Variabilidade genética e correlações juvenil - adulto de baru (Dipteryx alata Vog.) no Município de Brasilândia - Mg

Pós-graduação em Ciência Florestal - FCA

Habilidades auditivas e medidas da imitância acústica em crianças de 4 a 6 anos de idade

OBJETIVO: avaliar o desempenho em habilidades auditivas e as condições de orelha média de crianças de 4 a 6 anos de idade. MÉTODO: foram aplicados os testes de detecção sonora (audiômetro pediátrico em 20dBNA), a Avaliação Simplificada do Processamento Auditivo (ASPA) e as medidas de imitância acústica (handtymp com tom de 226Hz) em 61 crianças com média de idade de 5,65 anos. Para comparar os resultados das provas de habilidades auditivas e das medidas da imitância acústica foi aplicado o teste exato de Fisher com nível de significância de p< 0,05. RESULTADOS: houve alteração em pelo menos uma das habilidades auditivas investigadas em 24,6% das crianças. Houve alteração timpanométrica em 34,4% das crianças e 64% foram classificadas no critério "falha" para a pesquisa do reflexo acústico ispilateral. As crianças mais jovens apresentaram maior ocorrência de alterações de orelha média, mas não houve diferença estatisticamente significante entre as diferentes idades para as provas realizadas. CONCLUSÃO: as crianças mais jovens apresentaram maior ocorrência de alterações nas provas de habilidades auditivas e nas medidas de imitância acústica. Programas de investigação e acompanhamento das condições de orelha média e das habilidades auditivas em idade pré-escolar e escolar podem eliminar ou minimizar intercorrências que alterariam o desenvolvimento sócio-linguístico.

Evaluation of 9 biomarkers for predicting 10-year cardiovascular risk in patients undergoing coronary angiography: findings from the LUdwigshafen RIsk and Cardiovascular Health (LURIC) study.

BACKGROUND Conventional factors do not fully explain the distribution of cardiovascular outcomes. Biomarkers are known to participate in well-established pathways associated with cardiovascular disease, and may therefore provide further information over and above conventional risk factors. This study sought to determine whether individual and/or combined assessment of 9 biomarkers improved discrimination, calibration and reclassification of cardiovascular mortality. METHODS 3267 patients (2283 men), aged 18-95 years, at intermediate-to-high-risk of cardiovascular disease were followed in this prospective cohort study. Conventional risk factors and biomarkers were included based on forward and backward Cox proportional stepwise selection models. RESULTS During 10-years of follow-up, 546 fatal cardiovascular events occurred. Four biomarkers (interleukin-6, neutrophils, von Willebrand factor, and 25-hydroxyvitamin D) were retained during stepwise selection procedures for subsequent analyses. Simultaneous inclusion of these biomarkers significantly improved discrimination as measured by the C-index (0.78, P = 0.0001), and integrated discrimination improvement (0.0219, P<0.0001). Collectively, these biomarkers improved net reclassification for cardiovascular death by 10.6% (P<0.0001) when added to the conventional risk model. CONCLUSIONS In terms of adverse cardiovascular prognosis, a biomarker panel consisting of interleukin-6, neutrophils, von Willebrand factor, and 25-hydroxyvitamin D offered significant incremental value beyond that conveyed by simple conventional risk factors.

Modelos Estadísticos Dinámicos para Análisis de Evolución de Tasas de Accidentes: Metodología y Herramientas Computacionales

