Neste trabalho realizou-se o estudo de distribuição, riqueza e conservação do gênero Davilla Vand. (Dilleniaceae) no Neotrópico. Para tal utilizou-se a modelagem de distribuição de espécies com o algoritmo Maxent. Este produz distribuição das espécies no espaço geográfico a partir de dados ambiental e de ocorrência. Foram estudadas as espécies de acordo com o bioma de ocorrência: Mata Atlântica; Cerrado; e Amazônia. Este grupo está representado no Neotrópico por 25 espécies. Para o Cerrado incluiu-se além das espécies do gênero Davilla as demais espécies da família Dilleniaceae. Os resultados indicaram que no Cerrado o grupo está representado por nove espécies de Davilla, além de Curatella americana L. e três espécies de Doliocarpus Rol., destas cinco são endêmicas (Doliocarpus elegans Eichler e 4 Davilla spp.). Para a Mata Atlântica ocorrem 12 espécies de Davilla, oito delas são endêmicas, incluindo uma espécie ameaçada de extinção. Para a Floresta Amazônica são conhecidas nove espécies, cinco delas endêmicas. Duas outras espécies são Neotropicais, portanto, compartilhadas por todos os biomas citados anteriormente. As demais espécies são de ocorrência em pelo menos dois biomas. Para estes três biomas produziu-se a distribuição e a riqueza de espécies visando comparar os resultados com as unidades de conservação, objetivando discutir questões relativas à conservação deste grupo. Os parâmetros conservacionistas como espécies raras, zonas de endemismo, zonas de alta riqueza, áreas de preservação ambiental, foram confrontados objetivando indicar áreas prioritárias para a conservação do grupo e da biodiversidade. Os resultados indicaram existir três centros de diversidade para este grupo. O principal deles está localizado na Mata Atlântica, principalmente nas florestas litorâneas do estado da Bahia. Outro centro de diversidade localiza-se na região central do Cerrado, especialmente nos estados de Goiás e Bahia. A outra área de diversidade localiza-se próximo à foz do Rio Amazonas e ao longo de seu curso. Devido ao hábito predominante das espécies serem lianas, estas são importantes componentes das florestas, das quais usamos este referencial para discutir questões relativas à conservação destes habitats, de suas espécies e da biodiversidade. As informações completas estão apresentadas nos capítulos de acordo com os respectivos biomas abordados. / In this study was realized to study the distribution, richness and conservation of the Davilla Vand. (Dilleniaceae) in the neotropics. For this purpose was used to distribution model of species with Maxent algorithm. This produces species distribution in geographic in space based on environmental and occurrence data. Species in accordance with biome of occurrence were studied: Atlantic Forest; Cerrado; and the Amazon. This group is represented by 25 species in the neotropics. For the Cerrado was included in addition to the Davilla species all species of Dilleniaceae family. The results indicated that in the Cerrado this group is represented by nine species of Davilla, and Curatella americana L. and three species of Doliocarpus Rol., to these five are endemic (Doliocarpus elegans Eichler and 4 Davilla spp.). For Atlantic Forest occur 12 Davilla species, eight of which are endemic, including an endangered species. For the Amazon are known nine species, five of these endemic. Two other neotropical species are therefore shared by all biomes mentioned above. The other species are occurring in at least two biomes. For these three biomes produced the distribution and species richness in order to compare the results with the protected areas, aiming to discuss issues relating to the conservation of this group. Conservationists parameters as rare species, areas of endemism, areas of high species richness, conservation areas, were confronted aiming indicate priority areas for conservation of biodiversity and too this group. The results indicated three centers of diversity for this group. The main one is located in the Atlantic Forest in coastal forests of Bahia. Another center of diversity is located in central region of Cerrado, especially in the states of Goias and Bahia. The other area of diversity is located near the mouth of the Amazon River and along its course. Due to the prevailing habit of the species are lianas, these are important components of forests, of which we use this framework to discuss issues relating to the conservation of these habitats, their species and biodiversity. Full details are presented in chapters according to their biomes addressed.

No description available.

No description available.

