Le diagnostic et la prise en charge des infections ostéo-articulaires (IOA) sont souvent complexes occasionnant une perte osseuse irréversible. La variabilité intra et inter-patient en terme de présentation clinique rend impossible le recours à une description systématique ou à une analyse statistique pour le diagnostic et l'étude de cette pathologie. Le développement d'IOA résulte d'interactions complexes entre les mécanismes cellulaires et moléculaires du tissu osseux et les bactéries. L'objectif de cette thèse est de modéliser l'IOA afin de simuler le comportement du système suite à des interactions au niveau cellulaire et moléculaire en utilisant l'approche de modélisation à base d'agents. Nous avons utilisé une méthode basée sur l'analyse bibliographique pour extraire les caractéristiques du modèle et les utiliser pour deux aspects. Le premier consiste en l'élaboration de la structure du modèle en identifiant les agents et les interactions, et le deuxième concerne l'estimation quantitative des différents paramètres du modèle. La réponse du système BJI aux différentes tailles d’inoculum bactérien a été simulée par la variation de différents paramètres. L'évolution des agents simulés a ensuite été analysée en utilisant une modélisant par des systèmes dynamiques non linéaires et une méthodologie "Datadriven", grâce auxquelles nous avons décrit le système d'IOA et identifié des relations plausibles entre les agents. Le modèle a réussi à présenter la dynamique des bactéries, des cellules immunitaires innées et des cellules osseuses au cours de la première étape de l'IOA et pour différentes tailles d'inoculum bactérien. La simulation a mis en évidence les conséquences sur le tissu osseux résultant du processus de remodelage osseux au cours de l'IOA. Ces résultats peuvent être considérés comme une base pour une analyse plus approfondie et pour la proposition de différentes hypothèses et scénarios de simulation qui pourraient être étudiés dans ce laboratoire virtuel. / Bone and joint infections are one of the most challenging bone pathologies that associated with irreversible bone loss and long costly treatment. The high intra and inter patient's variability in terms of clinical presentation makes it impossible to rely on the systematic description or classical statistical analysis for its diagnosis or studying. The development of BJI encompasses a complex interplay between the cellular and molecular mechanisms of the host bone tissue and the infecting bacteria. The objective of this thesis is to provide a novel computational modeling framework that simulates the behavior resulting from the interactions on the cellular and molecular levels to explore the BJI dynamics qualitatively and comprehensively, using an agent-based modeling approach. We relied on a meta-analysis-like method to extract the quantitative and qualitative data from the literature and used it for two aspects. First, elaborating the structure of the model by identifying the agents and the interactions, and second estimating quantitatively the different parameters of the model. The BJI system’s response to different microbial inoculum sizes was simulated with respect to the variation of several critical parameters. The simulation output data was then analyzed using a data-driven methodology and system dynamics approach, through which we summarized the BJI complex system and identified plausible relationships between the agents using differential equations. The BJI model succeeded in imitating the dynamics of bacteria, the innate immune cells, and the bone cells during the first stage of BJI and for different inoculum size in a compatible way. The simulation displayed the damage in bone tissue as a result of the variation in bone remodeling process during BJI. These findings can be considered as a foundation for further analysis and for the proposition of different hypotheses and simulation scenarios that could be investigated through this BJI model as a virtual lab.

The degradation of natural resources as a result of consumption to support the economic growth of humans society represents one of the greatest sustainability challenges. In order to allow economic growth to continue in a sustainable way, it has to be decoupled from the consumption and destruction of natural resources. This thesis focuses on an innovative manufacturing technology called additive manufacturing (AM) and its potential to become a more efficient and cleaner manufacturing alternative. The thesis also investigates the benefits of accessing the technology through the result-oriented Product-Service Systems (PSS) approach. The outcome of the study is the quantification of raw materials and energy consumption. The scope of study is the application of AM in the scale model kit industry. The methods used are the life cycle inventory study and the system dynamics modeling. The result shows that AM has higher efficiency in terms of raw material usage, however it also has higher energy consumption in comparison to the more traditional manufacturing techniques. The result-oriented PSS approach is shown to be able to reduce the amount of manufacturing equipment needed, thus reducing the energy and raw materials used to produce the equipment, but does not completely decouple economic growth from the consumption of natural resources.

