Performing Department
(N/A)
Non Technical Summary
Soil microbiomes offer major opportunities to increase soil carbon, improve soil health, and ensure the sustainability of dryland systems. However, in drylands of the southwestern USA, there are few avenues to incorporate knowledge of the soil microbiome and plant-microbe interactions into management plans. Meanwhile, in these arid and semi-arid ecosystems, the additive effects of land- use intensification (grazing), climate changes (e.g., increasing drought events), and increased soil erosion create a threatening self-reinforcing cycle that will inhibit these soils to effectively produce food, sequester carbon, and support other ecosystems services in the future. Mechanistic studies are needed that will 1) assess how soil microbial diversity, composition, and functions vary across heterogeneous rangelands in the southwestern USA, 2) quantify the impacts of combined land-use and climate change, and 3) provide realistic management solutions for future restoration and conservation efforts. Here we propose a study that will test for the interacting effects of climate change and land-use on soil microbial functions, plant productivity, and carbon storage across the Sonoran and Chihuahuan Deserts. Using novel microbiome analyses, combined with an arid- focused soil health assessment framework, and innovative greenhouse experiments we will quantify the genomic and functional variability of the soil microbiome across dryland ecosystems and advance the basic understanding of microbial controls on carbon pools in drylands under global change pressures. We will then identify scenarios in which plant-microbe interactions and consortia of soil microbes can be leveraged in land management to resist increasing drought regimes and increase soil carbon under different land-uses.
Animal Health Component
10%
Research Effort Categories
Basic
80%
Applied
10%
Developmental
10%
Goals / Objectives
Goal: Link soil microbiome diversity and functions to soil carbon dynamics and ultimately make dryland ecosystems more sustainable for livestock grazing, support livelihoods of ranchers, and increase resistance to the pressures of climate change. Objective 1: Quantify microbiome diversity and function in relation to soil abiotic factors to build a stronger basis of carbon sequestration in dryland systems.Test the hypothesis that the relative connection between ecosystem functions (carbon storage, nutrient cycling, and water filtration) to microbiome functions will be positively related to higher plant productivity and overall better soil health.Objective2: Build a mechanistic understanding of feedbacks between dryland plants and their microbiome under drought and grazing conditions. Test the hypothesis that grasses that support soil food webs with a higher diversity of microbial functions will be better able to recover from drought and grazing events, while still increasing carbon storage.Objective 3:Integrate theories, measurements, and models of microbiome functional components and soil organic carbon dynamics. Test ourhypothesis that by including two microbial functional groups (copiotrophs and oligotrophs) in our model, we will be able to better predict SOC dynamics in dryland soils.
Project Methods
OBJECTIVE 1Soil collection We have identified 6 arid-rangeland sites spread between western Arizona and western Texas located within the Sonoran or Chihuahuan deserts - Oatman Flats Ranch, AZ, the Santa Rita Experimental Range, AZ, The Nature Conservancy, AZ, the Jornada Experimental Range, NM, Hueco Tanks State Park and Historical Site, TX and the Indio Mountain Research Site, TX (Fig. 3). Sites are similar in their relatively low annual precipitation, high average temperatures (Table 1), and both typically have a monsoon season in August. Additionally, sites represent a range of land-use and habitat types, soil texture, and soil organic carbon in the top 1 meter. Plant communities vary from grasslands to desert scrub dominated by mesquite, creosote, cactus, and grasses to those in the riparian region that have large oak and cottonwood trees. Following the summer monsoons (in Early October/November), at each site we will select 5 - 40m transects, and 4 replicates will be collected across each 40m transect. For each replicate approximately 100g of soils will be collected from the top 10cm of the soil. Samples will be homogenized and sieved to 2mm, thereby one subsample of will be stored at -80oC for DNA extraction for community analyses (Ramirez Lab) and metagenomics (Barberan Lab) (120 samples). The remaining soil will be analyzed for a suite of soil health indicators in the Blankinship Soil Health Lab at the University of Arizona.Shotgun metagenomics molecular analyses: For each of the 120 samples, CNA will be extracted using the QIAGEN DNeasy PowerLyzer PowerSoil Kit. DNA will be fragmented to ~500 bp length and ligated to Illumina adaptors using the QIAseq FX DNA Library Kit. Quality and quantity will be determined with Agilent 4150 TapeStation DNA bioanalyzer. Samples will be shotgun-sequenced on a 2x150bp paired-end Illumina NovaSeq6000 platform with S4 chemistry.Amplicon molecular analyses: From extracted DNA from the 120 samples, we will sequence the V4 hypervariable region of the 16S rRNA, using the 515-F and 926-R primer pair for bacteria and archaea. For fungi, we will sequence the first internal transcribed spacer (ITS1) region of the rRNA operon, using the ITS1-F and ITS2 primer pair93. Marker genes will be amplified using PCR (Roche LightCycler 96) with Illumina