Agent-based modeling for environmental management. Case study: virus dynamics affecting Norwegian fish farming in fjords

Background: Norwegian fish-farming industry is an important industry, rapidly growing, and facing significant challenges such as the spread of pathogens1, trade-off between locations, fish production and health. There is a need for research, i.e. the development of theories (models), methods, techniques and tools for analysis, prediction and management, i.e. strategy development, policy design and decision making, to facilitate a sustainable industry. Loss due to the disease outbreaks in the aquaculture systems pose a large risk to a sustainable fish industry system, and pose a risk to the coastal and fjord ecosystem systems as a whole. Norwegian marine aquaculture systems are located in open areas (i.e. fjords) where they overlap and interact with other systems (e.g. transport, wild life, tourist, etc.). For instance, shedding viruses from aquaculture sites affect the wild fish in the whole fjord system. Fish disease spread and pathogen transmission in such complex systems, is process that it is difficult to predict, analyze, and control. There are several time-variant factors such as fish density, environmental conditions and other biological factors that affect the spread process. In this thesis, we developed methods to examine these factors on fish disease spread in fish populations and on pathogen spread in the time-space domain. Then we develop methods to control and manage the aquaculture system by finding optimal system settings in order to have a minimum infection risk and a high production capacity. Aim: The overall objective of the thesis is to develop agent-based models, methods and tools to facilitate the management of aquaculture production in Norwegian fjords by predicting the pathogen dynamics, distribution, and transmission in marine aquaculture systems. Specifically, the objectives are to assess agent-based modeling as an approach to understanding fish disease spread processes, to develop agent-based models that help us predict, analyze and understand disease dynamics in the context of various scenarios, and to develop a framework to optimize the location and the load of the aquaculture systems so as to minimize the infection risk in a growing fish industry. Methods: We use agent-based method to build models to simulate disease dynamics in fish populations and to simulate pathogen transmission between several aquaculture sites in a Norwegian fjord. Also, we use particle swarm optimization algorithm to identify agent-based models’ parameters so as to optimize the dynamics of the system model. In this context, we present a framework for using a particle swarm optimization algorithm to identify the parameter values of the agent-based model of aquaculture system that are expected to yield the optimal fish densities and farm locations that avoid the risk of spreading disease. The use of particle swarm optimization algorithm helps in identifying optimal agent-based models’ input parameters depending on the feedback from the agentbased models’ outputs. Results: As the thesis is built on three main studies, the results of the thesis work can be divided into three components. In the first study, we developed many agent-based models to simulate fish disease spread in stand-alone fish populations. We test the models in different scenarios by varying the agents (i.e. fish and pathogens) parameters, environment parameters (i.e. seawater temperature and currents), and interactions (interaction between agents-agents, and agents-environment) parameters. We use sensitivity analysis method to test different key input parameters such as fish density, fish swimming behavior, seawater temperature, and sea currents to show their effects on the disease spread process. Exploring the sensitivity of fish disease dynamics to these key parameters helps in combatting fish disease spread. In the second study, we build infection risk maps in a space-time domain, by developing agent-based models to identify the pathogen transmission patterns. The agent-based method helps us advance our understanding of pathogen transmission and builds risk maps to help us reduce the spread of infectious fish diseases. By using this method, we may study the spatial and dynamic aspects of the spread of infections and address the stochastic nature of the infection process. In the third study, we developed a framework for the optimization of the aquaculture systems. The framework uses particle swarm optimization algorithm to optimize agent-based models’ parameters so as to optimize the objective function. The framework was tested by developing a model to find optimal fish densities and farm locations in marine aquaculture system in a Norwegian fjord. Results show so that the rapid convergence of the presented particle swarm optimization algorithm to the optimal solution, - the algorithm requires a maximum of 18 iterations to find the best solution which can increase the fish density to three times while keeping the risk of infection at an accepted level. Conclusion: There are many contributions of this research work. First, we assessed the agent-based modeling as a method to simulate and analyze fish disease spread dynamics as a foundation for managing aquaculture systems. Results from this study demonstrate how effective the use of agentbased method is in the simulation of infectious diseases. By using this method, we are able to study spatial aspects of the spread of fish diseases and address the stochastic nature of infections process. Agent-based models are flexible, and they can include many external factors that affect fish disease dynamics such as interactions with wild fish and ship traffic. Agent-based models successfully help us to overcome the problem associated with lack of data in fish disease transmission and contribute to our understanding of different cause-effects relationships in the dynamics of fish diseases. Secondly, we developed methods to build infection risk maps in a space-time domain conditioned upon the identification of the pathogen transmission patterns in such a space-time domain, so as to help prevent and, if needed, combat infectious fish diseases by informing the management of the fish industry in Norway. Finally, we developed a method by which we may optimize the fish densities and farm locations of aquaculture systems so as to ensure a sustainable fish industry with a minimum risk of infection and a high production capacity. This PhD study offers new research-based approaches, models and tools for analysis, predictions and management that can be used to facilitate a sustainable development of the marine aquaculture industry with a maximal economic outcome and a minimal environmental impact

