(Appendix A) Pigment content, microbial biomass and activity, and grain size characteristics in caged and control sites of the Arctic long-term observatory HAUSGARTEN

Present theories of deep-sea community organization recognize the importance of small-scale biological disturbances, originated partly from the activities of epibenthic megafaunal organisms, in maintaining high benthic biodiversity in the deep sea. However, due to technical difficulties, in situ experimental studies to test hypotheses in the deep sea are lacking. The objective of the present study was to evaluate the potential of cages as tools for studying the importance of epibenthic megafauna for deep-sea benthic communities. Using the deep-diving Remotely Operated Vehicle (ROV) "VICTOR 6000", six experimental cages were deployed at the sea floor at 2500 m water depth and sampled after 2 years (2y) and 4 years (4y) for a variety of sediment parameters in order to test for caging artefacts. Photo and video footage from both experiments showed that the cages were efficient at excluding the targeted fauna. The cage also proved to be appropriate to deep-sea studies considering the fact that there was no fouling on the cages and no evidence of any organism establishing residence on or adjacent to it. Environmental changes inside the cages were dependent on the experimental period analysed. In the 4y experiment, chlorophyll a concentrations were higher in the uppermost centimeter of sediment inside cages whereas in the 2y experiment, it did not differ between inside and outside. Although the cages caused some changes to the sedimentary regime, they are relatively minor compared to similar studies in shallow water. The only parameter that was significantly higher under cages at both experiments was the concentration of phaeopigments. Since the epibenthic megafauna at our study site can potentially affect phytodetritus distribution and availability at the seafloor (e.g. via consumption, disaggregation and burial), we suggest that their exclusion was, at least in part, responsible for the increases in pigment concentrations. Cages might be suitable tools to study the long-term effects of disturbances caused by megafaunal organisms on the diversity and community structure of smaller-sized organisms in the deep sea, although further work employing partial cage controls, greater replication, and evaluating faunal components will be essential to unequivocally establish their utility.

Effect of enhanced pCO2 levels on the production of dissolved organic carbon and transparent exopolymer particles in short-term bioassay experiments

It has been proposed that increasing levels of pCO2 in the surface ocean will lead to more partitioning of the organic carbon fixed by marine primary production into the dissolved rather than the particulate fraction. This process may result in enhanced accumulation of dissolved organic carbon (DOC) in the surface ocean and/or concurrent accumulation of transparent exopolymer particles (TEPs), with important implications for the functioning of the marine carbon cycle. We investigated this in shipboard bioassay experiments that considered the effect of four different pCO2 scenarios (ambient, 550, 750 and 1000 µatm) on unamended natural phytoplankton communities from a range of locations in the northwest European shelf seas. The environmental settings, in terms of nutrient availability, phytoplankton community structure and growth conditions, varied considerably between locations. We did not observe any strong or consistent effect of pCO2 on DOC production. There was a significant but highly variable effect of pCO2 on the production of TEPs. In three of the five experiments, variation of TEP production between pCO2 treatments was caused by the effect of pCO2 on phytoplankton growth rather than a direct effect on TEP production. In one of the five experiments, there was evidence of enhanced TEP production at high pCO2 (twice as much production over the 96 h incubation period in the 750 ?atm treatment compared with the ambient treatment) independent of indirect effects, as hypothesised by previous studies. Our results suggest that the environmental setting of experiments (community structure, nutrient availability and occurrence of phytoplankton growth) is a key factor determining the TEP response to pCO2 perturbations.

