Much research debates whether properties of ecological networks such as nestedness and connectance stabilise biological communities while ignoring key behavioural aspects of organisms within these networks. Here, we computationally assess how adaptive foraging (AF) behaviour interacts with network architecture to determine the stability of plant-pollinator networks. We find that AF reverses negative effects of nestedness and positive effects of connectance on the stability of the networks by partitioning the niches among species within guilds. This behaviour enables generalist pollinators to preferentially forage on the most specialised of their plant partners which increases the pollination services to specialist plants and cedes the resources of generalist plants to specialist pollinators. We corroborate these behavioural preferences with intensive field observations of bee foraging. Our results show that incorporating key organismal behaviours with well-known biological mechanisms such as consumer-resource interactions into the analysis of ecological networks may greatly improve our understanding of complex ecosystems.

To accurately predict the outcome of a late phase study, pharmacometric models can help in drug development. Making informed decision on which models to use will also facilitate drug development. This can depend on the mechanism of action for the drug as well as stability and runtime factors. This is an investigation of four published semi-mechanistic pharmacometric models to predict glycosylated red blood cells (HbA1c) in a late phase study of an anti-diabetic drug together with an assessment of their stability and power to detect drug effects. Mean plasma glucose (MPG), fasting plasma glucose (FPG) or FPG and fasting serum insulin (FSI) are used together with HbA1c as drivers for change in the models. We find that less complex models, with fewer differential equations, are quicker to run and more stable, and that MPG alone is superior to FPG or FPG and FSI to detect a drug effect. The findings are useful for drug development in the anti-diabetic area, and show that a less mechanistic model performs well under these conditions.

The current study is a part of a long term experimental project devoted to investigate flow boiling heat transfer, pressure drop and flow visualization of R134a in small to mini/micro-diameter tubes. The experimental facility was first designed and constructed by X. Huo (2005) with the contribution of L. Chen (2006). In the present study, the experimental facility was upgraded by changing the heating system from AC to DC heating and also upgrading the logging system through using a faster data logger and developing a new Labview program. The objectives of the current study include (i) contribute in identifying the reasons behind the wide scatter in the published flow boiling heat transfer results, (ii) contribute in understanding the fundamentals of flow boiling heat transfer in mini/micro-diameter tubes and (iii) evaluation of the existing heat transfer and pressure drop prediction methods. Two sizes of stainless steel tubes were investigated in the current study; 0.52 mm and 1.1 mm diameter. In the current study, the 0.52 mm tube was roughly called a “micro-tube” whilst the 1.1 mm tubes were called “mini-tubes”. The present study proposes two possible reasons for the scatter in the published heat transfer results. The first reason is the variations in the heated length from one study to another–there is no criterion for choosing the heated length. The second reason is the variations in the inner surface characteristics of the channels from one study to another. These two important parameters were not taken into consideration by researchers in the past studies. Accordingly, the effect of the heated length was investigated in the current study using a seamless cold drawn tube with diameter of 1.1 mm and heated length ranging from 150 to 450 mm. The effect of the tube inner surface was also tested here by conducting the test in two stainless steel tubes with diameter of 1.1 mm and manufactured by two different processes. The first tube was manufactured by welding technique whilst the second tube was a seamless cold drawn tube. Both tubes were identical in design and dimensions. The inner surface of each tube was examined first using SEM analysis and demonstrated that, the surface morphology is completely different. The local heat transfer coefficient was determined through measuring the local wall temperature using 14 K-type thermocouples attached to the wall using thermally conducting but electrically