Background Traffic Modeling for Large-Scale Network Simulation

Network simulation is an indispensable tool for studying Internet-scale networks due to the heterogeneous structure, immense size and changing properties. It is crucial for network simulators to generate representative traffic, which is necessary for effectively evaluating next-generation network protocols and applications. With network simulation, we can make a distinction between foreground traffic, which is generated by the target applications the researchers intend to study and therefore must be simulated with high fidelity, and background traffic, which represents the network traffic that is generated by other applications and does not require significant accuracy. The background traffic has a significant impact on the foreground traffic, since it competes with the foreground traffic for network resources and therefore can drastically affect the behavior of the applications that produce the foreground traffic. This dissertation aims to provide a solution to meaningfully generate background traffic in three aspects. First is realism. Realistic traffic characterization plays an important role in determining the correct outcome of the simulation studies. This work starts from enhancing an existing fluid background traffic model by removing its two unrealistic assumptions. The improved model can correctly reflect the network conditions in the reverse direction of the data traffic and can reproduce the traffic burstiness observed from measurements. Second is scalability. The trade-off between accuracy and scalability is a constant theme in background traffic modeling. This work presents a fast rate-based TCP (RTCP) traffic model, which originally used analytical models to represent TCP congestion control behavior. This model outperforms other existing traffic models in that it can correctly capture the overall TCP behavior and achieve a speedup of more than two orders of magnitude over the corresponding packet-oriented simulation. Third is network-wide traffic generation. Regardless of how detailed or scalable the models are, they mainly focus on how to generate traffic on one single link, which cannot be extended easily to studies of more complicated network scenarios. This work presents a cluster-based spatio-temporal background traffic generation model that considers spatial and temporal traffic characteristics as well as their correlations. The resulting model can be used effectively for the evaluation work in network studies.

Floral and faunal characteristics and content of photosynthetic pigment in soils of northern Victoria Land, Antarctica

Although soil algae are among the main primary producers in most terrestrial ecosystems of continental Antarctica, there are very few quantitative studies on their relative proportion in the main algal groups and on how their distribution is affected by biotic and abiotic factors. Such knowledge is essential for understanding the functioning of Antarctic terrestrial ecosystems. We therefore analyzed biological soil crusts from northern Victoria Land to determine their pH, electrical conductivity (EC), water content (W), total and organic C (TC and TOC) and total N (TN) contents, and the presence and abundance of photosynthetic pigments. In particular, the latter were tested as proxies for biomass and coarse-resolution community structure. Soil samples were collected from five sites with known soil algal communities and the distribution of pigments was shown to reflect differences in the relative proportions of Chlorophyta, Cyanophyta and Bacillariophyta in these sites. Multivariate and univariate models strongly indicated that almost all soil variables (EC, W, TOC and TN) were important environmental correlates of pigment distribution. However, a significant amount of variation is independent of these soil variables and may be ascribed to local variability such as changes in microclimate at varying spatial and temporal scales. There are at least five possible sources of local variation: pigment preservation, temporal variations in water availability, temporal and spatial interactions among environmental and biological components, the local-scale patchiness of organism distribution, and biotic interactions.

The CCRUSH Study: Coarse and fine particulate matter measurements in northeastern Colorado 2009-2012

