Social-ecological drivers of fleet behaviour and evidence of illegal fishing

UIDB/04647/2020 UIDP/04647/2020Managing the footprint of highly mobile fishing fleets is increasingly important due to continuing declines in fish populations. However, social-ecological drivers for fisher behaviour remain poorly understood for many fleets globally. Using the Sri Lankan fleet as a case study, we explored the role of social, environmental and policy drivers of effort distribution and illegal fishing. We used semi-structured interviews and participatory mapping with 95 fishers, combined with explanatory modelling (GLM) and multivariate statistics, including principal component analysis (PCA). Our findings highlighted the broad footprint (~3,800,000 km2) of this fleet, with fishing effort expended in high seas (53.9%), domestic (40.9%) and, illegally, in foreign waters (5.2%). Twenty-six per cent of fishers directly admitted to fishing illegally in foreign waters during interviews, whereas 62% of fishers indicated doing so during participatory mapping. GLMs explained underlying decisions of where to fish (36% of the total deviance in effort distribution) as a function of social variables (14%), notably distance from landing sites (13%), and environmental variables (11%), notably sea surface temperature (10%). Multivariate analysis revealed that individual fisher characteristics associated with illegal fishing, such as a level of reliance on sharks, vary across the fleet. The analysis of qualitative data suggested that the influence of interpersonal and community social networks and perceptions of higher catch value, particularly of sharks, may be important. Our approach demonstrated the utility of mixed methods research, including the collection of qualitative data, for creating a detailed understanding of spatial behaviour, including decisions of whether to fish illegally. Results highlighted the importance of adopting a social-ecological lens to investigate drivers for human behaviour and non-compliance with rules. We advocate for a nuanced approach to monitoring and managing of fleets, including investigating localised social drivers for illegal fishing and enhancing regional transparency in fleet monitoring. A free Plain Language Summary can be found within the Supporting Information of this article.publishersversionpublishe

Ocean-scale footprint of a highly mobile fishing fleet: Social-ecological drivers of fleet behaviour and evidence of illegal fishing.

Managing the footprint of highly mobile fishing fleets is increasingly important due to continuing declines in fish populations. However, social-ecological drivers for fisher behaviour remain poorly understood for many fleets globally. Using the Sri Lankan fleet as a case study, we explored the role of social, environmental and policy drivers of effort distribution and illegal fishing. We used semi-structured interviews and participatory mapping with 95 fishers, combined with explanatory modelling (GLM) and multivariate statistics, including principal component analysis (PCA). Our findings highlighted the broad footprint (~3,800,000 km2) of this fleet, with fishing effort expended in high seas (53.9%), domestic (40.9%) and, illegally, in foreign waters (5.2%). Twenty-six per cent of fishers directly admitted to fishing illegally in foreign waters during interviews, whereas 62% of fishers indicated doing so during participatory mapping. GLMs explained underlying decisions of where to fish (36% of the total deviance in effort distribution) as a function of social variables (14%), notably distance from landing sites (13%), and environmental variables (11%), notably sea surface temperature (10%). Multivariate analysis revealed that individual fisher characteristics associated with illegal fishing, such as a level of reliance on sharks, vary across the fleet. The analysis of qualitative data suggested that the influence of interpersonal and community social networks and perceptions of higher catch value, particularly of sharks, may be important. Our approach demonstrated the utility of mixed methods research, including the collection of qualitative data, for creating a detailed understanding of spatial behaviour, including decisions of whether to fish illegally. Results highlighted the importance of adopting a social-ecological lens to investigate drivers for human behaviour and non-compliance with rules. We advocate for a nuanced approach to monitoring and managing of fleets, including investigating localised social drivers for illegal fishing and enhancing regional transparency in fleet monitoring

Predicting spatial spread of rabies in skunk populations using surveillance data reported by the public

