Dissertations / Theses on the topic 'Ecological Modelling'

The modelling of biological communities is important to further the understanding of species coexistence and the mechanisms involved in maintaining biodiversity. This involves considering not only interactions between individual biological organisms, but also the incorporation of covariate information, if available, in the modelling process. This thesis explores the use of point processes to model interactions in bivariate point patterns within a Bayesian framework, and, where applicable, in conjunction with covariate data. Specifically, we distinguish between symmetric and asymmetric species interactions and model these using appropriate point processes. In this thesis we consider both pairwise and area interaction point processes to allow for inhibitory interactions and both inhibitory and attractive interactions. It is envisaged that the analyses and innovations presented in this thesis will contribute to the parsimonious modelling of biological communities.

Le tecniche di next generation sequencing costituiscono un potente strumento per diverse applicazioni, soprattutto da quando i loro costi sono iniziati a calare e la qualità dei loro dati a migliorare. Una delle applicazioni del sequencing è certamente la metagenomica, ovvero l'analisi di microorganismi entro un dato ambiente, come per esempio quello dell'intestino. In quest'ambito il sequencing ha permesso di campionare specie batteriche a cui non si riusciva ad accedere con le tradizionali tecniche di coltura. Lo studio delle popolazioni batteriche intestinali è molto importante in quanto queste risultano alterate come effetto ma anche causa di numerose malattie, come quelle metaboliche (obesità, diabete di tipo 2, etc.). In questo lavoro siamo partiti da dati di next generation sequencing del microbiota intestinale di 5 animali (16S rRNA sequencing) [Jeraldo et al.]. Abbiamo applicato algoritmi ottimizzati (UCLUST) per clusterizzare le sequenze generate in OTU (Operational Taxonomic Units), che corrispondono a cluster di specie batteriche ad un determinato livello tassonomico. Abbiamo poi applicato la teoria ecologica a master equation sviluppata da [Volkov et al.] per descrivere la distribuzione dell'abbondanza relativa delle specie (RSA) per i nostri campioni. La RSA è uno strumento ormai validato per lo studio della biodiversità dei sistemi ecologici e mostra una transizione da un andamento a logserie ad uno a lognormale passando da piccole comunità locali isolate a più grandi metacomunità costituite da più comunità locali che possono in qualche modo interagire. Abbiamo mostrato come le OTU di popolazioni batteriche intestinali costituiscono un sistema ecologico che segue queste stesse regole se ottenuto usando diverse soglie di similarità nella procedura di clustering. Ci aspettiamo quindi che questo risultato possa essere sfruttato per la comprensione della dinamica delle popolazioni batteriche e quindi di come queste variano in presenza di particolari malattie.

Amphibians are the most threatened taxon assessed by the IUCN Red List, with over 42% of all species in decline. The emerging infectious disease chytridiomycosis, caused by the fungus Batrachochytrium dendrobatidis, has been shown to a driver of many of these declines. The broad aim of this thesis is to develop mechanistic models that realistically capture the observed disease dynamics of Bd within Europe, and use these to help understand its ecological and environmental drivers. Mathematical modelling, field work and experimental work are used in order to obtain an understanding of a Bd-host system on Mallorca, and in combination, to show how the host population response to Bd is highly context-dependent. The understanding gained is used to help predict the consequences of an attempt to mitigate (reduce or avoid the negative effects of) Bd in this system, and the mitigation attempt’s short-comings are then analyzed in order to better inform future efforts. The context-dependence of a host-population response to Bd will depend of two components: a component dependent on the host and a component dependent on Bd. Modelling of infection experiment results in the frog species Silurana tropicalis is used to show a temperature-dependent host response which is separate to the temperature-dependent response of Bd. Multi-host models of Bd are created and used to show how increasing species diversity can increase disease risk, and a method of estimating unknown epidemiological parameters for Bd based on known facts about the host’s biology is presented.

The Systems Approach Framework (SAF) is a methodological framework designed to enhance the efficacy of human decision-making processes within social-ecological systems with regard to sustainability. The SAF was applied in two case studies in the coastal zone of Catalonia, in two separate European Commission Framework Programme projects entitled “Science and Policy Integration for Coastal System Assessment” (SPICOSA) and “Vectors of Change in Oceans and Seas-marine Life, Impact on Economic Sectors" (VECTORS). During the SPICOSA application, a common issue of interest to most stakeholders was the water quality (harmful bacteria and water clarity) of the local city beaches, particularly following combined sewer overflow events, and mitigating this impact by using stormwater collectors. Water quality influences the beach users’ decision whether to stay at the beach or to leave, thus affecting the revenue received by the bars and restaurants on the beach front. A social-ecological model was constructed using the methodology outlined in the SAF to represent this issue, so that it could be used as a tool for deliberation between the stakeholders. The model output implies that the stormwater collectors have been useful in improving beach water quality in Barcelona, but there will be diminished returns in constructing more. The value of the beach is clearly large in terms of both non-market value and revenues generated in the nearby bars and restaurants. However, the impact changes in water quality would have on the recreational appeal of the beach is estimated to be low and further research is recommended to determine beach users’ sensitivity to beach closures (bacteria limit exceeded) and turbidity. At the beginning of the VECTORS project, stakeholders who had participated during the previous SAF application expressed a lack of willingness to engage due to a lack of human resources. The scientific team therefore chose to continue the application with the aspiration of demonstrating the SAF model and results at a later date if the stakeholders found the required resources to engage with the process. There is a general perception that jellyfish abundances are increasing along the Catalan coast. Local authorities are concerned about the stranding events and arrivals of jellyfish to beaches and believe it could reduce the recreational appeal of the beaches. Previous studies also demonstrate the predation of jellyfish (Pelagia noctiluca ephyrae) upon some small pelagic fish larvae (Engraulis encrasicolus). Small pelagics are the principal source of revenue for the local fisheries. A social-ecological model was created in order to capture the effects of changes in abundance of Pelagia noctiluca upon the local fisheries, the tourist industry and the wider economy. Various future scenarios for different abundances of jellyfish blooms were run. Given the changes that these scenarios would cause on the regional gross domestic product and employment, this study concludes that the overall impact of either of these scenarios on the economy would not be significant at the regional scale. The inclusion of stakeholders in the SAF methodology is rightly fundamental, but in practice, it can be extremely difficult to persuade key stakeholders to participate, and this is a flaw in the SAF which needs addressing. SAF Application model builders are dependent on stakeholders sharing important data or knowledge but this may be withheld for a variety of reasons including, but not limited to, lack of resources to participate, disinterest, and concern about how the results will be used. The SAF is a well-structured methodology for cases where a mathematical model is both relevant and feasible and should be considered as a useful step-by-step guide for managing coastal zone systems towards sustainability.

Thesis (MSc)--Stellenbosch University, 2011.
ENGLISH ABSTRACT: In any ecological system, organisms need to interact with each other for their survival. Such interactions form ecological networks which are usually very complex. Nevertheless, they exhibit well de ned patterns; these regularities are often interpreted as products of meaningful ecological processes. As the networks are evolving through time, biological evolution is one of the factors that affects ecological network architecture. In this work, we develop a mathematical model that represents the evolution through time of such ecological interaction networks. The problem is approached by modelling network evolution as a continuous time Markov process, in such a way that the interactions in which a parent species is involved are potentially inherited by its descendant species. This approach allows us to infer ecological parameters and ecological network histories from real-world network data, as well as to simulate ecological networks under our model. While ecologists have long been aware of the in uence of evolutionary processes in shaping ecological networks, we are now able to evaluate the importance of such in uence.
AFRIKAANSE OPSOMMING: In enige ekologiese stelsel benodig organismes wisselwerkings met mekaar ten einde te oorleef. Sulke interaksies vorm ekologiese netwerke wat gewoonlik baie kompleks is maar nogtans goed-gede nieerde patrone vertoon. Hierdie patrone word dikwels geïnterpreteer as die produk van betekenisvolle ekologiese prosesse. Aangesien die netwerke met die verloop van tyd ontwikkel, is biologiese ewolusie een van die faktore wat ekologiese netwerkargitektuur beïnvloed. In hierdie studie ontwikkel ons 'n wiskundige model wat die ewolusie van sulke ekologiese interaksienetwerke voorstel. Die probleem word benader deur netwerkewolusie as 'n kontinue-tyd Markov-proses te modelleer, op so 'n manier dat die interaksies waarin 'n voorouerspesie betrokke is potensieel oorerf kan word deur die afstammelingspesies. Hierdie benadering laat ons toe om ekologiese parameters en ekologiese netwerkgeskiedenisse vanuit regte-wêreld data af te lei, sowel as om ekologiese netwerke onder ons model te simuleer. Alhoewel ekoloë al lank reeds bewus is van die invloed wat ewolusionêre prosesse het op die vorming van ekologiese netwerke, is ons nou in staat om die belangrikheid van hierdie invloed te evalueer.

In this thesis, we consider the problem of long-term persistence in ecological and epidemiological systems. This is important in conservation biology for protecting species at risk of extinction and in epidemiology for reducing disease prevalence and working towards elimination. Understanding how to predict and control persistence is critical for these aims. In Chapter 2, we discuss existing ways of characterising persistence and their relationship with the modelling paradigms employed in ecology and epidemiology. We note that data are often limited to information on the state of particular patches or populations and are modelled using a metapopulation approach. In Chapter 3, we define persistence in relation to a pre-specified time horizon in stochastic single-species and two-species competition models, comparing results between discrete and continuous time simulations. We find that discrete and continuous time simulations can result in different persistence predictions, especially in the case of inter-specific competition. The study also serves to illustrate the shortcomings of defining persistence in relation to a specific time horizon. A more mathematically rigorous interpretation of persistence in stochastic models can be found by considering the quasi-stationary distribution (QSD) and the associated measure of mean time to extinction from quasi-stationarity. In Chapter 4, we investigate the contribution of individual patches to extinction times and metapopulation size, and provide predictors of patch value that can be calculated easily from readily available data. In Chapter 5, we focus directly on the QSD of heterogeneous systems. Through simulation, we investigate possible compressions of the QSD that could be used when standard numerical approaches fail due to high system dimensionality, and provide guidance on appropriate compression choices for different purposes. In Chapter 6, we consider deterministic models and investigate the effect of introducing additional patch states on the persistence threshold. We suggest a possible model that might be appropriate for making predictions that extend to stochastic systems. By considering a family of models as limiting cases of a more general model, we demonstrate a novel approach for deriving quantities of interest for linked models that should help guide modelling decisions. Finally, in Chapter 7, we draw out implications for conservation biology and disease control, as well as for future work on biological persistence.

This thesis presents a new stratigraphic forward numerical model to simulate the carbonate production of marine sedimentary basin through ecological model which is implemented in the SIMSAFADIM-CLASTIC program. This ecological model is based on the Generalized Lotka Voltera equations that model the population evolution of species. These populations are controlled by biological factors (growth rate, carrying capacity and interaction among species), and by the environmental conditions (light, energy of the medium, nutrients, bottom slope and concentration of clastic sediments in suspension) which are combined forming a unique environmental factor that downscale the intrinsic rate of growth. The algorithm to apply in the code uses an explicit Runge-Kutta numerical method of order (4)5 to solve the differential equations formulated in the ecological model. Finally, a 3D visualization output files for the interpretation and analysis are generated using the VTK format. The obtained code has been applied in three sample experiments in order to discuss the possibilities and the limitations of the code. The first example is the model of a theoretical basin. The results are compared with real cases. The second example is an actual basin sited in western Mediterranean Sea. The results are discussed to show the applicability and the limitations of the model. The third example applies several configurations to the Aptian Galve sub-basin (Maestrat Basin, E Iberia), allowing to define the environmental conditions.

Mathematical models are a theoretical tool used to understand ecological processes. In this thesis we create mathematical frameworks to describe and evaluate four ecological systems. In the first case study we extend a host-pathogen framework to include a maternal effect which increases the disease resistance of offspring when the maternal environment is poor. Maternal effects impacting life-history traits have been shown to increase the propensity for population cycles. Our contrasting results show maternal effects acting on disease resistance stabilise host-pathogen systems. The second case study examines the impact infection may have on population estimates using Capture-Mark-Recapture (CMR) studies. We show that the estimates using the statistical Program Capture are accurate when capture rates are infection dependent. The final two case studies use spatial, individual-based, stochastic models to simulate disease spread and the colonisation of the Eurasian red squirrel (Sciurus vul- garis) on real-life landscapes. Using novel techniques we highlight the role habitat connectivity has on the dispersal routes which influence the spread of disease and re-population dynamics. Moreover the inclusion of seasonality shows that squirrel population dynamics are driven by the multi-year signal of resources.

