacterial community sequencing of the ITS2 and 16S regions, respectively, at the University of Arizona Genetics Core. Microbial community composition and relative abundances of these organisms at each sampling point will be analyzed via USEARCH and Qiime2 (Quantitative Insights into Microbial Ecology, version 2), software packages that will assign microbial identity and the frequency of occurrence of each organism will be completed in March 2024. We will assess differences in relative microbial community by distance using a PERMANOVA (Permutational Multivariate Analysis of Variance) using a Bray Curtis similarity matrix and be completed in May 2024.  

Objective A2) Determine if microbial biomass will increase along a distance gradient adjacent to compost application sites. 

Using samples and microbial community data collected from A1, qPCR (quantitative polymerase chain reaction), a method to quantify DNA, will be used to determine absolute abundances of bacteria and fungi at each distance. Statistical analysis will be the same those used in Objective A1 and be completed concurrently. 

Objective A3) Determine if specific microbial taxa differentially disperse outside the compost application site and their potential specialized functions such as N2 fixation.   

Using samples and microbial community data collected from Objective A1, microbial function will be identified using publicly available databases such as FUNGuild (Fungi Functional Guild) and literature available via GenBank. Statistical analyses will be the same as those used in A1. Assessment of functional implications are part of data analysis but will occur in June and July 2024 after results are obtained from A1. 

We hypothesize that compost associated microbial community similarity will be negatively correlated with distance from the application site (Figure 2a) based on the distance-decay theory (16), of which dispersal is a determining factor (17). Transects nearest the application site will require fewer dispersal pressures than those farther away, and experience not only wind and animal transport but also water-based transport through soil pores. If wind and animal transport occur gradually, differences between distances in plots with compost addition in 2021 will be weak and relatively stronger for the plots where compost was added in 2022. However, if the tenet “everything is everywhere and the environment selects” holds true microbial community structure will not vary strongly by distance between years (Figure 2a).  

We hypothesize that fungi with active or ejection-based dispersal mechanisms will be the dominant fungal components at the farthest distances as they will benefit from this additional method of transport. The most successful bacterial dispersers will be within the Actinomycetes phylum because they are able to produce their own mycelial network (18) and are successful components of the microbial community in environments subject to high temperature or water stress (19). Overall bacterial biomass will be positively correlated with Basidiomycetes as these fungi can form hyphal “highways” (20,21) which assist with bacterial transport. 

Objective B) Determine if the benefits of compost on soil properties and plant biomass will be present adjacent to the compost application site and if this correlates with microbial community shifts.  

Six soil samples will be collected per transect/plot and aggregate stability will be assessed using Herrick et al.’s method (22).  

Infiltration rate will be determined by using the NRCS (Natural Resources Conservation Service) Infiltration Protocol. As water infiltration is unlikely to change at the scale between transects, measurements will be taken inside the plot and at 7 m.  

Aboveground biomass will be determined using Nutnet protocols (23) using clip strips at each transect providing 5 sampling points per transect. Plant material will be clipped to the top of the root crown, 1 cm above the ground. Biomass will be transported to the lab, sorted to remove oxidized standing biomass, dried and weighed. 

Soil properties and plant biomass results will be compared to microbial biomass and community composition to correlate potential relationships (Figure 2b).  

We hypothesize that water infiltration, aggregate stability and aboveground biomass will be highest inside the plot and decrease in a similar fashion to that of microbial biomass (Figure 2b). Microbial biomass will likely decrease over time and with increasing distances from the application site. In conjunction with these decreases aggregate stability and water infiltration will decrease; however, drops will be less dramatic than those of biomass. Because aggregate stability and water infiltration increases are potentially due to microbial extrusion of exopolysaccharides, which function as binding agents and have high water holding capacity (24), stabilization and water holding services remain after microbes have died, extending their beneficial services temporally. Forage biomass changes are expected to be associated with specific microbial taxa and their corresponding functional role, pathogenesis for example causing a reduction in biomass.  

Implications for researchers: Correlating the results of ecological responses to specific taxonomic groups may provide novel, testable hypotheses for which taxa drive function in drylands.