Background: Prevention and control of wildlife disease invasions relies on the ability to predict spatio-temporal dynamics and understand the role of factors driving spread rates, such as seasonality and transmission distance. Passive disease surveillance (i.e., case reports by public) is a common method of monitoring emergence of wildlife diseases, but can be challenging to interpret due to spatial biases and limitations in data quantity and quality. Methodology/Principal findings: We obtained passive rabies surveillance data from dead striped skunks (Mephitis mephitis) in an epizootic in northern Colorado, USA. We developed a dynamic patch-occupancy model which predicts spatio-temporal spreading while accounting for heterogeneous sampling. We estimated the distance travelled per transmission event, direction of invasion, rate of spatial spread, and effects of infection density and season. We also estimated mean transmission distance and rates of spatial spread using a phylogeographic approach on a subsample of viral sequences from the same epizootic. Both the occupancy and phylogeographic approaches predicted similar rates of spatio-temporal spread. Estimated mean transmission distances were 2.3 km (95% Highest Posterior Density (HPD95): 0.02, 11.9; phylogeographic) and 3.9 km (95% credible intervals (CI95): 1.4, 11.3; occupancy). Estimated rates of spatial spread in km/year were: 29.8 (HPD95: 20.8, 39.8; phylogeographic, branch velocity, homogenous model), 22.6 (HPD95: 15.3, 29.7; phylogeographic, diffusion rate, homogenous model) and 21.1 (CI95: 16.7, 25.5; occupancy). Initial colonization probability was twice as high in spring relative to fall. Conclusions/Significance: Skunk-to-skunk transmission was primarily local (< 4 km) suggesting that if interventions were needed, they could be applied at the wave front. Slower viral invasions of skunk rabies in western USA compared to a similar epizootic in raccoons in the eastern USA implies host species or landscape factors underlie the dynamics of rabies invasions. Our framework provides a straightforward method for estimating rates of spatial spread of wildlife diseases

Spatial Dynamics of the Severe Acute Respiratory Syndrome (SARS) Epidemic in Hong Kong in 2003

The Severe Acute Respiratory Syndrome (SARS) epidemic in 2003 was the first infectious disease outbreak caused by a novel pathogen in the twenty-first century. The outbreak in Hong Kong was the second largest worldwide and was characterised by a large proportion of hospital infections and a super-spreading event caused by environmental factors in residential buildings. Hospitals treating SARS cases were at high risk for transmission. I found that hospital outbreaks triggered community transmission as well as the formation of spatial clusters of community cases. The size of the community outbreak in an area increased with the size of the outbreak in the nearest hospital treating SARS, and an area was more likely to have no community-infected cases if it was far from hospitals treating SARS, or had less hospital-infected cases within the area. To quantify the transmission between hospital and community, I developed a spatial epidemic-tree-reconstruction method that uses gravity models to spatially define the probability of contact between individuals in the community. From the reconstructed probabilistic infection tree, I estimated that 24% of community transmission was likely to be infected by cases infected in hospitals, with infected patients discharged during their incubation period and hospital visitors the most important drivers of transmission from healthcare settings to the community. Healthcare workers were key drivers of hospital transmission, with the hospital-to-hospital reproduction number, excluding a single hospital super-spreading event, estimated to be 0.8. A typical community-acquired case was estimated to generate 0.6 cases in the community and 0.2 cases in the hospital in which they were subsequently hospitalised. My findings suggest that hospital infection control could be improved. Restricted hospital visitor policies could have been imposed for longer time during the outbreak and quarantine could be considered for those who recently visited or have been discharged from hospitals treating SARS cases