Ecological problems are typically multi faceted and need to be addressed from a scientific and a management perspective. There is a wealth of modelling and simulation software available, each designed to address a particular aspect of the issue of concern. Choosing the appropriate tool, making sense of the disparate outputs, and taking decisions when little or no empirical data is available, are everyday challenges facing the ecologist and environmental manager. Bayesian Networks provide a statistical modelling framework that enables analysis and integration of information in its own right as well as integration of a variety of models addressing different aspects of a common overall problem. There has been increased interest in the use of BNs to model environmental systems and issues of concern. However, the development of more sophisticated BNs, utilising dynamic and object oriented (OO) features, is still at the frontier of ecological research. Such features are particularly appealing in an ecological context, since the underlying facts are often spatial and temporal in nature. This thesis focuses on an integrated BN approach which facilitates OO modelling. Our research devises a new heuristic method, the Iterative Bayesian Network Development Cycle (IBNDC), for the development of BN models within a multi-field and multi-expert context. Expert elicitation is a popular method used to quantify BNs when data is sparse, but expert knowledge is abundant. The resulting BNs need to be substantiated and validated taking this uncertainty into account. Our research demonstrates the application of the IBNDC approach to support these aspects of BN modelling. The complex nature of environmental issues makes them ideal case studies for the proposed integrated approach to modelling. Moreover, they lend themselves to a series of integrated sub-networks describing different scientific components, combining scientific and management perspectives, or pooling similar contributions developed in different locations by different research groups. In southern Africa the two largest free-ranging cheetah (Acinonyx jubatus) populations are in Namibia and Botswana, where the majority of cheetahs are located outside protected areas. Consequently, cheetah conservation in these two countries is focussed primarily on the free-ranging populations as well as the mitigation of conflict between humans and cheetahs. In contrast, in neighbouring South Africa, the majority of cheetahs are found in fenced reserves. Nonetheless, conflict between humans and cheetahs remains an issue here. Conservation effort in South Africa is also focussed on managing the geographically isolated cheetah populations as one large meta-population. Relocation is one option among a suite of tools used to resolve human-cheetah conflict in southern Africa. Successfully relocating captured problem cheetahs, and maintaining a viable free-ranging cheetah population, are two environmental issues in cheetah conservation forming the first case study in this thesis. The second case study involves the initiation of blooms of Lyngbya majuscula, a blue-green algae, in Deception Bay, Australia. L. majuscula is a toxic algal bloom which has severe health, ecological and economic impacts on the community located in the vicinity of this algal bloom. Deception Bay is an important tourist destination with its proximity to Brisbane, Australia’s third largest city. Lyngbya is one of several algae considered to be a Harmful Algal Bloom (HAB). This group of algae includes other widespread blooms such as red tides. The occurrence of Lyngbya blooms is not a local phenomenon, but blooms of this toxic weed occur in coastal waters worldwide. With the increase in frequency and extent of these HAB blooms, it is important to gain a better understanding of the underlying factors contributing to the initiation and sustenance of these blooms. This knowledge will contribute to better management practices and the identification of those management actions which could prevent or diminish the severity of these blooms.

The central question addressed in this thesis is whether descriptions of the dynamics of ecological systems at one scale may be effectively used as descriptions of the dynamics of ecological systems at larger scales. This question is addressed in the context of the dynamics of fungal communities. A simple experimental system and complementary theoretical approach, in the form of an individual-based (cellular automaton) model, is presented. Experimental results derived from small-scale systems are used to quantify parameters of the model; results from large-scale experimental systems serve to test the model. The theoretical analyses clearly demonstrate that the dynamics observed are a result of both local and non-local features of the experimental system. In cases such as this the immediate extrapolation of results derived from xperiments conducted out of the context of the community to represent system scale behaviour is not possible. In response to this observation a generic framework is developed to allow the consideration of effects at a range of scales through contextual parameterisation of localised dynamics. The framework is directed toward plant systems where a large body of experimental data exists, and may be parameterised by that experimental data. It represents the essential features of individual interactions in terms of competition for space and resource, and the behaviour of a given plant is described in terms of functional traits. Model runs demonstrate complex community patterns suggestive of a known biological phenomena, succession, that arises as a consequence of the coupling between the community and environment. This coupling may allow the long-term coexistence of species through some particular balance in individual function (traits) across the community. A search mechanism is determined to allow combinations of trait values at the scale of the individual to be assessed for a particular community-scale phenomenon. Initial results demonstrate that this mechanism may identify and converge on combinations of trait values that give rise to, in this case, a simple measure of diversity. The manner in which the generic framework developed may be applied to further the investigation into fungal community dynamics is addressed.

The systems of interest in this study are the spread of epidemics and invasions from a small propagule introduced into an arena that was initially devoid of the given species or stage of illness. In reaction-diffusion models, populations are continuous. Populations at low densities have the same growth functions as populations at high densities. In nature, such low densities would signify extinction of a population or of a disease. This property can be removed from reaction-diffusion models by small changes in the formulation so that small populations become extinct. This can be achieved by the use of a threshold density or an Allee effect, so there is negative growth at low densities. Both these alterations were made to the Fisher model, a predator-prey model and a two stage and a three stage epidemic model. A semi-numerical method, termed the Shooting method, was developed to predict the shapes and velocities of these wave fronts. This was found to correctly predict the velocity, the peak density of the invading stage or species and the width of the wave front. It was found that in oscillatory cases of the multi species models, a high threshold can remove the wave train or wake which would normally follow the wave front, so the wave becomes a soliton. The next step is to investigate probable causes of persistence behind the initial wavefront. To do this, discrete time and space versions of the models were formulated so that experiments investigating persistence can be carried out in a two dimensional arena with less computational effort. The formulations were chosen so that at reasonable time and space steps the discrete models show no behaviour different to that of the reaction diffusion model, and so that the Shooting method could also be used to make predictions about these wavefronts. Three mechanisms of persistence are investigated; environmental heterogeneity, long range dispersal and self organised patterns.

The aim of this Ph.D. was to contribute to the discipline of ecosystems networks, in particular to loop analysis, by improving on the current algorithm implementations, with particular emphasis in developing an approach to couple systems quantitative information to the analytical processes of loop analysis, and through it allow the exploration the mechanism behind a systems responsiveness to perturbations, that is, the importance of both the variables, the structure of linkages between them and the intensity of those linkages. In this thesis, after a presentation of the loop analysis and its main drawback, the inherent lack of associated link intensity and the repercussions these have on the system’s responsiveness, three chapters follow. In Chapter 3, the LevinsAnalysis R package is presented. In this package the improved code and its applications explained and demonstrated through the application of the package functions to a case study, the Savannah Fires (Bodini & Clerici, 2016) model. This case was specifically selected to demonstrate the potential of the package and its novel approach to identification of the importance of linkage strength and path analysis. In Chapter 4, I explore the Caspian Sea network prior to Mnemiopsis leidyi invasion, with the aim of investigating the mechanism behind the changes observed on multiple species and their importance compared with one another, the role that different species, the strength of interaction of the links and paths connecting them might have played in the system response to the different pressures it suffered. The result of this analysis, pointing to the importance of both kilkas and bony fish in the system’s response to perturbations such as overfishing. Phytoplankton also emerges as potentially playing an important role in the system, in particular a possible negative input on this variable seems to be of importance in describing the changes observed in the system. From this chapter also comes about how the strength of interplay between variables and from there the strength of pathways connecting the system play a central role in the Caspian Sea system and its response to press perturbations. In Chapter 5, a discussion is taken on the viability and potential use of loop analysis in the study of systems whose variables lay across the social and the ecological domains: species populations, predators and prey, but also governmental organizations, human dynamics and social mechanisms.
Lo scopo di questo lavoro di dottorato è di contribuire allo sviluppo della scienza delle reti in ambito ecologico. In particolare il lavoro si focalizza sulla tecnica della loop analysis ampliandone le potenzialità dell’algoritmo implementato su piattaforma informatizzata introducendo un’estensione quantitativa dell’algoritmo di predizione. Lo scopo è quello di rendere più efficace la ricerca dei maccanismi alla base delle risposte degli ecosistemi agli eventi perturbativi. Dopo una presentazione della metodologia e dei suoi limiti, con particolare attenzione alla mancanza di quantificazione dei coefficienti di interazione tra le component dell’ecosistema la tesi si sviluppa in tre capitoli. Nel capitolo 3 è presentato il software “LevinsAnalysis”, che è stato sviluppato in ambiente R. Lo compongono diverse funzioni che consentono una più agevole applicazione dell’algoritmo previsionale a qualsiasi rete interattiva di tipo ecologico (e non solo). L’applicabilità di tali funzioni è sviluppata attraverso un caso di studio inerente l’ecologia degli ambienti di savana. Il Capitolo 4 è dedicato a una applicazione ecologica e riguarda lo studio della comunità del Mar Caspio finalizzato alla comprensione dei meccanismi che hanno generato le trasformazioni ecologiche osservate in quell’ecosistema, con particolare riferimento alla riduzione drastica di alcune specie ittiche e di mammiferi e all’esplosione degli organismi gelatinosi. Lo studio ha mostrato l’importanza di alcune componenti dal punto di vista dinamico, e ha consentito di formulare ipotesi causative sulle risposte dell’ecosistema alle perturbazioni, risposte che si ricavano dallo studio dei percorsi di interazione e della loro intensità. Il capitolo 5 è sostanzialmente un capitolo di discussione in cui si enfatizzano gli aspetti applicativi della loop analysis anche in contesti non strettamente ecologici, data la versatilità della tecnica. Così lo strumento diventa importante per analizzare sistemi socio-ecologici, che considerano, cioè, non solo variabili ecologiche come prede e predatori ma anche le interferenze di organizzazioni governative, e gli effetti delle dinamiche sociali.

Despite the debate about the definition and subject of ecology, it is actually undeniable that the scientific study of the distribution and abundance of organisms, together with their underlying processes, is among the main subjects of ecology . Therefore, counting animals, and understanding the mechanisms that drive occurrence and abundance over space and time, have been the focus of many studies in animal science. Since population size is one of the fundamental state variables in ecology, obtaining accurate information on population abundance is of primary importance for conservation, monitoring and management of animal populations. Moreover, accurate population estimates allow the analysis of the temporal variation of abundance (i.e. trends detection), which is a major objective in species conservation and monitoring programs. Population abundance, however, is not the only candidate variable for ecological and conservation studies: other variables may be used to infer the status of a community or a population. For example, the proportion of area occupied by a species, i.e. Occupancy, is another important state variable of ecology. Although the use of Occupancy, instead of abundance, may appear limiting for drawing inferences about the status of a population or a species, Occupancy is actually related to temporal stability of populations. Occupancy also reflects habitat choice (or resource selection) and a higher Occupancy is usually linked to higher abundances . No matter what state variable we decide to adopt, the inference about abundance and Occupancy must face a critical aspect: these two variables, indeed, cannot be directly measured, because species occurrence and population abundance are always subject to imperfect detection. Usually, only a fraction of the population of interest is encountered and available for sampling, while an unknown fraction is unavailable and undetected. This issue led ecologists to the development of several techniques, for taking into account imperfect detection, and obtaining unbiased estimates of population abundance. Several methods rely on individual identification, such as capture-mark-recapture (CMR) and removal sampling, other methods take into account auxiliary data, such as distance sampling. These methods are widely capable of overcoming the issue of imperfect detection: however, they may be expensive in terms of costs and efforts, they can be applied to few populations at a time and they are not practical for large scale monitoring. In the last two decades, the development and application of Hierarchical Models (HMs) in ecology contributed to overcome this issue. HMs, from a mathematical point of view, are a sequence of probability models, ordered by their conditional probability structure, that describe conditionally dependent random variables. In other terms, and for what concerns the ecological applications in the present thesis, HM describe both the state variable , and the measurement error in the observation process. HMs are indeed composed by a sub-model for the true state of interest, that may be Occupancy or abundance, and a sub-model for the observation process, which allows to estimate detection probability. From the application of HMs in ecology, two main tools emerged: Occupancy models, and N-mixture models. From these foundational works, many other models have been developed, but at a bottom level HMs in ecology share some common principles and characteristics: i) they usually require a spatially structured design (several sampling locations), ii) they rely on repeated surveys over sampling locations (sampling sites should be visited several times), iii) they do not require individual identification, since they use presence/pseudo-absence or count data, and iv) the ecoogical and the detection process can be modelled as a function of environmental or sampling covariates. These characteristics make HMs a useful framework for scientific studies in ecology and also for conservation and management applications. The metapopulation design of HMs indeed allows to obtain estimates of the state variable for several populations, or wide study areas, at once. Abundance (but also other demographic parameters such as recruitment or survival), Occupancy and detection probability can be inferred on the basis of environmental variables or management options, trough the inclusion of appropriate covariates in the modelling process. Last but not least, the cost-effectiveness of HMs: the use of cheap methods to collect data, such as simple counts and presence/psesudoabsence data, make these methods highly recommended when time and economic resources are limited. Indeed, the application of HMs seems to be increasing over time, since their first formulation, and they received great interest by both scientists and managers in several fields of environmental science. The aim of the present thesis is to evaluate the application of HMs in the ecology and conservation of Amphibians and Reptiles.

