Individual and environmental risk factors in hand eczema have been investigated in a prospective cohort study of 2452 newly employed hospital workers with a follow-up time of 20 months. Current hand eczema was analyzed in 142 wet hospital workers from this cohort with respect to the etiologic importance of irritants, allergens and contact urticants. The density of the microflora and the effect on the microflora of topical treatment with a potent corticosteroid were studied in 20 patients with hand eczema. ’Wet’ hospital work was found to increase the odds of developing hand eczema only twice compared to 'dry' office work. Nursing children under four years old and the lack of a dish-washing machine significantly increased the risk of contracting hand eczema. Unfavourable combinations of these domestic factors increased the risk as much as wet work. A history of atopic dermatitis approximately tripled the odds both in wet as well as in dry work. Histories of earlier hand eczema (HHE), metal dermatitis (HMD) and of atopy were analyzed as risk factors for hand eczema in 1857 women in wet work. HHE increased the odds by a factor of 12.9 and created a subdivision of the population into high risk individuals and normal risk individuals. HHE was found in half of the subjects with atopic dermatitis, in one quarter of the subjects with atopic mucosal symptoms and in one fifth of the non-atopics. A HMD increased the odds by a factor of 1.8. This increase was seen as a high risk level in subjects with HHE and as a normal risk level in subjects with no HHE. A history of atopic disease as a complement to information about HHE and HMD increased the odds by another 1.3 times. The predicted probability of developing hand eczema ranged from 91 % in subjects with a combination of HHE, HMD and atopy to 24% in subjects with none of these risk factors. Subjects with AD were found to suffer a more severe form of hand eczema with significantly higher figures for medical consultation, sick- leave, termination due to hand eczema, early debut, permanent symtoms and vesicular lesions. Amongst the patients investigated for current hand eczema high risk individuals were overrepresented. It was claimed in 92.3% of the cases that trivial irritant factors had elicited the current episodes of hand eczema. In 35% of the cases the exposure to the irritant took place largely at home. Although contact sensitivity and contact urticaria were fairly common, they mostly seemed to be of minor importance in the etiology of the current hand eczema. Staphylococcus aureus colonized eczematous lesions of the hands in 18/20 patients. The density exceeded 105 colony forming units/cm2 in 15/20 patients. Only three of these patients showed signs of clinical infection. Successful topical treatment with a potent corticosteroid significantly reduced the colonization of S. aureus. / <p>Härtill 4 uppsatser</p> / digitalisering@umu

Orientador: Reinaldo José da Silva / Resumo: Nos últimos anos, os parasitas foram reconhecidos como importantes componentes dabiodiversidade global, dado os importantes papéis desempenhados por esses organismosem ecossistemas naturais. Embora o conhecimento sobre a diversidade de parasitas tenhaaumentado nas últimas décadas, o número de espécies de parasitas de peixes no Brasil érelativamente baixo quando comparado com a biodiversidade das espécies hospedeiras.Desta forma, o presente trabalho teve como objetivo realizar um levantamento dabiodiversidade dos parasitas de peixes procedentes de quatro locais em uma área sob ainfluência de Pequenas Centrais Hidrelétricas (PCHs) no rio Sapucaí-Mirim, Estado de SãoPaulo, Brasil, bem como avaliar a estrutura das comunidades de metazoários parasitas depeixes Characiformes e de quatro espécies do gênero Leporinus. Durante o período demarço de 2012 a julho de 2013, foram coletados 462 espécimes pertencentes a 16 espéciesde peixes das ordens Characiformes, Siluriformes, Gymnotiformes e Perciformes.Observou-se que 86,58% dos espécimes estavam parasitados por pelo menos um taxon demetazoário parasita. Os parasitas encontrados pertenciam a oito diferentes grupos(Myxozoa, Monogenea, Digenea, Cestoda, Nematoda, Acantocephala, Arthopoda eAnnelida), sendo coletado um total de 6.830 parasitas. Noventa e sete taxa de parasitasforam encontrados, sendo que a classe Monogenea foi o grupo que apresentou o maiornúmero de espécies, seguido do filo Nematoda e da s... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Recently, parasites have been recognized as important components of global biodiversitybecause the important roles played by these organisms in natural ecosystems. Althoughknowledge about the diversity of parasites has increased in recent decades, the number ofparasite species of fishes in Brazil is relatively low compared to the biodiversity of hostspecies. Thus, this study aimed to survey the biodiversity of fish parasites from foursampling sites in an area under the influence of Small Hydroelectric Power Plants in theSapucaí-Mirim River, São Paulo State, Brazil, as well as to evaluate the structure ofmetazoan parasite communities of Characiformes and four species of Leporinus sp. FromMarch 2012 to July 2013, 462 fish specimens