Coarse (PM10-2.5) and fine (PM2.5) particulate matter in the atmosphere adversely affect human health and influence climate. While PM2.5 is relatively well studied, less is known about the sources and fate of PM10-2.5. The Colorado Coarse Rural-Urban Sources and Health (CCRUSH) study measured PM10-2.5 and PM2.5 mass concentrations, as well as the fraction of semi-volatile material (SVM) in each size regime (SVM2.5, SVM10-2.5), for three years in Denver and comparatively rural Greeley, Colorado. Agricultural operations east of Greeley appear to have contributed to the peak PM10-2.5 concentrations there, but concentrations were generally lower in Greeley than in Denver. Traffic-influenced sites in Denver had PM10-2.5 concentrations that averaged from 14.6 to 19.7 µg/m**3 and mean PM10-2.5/PM10 ratios of 0.56 to 0.70, higher than at residential sites in Denver or Greeley. PM10-2.5 concentrations were more temporally variable than PM2.5 concentrations. Concentrations of the two pollutants were not correlated. Spatial correlations of daily averaged PM10-2.5 concentrations ranged from 0.59 to 0.62 for pairs of sites in Denver and from 0.47 to 0.70 between Denver and Greeley. Compared to PM10-2.5, concentrations of PM2.5 were more correlated across sites within Denver and less correlated between Denver and Greeley. PM10-2.5 concentrations were highest during the summer and early fall, while PM2.5 and SVM2.5 concentrations peaked in winter during periodic multi-day inversions. SVM10-2.5 concentrations were low at all sites. Diurnal peaks in PM10-2.5 and PM2.5 concentrations corresponded to morning and afternoon peaks of traffic activity, and were enhanced by boundary layer dynamics. SVM2.5 concentrations peaked around noon on both weekdays and weekends. PM10-2.5 concentrations at sites located near highways generally increased with wind speeds above about 3 m/s. Little wind speed dependence was observed for the residential sites in Denver and Greeley.

A suite of global, cross-scale topographic variables for environmental and biodiversity modeling, links to files in GeoTIFF format

Topographic variation, the spatial variation in elevation and terrain features, underpins a myriad of patterns and processes in geography and ecology and is key to understanding the variation of life on the planet. The characterization of this variation is scale-dependent, i.e. it varies with the distance over which features are assessed and with the spatial grain (grid cell resolution) of analysis. A fully standardized and global multivariate product of different terrain features has the potential to support many large-scale basic research and analytical applications, however to date, such technique is unavailable. Here we used the digital elevation model products of global 250 m GMTED and near-global 90 m SRTM to derive a suite of topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile and tangential curvature, and 10 geomorphological landform classes. We aggregated each variable to 1, 5, 10, 50 and 100 km spatial grains using several aggregation approaches (median, average, minimum, maximum, standard deviation, percent cover, count, majority, Shannon Index, entropy, uniformity). While a global cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains. All newly-developed variables are available for download at http://www.earthenv.org and can serve as a basis for standardized hydrological, environmental and biodiversity modeling at a global extent.

Wind Resource Mapping Using Landscape Roughness and Spatial Interpolation Methods

Energy saving, reduction of greenhouse gasses and increased use of renewables are key policies to achieve the European 2020 targets. In particular, distributed renewable energy sources, integrated with spatial planning, require novel methods to optimise supply and demand. In contrast with large scale wind turbines, small and medium wind turbines (SMWTs) have a less extensive impact on the use of space and the power system, nevertheless, a significant spatial footprint is still present and the need for good spatial planning is a necessity. To optimise the location of SMWTs, detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in this article, wind measurements and roughness maps were used to create a reliable annual mean wind speed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surface wind speed measurements were converted into meso- and macroscale wind data. The data were further processed by using seven different spatial interpolation methods in order to develop regional wind resource maps. Based on statistical analysis, it was found that the transformation into mesoscale wind, in combination with Simple Kriging, was the most adequate method to create reliable maps for decision-making on optimal production sites for SMWTs in Flanders (Belgium).

The relationship between vegetation and modern pollen assemblages on Mount Paggeo (NE Greece)

In this study, we investigated the relationship between vegetation and modern-pollen rain along the elevational gradient of Mount Paggeo. We apply multivariate data analysis to assess the relationship between vegetation and modern-pollen rain and quantify the representativeness of forest zones. This study represents the first statistical analysis of pollen-vegetation relationship along an elevational gradient in Greece. Hence, this paper improves confidence in interpretation of palynological records from north-eastern Greece and may refine past climate reconstructions for a more accurate comparison of data and modelling. Numerical classification and ordination were performed on pollen data to assess differences among plant communities that beech (Fagus sylvatica) dominates or co-dominates. The results show a strong relationship between altitude, arboreal cover, human impact and variations in pollen and nonpollen palynomorph taxa percentages.