Pore forming toxins are known for their ability to efficiently form transmembrane pores which eventually leads to cell lysis. PFTs have potential applications in devel-oping novel drug and gene delivery strategies. Although structural aspects of many pore forming toxins have been studied, very little is known about the dynamics and subsequent rupture mechanisms. In the first part of the thesis, a combined experimental and modeling study to understand the lytic action of Cytolysin A (ClyA) toxins on red blood cells (RBCs) has been presented. Lysis experiments are carried out on a 1% suspension of RBCs for different initial toxin concentrations ranging from 100 – 500 ng/ml and the extent of lysis is monitored spectrophotometrically. Using a mean field approach, we propose a non – equilibrium adsorption-reaction model to quantify the rate of pore formation on the cell surface. By analysing the model in a pre-lysis regime, the number of pores per RBC to initiate rupture was found to lie between 400 and 800. The time constants for pore formation are estimated to lie between 1-25 s and monomer conformation time scales were found to be 2-4 times greater than the oligomerization times. Using this model, we are able to predict the extent of cell lysis as a function of the initial toxin concentration. Various kinetic models for oligomerization mechanism have been explored. Irreversible sequential kinetic model has the best agreement with the available experimental data. Subsequent to the mean field approach, a population balance model was also formulated. The mechanics of cell rupture due to pore formation is poorly understood. Efforts to address this issue are concerned with understanding the changes in the membrane mechanical properties such as the modulus and tension in the presence of pores. The second part of the thesis is concerned with using atomic force microscopy to measure the mechanical properties of cells. We explore the possibility of employing tapping mode AFM (TM-AFM) to obtain the elastic modulus of soft samples. The dynamics of TM-AFM is modelled to predict the elastic modulus of soft samples, and predict optimal cantilever stiffness for soft biological samples. From experiments using TM-AFM on Nylon-6,6 the elastic modulus is predicted to lie between 2 and 5 GPa. For materials having elastic moduli in the range of 1– 20 GPa, the cantilever stiffness from simulations is found to lie in the range of 1 – 50 N/m. For soft biological samples, whose elastic moduli are in the range of 10-1000 kPa, a narrower range of cantilever stiffness (0.1 – 0.6 N/m), should be used.

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<div>The security, resilience and sustainability of water supply in urban areas are of major concern in cities around the world. Their dynamics and long-term trajectories result from external change processes, as well as adaptive and maladaptive management practices aiming to secure urban livelihoods. This dissertation examines the dynamics of urban water systems from a social-ecological-technical systems perspective, in which infrastructure and institutions mediate the human-water-ecosystem relationship. </div><div><br></div><div>The three concepts of security, resilience and sustainability are often used interchangeably, making the achievement of goals addressing such challenges somewhat elusive. This becomes evident in the international policy arena, with the UN Sustainable Development Goals being the most prominent example, in which aspirations for achieving the different goals for different sectors lead to conflicting objectives. Similarly, the scientific literature remains inconclusive on characterizations and quantifiable metrics. These and other urban water challenges facing the global urban community are discussed, and research questions and objectives are introduced in Section 1. </div><div><br></div><div>In Section 2, I suggest distinct definitions of urban water security, resilience and sustainability: Security refers to the state of system functioning regarding water services; resilience refers to ability to absorb shocks, to adapt and transform, and therefore describes the dynamic, short- to medium-term system behavior in response to shocks and disturbances; sustainability aims to balance the needs in terms of ecology and society (humans and the economic systems they build) of today without compromising the ability to meet the needs of future generations. Therefore, sustainability refers to current and long-term impacts on nature and society of maintaining system functions, and therefore affects system trajectories. I suggest that sustainability should include not only local effects, but consider impacts across scales and sectors. I propose methods for the quantification of urban water security, resilience and sustainability, an approach for modeling dynamic water system behavior, as well as an integrated framework combining the three dimensions for a holistic assessment of urban water supply systems. The framework integrates natural, human and engineered system components (“Capital Portfolio Approach”) and is applied to a range of case study cities selected from a broad range of hydro-climatic and socio-economic regions on four continents. Data on urban water infrastructure and services were collected from utilities in two cities (Amman, Jordan; Ulaanbaatar, Mongolia), key stakeholder interviews and a household survey conducted in Amman. Publicly available, empirical utility data and globally accessible datasets were used to support these and additional case studies. </div><div><br></div><div>The data show that community adaptation significantly