Optimizing Sampling Strategies for Near-Surface Soil Carbon Inventory: One Size Doesn’t Fit All

Abstract

Soils comprise the largest pool of terrestrial carbon yet have lost significant stocks due to human activity. Changes to land management in cropland and grazing systems present opportunities to sequester carbon in soils at large scales. Uncertainty in the magnitude of this potential impact is largely driven by the difficulties and costs associated with measuring near-surface (0–30 cm) soil carbon concentrations; a key component of soil carbon stock assessments. Many techniques exist to optimize sampling, yet few studies have compared these techniques at varying sample intensities. In this study, we performed ex-ante, high-intensity sampling for soil carbon concentrations at four farms in the eastern United States. We used post hoc Monte-Carlo bootstrapping to investigate the most efficient sampling approaches for soil carbon inventory: K-means stratification, Conditioned Latin Hypercube Sampling (cLHS), simple random, and regular grid. No two study sites displayed similar patterns across all sampling techniques, although cLHS and grid emerged as the most efficient sampling schemes across all sites and strata sizes. The number of strata chosen when using K-means stratification can have a significant impact on sample efficiency, and we caution future inventories from using small strata n, while avoiding even allocation of sample between strata. Our findings reinforce the need for adaptive sampling methodologies where initial site inventory can inform primary, robust inventory with site-specific sampling techniques.

Rapid soil harvesting using a novel soil auger system for farm‐scale soil carbon estimates

“…The budget of a project or the hours available for soil sampling are two major limiting factors in soil carbon projects attempting to quantify soil carbon stocks at the landscape scale (Bettigole et al, 2023;Stanley et al, 2023). The tradeoffs in speed and accuracy of different methods of soil harvesting affect the amount of time spent in the field and the number of samples that can be collected within a given number of personnel hours.…”

“…heterogeneity of soil carbon is greater than bulk density, one approach to efficiently measure stocks is to take soil carbon samples at greater spatial resolution (i.e., more dense sampling) than bulk density samples (Bettigole et al, 2023;Don et al, 2007). Considerations such as sampling density and frequency, sample compositing, and sampling depth are often factored into measuring soil C concentrations in order to minimize time and cost while maintaining the required level of accuracy for the project (Bettigole et al, 2023;Goodwin et al, 2022;Smith et al, 2020;Stanley et al, 2023). One component of sampling that is often not considered is the method of harvesting soils, despite the potential time-cost associated with high sampling densities required for soil C sampling.…”