Étude sur le choix du seuil de troncature en analyse des séries de durées partielles : application au Canada

L'estimation des débits de crues est d'une importance majeure pour la conception des ouvrages d'art et la gestion des ressources hydriques. La mauvaise évaluation de ces débits entraîne un surdimensionnement ou sous dimensionnement des ouvrages hydrauliques, induisant ainsi un investissement excessif ou un risque démesuré d'inondations. Un modèle de données chronologiques de durée partielle est retenu pour l'étude des crues. Ce modèle nécessite d'abord l'estimation du seuil de troncature qui définit la série chronologique intermittente à analyser. Ce paramètre joue un rôle majeur dans la solution du problème malgré le peu d'importance que lui reconnaît la littérature. Le but de la présente étude est d'élaborer une méthode graphique comme guide dans le choix du seuil. Par la suite, cette méthode est appliquée à 238 stations hydrométriques au Canada. Une fois le seuil obtenu pour ces stations hydrométriques, une régionalisation utilisant l'analyse de régression a été réalisée. Ces équations régionales peuvent servir à estimer le seuil d'une nouvelle série hydrologique sans avoir à passer par la méthode graphique.Accurate forecasting of flood flows is required for the efficient design and construction of hydraulic structures in rivers as well as for the effective management of water resources. Underestimation of flood flows can result in tragic consequences while overdesigned structures are expensive.One method for estimating flood flows is the partial duration series analysis. In this approach a truncation level defining the intermittent time series is chosen. All flows above this level (exceedances) are analyzed by assuming the time of occurrence of these floods to represent a Poisson distribution. In addition, exceedances are considered to be independent random variables identically distributed over a one-year time interval. The selection of the truncation level is somewhat problematic and not very well defined in the literature. This study presents a truncation level estimation technique based on a series of regional regression equations for 9 distinct regions in Canada, and documents their graphical derivation.According to previous research, the truncation level can be obtained in two ways. First, it is selected in accordance with physical criteria such as the overflowing of a river, the critical flow for flooding of a crop, etc. The second method of truncation level selection is primarily mathematical such as satisfying the analytical fit or the assumptions of the model. In the present study, the truncation level was selected based on the mathematical approach using a graphical technique and using the Chi-square test. The graphical truncation level selection technique is based on the equality of the mean and variance of the Poisson distribution. Given this property of the Poisson distribution, one can study the mean-to-variance ratio as a function of truncation level.Truncation levels were selected graphically from 238 gauging stations across Canada. The Chi-square at a level of significance of 5 % was used for their validation. It was observed, upon examination of the mean-to-variance ratio, that selection of the truncation level was easier in the eastern and western regions of Canada where the ratio varied very little around unity. In the prairies and northern regions, a small variation in the truncation level led to a large variation in the ratio, making the selection of a level more difficult.Following the selection of a truncation level for each hydrometric station, homogeneous regions were selected based on previous countrywide hydrological studies. The regression analysis was then carried out to explain this truncation level using several variables (including bath physiographic variables and streamflow characteristics). Physiographic variables included area of drainage basin (km2); area of lakes and swamps (km2) ; area of forests (km2) ; mean elevation (m) ; slope of drainage basin (%) ; slope of principal watercourse (m/km, %) ; length of principal water course (km) ; area controlled by lakes and swamps (km2) ; and drainage density (km/km2). The Streamflow characteristics included the mean annual flow and mean annual flood. The mean annual flood was included because previous research has shown a strong correlation between the truncation level and the two-year flood estimated by a log-Pearson type III distribution function. For ease of application, the mean annual flood was used as a low return flood estimate as it represents the two-year flood calculated by a normal distribution function. Low return floods of any given distribution function are demonstrated to be similar in magnitude.Multiple regression was carried out using original data and logarithmically transformed data. Equations were derived by selecting one variable, two variables, and so on until all explanatory variables were accounted for in a single equation. Among the selected parameters, the mean annual flood was the best parameter to explain the truncation level for all of the regions across Canada. The coefficient of determination, R2, of the equations calculated using mean annual flood varied between 0.847 and 0.987 from original data, and varied between 0.824 and 0.988 for logarithmically transformed data. In practice, the regional equation can eliminate the graphical estimation technique and a first truncation level can be obtained. This truncation level can be used in the partial duration series analysis with the different tests involved. If this first estimated level does not meet all the statistical tests, a second usually higher level is selected. It is important to note that when the selected level meets the statistical test requirements, the estimation of QT should be relatively insensitive to levels near the selected truncation level