contributes to urban water security and resilience, but the ability to adapt is highly heterogeneous across and within cities, leading to large inequality of water security. In cities with high levels of water security and resilience, adaptive capacity remains latent (inactive), while water-insecure cities rely on community adaptation for the self-provision of services. The framework is applied for assessing individual urban water systems, as well as for cross-city comparison for different types of cities. Results show that cities fall along a continuous gradient, ranging from water insecure and non-resilient cities with inadequate service provision prone to failure in response to extant shock regimes, to water secure and resilient systems with high levels of services and immediate recovery after shocks. Although limited by diverse constraints, the analyses show that urban water security and resilience tend to co-evolve, whereas sustainability, which considers local and global sustainable management, shows highly variable results across cities. I propose that the management of urban water systems should maintain a balance of security, resilience and sustainability.</div><div><br></div><div>The focus in Section 3 is on intra-city patterns and mechanisms, which contribute to urban water security, resilience and sustainability. In spite of engineering design and planning, and against common expectations, intra-city patterns emerge from self-organizing processes similar to those found in nature. These are related to growth processes following the principle of preferential attachment and functional efficiency considerations, which lead to Pareto power-law probability distributions characteristic of scale-free-like structures. Results presented here show that such structures are also present in urban water distribution and sanitary sewer networks, and how deviation from such specific patterns can result in vulnerability towards cascading failures. In addition, unbounded growth, unmanaged demand and unregulated water markets can lead to large inequality, which increases failure vulnerability. </div><div><br></div><div>The introduction of infrastructure and institutions for providing urban water services intercedes and mediates the human-water relationship. Complexity of infrastructural and institutional setups, growth patterns, management strategies and practices result in different levels of disconnects between citizens and the ecosystems providing freshwater resources. “Invisibility” of services to citizens results from maximized water system performance. It can lead to a lack of awareness about the effort and underlying infrastructure and institutions that operate for delivering services. Data for the seven cities illustrate different portfolios of complexity, invisibility and disconnection. Empirical data gathered in a household survey and key stakeholder interviews in Amman reveals that a misalignment of stakeholder perceptions resulting from the lack of information flow between citizens and urban managers can be misguiding and can constrain the decision-making space. Unsustainable practices are fostered by invisibility and disconnection and exacerbate the threats to urban water security and resilience. Such challenges are investigated in the context of urban water system traps: the poverty and the rigidity trap. Results indicate that urban water poverty is associated with local unsustainability, while rigidity traps combined with urban demand growth gravitate towards global unsustainability. </div><div><br></div><div>Returning to the city-level in Section 4, I investigate urban water system evolution. The question how the trajectories of urban water security, resilience and sustainability can be managed is examined using insights from hydrological and social-ecological systems research. I propose an “Urban Budyko Landscape”, which compares urban water supply systems to hydrological catchments and highlights the different roles of supply- and demand-management of water and water-related urban services. A global assessment of 38 cities around the world puts the seven case studies in perspective, emphasizing the relevance of the proposed framework and the representative, archetypal character of the selected case studies. </div><div><br></div><div>Furthermore, I examine how managing for the different dimensions of the CPA (capital availability, robustness, risk and sustainable management) determines the trajectories of urban water systems. This is done by integrating the CPA with the components of social-ecological system resilience, which explain how control of the different components determines the movement of systems through states of security and resilience in a stability landscape. Finally, potential feedbacks resulting from the global environment are investigated with respect to the role that globally sustainable local and regional water management can play in determining the trajectories of urban water systems. These assessments demonstrate how the impact of supply-oriented strategies reach beyond local, regional and into global boundaries for meeting a growing urban demand, and come at the cost of global sustainability and communities elsewhere.