Bibliometría

A principios de 1990, los documentalistas comienzan a interesarse en hacer aplicaciones matemáticas y estadísticas en las unidades bibliográficas. F. J. Coles y Nellie B. Eales en 1917 hicieron el primer estudio con un grupo de títulos de documentos cuyo análisis consideraba el país de origen (White, p. 35). En 1923, E. Wyndham Hulme fue la primera persona en usar el término "estadísticas bibliográficas".Y propuso la utilización de métodos estadísticos para tener parámetros que sirvan para conocer el proceso de la comunicación escrita y, la naturaleza y curso del desarrollo de una disciplina. Para lograr ese aspecto empezó contando un número de documentos y analizando varias facetas de la comunicación escrita empleada en ellos (Ferrante, p. 201). En un documento escrito en 1969, Alan Pritchard propuso el término bibliometría para reemplazar el término "estadísticas bibliográficas" empleado por Hulme, argumentando que el, término es ambiguo, no muy descriptivo y que puede ser confundido con las estadísticas puras o estadísticas de bibliografías. El definió el término bibliometría como la aplicación de la matemática y métodos estadísticos a los libros y otros documentos (p. 348-349). Y desde ese momento se ha utilizado este término.

Detección, diagnóstico e intervención temprana en niños menores de tres años de alto riesgo biológico y ambiental pertenecientes a la comunidad indígena de Salasaca provincia de Tungurahua

The main objective on this research is to evaluate and detect the profile of development and possible deviations that expouses a high biological, social and / or environmental risk on Indigenous children under three years old who attend to Child Centers of Good Living in the Indigenous Community of Salasaca - Tungurahua. The study was conducted with 90 children whom attend these centers. The Bayley Scale for Infant Development III (Bayley Scales for Infant Development - BSID) was applied to the study, for it was a standardized international test for scientific research on child development. It values the state of development and identifies deficits on children from 0 to 42 months old. Two types of questionnaires were applied to the Technical Assistants Child Development and to the Daily care Child Centers. Another querionary was used for the mothers of this centers in order to establish the level of knowledge over some factors, which may influence on child development during early childhood, as well as the parenting patterns characteristic of the indigenous community of Salasaca- Tungurahua. Analytical, synthetical and statistical methods for results interpretation were used for the Theoretical framework of this work. The scope of this research is the socio educative type. It benefits generally to all society particularly to children on infant stage and to the Indigenous Community of Salasaca...

The application of statistical process control charts to the detection and monitoring of hospital-acquired infections

The monitoring of infection control indicators including hospital-acquired infections is an established part of quality maintenance programmes in many health-care facilities. However, surveillance data use can be frustrated by the infrequent nature of many infections. Traditional methods of analysis often provide delayed identification of increasing infection occurrence, placing patients at preventable risk. The application of Shewhart, Cumulative Sum (CUSUM) and Exponentially Weighted Moving Average (EWMA) statistical process control charts to the monitoring of indicator infections allows continuous real-time assessment. The Shewhart chart will detect large changes, while CUSUM and EWMA methods are more suited to recognition of small to moderate sustained change. When used together, Shewhart and EWMA methods are ideal for monitoring bacteraemia and multiresistant organism rates. Shewhart and CUSUM charts are suitable for surgical infection surveillance.

Handling random errors and biases in methods used for short-term dietary assessment

Epidemiological studies have shown the effect of diet on the incidence of chronic diseases; however, proper planning, designing, and statistical modeling are necessary to obtain precise and accurate food consumption data. Evaluation methods used for short-term assessment of food consumption of a population, such as tracking of food intake over 24h or food diaries, can be affected by random errors or biases inherent to the method. Statistical modeling is used to handle random errors, whereas proper designing and sampling are essential for controlling biases. The present study aimed to analyze potential biases and random errors and determine how they affect the results. We also aimed to identify ways to prevent them and/or to use statistical approaches in epidemiological studies involving dietary assessments.