Thesis submitted to the Faculty of Sciences and Technology, New University of Lisbon, for the degree of Doctor of Philosophy in Environmental Sciences
Over the past few decades, policy-makers have defined new instruments to address coastal ecosystem degradation. Emerging coastal management frameworks highlight the use of the best available knowledge about the ecosystem to manage coastal resources and maintain ecosystem’s services. Progress is required, however, in translating data into useful knowledge for environmental problem solving. This thesis aims to contribute to research assessing changes in coastal ecosystems and benefits generated due to management actions (or to the lack thereof). The overall objectives are to assess the ecological and economic impacts of existing management programmes, as well as future response scenarios and to translate the outcomes into useful information for managers. To address these objectives, three different approaches were developed: A multilayered ecosystem model A multilayered ecosystem model was developed to simulate management scenarios that account for the cumulative impacts of multiple uses of coastal zones. This modelling field is still at an early stage of development and is crucial, for instance, to simulate the impacts of aquaculture activities on the ecosystem, accounting for multiple farms and their interactions with other coastal activities. The multilayered ecosystem model is applied in this thesis to test scenarios designed to improve water quality and manage aquaculture. An ecological-economic assessment methodology (ΔDPSIR approach) The Differential Drivers-Pressure-State-Impact-Response (ΔDPSIR) approach further develops the integrated approach by providing an explicit link between ecological and economic information related to the use and management of coastal ecosystems. Furthermore, the ΔDPSIR approach provides a framework to synthesise scientific data into useful information for the evaluation of previously adopted policies and future response scenarios. The ΔDPSIR application is tested using different datasets and scales of analysis, including: (i)assessment of the ecological-economic impacts of the scenarios at the waterbody/watershed level, using the multilayered ecosystem model outputs, and (ii) evaluation of the ecologicaleconomic effects of aquaculture options at the individual aquaculture level, using data from an abalone farm. These are two important scale of analysis for the development of an ecosystem approach to aquaculture.A dynamic ecological-economic model (MARKET model) One of the missing links in ecosystem modelling is with economics. The MARKET model was developed to simulate the feedbacks between the ecological-economic components of aquaculture production. This model was applied to simulate shellfish production in a given ecosystem under different assumptions for price and income growth rates and the maximum available area for cultivation. Further application of the MARKET model at a wider scale might be useful for understanding the ecological and economic limitations on global aquaculture production. This integrated ecological-economic modelling and assessment approach can be further applied to address new coastal management issues, such as coastal vulnerability to natural catastrophes. It can also support implementation of current legislation and policies, such as the EU Integrated Coastal Zone Management recommendation or the development of River Basin Management Plans following the EU Water Framework Directive requirements. On the other hand, the approach can address recurring coastal management needs, such as the assessment of the outcomes of past or on-going coastal management plans worldwide, in order to detect symptoms of the overuse and misuse of coastal ecosystems.
Portuguese Foundation for Science and Technology(FCT) as a Ph.D. scholarship (SFRH/BD/25131/2005.European Union, Sixth Framework Programme FP6-2002-INCO-DEV-1 SPEAR (INCO-CT-2004-510706) project

2013/2014
La tesi descrive il lavoro effettuato e i progressi raggiunti durante i miei tre anni di dottorato, volti allo studio della distribuzione delle concentrazioni di radon in ambienti indoor, nello specifico in abitazioni private del Friuli Venezia Giulia. Il principale obiettivo è stato la definizione geografica delle cosiddette radon prone areas (RPA), ovvero le aree con le più alte probabilità di trovare concentrazioni di radon più elevate. Nonostante ciò, molte analisi supplementari sono state effettuate per migliorare la suddetta definizione e per ampliare il bagaglio di conoscenze riguardante il radon indoor a tutto tondo. Abstract La prima parte della tesi è un'introduzione al corpo principale del testo e introduce il problema ambientale radon al lettore. Abstract Nel capitolo uno sono elencate i principali dettagli sul ^{222}Rn , il più frequente isotopo del suo tipo in natura, e un veloce excursus volto alla descrizione delle sue proprietà fisiche, in particolare i meccanismi di trasposto da e all'interno del suolo (che ne è la principale sorgente). Successivamente, i principali meccanismi di entrata in ambienti chiusi sono evidenziati con esempi dei modelli matematici che li descrivono. Abstract Il secondo capitolo è invece la presentazione del problema sanitario posto dal radon. Il suo processo di decadimento e i suoi “figli” sono presentati come principali contributori alla dose assorbita media di radiazione nella popolazione mondiale e il più comunemente accettato modello matematico di impatto viene descritto. Alcuni passaggi sono poi dedicati agli aspetti legislativi, con la legislazione corrente e i passaggi che hanno portato alla attuale situazione. Abstract Il terzo capitolo è la descrizione delle campagne di misura che hanno prodotto i dati sui quali ho lavorato. Le campagne sono due, la prima (RPA2006) si è conclusa otto anni fa, ma i dati non erano ancora stati completamente analizzati. Il mio lavoro principale nei primi due anni di phd è stato dedicato all'analisi dei suddetti, con le tecniche statistiche più raffinate tra quelle applicate in questo campo. La seconda campagna (RPA2014) è terminata nel Novembre del 2014 ed è stata curata completamente da me (con l'ovvio aiuto del personale ARPA), sia per quanto riguarda la logistica, sia per l'aspetto analitico. Abstract La seconda parte della tesi contiene analisi originali sui dati e può essere considerata una collezione di analisi esplorative, precedenti all'uso di tecniche e modelli di interpolazione. Abstract Il capitolo quattro può esser visto come una introduzione alle tecniche esplorative, perché introduce le principali ipotesi usate nella statistica spaziale non parametrica. A parte un piccolo accenno alla fine del capitolo, nessuna definizione richiede la conoscenza delle proprietà fisiche o statistiche del radon. Contiene già le prime mappe non parametriche, come esempi di applicazione delle ipotesi scritte nel testo. In alcune analoghe campagne effettuate in altre zone del pianeta, tali mappe sono spesso considerate sufficienti per la definizione delle RPA. Abstract Il quinto capitolo introduce, invece, le caratteristiche statistiche del radon, descrivendo le prime peculiarità che ho riconosciuto nei dati e che ho cercato di trattare. Nello specifico, gli argomenti qui affrontati sono la quasi-lognormalità, e conseguentemente la deviazione da essa, e l'eventuale multigaussianità. Il clustering (naturale e preferenziale) ha occupato una grossa parte del tempo speso in questi tre anni, di conseguenza alcuni algoritmi di analisi adottati per verificarne le proprietà sono descritti e esemplificati. Abstract Il capitolo sei spiega le analisi, usualmente univariate, che ho condotto con tutte le variabili covariate possibilmente legate al radon. Il corpo di tale capitolo è diviso in due paragrafi (e relativi sottoparagrafi) rispettivamente riguardanti le covariate geologiche e di housing (dettagli edilizi). Essendo il radon una variabile ambientale, molte delle covariate possibilmente legate ad esso sono categoriche, poiché frutto di opinione o valutazione di esperti. Di conseguenza il loro studio è basato principalmente su boxplot e test di correlazione statistica, usualmente non parametrici. Abstract La parte III della tesi è la parte di cui all'inizio del sommario, contenente gli studi e i modelli statistici principali usati per raffinare le analisi sviluppate nella parte precedente. Abstract Il settimo capitolo è un minuzioso studio geostatistico fatto sul database RPA2006. Il capitolo otto esamina invece gli studi di correlazione effettuati sul database RPA2014, dedicato alla verifica del se e come il radon varia all'interno di un edificio tra differenti piani e stanze. Abstract Le appendici non sono originali e comprendono: 1) la collezione degli strumenti statistici usati in questo elaborato, con le loro definizioni matematiche (ove possibile); 2) un'introduzione alla teoria geostatistica, nella quale è possibile trovare, almeno, tutti i chiarimenti necessari alla comprensione, almeno generale, dell'analisi fatta.
XXVII Ciclo
1985

Species distributions are often limited by environmental factors and according to the abundant—centre hypothesis, abundance should be highest Where the environment is most favourable for the species. So, do the same environmental factors determine occurrence and abundance patterns inside the range? I examined this question using Arthroleptella lightfooti, a species of frog from the family of Pyxicephalidae, endemic to the mountains of the Cape peninsula. South Africa. I used density estimates obtained from acoustic Spatially Explicit Capture Recapture (aSCR) methods and data from an acoustic survey using an array of 6 microphones to construct the first Peninsula wide population-density surface for this visually cryptic but acoustically active species. The analysis consisted of three stages. The first involved creating two sets of data from the original: one shows whether the species is present or not and the other indicates the density when the species is present. The second stage consisted of fitting a Hurdle Model to the data where the presence data is modelled using logistic regression and the density data is separately modelled using ordinary linear regression. The third stage involved combining the two models to estimate the expected density of the species. Confidence intervals were built using non-parametric bootstrapping. It was found that covariates explaining variation in occurrence were not the same as those explaining variation in density, suggesting that processes determining occurrence were not always those determining density. Of the environmental conditions examined, although predictive of occurrence, were generally poor predictors of A. lightfooti density. Presence of the Lightfoot’s moss frog was largely explained by topographic features and availability of water. In contrast. predictions of density were only weakly related to these same environmental factors and in some cases contradicting one another. The second part of this study produces the first Peninsula wide population density surface of A. 11'ghtfo0t1'. At the same time, it assesses the ability of using opportunistically collected presence-only records in combination with the higher quality density data to improve the estimation of expected population-density surface of A. Iightfooti. The presence-only records were constructed into a habitat suitability map using an ensemble of species distribution models. The habitat suitability map was then integrated in the modelling framework as a covariate in order to improve the estimation of expected population—(lensity surface of A. liglitfooti. However, the habitat suitability covariate resulted as being uninformative.

Thesis (PhD (Conservation Ecology and Entomology))--Stellenbosch University, 2008.
Dispersal plays an essential role in determining the distribution of populations of species, especially species expanding their ranges. Two disciplines are concerned with gaining understanding of spread of species, namely restoration ecology and invasion biology. Con- ceptual understanding of dispersal, its mechanisms and its management is essential to both disciplines. Nevertheless, the disciplines have quite opposite objectives: in restoration ecol- ogy, spread of indigenous species into transformed landscapes is promoted, while invasion biology aims to prevent the (further) spread of alien species into pristine or restored habi- tats. Despite these two opposite objectives of facilitating spread and preventing spread of their respective target species, these disciplines have essentially the same requirements in terms of information needed for restoration. In this thesis, I will present two modelling studies—one looking at the impact of two different seed-feeding alien control agents on the spread of Hakea sericea, the other investigating the recolonisation by Dicerothamnus rhinocerotis of an old field dominated by Cynodon dactylon. Based on these studies, I will draw conclusions for the management in each case. In a second step, I will compare these two seemingly-different studies and draw conclusions on how these two disciplines can learn from each other, and how conclusions drawn and management recommendations developed for the one discipline can be translated for the other. The invasion biology study concluded that seed-feeding biocontrol agents do have a considerable impact on the velocity of the spread of the target species. In addition, management recommendations included the possibility of substituting seed-feeding biocontrol agents with an increased fire frequency where the negative impact on natural vegetation, on the site invaded by the target species, is acceptable. The restoration study concluded that the main impact on the velocity of spread, and the speed of the return of the shrub species onto the old fields, is the availability of micro-sites. A sensitivity analysis showed the even a slight change from 1% to 2% increases the velocity and pattern of spread dramatically. The other parameters playing an important role are the mean rate of establishment and the time span between