ON SPATIOTEMPORAL CONNECTIVITY DYNAMICS: PERSPECTIVES FROM A NATURALLY FRAGMENTED METAPOPULATION

Connectivity has quickly become a central tenet of ecological research, frequently evoked for conservation research and management activities. However, the concept of connectivity has proliferated into many forms for many different perspectives. Generally said, population distributions, demography, landscape, and dispersal all contribute to connectivity in a meaningful way. While great progress has been made in increasing realism in connectivity, one component seemed to stand out as being underappreciated: the role of population dynamics in the application of landscape connectivity. I began to acquire an appreciation for how common modeling approaches make assumptions about these core components of connectivity. In Chapter 1 I argue connectivity is a dynamic property of landscapes, influenced by population distributions, distribution of habitat, and dispersal behavior and present the conceptual demographically-weighted connectivity framework. Through computer simulations, I investigated the consequences of common assumptions to understand under which conditions each assumption was valid. In order to determine whether these theoretical simulation-based results applied in practice, I evaluated these assumptions empirically using a model system, the naturally fragmented mammalian metapopulation system in Assynt, Scotland, UK. In Chapter 2, I explore demographically-weighted connectivity and the implications of the common assumption that connectivity is a static component of the landscape. In chapter 3, I demonstrate that the characteristics of the inter-patch landscape, though which dispersal must occur for spatially structured populations to persist, matters when characterizing connectivity. The ability to uncover connectivity’s influence is only as good as our ability to detect our study species, and thus my final data chapter of the dissertation is a verification of emerging technological advances to measuring biodiversity and occupancy in the landscape using environmental DNA and camera trapping techniques. This dissertation helps provide evidence to the demographic nature of connectivity and how our modeling assumptions may impact the efficacy of conservation plans and management actions. This dissertation provide support for advances in both measuring and understanding occupancy and connectivity, both important to consider in a time of shifting conservation needs

ORÁCULO: Detection of Spatiotemporal Hot Spots of Conflict-Related Events Extracted from Online News Sources

Dissertation presented as the partial requirement for obtaining a Master's degree in Geographic Information Systems and ScienceAchieving situational awareness in peace operations requires understanding where and when conflict-related activity is most intense. However, the irregular nature of most factions hinders the use of remote sensing, while winning the trust of the host populations to allow the collection of wide-ranging human intelligence is a slow process. Thus, our proposed solution, ORÁCULO, is an information system which detects spatiotemporal hot spots of conflict-related activity by analyzing the patterns of events extracted from online news sources, allowing immediate situational awareness. To do so, it combines a closed-domain supervised event extractor with emerging hot spots analysis of event space-time cubes. The prototype of ORÁCULO was tested on tweets scraped from the Twitter accounts of local and international news sources covering the Central African Republic Civil War, and its test results show that it achieved near state-of-theart event extraction performance, significant overlap with a reference event dataset, and strong correlation with the hot spots space-time cube generated from the reference event dataset, proving the viability of the proposed solution. Future work will focus on improving the event extraction performance and on testing ORÁCULO in cooperation with peacekeeping organizations. Keywords: event extraction, natural language understanding, spatiotemporal analysis, peace operations, open-source intelligence.Atingir e manter a consciência situacional em operações de paz requer o conhecimento de quando e onde é que a atividade relacionada com o conflito é mais intensa. Porém, a natureza irregular da maioria das fações dificulta o uso de deteção remota, e ganhar a confiança das populações para permitir a recolha de informações é um processo moroso. Assim, a nossa solução proposta, ORÁCULO, consiste num sistema de informações que deteta “hot spots” espácio-temporais de atividade relacionada com o conflito através da análise dos padrões de eventos extraídos de fontes noticiosas online, (incluindo redes sociais), permitindo consciência situacional imediata. Nesse sentido, a nossa solução combina um extrator de eventos de domínio limitado baseado em aprendizagem supervisionada com a análise de “hot spots” emergentes de cubos espaçotempo de eventos. O protótipo de ORÁCULO foi testado em tweets recolhidos de fontes noticiosas locais e internacionais que cobrem a Guerra Civil da República Centro- Africana. Os resultados dos seus testes demonstram que foram conseguidos um desempenho de extração de eventos próximo do estado da arte, uma sobreposição significativa com um conjunto de eventos de referência e uma correlação forte com o cubo espaço-tempo de “hot spots” gerado a partir desse conjunto de referência, comprovando a viabilidade da solução proposta. Face aos resultados atingidos, o trabalho futuro focar-se-á em melhorar o desempenho de extração de eventos e em testar o sistema ORÁCULO em cooperação com organizações que conduzam operações paz

Spatiotemporal mortality and demographic trends in a small cetacean: Strandings to inform conservation management

