Performing Department
(N/A)
Non Technical Summary
Project SummaryWhile there are many ways to assess soil, and much popular and research interest in soil health and regenerative agriculture practices, to date there is not a comprehensive framework or tool to understand what is "normal" or possible for improving soil conditions in agriculture or for ecological restoration. This project aims to fill that need by combining data from an already existing effort by researchers at land grant universities and the Colorado Dept. of Agriculture as well as natural and restored ecosystems to deepen our understanding of how managed soils compare to natural/restored soils and quantify the "soil health gap". The soil health gap is a way to assess the potential for soils to gain function and characteristics we know support diverse and robust life that considers the environmental and pedological processes inherent in a soil's characteristics, and ability and tendency to respond to changes in management. Ultimately, this research will be synthesized in a web-tool that will enable anyone to search and compare soil health data across the state by a number of variables such as soil type, climate, management practice, location, etc and compare it to natural & restored ecosystems which have been sampled in the state.Additionally, this project will advance fundamental knowledge of how management influences the behavior of soil microbial communities and their ability to accrue soil organic matter. This study will use a variety of soils under a range of plant diversity and perenniality to quantify how efficiently microbial communities utilize carbon and compare it to the form of the soil carbon in the soil.Together these efforts will advance our knowledge of how management impacts soil health, areas that have the greatest potential for improvement compared to relevant natural ecosystem benchmarks, and the role of plant diversity vs. perenniality in influencing the enhanced function of microbial communities. These efforts will also provide a tool for anyone, in particular the producers part of the Colorado STAR program, to better understand their soil conditions and how that compares to other soils across the state. Ultimately the hope is that this tool could be expanded to include additional data and synthesis across multiple regions to have a broad picture of soil health in the United States.Background and DetailsDespite the dearth of academic literature on soil health and soil carbon sequestration, there are few tools relevant to managers that provide meaningful interpretation of soil health. For soil carbon, the most commonly cited indicator of soil health, interpretation is 'more is better,' but soils have inherently different capacities to store and sequester carbon based on the soil forming factors originally proposed by Jenny (1941). Generating more trusted and relevant information to farmers and policy makers would encourage greater market and program entrance into regional programs designed to support farmers adopting new practices such as the Colorado Soil Health Program (CSHP) and emerging voluntary soil carbon markets. Moreover, soil organic matter (SOM) is most commonly assessed at the bulk soil level, though we know that organic matter is composed of functionally and chemically distinct forms (particulate (POM) and mineral-associated (MAOM)), which respond to management in different ways. Currently there is no tool or framework for farmers to be able to compare their soil health assessment to a relevant benchmark or interpret SOM fractions in a relevant way. This project aims to undertake a pilot project to fill this gap for growers in Colorado. In collaboration with the Colorado Soil Health program, this project will: 1a) Establish soil health and MAOM/POM benchmarks in native Colorado soils relevant to growers in the CSHP 1b) Assess the sensitivity of soil health and SOM to a gradient of conservation practices using the research sites from the CSHP and re-sampling previously studied farms; 2) Assess the effect of spatial vs. temporal plant diversity on microbial community function and SOM by comparing estimates of carbon-use-efficiency, enzyme and respiration activity, and SOM in soils across a spatio-temporal gradient of perenniality and diversity; and 3) Develop an online assessment tool for land managers to compare soil health to natural ecosystems in CO. This project will leverage soil health samples collected as part of the CSHP in conjunction with re-sampling previous research on working farms to create a database of current managed and natural ecosystem soil health in the state. Creating benchmarks and an online resource tool will allow land managers and policy makers to make better informed decisions on how to improve soil health locally and regionally with informed choices about the natural capacity of soil to store carbon. Additionally, this project will enhance understanding of how the universally recommended conservation management practice of increasing plant diversity and perenniality are associated with soil carbon sequestration.
Animal Health Component
0%
Research Effort Categories
Basic
60%
Applied
20%
Developmental
20%
Goals / Objectives
The major goals of this project are:Inform national approach to quantify the soil health gap and establish regional benchmarks for evaluating and improving soil healthDevelop a framework for interpreting soil organic carbon (SOC) change in a management context to provide insight into the stability and modes of SOC accrualIdentify management practices with the greatest potential to close the soil health gapThe specific objectives of this project are:Objective 1a: Establish soil health and mineral-associated organic carbon (MAOC) and particulate organic carbon (POC) benchmarks in native ColoradosoilsObjective 1b: Assess sensitivity of soil health and SOC to gradient of fallow frequency and crop diversity and quantify the soil health gap (SHG)Objective 2: Probing plant diversity and perenniality as a driver of balanced microbial community efficiency/activity and C accumulationObjective 3: Develop an assessment tool for land managers to compare soil health to natural ecosystems in Colorado
Project Methods