Los accidentes del tráfico son un fenómeno social muy relevantes y una de las principales causas de mortalidad en los países desarrollados. Para entender este fenómeno complejo se aplican modelos econométricos sofisticados tanto en la literatura académica como por las administraciones públicas. Esta tesis está dedicada al análisis de modelos macroscópicos para los accidentes del tráfico en España. El objetivo de esta tesis se puede dividir en dos bloques: a. Obtener una mejor comprensión del fenómeno de accidentes de trafico mediante la aplicación y comparación de dos modelos macroscópicos utilizados frecuentemente en este área: DRAG y UCM, con la aplicación a los accidentes con implicación de furgonetas en España durante el período 2000-2009. Los análisis se llevaron a cabo con enfoque frecuencista y mediante los programas TRIO, SAS y TRAMO/SEATS. b. La aplicación de modelos y la selección de las variables más relevantes, son temas actuales de investigación y en esta tesis se ha desarrollado y aplicado una metodología que pretende mejorar, mediante herramientas teóricas y prácticas, el entendimiento de selección y comparación de los modelos macroscópicos. Se han desarrollado metodologías tanto para selección como para comparación de modelos. La metodología de selección de modelos se ha aplicado a los accidentes mortales ocurridos en la red viaria en el período 2000-2011, y la propuesta metodológica de comparación de modelos macroscópicos se ha aplicado a la frecuencia y la severidad de los accidentes con implicación de furgonetas en el período 2000-2009. Como resultado de los desarrollos anteriores se resaltan las siguientes contribuciones: a. Profundización de los modelos a través de interpretación de las variables respuesta y poder de predicción de los modelos. El conocimiento sobre el comportamiento de los accidentes con implicación de furgonetas se ha ampliado en este proceso. bl. Desarrollo de una metodología para selección de variables relevantes para la explicación de la ocurrencia de accidentes de tráfico. Teniendo en cuenta los resultados de a) la propuesta metodológica se basa en los modelos DRAG, cuyos parámetros se han estimado con enfoque bayesiano y se han aplicado a los datos de accidentes mortales entre los años 2000-2011 en España. Esta metodología novedosa y original se ha comparado con modelos de regresión dinámica (DR), que son los modelos más comunes para el trabajo con procesos estocásticos. Los resultados son comparables, y con la nueva propuesta se realiza una aportación metodológica que optimiza el proceso de selección de modelos, con escaso coste computacional. b2. En la tesis se ha diseñado una metodología de comparación teórica entre los modelos competidores mediante la aplicación conjunta de simulación Monte Cario, diseño de experimentos y análisis de la varianza ANOVA. Los modelos competidores tienen diferentes estructuras, que afectan a la estimación de efectos de las variables explicativas. Teniendo en cuenta el estudio desarrollado en bl) este desarrollo tiene el propósito de determinar como interpretar la componente de tendencia estocástica que un modelo UCM modela explícitamente, a través de un modelo DRAG, que no tiene un método específico para modelar este elemento. Los resultados de este estudio son importantes para ver si la serie necesita ser diferenciada antes de modelar. b3. Se han desarrollado nuevos algoritmos para realizar los ejercicios metodológicos, implementados en diferentes programas como R, WinBUGS, y MATLAB. El cumplimiento de los objetivos de la tesis a través de los desarrollos antes enunciados se remarcan en las siguientes conclusiones: 1. El fenómeno de accidentes del tráfico se ha analizado mediante dos modelos macroscópicos. Los efectos de los factores de influencia son diferentes dependiendo de la metodología aplicada. Los resultados de predicción son similares aunque con ligera superioridad de la metodología DRAG. 2. La metodología para selección de variables y modelos proporciona resultados prácticos en cuanto a la explicación de los accidentes de tráfico. La predicción y la interpretación también se han mejorado mediante esta nueva metodología. 