http://hdl.handle.net/1842/1637 2013-06-19T04:35:05Z http://hdl.handle.net/1842/6574 Title: Understanding the effects of drought upon carbon allocation and cycling in an Amazonian rain forest Authors: Metcalfe, Daniel Benjamin Abstract: The Amazon rain forest plays an important role in regional and global biogeochemical cycling, but the region may undergo an increase in the frequency and severity of drought conditions driven by global climate change, regional deforestation and fire. The effects of this drought on carbon cycling in the Amazon, particularly below-ground, are potentially large but remain poorly understood. This thesis examines the impacts of seasonal and longer-term drought upon ecosystem carbon allocation and cycling at an Amazon rain forest site with a particular focus upon below-ground processes. Measurements are made at three one-hectare forest plots with contrasting soil type and vegetation structure, to observe responses across a range of Amazon primary forest types. A fourth plot is subjected to partial rainfall exclusion to permit measurement of forest responses to a wider range of soil moisture levels than currently exists naturally. An analysis of the number of samples required to accurately quantify important ecosystem carbon stocks and fluxes is used to guide the sampling strategy at the field site. Quantifying root dynamics, in particular, presents methodological challenges. Thus, I critically review existing methods, and develop techniques to accurately measure root standing biomass and production. Subsequently, these techniques are used to record root responses, in terms of standing biomass, production, morphology, turnover and nutrient content, to variation in soil moisture across the four rain forest plots. There is substantial environmental variation in root characteristics. However, several responses remain consistent across plots: root production of biomass, length, and surface area, is lower where soil is dry, while root length and surface area per unit mass show the opposite pattern. The other major component of the below-ground carbon cycle is soil carbon dioxide efflux. I partition this efflux, on each plot, into contributions from organic ground surface litter, roots and soil organic matter, and investigate abiotic and biotic causes for observed differences within and between plots. On average, the percentage contribution of soil organic matter respiration to total soil carbon dioxide efflux declines during the dry season, while root respiration contribution displays the opposite trend. However, spatial patterns in soil respiration are not directly attributable to variation in either soil moisture or temperature. Instead, ground surface organic litter mass and root mass account for 44 % of observed spatial heterogeneity in soil carbon dioxide efflux. Finally, information on below-ground carbon cycling is combined with aboveround data, of canopy dynamics and stem wood production and mortality, to analyze the potential effects of drought upon carbon cycling in an Amazon forest ecosystem. Comparison of the rainfall exclusion plot with a similar, but unmodified, control plot reveals potentially important differences in tree carbon allocation, mortality, reproduction, soil respiration and root dynamics. The apparent net consequence of these changes is that, under drier conditions, the amount of CO2 moving out of the forest and into the atmosphere is diminished. This synthesis of above-ground and below-ground data advances understanding of carbon cycling in rain forests, and provides information which should allow more accurate modelling of the response of the Amazon region to future drought. Additional measurements at other sites, and of other ecosystem carbon fluxes, should further refine modelling predictions. 2007-11-27T00:00:00Z http://hdl.handle.net/1842/6506 Title: Modelling the effects of genetic line and feeding system on methane emissions from dairy systems Authors: Bell, Matthew Abstract: Dairy cattle make a significant contribution to global methane emissions. Milking cows in the UK make up about a fifth of the total cattle population, with Holstein-Friesian cows being the most common breed. Investigating ways to minimise methane, a potent greenhouse gas (GHG) produced by dairy cows from enteric fermentation and manure, has gained importance in recent years due its role in climate change. Currently, GHG emissions from UK dairy farming are predicted using the Intergovernmental Panel on Climate Change (IPCC) Tier II methodology. The IPCC Tier II methodology and statistical prediction equations from the literature were evaluated for their ability to reliably model methane output using data from the Langhill Holstein-Friesian experimental herd. The Langhill dairy herd is on a long-term breeding and feeding systems experiment, and cows are on average 88% North American Holstein genes. The production systems within the herd represent a range of dairy systems that may be found commercially. Therefore, production values were assumed to be representative of those that could be found in the commercial Holstein-Friesian population, so factors affecting system methane emissions and appropriate mitigation options could be investigated. Prediction equations using dry matter (DM) intake and gross energy intake as input values were the most appropriate equations for reliably estimating daily enteric methane output. However, if DM intake values are not available, the IPCC Tier II method was found to provide a suitable prediction of methane emissions over a cow‘s lactation and lifetime. This study found that GHG emissions from enteric fermentation and manure, expressed as carbon dioxide equivalents (CO2-eq.), account for about 66% of dairy system CO2-eq. emissions, with enteric methane output being the main contributor (34% of system CO2-eq. emissions). Breeding for increased kilograms of milk fat plus protein production was shown to help reduce dairy system methane emissions. Cows of predominantly North American Holstein genes in this study produced more milk when fed a diet with a low proportion of forage and had lower GHG emissions and land requirement per kilogram energy corrected milk than similar cows fed a diet with a higher proportion of forage. Strategies to mitigate GHG emissions (including methane) and the environmental impact of dairy systems should seek to select animals that better utilise their feed intake to meet their genetic potential for milk production. 