Évaluation du débit réservé par méthodes hydrologiques et hydrobiologiques

Plusieurs méthodes existent pour calculer le débit réservé d'un cours d'eau. Dans la présente étude deux approches sont analysées, soit les approches par méthodes hydrologiques et hydrobiologiques. Cinq méthodes hydrologiques d'évaluation du débit réservé ont été appliquées au ruisseau Catamaran au Nouveau-Brunswick (Canada), ainsi qu'une méthode hydrobiologique. Parmi les méthodes hydrologiques, on retrouve la méthode de Tennant, celle de 25% du débit moyen annuel (DMA), la méthode du débit médian (Q50) mensuel, 90% du débit classé (Q90) et la méthode basée sur l'analyse statistique de fréquence des débits faibles (7Q10). La méthode hydrobiologique utilisée dans la présente étude fut l'application du modèle PHABSIM pour le saumon Atlantique juvénile. Ce modèle est calibré en utilisant les données de vitesse d'écoulement (V), profondeur d'eau (D) et grosseur du substrat (S) pour trois différents débits. L'application des méthodes hydrologiques a démontré que certaines méthodes telle que la méthode Tennant, 25% DMA et la méthode du débit médian, donnent des résultats similaires surtout en période d'étiage. D'autre part, deux méthodes en particulier, soit la méthode de 90% du débit classé et celle basée sur une analyse statistique des débits faibles prédisent un débit réservé très faible en période d'étiage.Une modélisation de l'habitat physique du ruisseau Catamaran démontre que l'habitat disponible maximal se trouve généralement aux environs du débit moyen. De plus, il a été observé qu'en appliquant les modèles hydrologiques, l'habitat disponible était réduit par rapport à l'habitat maximum prédit par PHABSIM. En effet, l'habitat résultant de l'application de Tennant (30% DMA) et du 25% DMA représente environ 70% de l'habitat disponible maximum. Le débit calculé par la méthode du débit médian correspond à un habitat qui n'est que de 50% de l'habitat disponible maximum, tandis que les méthodes basées sur 90% du débit classé et l'analyse statistique des débits faibles ne représentent plus que des habitats de l'ordre de 20% à 40% de l'habitat disponible maximum. L'application de ces deux dernières méthodes laisse beaucoup de doute sur le niveau de protection des habitats aquatiques qu'elles procurent et il a été jugé utile de ne pas les recommander pour l'évaluation du débit réservé dans la région d'étude. Les autres méthodes (Tennant, 25% DMA et Q50) peuvent être utilisées. Cependant, l'application de la méthode du débit médian, qui peut donner des résultats proches de 50% de l'habitat disponible maximum, doit être appliquée avec précaution.Many techniques exist to calculate instream flow requirements. This study considers hydrologically-based techniques and hydrobiological or habitat preference methods. The hydrologically-based techniques use only historical streamflow data, and require little or no field work. Conversely, the habitat preference methods require knowledge of the specific hydraulic conditions of the studied water course and the habitat preferences of the relevant fish species.Five hydrologically-based methods and one habitat preference method were applied to Catamaran Brook, a small drainage basin in New Brunswick, Canada. The hydrologically-based techniques included the Tennant Method, the 25% Mean Annual Flow (MAF), the median monthly flow (Q50), the 90% flow duration method (Q90) and a low-flow frequency method (7Q10). The habitat preference method studied was the PHABSIM model applied for Atlantic salmon.The PHABSIM model was calibrated using the hydraulic characteristics of water depth (D), velocity (V) and substrate (S) for three flows. It was then used to calculate the same physical habitat parameters (D,V,S) for other discharges. The hydraulic results were used with habitat preference (suitability curves) to calculate the potential habitat or weighted usable area (WUA).The application of hydrologically-based in-stream flow techniques showed that methods such as Tennant, 25% MAF and the median monthly flow method provided similar results, especially during low flow periods. The in-stream flow requirement calculated by Tennant Method (30% MAF) was 0.20 m3·s-1, and the 25% MAF represented a value of 0.16 m3·s-1. The application of the Q50 approach yielded results of 0.13 m3·s-1 for the month of August with higher values for other months. In contrast, the 90% flow duration and the low-flow frequency methods established very low discharge for in-stream flow requirements during low-flow periods. The lowest Q90 observed was in September at 0.050 m3·s-1 whereas the months of August, July, October, February and March all showed results slightly higher than September but still lower than 0.10 m3·s-1. The method that calculated the lowest in-stream flow value was the 7Q10 (low-flow frequency) Method with a discharge of only 0.037 m3·s-1. These results (Q90 and 7Q10) represent significantly lower in-stream flow values compared to the Tennant, 25% MAF and the Q50 methods.The application of a habitat model (PHABSIM) at Catamaran Brook showed that the maximum available habitat, expressed as weighted usable area (WUA), was observed at a discharge close to the mean annual flow. Results also showed more habitat for salmon parr than for fry at maximum available habitat (optimal habitat), and this optimal habitat was at a higher flow for parr than for fry. The results from hydrologically-based methods were compared to the maximum value derived from the PHABSIM method. This comparative study showed that habitat was reduced by 30% to 80% of the maximum WUA calculated by PHABSIM depending upon which hydrologically-based in-stream flow technique was applied. Habitat (WUA) resulting from the Tennant and the 25% MAF methods derived flows represents approximately 70% of the maximum available habitat. Results from the application of the median monthly flow method (Q50) showed in-stream flow providing over 50% of maximum available habitat. The 90% flow duration method and low-flow frequency method (7Q10) showed habitat values in the range of 20% to 40% of maximum. The application of these latter two methods clearly limits the available habitat for the protection of aquatic resources and they were therefore not recommended for use in in-stream flow studies in this region. Instead, methods such as Tennant and 25% MAF should be used. The Q50 method may be used with caution as its use results in habitat availability slightly over 50% of maximum WUA