</div><div><br></div><div>Despite stark differences between individual cities and large heterogeneities within cities, convergent trends and patterns emerge across systems and are revealed through application of the proposed concepts and frameworks. The implications of these findings are discussed in Section 5, and are summarized here as follows: </div><div>1) The management of urban water systems needs to move beyond the security and resilience paradigms, which focus on current system functioning and short-term behavior. Sustaining a growing global, urban population will require addressing the long-term, cross-scale and inter-sector impacts of achieving and maintaining urban water security and resilience. </div><div>2) Emergent spatial patterns are driven by optimization for the objective functions. Avoiding traps, cascading failure, extreme inequality and maintaining global urban livability requires a balance of supply- and demand-management, consideration of system complexity, size and reach (i.e., footprint), as well as internal structures and management strategies (connectedness and modularity).</div><div>3) Urban water security and resilience are threatened by long-term decline, which necessitates the transformation to urban sustainability. The key to sustainability lies in experimentation, modularization and the incorporation of interdependencies across scales, systems and sectors.</div><div><br></div>

Diese Dissertation beschäftigt sich mit der Evaluation von Sprachpolitiken mit Hilfe von Sprachdynamik Modellen. Da sprachliche Diversität ein zentrales Merkmal moderner Gesellschaften darstellt, müssen Staaten und Administrationen Sprachpolitiken sorgfältig gestalten und evaluieren. Mögliche Effekte, Nutzen und Kosten von Politiken müssen bewertet und gegeneinander abgewogen werden. Eine wichtige Eigenschaft von Sprachpolitiken ist dabei, dass sich die Anzahl derer, die von ihnen profitieren, sowie deren Kosten über die Zeit stark verändern können. Um dies zu berücksichtigen, präsentiert die Dissertation eine Kombination aus klassischen Politikanalyse Werkzeugen und neuen Sprachdynamik Modellen. Im Gegensatz zu bereits existierenden Modellen, können in den neu entwickelten Modellen Parameter aus empirischen Daten geschätzt werden. Dies ist eine Voraussetzung, um langfristige Effekte von Politiken realistisch abbilden zu können. Die Dissertation besteht aus vier eigenständigen Aufsätzen. Im ersten Aufsatz wird mit einem abstrakten Modell gezeigt, dass es für einen Staat optimal sein kann die Minderheitensprache in Form von Bilingualität am Leben zu erhalten. In den folgenden beiden Aufsätzen werden realistischere Modelle entwickelt und damit zwei empirische Fälle analysiert. Im letzten Aufsatz werden Erweiterungen der vorherigen Modelle auf den Fall multipler Minderheitensprachen vorgestellt. / This thesis deals with language policy evaluation from a language dynamics modeling perspective. As linguistic diversity is an essential feature of most modern societies, states and administrations have to thoroughly design and analyze language policies. Potential effects, benefits and costs have to be assessed and weighted against one another. A pivotal characteristic of language policies is that the numbers of their beneficiaries and costs can change dramatically over time. To account for these changes, the thesis proposes a combination of traditional policy evaluation techniques with well designed language dynamics models. In contrast to previous models in the literature, the thesis proposes and analyzes models based on parameters obtainable from empirical data. It is argued that this is a prerequisite to analyze the long term effects of policies in a realistic fashion. This thesis consists of four self-contained essays. In the first essay we show with the help of an abstract model that it can be optimal for the state to keep a minority language alive in the form of bilingualism. In the next two essays more realistic models are developed and applied to the empirical cases. In the last essay extensions of the previous models to the case of several minority languages are presented.

It appears to be unanimous that alien species in island environments tend to cause considerably more negative than positive impacts. To assess the potential level of threat aliens may pose to the native environment, understanding a species’ population structure and dynamics is of ultimate importance. Assessing both impacts and consequences of management interventions to alien species is likewise only possible through the comprehension of its population structure and dynamics. This can be achieved by estimating the number of individuals in the study site, as well as other population parameters through time, applying population models such as capture-recapture to the collected datasets. Nonetheless, alien species that have low capture rates, such as small mammals, might present a considerable obstacle for conservation, as available capturerecapture models need a relatively large dataset to precisely and accurately estimate population parameters. To improve accuracy and precision of estimates that use sparse datasets, the present study developed an integrated concurrent marking-observation capture-recapture model (C-MOM). The model proposed here, contrary to the commonly available mark-recapture and mark-resight models, allows for two different datasets (i.e. a capture-recapture and a population count) to be integrated, as well as for marking and observation (recapture) data to be collected simultaneously. While few models can integrate different datasets, no model is known to allow for concomitant capture-markobservation activities. To assess the performance of the C-MOM when estimating population parameters for sparse datasets, a virtual ecology study was carried out. The population dynamics of a small rodent, the rock cavy (Kerodon rupestris), as well as capture-recapture and population count datasets, were simulated under different scenarios. The sampled datasets were then analyzed by the C-MOM, and by two other established