Predicting spatial patterns of soil composition at high-latitudes

The Science

Rising temperatures and increasing human activity are affecting how carbon and nitrogen cycle through high-latitude ecosystems. The ratio of carbon-to-nitrogen (C:N) in soil is a key indicator of how these sensitive ecosystems might respond to changing conditions. But C:N ratios can vary greatly among different soil layers. This makes depth predictions challenging because ratios do not add up when crossing the variable and mixed soil layers found in cold-region soils. This study compared two methods for spatially predicting the C:N ratios of permafrost-affected soils at different depths. It also produced new insights for improving spatial and vertical predictions of soil C:N ratios in permafrost landscapes.

The Impact

This study is the first attempt to spatially predict and map soil C:N ratios in the permafrost region. When environmental conditions change, soil C:N ratios can be an indicator of potential impacts on soil stability, local water systems, and plant growth. By learning how C:N ratios vary across the landscape, scientists can better predict how permafrost soils will respond to physical disturbances and rising temperatures. Spatially explicit maps of soil C:N ratios at different depths provide important insights to help guide land-use choices and decisions about developing and maintaining energy and water infrastructure.

Summary

High-latitude regions are undergoing shifts in temperature and hydrology that can affect the cycling rates of carbon and nitrogen stored in permafrost-affected soils. Changes to these cycles can alter plant communities, gas exchanges with the atmosphere, and soil stability – all of which can have impacts on energy and water infrastructure. Soil C:N ratios can be an indicator of soil responses and a valuable input for modeling ecosystem processes. To explore the challenges of predicting the spatial variability of C:N ratios at multiple depths for permafrost-affected soils, researchers compared two approaches: indirect mapping, which calculates C:N ratios from separately predicted maps of carbon and nitrogen stocks, and direct mapping, which predicts C:N ratios directly. Indirect mapping was more effective for surface soils, while direct mapping performed slightly better at greater depths. Temperature and topography emerged as the most dominant geospatial predictors. The accuracy of both methods was affected by limited soil observations and the irregular patterns of carbon and nitrogen storage in permafrost soils. With more extensive soil datasets, however, indirect mapping might better capture the full range of observed C:N ratios. This pioneering effort identified avenues for overcoming prediction challenges. It also helps set the stage for further advancements in understanding high latitude landscapes and managing their built infrastructure.