Modélisation stochastique de la température de l'eau en rivière

Cette étude présente l'application d'un modèle stochastique de prédiction de la température de l'eau en rivière. L'analyse porte sur les variations imputables aux conditions naturelles et sur une évaluation des performances du modèle une fois appliqué au ruisseau Catamaran au Nouveau-Brunswick (Canada). Ce modèle stochastique est développé selon l'approche de Box et Jenkins (1976) basée sur les séries temporelles des températures de l'eau et de l'air. Le modèle a été calibré avec des données de 1990. L'évaluation de performance comprend une analyse des séries résiduelles et le calcul des erreurs quadratiques moyennes. Les résultats montrent que l'erreur quadratique mensuelle varie de 0,42 °C en juillet 1990 (année de calibration) jusqu'à 2,96 °C en septembre 1992. Finalement, une discussion est menée pour souligner les avantages et les inconvénients relatifs à cette approche.Water temperature is a very important parameter not only in water quality studies but also in biological studies. For instance, salmonids can be adversely affected by natural high stream water temperatures or by those resulting from anthropogenic sources such as deforestation. To predict stream water temperatures, two different approaches have been used; the deterministic and stochastic approaches. The deterministic approach consists of a physical model based on the energy budget (solar radiation, convection, etc.) and the physical characteristics of the stream (water depth, stream cover, etc.). The stochastic modelling approach consists of studying the structure (autocorrelation) of the stream water temperature time series and its dependence on air temperatures (cross-correlation).The purpose of this study is to develop and test the performanoe of a stream water temperature model using a stochastic approach to predict water temperatures in rivers under natural conditions. The performance of such an approach was tested using data from Catamaran Brook, a small stream in New Brunswick (Canada). It differs from previous studies in that most others were on larger river systems.This stochastic model incorporates the Box and Jenkins method (1976) which relates the time series data to both water and air temperature residuals. To calculate the residuals of both air and water temperatures, a seasonal component was first estimated using Fourier series analysis. This seasonal component better represents the long-term trend in air and water temperatures for the studied period or season (i.e. increasing water temperatures at first, then reaching a maximum during the early part of August and decreasing again later in the season). The Fourier series with one harmonic was chosen for the analysis as it has been shown in previous studies that the first harmonic represents most of the variation within the stream water temperature variable. The model was calibrated using the Box and Jenkins method and Catamaran Brook data from 1990. This analysis consist of determining a transfer function relating present water temperature residuals to past water and air temperature residuals including present air temperature residuals and a random component. The random component (also called « noise series ») of the model is a normally distributed variable with a standard deviation calculated using the calibration period. After the calibration period, subsequent years or post-calibration years were analyzed to predicted stream water temperatures with the model using air temperature data only.A study of residuals between predicted and measured stream water temperatures showed very good results during the calibration year (1990) with a calculated root-mean square error of 0.75°C. The predicted temperatures during post calibration years (i.e. 1991 and 1992) were good and the root-mean-square errors were similar to previous studies (e.g. Marceau et al. 1986) with values of 1.45°C and 2.10°C respectively. The measured stream water temperatures during the post-calibration years were only used to estimate the relative performance of the model as opposed to a forecasting model which utilizes actual measured temperatures.At Catamaran Brook is has been observed that natural variation in air temperatures can have an influence on the performanoe of the model. When air temperatures were recorded higher or lower than the long term values (normal temperatures) calculated by the Fourier series analysis, the predicted water temperatures was not as good. For instance it was observed that during September of 1992, during which time the air temperature was higher that normal, the performance of the model was not as good with a root me an squared error of 2.96°C. However, during July 1992, below normal air temperatures were also recorded and a very good prediction of stream water temperatures in Catamaran Brook was achieved with a root me an square error of 0.98°C. In general, satisfactory prediction of stream water temperatures was achieved using the Box and Jenkins stochastic modelling approach