2011-06-28T00:00:00Z http://hdl.handle.net/1842/6270 Title: Using satellite remote sensing to quantify woody cover and biomass across Africa Authors: Mitchard, Edward Thomas Alexander Abstract: The goal of quantifying the woody cover and biomass of tropical savannas, woodlands and forests using satellite data is becoming increasingly important, but limitations in current scientific understanding reduce the utility of the considerable quantity of satellite data currently being collected. The work contained in this thesis reduces this knowledgegap, using new field data and analysis methods to quantify changes using optical, radar and LiDAR data. The first paper shows that high-resolution optical data (Landsat & ASTER) can be used to track changes in woody vegetation in the Mbam Djerem National Park in Cameroon. The method correlates a satellite-derived vegetation index with field-measured canopy cover, and the paper concludes that forest encroached rapidly into savanna in the region from 1986-2006. Using the same study area, but with radar remote sensing data from 1996 and 2007 (ALOS PALSAR & JERS-1), the second paper shows that radar backscatter correlates well with field-measured aboveground biomass (AGB). This dataset confirms the woody encroachment within the park; however, in a larger area around the park, deforestation dominates. The AGB-radar relationships described above are expanded in the next paper to include field plots from Budongo Forest (Uganda), the Niassa Reserve (north Mozambique), and the Nhambita Community Project (central Mozambique). A consistent AGB-radar relationship is found in the combined dataset, with the RMSE for predicted AGB values for a site increasing by <30 %, compared with a site-specific equation, when using an AGB-radar equation derived from the three other sites. The study of the Nhambita site is extended in the following paper to assess the ability of radar to detect change over short time periods in this environment, as will be needed for REDD (Reducing Emissions from Deforestation and Degradation). Using radar mosaics from 2007 and 2009, areas known (from detailed ground data) to have been degraded decreased in AGB in the radar change detection, whereas areas of agroforestry and forest protection showed small increases. 2012-06-25T00:00:00Z http://hdl.handle.net/1842/6247 Title: Satellite investigations of ice dynamics and supraglacial lake development in Greenland Authors: Briggs, Kate Hannah Abstract: This thesis aims to improve the current understanding of the processes which control the flow variability of Greenland Ice Sheet (GrIS) outlet glaciers. The most recent Intergovernmental Governmental Panel on Climate Change (IPCC) report (Meehl et al., 2007) identifies that a critical limitation to forecasts of sea-level rise are uncertainties in modelling the ice dynamics of the GrIS. Using Synthetic Aperture Radar (SAR) feature tracking, seasonal velocities of land- and marine- terminating glaciers in a region in the northeast of Greenland are measured. Records of air temperature in conjunction with seasonal observations of supraglacial lake development, sea ice conditions and ice front positions, derived from SAR imagery, are used to investigate the controls on the observed variations in ice velocity. A clear link between ice velocities and glacier hydrology is found. These findings are consistent with observations from other glaciers in Greenland and are suggestive of a universal hydrological forcing of ice velocity for the whole of the GrIS ablation zone. Lake drainage events have been identified as a key factor in linking atmospheric changes, glacier hydrology and ice velocities in Greenland. For modelling purposes, a means of parameterising the distribution and evolution of supraglacial lakes is therefore needed. Assuming that water will pond in surface depressions, this thesis assesses the ability of using Digital Elevation Models (DEMs) for this purpose. High resolution DEMs are created using Interferometric SAR (InSAR) for two, separate regions of the GrIS. The positions and areal extent of surface depressions are compared with those of lakes observed in optical satellite imagery. The level of correspondence between the two datasets is found to be poor as a result of the resolution of the DEMs and the physical differences between surface depressions and lakes (e.g. lakes may not fill the capacity of the depression). An alternative method for parameterising the seasonal distribution of supra-glacial lakes, by extrapolating trends observed in current lake distributions, is investigated. The locations and evolution of lakes in the west of Greenland during the summer of 2003 are mapped using 47 Moderate Resolution Imaging Spectroradiometer (MODIS) images. Clear trends are identified in the distributions of lakes with elevation and are linked to the seasonal melt-cycle and to changes in ice thickness and its influence on surface depressions, tensile stresses and hydrofracturing. It may be possible to extrapolate these trends to other regions and higher elevations on the ice sheet, thereby enabling the distribution of lakes to be parameterised in ice sheet models. The findings of this thesis help to contribute to the understanding of the interaction between climate and ice dynamics in the context of the GrIS. 2012-06-25T00:00:00Z