In the last decade of the 20th Century Somalia made the headlines around the world as the place where a UN force had been withdrawn from due to losses inflicted on US and other troops by members of groups associated with two warlords. In the latter part of the first decade of the 21st Century Somalia was again in the global headlines, but this time associated with acts of piracy committed off its coastline. Behind these headlines lay a complex mixture of problems stretching back as far as the early colonisation of the lands that became Somalia and populated with western European concepts ill suited to the peoples of those lands. The loss of effective government opened the door to neo colonial issues of illegal fishing and hazardous waste dumping that contributed to the piracy problem. Finely interwoven amongst all these issues runs a thread of international law. This thesis examines that thread as it runs through the concept of state failure and asks if it is a legal term and what legal consequences, if any, are attached to it. It examines the international legal frameworks that support fishing and hazardous waste dumping and seeks to understand why they have not prevented illegal fishing and the illegal dumping of hazardous waste off the coast of Somalia. This thesis then examines the concept of piracy as applied to Somalian pirates and seeks answers to questions as to what it is and how it has been applied. It looks at the use of private security as a response and seeks to find the legitimation for their actions in relation to pirates. Sewn throughout is a comparison of responses and suggestions for improvement to international law.

This study analysed causes of the problem of over-fishing in the Jebel Aulia Reservoir (JAR) in Sudan and investigated reasons behind the failure of current management and policy regimes to promote sustainable management and exploitation of fishery in this reservoir. To achieve these objectives existing analytical frameworks and methodological approaches to study noncompliance with regulations have been adapted to allow two important extensions: (1) using frequency instead of intensity as a measure of violation rate and, (2) modifying the probability of detection to depend on time to account for frequency of violation. The adapted analytical models have then been empirically implemented to develop a typology of fishers according to violation rates and to analyse determinants of noncompliance and extent of violation with mesh size regulations among artisanal fishers in the JAR. This study represents the first research effort investigating causes and implications of illegal fishing and noncompliance with fishery regulations in Sudan in general and particularly in the JAR. The study extended the two times dynamic deterrence model (DDM) to use frequency instead of intensity of noncompliance as a measure of violation rate. The method of comparative statics was employed to derive analytical results on the sensitivity of optimal violation to a number of key factors of high relevance to compliance with regulations designed to protect against over-fishing. Analytical results obtained with this extended DDM confirmed the findings of earlier empirical studies employing alternative static and dynamic formulations and revealed interesting economic meanings of modelled relations. The study concludes that a number of factors related to market and institutional failures make frequency more suitable than intensity as a measure of violation in artisanal fisheries of developing countries. Applications of DDM have so far been limited to the case of constant probability of detection, which assumes independence of the length of time to detection. One objective of this study was therefore to modify the DDM to allow for more flexible and broader specification by introducing two important variables to the supply of offences function, namely, evasion activity and enforcement efforts .One of the major modifications made by this study is modelling the probability of detection as a Cox proportional hazard model instead of the survival hazard used in the literature. The new modelling of probability of detection also makes the previous specification only one of the three versions of the new model, since the new model accommodates the situations of constant and inconstant probability of detection. The results of comparative statics analysis revealed important potential ways of extending the standard DDM to allow for optimal choice among critical trade-offs between evasion efforts and violation rates. The study then applied the adapted DDM to empirically analyse and test specific hypotheses about artisanal fishers‘ compliance behaviour using data from a survey of artisanal fishers in the JAR area. Survey data was collected from a sample of 241 fishers from five landing sites at the study area. Factors that determine the probability of violation as well as the extent of violation were analysed employing an ordered Probit model and a count data model respectively, in two steps. The first step analysed the determinants of the choice to belong to one of the defined fishers‘ typologies. In the second step, a zero truncated negative binomial model was applied to analyse determinants of the extent and frequency of violation among violators only. Results of the empirical analyses suggest that fishers seem to care more about the size of the penalty than the presence of regulation enforcing agents as a deterrent, mainly due to corrupt options and effective evasion activities used by fishers. The study also suggests that better education of fishermen is necessary, as well as the provision of alternative income generating activities especially during the fish reproduction season, access to credit for ownership of legal nets, and finally, effective regulation of the importation of illegal nets will be necessary to enhance compliance with mesh size regulations in Sudan. It is also necessary to promote community level organisation and awareness campaigns among fishers about the dangers for future fish stocks of eroding small fish quantities through the use of illegal nets and consequently endangering the social welfare of all. / Thesis (PhD)--University of Pretoria, 2012. / Agricultural Economics, Extension and Rural Development / unrestricted

