Continuous cellular automata on irregular tessellations : mimicking steady-state heat flow

Leaving a few exceptions aside, cellular automata (CA) and the intimately related coupled-map lattices (CML), commonly known as continuous cellular automata (CCA), as well as models that are based upon one of these paradigms, employ a regular tessellation of an Euclidean space in spite of the various drawbacks this kind of tessellation entails such as its inability to cover surfaces with an intricate geometry, or the anisotropy it causes in the simulation results. Recently, a CCA-based model describing steady-state heat flow has been proposed as an alternative to Laplace's equation that is, among other things, commonly used to describe this process, yet, also this model suffers from the aforementioned drawbacks since it is based on the classical CCA paradigm. To overcome these problems, we first conceive CCA on irregular tessellations of an Euclidean space after which we show how the presented approach allows a straightforward simulation of steady-state heat flow on surfaces with an intricate geometry, and, as such, constitutes an full-fledged alternative for the commonly used and easy-to-implement finite difference method, and the more intricate finite element method

A review of wildland fire spread modelling, 1990-present 3: Mathematical analogues and simulation models

In recent years, advances in computational power and spatial data analysis (GIS, remote sensing, etc) have led to an increase in attempts to model the spread and behvaiour of wildland fires across the landscape. This series of review papers endeavours to critically and comprehensively review all types of surface fire spread models developed since 1990. This paper reviews models of a simulation or mathematical analogue nature. Most simulation models are implementations of existing empirical or quasi-empirical models and their primary function is to convert these generally one dimensional models to two dimensions and then propagate a fire perimeter across a modelled landscape. Mathematical analogue models are those that are based on some mathematical conceit (rather than a physical representation of fire spread) that coincidentally simulates the spread of fire. Other papers in the series review models of an physical or quasi-physical nature and empirical or quasi-empirical nature. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but much less comprehensively.Comment: 20 pages + 9 pages references + 1 page figures. Submitted to the International Journal of Wildland Fir

INVESTIGATION INTO GAME-BASED CRISIS SCENARIO MODELLING AND SIMULATION SYSTEM

A crisis is an infrequent and unpredictable event. Training and preparation process requires tools for representation of crisis context. Particularly, crisis events consist of different situations, which can occur at the same time combining into complex situation and becoming a challenge in coordinating several crisis management departments. In this regards, disaster prevention, preparedness and relief can be conceptualized into a design of hypothetical crisis game. Many complex tasks during development of emergency circumstance provide an opportunity for practitioners to train their skills, which are situation analysis, decision-making, and coordination procedures. While the training in physical workouts give crisis personal a hand-on experience in the given situation, it often requires a long time to prepare with a considerable budget. Alternatively, computational framework which allows simulation of crisis models tailoring into crisis scenario can become a cost-effective substitution to this study and training. Although, there are several existing computational toolsets to simulate crisis, there is no system providing a generic functionality to define crisis scenario, simulation model, agent development, and artificial intelligence problem planning in the single unified framework. In addition, a development of genetic framework can become too complex due to a multi-disciplinary knowledge required in each component. Besides, they have not fully incorporated a game technology toolset to fasten the system development process and provide a rich set of features and functionalities to these mentioned components. To develop such crisis simulation system, there are several technologies that must be studied to derive a requirement for software engineering approach in system’s specification designs. With a current modern game technology available in the market, it enables fast prototyping of the framework integrating with cutting-edge graphic render engine, asset management, networking, and scripting library. Therefore, a serious game application for education in crisis management can be fundamentally developed early. Still, many features must be developed exclusively for the novel simulation framework on top of the selected game engine. In this thesis, we classified for essential core components to design a software specification of a serious game framework that eased crisis scenario generation, terrain design, and agent simulation in UML formats. From these diagrams, the framework was prototyped to demonstrate our proposed concepts. From the beginning, the crisis models for different disasters had been analysed for their design and environment representation techniques, thus provided a choice of based simulation technique of a cellular automata in our framework. Importantly, a study for suitability in selection of a game engine product was conducted since the state of the art game engines often ease integration with upcoming technologies. Moreover, the literatures for a procedural generation of crisis scenario context were studied for it provided a structure to the crisis parameters. Next, real-time map visualization in dynamic of resource representation in the area was developed. Then the simulation systems for a large-scale emergency response was discussed for their choice of framework design with their examples of test-case study. An agent-based modelling tool was also not provided from the game engine technology so its design and decision-making procedure had been developed. In addition, a procedural content generation (PCG) was integrated for automated map generation process, and it allowed configuration of scenario control parameters over terrain design during run-time. Likewise, the artificial planning architecture (AI planning) to solve a sequence of suitable action toward a specific goal was considered to be useful to investigate an emergency plan. However, AI planning most often requires an offline computation with a specific planning language. So the comparison study to select a fast and reliable planner was conducted. Then an integration pipeline between the planner and agent was developed over web-service architecture to separate a large computation from the client while provided ease of AI planning configuration using an editor interface from the web application. Finally, the final framework called CGSA-SIM (Crisis Game for Scenario design and Agent modelling simulation) was evaluated for run-time performance and scalability analysis. It shown an acceptable performance framerate for a real-time application in the worst 15 frame-per-seconds (FPS) with maximum visual objects. The normal gameplay performed capped 60 FPS. At same time, the simulation scenario for a wildfire situation had been tested with an agent intervention which generated a simulation data for personal or case evaluation. As a result, we have developed the CGSA-SIM framework to address the implementation challenge of incorporating an emergency simulation system with a modern game technology. The framework aims to be a generic application providing main functionality of crisis simulation game for a visualization, crisis model development and simulation, real-time interaction, and agent-based modelling with AI planning pipeline

