  The world needs around 150 Pg of negative carbon emissions to mitigate
climate change. Global soils may provide a stable, sizeable reservoir to help
achieve this goal by sequestering atmospheric carbon dioxide as soil organic
carbon (SOC). In turn, SOC can support healthy soils and provide a multitude of
ecosystem benefits. To support SOC sequestration, researchers and policy makers
must be able to precisely measure the amount of SOC in a given plot of land.
SOC measurement is typically accomplished by taking soil cores selected at
random from the plot under study, mixing (compositing) some of them together,
and analyzing (assaying) the composited samples in a laboratory. Compositing
reduces assay costs, which can be substantial. Taking samples is also costly.
Given uncertainties and costs in both sampling and assay along with a desired
estimation precision, there is an optimal composite size that will minimize the
budget required to achieve that precision. Conversely, given a fixed budget,
there is a composite size that minimizes uncertainty. In this paper, we
describe and formalize sampling and assay for SOC and derive the optima for
three commonly used assay methods: dry combustion in an elemental analyzer,
loss-on-ignition, and mid-infrared spectroscopy. We demonstrate the utility of
this approach using data from a soil survey conducted in California. We give
recommendations for practice and provide software to implement our framework.