statistical models: a classical mark recapture (CMR) (based on the Jolly-Seber model), and a zero-truncated Poisson log-normal mixed effects (ZPNE), the only integrated mark-resight model that allows for recapture sampling with replacement. Estimates of population parameters provided by the three models were then compared in terms of bias, precision and accuracy. C-MOM and ZPNE models were afterwards applied to real data collected on a rock cavy colony in the island of Fernando de Noronha. The estimated parameters were used to extrapolate the number of individuals in the rock cavy colony to the whole population in the island. Subsequently, these results were used to develop a risk assessment for the species by modelling historical and management scenarios, simulating both the establishment of the species in the island, and the consequences of different management interventions applied to it. The virtual ecology study showed that, in comparison to the CMR and the ZPNE, the C-MOM presented improved accuracy without overestimating the precision of population parameter’s estimates. The last also presented reduced amplitude of the calculated credible interval at 95% when applied to real data in comparison to the ZPNE. While the extrapolation of C-MOM estimates suggests that the rock cavy population in Fernando de Noronha is 6,652 ± 1,587, ZPNE estimates are of 5,854 ± 3,269 individuals. In the risk assessment, historical simulation models demonstrated that even though different combinations of uncertainty in reproductive parameters of the rock cavy might be possible for the species, these did not interfere significantly in either establishment or spread of the rock cavy population in the island. Moreover, historical yearly mortality has most likely been under 30%. Regarding the species’ management simulations, the most effective management interventions to achieve population extinction were spaying and neutering of both sexes, although harvest effort presented the highest influence on this populations’ extirpation. Nonetheless, the relative influence of female and both sexes’ based interventions did not differ significantly regarding the frequency of extinction of stochastic replicates’. Moreover, none of the management interventions guaranteed the population extinction within the time span and harvest effort proposed for the management program. Neutering of both sexes was most inversely influential on time to extinction of this population, followed by removal of both sexes. Briefly, the C-MOM has proven to be a resourceful and precise model to estimate population parameters when low capture rates result in sparse datasets. Moreover, the rock cavy is well established in the island and likely at carrying capacity. In general, the risk assessment showed that the management interventions in the time span and harvest effort simulated in the present study were ineffective to extinguish the rock cavy population in Fernando de Noronha. Considering this, as well as the importance of investigating other vital factors to decide in favour of or contrary to the management of this species, it is recommended that both an impact assessment of the rock cavy and a cost-effectiveness analysis of the management interventions should be performed to complement the current study.:Acknowledgement III Abstract IV Zusammenfassung VI Resumen IX Table of Contents XII List of Tables and Figures XIV List of Abbreviations XIX 1. Introduction 1 1.1. Invasive alien species and their consequences 1 1.2. Population dynamics analysis 2 Capture-recapture models 3 Observation models 4 Integrated population models 5 Software 7 Model analysis 8 1.3. Fernando de Noronha and the rock cavy 10 1.4. Objectives 12 Overall Objectives 12 Specific Objectives 13 2. Study Framework 15 3. Methods 19 3.1. Study area 19 3.2. Study case species 21 3.3. Research Steps 24 RESEARCH STEP I: Comparing the C-MOM to established models – does this concurrent marking-observation model produces accurate estimates of population parameters for sparse datasets? 24 RESEARCH STEP II: C-MOM application to a real case study 40 RESEARCH STEP III: The rock cavy population in Fernando de Noronha 45 RESEARCH STEP IV: The colonization and eradication of the rock cavy in Fernando de Noronha 47 4. Results 63 4.1. RESEARCH STEP I: Comparing the C-MOM to established models – does this concurrent marking-observation model produces accurate estimates of population parameters for sparse datasets? 63 4.2. RESEARCH STEP II: C-MOM application to a real case study 72 4.3. RESEARCH STEP III: The rock cavy population in Fernando de Noronha 73 4.4. RESEARCH STEP IV: The colonization and eradication of the rock cavy in Fernando de Noronha 74 Sensitivity analysis 74 Simulation experiments 80 5. Discussion 83 5.1. Bias, precision and accuracy of population dynamic models for sparse datasets 85 Simulated data 85 Study case 90 5.2. Advantages and disadvantages of the C-MOM approach 93 5.3. Development and applications of the integrated models and the C-MOM 96 5.4. The reversed use of the PVA software Vortex to simulate AS and IAS populations’ extinction 97 5.5. Status of the rock cavy population in the island of Fernando de Noronha 100 The colonization of the rock cavy in Fernando de Noronha 101 Management of the rock cavy in Fernando de Noronha 104 Study case limitations and future researches 112 6. Conclusion 116 References 118 Appendices 124 APPENDIX I – Assessment of biological invasions 124 APPENDIX II – Population dynamics simulation and dataset sampling 125 APPENDIX III – CMR and C-MOM model codes in R 134 APPENDIX IV – ZPNE model code in R 138 APPENDIX V – C-MOM model used for real datasets 143 APPENDIX VI – Rock cavy colony sizes and number of individuals in Fernando de Noronha 145 APPENDIX VII – Parameter’s ranking of C-MOM, CMR and ZPNE models 148 APPENDIX VIII – Bias, precision and accuracy table 149