Long-term chemical characterization of aerosols at CVAO from 2007 to 2011

The first long-term aerosol sampling and chemical characterization results from measurements at the Cape Verde Atmospheric Observatory (CVAO) on the island of São Vicente are presented and are discussed with respect to air mass origin and seasonal trends. In total 671 samples were collected using a high-volume PM10 sampler on quartz fiber filters from January 2007 to December 2011. The samples were analyzed for their aerosol chemical composition, including their ionic and organic constituents. Back trajectory analyses showed that the aerosol at CVAO was strongly influenced by emissions from Europe and Africa, with the latter often responsible for high mineral dust loading. Sea salt and mineral dust dominated the aerosol mass and made up in total about 80% of the aerosol mass. The 5-year PM10 mean was 47.1 ± 55.5 µg/m**2, while the mineral dust and sea salt means were 27.9 ± 48.7 and 11.1 ± 5.5 µg/m**2, respectively. Non-sea-salt (nss) sulfate made up 62% of the total sulfate and originated from both long-range transport from Africa or Europe and marine sources. Strong seasonal variation was observed for the aerosol components. While nitrate showed no clear seasonal variation with an annual mean of 1.1 ± 0.6 µg/m**3, the aerosol mass, OC (organic carbon) and EC (elemental carbon), showed strong winter maxima due to strong influence of African air mass inflow. Additionally during summer, elevated concentrations of OM were observed originating from marine emissions. A summer maximum was observed for non-sea-salt sulfate and was connected to periods when air mass inflow was predominantly of marine origin, indicating that marine biogenic emissions were a significant source. Ammonium showed a distinct maximum in spring and coincided with ocean surface water chlorophyll a concentrations. Good correlations were also observed between nss-sulfate and oxalate during the summer and winter seasons, indicating a likely photochemical in-cloud processing of the marine and anthropogenic precursors of these species. High temporal variability was observed in both chloride and bromide depletion, differing significantly within the seasons, air mass history and Saharan dust concentration. Chloride (bromide) depletion varied from 8.8 ± 8.5% (62 ± 42%) in Saharan-dust-dominated air mass to 30 ± 12% (87 ± 11%) in polluted Europe air masses. During summer, bromide depletion often reached 100% in marine as well as in polluted continental samples. In addition to the influence of the aerosol acidic components, photochemistry was one of the main drivers of halogenide depletion during the summer; while during dust events, displacement reaction with nitric acid was found to be the dominant mechanism. Positive matrix factorization (PMF) analysis identified three major aerosol sources: sea salt, aged sea salt and long-range transport. The ionic budget was dominated by the first two of these factors, while the long-range transport factor could only account for about 14% of the total observed ionic mass.

Essays on the term structure of interest rates

This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed timevarying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible realtime term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.

Essays on the term structure of interest rates

This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed time-varying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible real-time term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.

Long-term relationship between energy consumption and GDP in Latin America: an empirical assessment using panel data

The main objetive of this research is to evaluate the long term relationship between energy consumption and GDP for some Latin American countries in the period 1980-2009 -- The estimation has been done through the non-stationary panel approach, using the production function in order to control other sources of GDP variation, such as capital and labor -- In addition to this, a panel unit root tests are used in order to identify the non-stationarity of these variables, followed by the application of panel cointegration test proposed by Pedroni (2004) to avoid a spurious regression (Entorf, 1997; Kao, 1999)

EVALUATION AND MONITORING OF ASH (FRAXINUS SPP.) TOLERANT TO LONG-TERM EMERALD ASH BORER (AGRILUS PLANIPENNIS [COLEOPTERA: BUPRESTIDAE]) EXPOSURE

Invasive insects that successfully establish in introduced areas can significantly alter natural communities. These pests require specific establishment criteria (e.g. host suitability) that, when known, can help quantify potential damage to infested areas. Emerald ash borer (Agrilus planipennis [Coleoptera: Buprestidae]) is an invasive phloem-feeding pest which is responsible for the death of millions of ash trees (Fraxinus spp. L.). Over 200 surviving ash trees were previously identified in the Huron-Clinton Metroparks located in southeast Michigan. Trees were assessed over a four year period and a hierarchical cluster analysis was performed on dieback, vigor, and presence of signs and symptoms, in order to place trees into one of three tolerance groups. The clustering of trees with different responses to emerald ash borer attack suggests that there are different tolerance levels in North American ash trees in southeastern Michigan, and these groups were designated as apparently tolerant, not tolerant and intermediate tolerance. Adult landing rates and evidence of adult emergence were significantly lower in the apparently tolerant group compared with the not tolerant group, but larval survival from eggs placed on trees did not differ between tolerance groups. Therefore, it appears that apparently tolerant trees survive because they are less attractive to adult beetles which results in fewer eggs being laid on them. Trees in the apparently tolerant group remained of higher vigor over the four years of the study. North American ash may survive the emerald ash borer epidemic due to natural variation and inherent resistance regardless of the lack of co-evolutionary history with emerald ash borer.