Some reflections on acquisition, processing and analysis of statistical data in forest soils

Beyond the classical statistical approaches (determination of basic statistics, regression analysis, ANOVA, etc.) a new set of applications of different statistical techniques has increasingly gained relevance in the analysis, processing and interpretation of data concerning the characteristics of forest soils. This is possible to be seen in some of the recent publications in the context of Multivariate Statistics. These new methods require additional care that is not always included or refered in some approaches. In the particular case of geostatistical data applications it is necessary, besides to geo-reference all the data acquisition, to collect the samples in regular grids and in sufficient quantity so that the variograms can reflect the spatial distribution of soil properties in a representative manner. In the case of the great majority of Multivariate Statistics techniques (Principal Component Analysis, Correspondence Analysis, Cluster Analysis, etc.) despite the fact they do not require in most cases the assumption of normal distribution, they however need a proper and rigorous strategy for its utilization. In this work, some reflections about these methodologies and, in particular, about the main constraints that often occur during the information collecting process and about the various linking possibilities of these different techniques will be presented. At the end, illustrations of some particular cases of the applications of these statistical methods will also be presented.

Extremum estimators and stochastic optimization methods

Submitted in partial fulfillment for the Requirements for the Degree of PhD in Mathematics, in the Speciality of Statistics in the Faculdade de Ciências e Tecnologia

Risk and global change : developing scientific methods for advocacy and awareness raising