Understanding Rare Species In California: An Assessment Of Camatta Canyon Amole (Hooveria Purpurea Var. Reducta) And A Meta-Analysis Of California Rare Plants In Literature

California is currently in the midst of a biodiversity crisis. There are approximately 5,000 native species of plants in California, a quarter of which are considered rare. Determining threats to these rare plants is often times difficult. Despite California\u27s botanical resources, we still know very little about much of California’s rare plants. San Luis Obispo County is home to 2,000 of California’s native plant taxa, one- third of which are rare or endemic to the county. These species are of great local and environmental concern. In Chapter 1, we attempted to assess the impact of non native species on a threatened species in eastern San Luis Obispo County. We conducted an invasive thatch removal experiment on 10 vegetation plots of Camatta Canyon Amole, Hooveria purpurea var. reducta. The Camatta Canyon Amole (CCA) is a federally listed “threatened” plant that is only known to occur on 21.15 ha of land on Los Padres National Forest (LPNF). In the 1980s, U.S. Fish and Wildlife Service established 10 plots to monitor the population of CCA. These biologists recorded a decrease in the CCA since the establishment of those plots in the 1980s. One hypothesis for the decline is the absence of cattle grazing from LPNF, which has resulted in the accumulation of a dense thatch layer. We experimentally removed this thatch layer in five of the 1980s vegetation plots to test this hypothesis. While our the experiment was designed to be a long term treatment, from the first 1.5 years, we found no relationship between thatch removal and the amount of CCA in each plot. The effect of our treatment may take many years to materialize. In Chapter 2, we conducted extensive botanical surveys of the Camatta Ranch, a 32,000 acre cattle ranch in eastern San Luis Obispo County. The goal of these surveys was to estimate the distribution and population size of CCA on private property, which has never before been accessed or surveyed. We did this in two ways: 1) We created a density ratio estimate based off of plot sampling done on the ranch and 2) we created a species distribution model (SDM) to predict the likelihood of presence throughout the ranch. Our surveys of Camatta Ranch, coupled with our SDM suggest that a majority of CCA’s preferred habitat is on Camatta Ranch, making the ranch of paramount concern for CCA’s protection. Our estimates suggest that 90% of the total population of CCA occurs on Camatta Ranch. In Chapter 3, we attempted to quantify biases in the literature about California’s flora. The California Floristic Province is one of the most biologically diverse floras in the world. Considerable legal and conservation attention is given to rare plants in California. However, there is no information as to the research effort given to rare species in California. Here we ask the question: Is there more research done on rare plants in California than on non-rare species? To answer this question, we quantified the amount of literature available on Google Scholar for California’s rare plants, weeds, and non-rare natives. To account for the differences in species geographic extent, we aggregated occurrence data for each species from GBIF to determine their ranges. We found that rare species were severely under-represented in the literature, even after accounting for the differences in species extent

Understanding The Influence Of Participants\u27 Preferences On The Affiliation Network Of Churches Using Agent-based Modeling

As the affiliation network of churches may potentially benefit public health, the impact of participants’ preferences on the affiliation network bears further study. This paper attempts to use agent-based modeling techniques associated with geographic information to study the affiliation network between churches and participants. Using churches in ZIP Code 30318 in Atlanta in Georgia, this study specifies the preferences of participants as personal radii and choice patterns. Results suggest (1) personal radii of participants are positively related to the size of affiliation network and the centralities of churches; (2) the change of choice pattern of participants can lead to a sharp reduction in size of the affiliation network of churches; (3) The centralities of churches among the affiliation network are corresponding to population density of census tracts. Findings can be used to understand the formulation of affiliation network of churches and their relationship with participants’ preferences