The consequences of reservoir host eradication on disease epidemiology in animal communities.

Non-native species have often been linked with introduction of novel pathogens that spill over into native communities, and the amplification of the prevalence of native parasites. In the case of introduced generalist pathogens, their disease epidemiology in the extant communities remains poorly understood. Here, Sphaerothecum destruens, a generalist fungal-like fish pathogen with bi-modal transmission (direct and environmental) was used to characterise the biological drivers responsible for disease emergence in temperate fish communities. A range of biotic factors relating to both the pathogen and the surrounding host communities were used in a novel susceptible-exposed-infectious-recovered (SEIR) model to test how these factors affected disease epidemiology. These included: (i) pathogen prevalence in an introduced reservoir host (Pseudorasbora parva); (ii) the impact of reservoir host eradication and its timing and (iii) the density of potential hosts in surrounding communities and their connectedness. These were modelled across 23 combinations and indicated that the spill-over of pathogen propagules via environmental transmission resulted in rapid establishment in adjacent fish communities (<1 year). Although disease dynamics were initially driven by environmental transmission in these communities, once sufficient numbers of native hosts were infected, the disease dynamics were driven by intra-species transmission. Subsequent eradication of the introduced host, irrespective of its timing (after one, two or three years), had limited impact on the long-term disease dynamics among local fish communities. These outputs reinforced the importance of rapid detection and eradication of non-native species, in particular when such species are identified as healthy reservoirs of a generalist pathogen

Detection of Flavobacterium Columnare in Tissues and Pond Water using Real-Time Polymerase Chain Reaction

Flavobacterium columnare, a Gram-negative rod-shaped bacterium, is the causative agent of columnaris disease in a variety of fish hosts but is of particular significance to the catfish industry located in the southeastern United States. Columnaris infections are a leading cause of mortalities in catfish ponds, occurring alone or in conjunction with other diseases. Typical diagnostic methods for columnaris infections involve the use of selective media following the observation of gross signs of disease. A real-time quantitative PCR (qPCR) assay to estimate the quantity of bacteria present in environmental and tissue samples was developed and validated. The genetic variability seen in F. columnare makes detection of isolates from different genomovars (genetic groups) essential to an assay for diagnostic application. Isolates from catfish generally fall into one of two different genomovars, one being virulent to catfish, while the other genomovar is thought to be largely opportunistic. The qPCR assay described herein was designed specifically to detect F. columnare isolates from the two major genomovars most often associated with farm-raised catfish. The assay was shown specific to F. columnare, regardless of genomovar, and demonstrated sensitivity consistent with similar qPCR assays. In addition, the assay provides quantitative information, estimating the bacterial loads in fish tissue and the environment. Two different applications of the assay are presented: (1) Estimate bacterial burden in fish tissue following immersion challenges to identify variation in transmission rates between channel and blue x channel hybrid catfish, and (2) Estimate the environmental burden of F. columnare in catfish ponds over the course of a single calendar year. This assay will provide an invaluable tool for researchers and diagnosticians in expanding our understanding of F. columnare and how it interacts with the host and environment

CONTROLLING INFECTIOUS DISEASE IN LABORATORY ZEBRAFISH (DANIO RERIO)