The Western Honeybee (Apis mellifera) is an important species, not only ecologically and economically, but as a source of recreation to many. The pollination services the species provides benefit a number of crops worldwide, and, as the honeybee is domesticated and kept in hives, can be directed commercially. Recently, although overall global stocks are growing, there have been reports of high colony losses worldwide. Due to the value of this species, this is a worrying trend. There are many stressors facing the honeybee, both natural and anthropogenic in origin. Two of the most prevalent, both in the popular media and in monitoring studies of colonies are insecticidal pesticides and the parasitic mite Varroa destructor. Due to the difficulties and expense of carrying out large-scale field studies required to properly investigate the multiple stressors and their interaction, the use of modelling to explore the problem and direct field work is a vital resource. In this thesis, I present research using the BEEHAVE model and a novel model to explore the exposure and potential impacts of pesticides and the varroa mite. The results show that the timing of a pesticide exposure in the year greatly changes the resultant impact on the colony. Pesticides can have many impacts on different stages of the honeybee, and I show that increased mortalities of different life stages of the honeybee (larvae, in-hive adults, foragers) and decreasing egg-laying rate, affect the development of the colony to different extents at different times of the year, with the colony being highly sensitive to losses of in-hive bees during the summer, and the over-wintering bees at the beginning and end of the year. A novel model is presented exploring the in-hive distribution of pesticide-containing nectar and the effect it has on the exposure of in-hive receiving bees and larvae. The results from this model show that, in-hive distribution is not important to consider for the adults, but may be for the larvae. The landscape, specifically the distance to pesticide-treated forage in relation to untreated forage also has an impact on the result of a pesticide exposure, and this is a potential avenue for the mitigation of pesticide impacts. I also present work towards the validation of BEEHAVE with regards to varroa mite infestation, finding that the model results are close to empirical data, both for datasets from the UK and USA, but the impact of varroa is underestimated. The results are discussed in the context of pesticide risk assessment, the mitigation of potential stressors and the modelling of the varroa mite. The BEEHAVE model is a vital tool for many applications, one being the risk assessment of pesticides. A review of the model by the European Food Security Agency (EFSA) highlighted extensions to the model required before it can be incorporated. This research begins to answer some questions asked in that review.

Conservation of biodiversity and sustainable resource use are central aims within ecology. This thesis focuses on the current data and environmental frameworks used to support these aims across different states in Europe. In particular, it examines the impact of geo-political boundaries on data-use, funding and planning for temporal movement of species in response to climate change. It also examines the current environmental framework agreements in Europe and their capacity to deal with trans-boundary aspects of biodiversity change. Through examination of European biodiversity datasets, undertaking species distribution modelling of forest taxa, examining economic data, palaeo-ecological data, and assessing international environmental framework agreements, this thesis identifies a number of important knowledge gaps. Probably unsurprisingly, the distribution of biodiversity in Europe mostly does not match political entities, all of which have individual aims, financial resources, and biodiversity management regimes in place. All have a significant impact on biodiversity conservation planning because i) the use of geo-politically truncated data influences modelling predictions, ii) financial commitment to biodiversity conservation varies between countries influencing success outcomes, iii) biodiversity persistence in current and future climate change does not recognise geo-political boundaries, and iv) many of the key environmental frameworks are implemented within countries and do not considering trans-boundary issues. Overall these findings significantly improve the understanding of conservation and resource management in Europe and fill a number of important knowledge gaps. They highlight the importance of appropriate trans-boundary ecological datasets and the need for more consistency across Europe in financial resources for biodiversity conservation. They also highlight the need for appreciation of areas of high-persistent biodiversity regardless of geo-political boundaries and environmental framework agreements that support cross-border conservation measures.

Compositional modelling is one of the most important knowledge-based approaches to automating domain model construction. However, its use has been limited to physical systems due to the specific presumptions made by existing techniques. Based on a critical survey of existing compositional modellers, the strengths and limitations of compositional modelling for its application in the ecological domain are identified and addressed. The thesis presents an approach for effectively building and (re-)using repositories of models of ecological systems, although the underlying methods are domainindependent. It works by translating the compositional modelling problem into a dynamic constraint satisfaction problem (DCSP). This enables the user of the compositional modeller to specify requirements to the model selection process and to find an appropriate model by the use of efficient DCSP solution techniques. In addition to hard dynamic constraints over the modelling choices, the ecologist/ user of the automated modeller may also have a set of preferences over these options. Because ecological models are typically gross abstractions of very complex and yet only partially understood systems, information on which modelling approach is better is limited, and opinions differ between ecologists. As existing preference calculi are not designed for reasoning with such information, a calculus of partially ordered preferences, rooted in order-of-magnitude reasoning, is also devised within this dissertation. The combination of the dynamic constraint satisfaction problem derived from compositional modelling with the preferences provided by the user, forms a novel type of constraint satisfaction problem: a dynamic preference constraint satisfaction problem (DPCSP). In this thesis, four algorithms to solve such DPCSPs are presented and experimental results on their performance discussed. The resulting algorithms to translate a compositional modelling problem into a DCSP, the order-of-magnitude preference calculus and one of the DPCSP solution algorithms constitute an automated compositional modeller. Its suitability for ecological model construction is demonstrated by applications to two sample domains: a set of small population dynamics models and a large model on Mediterranean vegetation growth. The corresponding knowledge bases and how they are used as part of compositional ecological modelling are explained in detail.

Population modelling is recognised as a potentially useful tool for pesticide risk assessment for vertebrate species. The European Food Safety Authority, which provids guidance on how to conduct such risk assessments in the EU, recommends using the woodpigeon (Columba palumbus) as a representative non-target species for a variety of crops, including oilseed rape and cereals. The woodpigeon was extensively studied in the UK for the second half of the twentieth century. The aim of this PhD was to produce a population model of wood pigeons for use in higher-tier pesticide risk assessment with a two-fold purpose: prediction of exposure and population-level effects of this exposure. In the thesis I first discussed how computer simulations are used for these purposes. Then I described the design of the woodpigeon model together with extensive reference to the scientific literature that backed the model and the tests conducted to assure the model credibility. The pattern-oriented evaluation was conducted to choose which foraging strategy allows for the best reproduction of data describing spatial and temporal characteristics of woodpigeon foraging. Memory-based foraging with flocking behaviour outperformed both optimal and random strategies. Next, I evaluated the model with respect to the responses of woodpigeon population to three stressors: nest destruction, shooting and pesticide application. Following the evaluation studies, the model was used to derive and analyse three measures of population-level exposure to pesticides: maximum dose, cumulative amount and duration of exposure. Life stage and pesticide application time proved important determinants of the exposure level. Finally the model was applied to check how the way of modelling exposure influenced the population size and breeding success. The realistically simulated exposure caused long-term damage to the population size and affected the breeding success more than exposure causing all the lethal effects within one day. I discussed the major findings of the thesis in the light of advances in applying population modelling for pesticide risk assessments and possible future application of the woodpigeon model.

Bacillus anthracis is the causal agent of anthrax which primarily affects ungulates, occasionally carnivores and less frequently humans. The endospores of this soil-borne bacterium are highly resistant to extreme conditions, and under ideal conditions, anthrax spores can survive for many years in the soil. The bacterium is generally found in soil at sites where infected animals have died. When these spores are exposed, they have the potential to be ingested by a mammalian species which could lead to an anthrax outbreak. Anthrax is almost never transmitted directly from host to host, but is rather ingested by herbivores while drinking, grazing or browsing in a contaminated environment, with the exception of scavengers and carnivores consuming infected prey. Anthrax is known to be endemic in the northern part of Kruger National Park (KNP) in South Africa (SA), with occasional epidemics spreading southward into the non-endemic areas. The aim of this study is to identify and map areas that are ecologically suitable for the harbouring of B. anthracis spores within the KNP. Anthrax surveillance data and selected environmental variables were used as inputs to the maximum entropy (Maxent) species distribution modelling method. Five-hundred and ninety-seven anthrax occurrence records, dating from the year 1988 to 2011, were extracted from the Skukuza State Veterinary Office’s database. A total of 40 environmental variables were used and their relative contribution to predicting suitability for anthrax occurrence was evaluated using Maxent software (version 3.3.3k). Variables showing the highest gain were then used for subsequent, refined model iterations until the final model parameters were established. The environmental variables that contributed the most to the occurrence of anthrax were soil type, normalized difference vegetation index (NDVI), land type and precipitation. A map was created using a geographic information system (GIS) that illustrates the sites where anthrax spores are most likely to occur throughout the Park. This included the known endemic Pafuri region as well as the low lying soils along the Shingwedzi-Phugwane-Bubube rivers and the Letaba-Olifants river drainage area. The outputs of this study could guide future targeted surveillance efforts to focus on areas predicted to be highly suitable for anthrax, especially since the KNP uses passive surveillance to detect anthrax outbreaks. Knowing where to look can improve sampling efficiency and lead to increased understanding of the ecology of anthrax within the KNP.
Dissertation (MMedVet)--University of Pretoria, 2013.
Production Animal Studies
unrestricted

Questa ricerca intende contribuire alla discussione sulla riduzione del rischio disastri (DRR), esplorando come le comunità locali dovrebbero adattarsi ai pericoli che le circondano. La prima parte riporta la teoria della panarchia alle dinamiche del rischio. Il modello teorico che ne deriva, la Panarchia Sociale-Ecologica, descrive le condizioni di rischio e permette di riconoscere i nuclei del DRR: la resilienza ai disastri e la sostenibilità ambientale. Il modello fornisce le basi per lo sviluppo di una Valutazione Combinata di Resilienza e Sostenibilità, concentrata sul rischio inondazione alla scala comunale. La seconda parte svolge un’analisi quantitativa attraverso indicatori, che identificano e caratterizzano i livelli di resilienza e sostenibilità. La terza parte impiega strumenti qualitativi (questionari) per raccogliere le percezioni delle comunità locali sui rischi presenti nei loro Comuni. L’analisi è stata applicata a due casi studio, la Regione Marche (Italia) e l’Hokkaidō (Giappone). I risultati mostrano il ruolo delle inondazioni nel determinare la resilienza locale, e degli impatti antropici per la sostenibilità. Le criticità maggiori sono concentrate nelle aree montane/collinari. Allo stesso tempo, aspetti di welfare e sicurezza sociale risultano fondamentali per formare la resilienza, così come la presenza di vegetazione lo è per la sostenibilità. Inoltre, emerge una sostanziale differenza fra misurazione e percezione di resilienza e sostenibilità, generalmente in senso peggiorativo. In generale, ulteriori sforzi dovrebbero essere diretti alle aree interne, benché la regione intera gioverebbe del consolidamento della resilienza locale. Inoltre, le comunità sembrano molto sensibili ai temi ambientali, per cui potrebbero appoggiare sforzi per aumentare la sostenibilità. Infine, questi studi possono contribuire alle strategie DRR, per promuovere l’adattamento trasformativo delle comunità locali, reso urgente dall’esasperazione degli eventi estremi.
This research intends to contribute to the discussion on disaster risk reduction (DRR), investigating the question of how local communities should adjust to the surrounding threats. The first part adapted the panarchy heuristics to risk dynamics. The drawn theoretical model, the Social-Ecological Panarchy, could describe the conditions of risk and allow to recognise the two cores of DRR: disaster resilience and environmental sustainability. The model supported the development of a Combined Assessment of Resilience and Sustainability, focused on flood risk at the Municipal scale. The second part of the research performed a quantitative analysis through numerical indicators, that identified and characterised the levels of resilience and sustainability. The third part of the research employed qualitative tools (questionnaires) to gather the thoughts of local communities on the risks affecting their Municipalities. The analysis was applied to two case studies, Marche Region (Italy) and Hokkaidō (Japan). Results evidenced the role of flood events in determining the resilience capacities of local communities, and of the anthropic impacts for defining their sustainability. Most critical issues lied in the mountainous/hill areas. At the same time, social welfare and protection appeared pivotal in building local resilience, while the presence of vegetation shaped sustainability. Besides, a substantial mismatch emerged between assessed and perceived conditions of resilience and sustainability, generally in negative terms. Overall, it appeared that further efforts should be tailored to the innermost areas, though the overall region might benefit from consolidated resilience. At the same time, local populations seemed highly responsive to environmental issues, possibly endorsing the enhancement of sustainability. Eventually, these insights might inform risk reduction strategies, to foster a transformative adaptation of local communities, urged by exacerbating disruptive threats.