3. Se ha implementado una metodología para profundizar en el conocimiento de la relación entre las estimaciones de los efectos de dos modelos competidores como DRAG y UCM. Un aspecto muy importante en este tema es la interpretación de la tendencia mediante dos modelos diferentes de la que se ha obtenido información muy útil para los investigadores en el campo del modelado. Los resultados han proporcionado una ampliación satisfactoria del conocimiento en torno al proceso de modelado y comprensión de los accidentes con implicación de furgonetas y accidentes mortales totales en España. ABSTRACT Road accidents are a very relevant social phenomenon and one of the main causes of death in industrialized countries. Sophisticated econometric models are applied in academic work and by the administrations for a better understanding of this very complex phenomenon. This thesis is thus devoted to the analysis of macro models for road accidents with application to the Spanish case. The objectives of the thesis may be divided in two blocks: a. To achieve a better understanding of the road accident phenomenon by means of the application and comparison of two of the most frequently used macro modelings: DRAG (demand for road use, accidents and their gravity) and UCM (unobserved components model); the application was made to van involved accident data in Spain in the period 2000-2009. The analysis has been carried out within the frequentist framework and using available state of the art software, TRIO, SAS and TRAMO/SEATS. b. Concern on the application of the models and on the relevant input variables to be included in the model has driven the research to try to improve, by theoretical and practical means, the understanding on methodological choice and model selection procedures. The theoretical developments have been applied to fatal accidents during the period 2000-2011 and van-involved road accidents in 2000-2009. This has resulted in the following contributions: a. Insight on the models has been gained through interpretation of the effect of the input variables on the response and prediction accuracy of both models. The behavior of van-involved road accidents has been explained during this process. b1. Development of an input variable selection procedure, which is crucial for an efficient choice of the inputs. Following the results of a) the procedure uses the DRAG-like model. The estimation is carried out within the Bayesian framework. The procedure has been applied for the total road accident data in Spain in the period 2000-2011. The results of the model selection procedure are compared and validated through a dynamic regression model given that the original data has a stochastic trend. b2. A methodology for theoretical comparison between the two models through Monte Carlo simulation, computer experiment design and ANOVA. The models have a different structure and this affects the estimation of the effects of the input variables. The comparison is thus carried out in terms of the effect of the input variables on the response, which is in general different, and should be related. Considering the results of the study carried out in b1) this study tries to find out how a stochastic time trend will be captured in DRAG model, since there is no specific trend component in DRAG. Given the results of b1) the findings of this study are crucial in order to see if the estimation of data with stochastic component through DRAG will be valid or whether the data need a certain adjustment (typically differencing) prior to the estimation. The model comparison methodology was applied to the UCM and DRAG models, considering that, as mentioned above, the UCM has a specific trend term while DRAG does not. b3. New algorithms were developed for carrying out the methodological exercises. For this purpose different softwares, R, WinBUGs and MATLAB were used. These objectives and contributions have been resulted in the following findings: 1. The road accident phenomenon has been analyzed by means of two macro models: The effects of the influential input variables may be estimated through the models, but it has been observed that the estimates vary from one model to the other, although prediction accuracy is similar, with a slight superiority of the DRAG methodology. 2. The variable selection methodology provides very practical results, as far as the explanation of road accidents is concerned. Prediction accuracy and interpretability have been improved by means of a more efficient input variable and model selection procedure. 3. Insight has been gained on the relationship between the estimates of the effects using the two models. A very relevant issue here is the role of trend in both models, relevant recommendations for the analyst have resulted from here. The results have provided a very satisfactory insight into both modeling aspects and the understanding of both van-involved and total fatal accidents behavior in Spain.