Mycorrhizal Networks (MNs) facilitate the exchange of resources including energy, water, nutrients, and information between trees and plants in forest ecosystems. This work explored MNs as an inspiration for new market models in transactive energy networks, which similarly involve exchanges of energy and information between buildings in local communities. Specific insights from the literature on the structure and function of MNs were translated into an energy model with the aim of addressing challenges associated with the proliferation of distributed energy resources (DERs) at the grid edge and the incorporation of DER aggregations into wholesale energy markets. First, a systematic review of bio-inspired computing interventions applied to microgrids and their interactions with modern energy markets established a technical knowledge base within the context of distributed electrical systems. Second, a bio-inspired design process built on this knowledge base to yield a structural and functional blueprint for a computational mycorrhizal energy market simulation. Lastly, that computational model was implemented and simulated on a blockchain-compatible, multi-agent software platform to determine the effect that mycorrhizal strategies have on transactive energy market performance. The structural translation of a mapped ectomycorrhizal network of Douglas-firs in Oregon, USA called the 'wood-wide web' created an effective framework for the organization of a novel mycorrhizal energy market model that enabled participating buildings to redistribute percentages of their energy assets on different competing exchanges throughout a series of week-long simulations. No significant changes in functional performance –- as determined by economic, technical, and ecological metrics – were observed when the mycorrhizal results were compared to those of a baseline transactive energy community without periodic energy asset redistribution. Still, the model itself is determined to be a useful tool for further exploration of innovative, automated strategies for DER integration into modern energy market structures and electrical infrastructure in the age of Web3, especially as new science emerges to better explain trigger and feedback mechanisms for carbon exchange through MNs and how mycorrhizae adapt to changes in the environment. This dissertation concludes with a brief discussion of policy implications and an analysis applying the ecological principles of robustness, biodiversity, and altruism to the collective energy future of the human species. / Doctor of Philosophy / Beneath the forest floor, a network of fungi connects trees and plants and allows them to exchange energy and other resources. This dissertation compares this mycorrhizal network (mycorrhiza = fungus + root) to a group of solar-powered buildings generating energy and exchanging it in a local community marketplace (transactive energy markets). In the analogy, the buildings become the plants, the solar panels become the leaves, and the electrical grid represents the mycorrhizal network. Trees and plants produce their own energy through photosynthesis and then send large portions of it down to the roots, where they can trade it or send it to neighbors via the mycorrhizal network. Similarly, transactive energy markets are designed to allow buildings to sell the energy they produce on-site to neighbors, usually at better rates. This helps address a major infrastructure challenge that is arising with more people adding roof-top solar to their homes. The grid that powers our buildings is old now and it was designed to send power from a central power plant out to its edges where most homes and businesses are located. When too many homes produce solar power at the same time, there is nowhere for it to go, and it can easily overload the grid leading to fires, equipment failures, and power outages. Mycorrhizal networks solve this problem in part through local energy balancing driven by cooperative feedback patterns that have evolved over millennia to sustain forest ecosystems. This work applies scientific findings on the structure and function of mycorrhizal networks (MNs) to energy simulation methods in order to better understand the potential for building bio-inspired energy infrastructure in local communities. Specifically, the mapped structure of a MN of douglas-fir trees in Oregon, USA was adapted into a digital transactive energy market (TEM) model. This adaptation process revealed that a single building can connect to many TEMs simultaneously and that the number of connections can change over time just as symbiotic connections between organisms grow, decay, and adapt to a changing environment. The behavior of MNs in terms of when those connections are added and subtracted informed the functionality of the TEM model, which adds connections when community energy levels are high and subtracts connections when energy levels are low. The resulting 'mycorrhizal' model of the TEM was able to change how much energy each connected household traded on it by changing the number of connections (more connections mean more energy and vice versa). Though the functional performance of the mycorrhizal TEM did not change significantly from that of a typical TEM when they were the context of decentralized computer networks (blockchains) and distributed artificial intelligence. A concluding discussion addresses ways in which elements of this new model could transform energy distribution in communities and improve the resilience of local energy systems in the face of a changing climate.