of 16 species of Characiformes,Siluriformes, Perciformes, and Gymnotiformes were collected. It was observed that86.58% of fish specimens were parasitized by at least one metazoan parasite taxon. Theparasites found belonged to eight different groups (Myxozoa, Monogenea, Digenea,Cestoda, Nematoda, Acantocephala, Arthopoda and Annelida) and a total of 6,830parasites were collected and analyzed. Ninety-seven parasite taxa were found, andMonogenea was the group that had the highest number of species, followed by Nematodaand Digenea. The parasite communities of Characiformes showed mainly differencesamong the host species, although belonging to the same order or family. The sampling site,condition factor and the host body ... (Complete abstract click electronic access below) / Doutor

Orientador: Reinaldo José da Silva / Resumo: Peixes da família Loricariidae (Siluriformes) apresentam grande plasticidade fenotípicaintraespecífica durante toda sua ontogenia. O conhecimento limitado sobre os aspectosbiológicos, padrões biogeográficos e elevada variabilidade morfológica destes peixesdificultam estudos sobre a biodiversidade acerca deste grupo, incluindo estudos sobre afauna parasitária. Assim, o objetivo deste estudo foi realizar levantamento dabiodiversidade de parasitas de peixes da família Loricariidae em áreas sob a influência daconstrução de Pequenas Centrais Hidrelétricas (PCHs) no rio Sapucaí-Mirim, Estado deSão Paulo, Brasil. Ademais, avaliar a estrutura das comunidades parasitárias doshospedeiros analisados (ao nível de infracomunidade e comunidade componente) epossíveis mudanças na abundância das infracomunidades baseadas em variáveisexplanatórias (espaciais, temporais e fatores intrínsecos ao hospedeiro). Para tanto, duranteos anos de 2012 e 2013 foram realizadas duas amostragens anuais (período seco/chuvoso),em oito áreas amostrais situadas nos reservatórios de três PCHs: Palmeiras, Anhanguera eRetiro. Foram necropsiados 334 loricarídeos pertencentes a 10 espécies: Loricaria prolixa,Hypostomus margaritifer, Hypostomus heraldoi, Hypostomus strigaticeps, Hypostomusregani, Hypostomus ancistroides, Hypostomus cf. margaritifer, Hypostomus topavae,Hypostomus aff. topavae, além de uma espécie não identificada pertencente ao gêneroHypostomus. Foram encontrados 29 ta... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Loricariid fishes (Siluriformes) presents great intraspecific phenotypic plasticity throughouttheir ontogeny. The limited knowledge about the biological aspects, biogeographic patternsof distribution and high morphological variability of these fishes make the studies onbiodiversity of this group difficult, including that about parasites. Therefore, the aim of thisstudy was to survey the biodiversity of parasites of Loricariidae fishes from an area underthe influence of the construction of Small Hydro Power Plants (SHPPs) in the Sapucaí-Mirim River, São Paulo State, Brazil. Moreover, the study evaluated the structure ofparasitic communities of these hosts (at both the component community andinfracommunity levels), assessing the possible variation in infracommunity abundanceamong sites and fish species based on explanatory variables (spatial, temporal, and hosttraits). During 2012 and 2013, two annual samples (dry/rainy seasons) were carried out, ineight sampling sites situated in the reservoirs of three SHPPs: Palmeiras, Anhanguera, andRetiro. Specimens of Loricaria prolixa, Hypostomus regani, Hypostomus ancistroides,Hypostomus strigaticeps, Hypostomus heraldoi, Hypostomus margaritifer, Hypostomus cf.margaritifer; Hypostomus topavae; Hypostomus aff. topavae and Hypostomus sp., wereanalyzed, totaling 334 fishes. Twenty-nine taxa were found, totaling 15,957 parasitespecimens, and Monogena was the dominant group, which showed the greatest richness ... (Complete abstract click electronic access below) / Doutor

The necessity of modeling is vital for the purpose of reasoning and diagnosing in complex systems, since the human mind might sometimes have a limited capacity and an inability to be objective. The chain graph (CG) class is a powerful and robust tool for modeling real-world applications. It is a type of probabilistic graphical models (PGM) and has multiple interpretations. Each of these interpretations has a distinct Markov property. This thesis deals with the multivariate regression chain graph (MVR-CG) interpretation. The main goal of this thesis is to implement and evaluate the results of the MVR-PC-algorithm proposed by Sonntag and Peña in 2012. This algorithm uses a constraint based approach used in order to learn a MVR-CG from data.In this study the MRV-PC-algorithm is implemented and tested to see whether the implementation is correct. For this purpose, it is run on several different independence models that can be perfectly represented by MVR-CGs. The learned CG and the independence model of the given probability distribution are then compared to ensure that they are in the same Markov equivalence class. Additionally, for the purpose of checking how accurate the algorithm is, in learning a MVR-CG from data, a large number of samples are passed to the algorithm. The results are analyzed based on number of nodes