Évaluation de l'applicabilité d'une méthode statistique aux variations saisonnières des relations concentration-débit sur un petit cours d'eau

Les paramètres chimiques jouent un rôle important dans l'équilibre des écosystèmes aquatiques. De nombreuses études ont déjà démontré que les caractéristiques chimiques d'un cours d'eau peuvent changer avec les saisons. Cette étude a pour but de revoir les relations débit- concentration sur un petit cours d'eau, dans le contexte des variations entre deux périodes climatiques. Pour ce faire, une analyse de régression entre le débit et six paramètres de qualité de d'eau (sodium, magnésium, conductivité, pH, azote total et le carbone organique dissous) provenant d'un petit bassin versant forestier (ruisseau Catamaran, N.-B., Canada) a été réalisée afin de déterminer la différence entre la saison sans glace et la saison avec glace. Des échantillons mensuels d'eau ont été récoltés sur le ruisseau Catamaran depuis 1990. Les analyses chimiques faites sur ses échantillons ont permis de déterminer les concentrations des paramètre étudiés. La plupart des variables de qualité ont démontré une relation significative avec le débit, sauf l'azote total. Les coefficients de détermination variaient entre 0.752 et 0.898, exception faite du carbone organique dissous dont le r2 était de 0.294. La conductivité était le paramètre dont le débit expliquait le plus la variance. Une étude des rapports des sommes des carrés des résidus a permis de déterminer que seul le pH requiert un modèle différent pour la période sans glace et la saison avec glace. Les variations saisonnières de la relation débit-pH revêt une importance significative pour les ruisseaux comme celui de Catamaran, qui incluent de nombreux habitats pour le saumon de l'Atlantique. Les résultats des analyses de régressions indiquent que lorsque la géochimie est plus complexe, comme c'est le cas pour le pH, il faut diviser les séries temporelles en sous-composantes saisonnières avant de tenter d'établir une relation débit-concentration.The chemical composition of water is of great importance to ecosystem functioning and in habitat management. Many studies have already shown that the chemical characteristics of a stream change with seasons. These variations have a strong impact on the ecosystem, especially on fish populations. The objective of this study is to quantify the relationship between the logarithm of discharge and six water quality parameters (sodium, magnesium, conductivity, pH, dissolved organic carbon and total nitrogen) for a small forested catchment (Catamaran Brook, N.B., Canada) and to verify the importance of seasonality. Monthly water samples have been gathered at Catamaran Brook since 1990. Detailed water chemistry performed on these samples provided a data base for this project. Various linear regression models were tested to verify if regressions were required for the winter season. The criterion used was the ratio of the squared sum of residuals for each data set, which follows a Fisher distribution. Of the six water quality parameters, all except total nitrogen showed a significant relationship with discharge. On an annual basis, the coefficient of determination (r2) varied between 0.752 and 0.898, except for dissolved organic carbon which showed a r2 of 0.294. Of the studied parameters, conductivity was the parameter for which discharge explained the most variance. Ratios of the squared sum of residuals were analyzed to verify the need for different regression models for the ice-covered and ice-free seasons. Only streamwater pH required 2 different models. This is of specific importance and interest because of an important salmon population in Catamaran Brook. Other researchers have shown that salmonids can be negatively impacted by pH depressions during snowmelt events.These results show that most dissolved ions which follow simple geochemical reactions can be modelled year-round with only one linear regression. When the geochemistry is more complex, such as in the case of pH, linear regression models can sometimes be used, provided that the annual time-series is divided into seasons with relatively homogenous hydrological and geochemical functions

Estimation de la température de l'eau de rivière en utilisant les réseaux de neurones et la régression linéaire multiple