adapters and unique error-correcting 12-bp barcodes. Amplicon products will be quantified fluorescently with ThermoFisher Scientific Quant-It PicoGreen dsDNA assay, pooled in equimolar concentration, and sequenced on an Illumina Miseq instrument.Plant Community Assessment: For each soil collection point at all field sites, we will classify plant species by functional groups (annual and perennial grasses, other graminoids, annual, biennial, and perennial forbs, annual, biennial, and perennial legumes, and woody species) as described in Prober et al.100, in a 1 m2 plot around the collection point. Additionally, we will visually estimate percent cover for all vascular plants and assign to species, when possible, otherwise plant genera will be used for alpha diversity measurements.Soil Carbon: Total soil C and N will be measured using an elemental combustion system (Elementar Vario Max Cube). Soil inorganic C will be measured using an established calcimetry method, thus enabling total organic carbon by the difference between total and inorganic C. Labile (fast-cycling) particulate organic carbon (POC) versus stable (slow-cycling) mineral-associated organic carbon (MAOC) will be separated using dispersion followed by size separation (< 53 μm) using a centrifugation methodand subsequent analysis on the elemental combustion system.Moisture, Nutrients, and Aggregates: Carbon in the clay and silt fraction also positively correlates with soil C storage in arid and semiarid ecosystems. Soil physical structure will be measured by water-stable macroaggregates (using established wet-sieving methods with automated 250-μm sieve). Soil water-holding capacity will be measured using an established gravimetric method. Soil alkalinity and salinity will be measured by pH and electrical conductivity, respectively (2:1 water:soil). Finally, all plant-available macronutrients (N, P, K, Ca, Mg, and S) and micronutrients (Cl, Fe, B, Mn, Zn, Cu, Mo, and Ni) will be measured using an established Mehlich III extraction followed by analysis of extracts on a Thermo Scientific inductively coupled plasma optical emission spectrometer.OBJECTIVE 2Feedback Experiment:We will establish a 3-Phase greenhouse feedback experiment where 5 grass species- 4 native, 1 non-native (Sprobolus cryptandrus, Aristida purpurea, Muhlenbergia porter, Bouteloua eropod, and Eragrostis lehmanniana) will be subjected to a full factorial design of treatments (control, drought, grazing, drought + grazing) with 6 replicates (Fig. 4). Each phase or 'growing season' will begin at t0 where 6 seedlings of each species are planted into 500g of soil. After 3 months, plants will be destructively harvested to weigh both above- and belowground biomass and soil will be collected to analyze the bacterial and fungal communities via amplicon sequencing (see AIM1), and microbial functional capabilities via enzyme analyses and nutrient cycling1.. Then 250g of soil from Phase 1 will be mixed with 250g of sterile soil (to ensure nutrient levels are sufficient) for the Phase 2. New seedlings will be planted, and the drought and grazing treatments will be repeated. This will be repeated for Phase 3 (total 360 samples for all three phases). Drought will be based on an assumption that the average rainfall in the SW drylandis 243mm/year, with 50% of the rain falling from July to Septemberof their annually projected rainfall. Pots will be weighed weekly, and pots will be maintained at their desired weight. Grazing will be simulated through clipping of grasses once grasses reach 10cm.Plant Biomass Above- and belowground biomass production of each treatment will be compared with control to study legacy effects of droughts, microbial inoculum, and litter addition. Biomass will be calculated relative to control to cancel differences between the phases other than drought legacy. This comparison will be used to analyze any differences in biomass production through drought legacies, with or without a different timing. Differences between the biomass production of each plant species will be compared between all the treatments.Soil nutrients and enzyme analyses: See Objective 1OBJECTIVE 3Lab soil incubation:Briefly, 4 replicates from each of the 6 sites (AIM 1) (24), plus 4 replicates from each of the 4 treatments and at each phase in Aim 2 (36) will be selected. Totaling 60 samples. SIR will be performed first. Then, to measure CO2 flux rates, soils will be incubated at 20°C for 1 year. During that time CO2 flux will be measured at 24 time points, and microbial biomass and bacterial community structure will be measured at the end of the incubation.These data will then be used to calibrate a model with 2 carbon pools and 2 microbial functional pools.Substrate induced respiration (SIR): SIR will be measured in the lab by adding different carbon substrates and measuring the difference in headspace CO2 concentrations with an infra-red gas analyzer (LI-6200 Portable Photosynthesis System, LI-COR Biosciences, Lincoln, USA) along a time series.Model Development:In our model we will substitute equations relating to enzyme activity with microbial biomass and set a standard decay rate of soil C we will separate C into fresh organic matter(FOM) and soil organic matter (SOM). Additionally, implication of the two carbon pools is that at a given time, there is a portion of C that is more labile (FOM), as compared to the more recalcitrant SOM pool. Further, we can assume that the FOM pool is limited (in the absence of C inputs), and thus in a laboratory experiment this pool would be mostly depleted.