and average number of adjacents per node. The accuracy of the algorithm is measured by the precision and recall of independencies and dependencies.In general, the higher the number of samples given to the algorithm, the more accurate the learned MVR-CGs become. In addition, when the graph is sparse, the result becomes significantly more accurate. The number of nodes can affect the results slightly. When the number of nodes increases it can lead to better results, if the average number of adjacents is fixed. On the other hand, if the number of nodes is fixed and the average number of adjacents increases, the effect is more considerable and the accuracy of the results dramatically declines. Moreover the type of the random variables can affect the results. Given the samples with discrete variables, the recall of independencies measure would be higher and the precision of independencies measure would be lower. Conversely, given the samples with continuous variables, the recall of independencies would be less but the precision of independencies would be higher.

Modeling is a powerful tool that can be used to identify important relationships between organisms and their habitat (Guisan & Zimmermann, 2000). Understanding the dynamics of how the two relate to one another is important for conserving and managing ecosystems, but the extreme complexity of those ecosystems makes it very difficult to fully diagram. Unlike many other modeling techniques, Multivariate Regression Trees (MRTs) are not limited by a prior assumptions, pre-determined relationships, transformations, or correlations. MRTs have the power to provide both explanation and prediction of ecological data by producing simple models that are easy to interpret. This study proposed to use MRTs to evaluate and model relationships between Lucania parva and the environment and habitat of Florida Bay. Counts were transformed to presence-absence and abundance groupings. Models were first run using a variety of combination of response variables and all explanatory variables. Results of these models were used to select the best combination of response and explanatory variables in an effort to create a best fit model. Models indicated that Lucania parva populations are found in the dense (cover ≥50%), shallow water (<1.8 m) grass beds that occur in the western portion of Florida Bay. A best fit model was able to explain 63.7% of the variance with predictive error of 0.43.

One of the challenges in the structural biological community is processing the wealth of protein data being produced today; therefore, the use of computational tools has been incorporated to speed up and help understand the structures of proteins, hence the functions of proteins. In this thesis, protein structure investigations were made through the use of Multivariate Analysis (MVA), and Fourier Transformed Infrared (FTIR), a form of vibrational spectroscopy. FTIR has been shown to identify the chemical bonds in a protein in solution and it is rapid and easy to use; the spectra produced from FTIR are then analysed qualitatively and quantitatively by using MVA methods, and this produces non-redundant but important information from the FTIR spectra. High resolution techniques such as X-ray crystallography and NMR are not always applicable and Fourier Transform Infrared (FTIR) spectroscopy, a widely applicable analytical technique, has great potential to assist structure analysis for a wide range of proteins. FTIR spectral shape and band positions in the Amide I (which contains the most intense absorption region), Amide II, and Amide III regions, can be analysed computationally, using multivariate regression, to extract structural information. In this thesis Partial least squares (PLS), a form of MVA, was used to correlate a matrix of FTIR spectra and their known secondary structure motifs, in order to determine their structures (in terms of "helix", "sheet", “310-helix”, “turns” and "other" contents) for a selection of 84 non-redundant proteins. Analysis of the spectral wavelength range between 1480 and 1900 cm-1 (Amide I and Amide II regions) results in high accuracies of prediction, as high as R2 = 0.96 for α-helix, 0.95 for β-sheet, 0.92 for 310-helix, 0.94 for turns and 0.90 for other; their Root Mean Square Error for Calibration (RMSEC) values are between 0.01 to 0.05, and their Root Mean Square Error for Prediction (RMSEP) values are between 0.02 to 0.12. The Amide II region also gave results comparable to that of Amide I, especially for predictions of helix content. We also used Principal Component Analysis (PCA) to classify FTIR protein spectra into their natural groupings as proteins of mainly α-helical structure, or protein of mainly β-sheet structure or proteins of some mixed variations of α-helix and β-sheet. We have also been able to differentiate between parallel and anti-parallel β-sheet. The developed methods were applied to characterize the secondary structure conformational changes of an unfolding protein as a function of pH and also to determine the limit of Quantitation (LoQ).Our structural analyses compare highly favourably to those in the literature using machine learning techniques. Our work proves that