Ecological modelling problems have characteristics both featured in other modelling fields and specific ones, hence, methods developed and tested in other research areas may not be suitable for modelling ecological problems or may perform poorly when used on ecological data. This thesis identifies issues associated with the techniques typically used for solving ecological problems and develops new generic methods for decision support, especially suitable for ecological data modelling, which are characterised by: (1) adaptive learning, (2) knowledge discovery and (3) accurate prediction. These new methods have been successfully applied to challenging real world ecological problems. Despite the fact that the number of possible applications of computational intelligence methods in ecology is vast, this thesis primarily concentrates on two problems: (1) species establishment prediction and (2) environmental monitoring. Our review of recent papers suggests that multi-layer perceptron networks trained using the backpropagation algorithm are most widely used of all artificial neural networks for forecasting pest insect invasions. While the multi-layer perceptron networks are appropriate for modelling complex nonlinear relationships, they have rather limited exploratory capabilities and are difficult to adapt to dynamically changing data. In this thesis an approach that addresses these limitations is proposed. We found that environmental monitoring applications could benefit from having an intelligent taste recognition system possibly embedded in an autonomous robot. Hence, this thesis reviews the current knowledge on taste recognition and proposes a biologically inspired artificial model of taste recognition based on biologically plausible spiking neurons. The model is dynamic and is capable of learning new tastants as they become available. Furthermore, the model builds a knowledge base that can be extracted during or after the learning process in form of IF-THEN fuzzy rules. It also comprises a layer that simulates the influence of taste receptor cells on the activity of their adjacent cells. These features increase the biological relevance of the model compared to other current taste recognition models. The proposed model was implemented in software on a single personal computer and in hardware on an Altera FPGA chip. Both implementations were applied to two real-world taste datasets.In addition, for the first time the applicability of transductive reasoning for forecasting the establishment potential of pest insects into new locations was investigated. For this purpose four types of predictive models, built using inductive and transductive reasoning, were used for predicting the distributions of three pest insects. The models were evaluated in terms of their predictive accuracy and their ability to discover patterns in the modelling data. The results obtained indicate that evolving connectionist systems can be successfully used for building predictive distribution models and environmental monitoring systems. The features available in the proposed dynamic systems, such as on-line learning and knowledge discovery, are needed to improve our knowledge of the species distributions. This work laid down the foundation for a number of interesting future projects in the field of ecological modelling, robotics, pervasive computing and pattern recognition that can be undertaken separately or in sequence.

In this study the behaviour of multivariate plankton communities and their relationships with climate is explored. Existing statistical methodology is adapted to analyse both the plankton communities and sea surface temperature. In the first part of this study a large scale exploratory analysis is applied using principal component analysis. Dominant temporal trends and spatial patterns for a number of indicator species and the joint responses of functional groups of species are found.The community analysis focuses on on the zooplankton and the phytoplankton, the latter respresented by diatoms. This research is novel because the full multivariate structure of the plankton data has not been studied across communities before. The common trends are regressed against different climate signals to determine dominant drivers and cluster analysis identifies regions based on species. In the second part ‘regime shifts’ described by changes in ecoregions are explored. Whilst changes in spatial patterns over time have been studied over indicator species, this study describes the shift across communities, providing an overview of how the ‘regime shift’ is differently expressed for the two species groups. To explore changes in biogeographical patterns, the data is then divided in to a pre-1985 and post-1985 regimes. The results show a northwards movement of zooplankton species and increased spatial structure across the diatom group, following the bathymetry. In the final part the model is used to predict vulnerability of different indicator species and the community as a whole to changes in climate drivers across space, which is used to find climate change ‘hotspots’. Vulnerability is defined as a significant change in abundance in response to a relatively small change in the climate signal. Vulnerability is also explored at different scales. These results highlight the spatial inhomogeneity of species responses and are of great interest to environmental policy makers.

This thesis proposes a collection of analytical and computational methods for inferring an underlying social structure of a given population, observed only via timestamped occurrences of its members across a range of locations. It shows that such data streams have a modular and temporally-focused structure, neither fully ordered nor completely random, with individuals appearing in "gathering events". By exploiting such structure, the thesis proposes an appropriate mapping of those spatio-temporal data streams to a social network, based on the co-occurrences of agents across gathering events, while capturing the uncertainty over social ties via the use of probability distributions. Given the extracted graphs mentioned above, an approach is proposed for studying their community organisation. The method considers communities as explanatory variables for the observed interactions, producing overlapping partitions and node membership scores to groups. The aforementioned models are motivated by a large ongoing experiment at Wytham woods, Oxford, where a population of Parus major wild birds is tagged with RFID devices and a grid of feeding locations generates thousands of spatio-temporal records each year. The methods proposed are applied on such data set to demonstrate how they can be used to explore wild bird sociality, reveal its internal organisation across a variety of different scales and provide insights into important biological processes relating to mating pair formation.

The Gulf of Aqaba represents a small scale, easy to access, regional analogue of larger oceanic oligotrophic systems. In this Gulf, the seasonal cycles of stratification and mixing drives the seasonal phytoplankton dynamics. In summer and fall, when nutrient concentrations are very low, Prochlorococcus and Synechococcus are more abundant in the surface water. This two populations are exposed to phosphate limitation. During winter mixing, when nutrient concentrations are high, Chlorophyceae and Cryptophyceae are dominant but scarce or absent during summer. In this study it was tried to develop a simulation model based on historical data to predict the phytoplankton dynamics in the northern Gulf of Aqaba. The purpose is to understand what forces operate, and how, to determine the phytoplankton dynamics in this Gulf. To make the models data sampled in two different sampling station (Fish Farm Station and Station A) were used. The data of chemical, biological and physical factors, are available from 14th January 2007 to 28th December 2009. The Fish Farm Station point was near a Fish Farm that was operational until 17th June 2008, complete closure date of the Fish Farm, about halfway through the total sampling time. The Station A sampling point is about 13 Km away from the Fish Farm Station. To build the model, the MATLAB software was used (version 7.6.0.324 R2008a), in particular a tool named Simulink. The Fish Farm Station models shows that the Fish Farm activity has altered the nutrient concentrations and as a consequence the normal phytoplankton dynamics. Despite the distance between the two sampling stations, there might be an influence from the Fish Farm activities also in the Station A ecosystem. The models about this sampling station shows that the Fish Farm impact appears to be much lower than the impact in the Fish Farm Station, because the phytoplankton dynamics appears to be driven mainly by the seasonal mixing cycle.

Current practice for landscape reconstruction following opencast mining relies on topographic reconstruction, adaptive land management and botanical characterisation. Environmental processes may be altered where reconstructed landforms have significant relief. Consequently, environmental outcomes in cases where there is large scale land forming are unpredictable. Moreover, landscape restoration lacks an integrated methodology, and while many mine closures have detailed ecosystem and biodiversity objectives based on natural analogue areas there has been no reliable way to design these objectives into mine landforms. The methods used in landscape restorations to describe reference conditions are based on generalised environmental factors using regional information and incorporating conceptual models. Such models lack the precision and accuracy required to understand and restore hillslope environmental pattern at mine sites. However, methodological integration and statistical inference models underpinning the spatial inference methods in conservation and landscape ecology, and pedology may be applied to solve this problem. These inference models utilise digital terrain models as the core environmental data incorporating ecological theory to predict biodiversity and species distribution. Also, numerical mass balance models such as water and solute balance, which have been applied to understand environmental processes in landscapes, can be used to assess mine landform design. The objective of the work reported here was to investigate environmental variation, with sufficient accuracy and precision, in natural landscapes to design mature mine landforms and to demonstrate the capacity to predict ecological outcomes. This would extend current best practice - designing mine landforms with predictable hydrological and geotechnical outcomes needed to protect off-site environmental conditions – to the on-site environment after closure. The specific aims of this thesis were to: (i) evaluate the predictability of ecosystems based on regional ecological mapping: (ii) develop and evaluate quantitative, site specific environmental mapping and natural analogue selection methodology; (iii) evaluate a trial final landform cover (reconstructed soil) using water balance, water chemistry monitoring; (iv) design and evaluate a conceptual mine landform through the assessment of environmental processes in natural analogue areas; and (v) make valid predictions of revegetation outcomes on the conceptual landform. In meeting these aims, links between ecological theory, landscape analysis and the current practice in mine landform design were identified. The first phase of the thesis involved environmental investigations and surveys of extensive savanna environments on the Tiwi Islands (7320 km-2) and similar environments in the vicinity of Ranger uranium mine (150 km-2) in northern Australia. This first phase, reported in Chapter 3, investigated the reliability of conceptual landscape models used in regional ecological mapping in predicting ecological patterns in terms of vegetation and soil. The Tiwi Islands was selected because of the relatively uniform parent material and its simplified climate. This allowed the study of physiographic control of soil and vegetation patterns. The results identified correlations between vegetation pattern and landform that were confounded by a subjective and complex land unit model of ecosystems. This investigation enabled the development methodological approach to analogue selection and ecological modelling at Ranger uranium mine – a site that will require a restoration approach so as to meet environmental closure objectives. The second phase is the methodological development – involving an initial reconnaissance, is presented in Chapter 4. This phase was aimed at selecting natural analogue areas for mined land restoration. Environmental pattern recognition involving classification, ordination and network analysis was implemented based on methods of conservation ecology. This led to quantitative landscape model to identify natural analogue areas and design ecosystem surveys. This quantitative landscape model incorporated a grid survey of vegetation and soil variation into a nearby analogue landform that matched the area of mine disturbance. This analogue landform encapsulates the entire ecosystem types observed on rocky substrates in the broader reconnaissance survey. The natural analogue selection incorporated a combination of digital terrain analysis and k-means clustering of primary and secondary terrain variables to classify habitat variation on hillslopes. Landscapes with similar extent to the mine landscape were identified from numerical similarity measures (Bray-Curtis) of fine grained habitat variation and summarised using a dendrogram. The range in hillslope ecosystem types were described from stratified environmental surveys of vegetation and soils along environmental gradients in selected analogue landforms. The results show that the mapped environmental factors in close correlation with water and sediment distribution were strongly associated with observed vegetation patterns in analogue areas at Ranger uranium mine. Environmental grain size and landform extent concepts were therefore introduced using landscape ecology theory to integrate different scales of environmental variation in a way that provides direct context with the area impacted by mining. Fine-grained environmental terrain attributes that describe runoff, erosion and sediment deposition were derived from a digital elevation model and classified using non-hierarchical multivariate methods to create a habitat class map. Patch analysis was used to aggregate this fine-grained environmental pattern into a grid that matched the scale of the mine landform. The objective was to identify landforms that were similar in extent to the reconstructed mine landscape. Ecosystem support depends on soil as well as geomorphic factors. An investigation into critical environmental processes, water balance and solute balance, on a waste rock landform at Ranger uranium mine is presented in Chapter 5 to characterise waste rock soils and investigate cover design options that affect environmental support. This involved monitoring of water balance of a reconstructed soil cover on a waste rock landform for four years and the solute loads for two years. A one dimensional water balance model was parameterised and run based on 21 years of rainfall records so as to assess the long-term effects of varying cover thickness and surface compactness on cover performance. The results show that the quality of runoff and seepage water did not improve substantially after two years as large amount of dissolved metal loads persisted. Also, tree roots interacted with the subsoil drainage-limiting layer at one metre below the land surface in just over two years - and thus altering the hydraulic properties of the layer. Further, the results of water balance simulations indicate that increasing the depth to, and thickness of, the drainage-limiting layer would reduce drainage flux. Increasing layer thickness could also limit tree root penetration. It was also found that surface compaction was the most effective means of limiting deep drainage, which contained high concentrations of dissolved metals. However, surface compaction creates an ecological desert. Therefore long-term rehabilitation of the cover will be required to allow water to infiltrate for it to be available for ecosystems. A cover that can store and release sufficient water to support native savanna eucalypt woodland may need to be three to five metres deep, including a drainage limiting layer at depth so as to slow vertical water movement and comprise a well graded mix of hard rock and weathered rock to provide water storage and erosion resistance. The resulting waste rock soils would be similar, morphologically to the gradational, gravelly soils found in natural analogue areas. The study then shifted from mined land back to a selected natural analogue landscape at Ranger mine in Chapter 6. The fine grained variation in terrain attributes is described to support a landform design that allowed for mine plan estimates of waste rock volumes and pit void volumes. A process of developing and evaluating the landform design was put forward, in the case of Ranger, that begins with key stakeholder consultation, followed by an independent scientific validation using published landform evolution and integrated, surface-groundwater water balance modelling. The natural analogue and draft final landforms were compared in terms of terrain attributes, landform evolution and eco-hydrological processes to identify where improvements could be required. The results of the independent design reviews are contained in confidential reports to Ranger mine and in conference proceedings that are referenced in Chapter 6. Independent validation will be a key element of an ecological landform design process and the application of published eco-hydrological and landform evolution models at the Ranger mine case study site are presented as an example of current best practice. Also, detailed assessment was made of environmental variation and soil and geomorphic range in the selected analogue landscape to support the landform design process with the mining department. Ecological modelling of the distributions of framework species in the reconstructed landscape is proposed as an additional assessment tool in this thesis to validate an ecological landform design methodology. To this end, a detailed environmental survey is presented in Chapter 6 of the soils and vegetation in a selected natural analogue area of Ranger mine to identify common and abundant plant species and their distribution in a similar landscape context to the mined land. This work supported ecological modelling of species distributions in reconstructed and natural landscapes in the following chapter. The results of species distribution models for reconstructed and natural landscapes at the Ranger mine site are reported in Chapter 7. The aim was to predict the distribution of common and abundant native woodland species across a landscape comprising a sculpted, post mining landform within a natural landscape. Species distribution models were developed from observations of species presence-absence at 102 sites in the grid survey of the natural analogue area that was reported in Chapter 6. Issues related to optimising predictor selection and the range of environmental support were investigated by introducing survey sites from the broad area reconnaissance survey reported in Chapter 4. Added to these are the published species abundance data from an independent regional biodiversity survey of rocky, well drained eucalypt woodlands, used as analogues of mined land. Plant species responses to continuous and discrete measures of environmental variation were then analysed using multivariate detrended correspondence analysis and canonical correspondence analysis to select independent variables and assess the relative merits of abundance versus presence absence observations of species. Then, generalised additive statistical methods were used to predict species distributions from primary and secondary terrain variables across the natural analogue area and a reconstructed post-mining landform. This analysis was completed with an assessment of the effect that survey support has on model formulation and accuracy. The scale of the mine landscape was found to provide important context for the stratified environmental surveys needed to support predictive modelling. Extending the geographic range of survey support did not improve model performance, while survey sites remote from the mine introduced some degree of spatial autocorrelation that could reduce the prediction accuracy of species distributions in the mine landscape. Further work is needed to address uncommon species or species with highly constrained environmental ranges and aspects of landform cover design and land management that affect woodland type and vigour. The combined studies reported in this thesis show that the predictability of mine land restorations is dependent on the landscape models used to characterise the natural analogue areas. It is demonstrated that conceptual ecological models developed for regional land resources survey, commonly used to select natural analogue areas, are subjective, complex and unreliable predictors of vegetation and soil patterns in hillslope environments at particular sites. It was recognised that environmental patterns are subject to terrain and hillslope environmental variation across an extensive areas. The landform model for selecting natural analogues was refined by introducing grain size and ecological extent concepts, used to describe ecological scale in landscape ecology, to address these effects. These refined concepts were adapted to define environmental variation in the context of natural analogue selection for mining restoration, rather than home range habitat conditions for native animals as was their original purpose. It is demonstrated here that the grain size and extent of environmental variation in the natural landscape can be used to select natural analogue landforms, develop ecological design criteria and design field surveys that support the capacity to predict the distributions of common and abundant woodland species in a reconstructed landscape. In conclusion, it is worth noting that an integrated ecological approach to landscape design can be applied to closure planning at mine sites where cultural and ecological objectives are critical to the success of the mine rehabilitation. Furthermore final landform trials could be used to support a restoration approach — providing an understanding of the interactions between critical physical and ecological processes in the soil layers and environmental processes at catchment scales. The accuracy of the inferences made is dependent on the understanding of hydrological processes in natural and constructed landforms. However, the natural analogue approach provides a clear landscape context for these trials. In a world where species extinction resulting from habitat loss is one of the most important global ecological issues, mine rehabilitation offers unique experimental opportunities to develop capability in ecosystem rehabilitation.