Les catastrophes sont souvent perçues comme des événements rapides et aléatoires. Si les déclencheurs peuvent être soudains, les catastrophes, elles, sont le résultat d'une accumulation des conséquences d'actions et de décisions inappropriées ainsi que du changement global. Pour modifier cette perception du risque, des outils de sensibilisation sont nécessaires. Des méthodes quantitatives ont été développées et ont permis d'identifier la distribution et les facteurs sous- jacents du risque.¦Le risque de catastrophes résulte de l'intersection entre aléas, exposition et vulnérabilité. La fréquence et l'intensité des aléas peuvent être influencées par le changement climatique ou le déclin des écosystèmes, la croissance démographique augmente l'exposition, alors que l'évolution du niveau de développement affecte la vulnérabilité. Chacune de ses composantes pouvant changer, le risque est dynamique et doit être réévalué périodiquement par les gouvernements, les assurances ou les agences de développement. Au niveau global, ces analyses sont souvent effectuées à l'aide de base de données sur les pertes enregistrées. Nos résultats montrent que celles-ci sont susceptibles d'être biaisées notamment par l'amélioration de l'accès à l'information. Elles ne sont pas exhaustives et ne donnent pas d'information sur l'exposition, l'intensité ou la vulnérabilité. Une nouvelle approche, indépendante des pertes reportées, est donc nécessaire.¦Les recherches présentées ici ont été mandatées par les Nations Unies et par des agences oeuvrant dans le développement et l'environnement (PNUD, l'UNISDR, la GTZ, le PNUE ou l'UICN). Ces organismes avaient besoin d'une évaluation quantitative sur les facteurs sous-jacents du risque, afin de sensibiliser les décideurs et pour la priorisation des projets de réduction des risques de désastres.¦La méthode est basée sur les systèmes d'information géographique, la télédétection, les bases de données et l'analyse statistique. Une importante quantité de données (1,7 Tb) et plusieurs milliers d'heures de calculs ont été nécessaires. Un modèle de risque global a été élaboré pour révéler la distribution des aléas, de l'exposition et des risques, ainsi que pour l'identification des facteurs de risque sous- jacent de plusieurs aléas (inondations, cyclones tropicaux, séismes et glissements de terrain). Deux indexes de risque multiples ont été générés pour comparer les pays. Les résultats incluent une évaluation du rôle de l'intensité de l'aléa, de l'exposition, de la pauvreté, de la gouvernance dans la configuration et les tendances du risque. Il apparaît que les facteurs de vulnérabilité changent en fonction du type d'aléa, et contrairement à l'exposition, leur poids décroît quand l'intensité augmente.¦Au niveau local, la méthode a été testée pour mettre en évidence l'influence du changement climatique et du déclin des écosystèmes sur l'aléa. Dans le nord du Pakistan, la déforestation induit une augmentation de la susceptibilité des glissements de terrain. Les recherches menées au Pérou (à base d'imagerie satellitaire et de collecte de données au sol) révèlent un retrait glaciaire rapide et donnent une évaluation du volume de glace restante ainsi que des scénarios sur l'évolution possible.¦Ces résultats ont été présentés à des publics différents, notamment en face de 160 gouvernements. Les résultats et les données générées sont accessibles en ligne (http://preview.grid.unep.ch). La méthode est flexible et facilement transposable à des échelles et problématiques différentes, offrant de bonnes perspectives pour l'adaptation à d'autres domaines de recherche.¦La caractérisation du risque au niveau global et l'identification du rôle des écosystèmes dans le risque de catastrophe est en plein développement. Ces recherches ont révélés de nombreux défis, certains ont été résolus, d'autres sont restés des limitations. Cependant, il apparaît clairement que le niveau de développement configure line grande partie des risques de catastrophes. La dynamique du risque est gouvernée principalement par le changement global.¦Disasters are often perceived as fast and random events. If the triggers may be sudden, disasters are the result of an accumulation of actions, consequences from inappropriate decisions and from global change. To modify this perception of risk, advocacy tools are needed. Quantitative methods have been developed to identify the distribution and the underlying factors of risk.¦Disaster risk is resulting from the intersection of hazards, exposure and vulnerability. The frequency and intensity of hazards can be influenced by climate change or by the decline of ecosystems. Population growth increases the exposure, while changes in the level of development affect the vulnerability. Given that each of its components may change, the risk is dynamic and should be reviewed periodically by governments, insurance companies or development agencies. At the global level, these analyses are often performed using databases on reported losses. Our results show that these are likely to be biased in particular by improvements in access to information. International losses databases are not exhaustive and do not give information on exposure, the intensity or vulnerability. A new approach, independent of reported losses, is necessary.¦The researches presented here have been mandated by the United Nations and agencies working in the development and the environment (UNDP, UNISDR, GTZ, UNEP and IUCN). These organizations needed a quantitative assessment of the underlying factors of risk, to raise awareness amongst policymakers and to prioritize disaster risk reduction projects.¦The method is based on geographic information systems, remote sensing, databases and statistical analysis. It required a large amount of data (1.7 Tb of data on both the physical environment and socio-economic parameters) and several thousand hours of processing were necessary. A comprehensive risk model was developed to reveal the distribution of hazards, exposure and risk, and to identify underlying risk factors. These were performed for several hazards (e.g. floods, tropical cyclones, earthquakes and landslides). Two different multiple risk indexes were generated to compare countries. The results include an evaluation of the role of the intensity of the hazard, exposure, poverty, governance in the pattern and trends of risk. It appears that the vulnerability factors change depending on the type of hazard, and contrary to the exposure, their weight decreases as the intensity increases.¦Locally, the method was tested to highlight the influence of climate change and the ecosystems decline on the hazard. In northern Pakistan, deforestation exacerbates the susceptibility of landslides. Researches in Peru (based on satellite imagery and ground data collection) revealed a rapid glacier retreat and give an assessment of the remaining ice volume as well as scenarios of possible evolution.¦These results were presented to different audiences, including in front of 160 governments. The results and data generated are made available online through an open source SDI (http://preview.grid.unep.ch). The method is flexible and easily transferable to different scales and issues, with good prospects for adaptation to other research areas. The risk characterization at a global level and identifying the role of ecosystems in disaster risk is booming. These researches have revealed many challenges, some were resolved, while others remained limitations. However, it is clear that the level of development, and more over, unsustainable development, configures a large part of disaster risk and that the dynamics of risk is primarily governed by global change.