Acoustic telemetry and network analysis reveal the space use of multiple reef predators and enhance marine protected area design

Marine protected areas (MPAs) are commonly employed to protect ecosystems from threats like overfishing. Ideally, MPA design should incorporate movement data from multiple target species to ensure sufficient habitat is protected. We used long-term acoustic telemetry and network analysis to determine the fine-scale space use of five shark and one turtle species at a remote atoll in the Seychelles, Indian Ocean, and evaluate the efficacy of a proposed MPA. Results revealed strong, species-specific habitat use in both sharks and turtles, with corresponding variation in MPA use. Defining the MPA's boundary from the edge of the reef flat at low tide instead of the beach at high tide (the current best in Seychelles) significantly increased the MPA's coverage of predator movements by an average of 34%. Informed by these results, the larger MPA was adopted by the Seychelles government, demonstrating how telemetry data can improve shark spatial conservation by affecting policy directly.

Acoustic telemetry and network analysis reveal the space use of multiple reef predators and enhance marine protected area design

Marine protected areas (MPAs) are commonly employed to protect ecosystems from threats like overfishing. Ideally, MPA design should incorporate movement data from multiple target species to ensure sufficient habitat is protected. We used long-term acoustic telemetry and network analysis to determine the fine-scale space use of five shark and one turtle species at a remote atoll in the Seychelles, Indian Ocean, and evaluate the efficacy of a proposed MPA. Results revealed strong, species-specific habitat use in both sharks and turtles, with corresponding variation in MPA use. Defining the MPA's boundary from the edge of the reef flat at low tide instead of the beach at high tide (the current best in Seychelles) significantly increased the MPA's coverage of predator movements by an average of 34%. Informed by these results, the larger MPA was adopted by the Seychelles government, demonstrating how telemetry data can improve shark spatial conservation by affecting policy directly.

Multivariate analysis of regional-scale geochemical data for environmental monitoring

A compositional multivariate approach is used to analyse regional scale soil geochemical data obtained as part of the Tellus Project generated by the Geological Survey Northern Ireland (GSNI). The multi-element total concentration data presented comprise XRF analyses of 6862 rural soil samples collected at 20cm depths on a non-aligned grid at one site per 2 km2. Censored data were imputed using published detection limits. Using these imputed values for 46 elements (including LOI), each soil sample site was assigned to the regional geology map provided by GSNI initially using the dominant lithology for the map polygon. Northern Ireland includes a diversity of geology representing a stratigraphic record from the Mesoproterozoic, up to and including the Palaeogene. However, the advance of ice sheets and their meltwaters over the last 100,000 years has left at least 80% of the bedrock covered by superficial deposits, including glacial till and post-glacial alluvium and peat. The question is to what extent the soil geochemistry reflects the underlying geology or superficial deposits. To address this, the geochemical data were transformed using centered log ratios (clr) to observe the requirements of compositional data analysis and avoid closure issues. Following this, compositional multivariate techniques including compositional Principal Component Analysis (PCA) and minimum/maximum autocorrelation factor (MAF) analysis method were used to determine the influence of underlying geology on the soil geochemistry signature. PCA showed that 72% of the variation was determined by the first four principal components (PC’s) implying “significant” structure in the data. Analysis of variance showed that only 10 PC’s were necessary to classify the soil geochemical data. To consider an improvement over PCA that uses the spatial relationships of the data, a classification based on MAF analysis was undertaken using the first 6 dominant factors. Understanding the relationship between soil geochemistry and superficial deposits is important for environmental monitoring of fragile ecosystems such as peat. To explore whether peat cover could be predicted from the classification, the lithology designation was adapted to include the presence of peat, based on GSNI superficial deposit polygons and linear discriminant analysis (LDA) undertaken. Prediction accuracy for LDA classification improved from 60.98% based on PCA using 10 principal components to 64.73% using MAF based on the 6 most dominant factors. The misclassification of peat may reflect degradation of peat covered areas since the creation of superficial deposit classification. Further work will examine the influence of underlying lithologies on elemental concentrations in peat composition and the effect of this in classification analysis.