Mycobacteriosis is a bacterial disease caused by Mycobacterium spp. that is common in captive, wild and research fish species. The overall goal of this thesis was to investigate mycobacteriosis in laboratory zebrafish in order to increase our understanding of this disease with the intention of influencing control and management practices. First, disease prevention through embryo disinfection was investigated. The effectiveness of several disinfectants were evaluated and povidone-iodine was identified as an effective disinfectant in vitro, it was then evaluated in vivo and showed minimal effects embryo health. Second, the potential of antibiotic treatment against mycobacteriosis in zebrafish was evaluated in vitro where tigecycline and clarithromycin were identified as key drug candidates. The tolerance and efficacy of both antibiotics were tested in vivo in adult zebrafish; where treatments were well tolerated and resulted in a decreased severity in establish mycobacterial infections. Last, natural modes of transmission were examined. Transmission between tank biofilms and zebrafish was demonstrated and the role mycobacterial biofilms play as both a reservoir for and source of Mycobacterium spp. in zebrafish tanks was identified. Finally, the role that live feeds play as a vector of mycobacterial transmission to zebrafish was tested and common zebrafish feeds are able to transmit Mycobacterium spp. to zebrafish. Altogether, these studies contribute to our current knowledge of mycobacterial infections in laboratory zebrafish and inform management. These results are also of use to other fish species as well

Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

© 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care

Book of Abstracts. 9th International Sea Lice Conference

Deltakere på Konferansen: Howard Browman, Elen Hals, Ingrid Askeland Johnsen, Bjørn Olav Kvamme, Lina Ljungfeldt, Abdullah Madhun, Stig Mæhle, Frode Oppedal, Enrique Perez Garcia, Ole Bent Samuelsen, Rasmus Skern-Mauritzen, Anne Berit Skiftesvik, Ove Skilbrei og Ole Torrissen. / Ole Torrissen og Karin Kroon Boxaspen satt også i den nasjonale komiteen

Virginia Institute of Marine Science Programs and Services

Programs and faculty, education and Institute support resources are described

Parasitism perturbs the mucosal microbiome of Atlantic Salmon

Interactions between parasite, host and host-associated microbiota are increasingly understood as important determinants of disease progression and morbidity. Salmon lice, including the parasitic copepod Lepeophtheirus salmonis and related species, are perhaps the most important problem facing Atlantic Salmon aquaculture after feed sustainability. Salmon lice parasitize the surface of the fish, feeding off mucus, scales and underlying tissue. Secondary bacterial infections are a major source of associated morbidity. In this study we tracked the diversity and composition of Salmo salar skin surface microbiota throughout a complete L. salmonis infection cycle among 800 post-smolts as compared to healthy controls. Among infected fish we observed a significant reduction in microbial richness (Chao1, P = 0.0136), raised diversity (Shannon, P &#60; 7.86e-06) as well as highly significant destabilisation of microbial community composition (Pairwise Unifrac, beta-diversity, P &#60; 1.86e-05; P = 0.0132) by comparison to controls. While undetectable on an individual level, network analysis of microbial taxa on infected fish revealed the association of multiple pathogenic genera (Vibrio, Flavobacterium, Tenacibaculum, Pseudomonas) with high louse burdens. We discuss our findings in the context of ecological theory and colonisation resistance, in addition to the role microbiota in driving primary and secondary pathology in the host

Simulated Marine Heat Wave Alters Abundance and Structure of Vibrio Populations Associated with the Pacific Oyster Resulting in a Mass Mortality Event

© 2018, Springer Science+Business Media, LLC, part of Springer Nature. Marine heat waves are predicted to become more frequent and intense due to anthropogenically induced climate change, which will impact global production of seafood. Links between rising seawater temperature and disease have been documented for many aquaculture species, including the Pacific oyster Crassostrea gigas. The oyster harbours a diverse microbial community that may act as a source of opportunistic pathogens during temperature stress. We rapidly raised the seawater temperature from 20 °C to 25 °C resulting in an oyster mortality rate of 77.4%. Under the same temperature conditions and with the addition of antibiotics, the mortality rate was only 4.3%, strongly indicating a role for bacteria in temperature-induced mortality. 16S rRNA amplicon sequencing revealed a change in the oyster microbiome when the temperature was increased to 25 °C, with a notable increase in the proportion of Vibrio sequences. This pattern was confirmed by qPCR, which revealed heat stress increased the abundance of Vibrio harveyi and Vibrio fortis by 324-fold and 10-fold, respectively. Our findings indicate that heat stress-induced mortality of C. gigas coincides with an increase in the abundance of putative bacterial pathogens in the oyster microbiome and highlights the negative consequences of marine heat waves on food production from aquaculture