Detecting, quantifying and adjusting for publication bias in meta-analyses: protocol of a systematic review on methods.

BACKGROUND: Health professionals and policymakers aspire to make healthcare decisions based on the entire relevant research evidence. This, however, can rarely be achieved because a considerable amount of research findings are not published, especially in case of 'negative' results - a phenomenon widely recognized as publication bias. Different methods of detecting, quantifying and adjusting for publication bias in meta-analyses have been described in the literature, such as graphical approaches and formal statistical tests to detect publication bias, and statistical approaches to modify effect sizes to adjust a pooled estimate when the presence of publication bias is suspected. An up-to-date systematic review of the existing methods is lacking. METHODS/DESIGN: The objectives of this systematic review are as follows:âeuro¢ To systematically review methodological articles which focus on non-publication of studies and to describe methods of detecting and/or quantifying and/or adjusting for publication bias in meta-analyses.âeuro¢ To appraise strengths and weaknesses of methods, the resources they require, and the conditions under which the method could be used, based on findings of included studies.We will systematically search Web of Science, Medline, and the Cochrane Library for methodological articles that describe at least one method of detecting and/or quantifying and/or adjusting for publication bias in meta-analyses. A dedicated data extraction form is developed and pilot-tested. Working in teams of two, we will independently extract relevant information from each eligible article. As this will be a qualitative systematic review, data reporting will involve a descriptive summary. DISCUSSION: Results are expected to be publicly available in mid 2013. This systematic review together with the results of other systematic reviews of the OPEN project (To Overcome Failure to Publish Negative Findings) will serve as a basis for the development of future policies and guidelines regarding the assessment and handling of publication bias in meta-analyses.

REGSTATTOOLS: freeware statistical tools for the analysis of disease population databases used in health and social studies

Background: The repertoire of statistical methods dealing with the descriptive analysis of the burden of a disease has been expanded and implemented in statistical software packages during the last years. The purpose of this paper is to present a web-based tool, REGSTATTOOLS http://regstattools.net intended to provide analysis for the burden of cancer, or other group of disease registry data. Three software applications are included in REGSTATTOOLS: SART (analysis of disease"s rates and its time trends), RiskDiff (analysis of percent changes in the rates due to demographic factors and risk of developing or dying from a disease) and WAERS (relative survival analysis). Results: We show a real-data application through the assessment of the burden of tobacco-related cancer incidence in two Spanish regions in the period 1995-2004. Making use of SART we show that lung cancer is the most common cancer among those cancers, with rising trends in incidence among women. We compared 2000-2004 data with that of 1995-1999 to assess percent changes in the number of cases as well as relative survival using RiskDiff and WAERS, respectively. We show that the net change increase in lung cancer cases among women was mainly attributable to an increased risk of developing lung cancer, whereas in men it is attributable to the increase in population size. Among men, lung cancer relative survival was higher in 2000-2004 than in 1995-1999, whereas it was similar among women when these time periods were compared. Conclusions: Unlike other similar applications, REGSTATTOOLS does not require local software installation and it is simple to use, fast and easy to interpret. It is a set of web-based statistical tools intended for automated calculation of population indicators that any professional in health or social sciences may require.

Development and validation of RP-LC and uv spectrophotometric methods to assay bromopride in oral and injectable solutions

A reversed-phase liquid chromatographic (LC) and ultraviolet (UV) spectrophotometric methods were developed and validated for the assay of bromopride in oral and injectable solutions. The methods were validated according to ICH guideline. Both methods were linear in the range between 5-25 μg mL-1 (y = 41837x - 5103.4, r = 0.9996 and y = 0.0284x - 0.0351, r = 1, respectively). The statistical analysis showed no significant difference between the results obtained by the two methods. The proposed methods were found to be simple, rapid, precise, accurate, and sensitive. The LC and UV methods can be used in the routine quantitative analysis of bromopride in oral and injectable solutions.

