Integrating knowledge about complex adaptive systems: insights from modelling the Eastern Baltic cod

Currently, the Eastern Baltic cod (EBC) is in continuing decline. Supporting management efforts to assist in its recovery will require a functional understanding of the dynamics of the EBC and the Baltic ecosystem. However, aquatic environments are challenging to research as they are elusive, encompass many scientific disciplines and are complex adaptive systems. This thesis explores how modelling and simulation methods can be applied and adapted to meet the specific needs of fisheries biologies’ current challenges regarding the EBC and potentially those of other stocks in similar situations.Aktuell verschlechtert sich der Zustand des Ostdorsches anhaltend und unterstützende Bewirtschaftungsmaßnahmen zu identifizieren erfordert ein funktionales Verständnis des Bestands und des Ökosystems Ostsee. Die Erforschung aquatischer Systeme ist jedoch schwierig: sie sind flüchtig, umfassen eine Vielzahl an Disziplinen und sind komplexe adaptiver Systeme. Diese Arbeit untersucht, wie Modellierungs- und Simulationsmethoden angewendet und angepasst werden können, um den Anforderungen der Fischereibiologie beim Ostdorsch und potentiell bei anderer Bestände in ähnlichen Situationen zu begegnen

Multilevel Weighted Support Vector Machine for Classification on Healthcare Data with Missing Values

This work is motivated by the needs of predictive analytics on healthcare data as represented by Electronic Medical Records. Such data is invariably problematic: noisy, with missing entries, with imbalance in classes of interests, leading to serious bias in predictive modeling. Since standard data mining methods often produce poor performance measures, we argue for development of specialized techniques of data-preprocessing and classification. In this paper, we propose a new method to simultaneously classify large datasets and reduce the effects of missing values. It is based on a multilevel framework of the cost-sensitive SVM and the expected maximization imputation method for missing values, which relies on iterated regression analyses. We compare classification results of multilevel SVM-based algorithms on public benchmark datasets with imbalanced classes and missing values as well as real data in health applications, and show that our multilevel SVM-based method produces fast, and more accurate and robust classification results.Comment: arXiv admin note: substantial text overlap with arXiv:1503.0625

Models for an Ecosystem Approach to Fisheries

This document is one outcome from a workshop held in Gizo in October 2010 attended by 82 representatives from government, NGO's private sector, and communities. The target audience for the document is primarily organizations planning to work with coastal communities of Solomon Islands to implement Community-Based Resource Management (CBRM). It is however also envisaged that the document will serve as a reference for communities to better understand what to expect from their partners and also for donors, to be informed about agreed approaches amongst Solomon Islands stakeholders. This document does not attempt to summarize all the outcomes of the workshop; rather it focuses on the Solomon Islands Coral Triangle Initiative (CTI) National Plan of Action (NPoA): Theme 1: Support and implementation of CBRM and specifically, the scaling up of CBRM in Solomon Islands. Most of the principles given in this document are derived from experiences in coastal communities and ecosystems as, until relatively recently, these have received most attention in Solomon Islands resource management. It is recognized however that the majority of these principles will be applicable to both coastal and terrestrial initiatives. This document synthesizes information provided by stakeholders at the October 2010 workshop and covers some basic principles of engagement and implementation that have been learned over more than twenty years of activities by the stakeholder partners in Solomon Islands. The document updates and expands on a summary of guiding principles for CBRM which was originally prepared by the Solomon Islands Locally Managed Marine Area Network (SILMMA) in 2007

Testing the implications of a permanent or seasonal marine reserve on the population dynamics of Eastern Baltic cod under varying environmental conditions

In order to test the implications of the establishment of a marine reserve in the Baltic Sea, a spatially disaggregated, discrete time, age-structured model for the Eastern Baltic cod (Gadus morhua callarias L.) stock was constructed. Functional relationships for recruitment and predation mortality were developed by multiple regression analyses. The resultant model output compares well with observed data from the fishery. The model was then applied to simulate stock development over a 50 year time period using different management policies and a variety of environmental conditions. The investigated management policies reduce fishing mortality and range from a moratorium on the Eastern Baltic cod fishery via the establishment of a permanent or a seasonal marine reserve in ICES subdivision 25 to a fishing as usual scenario. The environmental conditions incorporated were based on the size of the reproductive volume (RV) and comprise a best case and a worst case of reproductive conditions, and two more realistic scenarios, where we assumed that a historic series of RV-sizes reoccurs over the simulation period. Our results show a strong dependence of stock dynamics on the environmental conditions. Under prevailing low RV, our model projects stock extinction by the year 2020, if fishing continues as usual. Under the restrictive scenarios, where fishing mortality is reduced either directly or by implementation of a marine reserve, the stock benefits from an increase in stock size and an improved age-structure. A seasonal closure of SD 25 as opposed to a closure of the entire Baltic Sea appears to be sufficient to prevent the Eastern Baltic cod stock from falling below safe biological limits.Baltic cod, management, age-structured model, population dynamics, MPA, environmental variability, reproductive volume