Die Doktorarbeit untersucht, wie sich Mensch-Umwelt-Interaktionen am Beispiel von Abholzung und Landnutzungsänderungen im Amazonas analysieren und modellieren lassen. Die Abholzung tropischer Wälder bedroht die Stabilität artenreicher Ökosysteme, lokaler Wettergeschehen und des globalen Klimas. Drei Hauptteile erforschen das Thema mit Konzepten der theoretischen Physik und Netzwerktheorie. Der erste Teil gibt einen kritischen Überblick über Modellansätze, die Entscheidungen und menschliches Verhalten beschreiben. Agentenbasierte Netzwerkmodelle ergeben sich als vielversprechender Ansatz um sozial-ökologische Systeme zu modellieren. Der zweite Teil identifiziert Muster in satellitengestützten Landbedeckungsdaten im brasilianischen Amazonas. Basierend auf der Theorie der Markov-Ketten werden Übergangsraten zwischen verschiedenen Typen von Landbedeckung berechnet und Übergangsmatrizen für Teilgebiete mit Clusteralgorithmen verglichen. Angrenzende Teilgebiete weisen ähnliche Übergänge auf. Die identifizierten Cluster decken sich mit Erkenntnissen aus Feldstudien. Auf Grundlage der geschätzten Übergangsrate ergeben sich Projektionen für die Entwicklung der Landbedeckungsanteile. Der dritte Teil entwickelt ein agentenbasiertes Modell um zu untersuchen, unter welchen Bedingungen die Intensivierung der Viehhaltung im Amazonas die Abholzung reduzieren kann. Das Modell kombiniert ökologische, ökonomische und soziale Prozesse und modelliert Landnutzungsstrategien mit Heuristiken. Die Modellanalyse zeigt, dass eine Intensivierung die Abholzung nur dann verringert, wenn der lokale Viehmarkt saturiert. Unter anderen ökonomischen Bedingungen kann Intensivierung die Abholzung erhöhen. Die Arbeit demonstriert, dass eine Kombination von Methoden aus der Theorie komplexer Systeme mit sozialwissenschaftlichen Theorien zu einem besseren Verständnis der emergenten Dynamik sozial-ökologischer Systeme führen kann – eine Grundvoraussetzung, um solche Systeme nachhaltig zu bewirtschaften. / This thesis investigates how to model and analyze human-nature interactions using the example of deforestation and land-use change in the Brazilian Amazon. Deforestation of tropical forests threatens the stability of species-rich ecosystems, local weather patterns, and global climate. The three main parts of the thesis study different aspects of this topic using concepts from theoretical physics and network theory. The first part reviews modeling approaches to human decision making and behavior. From the review, networked agent-based models emerge as promising tools to capture the dynamics of social-ecological systems such as the land system. The second part of the thesis combines Markov-chain and cluster analyses to detect patterns in satellite-derived land-cover maps of the Brazilian Amazon. I compute transition rates between different land-cover types and apply clustering algorithms to find spatial patterns. The analysis shows that neighboring subregions undergo similar transitions and identifies clusters corresponding to findings from field surveys. Markov-chain models, parameterized with the transition rates, are used to compute land-cover projections. In the third part, I develop an agent-based model to investigate under which conditions the intensification of cattle ranching can reduce deforestation in the Amazon. The model captures stylized environmental, economic, as well as social processes, and uses heuristic decision theory to represent different land management strategies. A detailed analysis reveals that fast intensification can only lower deforestation rates if local cattle markets saturate. Under other economic conditions intensification may increase deforestation. The contributions of this thesis demonstrate that combining modeling tools from complexity science with social-science theories allow better understanding the emergent dynamics of social-ecological systems, which is a prerequisite for their sustainable management.

Research Doctorate - Doctor of Philosophy (PhD) / The original contribution of this thesis is to demonstrate the use of a generalised and parsimonious approach to building individual-based computer models of ecological systems with the objective of advancing our mechanistic understanding of these systems. Two models are presented; the first, a model of predator-prey interaction, produces the expected non-linear dynamics and illustrates the importance of the timing of variable updating and individual variation for the persistence of the populations. This model is applied to two near-exclusive, cycling predator-prey systems, those of the Canadian lynx and snowshoe hare and the Fennoscandian mustelid predators and their microtine prey. The reproduction of the patterns found in the empirical data of these systems by the model suggests that the underlying mechanism of these predator-prey systems may be more simple than is suggested by other more complex models reported in the literature. The second model describes a system similar to that of a grazing herbivore in a two-dimensional space. The emergence of complex behaviour resulting from the use of space in the model, including metapopulation-like local extinction and re-population and the effects of corridors and edge qualities on the species are demonstrated. The inclusion of a graphical display of the two-dimensional space in the computer interface to the model reveals important details of system behaviour not evident in the population means, including herding behaviour. The latter is dependent on herbivore mobility and the re-growth of resources in an heterogeneous environment, and emerges in the absence of social behaviour. The problem of detecting herding behaviour automatically is addressed, including the development of qualitative and quantitative definitions of herding in the model.