Methods for construction and analysis of computational models in systems biology : applications to the modelling of the heat shock response and the self-assembly of intermediate filaments

Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis.

Statistical Inference for Computable General Equilibrium Models with Application to a Model of the Moroccan Economy

We study the problem of measuring the uncertainty of CGE (or RBC)-type model simulations associated with parameter uncertainty. We describe two approaches for building confidence sets on model endogenous variables. The first one uses a standard Wald-type statistic. The second approach assumes that a confidence set (sampling or Bayesian) is available for the free parameters, from which confidence sets are derived by a projection technique. The latter has two advantages: first, confidence set validity is not affected by model nonlinearities; second, we can easily build simultaneous confidence intervals for an unlimited number of variables. We study conditions under which these confidence sets take the form of intervals and show they can be implemented using standard methods for solving CGE models. We present an application to a CGE model of the Moroccan economy to study the effects of policy-induced increases of transfers from Moroccan expatriates.

Automatic Detection and Classification of Glioma Tumors using Statistical Features

The characterization and grading of glioma tumors, via image derived features, for diagnosis, prognosis, and treatment response has been an active research area in medical image computing. This paper presents a novel method for automatic detection and classification of glioma from conventional T2 weighted MR images. Automatic detection of the tumor was established using newly developed method called Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA).Statistical Features were extracted from the detected tumor texture using first order statistics and gray level co-occurrence matrix (GLCM) based second order statistical methods. Statistical significance of the features was determined by t-test and its corresponding p-value. A decision system was developed for the grade detection of glioma using these selected features and its p-value. The detection performance of the decision system was validated using the receiver operating characteristic (ROC) curve. The diagnosis and grading of glioma using this non-invasive method can contribute promising results in medical image computing

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.

Linking Canadian Harvested Juvenile American Black Ducks to Their Natal Areas Using Stable Isotope (δD, δ13C, and δ15N) Methods

Understanding source-sink dynamics of game birds is essential to harvest and habitat management but acquiring this information is often logistically and financially challenging using traditional methods of population surveys and banding studies. This is especially true for species such as the American Black Duck (Anas rubripes), which have low breeding densities and extensive breeding ranges that necessitate extensive surveys and banding programs across eastern North America. Despite this effort, the contribution of birds fledged from various landscapes and habitat types within specific breeding ranges to regional harvest is largely unknown but remains an important consideration in adaptive harvest management and targeted habitat conservation strategies. We investigated if stable isotope (δD, δ13C, δ15N) could augment our present understanding of connectivity between breeding and harvest areas and so provide information relevant to the two main management strategies for black ducks, harvest and habitat management. We obtained specimens from 200 hatch-year Black Duck wings submitted to the Canadian Wildlife Service Species Composition Survey. Samples were obtained from birds harvested in Western, Central, and Eastern breeding/harvest subregions to provide a sample representative of the range and harvest rate of birds harvested in Canada. We sampled only hatch-year birds to provide an unambiguous and direct link between production and harvest areas. Marine origins were assigned to 12%, 7%, and 5% of birds harvested in the Eastern, Central, and Western subregions, respectively. In contrast, 32%, 9%, and 5% of birds were assigned, respectively, to agricultural origins. All remaining birds were assigned to nonagricultural origins. We portrayed probability of origin using a combination of Bayesian statistical and GIS methods. Placement of most eastern birds was western Nova Scotia, eastern New Brunswick, Prince Edward Island, and southern Newfoundland. Agricultural birds from the Central region were consistent with the Saguenay region of Québec and the eastern claybelt with nonagricultural birds originating in the boreal. Western nonagricultural birds were associated with broad boreal origins from southern James Bay to Lake of the Woods and east to Cochrane, Ontario. Our work shows that the geographic origins, landscape, and habitat associations of hatch-year Black Ducks can be inferred using this technique and we recommend that a broad-scale isotopic study using a large sample of Canadian and US harvested birds be implemented to provide a continental perspective of source-sink population dynamics.