With global increases in anthropogenic pressures on wildlife populations comes a responsibility to manage them effectively. The assessment of marine ecosystem health is challenging and often relies on monitoring indicator species, such as cetaceans. Most cetaceans are however highly mobile and spend the majority of their time hidden from direct view, resulting in uncertainty on even the most basic population metrics. Here, we discuss the value of long-term and internationally combined stranding records as a valuable source of information on the demographic and mortality trends of the harbour porpoise (Phocoena phocoena) in the North Sea. We analysed stranding records (n = 16,181) from 1990 to 2017 and demonstrate a strong heterogeneous seasonal pattern of strandings throughout the North Sea, indicative of season-specific distribution or habitat use, and season-specific mortality. The annual incidence of strandings has increased since 1990, with a notable steeper rise particularly in the southern North Sea since 2005. A high density of neonatal strandings occurred specifically in the eastern North Sea, indicative of areas important for calving, and large numbers of juvenile males stranded in the southern parts, indicative of a population sink or reflecting higher male dispersion. These findings highlight the power of stranding records to detect potentially vulnerable population groups in time and space. This knowledge is vital for managers and can guide, for example, conservation measures such as the establishment of time-area-specific limits to potentially harmful human activities, aiming to reduce the number and intensity of human-wildlife conflicts

Spatiotemporal mortality and demographic trends in a small cetacean: Strandings to inform conservation management

With global increases in anthropogenic pressures on wildlife populations comes a responsibility to manage them effectively. The assessment of marine ecosystem health is challenging and often relies on monitoring indicator species, such as cetaceans. Most cetaceans are however highly mobile and spend the majority of their time hidden from direct view, resulting in uncertainty on even the most basic population metrics. Here, we discuss the value of long-term and internationally combined stranding records as a valuable source of information on the demographic and mortality trends of the harbour porpoise (Phocoena phocoena) in the North Sea. We analysed stranding records (n = 16,181) from 1990 to 2017 and demonstrate a strong heterogeneous seasonal pattern of strandings throughout the North Sea, indicative of season-specific distribution or habitat use, and season-specific mortality. The annual incidence of strandings has increased since 1990, with a notable steeper rise particularly in the southern North Sea since 2005. A high density of neonatal strandings occurred specifically in the eastern North Sea, indicative of areas important for calving, and large numbers of juvenile males stranded in the southern parts, indicative of a population sink or reflecting higher male dispersion. These findings highlight the power of stranding records to detect potentially vulnerable population groups in time and space. This knowledge is vital for managers and can guide, for example, conservation measures such as the establishment of time-area-specific limits to potentially harmful human activities, aiming to reduce the number and intensity of human-wildlife conflicts

Assessing, monitoring and mapping forest resources in the Blue Nile Region of Sudan using an object-based image analysis approach