FTIR spectra in combination with multivariate regression analysis like PCA and PLS, can accurately identify and quantify protein secondary structure. The developed models in this research are especially important in the pharmaceutical industry where the therapeutic effect of drugs strongly depends on the stability of the physical or chemical structure of their proteins targets; therefore, understanding the structure of proteins is very important in the biopharmaceutical world for drugs production and formulation. There is a new class of drugs that are proteins themselves used to treat infectious and autoimmune diseases. The use of spectroscopy and multivariate regression analysis in the medical industry to identify biomarkers in diseases has also brought new challenges to the bioinformatics field. These methods may be applicable in food science and academia in general, for the investigation and elucidation of protein structure.

After a 100-year history, traditional zoning practices are being challenged as a contributing factor in a number of social, heath and economic problems facing cities in the United States. In this context, form based codes have emerged as a possible alternative way for cities to guide development. Growing out of the New Urbanist movement, form based codes frequently mix uses, allow for a greater variety of housing types and encourage development that is both denser and more compact. Despite an established literature which links land-use regulations, and zoning in particular, to fiscal outcomes, the impacts that form based codes have on public finance in the growing number of cities which have adopted them has yet to be fully investigated. The goal of this research is to examine if and how form based codes alter property tax and sales tax generation in the cities that adopt them. To examine the relationship between form based codes and public finance a series of two multivariate regression analyses were conducted using historic property and sales tax data. The first regression analysis was performed using the full list of 122 cities which have adopted form based standards from between 1984 and 2009. In an attempt to limit the diversity of sample cities and improve the ability to generalize results a second regression analysis was performed using a smaller list of 47 cities with populations between 50,000 and 200,000 thousand that had adopted form based standards between 1984 and 2009. The results of the first analysis established that a statistically significant positive relationship existed between the presence of form based standards which were implemented citywide and observed property tax revenue both in total and on a per capita basis. Similarly, a statistically significant positive relationship between the presence of form based standards implemented at the neighborhood level and total property tax revenue was observed. No significant relationship was found between the presence of neighborhood level standards and per capita property tax revenue. Further no significant relationship was found between form based standards and sales tax revenue. In general, these findings support the theory that form based codes and the development they allow, does alter the amount of property tax a city collects, but does not support the theory that form based codes affect sales tax revenues by facilitating the development of a more conducive urban, walkable environment or for any other reason. The results of the second regression analysis using data from cities with populations between 50,000 and 200,000 showed a significant positive relationship between the presences of citywide form based standards and total property tax revenue and per capita property tax revenue. Analysis of sales tax data showed a positive relationship between total sales tax revenue and the presence of form based standards at the neighborhood level. No other significant relationship between form based standards and sales tax revenue was observed. Similar, to analysis of all cities, the results for cities with population of 50,000 to 200,000 support the theory that form based codes and the development they allow does alter the amount of property tax a city collects, and that form based codes do not affect sales tax revenues except in the case of codes adopted at the neighborhood level, where a generally positive relationship was identified at the 10% confidence interval. Following this multivariate regression analysis, a case study of Saratoga Springs, New York was completed. Located in the far reaches of the Albany Metropolitan Area, Saratoga Springs developed as a popular tourist destination in the mid 1800’s. After experiencing economic decline in line with that of its peer cities in the mid to late 20th century, Saratoga Springs has experience a boom and now boast some of the highest home values in Upstate New York. In 2003 the city was one of the first in country to adopt form based standards, which have guided a significant amount of development in the city’s historic downtown as the city re-emerged as a popular tourist destination. Since the adoption of form based standards in Saratoga Springs both property tax and sales tax receipts have doubled.