insulating epoxy supplied by Omega. Pressure drop was measured directly across the heated section and a high speed camera was used for the flow visualization at 1000 frames/s. All measurements were recorded after the system attained steady state. The experimental conditions include mass flux range of 100 – 500 kg/m2 s, system pressure range of 6 – 10 bar, inlet sub-cooling of about 5K and exit quality up to about 0.9. The most frequently observed flow regimes in the 0.52 mm tube were found to be slug (elongated bubble), transition to annular and annular flow regimes. In the 1.1 mm tube, the observed regimes were found to be slug, churn and annular. The transition from slug flow to annular flow in the 0.52 mm tube occurred smoothly with little disturbances at the liquid vapour interface compared to the 1.1 mm tube. Additionally, increasing the heated length of the 1.1 mm tube was found to shift the transition to annular flow to occur at lower vapour quality. The heat transfer results demonstrated that the behaviour of the local heat transfer coefficient in the 0.52 mm diameter tube is different compared to that in the 1.1 mm tubes. Also, the tube inner surface characteristics and the heated length were found to strongly influence the local behaviour of the heat transfer coefficient. Flow boiling hysteresis was investigated and the results indicated that hysteresis exists only at very low heat fluxes near the boiling incipience. Existing heat transfer and pressure drop correlations were examined using the results of the 0.52 and 1.1 mm seamless cold drawn tubes. The pressure drop data were predicted very well using the Muller-Stienhagen and Heck (1986) correlation, the homogeneous flow model and the correlation of Mishima and Hibiki (1996). On the contrary, all macro and microscale heat correlations failed to predict the current experimental data. The mechanistic models failed to predict the data of all tubes with the same accuracy. Accordingly, two heat transfer correlations were proposed in the current study. The first correlation is based on dimensionless groups whilst the second is based on the superposition model of Chen (1966). Both correlations predicted the current experimental data and the data of Huo (2005) and Shiferaw (2008) very well.

Mixoplankton are protist plankton that are capable of phototrophy and phagotrophy. These organismsare increasingly recognised not just as freaks of nature, but as a substantial part of marineplankton. Most existing plankton models still assume a strict dichotomy between phototrophsand heterotrophs. Few models consider mixoplanktonic activity as a synergism of the two trophicmodes. Many different mixoplankton functional types exist on a gradient between heterotrophy andphototrophy. The cryptophyte (Teleaulax)-Mesodinium-Dinophysis (TMD) complex is a specificpredator-prey interaction of different types of mixoplankton and a good example of the complexityof mixoplankton interaction and trophodynamics. The specialist non-constitutive mixoplankton(SNCM) Mesodinium acquires its chloroplasts strictly from a specific constitutive mixoplankton(CM) cryptophyte, while the harmful algal bloom (HAB) species Dinophysis acquires its third-handchloroplasts exclusively from Mesodinium.The generic NPZ-style protist model developed here shows that mixoplankton displays dynamicsthat are distinctly different from strict heterotrophs and autotrophs in terms of growth and theway they shape their environment. In addition, there is a clear niche separation between differentmixoplankton types (general non-constitutive mixoplankton (GNCM), SNCM and CM) according tonutrient, prey and light resource availabilities indicating a niche separation of each type. Thus,considering the different mixoplankton functional types in specialised multi-organism relationshipsas they are found in the TMD-complex may be important for their understanding and accurateprediction of growth and biomass development. Currently, none of the many models of Dinophysiscapture the biological dependencies. Results from a nitrogen-based TMD model suggest thatthe timing and quantity of prey availability is crucial for the bloom dynamics of Mesodinium andDinophysis. Some CMs may only feed when phosphate is the limiting nutrient. The results ofthe variable stoichiometric “Perfect Beast” model that was configured as Teleaulax amphioxeia incombination with experimental data strongly suggest that the cryptophyte feeds on bacteria tocompensate for phosphate limitation.This work shows the importance of considering mixoplankton in ecosystem models alongsidestrict heterotrophs