Following the hierarchical nature of forest resource management, the present work focuses on the natural forest cover at various abstraction levels of details, i.e. categorical land use/land cover (LU/LC) level and a continuous empirical estimation of local operational level. As no single sensor presently covers absolutely all the requirements of the entire levels of forest resource assessment, multisource imagery (i.e. RapidEye, TERRA ASTER and LANDSAT TM), in addition to other data and knowledge have been examined. To deal with this structure, an object-based image analysis (OBIA) approach has been assessed in the destabilized Blue Nile region of Sudan as a potential solution to gather the required information for future forest planning and decision making. Moreover, the spatial heterogeneity as well as the rapid changes observed in the region motivates the inspection for more efficient, flexible and accurate methods to update the desired information. An OBIA approach has been proposed as an alternative analysis framework that can mitigate the deficiency associated with the pixel-based approach. In this sense, the study examines the most popular pixel-based maximum likelihood classifier, as an example of the behavior of spectral classifier toward respective data and regional specifics. In contrast, the OBIA approach analyzes remotely sensed data by incorporating expert analyst knowledge and complimentary ancillary data in a way that somehow simulates human intelligence for image interpretation based on the real-world representation of the features. As the segment is the basic processing unit, various combinations of segmentation criteria were tested to separate similar spectral values into groups of relatively homogeneous pixels. At the categorical subtraction level, rules were developed and optimum features were extracted for each particular class. Two methods were allocated (i.e. Rule Based (RB) and Nearest Neighbour (NN) Classifier) to assign segmented objects to their corresponding classes. Moreover, the study attempts to answer the questions whether OBIA is inherently more precise at fine spatial resolution than at coarser resolution, and how both pixel-based and OBIA approaches can be compared regarding relative accuracy in function of spatial resolution. As anticipated, this work emphasizes that the OBIA approach is can be proposed as an advanced solution particulary for high resolution imagery, since the accuracies were improved at the different scales applied compare with those of pixel-based approach. Meanwhile, the results achieved by the two approaches are consistently high at a finer RapidEye spatial resolution, and much significantly enhanced with OBIA. Since the change in LU/LC is rapid and the region is heterogeneous as well as the data vary regarding the date of acquisition and data source, this motivated the implementation of post-classification change detection rather than radiometric transformation methods. Based on thematic LU/LC maps, series of optimized algorithms have been developed to depict the dynamics in LU/LC entities. Therefore, detailed change “from-to” information classes as well as changes statistics were produced. Furthermore, the produced change maps were assessed, which reveals that the accuracy of the change maps is consistently high. Aggregated to the community-level, social survey of household data provides a comprehensive perspective additionally to EO data. The predetermined hot spots of degraded and successfully recovered areas were investigated. Thus, the study utilized a well-designed questionnaire to address the factors affecting land-cover dynamics and the possible solutions based on local community's perception. At the operational structural forest stand level, the rationale for incorporating these analyses are to offer a semi-automatic OBIA metrics estimates from which forest attribute is acquired through automated segmentation algorithms at the level of delineated tree crowns or clusters of crowns. Correlation and regression analyses were applied to identify the relations between a wide range of spectral and textural metrics and the field derived forest attributes. The acquired results from the OBIA framework reveal strong relationships and precise estimates. Furthermore, the best fitted models were cross-validated with an independent set of field samples, which revealed a high degree of precision. An important question is how the spatial resolution and spectral range used affect the quality of the developed model this was also discussed based on the different sensors examined. To conclude, the study reveals that the OBIA has proven capability as an efficient and accurate approach for gaining knowledge about the land features, whether at the operational forest structural attributes or categorical LU/LC level. Moreover, the methodological framework exhibits a potential solution to attain precise facts and figures about the change dynamics and its driving forces.Da das Waldressourcenmanagement hierarchisch strukturiert ist, beschäftigt sich die vorliegende Arbeit mit der natürlichen Waldbedeckung auf verschiedenen Abstraktionsebenen, das heißt insbesondere