Many species are sensitive to a light in ultraviolet spectrum. Some species have surface patterns that reflect ultraviolet light. These markings have been observed in many animal taxa; butterflies (Lepidoptera) are no exception. UV-reflectance in butterflies has been primarily connected to sexual selection and in this respect it has been a subject of many studies. In my work I propose an alternative view to this phenomenon. The aim of my work is to reveal how a particular environmental factors influence the morphospace of UV- reflectant patterns and wing shape of the Gonepteryx rhamni (Pieridae). The effect of various environmental factors (latitude, longitude, altitude, mean annual temperature, mean annual precipitation, normalized difference vegetation index - NDVI or net primary productivity - NPP) on wing morphospace was tested using the methods of Geometric morphometrics. I have also studied shape variability among the males and females, specimens from different locations and differences in morphospace of several G. rhamni subspecies. The dataset used in this analysis includes 118 males and 67 females from the Palearctic ecozone. The effect of almost all environmental (except to NDVI and NPP) predictors on shape of the UV-pattern and wing margin was significant in the case of males. In the...

本研究以不動產估價技術規則第19條第7項與第20條之規定，引用相似無關迴歸模式、多變量迴歸模式與典型相關分析等計量模式，對金融機構所做的擔保品估價進行驗證、預測及控制分析。 擔保品估價中會產生兩價，即擔保品的評估市場價格與評估擔保值（價），大部分的人都認為兩價存在一個比率關係。傳統的迴歸分析估價模式係由一組價格影響因素影響一個不動產價格，上述情形是否可能由同一組價格影響因素影響兩個不動產價格？本研究實證結果顯示，在95％統計信賴水準下，有兩個不動產價格受同一組價格因素影響的結果。既然驗證存在同一組價格影響因素影響兩個不動產價格，是否有更具效率的計量估價模式呢？典型相關分析係透過兩組變項之相關關係建構計量模式，除可再度驗證同一組價格影響因素影響兩個不動產價格，並可如同因素分析或主成份分析的功能，對兩組變項各做變項縮減的工作，達到對變項去蕪存菁的效果。 / This thesis is based on Article 19 No 7 and Article 20 of the Real Estate Appraisal Regulation. Seemingly Unrelated Regression Model, Multivariate Regression Model and Econometric Model and so on econometric model are applied. In addition, collateral valuations done by financial institutions are verified, predicted and analyzed. In collateral valuations, there are two-value references: assessed market value and assessed accommodation value. Majority believe that there is a ratio between these two values. The traditional regression analysis of the valuation model is having one set of pricing factors to have impact on the real estate price. However, is it possible that one set of pricing factors will affect two real estate prices? The findings approve that, under statistical confidence level with 95%, more than two real estate prices can be influenced by one set of pricing factors. Further more, this thesis also examines if there are other econometric valuation models to be applied? The canonical correlation analysis is to build a calculation model to analyze correlation between two variables. Other than examining one set of pricing factors can influence two real estate prices, this analysis also provides a similar function of the factor analysis or principal analysis to reduce variables caused by two sets of variable.