Handbook of hearing aid measurement /

Description based on: 1981.

Assessing the performance of a nucleus estate and smallholder scheme for oil palm production in West Sumatra: a stochastic frontier analysis

In this paper, we study the performance of smallholders in a nucleus estate and smallholder (NES) scheme in oil palm production schemein West Sumatra by measuring their technical efficiency using a stochastic frontier production function. Our results indicate a mean technical efficiency of 66%, which is below what we would have expected given the uniformity of the climate, soils and plantation construction among the sample farmers. The use of progressive farmers as a means of disseminating extension advice does not appear to have been successful, and more rigorous farmer selection procedures need to be put in place for similar schemes and for general agricultural extension in future. No clear relationship was established between technical efficiency and the use of female labour, suggesting there is no need to target extension services specifically at female labourers in the household. Finally, education was found to have an unexpectedly negative impact on technical efficiency, indicating that farmers with primary education may be more important than those with secondary and tertiary education as targets of development schemes and extension programs entailing non-formal education. (C) 2003 Elsevier Ltd. All rights reserved.

A new method for conservation planning for the persistence of multiple species

Although the aim of conservation planning is the persistence of biodiversity, current methods trade-off ecological realism at a species level in favour of including multiple species and landscape features. For conservation planning to be relevant, the impact of landscape configuration on population processes and the viability of species needs to be considered. We present a novel method for selecting reserve systems that maximize persistence across multiple species, subject to a conservation budget. We use a spatially explicit metapopulation model to estimate extinction risk, a function of the ecology of the species and the amount, quality and configuration of habitat. We compare our new method with more traditional, area-based reserve selection methods, using a ten-species case study, and find that the expected loss of species is reduced 20-fold. Unlike previous methods, we avoid designating arbitrary weightings between reserve size and configuration; rather, our method is based on population processes and is grounded in ecological theory.

Biodiversity conservation planning tools: Present status and challenges for the future

Species extinctions and the deterioration of other biodiversity features worldwide have led to the adoption of systematic conservation planning in many regions of the world. As a consequence, various software tools for conservation planning have been developed over the past twenty years. These, tools implement algorithms designed to identify conservation area networks for the representation and persistence of biodiversity features. Budgetary, ethical, and other sociopolitical constraints dictate that the prioritized sites represent biodiversity with minimum impact on human interests. Planning tools are typically also used to satisfy these criteria. This chapter reviews both the concepts and technical choices that underlie the development of these tools. Conservation planning problems can be formulated as optimization problems, and we evaluate the suitability of different algorithms for their solution. Finally, we also review some key issues associated with the use of these tools, such as computational efficiency, the effectiveness of taxa and abiotic parameters at choosing surrogates for biodiversity, the process of setting explicit targets of representation for biodiversity surrogates, and

Conservation planning with irreplaceability: does the method matter?

A number of systematic conservation planning tools are available to aid in making land use decisions. Given the increasing worldwide use and application of reserve design tools, including measures of site irreplaceability, it is essential that methodological differences and their potential effect on conservation planning outcomes are understood. We compared the irreplaceability of sites for protecting ecosystems within the Brigalow Belt Bioregion, Queensland, Australia, using two alternative reserve system design tools, Marxan and C-Plan. We set Marxan to generate multiple reserve systems that met targets with minimal area; the first scenario ignored spatial objectives, while the second selected compact groups of areas. Marxan calculates the irreplaceability of each site as the proportion of solutions in which it occurs for each of these set scenarios. In contrast, C-Plan uses a statistical estimate of irreplaceability as the likelihood that each site is needed in all combinations of sites that satisfy the targets. We found that sites containing rare ecosystems are almost always irreplaceable regardless of the method. Importantly, Marxan and C-Plan gave similar outcomes when spatial objectives were ignored. Marxan with a compactness objective defined twice as much area as irreplaceable, including many sites with relatively common ecosystems. However, targets for all ecosystems were met using a similar amount of area in C-Plan and Marxan, even with compactness. The importance of differences in the outcomes of using the two methods will depend on the question being addressed; in general, the use of two or more complementary tools is beneficial.

When do conservation planning methods deliver? Quantifying the consequences of uncertainty