and autotrophs and that distinction between different mixoplankton functionaltypes matters. Mixoplankton distinctly differ in their nutrient utilisation and growth dynamics.Predator-prey interactions have different implications for mixoplankton than for heterotrophs andtheir inclusion in models could improve our understanding of the formation of harmful mixoplanktonblooms. The unique physiology of mixoplankton and their nutrient utilisation and trophic levelsneed consideration in species specific models. / Le mixoplancton inclut les protistes planctoniques capables de phototrophie et de phagotrophie.Ces organismes sont de plus en plus reconnus comme une partie importante du plancton marin.Toutefois, la plupart des modèles mathématiques planctoniques existants supposent encoreune stricte dichotomie entre les organismes phototrophes et hétérotrophes et peu de modèlesconsidèrent l’activité mixoplanctonique comme une synergie entre les deux modes trophiques.De nombreux types fonctionnels mixoplanctoniques différents existent dans un gradient entrel’hétérotrophie et la phototrophie. Le complexe cryptophyte (Teleaulax)-Mesodinium-Dinophysis(TMD) est une interaction prédateur-proie spécifique entre différents types de mixoplancton et unbon exemple de la complexité des interactions et des relations trophodynamiques du mixoplancton.Mesodinium, mixoplancton spécialiste non constitutif (SNCM), ne peut acquérir ses chloroplastesque de cryptophytes (mixoplancton constitutif (CM)) spécifiques (tel que Teleaulax), tandis quel’espèce Dinophysis, responsable d’efflorescences algales nuisibles, acquiert ses chloroplastesexclusivement de Mesodinium. Le modèle générique de protistes, de type NPZ, développé dansce travail montre que le mixoplancton présente une dynamique nettement différente de celle deshétérotrophes et autotrophes strictes en termes de croissance et de la façon dont ils façonnentleur environnement. En outre, il existe une séparation de niches claire entre les différents typesde mixoplancton (mixoplancton généraliste non-constitutif (GNCM), SNCM et CM) en fonction dela disponibilité en lumière, en nutriments et en proies. En conséquence, la prise en compte desdifférents types fonctionnels du mixoplancton dans des relations multi-organismes spécialisées,telles qu’on les trouve dans le complexe TMD, peut être importante pour leur compréhension et laprédiction précise de leur croissance et biomasse. Actuellement, aucun des modèles existants deDinophysis ne rend compte de ces dépendances biologiques. Les résultats d’un modèle TMD basésur l’azote suggèrent que le moment et la quantité de proies disponibles sont des facteurs cruciauxpour la dynamique de Mesodinium et de Dinophysis. Certains CM peuvent se nourrir uniquementlorsque le phosphate est le nutriment limitant. Les résultats du modèle à stoechiométrie variable"Perfect Beast", qui a été configuré pour représenter Teleaulax amphioxeia sur base de donnéesexpérimentales, suggèrent fortement que le cryptophyte se nourrit de bactéries pour compenserla limitation en phosphate. Ce travail montre l’importance de prendre en compte le mixoplanctondans les modèles d’écosystème en plus des hétérotrophes et des autotrophes stricts et que ladistinction entre les différents types fonctionnels de mixoplancton est importante. Le mixoplanctonse distingue par son utilisation des nutriments et sa dynamique de croissance. Les interactionsprédateur-proie n’ont pas les mêmes implications pour le mixoplancton que pour les hétérotropheset leur prise en compte dans les modèles pourrait améliorer notre compréhension de la formationdes efflorescences nuisibles de mixoplancton. La physiologie unique du mixoplancton, sonutilisation des nutriments et ses niveaux trophiques doivent être pris en compte dans les modèlesspécifiques aux espèces. / Doctorat en Sciences agronomiques et ingénierie biologique / info:eu-repo/semantics/nonPublished

The present thesis aims to introduce process-based model for species range dynamics that can be fitted to abundance data. For this purpose, the well-studied Proteaceae species of the South African Cape Floristic Region (CFR) offer a great data set to fit process-based models. These species are subject to wildflower harvesting and environmental threats like habitat loss and climate change. The general introduction of this thesis presents shortly the available models for species distribution modelling. Subsequently, it presents the feasibility of process-based modelling. Finally, it introduces the study system as well as the objectives and layout. In Chapter 1, I present the process-based model