Gregory J. Fiske

The biogeochemistry of carbon across a gradient of streams and rivers within the Congo Basin

Dissolved organic carbon (DOC) and inorganic carbon (DIC and pCO2), lignin biomarkers and the optical properties of dissolved organic matter (DOM) were measured in a gradient of streams and rivers within the Congo Basin (Republic of Congo), with the aim of examining how vegetation cover and hydrology influences the composition and concentration of exported fluvial carbon (C). Three sampling campaigns (February 2010, November 2010 and August 2011) spanning 56 sites are compared by sub-basin watershed land cover type (savannah, tropical forest, and swamp) and hydrologic regime (high, intermediate, and low). Land cover properties predominately controlled the amount and quality of DOC, chromophoric DOM (CDOM) and lignin phenol concentrations (∑8) exported in streams and rivers throughout the Congo Basin. Higher DIC concentrations and changing DOM composition (lower molecular weight, less aromatic C) during periods of low hydrologic flow indicated a shift from rapid overland supply pathways in wet conditions to deeper groundwater inputs during drier periods. Lower DOC concentrations in forest and swamp sub-basins were apparent with increasing catchment area, indicating enhanced DOC loss with extended water residence time. Surface water pCO2 in savannah and tropical forest catchments ranged between 2600 and 11922 µatm, and swamp regions contained extremely high pCO2 (10598-15802 µatm), highlighting their potential as significant pathways for water-air efflux. Our data suggest that the quantity and quality of DOM exported to streams and rivers is largely driven by terrestrial ecosystem structure and that anthropogenic land-use or climate change may impact the composition and reactivity of fluvial C, with ramifications for regional C budgets and future climate scenarios.

Soil carbon debt of 12,000 years of human land use

Significance Land use and land cover change has resulted in substantial losses of carbon from soils globally, but credible estimates of how much soil carbon has been lost have been difficult to generate. Using a data-driven statistical model and the History Database of the Global Environment v3.2 historic land-use dataset, we estimated that agricultural land uses have resulted in the loss of 133 Pg C from the soil. Importantly, our maps indicate hotspots of soil carbon loss, often associated with major cropping regions and degraded grazing lands, suggesting that there are identifiable regions that should be targets for soil carbon restoration efforts. Human appropriation of land for agriculture has greatly altered the terrestrial carbon balance, creating a large but uncertain carbon debt in soils. Estimating the size and spatial distribution of soil organic carbon (SOC) loss due to land use and land cover change has been difficult but is a critical step in understanding whether SOC sequestration can be an effective climate mitigation strategy. In this study, a machine learning-based model was fitted using a global compilation of SOC data and the History Database of the Global Environment (HYDE) land use data in combination with climatic, landform and lithology covariates. Model results compared favorably with a global compilation of paired plot studies. Projection of this model onto a world without agriculture indicated a global carbon debt due to agriculture of 133 Pg C for the top 2 m of soil, with the rate of loss increasing dramatically in the past 200 years. The HYDE classes “grazing” and “cropland” contributed nearly equally to the loss of SOC. There were higher percent SOC losses on cropland but since more than twice as much land is grazed, slightly higher total losses were found from grazing land. Important spatial patterns of SOC loss were found: Hotspots of SOC loss coincided with some major cropping regions as well as semiarid grazing regions, while other major agricultural zones showed small losses and even net gains in SOC. This analysis has demonstrated that there are identifiable regions which can be targeted for SOC restoration efforts.

On the Relationship Between Stream Biotic Diversity and Exurbanization in the Northeastern USA

Stream macroinvertebrate diversity is a commonly used indicator of aquatic health, reflecting overall ecological integrity within a watershed. Our study made use of two metrics of stream biota, the Hilsenhoff Biotic Index (HBI) and the diversity of Ephemeroptera, Plecoptera, and Tricoptera (nEPT) species, to develop statistical models relating land cover information within watersheds to these stream biotic health indicators. The study area in southern New England included over 100 small streams, which make up a substantial portion of the region’s largest catchments. General additive models (GAM) and step-wise multiple linear regression (MLR) models were used to explore the relationship between the land cover and the biotic indicators. Although the GAMs explained a greater amount of the variation in the stream biota metrics, the MLR models were also consistently reliable predictors of nEPT and HBI. This research indicates land cover can be used as a robust predictor of stream biological indicators of small catchments (HUC12) in the region, and help to target streams for restoration or protection.