Introduction: Mathematical models of HIV transmission have played an important role in helping to understand the drivers of the HIV epidemic, and shape the global HIV response. The underlying approaches, assumptions and structures used in HIV modelling have the potential to fundamentally influence the conclusions of any modelling analyses. For this reason, it is important that approaches to modelling HIV transmission in different contexts carefully consider how best to ‘characterise’ a populations distribution of risk and networks of sexual interaction based on data, and the implications of incorporating different levels of epidemiological complexity into their modelling. Across West Africa there are substantial variations in population HIV prevalence - ranging from 0.5-6%. To date, there has been limited exploration of the potential factors influencing this population variation. This PhD aims to inform our understanding of the determinants of population variations in HIV prevalence across West Africa, using a combination of ecological analysis of population data, and both simple and more complex epidemiological modelling. The findings are used both to explore the determinants of HIV transmission across West Africa, and to discuss the implications for future modelling and epidemic appraisal approaches. Methods: A range of modelling and epidemiological analytical approaches were used. Firstly, an existing policy model, The Modes of Transmission (MoT) model, designed to predict patterns of HIV incidence, was revised and re-parameterised using data from Nigeria, to explore the effect on overall conclusions of adding additional heterogeneity into the model, and considering more explicitly how to model HIV risk amongst lower-risk subgroups. Secondly, population data from 13 West African countries were compiled. Linear regression analyses were used to assess potential relationships between HIV prevalence in high-risk groups and population HIV prevalence and the size of high-risk population subgroups and HIV prevalence in the general population. Based on the findings from the MoT and ecological analysis, a dynamic deterministic model was developed to explore the variations in HIV prevalence across West Africa. The population model not only included sex work, client and general population sub-groups, but also included a category of adolescent females (15-24) and a category of males with multiple sexual partners, with a mixing formulation being used to vary the degree the adolescent females form partnerships with clients of female sex workers and the subgroup of males who have multiple partnerships Input parameters were sampled from ranges relevant for West Africa, using Latin Hypercube sampling. The model was fitted to equilibrium prevalence in the general population. Results: A critique and revisions to the MoT, identified high levels of infections in previously unrecognised subgroups. These included 16% of new infections occurring in young females engaging in transactional sex. Findings from the ecological analysis, showed that across West Africa HIV prevalence in FSWs and their clients is not associated with higher HIV prevalence in the general population. Instead, the size of groups of males and females with multiple partners is correlated with higher HIV prevalence levels. The deterministic model generated 11000 fits. Grouping fits, based on epidemic size (with 1% incremental increases from 0-6%), the findings revealed that population sizes of key subgroups is the predominant driver of the epidemic. For epidemics where prevalence is less than 3%, FSW population size is the most important determinant of HIV prevalence. For epidemics above 3%, it is the size of the group of adolescent females with multiple partners and their level of interaction with clients of FSWs that is the most significant variable related to higher HIV prevalence. When the limiting effects on HIV transmission of male circumcision are removed from the model, the findings are less clear, with both sex work and the role of adolescent females with multiple partners being important determinants of the epidemic. Circumcision is however shown to significantly limit the magnitude of an epidemic and epidemic categorisation should account for these variations accordingly. Conclusions: Behavioural heterogeneity has long been recognised as an important component of model development. The results from this thesis show the importance of carefully considering how to compartmentalise population HIV models. Even for simple static models, the inclusion of additional subgroups change model conclusions and suggests different intervention priorities. The use of results and findings from ecological analyses, whilst unable to provide strong evidence of causality, can provide useful insights into the relationship between population level factors or behavioural variables and HIV prevalence in the general population. These findings may then be used to inform model development. Deterministic dynamic modelling used in this thesis demonstrates that the size and sexual networks of vulnerable subgroups in the population may be of key importance in determining levels of HIV epidemics in West Africa. In-particular, adolescent females engaging in noncommercial multiple partnerships, often associated with transactional exchange are an important determinant of the HIV epidemic in West Africa. An improved understanding of this group, their size and motivations for engaging in multiple partnerships, through the use of epidemic mapping techniques and social research, will be important to future HIV intervention activities.

Un réseau écologique constitue une représentation de l'ensemble des interactions entre espèces dans un contexte donné. L'analyse de la structure topologique de ces réseaux permet aux écologues d'identifier et de comprendre les processus sous-jacents. La détection de sous-groupes d'espèces interagissant fortement ensemble, souvent nommés communautés o compartiments, est un des principaux moyens pour interpréter la structure sous-jacente des réseaux. Il existe de nombreuses méthodes de classification non supervisée, qui peuvent être utilisées pour analyser des réseaux écologiques. L'analyse des réseaux est actuellement un sujet de recherche en pleine expansion avec des applications dans des domaines de recherches variés. À notre connaissance, il n'existe pas de comparaison des méthodes de classification non supervisée dans le cas des réseaux écologique. Nous avons effectué une revue des méthodes disponibles de classification non supervisées des noeuds, et nous les avons comparé dans un contexte écologique. Afin d'évaluer la contribution des différents processus expliquant la structure d'un réseau, nous avons introduit de l'information extérieure au réseau. Nous avons analysé deux réseaux d'interaction arbre-champignon et arbre-insecte. Ces résultats sont préliminaires, mais la méthode semble ouvrir des perspectives intéressantes en écologie. Nous avons également étudié un réseau écologique de nature différente, un réseau de reproduction entre arbres. Nous avons utilisé ces résultats pour discuter d'un concept central en écologie, le concept d'espèce
An ecological network is a representation of the whole set of interactions between species in a given context. Ecological scientists analyse the topological structure of such networks, in order to understand the underlying processes. The identification of sub-groups of highly-interacting species (usually called communities, or compartments) is an important stream of research. The most popular method for the search of communities in ecological networks is the modularity optimization method. However this popularity is more due to the first paper published on this topic than to a rational choice based on solid grounds. There are many other clustering methods that could be used to delimit communities in ecological networks. The analysis of complex networks is indeed a rapidly growing topic with many applications in several scientific fields. To our knowledge, no comparison of different clustering methods is available in the case of ecological networks. Here we reviewed the whole set of methods available for clustering networks and we compared them using an ecological benchmark. In order to assess the relative contribution of several processes to the network structure, we integrated exogenous information in the clustering model. We analysed two bipartite antagonistic networks with this method, a tree-fungus and tree-insect network. The results are still preliminary but the method seems to us very promising for future ecological studies. Finally we searched communities in a different kind of network, a mating network between individuals belonging to two hybridizing tree species. We used our results to discuss a concept which is central in ecology, the species concept

Progress towards sustainability requires changes in our individual and collective behaviour. Yet, our fundamental understanding of behaviour in relation to environmental change remains severely limited. In particular, little attention has been given to how individual and collective behaviours respond to, and are shaped by, non-linear environmental change (such as ‘regime shifts’) and its inherent uncertainties. The thesis makes two main contributions to the literature: 1) it provides one of the first accounts of human behaviour and collective action in relation to ecological regime shifts and associated uncertainties; and 2) extends the incipient behavioural common-pool resource literature that acknowledges social-ecological dynamics and ecological complexity. The overarching aim of this thesis is to further advance an empirically grounded understanding of human behaviour in social-ecological systems. In particular, the thesis attempts to unravel critical social-ecological factors and mechanisms for the sustainability of common-pool resources. This is especially relevant for contexts in which livelihoods can be more directly threatened by regime shifts. The following methods are applied: behavioural economic experiments in the lab (with students; Papers I and II) and in the field (with small-scale fishers from four different communities in the Colombian Caribbean; Paper III), and agent-based modelling empirically informed by a subset of the lab experiments (Paper IV). Paper I tests the effect of an endogenously driven regime shift on the emergence of cooperation and sustainable resource use. Paper II tests the effect of different risk levels of such a regime shift. The regime shift in both papers has negative consequences for the productivity of the shared resource. Paper III assesses the effect of different degrees of uncertainty about a climate-induced threshold in stock dynamics on the exploitation patterns; as well as the role of social and ecological local context. Paper IV explores critical individual-level factors and processes affecting the simultaneous emergence of collective action and sustainable resource use. Results cumulatively suggest that existing scientific knowledge indicating the potential for ecological regime shifts should be communicated to affected local communities, including the remaining uncertainties, as this information can encourage collective action for sustainable resource use. Results also highlight the critical role of ecological knowledge, knowledge-sharing, perceived ecological uncertainties, and the role local contexts play for sustainable outcomes. This thesis enriches the literature on social-ecological systems by demonstrating how a behavioural experimental approach can contribute new insights relevant for sustainability. Overall, these insights indicate that, given the opportunity and the willingness of people to come together, share knowledge, exchange ideas, and build trust, potential ecological crises can encourage collective action, and uncertainties can be turned into opportunities for dealing with change in constructive ways. This provides a hopeful outlook in the face of escalating environmental change and inherent uncertainties.

At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 3: Manuscript.