for range dynamics and a statistical framework to fit it to abundance distribution data. The model has a spatially-explicit demographic submodel (describing dispersal, reproduction, mortality and local extinction) and an observation submodel (describing imperfect detection of individuals). The demographic submodel links species-specific habitat models describing the suitable habitat and process-based demographic models that consider local dynamics and anemochoric seed dispersal between populations. After testing the fitting framework with simulated data, I applied it to eight Proteaceae species with different demographic properties. Moreover, I assess the role of two other demographic mechanisms: positive (Allee effects) and negative density-dependence. Results indicate that Allee effects and overcompensatory local dynamics (including chaotic behaviour) seem to be important for several species. Most parameter estimates quantitatively agreed with independent data. Hence, the presented approach seemed to suit the demand of investigating non-equilibrium scenarios involving wildflower harvesting (Chapter 2) and environmental change (Chapter 3). The Chapter 2 addresses the impacts of wildflower harvesting. The chapter includes a sensitivity analysis over multiple spatial scales and demographic properties (dispersal ability, strength of Allee effects, maximum reproductive rate, adult mortality, local extinction probability and carrying capacity). Subsequently, harvesting effects are investigated on real case study species. Plant response to harvesting showed abrupt threshold behavior. Species with short-distance seed dispersal, strong Allee effects, low maximum reproductive rate, high mortality and high local extinction are most affected by harvesting. Larger spatial scales benefit species response, but the thresholds become sharper. The three case study species supported very low to moderate harvesting rates. Summarizing, demographic knowledge about the study system and careful identification of the spatial scale of interest should guide harvesting assessments and conservation of exploited species. The sensitivity analysis’ results can be used to qualitatively assess harvesting impacts for poorly studied species. I investigated in Chapter 3 the consequences of past habitat loss, future climate change and their interaction on plant response. I use the species-specific estimates of the best model describing local dynamics obtained in Chapter 1. Both habitat loss and climate change had strong negative impacts on species dynamics. Climate change affected mainly range size and range filling due to habitat reductions and shifts combined with low colonization. Habitat loss affected mostly local abundances. The scenario with both habitat loss and climate change was the worst for most species. However, this impact was better than expected by simple summing of separate effects of habitat loss and climate change. This is explained by shifting ranges to areas less affected by humans. Range size response was well predicted by the strength of environmental change, whereas range filling and local abundance responses were better explained by demographic properties. Hence, risk assessments under global change should consider demographic properties. Most surviving populations were restricted to refugia, serving as key conservation focus.The findings obtained for the study system as well as the advantages, limitations and potentials of the model presented here are further discussed in the General Discussion. In summary, the results indicate that 1) process-based demographic models for range dynamics can be fitted to data; 2) demographic processes improve species distribution models; 3) different species are subject to different processes and respond differently to environmental change and exploitation; 4) density regulation type and Allee effects should be considered when investigating range dynamics of species; 5) the consequences of wildflower harvesting, habitat loss and climate change could be disastrous for some species, but impacts vary depending on demographic properties; 6) wildflower harvesting impacts varies over spatial scale; 7) The effects of habitat loss and climate change are not always additive. / Das Ziel dieser Studie bestand daher darin, prozess-basierte Modelle zu entwickeln, die mit Daten zur Abundanz von Arten parametrisiert werden können. Die außergewöhnlich gut erforschten Proteaceen der südafrikanischen Kapregion (CFR), für die ein umfangreicher Datensatz zur Verfügung steht, stellen ein sehr geeignetes Untersuchungssystem zur Erstellung derartiger