Effects of Climate Change and Landscape-Scale Forest Management on Avian Communities, Abundance, and Nest Success in the Appalachian Mountains

Birds are integral components of ecosystems and account for billions of dollars in tangible benefits to humans. As such, recent continental declines of bird species have ecological and economic consequences, providing the impetus for my dissertation research. I identified knowledge gaps and proposed novel questions about how birds in the Appalachian Mountains are influenced by changing environmental conditions due to climate change and forest management. The Appalachian Mountains encompass an important biogeographical region with high conservation value due to its myriad habitats and corresponding bird species diversity. Thus, there is a critical need to evaluate the effects of shifting climate factors and land management decisions on long-term trends in bird populations in this region. I designed my dissertation research to fulfill that need, developing 4 chapters that investigate the effects of temperature, precipitation, land cover, and management actions on Appalachian forest bird communities. The first 2 chapters of my dissertation emphasize the role of climate in the Appalachian Mountains. In Chapter 1, I determined the potential effects of both climate and land cover change on forest songbirds breeding in the Appalachian Mountains region by conducting a comprehensive review of published literature and presenting a novel case study. The literature review focused on synthesizing documented and predicted changes in bird species distributions, populations, and communities in response to changes in climate and land cover across the Appalachian Mountains. I concluded by noting the dearth of studies from the Appalachian Mountains that track long-term avian responses, particularly population dynamics, to changing climate and land cover. For my case study, I used 20 years of North American Breeding Bird Survey data from 322 survey routes within the Appalachian Mountains Bird Conservation Region to model the regionwide abundance and distributions of 14 songbird species, disentangle the influences of climate versus land cover change, and predict the consequences of future shifts in climate and land cover patterns. I found that both climate and land cover variables were important in shaping forest songbird distributions. However, the proportions of land cover types tended to be more influential and had higher effect sizes than temperature or precipitation variables. When predicting future distributions of the 14 focal forest songbird species within the Appalachian Mountains, the future climate and land cover combination scenarios had varying but limited impacts on projected relative abundance, regional occupancy, and shifts in the distribution of relative abundance, with the strongest consistent effects on cold-associated species and the 2 warmest scenarios resulting in the greatest differences between contemporary and future projections. Overall, the net projected impact of climate change on breeding forest songbirds within the Appalachian Mountains was modest at a broad spatiotemporal scale, but there may be cause for conservation concern for cold-associated species if greenhouse gas emissions remain high. Furthermore, based on the importance and effect sizes of land cover variables in my case study, land use changes that result in reduced forest cover and increased urban cover may pose a more immediate threat than climate change to forest songbirds in this region. The second chapter of my dissertation takes a finer-scale approach compared to Chapter 1 and investigates whether the influence of climate change on forest songbirds in the Appalachian Mountains is mediated by latitude and elevation. In Chapter 2, I quantified differences in how forest songbird communities are affected by climate factors and additionally explored concurrent temporal trends across latitudinal and elevational gradients within the Appalachian Mountains. My specific objectives were to apply interactions with both latitude and elevation in quantifying how temperature, precipitation, and other temporal factors influence climate-related guild richness and the abundance of specific focal species during the breeding season. I used nearly 30 years of bird survey data from 1,733 sites at various elevations in National Forests located within the Northern, Central, and Southern Appalachians to model responses in guild richness and focal species abundance to climate factors and long-term temporal trends. I found that guild-specific relationships varied among latitudinal regions and along elevational gradients within the Appalachian Mountains. The results of this study are valuable for understanding historical effects of changing climate factors and improving predictions of future climate change impacts on forest songbirds in the Appalachian Mountains by verifying and delineating the dynamic nature of the relationships with temperature and precipitation across latitudinal and elevational gradients. My findings will also help to inform forest songbird conservation efforts in the Appalachian Mountains because they quantify the regional effects of temperature and precipitation on climate-related guilds and forest songbird species, and identify specific latitudes and elevations at which they are at the highest risk from climate change and other temporal factors. Based on my models, climate mitigation strategies for forest songbirds in the Appalachian Mountains are most needed for cold-associated species and for low elevations in the Southern Appalachians. My final 2 chapters focus on the role of land management decisions within the Central Appalachian region. In Chapter 3, I used 17 years of historical bird survey data to fill a knowledge gap about long-term bird responses to landscape-scale forest management by investigating how avian diversity, abundance, and population dynamics changed over time in 2 Central Appalachian forested landscapes with varying levels of timber harvest intensity. My specific objectives were to examine the influence and effect of interactions between time and landscape-scale timber harvest intensity on breeding season songbird guild richness, focal species abundance, and focal species nest success. I found that guild richness and focal species abundance tended to be consistently higher in the actively harvested landscape, and trends in guild richness and species abundance over time were consistently positive in the actively harvested landscape and negative in the minimally harvested landscape. In particular, early-successional / edge-associated species and forest-gap species were found in higher numbers and exhibited positive temporal trends in the actively harvested landscape. However, a holistic assessment that included trends in reproductive success highlighted long-term declines in nest success for a forest-interior species of regional conservation concern within the actively harvested landscape but not the minimally harvested landscape. Thus, there are important trade-offs to consider when using landscape-scale forest management to promote songbird communities and populations in forested landscapes. The fourth chapter of my dissertation addresses specific management efforts to promote target game birds and a diversity of breeding and post-breeding songbirds in heavily forested landscapes. In Chapter 4, I collected extensive data from 335 wildlife openings within the Monongahela National Forest, and then quantified how a suite of site-level and landscape-level wildlife opening attributes relate to multi-species occupancy of 3 game birds (wild turkey, ruffed grouse, and American woodcock) during the game bird courtship season and songbird guild richness during the breeding and post-breeding seasons. I found that game bird species occupancy in wildlife openings may be best explained by management actions and local habitat attributes. My findings further indicated that it is feasible to manage wildlife openings for the mutual benefit of different species groups across seasons. I presented a set of management recommendations to maximize occurrence of wild turkey, ruffed grouse, and American woodcock in concordance with breeding and post-breeding songbird occurrence within wildlife openings, with considerations for minimizing negative impacts to breeding songbirds in adjacent forests. These actions can be applied by private landowners, non-governmental organizations, and government agencies to simultaneously meet management goals and promote avian diversity in forest ecosystems. Combining all 4 chapters, my dissertation research generates critical knowledge needed to manage and conserve important natural resources that are ecologically and economically valuable, particularly in the Appalachian Mountains region. My first 2 research studies advance understanding of climate change effects and underscore the significance of the Appalachian Mountains to regional bird communities, especially cold-associated bird species, with important implications for mitigating large-scale threats to biodiversity. The final 2 research studies provide specific management considerations and recommendations for Central Appalachian forests that will holistically benefit and sustain many forest bird species, including target game birds and species of regional conservation concern