Modeling long-term variability and change of soil moisture and groundwater level - from catchment to global scale

The water stored in and flowing through the subsurface is fundamental for sustaining human activities and needs, feeding water and its constituents to surface water bodies and supporting the functioning of their ecosystems. Quantifying the changes that affect the subsurface water is crucial for our understanding of its dynamics and changes driven by climate change and other changes in the landscape, such as in land-use and water-use. It is inherently difficult to directly measure soil moisture and groundwater levels over large spatial scales and long times. Models are therefore needed to capture the soil moisture and groundwater level dynamics over such large spatiotemporal scales. This thesis develops a modeling framework that allows for long-term catchment-scale screening of soil moisture and groundwater level changes. The novelty in this development resides in an explicit link drawn between catchment-scale hydroclimatic and soil hydraulics conditions, using observed runoff data as an approximation of soil water flux and accounting for the effects of snow storage-melting dynamics on that flux. Both past and future relative changes can be assessed by use of this modeling framework, with future change projections based on common climate model outputs. By direct model-observation comparison, the thesis shows that the developed modeling framework can reproduce the temporal variability of large-scale changes in soil water storage, as obtained from the GRACE satellite product, for most of 25 large study catchments around the world. Also compared with locally measured soil water content and groundwater level in 10 U.S. catchments, the modeling approach can reasonably well reproduce relative seasonal fluctuations around long-term average values. The developed modeling framework is further used to project soil moisture changes due to expected future climate change for 81 catchments around the world. The future soil moisture changes depend on the considered radiative forcing scenario (RCP) but are overall large for the occurrence frequency of dry and wet events and the inter-annual variability of seasonal soil moisture. These changes tend to be higher for the dry events and the dry season, respectively, than for the corresponding wet quantities, indicating increased drought risk for some parts of the world.

Multilevel processes and cultural adaptation: examples from past and present small-scale societies

The last two decades have seen a proliferation of research frameworks that emphasise the importance of understanding adaptive processes that happen at different levels. We contribute to this growing body of literature by exploring how cultural (mal)adaptive dynamics relate to multilevel social-ecological processes occurring at different scales, where the lower levels combine into new units with new organizations, functions, and emergent properties or collective behaviors. After a brief review of the concept of “cultural adaptation” from the perspective of cultural evolutionary theory, the core of the paper is constructed around the exploration of multilevel processes occurring at the temporal, spatial, social, and political scales. We do so by using insights from cultural evolutionary theory and by examining small-scale societies as case studies. In each section, we discuss the importance of the selected scale for understanding cultural adaptation and then present an example that illustrates how multilevel processes in the selected scale help explain observed patterns in the cultural adaptive process. The last section of the paper discusses the potential of modeling and computer simulation for studying multilevel processes in cultural adaptation. We conclude by highlighting how elements from cultural evolutionary theory might enrich the multilevel process discussion in resilience theory.

Long-term fish community response to a reach-scale stream restoration

At a global scale, aquatic ecosystems are being altered by human activities at a greater rate than at any other time in history. In recent years, grassroots efforts have generated interest in the restoration of degraded or destroyed aquatic habitats, especially small wetlands and streams where such projects are feasible with local resources. We present ecological management lessons learned from 17 years of monitoring the fish community response to the channel relocation and reach-level restoration of Juday Creek, a 3rd-order tributary of the St. Joseph River in Indiana, USA. The project was designed to increase habitat complexity, reverse the effects of accumulated fine sediment (< 2 mm diameter), and mitigate for the impacts of a new golf course development. The 1997 restoration consisted of new channel construction within two reaches of a 1.2-km section of Juday Creek that also contained two control reaches. A primary social goal of the golf course development and stream restoration was to avoid harm to the non-native brown trout fishery, as symbolic of community concerns for the watershed. Our long-term monitoring effort revealed that, although fine sediment increased over time in the restored reaches, habitat conditions have promoted the resurgence of native fish species. Since restoration, the fish assemblage has shifted from non-native Salmonidae (brown trout, rainbow trout) to native Centrarchidae (rock bass, largemouth bass, smallmouth bass). In addition, native, nongame species have remained stable or have increased in population abundance (e.g., Johnny darter, mottled sculpin). The results of this study demonstrate the value of learning from a restoration project to adjust management decisions that enhance environmental quality.