Small-scale fisheries represent an important sector for Tanzania’s economy and the contribution to the livelihood of people. In Lake Babati, fish stocks are decreasing, mainly because of illegal fishing methods. This study therefore aims at examining how the problems of illegal fishing affect the fishermen, as well as their perceptions of the implemented fish ban. By using semi-structured interviews, a seasonal calendar and a Venn diagram, the data was analysed through a Critical Institutionalist lens. The results show that the fish ban has not improved the situation and that the fisheries co-management in Lake Babati is weakly practiced. Furthermore, the complexity of socially embedded relations constrains the organisation among the fishermen. As a response to the inadequate management, the fishermen suggest other solutions for preventing illegal fishing.

This doctoral thesis examines the challenges to co-management in the Tanzania part of Lake Victoria. The study mainly addresses the Nile perch fishery and uses the fishing communities of Bukoba Rural district, Tanzania as a case study. Co-management in Lake Victoria is defined as the sharing of the management responsibilities between the state and the fishing communities. Co-management was adopted in the Lake Victoria fisheries on the understanding that it has the capacity to provide space in which the poor resource users could be empowered to sustainably manage their resource base. The assumption was that the sharing of the management responsibilities between the state and the community of users would have led to equity in resource access, poverty reduction and resource sustainability. Thus, reducing the role of the state and enhancing that of the communities was seen as a solution to the problems of poverty and illegal fishing that are threatening the sustainability of the fishery and the fishers dependent on it. However, in spite of these proclaimed efforts, illegal fishing and poverty in Lake Victoria remain major threats to the long-term sustainability of the fishery, a fact that is raising questions on the efficacy of co-management in Lake Victoria. These questions have particularly focused on the co-management model and the neo-liberal ideals that underlie it, namely decentralization, participation and accountability. The central argument in this thesis, however, is that co-management performance in Lake Victoria is to a large extent shaped by the complex international, national, and local context in which it is implemented and which in turn shapes the problems of poverty and illegal fishing that co-management is supposed to address. The study concludes that the international and national politics behind the Nile perch fishery intersect with the cultural and social context in which the fishery is embedded to shape co-management performance at the local level. For analysis, the study applies a multi-level approach and draws insights from the common pool resources theory, the actor-oriented approach, the entitlement framework, and the theory of the state. Detailed interviews across scale, secondary data, policy documents, and laws, supported by quantitative data are the methods applied.

The oceans around the world have been heavily impacted by overfishing due to very intensive commercial fishing in recent times. A large number of fish stocks have already been fully exploited. Vessel Monitoring System has been put in place to regulate fishing vessels and enforce sustainable fisheries management. Data coming from such systems can be used for the detection of illegal, unregulated, and unreported fishing. In this thesis, we present various machine learning models for the classification of fishing trip trajectories. To train these models, we develop a trajectory segmentation algorithm to create trip trajectories out of raw data and design a graphical user interface for labeling the trip trajectories into fishing and non-fishing. We also examine the impact of the temporal resolution of the data. In conclusion, the CNN-Transformer network performed the best on the binary classification of two different fishing vessel types. During the project, we realized that segmentation of real trajectory data into trips poses many problems and presents the biggest obstacle. The experiment on the varying temporal resolution of the data showed that having a higher temporal resolution gives better modeling results but only to a certain point. / Haven runt om i världen har drabbats hårt av överfiske på grund av ett mycket intensivt kommersiellt fiske på senare tid. Ett stort antal fiskbestånd har redan utnyttjats fullt ut. Fartygsövervakningssystem har införts för att reglera fiskefartyg och upprätthålla hållbar fiskeförvaltning. Data som kommer från sådana system kan användas för att upptäcka olagligt, oreglerat och orapporterat fiske. I detta examensarbete presenterar vi olika maskininlärningsmodeller för klassificering av fisketursbanor. För att träna dessa modeller utvecklar vi en segmenteringsalgoritm för att skapa turbanor av rådata och designa ett grafiskt användargränssnitt för att märka resbanorna till fiske och icke-fiske. Vi undersöker också effekten av den tidsmässiga upplösningen av datan. Sammanfattningsvis presterade CNN-Transformer-nätverket bäst i den binära klassificeringen av två olika fiskefartygstyper. Under projektet insåg vi att segmentering av verkliga bandata till resor utgör många problem och utgör det största hindret. Experimentet på den varierande tidsupplösningen av data visade att en högre tidsupplösning ger bättre modelleringsresultat men bara till en viss punkt.

