Geology Reports⌕ Search

Geology topics

E.S. Kane

Publications and source records attributed to E.S. Kane.

6 recordsLinked to original sources
USGS2026

Quantifying methane emissions from a rich fen with uncrewed aircraft systems in boreal Alaska

Thawing of permafrost in northern latitudes is accelerating, potentially releasing substantial amounts of methane (CH 4 ) as forested permafrost plateaus transition into wetlands. This ecosystem shift alters the carbon exchange between the soil and atmosphere, influencing the permafrost-carbon feedback. Monitoring these changes may require measurement platforms operating across varied spatial and temporal scales. Recent advancements in small uncrewed aircraft systems (sUAS) enable high resolution CH 4 flux quantification in remote, complex terrains; however, comparisons with established methods such as eddy covariance flux towers remain limited. We used a hexacopter sUAS to quantify CH 4 emissions from the Alaska Peatland Experiment, a wetland within the Bonanza Creek Experimental Forest. Using an ensemble of methods to define the background CH 4 concentration, along with near surface emissions from soil chambers, helped constrain our flux estimates. The sUAS method yielded an average flux of 0.0077 ± 0.0019 mol s −1 CH 4 , within a factor of two concurrent tower-derived total source flux estimates (0.0036 ± 0.00042 mol s −1 CH 4 ). To assess spatial drivers of observed fluxes, we conducted a 2D footprint analysis and overlaid the results with high-resolution hyperspectral land cover classification, quantifying vegetative contributions within each footprint. This revealed higher fen representation in sUAS measurements (73.8%) than in tower footprints (58.8%), and lower tussock meadow representation (15.6% and 30.3%, respectively). These differences were consistent with known variation in vegetation-specific CH 4 emissions. Our results highlight that combining footprint modeling with land cover characterization can enhance interpretations of CH 4 fluxes and guide cross-platform comparisons.

JGR Atmospheres↗
USGS2013

Response of anaerobic carbon cycling to water table manipulation in an Alaskan rich fen

To test the effects of altered hydrology on organic soil decomposition, we investigated CO 2 and CH 4 production potential of rich-fen peat (mean surface pH = 6.3) collected from a field water table manipulation experiment including control, raised and lowered water table treatments. Mean anaerobic CO 2 production potential at 10 cm depth (14.1 ± 0.9 μmol C g −1 d −1 ) was as high as aerobic CO 2 production potential (10.6 ± 1.5 μmol C g −1 d −1 ), while CH4 production was low (mean of 7.8 ± 1.5 nmol C g −1 d −1 ). Denitrification enzyme activity indicated a very high denitrification potential (197 ± 23 μg N g −1 d −1 ), but net NO - 3 reduction suggested this was a relatively minor pathway for anaerobic CO 2 production. Abundances of denitrifier genes ( nirK and nosZ ) did not change across water table treatments. SO 2- 4 reduction also did not appear to be an important pathway for anaerobic CO 2 production. The net accumulation of acetate and formate as decomposition end products in the raised water table treatment suggested that fermentation was a significant pathway for carbon mineralization, even in the presence of NO - 3 . Dissolved organic carbon (DOC) concentrations were the strongest predictors of potential anaerobic and aerobic CO 2 production. Across all water table treatments, the CO 2 :CH 4 ratio increased with initial DOC leachate concentrations. While the field water table treatment did not have a significant effect on mean CO 2 or CH 4 production potential, the CO 2 :CH 4 ratio was highest in shallow peat incubations from the drained treatment. These data suggest that with continued drying or with a more variable water table, anaerobic CO 2 production may be favored over CH 4 production in this rich fen. Future research examining the potential for dissolved organic substances to facilitate anaerobic respiration, or alternative redox processes that limit the effectiveness of organic acids as substrates in anaerobic metabolism, would help explain additional uncertainty concerning carbon mineralization in this system.