mit der Ebene der kategorischen Landnutzung / Landbedeckung (LU/LC) sowie mit der kontinuierlichen empirischen Abschätzung auf lokaler operativer Ebene. Da zurzeit kein Sensor die Anforderungen aller Ebenen der Bewertung von Waldressourcen und von Multisource-Bildmaterialien (d.h. RapidEye, TERRA ASTER und LANDSAT TM) erfüllen kann, wurden zusätzlich andere Formen von Daten und Wissen untersucht und in die Arbeit mit eingebracht. Es wurde eine objekt-basierte Bildanalyse (OBIA) in einer destabilisierten Region des Blauen Nils im Sudan eingesetzt, um nach möglichen Lösungen zu suchen, erforderliche Informationen für die zukünftigen Waldplanung und die Entscheidungsfindung zu sammeln. Außerdem wurden die räumliche Heterogenität, sowie die sehr schnellen Änderungen in der Region untersucht. Dies motiviert nach effizienteren, flexibleren und genaueren Methoden zu suchen, um die gewünschten aktuellen Informationen zu erhalten. Das Konzept von OBIA wurde als Substitution-Analyse-Rahmen vorgeschlagen, um die Mängel vom früheren pixel-basierten Konzept abzumildern. In diesem Sinne untersucht die Studie die beliebtesten Maximum-Likelihood-Klassifikatoren des pixel-basierten Konzeptes als Beispiel für das Verhalten der spektralen Klassifikatoren in dem jeweiligen Datenbereich und der Region. Im Gegensatz dazu analysiert OBIA Fernerkundungsdaten durch den Einbau von Wissen des Analytikers sowie kostenlose Zusatzdaten in einer Art und Weise, die menschliche Intelligenz für die Bildinterpretation als eine reale Darstellung der Funktion simuliert. Als ein Segment einer Basisverarbeitungseinheit wurden verschiedene Kombinationen von Segmentierungskriterien getestet um ähnliche spektrale Werte in Gruppen von relativ homogenen Pixeln zu trennen. An der kategorische Subtraktionsebene wurden Regeln entwickelt und optimale Eigenschaften für jede besondere Klasse extrahiert. Zwei Verfahren (Rule Based (RB) und Nearest Neighbour (NN) Classifier) wurden zugeteilt um die segmentierten Objekte der entsprechenden Klasse zuzuweisen. Außerdem versucht die Studie die Fragen zu beantworten, ob OBIA in feiner räumlicher Auflösung grundsätzlich genauer ist als eine gröbere Auflösung, und wie beide, das pixel-basierte und das OBIA Konzept sich in einer relativen Genauigkeit als eine Funktion der räumlichen Auflösung vergleichen lassen. Diese Arbeit zeigt insbesondere, dass das OBIA Konzept eine fortschrittliche Lösung für die Bildanalyse ist, da die Genauigkeiten - an den verschiedenen Skalen angewandt - im Vergleich mit denen der Pixel-basierten Konzept verbessert wurden. Unterdessen waren die berichteten Ergebnisse der feineren räumlichen Auflösung nicht nur für die beiden Ansätze konsequent hoch, sondern durch das OBIA Konzept deutlich verbessert. Die schnellen Veränderungen und die Heterogenität der Region sowie die unterschiedliche Datenherkunft haben dazu geführt, dass die Umsetzung von Post-Klassifizierungs- Änderungserkennung besser geeignet ist als radiometrische Transformationsmethoden. Basierend auf thematische LU/LC Karten wurden Serien von optimierten Algorithmen entwickelt, um die Dynamik in LU/LC Einheiten darzustellen. Deshalb wurden für Detailänderung "von-bis"-Informationsklassen sowie Veränderungsstatistiken erstellt. Ferner wurden die erzeugten Änderungskarten bewertet, was zeigte, dass die Genauigkeit der Änderungskarten konstant hoch ist. Aggregiert auf die Gemeinde-Ebene bieten Sozialerhebungen der Haushaltsdaten eine umfassende zusätzliche Sichtweise auf die Fernerkundungsdaten. Die vorher festgelegten degradierten und erfolgreich wiederhergestellten Hot Spots wurden untersucht. Die Studie verwendet einen gut gestalteten Fragebogen um Faktoren die die Dynamik der Änderung der Landbedeckung und mögliche Lösungen, die auf der Wahrnehmung der Gemeinden basieren, anzusprechen. Auf der Ebene des operativen strukturellen Waldbestandes wird die Begründung für die Einbeziehung dieser Analysen angegeben um semi-automatische OBIA Metriken zu schätzen, die aus dem Wald-Attribut durch automatisierte Segmentierungsalgorithmen in den Baumkronen abgegrenzt oder Cluster von Kronen Ebenen erworben wird. Korrelations- und Regressionsanalysen wurden angewandt, um die Beziehungen zwischen einer Vielzahl von spektralen und strukturellen Metriken und den aus den Untersuchungsgebieten abgeleiteten Waldattributen zu identifizieren. Die Ergebnisse des OBIA Rahmens zeigen starke Beziehungen und präzise Schätzungen. Die besten Modelle waren mit einem unabhängigen Satz von kreuz-validierten Feldproben ausgestattet, welche hohe Genauigkeiten ergaben. Eine wichtige Frage ist, wie die räumliche Auflösung und die verwendete Bandbreite die Qualität der entwickelten Modelle auch auf der Grundlage der verschiedenen untersuchten Sensoren beeinflussen. Schließlich zeigt die Studie, dass OBIA in der Lage ist, als ein effizienter und genauer Ansatz Kenntnisse über die Landfunktionen zu erlangen, sei es bei operativen Attributen der Waldstruktur oder auch auf der kategorischen LU/LC Ebene. Außerdem zeigt der methodischen Rahmen eine mögliche Lösung um präzise Fakten und Zahlen über die Veränderungsdynamik und ihre Antriebskräfte zu ermitteln