Mapping the bacterial metabolic niche space

The rise in the availability of bacterial genomes defines a need for synthesis: abstracting from individual taxa, to see larger patterns of bacterial lifestyles across systems. A key concept for such synthesis in ecology is the niche, the set of capabilities that enables a population’s persistence and defines its impact on the environment. The set of possible niches forms the niche space, a conceptual space delineating ways in which persistence in a system is possible. Here we use manifold learning to map the space of metabolic networks representing thousands of bacterial genera. The results suggest a metabolic niche space comprising a collection of discrete clusters and branching manifolds, which constitute strategies spanning life in different habitats and hosts. We further demonstrate that communities from similar ecosystem types map to characteristic regions of this functional coordinate system, permitting coarse-graining of microbiomes in terms of ecological niches that may be filled

Urban metabolism and land use modeling for urban designers and planners: A land use model for the Integrated Urban Metabolism Analysis Tool

Predicting the resource consumption in the built environment and its associated environmental consequences (urban metabolism analysis) is one of the core challenges facing policy-makers and planners seeking to increase the sustainability of urban areas. There is a critical need for a single integrated framework to analyze the consequences of urban growth and eventually predict the impacts of sustainable policies on the urbanscape. This dissertation presents the development of an Integrated Urban Metabolism Analysis Tool (IUMAT) – an analytical framework that simulates urban metabolism by integrating urban subsystems in a single comprehensive computational environment. It reviews the existing literature on urban sustainability, urban metabolism, as well as introducing the general framework for IUMAT. IUMAT uses three separate models for quantifying environmental impacts of land-use transition, consumption of resources, and transportation. This work outlines the development of IUMAT Land-Use Model that uses Remote Sensing, GIS, and Artificial Neural Networks (ANNs) to predict land use change patterns. By using Density-Based Spatial Clustering and normal equations, this dissertation introduces a method for generating building-form variables from Light Detection and Ranging (LIDAR) data, which can be used as a new determinant factor in land-use change modeling. The proposed Land-use Model, within IUMAT or other analytical models, can be useful to local planning officials in understanding the complexity of land-use change and developing enhanced land-use policies

Predicting Marine Teleost Responses to Ocean Warming and Pollution

Ocean warming and pollution are two detrimental anthropogenic factors causing rapid marine ecosystem degradation recorded in the past decades. These factors alter the marine environment intolerable for many marine species, forcing them to either adapt or shift their contemporary habitat ranges to reduce the extinction risk embedded with environmental degradation. Estimating marine species’ habitat range shifts, and their potential for developing adaptive mechanisms are critical for ecosystem conservation and management, human health risk assessment, and climate change vulnerability assessments. Given that, for the first chapter of this thesis, we focused on developing a species distribution model (SDM) integrating marine species temperature-sensitive physiological factor, into a bioclimate model to better predict future habitat patterns with warming. We integrated two omics datasets for the second and third chapters to determine the potential transcriptomic and epigenomic mechanisms underlying marine species’ evolved resistance to extreme pollution. We tested the new model to predict the future (the 2050s and 2080s) habitat ranges of the highly eurythermal intertidal minnow, Atlantic killifish (Fundulus heteroclitus), as a best-case scenario. Our SDM predicts complex and diverse habitat patterns for Atlantic killifish, including habitat fragmentation, migration between adjacent populations, and range contractions but no poleward range expansion. Our model predictions are quite unique compared to existing SDMs, mainly with the integration of thermal physiology into the model. The molecular analysis in the second and third chapters posited the repeated desenstivity of the Aryl Hydrocarbon Receptor (AHR) pathway regulated through the downregulation of the ahr2 gene. ahr2 gene intron hypermethylation was also detected in a Polycyclic Aromatic Hydrocarbons (PAHs)-resistant killifish population, a potential novel molecular mechanism underlying killifish rapid adaptations to PAHs toxicity. Reduced lipid metabolism and mitochondrial respiration were also identified as other key molecular processes underlying the evolved PAHs resistance in Atlantic killifish. Overall, the chapters of this thesis demonstrate the importance of integrating ectotherm physiology into SDMs to better predict their future habitat range shift patterns with ocean warming and the necessity of integrating different omics data to uncover the complex patterns of molecular mechanisms underlying marine organisms’ evolved resistance to ubiquitous aquatic pollution

What does a bioenergetic network approach tell us about the functioning of ecological communities?

