Thesis (M.S.)--Oregon State University, 1995. / Typescript (photocopy). Includes bibliographical references (leaves 59-64). Also available on the World Wide Web.

Thesis (M.S.)--Montana State University--Bozeman, 2005. / Typescript. Chairperson, Graduate Committee: John Antle. Includes bibliographical references (leaves 115-124).

Microbial decomposition of soil organic matter (SOM) releases around 98 Pg of C (as CO2) to the atmosphere annually. Quantifying CO2 emissions from SOM is necessary to monitor and manage them but is complicated by proximate respiration of CO2 from plant roots, and by the influence of roots on SOM decomposition rate. Differences in the natural abundance of 13C in root and SOM-derived respiration (of < 10 ‰ in most temperate ecosystems) can be used to apportion their contributions to soil-surface CO2 efflux. However, this is challenging because all three δ13CO2 measurements are susceptible to significant sampling errors, which this study set out to identify and resolve, as follows. Respired CO2 sampled from excised roots is 13C-depleted by 1.8 ‰ (± 0.47) compared to intact roots due to the contribution of CO2 from root wounds. Root-respired δ13CO2 is more reliably measured using chambers around live, intact roots. These chambers also permit detection of diurnal changes in root-respired δ13CO2. Soil disturbance during sampling and root removal changes the carbon substrates available to microbes and this is reflected in a rapid (1-2 hours) decrease in δ13C of respiration of c. 4 ‰. This change can be regressed to estimate the δ13CO2 of microbial respiration from undisturbed soil. Techniques for measuring soil-surface efflux δ13CO2 induce method-specific biases of as much as 5 ‰, as measured in intact mesocosm soil and when simulated using a numerical diffusion model. Discrepancies between measurements and model predictions may be due to complexities of gas transport not currently accommodated in diffusion models, namely, near-surface advection and non-uniform soil diffusivity. Using improved techniques, this study used natural abundance 13C partitioning to assess priming effects, identify distinct environmental drivers of root-respired and SOM-derived CO2 fluxes, and detect differences in soil carbon cycling between tree species, possibly attributable to mycorrhizal type.

Rises in anthropogenic CO2 emissions are now widely acknowledged to be responsible for changes in the global climate, with potentially disastrous consequences if these rises continue unchecked. Although knowledge of ecosystem responses to climate change has improved, there are still large underlying uncertainties regarding their response to warming. Of all the ecosystems with the potential to mitigate rises in CO2, forests are arguably the most important because of their huge land area and store of carbon. A large proportion of the carbon stored in forests is found in the soil, and it is the response of this soil carbon to temperature that is the main determinant of a forest’s ability to act as a carbon sink, or indeed source. Understanding the response of soil carbon flux to temperature, as well as the contribution of soil carbon flux to the carbon balance of forests as a whole is crucial in helping to improve modelling approaches. In this thesis I first examined the temperature response of old and new soil organic carbon from a Sitka spruce plantation under controlled laboratory conditions. Both the old and new soil organic carbon showed similar temperature sensitivities after prolonged incubation at 20 °C, thus implying a similar response to increasing temperatures. Using a variety of different methods (root intensity, meshing and stable isotope analysis) I then studied the responses under field conditions. These methods showed that autotrophic respiration was responsible for up to 50 % of total soil respiration, and was more sensitive to temperature than heterotrophic respiration. Finally, I compared the contributions and determinants (particularly temperature and moisture) of soil respiration fluxes to ecosystem fluxes at a temperate (Sitka spruce) and Mediterranean (Maritime pine) forest. Temperature was found to be the dominant driver of soil respiration fluxes at the temperature forest, whilst soil respiration was limited by moisture at the Mediterranean forest. Statistically significant relationships between net ecosystem productivity and soil respiration (and the stable isotope signature of soil respiration) were found at both forests, indicating a close coupling between above-ground processes and soil respiration.