prozess-basierter Modelle dar. In Kapitel 1 beschreibe ich ein prozess-basiertes Modell für die Verbreitungsdynamik sowie die Methoden zur Parametrisierung des Modells mit Daten zu Abundanzverteilungen. Das Modell umfasst ein räumlich-explizites demographisches Modul und ein Beobachtungsmodul. Das demographische Modul verbindet artspezifische Habitatmodelle, die das geeignete Habitat beschreiben, und prozess-basierte demographische Modelle, die die lokale Dynamik und die Windausbreitung von Samen umfassen. Nach der Überprüfung der Parametrisierungs¬methoden mit simulierten Daten, wende ich die Modelle auf acht Proteaceenarten mit unterschiedlichen demographischen Eigenschaften an. Außerdem untersuche ich die Rolle von positiver (Allee-Effekte) und negativer Dichte-Abhängigkeit. Die Ergebnisse zeigen, dass Allee-Effekte und überkompensatorische Dynamik für viele Arten tatsächlich eine Rolle spielen. Der Großteil der geschätzten Parameter stimmt quantitativ mit unabhängigen Daten und beschreibt erfolgreich, wie die Abundanzverteilung aus der Bewegung und Interaktion der Individuen entsteht. Die vorgestellten Methoden scheinen daher zur Untersuchung von Ungleichgewichtsszenarien geeignet, die die Ernte von Infloreszenzen in Wildbeständen (Kapitel 2) und Umweltwandel (Kapitel 3) einschließen. In Kapitel 2 untersuche ich die Effekte der Ernte von Infloreszenzen in Wildbeständen. Das Kapitel beinhaltet eine Sensitivitätsanalyse über mehrere räumliche Skalen sowie demographische Eigenschaften. Darauf folgend wurden die Effekte der Ernte anhand von drei realen Arten untersucht. Die Reaktion der Pflanzen auf die Ernte zeigte ein Verhalten mit abrupten Schwellenwerten. Die durch die Ernte am stärksten gefährdeten Arten zeichneten sich durch kurze Samenausbreitungsdistanzen, starke Allee Effekte, geringe maximale Reproduktionsrate, hohe Mortalität und hohe lokale Aussterbewahrscheinlichkeit aus. Die Betrachtung größerer räumlicher Skalen wirkte sich trotz schärferer Grenzwerte positiv auf die Reaktion der Arten aus. Die drei untersuchten realen Arten konnten sehr geringe bis mittlere nachhaltige Ernteraten ertragen. Zusammenfassend lässt sich sagen, dass Kenntnisse über die Demographie des Untersuchungssystems und die umsichtige Identifizierung der zu betrachtenden räumlichen Skala zu einer besseren Einschätzung der Ernteintensität und der Naturschutzziele führen sollten. In Kapitel 3 wird die Reaktion der Arten auf vergangene Habitatverluste und zukünftigen Klimawandel sowie die Interaktion der beiden untersucht. Der Klimawandel wirkte sich dabei vornehmlich negativ auf die Größe des Verbreitungsgebiets und die Ausnutzung des potentiellen Habitats (‚Range Filling’) aus, wobei es zu einer Verschiebung des Habitats ohne erfolgreiche Kolonisierung kam. Der Habitatverlust reduzierte vor allem die lokalen Abundanzen. Die meisten Arten wurden vor allem durch das Szenario mit beiden Klimawandel und Habitatsverlust stark beeinträchtigt. Der negative Effekt war allerdings geringer als nach einer einfachen Aufsummierung der Einzeleffekte zu erwarten wäre. Dies erklärt sich aus einer Verschiebung des Verbreitungsgebiets der Arten in Regionen, in denen es in der Vergangenheit zu geringeren Habitatverlusten kam. Die Größe des Verbreitungsgebiets wurde am besten durch die Stärke des Umweltwandels vorhergesagt, wogegen das Range Filling und die lokalen Abundanzen hauptsächlich von den demographischen Eigenschaften abhingen. Aus diesen Ergebnissen lässt sich schließen, dass Abschätzungen des Aussterbensrisikos unter Umweltwandel demographische Eigenschaften einbeziehen sollten. Die meisten überlebenden Populationen waren auf Refugien reduziert, die im Fokus der Naturschutzmaßnahmen stehen sollten. Zusammenfassend zeigen die Ergebnisse, dass 1) prozess-basierte demographische Modelle für die Verbreitungsdynamik von Arten mit Daten parametrisierbar sind; 2) die Einbeziehung demographischer Prozesse die Modelle für die Verbreitung von Arten verbessert; 3) verschiedene Arten von unterschiedlichen Prozessen beeinflusst werden und unterschiedlich auf Umweltwandel und Beerntung reagieren; 4) Dichteregulierung und Allee-Effekte bei der Untersuchung der Verbreitungsdynamik von Arten berücksichtigt werden sollten; 5) die Ernte von Infloreszenzen in Wildbeständen, sowie Habitatverlust und Klimawandel für manche Arten katastrophale Folgen haben können, deren Effekte aber von den demographischen Eigenschaften abhängen; 6) der Einfluss der Beerntung in Abhängigkeit von der betrachteten räumlichen Skala variiert; 7) die Effekte von Habitatverlust und Klimawandel nicht additiv sind.