The increasing demand for food and fiber, the need for climate change mitigation and adaptation as well as for environmental protection impose severe challenges on land systems worldwide. Solutions to support the transformation towards a sustainable development of land systems are needed. One response to the multiple challenges is the introduction of policy options aimed at steering land use activities towards a bundle of societal goals. However, it is difficult to empirically foresee the effectiveness and unintended consequences of policy options prior to their deployment. A second response is environmental education because human consumption behavior, among other factors, strongly influences natural ecosystems. However, it is a non-trivial task to develop effective communication strategies for complex topics such as sustainable land management. In both cases, modeling can help to overcome the different obstacles along the way. In this thesis, dynamic process-based social-ecological models at the individual scale are developed and analyzed to study effectiveness and unintended side effects of policy options, which promote agricultural management strategies and were intentionally designed to cope with multiple societal challenges. Two case studies of political intervention are investigated: the promotion of perennial woody crops in European agricultural landscapes for a sustainable bioeconomy and governmental supplementary feeding programs to cope with climate risks in pastoral systems in drylands. These two case studies are complemented by the development of a serious online game on sustainable land management in general that bridges the gap between land use modeling and environmental education. Simulation results of this thesis provide insights into (i) the performance of the politically promoted agricultural management strategies in meeting various intended goals such as poverty alleviation or the maintenance of biodiversity and ecosystem services, (ii) the emergence of unintended (environmental and social) side effects such as land use conflicts, land degradation or cost explosion and (iii) the mitigation of such side effects by appropriately adjusting the design of the policy options. These insights are enabled by representing temporal as well as spatial variability in the developed models. Furthermore, different mechanistic approaches of transferability analyses based on stylized landscapes are developed and applied. They enable to check whether and in what respect policy impacts actually differ substantially between regional contexts, to identify what regional factors steer the impact and to derive indicators for grouping regions of similar policy impacts. Finally, based on a conducted survey-based evaluation and experiences from various applications, the value of the developed serious game for environmental education is revealed and discussed.Altogether, this thesis contributes to model-based decision support for steering transformation towards the sustainable development of land systems in an appropriate way. This is done by developing appropriate social-ecological modeling approaches, by performing specific policy impact analyses in two transformative agricultural systems using these models and by providing a model-based communication tool for environmental education.

La recherche porte sur les patrons de distribution longitudinale (amont-aval) et transversale (rive nord - rive sud) des communautés de crustacés planctoniques qui ont été analysés le long du fleuve Saint-Laurent entre le lac Saint-François et la zone de transition estuarienne, à deux hydropériodes en mai (crue) et en août (étiage). Les données zooplanctoniques et environnementales ont été récoltées à 52 stations réparties sur 16 transects transversaux en 2006. Au chapitre 1, nous présentons les principaux modèles écosystémiques en rivière, une synthèse des facteurs influençant le zooplancton en rivières et les objectifs et hypothèses de recherche. Au chapitre 2, nous décrivons la structure des communautés de zooplancton dans trois zones biogéographiques du fleuve et 6 habitats longitudinaux, ainsi que les relations entre la structure du zooplancton et la distribution spatiale des masses d’eau et les variables environnementales. Au chapitre 3, nous réalisons une partition de la variation des variables spatiales AEM (basées sur la distribution des masses d’eau) et des variables environnementales pour évaluer quelle part de la variation du zooplancton est expliquée par les processus hydrologiques (variables AEM) et les conditions locales (facteurs environnementaux). Le gradient salinité-conductivité relié à la discontinuité fleuve-estuaire a déterminé la distribution à grande échelle du zooplancton. Dans les zones fluviales, la distribution du zooplancton est davantage influencée par la distribution des masses d’eau que par les facteurs environnementaux locaux. La distribution des masses d’eau explique une plus grande partie de la variation dans la distribution du zooplancton en août qu’en mai. / The research aims to determine the distribution patterns of crustacean plankton along the longitudinal (west-east) and transversal (north shore - south shore) axes of the St. Lawrence River between Lake Saint-François and the estuarine transition zone, during two hydroperiods in May (high discharge) and August (low discharge). The zooplankton samples and the environmental data were collected at 52 stations distributed along 16 transversal transects in 2006. In chapter 1, we present the theoretical concepts of river ecosystem models, and a synthesis on the generative processes driving zooplankton spatial patterns in rivers. We also present our research objectives and hypotheses. In chapter 2, we describe spatial patterns of the zooplankton community structure in three biogeographic zones of the St. Lawrence and 6 longitudinal habitats, together with the relationships between zooplankton spatial structure and water masses spatial distribution and environmental characteristics. In chapter 3, we perform a variation partitioning procedure on spatial variables AEM (based on water masses spatial distribution) and environmental variables in order to assess how much of the zooplankton variation is explained by hydrological processes (AEM variables) and local conditions (environmental factors). The salinity-conductivity gradient related to the fluvial-estuary discontinuity determines the large-scale spatial patterns of the crustacean zooplankton. In the fluvial zones, the zooplankton distribution patterns are more influenced by the water masses spatial structure than by local environmental factors. The spatial distribution of the water masses explained more of the spatial structure of zooplankton communities in August than in May.