Residue analyses and exposure assessment of the Irish population to nitrofuran metabolites from different food commodities in 2009–2010

peer-reviewedAn exposure assessment to nitrofuran residues was performed for three human populations (adults, teenagers and children), based on residue analyses of foods of animal origin (liver, honey, eggs and aquaculture) covering the 2-year period 2009– 2010. The occurrence of nitrofuran metabolites in food on the Irish market was determined for the selected period using the data from Ireland’s National Food Residue Database (NFRD) and from results obtained from the analysis of retail samples (aquaculture and honey). Laboratory analyses of residues were performed by methods validated in accordance with Commission Decision 2002/657/EC regarding performance of the analytical method and interpretation of results. Semicarbazide (SEM) was the contaminant most frequently identified and its content ranged from 0.09 to 1.27 μg kg−1. SEM is currently used as a marker of nitrofuran abuse, but it may also occur from other sources. The presence of nitrofuran metabolite 3-amino-2-oxazolidinone (AOZ) was detected in two aquaculture samples (prawns) at 1.63 and 1.14 μg kg−1, but such a low number of positive cases did not present sufficient data for a full AOZ exposure assessment. Therefore, the evaluation of exposure was focused on SEM-containing food groups only. Exposure assessments were completed using a probabilistic approach that generated 10 iterations. The results of both the upper- and lower-bound exposure assessments demonstrate that SEM exposure for Irish adults, teenagers and children from selected food commodities are well below EFSA-estimated safe levels.This research was funded by the Food for Health Research Initiative (FHRI) administered by the Irish Department of Agriculture, Food and the Marine and the Health Research Board (Contract 07FHRIAFRC5

Rebuilding the Eastern Baltic cod stock under environmental change - a preliminary approach using stock, environmental, and management constraints

The population dynamics of the Eastern Baltic cod (Gadus morhua callarias L.), unlike many other stocks, shows a strong dependency on environmental conditions. To test the implications of different management policies on the stock and the fishery in a system of global environmental change, we apply a spatially disaggregated, discrete time, age-structured model of the Eastern Baltic cod stock in 50 year simulation analyses. The simulation provides an analysis of stock, yield, and revenue development under various management policies and environmental scenarios. The policy analysis, focusing on different regulations of fishing mortality, is embedded into three environmental scenarios, assuming low, medium, or high climate and environmental change. The environmental assumptions are based on simulation results from a coupled atmosphere-ocean regional climate model, which project salinity in the Baltic Sea to decrease by 7-47% in the period 2071-2100 relative to the reference period 1961-1990. Our simulation results show that a significant reduction in fishing mortality is necessary for achieving high long-term economic yields. Moreover, under the presented environmental scenarios, a stock collapse cannot be prevented. It can, however, be postponed by the establishment of a marine reserve in ICES subdivision 25.Baltic cod, climate change, environmental variability, reproductive volume, population dynamics, management, policy, age-structured model, temporal marine reserve

Model Assisted Variable Clustering: Minimax-optimal Recovery and Algorithms

Model-based clustering defines population level clusters relative to a model that embeds notions of similarity. Algorithms tailored to such models yield estimated clusters with a clear statistical interpretation. We take this view here and introduce the class of G-block covariance models as a background model for variable clustering. In such models, two variables in a cluster are deemed similar if they have similar associations will all other variables. This can arise, for instance, when groups of variables are noise corrupted versions of the same latent factor. We quantify the difficulty of clustering data generated from a G-block covariance model in terms of cluster proximity, measured with respect to two related, but different, cluster separation metrics. We derive minimax cluster separation thresholds, which are the metric values below which no algorithm can recover the model-defined clusters exactly, and show that they are different for the two metrics. We therefore develop two algorithms, COD and PECOK, tailored to G-block covariance models, and study their minimax-optimality with respect to each metric. Of independent interest is the fact that the analysis of the PECOK algorithm, which is based on a corrected convex relaxation of the popular K-means algorithm, provides the first statistical analysis of such algorithms for variable clustering. Additionally, we contrast our methods with another popular clustering method, spectral clustering, specialized to variable clustering, and show that ensuring exact cluster recovery via this method requires clusters to have a higher separation, relative to the minimax threshold. Extensive simulation studies, as well as our data analyses, confirm the applicability of our approach.Comment: Maintext: 38 pages; supplementary information: 37 page

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range

Simulating the conflict between reputation and profitability for online rating portals

We simulate the process of possible interactions between a set of competitive services and a set of portals that provide online rating for these services. We argue that to have a profitable business, these portals are forced to have subscribed services that are rated by the portals. To satisfy the subscribing services, we make the assumption that the portals improve the rating of a given service by one unit per transaction that involves payment. In this study we follow the 'what-if' methodology, analysing strategies that a service may choose from to select the best portal for it to subscribe to, and strategies for a portal to accept the subscription such that its reputation loss, in terms of the integrity of its ratings, is minimised. We observe that the behaviour of the simulated agents in accordance to our model is quite natural from the real-would perspective. One conclusion from the simulations is that under reasonable conditions, if most of the services and rating portals in a given industry do not accept a subscription policy similar to the one indicated above, they will lose, respectively, their ratings and reputations, and, moreover the rating portals will have problems in making a profit. Our prediction is that the modern portal-rating based economy sector will eventually evolve into a subscription process similar to the one we suggest in this study, as an alternative to a business model based purely on advertising