La température de l'eau en rivière est un paramètre ayant une importance majeure pour la vie aquatique. Les séries temporelles décrivant ce paramètre thermique existent, mais elles sont moins nombreuses et souvent courtes, ou comptent parfois des valeurs manquantes. Cette étude présente la modélisation de la température de l'eau en utilisant des réseaux de neurones et la régression linéaire multiple pour relier la température de l'eau à celle de l'air et le débit du ruisseau Catamaran, situé au Nouveau-Brunswick, Canada. Une recherche multidisciplinaire à long terme se déroule présentement sur ce site. Les données utilisées sont de 1991 à 2000 et comprennent la température de l'air de la journée en cours, de la veille et de l'avant-veille, le débit ainsi que le temps transformé en série trigonométrique. Les données de 1991 à 1995 ont été utilisées pour l'entraînement ou la calibration du modèle tandis que les données de 1996 à 2000 ont été utilisées pour la validation du modèle. Les coefficients de détermination obtenus pour l'entraînement sont de 94,2 % pour les réseaux de neurones et de 92,6 % pour la régression linéaire multiple, ce qui donne un écart-type des erreurs de 1,01 C pour les réseaux de neurones et de 1,05 C pour la régression linéaire multiple. Pour la validation, les coefficients de détermination sont de 92,2 % pour les réseaux de neurones et de 91,6 % pour la régression linéaire multiple, ce qui se traduit en un écart-type des erreurs de 1,10 C pour les réseaux de neurones et de 1,25 C pour la régression linéaire multiple. Durant la période d'étude (1991-2000), le biais a été calculé à +0,11 C pour le modèle de réseaux de neurones et à -0,26 °C pour le modèle de régression. Ces résultats permettent de conclure qu'il est possible de prévoir la température de l'eau de petits cours d'eau en utilisant la température de l'air et le débit, aussi bien avec les réseaux de neurones qu'avec la régression linéaire multiple. Les réseaux de neurones semblent donner un ajustement aux données légèrement meilleur que celui offert par la régression linéaire multiple, toutefois ces deux approches de modélisation démontrent une bonne performance pour la prédiction de la température de l'eau en rivière.Water temperature is a parameter of great importance for water resources. For instance, modifications of the thermal regime of a river can have a significant impact on fish habitat. Therefore, understanding and predicting water temperatures is essential in order to help prevent or forecast high temperature problems. In order to predict water temperatures, data series are necessary. Many data series exist for air temperatures, but water temperature series are relatively scarce and those available are often short or have missing values. This study presents the modelling of water temperature using neural networks and multiple linear regression to relate water temperature to air temperature and discharge in Catamaran Brook, New Brunswick, Canada.Catamaran Brook is a small stream (51 km2) where long-term multidisciplinary habitat research is being carried out. Many variables can impact water temperatures in a river, such as air temperature, solar radiation, wind speed, discharge, groundwater flow, etc. For this study, only air temperature and discharge were used. These were judged to be the most often available parameters for modelling temperatures in rivers, and to have the greatest impact on water temperature. More precisely, input variables included current air temperature (°C), air temperature of the previous day (°C), air temperature two days earlier (°C), discharge (m3 /s) and a trigonometric function of time (days). Data used for the analysis were from 1991 to 2000. Data from 1991 to 1995 were used to calibrate the model while data from 1996 to 2000 were used for validation purposes. Observed and predicted water temperatures for each model were presented for the calibration data and the validation data. The coefficient of determination, R2, was used to compare the efficiency of both models as well as the residual standard deviation and the bias. This is equivalent to basing the comparison on the standard deviation (or variance) of the residuals. Coefficients of determination for calibration were 94.2% for the neural networks and 92.6% for the multiple linear regression, which correspond to a residual standard deviation of 1.01°C for the neural networks and of 1.05°C for the multiple linear regression. For validation, coefficients of determination were 92.2% for the neural networks and 91.6% for the multiple linear regression, which correspond to a residual standard deviation of 1.10°C for the neural networks, and of 1.25°C for the multiple regression. The overall bias during the study period (1991-2000) was calculated at +0.11°C for the neural network model and at -0.26°C for the regression model. Results indicated that it was possible to predict water temperature for a small stream using air temperature, flow and time, as input variables, with neural networks and multiple linear regression. The residual series obtained by both models were very similar. Of the two models, neural networks gave slightly better results in terms of fit, but the small difference in results lets us believe that both approaches are equally good in predicting stream water temperatures