Methods for Objective 1: I will utilize the 7 research sites that are part of the CSHP as well as 5 previously sampled working farms in Colorado to compare management practices with a gradient of fallow duration and crop rotation diversity. Using data from these sites as well as the broader enrollment of 131 farms in the CSHP, I will assess the SHG by conservation district and, where previous SOC measurements are available, quantify change in SOC since the last sampling (2016 or 2018).Sampling Strategy for 1a and 1b: I will use a random, stratified sampling design for each natural and agricultural area based on mapped soil data (GSSURGO) for soil order and percent clay, vegetation indices (NDVI), and slope to identify regions most likely to have similar variability. Since I anticipate being able to sample up to 16 composited samples per site, I will follow procedures for a spatially balanced sampling design to be able to adjust sample locations if a selected point is inaccessible61. Where previous data are available on bulk density or SOC, I will perform a power analysis to estimate the number of samples needed to achieve a 90% probability of detecting differences in SOC given the estimated variability to ensure 16 samples is sufficient. For each soil sample, I will collect three cores to composite over two depths: 0-15 cm, 15-50 cm and process in a typical fashion with measurements needed for calculating C stocks via equivalent soil mass62.Field Data Collection for 1a and 1b: Vegetation and management: Research sites within the CSHP will have detailed management history included as part of that project; for additional farms sampled outside of that program, I will collect updated management data about crop rotations, amendments, and yield in the same format to ensure data comparability. For natural ecosystem benchmark sites, I will characterize vegetation use a step-point method by recording the nearest plant species to a point frame along randomized 50 m transects63 to estimate percent ground cover, relative abundance of plant species, species richness and evenness and the Shannon Index (α-diversity).Soil: Samples collected as part of the CSHP (0-10 cm) are already slated to be analyzed for water stable aggregation (WSA)64, microbial biomass65, and a panel of soil health metrics including C, N, pH, texture (% sand, silt, clay), SOC, potentially mineralizable C (POX-C) and N, cation exchange capacity, and micronutrients. The CDA has agreed to share these data in collaboration with this project (see provided Letter of Support). These same soil health measurements will be performed on the natural ecosystem and on-farm samples by Ward Laboratories which conducts the routine soil health analyses for participants of the CSHP.In order to assess the distribution of SOC into chemically protected and readily mineralizable pools, I will perform a size fractionation to quantify MAOC (<53 μm)/POC (>53 μm)38 and bulk soil C and N. For any soils indicated to have inorganic C (IC) by exposure to 1M HCl will have IC quantified by pressure-transducer66 and SOC calculated as the difference between total and IC measurements. I will additionally be trained in the use of Fourier-transform infrared spectroscopy to use MID-IR bands67,68 to estimate a suite of soil characteristics and develop regionally appropriate equations for estimating SOC, soil texture and mineral characteristics, and more. These equations, calibrated by region, could be used to expand the power of analyses by reducing effort needed to evaluate soil conditions.Data analysis: In order to compare managed and natural ecosystems, for each measured variable, I will quantify the "soil health gap" (SHG) using the following equation based on average and paired values for each farm and nearest/best-matched natural area:SHGx = (SH)n - (SH)m (Eqn 1)where x is the specific property compared, n is native soil and m is managed cropland soil. I will also perform a multivariate principal component analysis to assess which variables explain the greatest proportion of variability in SOC and the SHG. I will perform a mixed-effects linear-regression analysis using Akaike information criterion model selection to quantify the effects of management practices on yield, SOC, and change in SOC for farms with previous sampling history.Methods for Objective 2: Soils collected from Obj1 will be part of the experiment for Obj2. Additionally, I will partner with colleagues at The Land Institute (TLI) to obtain additional samples from Kernza fields, a perennial wheatgrass grown for grain, and Kernza-alfalfa fields which have been used in other studies2. The goal is to establish a gradient of both plant diversity across space and time to assess the functions of the microbial communities (Table 1).Table 1. Experimental treatments for Obj 2 diversity-perenniality gradient1) Treatment2) Native System3) P. grain-legume biculture4) P. Grain mono.5) Rot. w/ diverse CC mix6) 5+ yr rot mono.7) 2-3 yr rot. Mono.8) Grain-fallow mono.1) 2) 3) 4) 5) 6) 7) 8)Co-existing species 5+ 2 1 1 - 4 1 1 0 - 1Species over time 5+ 2 1 4+ 52 - 3 1Annual or Perennial* P P P A A A AAmt..Yr Soil Covered 1 11 0.8 0.5 0.5 0.25____________________________________________________________________________*A=Annual; CC= cover crop; mono=monoculture; P=perennial; Rot=Rotation; Yr=yearIn order to determine the extent that diversity vs. perenniality enhances the efficiency of the microbial community, I will estimate microbial CUE by 13C glutamic acid tracing method52. Glutamic acid is consumed directly by microbial cells facilitating direct comparison across treatments with minimal interference from enzyme production70. After incubation, I will determine 13CO2-C respiration and direct incorporation into tissues by fumigation-extraction65 and subsequent analysis on an isotope-ratio mass spectrometer.I will assess functional capacity of microbial communities to degrade soil C by quantifying hydrolytic enzymes α-glucosidase, acid phosphatase, β-1,4-glucosidase, β-xylosidase, cellobiohydrolase, and N-acetyl-β-Dglucosaminidase fluorometrically71,72 and the oxidase enzymes polyphenol oxidase and peroxidase (lignin, aromatic compound decomposition) spectrophotometrically. In order to infer the likely origin of MAOC, I will scan this fraction using FTIR in the midinfrared range (peaks 2,930 cm-1 for aliphatic groups from microbial cell components and plant waxes; peaks 1,530 and 1,620 cm-1 from lignin-derived inputs73,74.Effortsinclude research publications of scientific findings, webinar used to provide instructions and solicitfeedback on the soil health gap web-tool, presentation and seminar synthesis to disseminate knowledge to other researchers and bring together research partners studying soil health, and a seminar class with graduate students interested in designing projects relevant to and in collaboration with growers and land managers.Evaluation Plan: Progress on the proposed work will be evaluated through monthly assessments with my mentors. We will assess progress based on the timeline outlined in the application. I will remain current with data processing and analyses by presenting project updates at least quarterly in the weekly lab meeting or with the CSHP. The proposed work has the potential for two published papers and conference presentations in addition to the in-person educational event, webinar, and web-tool. This webtool has the potential to be hosted on professional and trusted sources of either the CSHP, SCSC at CSU, or both. Research results will be archived with the CSHP through the CDA as well as any additional research sites in accordance with letters of cooperation. Additionally, I will record research deliverables on my public professional profiles.