En écologie, dans le cadre par exemple d’études des services fournis par les écosystèmes, les modélisations descriptive, explicative et prédictive ont toutes trois leur place distincte. Certaines situations bien précises requièrent soit l’un soit l’autre de ces types de modélisation ; le bon choix s’impose afin de pouvoir faire du modèle un usage conforme aux objectifs de l’étude. Dans le cadre de ce travail, nous explorons dans un premier temps le pouvoir explicatif de l’arbre de régression multivariable (ARM). Cette méthode de modélisation est basée sur un algorithme récursif de bipartition et une méthode de rééchantillonage permettant l’élagage du modèle final, qui est un arbre, afin d’obtenir le modèle produisant les meilleures prédictions. Cette analyse asymétrique à deux tableaux permet l’obtention de groupes homogènes d’objets du tableau réponse, les divisions entre les groupes correspondant à des points de coupure des variables du tableau explicatif marquant les changements les plus abrupts de la réponse. Nous démontrons qu’afin de calculer le pouvoir explicatif de l’ARM, on doit définir un coefficient de détermination ajusté dans lequel les degrés de liberté du modèle sont estimés à l’aide d’un algorithme. Cette estimation du coefficient de détermination de la population est pratiquement non biaisée. Puisque l’ARM sous-tend des prémisses de discontinuité alors que l’analyse canonique de redondance (ACR) modélise des gradients linéaires continus, la comparaison de leur pouvoir explicatif respectif permet entre autres de distinguer quel type de patron la réponse suit en fonction des variables explicatives. La comparaison du pouvoir explicatif entre l’ACR et l’ARM a été motivée par l’utilisation extensive de l’ACR afin d’étudier la diversité bêta. Toujours dans une optique explicative, nous définissons une nouvelle procédure appelée l’arbre de régression multivariable en cascade (ARMC) qui permet de construire un modèle tout en imposant un ordre hiérarchique aux hypothèses à l’étude. Cette nouvelle procédure permet d’entreprendre l’étude de l’effet hiérarchisé de deux jeux de variables explicatives, principal et subordonné, puis de calculer leur pouvoir explicatif. L’interprétation du modèle final se fait comme dans une MANOVA hiérarchique. On peut trouver dans les résultats de cette analyse des informations supplémentaires quant aux liens qui existent entre la réponse et les variables explicatives, par exemple des interactions entres les deux jeux explicatifs qui n’étaient pas mises en évidence par l’analyse ARM usuelle. D’autre part, on étudie le pouvoir prédictif des modèles linéaires généralisés en modélisant la biomasse de différentes espèces d’arbre tropicaux en fonction de certaines de leurs mesures allométriques. Plus particulièrement, nous examinons la capacité des structures d’erreur gaussienne et gamma à fournir les prédictions les plus précises. Nous montrons que pour une espèce en particulier, le pouvoir prédictif d’un modèle faisant usage de la structure d’erreur gamma est supérieur. Cette étude s’insère dans un cadre pratique et se veut un exemple pour les gestionnaires voulant estimer précisément la capture du carbone par des plantations d’arbres tropicaux. Nos conclusions pourraient faire partie intégrante d’un programme de réduction des émissions de carbone par les changements d’utilisation des terres. / In ecology, in ecosystem services studies for example, descriptive, explanatory and predictive modelling all have relevance in different situations. Precise circumstances may require one or the other type of modelling; it is important to choose the method properly to insure that the final model fits the study’s goal. In this thesis, we first explore the explanatory power of the multivariate regression tree (MRT). This modelling technique is based on a recursive bipartitionning algorithm. The tree is fully grown by successive bipartitions and then it is pruned by resampling in order to reveal the tree providing the best predictions. This asymmetric analysis of two tables produces homogeneous groups in terms of the response that are constrained by splitting levels in the values of some of the most important explanatory variables. We show that to calculate the explanatory power of an MRT, an appropriate adjusted coefficient of determination must include an estimation of the degrees of freedom of the MRT model through an algorithm. This estimation of the population coefficient of determination is practically unbiased. Since MRT is based upon discontinuity premises whereas canonical redundancy analysis (RDA) models continuous linear gradients, the comparison of their explanatory powers enables one to distinguish between those two patterns of species distributions along the explanatory variables. The extensive use of RDA for the study of beta diversity motivated the comparison between its explanatory power and that of MRT. In an explanatory perspective again, we define a new procedure called a cascade of multivariate regression trees (CMRT). This procedure provides the possibility of computing an MRT model where an order is imposed to nested explanatory hypotheses. CMRT provides a framework to study the exclusive effect of a main and a subordinate set of explanatory variables by calculating their explanatory powers. The interpretation of the final model is done as in nested MANOVA. New information may arise from this analysis about the relationship between the response and the explanatory variables, for example interaction effects between the two explanatory data sets that were not evidenced by the usual MRT model. On the other hand, we study the predictive power of generalized linear models (GLM) to predict individual tropical tree biomass as a function of allometric shape variables. Particularly, we examine the capacity of gaussian and gamma error structures to provide the most precise predictions. We show that for a particular species, gamma error structure is superior in terms of predictive power. This study is part of a practical framework; it is meant to be used as a tool for managers who need to precisely estimate the amount of carbon recaptured by tropical tree plantations. Our conclusions could be integrated within a program of carbon emission reduction by land use changes.