<p>Uncertainty analysis is of great use both for calculating outputs that are more akin to real<br> flight, and for optimization to more robust shapes. However, implementation of uncertainty<br> has been a longstanding challenge in the field of aerodynamics due to the computational cost<br> of simulations. Geometric uncertainty in particular is often left unexplored in favor of uncer-<br> tainties in freestream parameters, turbulence models, or computational error. Therefore, this<br> work proposes a method of geometric uncertainty analysis for aerodynamic shapes that miti-<br> gates the barriers to its feasible computation. The process takes a two- or three-dimensional<br> shape and utilizes a combination of multifidelity meshes and Gaussian process regression<br> (GPR) surrogates in a multifidelity Monte Carlo (MFMC) algorithm. Multifidelity meshes<br> allow for finer sampling with a given budget, making the surrogates more accurate. GPR<br> surrogates are made practical to use by parameterizing major factors in geometric uncer-<br> tainty with only four variables in 2-D and five in 3-D. In both cases, two parameters control<br> the heights of steps that occur on the top and bottom of airfoils where leading and trailing<br> edge devices are attached. Two more parameters control the height and length of waves<br> that can occur in an ideally smooth shape during manufacturing. A fifth parameter controls<br> the depth of span-wise skin buckling waves along a 3-D wing. Parameters are defined to<br> be uniformly distributed with a maximum size of 0.4 mm and 0.15 mm for steps and waves<br> to remain within common manufacturing tolerances. The analysis chain is demonstrated<br> with two test cases. The first, the RAE2822 airfoil, uses transonic freestream parameters<br> set by the ADODG Benchmark Case 2. The results show a mean drag of nearly 10 counts<br> above the deterministic case with fixed lift, and a 2 count increase for a fixed angle of attack<br> version of the case. Each case also has small variations in lift and angle of attack of about<br> 0.5 counts and 0.08◦, respectively. Variances for each of the three tracked outputs show that<br> more variability is possible, and even likely. The ONERA M6 transonic wing, popular due<br> to the extensive experimental data available for computational validation, is the second test<br> case. Variation is found to be less substantial here, with a mean drag increase of 0.5 counts,<br> and a mean lift increase of 0.1 counts. Furthermore, the MFMC algorithm enables accurate<br> results with only a few hours of wall time in addition to GPR training. </p>

<p dir="ltr">Global forest ecosystems provide essential ecosystem services that contribute to water and climate regulation, food production, recreation, and raw materials. They also serve as crucial habitats for numerous terrestrial species of amphibians, birds, and mammals worldwide. However, recent decades have witnessed unprecedented changes in forest ecosystems due to climate change, shifts in species distribution patterns, increased planted forest areas, and various disturbances such as forest fires, insect infestations, and urbanization. These changes can have far-reaching impacts on ecological networks, human well-being, and the well-being of global forest ecosystems. To address these challenges, I present four studies to quantify forest dynamics through mapping, classification, and projection, using artificial intelligence tools in combination with a vast amount of training data. (I) I present a spatially continuous map of planted forest distribution across East Asia, produced by integrating multiple sources of planted and natural forest data. I found that China contributed 87% of the total planted forest areas in East Asia, most of which are located in the lowland tropical/subtropical regions and Sichuan Basin. I also estimated the dominant genus in each planted forest location. (II) I used continent-wide forest inventory data to compare the range shifts of forest types and their constituent tree species in North America in the past 50 years. I found that forest types shifted more than three times as fast as the average of their constituent tree species. This marked difference was attributable to a predominant positive covariance between tree species ranges and the change of species relative abundance. (III) Based on individual-level field surveys of trees and breeding birds across North America, I characterized New World wood-warbler (<i>Parulidae</i>) species richness and its potential drivers. I identified forest type as the most powerful predictor of New World wood-warbler species richness, which adds valuable evidence to the ongoing physiognomy versus composition debate among ornithologists. (IV) In the appendix, I utilized continent-wide forest inventory data from North America and South America and the combination of supervised and unsupervised machine learning algorithms to produce the first data-driven map of forest types in the Americas. I revealed the distribution of forest types, which are useful for cost-effective forest and biodiversity management and planning. Taken together, these studies provide insight into the dynamics of forest ecosystems at a large geographic scale and have implications for effective decision-making in conservation, management, and global restoration programs in the midst of ongoing global change.</p>