GENETIC VARIATION, LOCAL ADAPTATION AND POPULATION STRUCTURE IN NORTH AMERICAN RED OAK SPECIES, QUERCUS RUBRA L. AND Q. ELLIPSOIDALIS E. J. HILL

Forest trees, like oaks, rely on high levels of genetic variation to adapt to varying environmental conditions. Thus, genetic variation and its distribution are important for the long-term survival and adaptability of oak populations. Climate change is projected to lead to increased drought and fire events as well as a northward migration of tree species, including oaks. Additionally, decline in oak regeneration has become increasingly concerning since it may lead to decreased gene flow and increased inbreeding levels. This will in turn lead to lowered levels of genetic diversity, negatively affecting the growth and survival of populations. At the same time, populations at the species’ distribution edge, like those in this study, could possess important stores of genetic diversity and adaptive potential, while also being vulnerable to climatic or anthropogenic changes. A survey of the level and distribution of genetic variation and identification of potentially adaptive genes is needed since adaptive genetic variation is essential for their long-term survival. Oaks possess a remarkable characteristic in that they maintain their species identity and specific environmental adaptations despite their propensity to hybridize. Thus, in the face of interspecific gene flow, some areas of the genome remain differentiated due to selection. This characteristic allows the study of local environmental adaptation through genetic variation analyses. Furthermore, using genic markers with known putative functions makes it possible to link those differentiated markers to potential adaptive traits (e.g., flowering time, drought stress tolerance). Demographic processes like gene flow and genetic drift also play an important role in how genes (including adaptive genes) are maintained or spread. These processes are influenced by disturbances, both natural and anthropogenic. An examination of how genetic variation is geographically distributed can display how these genetic processes and geographical disturbances influence genetic variation patterns. For example, the spatial clustering of closely related trees could promote inbreeding with associated negative effects (inbreeding depression), if gene flow is limited. In turn this can have negative consequences for a species’ ability to adapt to changing environmental conditions. In contrast, interspecific hybridization may also allow the transfer of genes between species that increase their adaptive potential in a changing environment. I have studied the ecologically divergent, interfertile red oaks, Quercus rubra and Q. ellipsoidalis, to identify genes with potential roles in adaptation to abiotic stress through traits such as drought tolerance and flowering time, and to assess the level and distribution of genetic variation. I found evidence for moderate gene flow between the two species and low interspecific genetic differences at most genetic markers (Lind and Gailing 2013). However, the screening of genic markers with potential roles in phenology and drought tolerance led to the identification of a CONSTANS-like (COL) gene, a candidate gene for flowering time and growth. This marker, located in the coding region of the gene, was highly differentiated between the two species in multiple geographical areas, despite interspecific gene flow, and may play a role in reproductive isolation and adaptive divergence between the two species (Lind-Riehl et al. 2014). Since climate change could result in a northward migration of trees species like oaks, this gene could be important in maintaining species identity despite increased contact zones between species (e.g., increased gene flow). Finally I examined differences in spatial genetic structure (SGS) and genetic variation between species and populations subjected to different management strategies and natural disturbances. Diverse management activities combined with various natural disturbances as well as species specific life history traits influenced SGS patterns and inbreeding levels (Lind-Riehl and Gailing submitted).