The soil organic carbon (C) pool is estimated to contain at least three times as much organic C as is stored in vegetation. However, the processes controlling below-ground C dynamics are poorly understood, representing a key uncertainty in ecosystem models. Soil respiration rate (Rs) is a large component of the forest carbon cycle, however the factors that control it are still poorly understood, and those affecting autotrophic (Ra) and heterotrophic (Rh) respiration rates differ and vary in space and time. A variety of direct (i.e. soil and ingrowth cores) and indirect (i.e. rhizotron and minirhizotron) methods exist for obtaining estimates of fine root (< 2 mm diameter) production, with the consequence that there is a high variability in root biomass estimates between root studies. In this thesis I aim to contribute towards a better understanding of processes governing below-ground C dynamics. In particular I focus on: 1) the spatial and seasonal variability of Rs and drivers; 2) the uncertainty on fine root C pool measurement methods; 3) comparing novel datasets of Rs, fine root biomass and girth increment, with outputs from the SPA v2 model. To determine the dominant controls and spatial heterogeneity of Rs, I measured Rs and key biotic and abiotic drivers seasonally, in a Quercus robur forest in southern England. Measurements were made quarterly in three plots, each with measurement points arranged according to a spatial sampling design, enabling any spatial autocorrelation to be detected. Rs drivers were categorised into plant (i.e. leaf area index, weighted tree proximity (i.e. mean dbh within 4 m of a point), and fine root biomass), physical (i.e. soil moisture, soil temperature and soil bulk density) and substrate (i.e. litter depth and organic layer depth) factors. I explore: 1) what the dominant controls of Rs are and whether they change during the growing season; 2) whether micro-topography and stand structure are correlated with drivers, and influence the spatial variability of Rs, thereby simplifying up-scaling processes; 3) if physical drivers of Rs are spatially more homogeneous than plant drivers and the availability of substrate. I found no clear seasonal difference in drivers, with Rs consistently responding to litter depth, bulk density and soil moisture. The only significant response of Rs to micro-topography and tree factor was in August and September respectively and physical factors were found to be the most spatially homogeneous. Rs measurements were non-normally distributed, with ‘hotspots’ of particularly high fluxes found that remained stable throughout the measurement campaign. These findings suggest that the seasonal and spatial variability and distribution of Rs and its main drivers should be considered at the sampling design stage, to avoid bias for up-scaling non-linear processes. To address the uncertainties associated with determining fine root biomass change, we compared the measurement error for five methodologies (four indirect and one direct) in a Pinus contorta and Quercus robur forest during 2010. Rhizotron and ingrowth measurements were taken during 2010 and fine root standing crop was measured in 2009. Root length against the rhizotron screens was measured using novel software (ORIDIS), developed as part of a collaboration here in Edinburgh. The software was developed to increase precision and reduce the cost and processing time of rhizotron measurements. Differences in final cumulative root ingrowth for each conversion method ranged between 20.7g-2 - 245.0 g m-2 in the oak forest and 89.7 g m-2 - 273.0 g m-2 in the pine forest. The study found that indirect measurements of root length had less operator error than indirect measurements of root diameter. Direct methods of determining root growth using ingrowth cores also showed a seasonal trend; however artefacts may have been introduced into the method, from the affect of severing roots and changing soil conditions. To test the representation of below-ground processes in an ecosystem model, I validate modelled dynamics using default SPA v2 parameters, against independent CO2 flux and C pool datasets. The flux data were of eddy covariance and automatic chamber measurements, partitioned into root (Rroot), mycorhizal (Rmyc) and microbial heterotrophic (Rh) components. The biometric measurements were of foliage, fine root biomass and woody biomass increment. The key findings of this study were that: 1) SPA outputs compare well to ecosystem scale measurements of NEE and GPP. However, model-data mismatch occurs for fine root and wood C allocation; 2) the timing of fine root C allocation is 53 days too late and the turnover rate of fine roots 17 times too high; 3) the timing of modelled below-ground Rh and Ra could be improved by separating above and below-ground Ra and including individual root, mychorrizae and microbial C pools. The thesis concludes by discussing the implications of each chapter for our understanding and capability to model below-ground C dynamics. I find that the key challenge for measuring individual below-ground C pools and fluxes is ensuring that the measurements are spatially representative and avoid bias. The key challenge for modelling below-ground C dynamics is ensuring processes sufficiently reflect reality, when the sparse data that exist for corroboration, capture multiple processes. I explore the possibilities of further research that could be conducted, as a result of this work.

Thesis (M.S. in environmental engineering)--Washington State University, May 2009. / Title from PDF title page (viewed on June 19, 2009). "Department of Civil and Environmental Engineering." Includes bibliographical references (p. 58-61).

Thesis (M.S.)--Montana State University--Bozeman, 2006. / Typescript. Chairperson, Graduate Committee: Richard E. Engel. Includes bibliographical references (leaves 73-84).

Planting trees on agricultural land either as farm woodlands or agroforestry (trees integrated with farming) is one option for reducing the level of atmospheric carbon dioxide. Trees store carbon as biomass, and may increase carbon storage in the ground. A review of the literature outlined uncertainty relating to changes in carbon storage after planting trees on agricultural land. The aim of this thesis is to deter¬mine the impact of tree planting on arable and pasture land in terms of above and belowground carbon storage and thereby address these uncertainties, and assess the implications for the Woodland Carbon Code: a voluntary standard for carbon storage in UK woodlands. Measurements of soil organic carbon to a depth of 1.5 m were taken at two field sites in Bedfordshire in the UK: a 19 year old silvoarable trial, and a 14 year old silvopasture and farm woodland. On average 60% and 40% of the soil carbon (rel¬ative to 1.5 m) was found beneath 0.2 and 0.4 m in depth respectively. Whilst tree planting in the arable system showed gains in soil organic carbon (12.4 t C ha−1 at 0–40 cm), tree planting in the pasture was associated with losses of soil organic carbon (6.1–13.4 t C ha−1 at 0–10 cm). Evidence from a nearby mature grazed woodland indicate that these losses may be recovered. No differences associated with tree planting were found to the full 1.5 m, though this may be due to a lack of statistical power. Measurements of above and belowground biomass, and the root distribution of 19 year old poplar (Populus spp.) trees (at the silvoarable trial) and ash (Fraxinus excelsior) trees ranging from 7 to 21 years (at several field sites across Bedfordshire) were made, involving the destructive harvest of 48 trees. These measurements suggest that Forestry Commission yield tables overestimate yield for poplar trees grown in a silvoarable system. An allometric relationship for determining ash tree biomass from diameter measurements was established. The biophysical model Yield-SAFE was updated to take into account root growth, and was parameterised using field measurements. It was successfully used to describe existing tree growth at two sites, and was then used to predict future biomass carbon storage at the silvoarable trial. Measurements indicate that losses in soil carbon at relatively shallow depths can offset a large proportion of the carbon stored in tree biomass, but assessing changes on a site by site basis may be prohibitively expensive for schemes such as the Woodland Carbon Code.

Diss. (sammanfattning) Uppsala : Sveriges lantbruksuniversitet, 2004. / Härtill 4 uppsatser.

Diss. (sammanfattning) Uppsala : Sveriges lantbruksuniv., 2007. / Härtill 4 uppsatser.