Les perturbations auxquelles font face les communautés écologiques, du fait des activités humaines, sont à l'origine de changements profonds dans ces communautés. Nombreuses caractéristiques des espèces sont altérées, de leur physiologie à leur occurrence même. Ces changements se répercutent sur la composition, la diversité et la structure des communautés, puisque les espèces n'interagissent pas tout le temps de la même manière en fonction des conditions. Prévoir le devenir de ces communautés émergentes, et des fonctions qu'elles soutiennent est un défi central de l'écologie et de nos sociétés. Différents cadres conceptuels ont été utilisés pour relever ce défi, basés sur différents mécanismes écologiques, et ont divergé en plusieurs domaines. D'un côté, l'analyse des chaînes trophiques utilise la consommation pour expliquer les effets de la diversité verticale (le nombre de niveaux trophiques) sur le fonctionnement, et de l'autre côté, les analyses biodiversité-fonctionnement lient compétition et effets de la diversité horizontale (la diversité au sein des niveaux trophiques isolés). Chacun de ces domaines a produit des résultats clés pour comprendre les conséquences fonctionnelles des changements de composition et diversité des communautés écologiques. Cependant, ils sont chacun basés sur différentes simplifications fortes des communautés. L'hypothèse qui sous-tend cette thèse est que la réconciliation en un même cadre de travail des résultats fondamentaux de ces champs conceptuels divergents, ainsi que des effets des changements de structure de la biodiversité, est une étape clé pour pouvoir améliorer notre compréhension du fonctionnement de communautés écologiques en changement. L'essor récent des méthodes d'analyse des réseaux trophiques, et des modèles permettant de simuler le fonctionnement de ces réseaux trophiques offre un cadre idéal pour cette réconciliation. En effet, les réseaux trophiques cartographient les échanges de matière entre toutes les espèces d'une communauté, permettant la mise en place d'interactions variées. Ils reflètent mieux la réalité complexe des communautés que les chaînes trophiques ou leurs niveaux trophiques isolés en intégrant notamment compétition et consommation. Un modèle ressource-consommateur bioénergétique classique, développé par Yodzis et Innes (1992), permet d'en simuler le fonctionnement, en intégrant des mécanismes et taux testés empiriquement. Au-delà d'utiliser ces outils, cette thèse se concentre aussi sur leur évaluation. Après un premier chapitre d'introduction, le second chapitre propose une plateforme ouverte, commune, solidement testée et efficace pour l'utilisation du modèle bioénergétique, permettant ainsi une synthèse plus rapide et aisée des résultats. Le troisième chapitre est une revue du corpus méthodologique d'analyse des réseaux trophiques, proposant une gamme de méthodes robustes et informatives, et soulignant leur domaine d'application et leurs limites. Enfin le quatrième chapitre met ce cadre méthodologique à l'épreuve. Dans ce chapitre, nous montrons l'existence d'une relation entre la complexité de la structure du réseau trophique des communautés et leur régime de fonctionnement, se traduisant par la réalisation de différentes prédictions issues de l'analyse des chaînes trophiques ou des analyses diversité-fonctionnement. Cette mise en évidence des conditions structurelles pour la réalisation de différentes prédictions nous permet de mieux comprendre quels mécanismes écologiques prédominent selon différentes conditions, dirigeant l'effet de la diversité sur le fonctionnement.Human-driven disturbances are causing profound changes in ecological communities, as many characteristics of species are altered, from their physiology to their very occurrence. These changes affect the composition, diversity and structure of communities, since species do not always interact in the same way under different conditions. Predicting the fate of these emerging communities, and the functions they support, is a central challenge for ecology and our societies. Diverging conceptual frameworks have been used to address this challenge, based on different ecological mechanisms. On the one hand, food chain analysis uses consumption to explain the effects of vertical diversity (the number of trophic levels) on functioning, and on the other hand, biodiversity-functioning analyses link competition and the effects of horizontal diversity (diversity within isolated trophic levels). Each of these domains has produced key results for understanding the functional consequences of changes in the composition and diversity of ecological communities. However, they are each based on different strong simplifications of communities. The hypothesis underlying this thesis is that reconciling the fundamental results of these divergent conceptual fields, as well as the effects of changes in the structure of biodiversity, into a single framework is a key step towards improving our understanding of the functioning of changing ecological communities. The recent development of food web analysis and of models to simulate food webs functioning provides an ideal framework for this reconciliation. Food webs map the exchange of matter between all species in a community, allowing for a variety of interactions to take place. They better reflect the complex reality of communities than food chains or their isolated trophic levels, notably by integrating competition and consumption. A classical consumer-resource bioenergetic model developed by Yodzis and Innes (1992) specifically makes it possible to realistically simulate their functioning, using empirically tested mechanisms and rates. Beyond using these tools, this thesis focuses on their evaluation and implementation. After a first, introductory chapter, the second chapter proposes an open, common, well-tested and efficient platform for the use of the bioenergetic model, allowing a faster and easier synthesis of the results. The third chapter is a review of the methodological corpus for ecological networks analysis, outlining a range of robust and informative methods, and highlighting their scope and limitations. Finally, the fourth chapter puts this methodological framework to the test. In this chapter, we show the existence of a relationship between the complexity of communities' food-web structure and functioning regime, resulting in the realization of different predictions from food chain analysis or diversity-functioning analyses. This demonstration of the structural conditions for the realization of different predictions allows us to better understand which ecological mechanisms predominate under different conditions, directing the effect of diversity on functioning

