Geology topics

L. Tieszen

Publications and source records attributed to L. Tieszen.

4 recordsLinked to original sources

USGS2011

Mapping and monitoring Louisiana's mangroves in the aftermath of the 2010 Gulf of Mexico Oil spill

Information regarding the present condition, historical status, and dynamics of mangrove forests is needed to study the impacts of the Gulf of Mexico oil spill and other stressors affecting mangrove ecosystems. Such information is unavailable for Louisiana at sufficient spatial and thematic detail. We prepared mangrove forest distribution maps of Louisiana (prior to the oil spill) at 1 m and 30 m spatial resolution using aerial photographs and Landsat satellite data, respectively. Image classification was performed using a decision-tree classification approach. We also prepared land-cover change pairs for 1983, 1984, and every 2 y from 1984 to 2010 depicting “ecosystem shifts” (e.g., expansion, retraction, and disappearance). This new spatiotemporal information could be used to assess short-term and long-term impacts of the oil spill on mangroves. Finally, we propose an operational methodology based on remote sensing (Landsat, Advanced Spaceborne Thermal Emission and Reflection Radiometer [ASTER], hyperspectral, light detection and ranging [LIDAR], aerial photographs, and field inventory data) to monitor the existing and emerging mangrove areas and their disturbance and regrowth patterns. Several parameters such as spatial distribution, ecosystem shifts, species composition, and tree height/biomass could be measured to assess the impact of the oil spill and mangrove recovery and restoration. Future research priorities will be to quantify the impacts and recovery of mangroves considering multiple stressors and perturbations, including oil spill, winter freeze, sea-level rise, land subsidence, and land-use/land-cover change for the entire Gulf Coast.

Journal of Coastal Research↗

USGS2008

Coherent changes in relative C4 plant productivity and climate during the late Quaternary in the North American Great Plains

Evolution of the mixed and shortgrass prairie of the North American Great Plains is poorly understood because of limited proxies available for environmental interpretations. Buried soils in the Great Plains provide a solution to the problem because they are widespread both spatially and temporally with their organic reservoirs serving as a link to the plants than once grew on them. Through stable carbon isotopic analysis of soil organic carbon (??13C), the percent carbon from C4 plants (%C4) can be ascertained. Because C4 plants are primarily warm season grasses responding positively to summer temperature, their representation has the added advantage of serving as a climate indicator. To better understand grassland and climate dynamics in the Great Plains during the last 12 ka (ka=1000 radiocarbon years) we developed an isotopic standardization technique by: determining the difference in buried soil ??13C and modern soil ??13C expected for that latitude (????13C), and transferring the ????13C to ??%C4 (% C4) using mass balance calculations. Our analysis reveals two isotopic stages in the mixed and shortgrass prairie of the Great Plains based on trends in ??%C4. In response to orbital forcing mechanisms, ??%C4 was persistently below modern in the Great Plains between 12 and 6.7 ka (isotopic stage II) evidently because of the cooling effect of the Laurentide ice sheet and proglacial lakes in northern latitudes, and glacial meltwater pulses cooling the Gulf of Mexico and North Atlantic Ocean. The ??%C4 after 6.7 ka (isotopic stage I) increased to modern levels as conditioned by the outflow of warm, moist air from the Gulf of Mexico and dry incursions from the west that produced periodic drought. At the millennial-scale, time series analysis demonstrates that ??%C4 oscillated with 0.6 and 1.8 ka periodicities, possibly governed by variations in solar irradiance. Our buried soil isotopic record correlates well with other environmental proxy from the Great Plains and surrounding regions. ?? 2008 Elsevier Ltd.

Quaternary Science Reviews↗

USGS2007

Late quaternary temperature record from buried soils of the North American Great Plains

We present the first comprehensive late Quaternary record of North American Great Plains temperature by assessing the behavior of the stable isotopic composition (δ 13 C) of buried soils. After examining the relationship between the δ 13 C of topsoil organic matter and July temperature from 61 native prairies within a latitudinal range of 46°–38°N, we applied the resulting regression equation to 64 published δ 13 C values from buried soils of the same region to construct a temperature curve for the past 12 k.y. Estimated temperatures from 12 to 10 ka (1 k.y. = 1000 14 C yr B.P.) fluctuated with a periodicity of ∼1 k.y. with two cool excursions between −4.5 and −3.5 °C and two warmer excursions between −1 and 0 °C, relative to modern. Early Holocene temperatures from ca. 10–7.5 ka were −1.0 to −2.0 °C before rising to +1.0 °C in the middle Holocene between 6.0 and 4.5 ka. After a cool interlude from 4.2 to 2.6 ka, when temperatures dropped to slightly below modern, another warm interval ensued from 2.6 to 1 ka as temperatures increased to ∼+0.5 °C. A final decline in temperature to below modern occurred beginning ca. 0.5 ka. Cooler than present temperatures in the Great Plains indicate telecommunications with cool-water episodes in the Gulf of Mexico and North Atlantic potentially governed by a combination of glacial meltwater pulses and low solar irradiance.

Geology↗

USGS2007

Optimization of an ecosystem model through the assimilation of eddy flux observations using a smoothed ensemble Kalman filter

The parameters of ecosystem models are conventionally optimized through nonsequential inversion methods, which treat observations as a whole and lack the flexibility to investigate possible temporal evolution of the model parameters. This research developed a smoothed ensemble Kalman filter (SEnKF) to assess to what extent the parameters and state variables of an ecosystem model can be simultaneously optimized through the assimilation of eddy flux observations. The performance of the SEnKF was demonstrated in one case study: the assimilation of measurements of carbon exchange between a mixed forest and the atmosphere at Niwot Ridge Forest (Colorado, USA) from 2000 to 2004 into a carbon flux partition model. Our analyses demonstrated that some model parameters, such as light use efficiency and respiration coefficients, were highly constrained by eddy flux data at daily to seasonal time scales. Light use efficiency was strongly seasonal. Model predictions based on parameters modified by the SEnKF were much improved, compared to predictions made without progressive data assimilation. The SEnKF reduced the variance of state variables that is caused by uncertainties of parameters and driving variables. The analysis of net ecosystem exchange of carbon between the forest and the atmosphere was improved.

Conference Paper↗