For the west coast of North America, from northern California to southern Washington, a habitat suitability prediction framework was developed to support wave energy device siting. Concern that wave energy devices may impact the seafloor and benthos has renewed research interest in the distribution of marine benthic invertebrates and factors influencing their distribution. A Bayesian belief network approach was employed for learning species-habitat associations for Rhabdus rectius, a tusk-shaped marine infaunal Mollusk. Environmental variables describing surficial geology and water depth were found to be most influential to the distribution of R. rectius. Water property variables, such as temperature and salinity, were less influential as distribution predictors. Species-habitat associations were used to predict habitat suitability probabilities for R. rectius, which were then mapped over an area of interest along the south-central Oregon coast. Habitat suitability prediction models tested well against data withheld for crossvalidation supporting our conclusion that Bayesian learning extracts useful information available in very small, incomplete data sets and identifies which variables drive habitat suitability for R. rectius. Additionally, Bayesian belief networks are easily updated with new information, quantitative or qualitative, which provides a flexible mechanism for multiple scenario analyses. The prediction framework presented here is a practical tool informing marine spatial planning assessment through visualization of habitat suitability. / Graduation date: 2012

La recherche porte sur les patrons de distribution longitudinale (amont-aval) et transversale (rive nord - rive sud) des communautés de crustacés planctoniques qui ont été analysés le long du fleuve Saint-Laurent entre le lac Saint-François et la zone de transition estuarienne, à deux hydropériodes en mai (crue) et en août (étiage). Les données zooplanctoniques et environnementales ont été récoltées à 52 stations réparties sur 16 transects transversaux en 2006. Au chapitre 1, nous présentons les principaux modèles écosystémiques en rivière, une synthèse des facteurs influençant le zooplancton en rivières et les objectifs et hypothèses de recherche. Au chapitre 2, nous décrivons la structure des communautés de zooplancton dans trois zones biogéographiques du fleuve et 6 habitats longitudinaux, ainsi que les relations entre la structure du zooplancton et la distribution spatiale des masses d’eau et les variables environnementales. Au chapitre 3, nous réalisons une partition de la variation des variables spatiales AEM (basées sur la distribution des masses d’eau) et des variables environnementales pour évaluer quelle part de la variation du zooplancton est expliquée par les processus hydrologiques (variables AEM) et les conditions locales (facteurs environnementaux). Le gradient salinité-conductivité relié à la discontinuité fleuve-estuaire a déterminé la distribution à grande échelle du zooplancton. Dans les zones fluviales, la distribution du zooplancton est davantage influencée par la distribution des masses d’eau que par les facteurs environnementaux locaux. La distribution des masses d’eau explique une plus grande partie de la variation dans la distribution du zooplancton en août qu’en mai. / The research aims to determine the distribution patterns of crustacean plankton along the longitudinal (west-east) and transversal (north shore - south shore) axes of the St. Lawrence River between Lake Saint-François and the estuarine transition zone, during two hydroperiods in May (high discharge) and August (low discharge). The zooplankton samples and the environmental data were collected at 52 stations distributed along 16 transversal transects in 2006. In chapter 1, we present the theoretical concepts of river ecosystem models, and a synthesis on the generative processes driving zooplankton spatial patterns in rivers. We also present our research objectives and hypotheses. In chapter 2, we describe spatial patterns of the zooplankton community structure in three biogeographic zones of the St. Lawrence and 6 longitudinal habitats, together with the relationships between zooplankton spatial structure and water masses spatial distribution and environmental characteristics. In chapter 3, we perform a variation partitioning procedure on spatial variables AEM (based on water masses spatial distribution) and environmental variables in order to assess how much of the zooplankton variation is explained by hydrological processes (AEM variables) and local conditions (environmental factors). The salinity-conductivity gradient related to the fluvial-estuary discontinuity determines the large-scale spatial patterns of the crustacean zooplankton. In the fluvial zones, the zooplankton distribution patterns are more influenced by the water masses spatial structure than by local environmental factors. The spatial distribution of the water masses explained more of the spatial structure of zooplankton communities in August than in May.