Energieeffiziente und rechtzeitige Ereignismeldung mittels drahtloser Sensornetze

This thesis investigates the suitability of state-of-the-art protocols for large-scale and long-term environmental event monitoring using wireless sensor networks based on the application scenario of early forest fire detection. By suitable combination of energy-efficient protocol mechanisms a novel communication protocol, referred to as cross-layer message-merging protocol (XLMMP), is developed. Qualitative and quantitative protocol analyses are carried out to confirm that XLMMP is particularly suitable for this application area. The quantitative analysis is mainly based on finite-source retrial queues with multiple unreliable servers. While this queueing model is widely applicable in various research areas even beyond communication networks, this thesis is the first to determine the distribution of the response time in this model. The model evaluation is mainly carried out using Markovian analysis and the method of phases. The obtained quantitative results show that XLMMP is a feasible basis to design scalable wireless sensor networks that (1) may comprise hundreds of thousands of tiny sensor nodes with reduced node complexity, (2) are suitable to monitor an area of tens of square kilometers, (3) achieve a lifetime of several years. The deduced quantifiable relationships between key network parameters — e.g., node size, node density, size of the monitored area, aspired lifetime, and the maximum end-to-end communication delay — enable application-specific optimization of the protocol

Towards simulating the emergence of environmentally responsible behavior among natural resource users : an integration of complex systems theory, machine learning and geographic information science