Ecosystems consist of complex dynamic interactions among species and the environment, the understanding of which has implications for predicting the environmental response to changes in climate and biodiversity. Understanding the nature of functional relationships (such as prey-predator) between species is important for building predictive models. However, modelling the interactions with external stressors over time and space is also essential for ecosystem-based approaches to fisheries management. With the recent adoption of more explorative tools, like Bayesian networks, in predictive ecology, fewer assumptions can be made about the data and complex, spatially varying interactions can be recovered from collected field data and combined with existing knowledge. In this thesis, we explore Bayesian network modelling approaches, accounting for latent effects to reveal species dynamics within geographically different marine ecosystems. First, we introduce the concept of functional equivalence between different fish species and generalise trophic structure from different marine ecosystems in order to predict influence from natural and anthropogenic sources. The importance of a hidden variable in fish community change studies of this nature was acknowledged because it allows causes of change which are not purely found within the constrained model structure. Then, a functional network modelling approach was developed for the region of North Sea that takes into consideration unmeasured latent effects and spatial autocorrelation to model species interactions and associations with external factors such as climate and fisheries exploitation. The proposed model was able to produce novel insights on the ecosystem's dynamics and ecological interactions mainly because it accounts for the heterogeneous nature of the driving factors within spatially differentiated areas and their changes over time. Finally, a modified version of this dynamic Bayesian network model was used to predict the response of different ecosystem components to change in anthropogenic and environmental factors. Through the development of fisheries catch, temperature and productivity scenarios, we explore the future of different fish and zooplankton species and examine what trends of fisheries exploitation and environmental change are potentially beneficial in terms of ecological stability and resilience. Thus, we were able to provide a new data-driven modelling approach which might be beneficial to give strategic advice on potential response of the system to pressure.

During the Pre-Pottery Neolithic - Pottery Neolithic transition in the Levant, several centuries after the widespread adoption of agriculture and shortly after the adoption of mixed farming, a number of large, formerly successful communities seem to have been abandoned. These apparent settlement transformations are reported to have occurred alongside changes in technology and production, ideological behaviour and the treatment of the dead, and subsistence economy. Whether one views these purported changes as evidence of 'collapse' or not, particular transformations do seem to have taken place and require explanation. Several proposed models attempt to explain why these changes may have occurred, but the anthropogenically induced ecological degradation argument is the most pervasive. While this model has already been tested in a preliminary manner, detailed evaluation of the degradation argument partly based on agronomic research on the ecological impacts of mixed farming is still due.

Estonian coastal wetlands are of international importance as they support characteristic biological diversity. Their limited extent and distribution mean that these wetlands are of high conservation concern, and as such have been identified as a priority in the European Union Habitats Directive. These wetlands are typified by a flat, extensive landscape, situated between the micro-tidal «0.02m), brackish Baltic Sea and a forest interior. Due to the low relief these wetlands may be under threat from sea level rise. This research consisted of four studies: (i) to determine and quantify the relationship between a range of coastal wetland plant community types, elevation and edaphic conditions. Results demonstrated that plant community distribution was significantly affected by micro-topography and edaphic variability. The majority of the plant communities were discernible in the field by elevation alone and elevation was found to be the factor that could distinguish the greatest number of plant communities. (ii) to determine an appropriate method of interpolating LiDAR elevation data and assess the use of LiDAR data in creating a static correlative model to determine plant community type based on elevation. Results showed that with dGPS calibration the model could accurately predict plant community location. Validation of the model in two further sites showed that the correlative model was able to predict plant community with almost perfect (K 0.81) and moderate agreement (K 0.53) dependent on the site. (iii) to determine sediment accretion rates to complete the dynamic model by analysing the level of radionuclides, 137CS and 210Pb, in discrete core sections. Results showed that during periods of greater storminess sediment accretion increased almost threefold. These sensitivity data were included in the dynamic correlative model. (iv) to assess the effects of sea level rise on plant communities in Estonian coastal wetlands under five sea level scenarios, two accretion rate scenarios and factoring in isostatic uplift rates. Results showed that local sea level will rise in some sites and decrease in others dependent on location and SLR scenario. This study has indicated that in many instances Estonian coastal wetlands will increase in extent in the future due to high rates of sediment accretion, particularly in a scenario with more frequent storms, and isostatic uplift. The study has shown that following validation, calibration and sensitivity analysis LiDAR data can be used to accurately predict plant community type in microtopographical ecosystems. The model developed in this study of Estonian coastal wetlands is likely to be transferable to other appropriate habitats such as tidal, estuarine, and floodplains wetlands.

Freshwater lakes are among the most important ecosystems for both human and other biological communities. They account for about 87% of surface freshwater in the planet, thus constituting a major source of drinking water. They also provide a wide range of ecosystem services that go from the sustenance of a rich biodiversity to the regulation of hydrological extremes; from the provision of a means for recreation to the support of local economies, e.g., through tourism and fisheries, just to cite a few. Lakes are now also widely recognised as natural early warning systems, their responses potentially being effective indicators of local, regional and global scale phenomena such as acidification and climate change, respectively. This is because of their high sensitivity to environmental factors of the most diverse nature that can rapidly alter the course of their evolution. Examples of this are the observed abrupt shifts between alternative stable states in shallow lakes, which led them to become the archetype, go-to example in alternative stable state theory. Therefore, attaining a good scientific understanding of the many processes that take place within these ecosystems is fundamental for their adequate management. Among the tools that serve this purpose, ecological models are particularly powerful ones. Since their introduction in the 1960s, the development of mechanistic ecological models has been driven by their wide spectrum of potential applications. Nevertheless, these models often fall into one of the two following categories: overly simplistic representations of isolated processes, with limited potential to explain real-world observations as they fail to see the bigger picture; or overly complex and over-parameterised models that can hardly improve scientific understanding, their results being too difficult to analyse in terms of fundamental processes and controls. Moreover, it is now well known that an increased complexity in the mechanistic description of ecological processes, does not necessarily improve model accuracy, predictive capability or overall simulation results. To the contrary, a simpler representation allows for the inclusion of more links between model components, feedbacks which are usually overlooked in highly-complex models that partially couple a hydro-thermodynamic module to a biogeochemical one. However, ecological processes are now known to have the potential to significantly alter the physical response of aquatic ecosystems to environmental forcing. For example, steadily increasing concentrations of coloured dissolved organic carbon, a process known as brownification (also browning), as well as the intense phytoplankton blooms that characterise lakes undergoing severe nutrient enrichment, a process known as eutrophication, have been shown to have the potential to alter the duration of the stratified period, thermal structure and mixing regime of some lakes. In this thesis, with the aim of addressing the limitation of partially-coupled models to account for such feedbacks, we further develop a process-based model previously reported in scientific literature. Subsequent studies have already built upon this model in the last few years. In Chapter 2, we do so too by integrating hydro-thermodynamics and biogeochemistry in a reduced complexity framework, i.e., customising the model so that each version only includes the fundamental processes that, brought together, sufficiently describe the studied phenomena. Two case studies served the purpose of testing the adaptability and applicability of the developed model under different configurations and requirements. Limnological data for these two studies were measured at high spatial and temporal resolutions by means of an automated profiling system and recorded as part of two large-scale mesocosm experiments conducted in 2015 and 2016 at the IGB LakeLab in Lake Stechlin, Brandenburg, Germany. Meteorological datasets were also made available to us for both periods by the German Federal Environment Agency. The scope of the first experiment, which we describe in Chapter 3, was that of detecting any changes attributable to eutrophication and browning, in the competition for nutrients and light between four different groups of lake primary producers. These four groups are phytoplankton, periphyton, epiphyton and macrophytes. The model version for this study, therefore, includes equations for all four groups. By tailoring the model to these very specific needs with relative ease, we demonstrate its versatility and hint at its potential. The second experiment, described in Chapter 4, sought to shed light on the largely unknown effects of an increase in the diffuse luminance of the night sky that is due to artificial light at night (artificial skyglow) on lake metabolic rates, i.e., gross primary productivity, ecosystem respiration and net ecosystem productivity (the difference between the first two). For this purpose, an empirical equation for dissolved oxygen concentration was included, the parameters of which were estimated by means of a Markov Chain Monte Carlo sampling method within a Bayesian statistical framework, showing the compatibility, with these statistical methods, of our otherwise fully deterministic model. In Chapter 5, we present a theoretical study on the ecological controls of light and thermal patterns in lake ecosystems. A series of simulations were performed to determine in which cases ecological processes such as eutrophication and brownification may have an observable effect on the physical response of lakes to environmental forcing, which we assessed along a latitudinal gradient. Results show that, in general, across all examined latitudes, and consistent with previous studies, accounting for phytoplankton biomass results in higher surface temperatures during the warm-up phase, slightly lower water temperatures during the cool-down phase, and a shallower thermocline throughout the entire stratified period. This effect is relatively more important in eutrophic lakes where intense blooms are likely. This importance, however, decreases as lakes get browner. Finally, in line with the overall scope of the SMART EMJD, in Chapter 6 we illustrate the case of Ypacaraí Lake, the most important lake in landlocked Paraguay, hoping to provide an example of how interdisciplinary research and international intersectoral collaboration can help bridge the gap between science and management of freshwater ecosystems. This lake presents very special hydro-ecological conditions, such as very high turbidity that can impair phytoplankton growth despite its nutrient-based trophic state indices having consistently fallen within the hyper-eutrophic range in recent years. A strong interest in its complex functioning, through modelling, was taken early on. This led to a collaborative research line being established among several public and private institutions in Italy, Germany and Paraguay. Results so far include: • three concluded UniTN Master theses in Environmental Engineering, partly developed in Paraguay, the first two in collaboration with the “Nuestra Señora de la Asunción” Catholic University (UCNSA) and the third one with the National University of Asunción (UNA); • a collaborative UCNSA-UniTN research proposal submitted for consideration to receive funding through the PROCIENCIA Programme of the National Council of Science and Technology of Paraguay (CONACYT); and • the first multidisciplinary review that has ever been published about the case of Ypacaraí Lake, which highlights the importance of such a collaborative and integrative approach to further advance scientific knowledge and effectively manage this ecosystem.