Les distributions d'espèces observées dans un environnement hétérogène résultent de plusieurs processus déterministes et stochastiques agissant comme des filtres pour contraindre la coexistence des espèces. L’action successive de ces processus a pour conséquence directe de structurer spatialement la composition des communautés et la variation de ces compositions (i.e., diversité bêta). Un des objectifs majeurs de l'écologie des communautés et métacommunautés consiste à identifier et quantifier les effets respectifs de ces différents processus sur la diversité bêta des communautés afin de mieux comprendre et prédire la distribution de la biodiversité. L'expérimentation étant difficilement possible, les processus responsables de la variation spatiale de la composition des communautés sont généralement inférés à partir des structures spatiales des distributions d’espèces observées dans la nature. La thèse s’inscrit dans ce contexte et vise à améliorer les outils de statistique multivariée permettant d’identifier et quantifier l'effet des processus écologiques structurant les communautés et métacommunautés. En particulier, il est proposé d’intégrer les échelles écologiques et les modèles nuls contraints pour étudier l’effet de l’environnement. La décomposition des relations trait-environnement dans les échelles spatiales et phylogénétiques permet une étude plus approfondie du filtrage environnemental en associant son échelle spatiale d’action au signal phylogénétique des traits sélectionnés pour capturer l’histoire évolutive associée au filtrage environnemental. L’interprétation en terme de processus évolutifs est néanmoins limitée et mériterait l’intégration de modèles nuls phylogénétiquement contraints pour une analyse plus fine. Dans la continuité, des modèles nuls spatialement contrains ont été développés et intégrés à deux analyses multivariées très largement utilisées en écologie des communautés (i.e., partitionnement de variation et test de Mantel) pour estimer et tester l’effet de l’environnement sur les assemblages d’espèces. Ces deux analyses présentaient une surestimation de leur statistique mesurée ainsi qu’un taux anormal de faux positifs lorsque les distributions d’espèces (via processus de dispersion limitée) et l’environnement étaient indépendamment spatialement structurés. L’intégration de modèles nuls spatialement contraints a permis d’ajuster à la fois les estimations et les tests de ces deux analyses illustrant ainsi le besoin d’utiliser des modèles nuls écologiquement contraints pour une identification et quantification correctes des processus écologiques / Species distributions observed in an heterogeneous environment result from multiple deterministic and stochastic processes acting as filters to constrain species co-existence. As a direct consequence, the successive actions of these processes spatially structure communities composition and the variation of these compositions (i.e., beta-diversity). One of the major objective in community and metacommunity ecology is to identify and quantify the respective effects of these different processes on communities beta-diversity to better understand and predict the distribution of biodiversity. Experiments being hardly possible, processes responsible for the spatial variation of communities composition are generally inferred from spatial patterns of species distributions observed in nature. In this context, the thesis aims at improving multivariate statistical tools conducted to identify and quantify the effects of ecological processes shaping communities and metacommunities. In particular, this thesis proposes to integrate ecological scales and constrained null models to study the effect of environment.Decomposing trait-environment relationships through spatial and phylogenetic scales allows to further study environmental filtering. The association of spatial scales involved in environmental filtering with the phylogenetic signals of traits allowed to capture the evolutive history related to environmental filtering. The interpretation in terms of evolutive processes is however limited and phylogenetically-constrained null models should be considered to improve the analysis. Following on from this work, spatially-constrained null models were developed and integrated into two multivariate analyses widely used in community ecology (i.e., variation partitioning and Mantel tests) to estimate and test the effect of environmental filtering on species assemblages. Both approaches presented overestimation of their computed statistic as well as high rates of false positive when species distributions (via limited dispersal) and environmental conditions were independently spatially structured. Integrating spatially-constrained null models allowed to adjust both their tests and the values of their statistic, as such demonstrating the need of using ecologically-constrained null models to correctly identify and quantify ecological processes.For future works, the thesis suggests that adopting a scaling approach to study ecological processes in addition to mechanistic null models could offer the possibility to distinguish processes from one another