Linking physiology and climate to infer species distributions in Australian skinks

1. Climate has a key impact on animal physiology, which in turn can have a profound influence on geographic distributions. Yet, the mechanisms linking climate, physiology and distribution are not fully resolved. 2. Using an integrative framework, we tested the predictions of the climatic variability hypothesis (CVH), which states that species with broader distributions have broader physiological tolerance than range-restricted species, in a group of Lampropholis skinks (8 species, 196 individuals) along a latitudinal gradient in eastern Australia. We investigated several physiological aspects including metabolism, water balance, thermal physiology, thermoregulatory behaviour and ecological performance. 3. Additionally, to test whether organismal information (e.g. behaviour and physiology) can enhance distribution models, hence providing evidence that physiology and climate interact to shape range sizes, we tested whether species distribution models incorporating physiology better predict the range sizes than models using solely climatic layers. 4. In agreement with the CVH, our results confirm that widespread species can tolerate and perform better at broader temperature ranges than range-restricted species. We also found differences in field body temperatures, but not thermal preference, between widespread and range-restricted species. However, metabolism and water balance did not correlate with range size. 5. Biophysical modelling revealed that the incorporation of physiological and behavioural data improves predictions of Lampropholis distributions compared with models based solely on macroclimatic inputs, but mainly for range-restricted species. 6. By integrating several aspects of the physiology and niche modelling of a group of ectothermic animals, our study provides evidence that physiology correlates with species distributions. Physiological responses to climate are central in establishing geographic ranges of skinks, and the incorporation of processes occurring at local scales (e.g. behaviour) can improve species distribution models

Regenerative Territories

This open access book provides new perspectives on circular economy and space, explored towards the definition of regenerative territories characterised by healthy metabolisms. Going beyond the mere reuse/recycle of material waste as resources, this work aims to understand how to apply circularity principles to, among others, the regeneration of wastescapes. The main focus is the development over time, and in particular the way how spatial planning and strategies respond to new unpredictable urgencies and opportunities related with territorial metabolisms. The book specifically focuses on living labs environments, where it is possible to tackle complex problems through a multidisciplinary and multi-stakeholder approach - including the use of digital spatial decision support environment – which could be able to include all the involved stakeholders. Through a spatial scope of circularity, this book describes several examples including among others ideas from different contexts such as Italy, The Netherlands, Belgium and Vietnam. Through including reflections on methodology and representation, as well as on solutions for circular and healthy metabolisms, the book provides an excellent resource to researchers and students