Soil Biology and Biochemistry↗
USGS2011

Soil carbon distribution in Alaska in relation to soil-forming factors

The direction and magnitude of soil organic carbon (SOC) changes in response to climate change remain unclear and depend on the spatial distribution of SOC across landscapes. Uncertainties regarding the fate of SOC are greater in high-latitude systems where data are sparse and the soils are affected by sub-zero temperatures. To address these issues in Alaska, a first-order assessment of data gaps and spatial distributions of SOC was conducted from a recently compiled soil carbon database. Temperature and landform type were the dominant controls on SOC distribution for selected ecoregions. Mean SOC pools (to a depth of 1-m) varied by three, seven and ten-fold across ecoregion, landform, and ecosystem types, respectively. Climate interactions with landform type and SOC were greatest in the uplands. For upland SOC there was a six-fold non-linear increase in SOC with latitude (i.e., temperature) where SOC was lowest in the Intermontane Boreal compared to the Arctic Tundra and Coastal Rainforest. Additionally, in upland systems mineral SOC pools decreased as climate became more continental, suggesting that the lower productivity, higher decomposition rates and fire activity, common in continental climates, interacted to reduce mineral SOC. For lowland systems, in contrast, these interactions and their impacts on SOC were muted or absent making SOC in these environments more comparable across latitudes. Thus, the magnitudes of SOC change across temperature gradients were non-uniform and depended on landform type. Additional factors that appeared to be related to SOC distribution within ecoregions included stand age, aspect, and permafrost presence or absence in black spruce stands. Overall, these results indicate the influence of major interactions between temperature-controlled decomposition and topography on SOC in high-latitude systems. However, there remains a need for more SOC data from wetlands and boreal-region permafrost soils, especially at depths > 1 m in order to fully understand the effects of climate on soil carbon in Alaska.

Geoderma↗
USGS2010

Recent acceleration of biomass burning and carbon losses in Alaskan forests and peatlands

Climate change has increased the area affected by forest fires each year in boreal North America. Increases in burned area and fire frequency are expected to stimulate boreal carbon losses. However, the impact of wildfires on carbon emissions is also affected by the severity of burning. How climate change influences the severity of biomass burning has proved difficult to assess. Here, we examined the depth of ground-layer combustion in 178 sites dominated by black spruce in Alaska, using data collected from 31 fire events between 1983 and 2005. We show that the depth of burning increased as the fire season progressed when the annual area burned was small. However, deep burning occurred throughout the fire season when the annual area burned was large. Depth of burning increased late in the fire season in upland forests, but not in peatland and permafrost sites. Simulations of wildfire-induced carbon losses from Alaskan black spruce stands over the past 60 years suggest that ground-layer combustion has accelerated regional carbon losses over the past decade, owing to increases in burn area and late-season burning. As a result, soils in these black spruce stands have become a net source of carbon to the atmosphere, with carbon emissions far exceeding decadal uptake.

Nature Geoscience↗
USGS2010

Modeling fire severity in black spruce stands in the Alaskan boreal forest using spectral and non-spectral geospatial data

Biomass burning in the Alaskan interior is already a major disturbance and source of carbon emissions, and is likely to increase in response to the warming and drying predicted for the future climate. In addition to quantifying changes to the spatial and temporal patterns of burned areas, observing variations in severity is the key to studying the impact of changes to the fire regime on carbon cycling, energy budgets, and post-fire succession. Remote sensing indices of fire severity have not consistently been well-correlated with in situ observations of important severity characteristics in Alaskan black spruce stands, including depth of burning of the surface organic layer. The incorporation of ancillary data such as in situ observations and GIS layers with spectral data from Landsat TM/ETM+ greatly improved efforts to map the reduction of the organic layer in burned black spruce stands. Using a regression tree approach, the R2 of the organic layer depth reduction models was 0.60 and 0.55 (pb0.01) for relative and absolute depth reduction, respectively. All of the independent variables used by the regression tree to estimate burn depth can be obtained independently of field observations. Implementation of a gradient boosting algorithm improved the R2 to 0.80 and 0.79 (pb0.01) for absolute and relative organic layer depth reduction, respectively. Independent variables used in the regression tree model of burn depth included topographic position, remote sensing indices related to soil and vegetation characteristics, timing of the fire event, and meteorological data. Post-fire organic layer depth characteristics are determined for a large (N200,000 ha) fire to identify areas that are potentially vulnerable to a shift in post-fire succession. This application showed that 12% of this fire event experienced fire severe enough to support a change in post-fire succession. We conclude that non-parametric models and ancillary data are useful in the modeling of the surface organic layer fire depth. Because quantitative differences in post-fire surface characteristics do not directly influence spectral properties, these modeling techniques provide better information than the use of remote sensing data alone.

Remote Sensing of Environment↗