ANALYSIS OF POPULUS TREMULOIDES CLONAL VARIATION AND DELINEATION IN THE OTTAWA NATIONAL FOREST

The technique of delineating Populus tremuloides (Michx.) clonal colonies based on morphology and phenology has been utilized in many studies and forestry applications since the 1950s. Recently, the availability and robustness of molecular markers has challenged the validity of such approaches for accurate clonal identification. However, genetically sampling an entire stand is largely impractical or impossible. For that reason, it is often necessary to delineate putative genet boundaries for a more selective approach when genetically analyzing a clonal population. Here I re-evaluated the usefulness of phenotypic delineation by: (1) genetically identifying clonal colonies using nuclear microsatellite markers, (2) assessing phenotypic inter- and intraclonal agreement, and (3) determining the accuracy of visible characters to correctly assign ramets to their respective genets. The long-term soil productivity study plot 28 was chosen for analysis and is located in the Ottawa National Forest, MI (46° 37'60.0" N, 89° 12'42.7" W). In total, 32 genets were identified from 181 stems using seven microsatellite markers. The average genet size was 5.5 ramets and six of the largest were selected for phenotypic analyses. Phenotypic analyses included budbreak timing, DBH, bark thickness, bark color or brightness, leaf senescence, leaf serrations, and leaf length ratio. All phenotypic characters, except for DBH, were useful for the analysis of inter- and intraclonal variation and phenotypic delineation. Generally, phenotypic expression was related to genotype with multiple response permutation procedure (MRPP) intraclonal distance values ranging from 0.148 and 0.427 and an observed MRPP delta value=0.221 when the expected delta=0.5. The phenotypic traits, though, overlapped significantly among some clones. When stems were assigned into phenotypic groups, six phenotypic groups were identified with each group containing a dominant genotype or clonal colony. All phenotypic groups contained stems from at least two clonal colonies and no clonal colony was entirely contained within one phenotypic group. These results demonstrate that phenotype varies with genotype and stand clonality can be determined using phenotypic characters, but phenotypic delineation is less precise. I therefore recommend that some genetic identification follow any phenotypic delineation. The amount of genetic identification required for clonal confirmation is likely to vary based on stand and environmental conditions. Further analysis, however, is needed to test these findings in other forest stands and populations.

Measuring Latency Variation in the Internet

We analyse two complementary datasets to quantify the latency variation experienced by internet end-users: (i) a large-scale active measurement dataset (from the Measurement Lab Network Diagnostic Tool) which shed light on long-term trends and regional differences; and (ii) passive measurement data from an access aggregation link which is used to analyse the edge links closest to the user. The analysis shows that variation in latency is both common and of significant magnitude, with two thirds of samples exceeding 100\,ms of variation. The variation is seen within single connections as well as between connections to the same client. The distribution of experienced latency variation is heavy-tailed, with the most affected clients seeing an order of magnitude larger variation than the least affected. In addition, there are large differences between regions, both within and between continents. Despite consistent improvements in throughput, most regions show no reduction in latency variation over time, and in one region it even increases. We examine load-induced queueing latency as a possible cause for the variation in latency and find that both datasets readily exhibit symptoms of queueing latency correlated with network load. Additionally, when this queueing latency does occur, it is of significant magnitude, more than 200\,ms in the median. This indicates that load-induced queueing contributes significantly to the overall latency variation.

Geographic Variation of Notified Ross River Virus Infections in Queensland, Australia, 1985-1996

The spatial and temporal variations of Ross River virus infections reported in Queensland, Australia, between 1985 and 1996 were studied by using the Geographic Information System. The notified cases of Ross River virus infection came from 489 localities between 1985 and 1988, 805 between 1989 and 1992, and 1,157 between 1993 and 1996 (chi2(df = 2) = 680.9; P < 0.001). There was a marked increase in the number of localities where the cases were reported by 65 percent for the period of 1989-1992 and 137 percent for 1993-1996, compared with that for 1985-1988. The geographic distribution of the notified Ross River virus cases has expanded in Queensland over recent years. As Ross River virus disease has impacted considerably on tourism and industry, as well as on residents of affected areas, more research is required to explore the causes of the geographic expansion of the notified Ross River virus infections.