Le suivi, le contrôle et la surveillance (MCS) des pêches marines sont des problèmes essentiels pour la gestion durable des ressources halieutiques. Dans cette thèse, nous étudions le suivi spatial des activités des navires de pêche en utilisant les données de trajectoire du système de surveillance des navires (VMS) dans le cadre du projet INDESO (2013-2017). Notre objectif général est de développer une chaîne de traitement des données VMS afin de: i) effectuer un suivi de l'effort de pêche des flottilles de palangriers indonésiens, ii) détecter les activités de pêche illégales et évaluer leur importance. L'approche proposée repose sur des modèles de mélange gaussien (GMM) et les modèles de Markov cachés (HMM), en vue d'identifier les comportements élémentaires des navires de pêche, tels que les voyages, la recherche et les activités de pêche, dans un cadre non supervisé. Nous considérons différentes paramétrisations de ces modèles avec une étude particulière des palangriers indonésiens, pour lesquels nous pouvons bénéficier de données d'observateurs embarqués afin de procéder à une évaluation quantitative des modèles proposés et testés.Nous exploitons ensuite ces modèles statistiques pour deux objectifs différents: a) la discrimination des différents flottilles de pêche à partir des trajectoires des navires de pêche et l'application à la détection et à l'évaluation des activités de pêche illégale, b) l'évaluation d'un effort de pêche spatialisé à partir des données VMS. Nous obtenons de très bons taux de reconnaissance (environ 97%) pour la première tâche et nos expériences soutiennent le potentiel d'une exploration opérationnelle de l'approche proposée. En raison du nombre limité de données d'observateurs embarqués, seules des analyses préliminaires on pu être effectuées pour l'estimation de l'effort de pêche à partir des données VMS. Au-delà des développements méthodologiques potentiels, cette thèse met l'accent sur l'importance de la qualité de données d'observation en mer représentatives pour développer davantage l'exploitation des données VMS tant pour la recherche que pour les questions opérationnelles. / Monitoring, control and surveillance (MCS) of marine fisheries are critical issues for the sustainable management of marine fisheries. In this thesis we investigate the space-based monitoring of fishing vessel activities using Vessel Monitoring System (VMS) trajectory data in the context of INDESO project (2013-2017). Our general objective is to develop a processing chain of VMS data in order to: i) perform a follow-up of the fishing effort of the Indonesian longline fleets, ii) detect illegal fishing activities and assess their importance. The proposed approach relies on classical latent class models, namely Gaussian Mixture Models (GMM) and Hidden Markov Models (HMM), with a view to identifying elementary fishing vessel behaviors, such as travelling, searching and fishing activities, in a unsupervised framework. Following state-of-the-art approaches, we consider different parameterizations of these models with a specific focus on Indonesian longliners, for which we can benefit from at-sea observers¿ data to proceed to a quantitative evaluation. We then exploit these statistical models for two different objectives: a) the discrimination of different fishing fleets from fishing vessel trajectories and the application to the detection and assessment of illegal fishing activities, b) the assessment of a spatialized fishing effort from VMS data. We report good recognition rate (about 97%) for the former task and our experiments support the potential for an operational exploration of the proposed approach. Due to limited at-sea observers¿ data, only preliminary analyses could be carried out for the proposed VMS-derived fishing effort. Beyond potential methodological developments, this thesis emphasizes the importance of high-quality and representative at-sea observer data for further developing the exploitation of VMS data both for research and operational issues.