22 research outputs found

    Predicting the Spatial Variation of the Soil Organic Carbon Pool at a Regional Scale

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    Estimates of soil organic C (SOC) storage and their variability at various spatial scales are essential to better understand the global C cycle, estimate C sink capacity, identify effective C sequestration strategies, and quantify the amount of SOC sequestered during a specific period of time. This study used a geographically weighted regression (GWR) approach to predict the SOC pool at a regional scale. The GWR considers varying relationships between the SOC pool and environmental variables across the study area. The range of the variogram of SOC observations was used to define a search radius in the GWR. Terrain attributes, climate data, land use data, bedrock geology, and normalized difference vegetation index data were used to predict the SOC pool for seven states in the midwestern United States. The prediction accuracy of this SOC pool map was compared with the multiple linear regression (MLR) and regression kriging (RK) approaches. Higher contrast and wider variability (1.73-39.3 kg m(-2)) of the SOC pool were predicted with lower global prediction errors (mean estimation error = -0.11 kg m(-2), RMSE = 6.40 kg m(-2)) in GWR compared with the other approaches. A relative improvement of 22% over MLR and 2% over RK was observed in SOC prediction. The total SOC pool to the 0.5-m depth was estimated to be 6.22 Pg. The results suggest that the GWR approach is a promising tool for regional-scale SOC prediction

    Soil Carbon Isotope Values and Paleoprecipitation Reconstruction

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    Anthropogenic climate change has significant impacts at the ecosystem scale including widespread drought, flooding, and other natural disasters related to precipitation extremes. To contextualize modern climate change, scientists often look to ancient climate changes, such as shifts in ancient precipitation ranges. Previous studies have used fossil leaf organic geochemistry and paleosol inorganic chemistry as paleoprecipitation proxies, but have largely ignored the organic soil layer, which acts as a bridge between aboveground biomass and belowground inorganic carbon accumulation, as a potential recorder of precipitation. We investigate the relationship between stable carbon isotope values in soil organic matter (δ13CSOM) and a variety of seasonal and annual climate parameters in modern ecosystems and find a statistically significant relationship between δ13CSOM values and mean annual precipitation (MAP). After testing the relationship between actual and reconstructed precipitation values in modern systems, we test this potential paleoprecipitation proxy in the geologic record by comparing precipitation values reconstructed using δ13CSOM to other reconstructed paleoprecipitation estimates from the same paleosols. This study provides a promising new proxy that can be applied to ecosystems post‐Devonian (∼420 Ma) to the Miocene (∼23 Ma), and in mixed C3/C4 ecosystems in the geologic record with additional paleobotanical and palynological information. It also extends paleoprecipitation reconstruction to more weakly developed paleosol types, such as those lacking B‐ horizons, than previous inorganic proxies and is calibrated for wetter environments.Plain Language SummaryRainfall is very important to plant health and function. When plant material is deposited onto the ground, it becomes soil. This soil retains records of plant chemistry. We tested whether this plant chemistry recorded amount of rainfall over a wide range of environments, and found that soil chemistry does record rainfall. When tested in fossil soils, the soil chemistry as it remained of prior plant deposition could be used to calculate ancient rainfall, millions of years ago.Key PointsSoil carbon isotope values can be used to reconstruct precipitationReconstructed paleoprecipitation using carbon isotope values of organic matter are comparable to reconstructions with other proxiesThese soil isotope geochemistry findings validate prior work linking aboveground plant biomass isotope ecology and precipitationPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/167532/1/palo21004.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/167532/2/palo21004_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/167532/3/2020PA004158-sup-0001-Supporting_Information_SI-S01.pd
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