The rapid global loss of biodiversity has led to a proliferation of systematic conservation planning methods. In spite of their utility and mathematical sophistication, these methods only provide approximate solutions to real-world problems where there is uncertainty and temporal change. The consequences of errors in these solutions are seldom characterized or addressed. We propose a conceptual structure for exploring the consequences of input uncertainty and oversimpli?ed approximations to real-world processes for any conservation planning tool or strategy. We then present a computational framework based on this structure to quantitatively model species representation and persistence outcomes across a range of uncertainties. These include factors such as land costs, landscape structure, species composition and distribution, and temporal changes in habitat. We demonstrate the utility of the framework using several reserve selection methods including simple rules of thumb and more sophisticated tools such as Marxan and Zonation. We present new results showing how outcomes can be strongly affected by variation in problem characteristics that are seldom compared across multiple studies. These characteristics include number of species prioritized, distribution of species richness and rarity, and uncertainties in the amount and quality of habitat patches. We also demonstrate how the framework allows comparisons between conservation planning strategies and their response to error under a range of conditions. Using the approach presented here will improve conservation outcomes and resource allocation by making it easier to predict and quantify the consequences of many different uncertainties and assumptions simultaneously. Our results show that without more rigorously generalizable results, it is very dif?cult to predict the amount of error in any conservation plan. These results imply the need for standard practice to include evaluating the effects of multiple real-world complications on the behavior of any conservation planning method.

The abstracts of the 4th UQ symposium on organisational psychology

These abstracts form the collection of papers that were presented at the 4th UQ Symposium on Organisational Psychology held at Emmanuel College, University of Queensland, Brisbane on Saturday 24th July, 2004. The UQ Symposium on Organisational Psychology is an annual even organised by the Centre for Organisational Psychology at the University of Queensland. The aim of the symposium is for academic psychologists to present their latest research to fellow academics and practitioners. Papers were accepted for either paper presentation or poster presentation following a peer-review process. The 100 delegates who attended consisted of practitioners and academics. The invited speaker was Dr Sally Carless (Monash University, Melbourne) who presented her latest research on selection procedures. The 5th Symposium will take place on Saturday 4th June, 2005. For more information about the UQ Symposium on Organisational Psychology series please contact Robin Martin

Méthodes de Bootstrap pour les modèles à facteurs

Cette thèse développe des méthodes bootstrap pour les modèles à facteurs qui sont couram- ment utilisés pour générer des prévisions depuis l'article pionnier de Stock et Watson (2002) sur les indices de diffusion. Ces modèles tolèrent l'inclusion d'un grand nombre de variables macroéconomiques et financières comme prédicteurs, une caractéristique utile pour inclure di- verses informations disponibles aux agents économiques. Ma thèse propose donc des outils éco- nométriques qui améliorent l'inférence dans les modèles à facteurs utilisant des facteurs latents extraits d'un large panel de prédicteurs observés. Il est subdivisé en trois chapitres complémen- taires dont les deux premiers en collaboration avec Sílvia Gonçalves et Benoit Perron. Dans le premier article, nous étudions comment les méthodes bootstrap peuvent être utilisées pour faire de l'inférence dans les modèles de prévision pour un horizon de h périodes dans le futur. Pour ce faire, il examine l'inférence bootstrap dans un contexte de régression augmentée de facteurs où les erreurs pourraient être autocorrélées. Il généralise les résultats de Gonçalves et Perron (2014) et propose puis justifie deux approches basées sur les résidus : le block wild bootstrap et le dependent wild bootstrap. Nos simulations montrent une amélioration des taux de couverture des intervalles de confiance des coefficients estimés en utilisant ces approches comparativement à la théorie asymptotique et au wild bootstrap en présence de corrélation sérielle dans les erreurs de régression. Le deuxième chapitre propose des méthodes bootstrap pour la construction des intervalles de prévision permettant de relâcher l'hypothèse de normalité des innovations. Nous y propo- sons des intervalles de prédiction bootstrap pour une observation h périodes dans le futur et sa moyenne conditionnelle. Nous supposons que ces prévisions sont faites en utilisant un ensemble de facteurs extraits d'un large panel de variables. Parce que nous traitons ces facteurs comme latents, nos prévisions dépendent à la fois des facteurs estimés et les coefficients de régres- sion estimés. Sous des conditions de régularité, Bai et Ng (2006) ont proposé la construction d'intervalles asymptotiques sous l'hypothèse de Gaussianité des innovations. Le bootstrap nous permet de relâcher cette hypothèse et de construire des intervalles de prédiction valides sous des hypothèses plus générales. En outre, même en supposant la Gaussianité, le bootstrap conduit à des intervalles plus précis dans les cas où la dimension transversale est relativement faible car il prend en considération le biais de l'estimateur des moindres carrés ordinaires comme le montre une étude récente de Gonçalves et Perron (2014). Dans le troisième chapitre, nous suggérons des procédures de sélection convergentes pour les regressions augmentées de facteurs en échantillons finis. Nous démontrons premièrement que la méthode de validation croisée usuelle est non-convergente mais que sa généralisation, la validation croisée «leave-d-out» sélectionne le plus petit ensemble de facteurs estimés pour l'espace généré par les vraies facteurs. Le deuxième critère dont nous montrons également la validité généralise l'approximation bootstrap de Shao (1996) pour les regressions augmentées de facteurs. Les simulations montrent une amélioration de la probabilité de sélectionner par- cimonieusement les facteurs estimés comparativement aux méthodes de sélection disponibles. L'application empirique revisite la relation entre les facteurs macroéconomiques et financiers, et l'excès de rendement sur le marché boursier américain. Parmi les facteurs estimés à partir d'un large panel de données macroéconomiques et financières des États Unis, les facteurs fortement correlés aux écarts de taux d'intérêt et les facteurs de Fama-French ont un bon pouvoir prédictif pour les excès de rendement.