Freshwater lakes are among the most important ecosystems for both human and other biological communities. They account for about 87% of surface freshwater in the planet, thus constituting a major source of drinking water. They also provide a wide range of ecosystem services that go from the sustenance of a rich biodiversity to the regulation of hydrological extremes; from the provision of a means for recreation to the support of local economies, e.g., through tourism and fisheries, just to cite a few. Lakes are now also widely recognised as natural early warning systems, their responses potentially being effective indicators of local, regional and global scale phenomena such as acidification and climate change, respectively. This is because of their high sensitivity to environmental factors of the most diverse nature that can rapidly alter the course of their evolution. Examples of this are the observed abrupt shifts between alternative stable states in shallow lakes, which led them to become the archetype, go-to example in alternative stable state theory. Therefore, attaining a good scientific understanding of the many processes that take place within these ecosystems is fundamental for their adequate management. Among the tools that serve this purpose, ecological models are particularly powerful ones. Since their introduction in the 1960s, the development of mechanistic ecological models has been driven by their wide spectrum of potential applications. Nevertheless, these models often fall into one of the two following categories: overly simplistic representations of isolated processes, with limited potential to explain real-world observations as they fail to see the bigger picture; or overly complex and over-parameterised models that can hardly improve scientific understanding, their results being too difficult to analyse in terms of fundamental processes and controls. Moreover, it is now well known that an increased complexity in the mechanistic description of ecological processes, does not necessarily improve model accuracy, predictive capability or overall simulation results. To the contrary, a simpler representation allows for the inclusion of more links between model components, feedbacks which are usually overlooked in highly-complex models that partially couple a hydro-thermodynamic module to a biogeochemical one. However, ecological processes are now known to have the potential to significantly alter the physical response of aquatic ecosystems to environmental forcing. For example, steadily increasing concentrations of coloured dissolved organic carbon, a process known as brownification (also browning), as well as the intense phytoplankton blooms that characterise lakes undergoing severe nutrient enrichment, a process known as eutrophication, have been shown to have the potential to alter the duration of the stratified period, thermal structure and mixing regime of some lakes. In this thesis, with the aim of addressing the limitation of partially-coupled models to account for such feedbacks, we further develop a process-based model previously reported in scientific literature. Subsequent studies have already built upon this model in the last few years. In Chapter 2, we do so too by integrating hydro-thermodynamics and biogeochemistry in a reduced complexity framework, i.e., customising the model so that each version only includes the fundamental processes that, brought together, sufficiently describe the studied phenomena. Two case studies served the purpose of testing the adaptability and applicability of the developed model under different configurations and requirements. Limnological data for these two studies were measured at high spatial and temporal resolutions by means of an automated profiling system and recorded as part of two large-scale mesocosm experiments conducted in 2015 and 2016 at the IGB LakeLab in Lake Stechlin, Brandenburg, Germany. Meteorological datasets were also made available to us for both periods by the German Federal Environment Agency. The scope of the first experiment, which we describe in Chapter 3, was that of detecting any changes attributable to eutrophication and browning, in the competition for nutrients and light between four different groups of lake primary producers. These four groups are phytoplankton, periphyton, epiphyton and macrophytes. The model version for this study, therefore, includes equations for all four groups. By tailoring the model to these very specific needs with relative ease, we demonstrate its versatility and hint at its potential. The second experiment, described in Chapter 4, sought to shed light on the largely unknown effects of an increase in the diffuse luminance of the night sky that is due to artificial light at night (artificial skyglow) on lake metabolic rates, i.e., gross primary productivity, ecosystem respiration and net ecosystem productivity (the difference between the first two). For this purpose, an empirical equation for dissolved oxygen concentration was included, the parameters of which were estimated by means of a Markov Chain Monte Carlo sampling method within a Bayesian statistical framework, showing the compatibility, with these statistical methods, of our otherwise fully deterministic model. In Chapter 5, we present a theoretical study on the ecological controls of light and thermal patterns in lake ecosystems. A series of simulations were performed to determine in which cases ecological processes such as eutrophication and brownification may have an observable effect on the physical response of lakes to environmental forcing, which we assessed along a latitudinal gradient. Results show that, in general, across all examined latitudes, and consistent with previous studies, accounting for phytoplankton biomass results in higher surface temperatures during the warm-up phase, slightly lower water temperatures during the cool-down phase, and a shallower thermocline throughout the entire stratified period. This effect is relatively more important in eutrophic lakes where intense blooms are likely. This importance, however, decreases as lakes get browner. Finally, in line with the overall scope of the SMART EMJD, in Chapter 6 we illustrate the case of Ypacaraí Lake, the most important lake in landlocked Paraguay, hoping to provide an example of how interdisciplinary research and international intersectoral collaboration can help bridge the gap between science and management of freshwater ecosystems. This lake presents very special hydro-ecological conditions, such as very high turbidity that can impair phytoplankton growth despite its nutrient-based trophic state indices having consistently fallen within the hyper-eutrophic range in recent years. A strong interest in its complex functioning, through modelling, was taken early on. This led to a collaborative research line being established among several public and private institutions in Italy, Germany and Paraguay. Results so far include: • three concluded UniTN Master theses in Environmental Engineering, partly developed in Paraguay, the first two in collaboration with the “Nuestra Señora de la Asunción” Catholic University (UCNSA) and the third one with the National University of Asunción (UNA); • a collaborative UCNSA-UniTN research proposal submitted for consideration to receive funding through the PROCIENCIA Programme of the National Council of Science and Technology of Paraguay (CONACYT); and • the first multidisciplinary review that has ever been published about the case of Ypacaraí Lake, which highlights the importance of such a collaborative and integrative approach to further advance scientific knowledge and effectively manage this ecosystem.

At the Rio Conference in 1992, the sustainable development agenda promised a new era for natural resource management, where the wellbeing of human society would be enhanced through a more sustainable use of natural resources. Several decades on, economic growth continues unabated at the expense of natural capital – as evidenced by natural resource depletion, biodiversity loss, climate change and further environmental issues. Why is this happening and what can be done about it? This research examines what socio-economic and governance factors affect sustainability in complex coupled social-ecological systems. Furthermore, it analyses the role of power relations and imbalances between economic and conservation forces with regard to sustainable development. The original contribution to knowledge of this thesis is based on one conceptual and two empirical (Agent-Based) models. These explore, through several case-studies, the potential of different future scenarios in fostering synergies and win-win contexts of ecosystem services and socio-economic indicators. Overall, the research showed the complex and interconnected relationship between the economy and natural systems, and between economic and conservation forces, in coupled social-ecological systems. Addressing complex sustainability issues requires the use of integrative, holistic and interdisciplinary approaches, in addition to considering the particular socio-economic, cultural, political and environmental contexts of the social-ecological system being analysed. The models demonstrated that the current economic system requires an ever-increasing use of natural resources, and that the economy does not protect the natural capital on which it depends. This is based on a disjunction of the economic and conservation elements upon which the sustainable development paradigm is founded. Furthermore, several socio-economic and governance factors appeared to be key for diminishing sustainability in coupled social-ecological systems; namely, the type of economic and production systems, the particular use of monetary debt, technological development, and weak conservation forces (both top-down and bottom-up). However, results also showed alternative scenarios where these same factors could be redirected to enhance social-ecological sustainability. This dual role supports the argument that the current economic system is not inherently (i.e. by definition, per se) unsustainable. Rather, the specific use of economic mechanisms and behaviour of economic entities, as well as their decisions and relationships with the environment, show a tendency to increase unsustainability. Hence, short- and medium-term sustainability can be enhanced by developing mechanisms that start shifting capitalist forces to support environmental conservation; here, the role of Payments for Ecosystem Services will be essential. Enhancing long-term sustainability, however, may require a further paradigm change – where economic and production systems integrate, and fully account for, externalities and the value of natural capital, thus human society is embedded within the wider, and more important, natural environmental system.

Severe declines in the number of some songbirds over the last 40 years have caused heated debate amongst interested parties. Many factors have been suggested as possible causes for these declines, including an increase in the abundance and distribution of an avian predator, the Eurasian sparrowhawk Accipiter nisus. To test for evidence for a predator effect on the abundance of its prey, we analyse data on 10 species visiting garden bird feeding stations monitored by the British Trust for Ornithology in relation to the abundance of sparrowhawks. We apply Bayesian hierarchical models to data relating to averaged maximum weekly counts from a garden bird monitoring survey. These data are essentially continuous, bounded below by zero, but for many species show a marked spike at zero that many standard distributions would not be able to account for. We use the Tweedie distributions, which for certain areas of parameter space relate to continuous nonnegative distributions with a discrete probability mass at zero, and are hence able to deal with the shape of the empirical distributions of the data. The methods developed in this thesis begin by modelling single prey species independently with an avian predator as a covariate, using MCMC methods to explore parameter and model spaces. This model is then extended to a multiple-prey species model, testing for interactions between species as well as synchrony in their response to environmental factors and unobserved variation. Finally we use a relatively new methodological framework, namely the SPDE approach in the INLA framework, to fit a multi-species spatio-temporal model to the ecological data. The results from the analyses are consistent with the hypothesis that sparrowhawks are suppressing the numbers of some species of birds visiting garden feeding stations. Only the species most susceptible to sparrowhawk predation seem to be affected.

Urbanisation often exerts large-scale adverse effects on coastal areas and estuaries, which are ecologically diverse and highly productive habitats. Understanding the ecological resilience of these habitats is a prerequisite for their management. Direct quantification of ecosystem functioning using conventional approaches, however, is difficult and time-consuming. This difficulty has greatly restricted ecosystem-level research and thus, the ability to predict an ecosystem’s responses to urbanisation. The main aim of this thesis was to assess the impact of urbanisation on estuarine sandflats. I developed a novel food web analytical approach, by combining stable isotope (13C) enrichment, compartmental modelling, and ecological network analysis techniques to quantify food web dynamics. This approach was tested with estuarine sandflats, which is one of the most important coastal habitats worldwide. The novel approach allows quantitative testing of specific hypotheses about food web dynamics through manipulative experiments, by comparing system indices that reflect ecosystem condition. Further, I conducted manipulative experiments using this approach to investigate the structural and functional response of a multi-level estuarine sandflat food web to two common anthropogenic stressors from urbanisation, namely, organic enrichment and physical disturbance.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Giffith School of Environment
Science, Environment, Engineering and Technology
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In the management of agricultural insect pests, short-term costs must be balanced against long-term benefits. Controls should be selected to account for both their immediate and downstream effects upon the demography and genetics of the pest, enabling suppression today without threatening suppression tomorrow. The iterative, algorithmic method of dynamic programming can provide optimal solutions to problems of this type, in which actions are taken sequentially and each action may influence those which follow it. However, this approach is fundamentally constrained with regards to the magnitude of the problems it may solve. As questions of insect pest management can be subject to ecological and evolutionary complexities, this may place them beyond the scope of dynamic programming. When it is the intricacies of a problem that are of interest, it may be more productive to utilise approximate dynamic programming (ADP) methods which can attempt problems of arbitrary complexity, although at the expense of no longer guaranteeing optimality. In this thesis I first challenge a dynamic programming algorithm with the management of a hypothetical insect pest feeding upon a transgenic insecticidal crop. The model explores how different realisations of fitness costs to resistance influence the algorithms suggested actions. I then apply a brute-force variant of ADP, a lookahead policy, to the management of a stage-structured, continuously reproducing pest population. This was to explore the extent to which an algorithm with a limited temporal perspective is able to balance the timetable of pest demography against the timescale over which insecticidal sprays and bisex-lethal sterile insect releases unfold. This same decision framework is then applied to a modified problem in which resistance to insecticidal toxins may evolve and releases are now male-selecting. This was used to assess the efficacy with which simple lookahead policies utilise a control with delayed benefits (the male-selecting releases) and possible constraints on their capacity to respond to resistance evolution. Dynamic programming and ADP methods offer a versatile toolbox for accounting for the potential impacts of the evolutionary and ecological peculiarities of particular pests upon control decisions.

Doutoramento em Engenharia do Ambiente - Instituto Superior de Agronomia
In freshwater ecosystems associated with agricultural areas, organisms are exposed to a multitude of toxicologically and structurally distinct pesticides in concentrations that may fluctuate over time. However, the environmental risks of chemicals are traditionally evaluated and regulated on the basis of single substance. Understanding and improving the link between effects and exposure assessment is an important step in the current challenges of risk assessment in order to increase its ecological relevance. To this end, integrated approaches of different hierarchical levels of complexity and ecological realism have been developed and applied, including: exposure modelling, laboratory testing with individual organisms, species sensitivity distribution, ecosystem models and assessment of aquatic community interactions to evaluate the effects of realistic pesticide combinations on water bodies associated with rice, tomato and maize typical agroecosystems of Mediterranean conditions. Contributing to the overall knowledge of the adequacy of the prospective risk assessment and demonstrating that pesticide risk may be underestimated during the actual registration procedure. The data generated in the present study contributed to the derivation of optimized programs of measures under the scope of European legislation; the identification of sites with the highest expected impacts of pesticide mixtures; the evaluation of the major pesticide compounds that contributed mostly to the identified aquatic risks. Furthermore contribute to a deeper knowledge and unravel the effects of co-occurring chemicals, environmental and biological stressors in aquatic ecosystems considering the effects of biotic and abiotic interactions at community and ecosystem levels. The results contribute to reducing the risks of pesticides in freshwater
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A variety of econometric models have been created, including a travel cost model, contingent behaviour models and a contingent valuation model. Based on these models a “typical” day at Loch Lomond is valued at £20.53, with visitors willing to pay an additional £1.76 to fund environmental improvements. Looking at the particular environmental issues of noise, crowding and environmental damage, noise pollution appears to have the greatest influence on recreation enjoyment. Noise pollution is caused primarily by the use of personal watercraft (“jet-skis”). It was found that an asymmetrical conflict exists between jet-skiers and non jet-skiers. The research project reveals that there is no simple relationship between the perception of and reality of environmental damage. Although visitor perception of environmental damage often differs from actual levels of environmental damage, the relationship is complex. In terms of “real” environmental impact around the loch area, the visitor-induced environmental damage survey estimates that just over 9% of the loch shore suffers from severe environmental impact. Ecological vegetation surveys also confirm that recreation pressure is a statistically significant influence on the presence/absence of plant communities, but that this ecological impact is spatially limited to specific sites around the loch. Following on from both the perceptual and ecological results, policy and management implications are investigated and recommendations are provided – for example the implementation of a possible vehicle parking fee at various sites around Loch Lomond. It is suggested that recreational carrying capacity frameworks such as VERP should be applied, as they assimilate the ecological and social facets of outdoor recreation. An overall conclusion to the thesis is thus that a sustainable approach (framework) to recreation management, one that encompasses the perceptual and ecological dimensions of outdoor recreation, is the only way of maintaining the beauty and enjoyment of Loch Lomond – and, it is suggested, national parks world-wide – for present and future generations.