Performance/outcomes data and physician process challenges for practical big data efforts in radiation oncology

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146290/1/mp13136.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146290/2/mp13136_am.pd

A data-driven synthesis of research evidence for domains of hearing loss, as reported by adults with hearing loss and their communication partners

A number of assessment tools exist to evaluate the impact of hearing loss, with little consensus among researchers as to either preference or psychometric adequacy. The item content of hearing loss assessment tools should seek to capture the impact of hearing loss on everyday life, but to date no one has synthesized the range of hearing loss complaints from the perspectives of the person with hearing loss and their communication partner. The current review aims to synthesize the evidence on person with hearing loss- and communication partner-reported complaints of hearing loss. Searches were conducted in Cos Conference Papers Index, the Cumulative Index to Nursing and Allied Health Literature, Excerpta Medica Database, PubMed, Web of Science, and Google Scholar to identify publications from May 1982 to August 2015. A manual search of four relevant journals updated the search to May 2017. Of the 9,516 titles identified, 78 records (comprising 20,306 participants) met inclusion criteria and were taken through to data collection. Data were analyzed using meta-ethnography to form domains representing the person with hearing loss- and communication partner-reported complaints of hearing loss as reported in research. Domains and subdomains mutual to both perspectives are related to ‘‘Auditory’’ (listening, communicating, and speaking), ‘‘Social’’ (relationships, isolation, social life, occupational, and interventions), and ‘‘Self’’ (effort and fatigue, emotions, identity, and stigma). Our framework contributes fundamental new knowledge and a unique resource that enables researchers and clinicians to consider the broader impacts of hearing loss. Our findings can also be used to guide questions during diagnostic assessment and to evaluate existing measures of hearing loss

Increasing Potential Risk of a Global Aquatic Invader in Europe in Contrast to Other Continents under Future Climate Change

BACKGROUND: Anthropogenically-induced climate change can alter the current climatic habitat of non-native species and can have complex effects on potentially invasive species. Predictions of the potential distributions of invasive species under climate change will provide critical information for future conservation and management strategies. Aquatic ecosystems are particularly vulnerable to invasive species and climate change, but the effect of climate change on invasive species distributions has been rather neglected, especially for notorious global invaders. METHODOLOGY/PRINCIPAL FINDINGS: We used ecological niche models (ENMs) to assess the risks and opportunities that climate change presents for the red swamp crayfish (Procambarus clarkii), which is a worldwide aquatic invasive species. Linking the factors of climate, topography, habitat and human influence, we developed predictive models incorporating both native and non-native distribution data of the crayfish to identify present areas of potential distribution and project the effects of future climate change based on a consensus-forecast approach combining the CCCMA and HADCM3 climate models under two emission scenarios (A2a and B2a) by 2050. The minimum temperature from the coldest month, the human footprint and precipitation of the driest quarter contributed most to the species distribution models. Under both the A2a and B2a scenarios, P. clarkii shifted to higher latitudes in continents of both the northern and southern hemispheres. However, the effect of climate change varied considerately among continents with an expanding potential in Europe and contracting changes in others. CONCLUSIONS/SIGNIFICANCE: Our findings are the first to predict the impact of climate change on the future distribution of a globally invasive aquatic species. We confirmed the complexities of the likely effects of climate change on the potential distribution of globally invasive species, and it is extremely important to develop wide-ranging and effective control measures according to predicted geographical shifts and changes

Monitoring activities of teenagers to comprehend their habits: study protocol for a mixed-methods cohort study

Abstract: Background: Efforts to increase physical activity in youth need to consider which activities are most likely to be sustained over time in order to promote lifelong participation in physical activity. The Monitoring Activities of Teenagers to Comprehend their Habits (MATCH) study is a prospective cohort study that uses quantitative and qualitative methods to develop new knowledge on the sustainability of specific physical activities. Methods/design: Eight hundred and forty-three grade 5 and 6 students recruited from 17 elementary schools in New Brunswick, Canada, are followed-up three times per year. At each survey cycle, participants complete self-report questionnaires in their classroom under the supervision of trained data collectors. A sub-sample of 24 physically active students is interviewed annually using a semi-structured interview protocol. Parents (or guardians) complete telephone administered questionnaires every two years, and a health and wellness school audit is completed for each school. Discussion: MATCH will provide a description of the patterns of participation in specific physical activities in youth, and enable identification of the determinants of maintenance, decline, and uptake of participation in each activity. These data will inform the development of interventions that take into account which activities are the most likely to be maintained and why activities are maintained or dropped