Predators on private land: broad-scale socioeconomic interactions influence large predator management

The proliferation of private land conservation areas (PLCAs) is placing increasing pressure on conservation authorities to effectively regulate their ecological management. Many PLCAs depend on tourism for income, and charismatic large mammal species are considered important for attracting international visitors. Broad-scale socioeconomic factors therefore have the potential to drive fine-scale ecological management, creating a systemic scale mismatch that can reduce long-term sustainability in cases where economic and conservation objectives are not perfectly aligned. We assessed the socioeconomic drivers and outcomes of large predator management on 71 PLCAs in South Africa. Owners of PLCAs that are stocking free-roaming large predators identified revenue generation as influencing most or all of their management decisions, and rated profit generation as a more important objective than did the owners of PLCAs that did not stock large predators. Ecotourism revenue increased with increasing lion (Panthera leo) density, which created a potential economic incentive for stocking lion at high densities. Despite this potential mismatch between economic and ecological objectives, lion densities were sustainable relative to available prey. Regional-scale policy guidelines for free-roaming lion management were ecologically sound. By contrast, policy guidelines underestimated the area required to sustain cheetah (Acinonyx jubatus), which occurred at unsustainable densities relative to available prey. Evidence of predator overstocking included predator diet supplementation and frequent reintroduction of game. We conclude that effective facilitation of conservation on private land requires consideration of the strong and not necessarily beneficial multiscale socioeconomic factors that influence private land management.

Catalyst: reimagining sustainability with and through fine art

How might we begin to explore the concept of the “sustainable city” in a world often characterized as dynamic, fluid, and contested? Debates about the sustainable city are too often dominated by a technological discourse conducted among professional experts, but this technocratic framing is open to challenge. For some critics, sustainability is a meaningless notion, yet for others its semantic pliability opens up discursive spaces through which to explore interconnections across time, space, and scale. Thus, while enacting sustainability in policy and practice is an arduous task, we can productively ask how cultural imaginations might be stirred and shaken to make sustainability accessible to a wider public who might join the conversation. What role, we ask, can and should the arts play in wider debates about sustainability in the city today? We explore a coproduced artwork in the northeast of England in order to explain how practice-led research methods were put into dialogue with the social sciences to activate new perspectives on the politics, aesthetics, and practices of sustainability. The case is presented to argue that creative material experimentations can be used as an active research inquiry through which ideas can be tested without knowing predefined means or ends. The case shows how such creativity acts as a catalyst to engage a heterogeneous mix of actors in the redefinition of urban spaces, juxtaposing past and present, with the ephemeral and the (seemingly) durable.

Spatial and Temporal Dynamics of Larval Atlantic Menhaden on the East Coast of the United States

Atlantic Menhaden Brevoortia tyrannus is a commercially and ecologically important forage fish abundant on the Atlantic Coast of the United States. We conducted spatial and temporal analyses of larval Atlantic Menhaden using data collected from two large-scale ichthyoplankton programs during 1977-1987 and 1999-2013 to construct indices of larval abundance and survival over time, evaluate how environmental factors affect early life survival, and examine how larvae are distributed in space to gain knowledge on spawning and larval dispersal. Over time, we found larval abundance to increase, while early life survival declined. Coastal temperature, wind speed, and Atlantic Multidecadal Oscillation were found to potentially explain some of this decline in survival. Over both periods, we found evidence spawning predominantly occurs near shore, from New York to North Carolina, increasing in intensity southwards. While the general spatial patterns were consistent, we observed some localized variation and overall expansion of occupied area by larvae.