La gouvernance pour le développement durable comporte de nombreux défis. L'un de ces défis consiste à mieux comprendre les systèmes socio-écologiques gouvernés. Dans de tels systèmes, l'apprentissage par essais et erreurs implique le risque de conséquences inattendues, irréversibles et néfastes. De plus, en raison de la complexité des systèmes socio-écologiques, les leçons tirées d'expériences à petite échelle ne peuvent pas toujours être applicables à des problèmes à grande échelle. Un autre aspect difficile des problèmes de développement durable est que ces problèmes sont souvent multidisciplinaires et composés de composants qui sont chacun étudiés individuellement dans une discipline différente, mais il existe peu d'informations sur leur comportement ensemble. Un troisième défi de la gouvernance pour le développement durable est qu'il est souvent nécessaire d'impliquer les parties prenantes dans des actions de gestion et des mesures d'intervention coûteuses pour les individus qui y participent. De plus, dans de nombreuses situations de ce type, les incitations financières et l'application des réglementations se soldent par un échec et ne constituent donc pas des options de gouvernance. Dans cette thèse, les défis ci-dessus sont abordés dans un exemple de contrôle des perturbations forestières avec une approche intégrée. Pour éviter le problème des effets indésirables irréversibles et pour permettre des expériences répétées, une approche de simulation est utilisée. Pour relever le défi de la multidisciplinarité des problèmes des systèmes socio-écologiques, deux modèles sont développés indépendamment - portant sur les aspects sociaux et écologiques du système de l'étude - et ils sont ensuite couplés de telle sorte que la sortie de chaque modèle est utilisée comme entrée pour l'autre modèle. Pour résoudre le problème de l'engagement des parties prenantes, un plan est proposé pour la promotion d'un comportement respectueux de l'environnement. Ce plan est basé sur l'offre de reconnaissance à ceux qui adoptent volontairement le comportement responsable. Le modèle écologique de cette étude, qui simule la propagation d'une perturbation forestière, est construit à l'aide de l’apprentissage automatique supervisé. Le modèle social de cette étude, qui simule l'émergence d'une nouvelle norme de comportement, est construit à l'aide de l'apprentissage par renforcement. Les deux modèles sont testés et validés avant couplage. Le modèle couplé est ensuite utilisé comme un laboratoire virtuel, où plusieurs expériences sont réalisées dans un cadre hypothétique et selon différents scénarios. Chacune de ces expériences est une simulation. A travers ces simulations, cette étude montre qu'avec un algorithme de prise de décision approprié et avec suffisamment de temps pour l'interaction entre une entité gouvernante et la société, il est possible de créer une motivation pour un comportement responsable dans la société. En d'autres termes, il est possible d'encourager la participation volontaire des acteurs à l'action pour le développement durable, sans que l'entité gouvernante ait besoin d'utiliser des incitations financières ou d'imposer son autorité. Ces résultats peuvent être applicables à d'autres contextes où un comportement responsable des individus ou des entreprises est recherché afin d'atténuer l'impact d'une perturbation, de protéger une ressource écologique, ou de faciliter une transition sectorielle vers la durabilité.Governance for sustainable development involves many challenges. One of those challenges is to gain insight about the social-ecological systems being governned. In such systems, learning by trial and error involve the risk of unexpected, irreversible and adverse consequences. Moreover, due to complexity of social-ecological systems, lessons learned from small scale experiments may not be applicable in large-scale problems. Another challenging aspect of problems of sustainable development is that these problems are often multidisciplinary and comprised of components that are each studied individually in a different discipline, but little information exists about their behavior together as a whole. A third challenge in governance for sustainable development is that often it is necessary to involve stakeholders in management actions and intervention measures that are costly for individuals who participate in them. Moreover, in many of these situations financial incentives or enforcement of regulations result in failure, and are thus not options for governance. In this thesis, the above challenges are addressed in an example case of forest disturbance control with an integrated approach. To avoid the problem of irreversible adverse effects and to allow repeated experiments, a simulation approach is used. To tackle the challenge of multidisciplinarity of problems of social-ecological systems, two models are independently developed – pertaining to social and ecological aspects of the system of the study – and they are subsequently coupled in such a way that the output of each model served as an input for the other. To address the problem of engagement of stakeholders, a scheme is proposed for promotion of environmentally responsible behavior. This scheme is based on offering recognition to those who voluntarily perform the responsible behavior. The ecological model of this study, which simulates the spread of a forest disturbance, is built using Supervised Machine Learning. The social model of this study, which simulates the emergence of a new norm of behavior, is built using Reinforcement Learning. Both models are tested and validated before coupling. The coupled model is then used as a virtual laboratory, where several experiments are performed in a hypothetical setting and under various scenarios. Each such experiment is a simulation. Through these simulations, this study shows that with an appropriate decision-making algorithm and with sufficient time for interaction between a governing entity and the society, it is possible to create motivation for responsible behavior in the society. In other words, it is possible to encourage voluntary participation of stakeholders in action for sustainable development, without the need for the governing entity to use financial incentives or impose its authority. These results may be applicable to other contexts where responsible behavior by individuals or enterprises is sought in order to mitigate the impact of a disturbance, protect an ecological resource, or facilitate a sectoral transition towards sustainability