Regenerative Territories: Dimensions of Circularity for Healthy Metabolisms

This open access book provides new perspectives on circular economy and space, explored towards the definition of regenerative territories characterised by healthy metabolisms. Going beyond the mere reuse/recycle of material waste as resources, this work aims to understand how to apply circularity principles to, among others, the regeneration of wastescapes. The main focus is the development over time, and in particular the way how spatial planning and strategies respond to new unpredictable urgencies and opportunities related with territorial metabolisms. The book specifically focuses on living labs environments, where it is possible to tackle complex problems through a multidisciplinary and multi-stakeholder approach - including the use of digital spatial decision support environment – which could be able to include all the involved stakeholders. Through a spatial scope of circularity, this book describes several examples including among others ideas from different contexts such as Italy, The Netherlands, Belgium and Vietnam. Through including reflections on methodology and representation, as well as on solutions for circular and healthy metabolisms, the book provides an excellent resource to researchers and students

Global plant characterisation and distribution with evolution and climate

Since Arrhenius published seminal work in 1921, research interest in the description of plant traits and grouped characteristics of plant species has grown, underpinning diversity in trophic levels. Geographic exploration and diversity studies prior to and after 1921 culminated in biological, chemical and computer-simulated approaches describing rudiments of growth patterns within dynamic conditions of Earth. This thesis has two parts:- classical theory and multidisciplinary fusion to give mathematical strength to characterising plant species in space and time.Individual plant species occurrences are used to obtain a Species-Area Relationship. The use of both Boolean and logic-based mathematics is then integrated to describe classical methods and propose fuzzy logic control to predict species ordination. Having demonstrated a lack of significance between species and area for data modelled in this thesis a logic based approach is taken. Mamdani and T-S-K fuzzy system stability is verified by application to individual plant occurrences, validated by a multiple interfaced data portal. Quantitative mathematical models are differentiated with a genetic programming approach, enabling visualisation of multi-objective dispersal of plant strategies, plant metabolism and life-forms within the water-energy dynamic of a fixed time-scale scenario. The distributions of plant characteristics are functionally enriched through the use of Gaussian process models. A generic framework of a Geographic Information System is used to visualise distributions and it is noted that such systems can be used to assist in design and implementation of policies. The study has made use of field based data and the application of mathematic methods is shown to be appropriate and generative in the description of characteristics of plant species, with the aim of application of plant strategies, life-forms and photosynthetic types to a global framework. Novel application of fuzzy logic and related mathematic method to plant distribution and characteristics has been shown on a global scale. Quantification of the uncertainty gives novel insight through consequent trophic levels of biological systems, with great relevance to mathematic and geographic subject development. Informative value of Z matrices of plant distribution is increased substantiating sustainability and conservation policy value to ecosystems and human populations dependent upon them for their needs.Key words: sustainability, conservation policy, Boolean and logic-based, fuzzy logic, genetic programming, multi-objective dispersal, strategies, metabolism, life-forms

Causes and consequences of plant climate adaptation

2019 Spring.Includes bibliographical references.Climatic conditions such as temperature and drought can sources of strong selection on natural populations. In plants, whose sessile nature forces them to adapt to local climate conditions, extensive evidence of local adaptation has been observed. However, the consequences of this adaptation on ecosystem processes such as carbon cycling remain poorly understood. Additionally, the molecular basis of adaptation is often unresolved and the specific climatic factors that drive adaptive evolution unclear. Addressing these knowledge gaps has become increasingly urgent as climate change threatens to rapidly alter selection regimes. Fortunately, conceptual and technical advances provide new opportunities to characterize and integrate environments, phenotypes, and genes, and thus advance our understanding of the causes and consequences of climate adaptation. In Chapter 2 of this dissertation, I consider the consequences of climate adaptation through the lens of ecoevolutionary dynamics. Integrating environments and phenotypes by considering ecosystem impacts of adaptive evolution, I review empirical evidence that contemporary climate adaptation could significantly alter the carbon cycle. In Chapter 3, I investigate the molecular basis of adaptation to winter temperatures in the model plant Arabidopsis thaliana by integrating genes and environments through the framework of landscape and population genetics. Specifically, I address the hypothesis that loss-of-function in a family of transcription factors contributes to adaptation to warmer climates. In Chapter 4, I develop methods combining whole genome sequence data, long term remote sensing, and reverse genetics to study drought as an agent of selection on flowering time and identify loss-of-function variants contributing to this evolution in Arabidopsis thaliana. Together, this work has inspired my interest in combining conceptual, computational, experimental innovations into an integrated research program to understand climate adaptation