Governing the transition to higher levels of education and differences between achievement and school grades by gender

The author will explore the performance of boys and girls in external examinations in Slovenia at the beginning of upper secondary and tertiary education. These are critical points in students’ educational career at which he/she has to choose a school/university. Since both transitions are managed centrally by appropriate authorities, this is also a question of Educational Governance. Transitions between levels of education should, above all, assure fairness in selection procedures. At the point of transition to upper secondary schools we will explore differences between students’ achievements in various school subjects tested at the national assessment of knowledge (NA), and their school grades by gender. Since only school grades are used as admission criteria to upper secondary schools, this comparison of school grades with external and more objective measure of students’ achievement will show possible bias. In Slovenia admission to tertiary education usually consists of (externally assessed) Matura results and school grades in the last two years of upper secondary school. The author will compare the effects of both most commonly used measures of academic achievement on admission in view of gender differences. Study courses where selection procedure was actually applied will be of specific interest since they can show signs of (un)fairness. Results show signs of bias and build case for better Educational Governance. (DIPF/Orig.)

Méthodes de Bootstrap pour les modèles à facteurs

Cette thèse développe des méthodes bootstrap pour les modèles à facteurs qui sont couram- ment utilisés pour générer des prévisions depuis l'article pionnier de Stock et Watson (2002) sur les indices de diffusion. Ces modèles tolèrent l'inclusion d'un grand nombre de variables macroéconomiques et financières comme prédicteurs, une caractéristique utile pour inclure di- verses informations disponibles aux agents économiques. Ma thèse propose donc des outils éco- nométriques qui améliorent l'inférence dans les modèles à facteurs utilisant des facteurs latents extraits d'un large panel de prédicteurs observés. Il est subdivisé en trois chapitres complémen- taires dont les deux premiers en collaboration avec Sílvia Gonçalves et Benoit Perron. Dans le premier article, nous étudions comment les méthodes bootstrap peuvent être utilisées pour faire de l'inférence dans les modèles de prévision pour un horizon de h périodes dans le futur. Pour ce faire, il examine l'inférence bootstrap dans un contexte de régression augmentée de facteurs où les erreurs pourraient être autocorrélées. Il généralise les résultats de Gonçalves et Perron (2014) et propose puis justifie deux approches basées sur les résidus : le block wild bootstrap et le dependent wild bootstrap. Nos simulations montrent une amélioration des taux de couverture des intervalles de confiance des coefficients estimés en utilisant ces approches comparativement à la théorie asymptotique et au wild bootstrap en présence de corrélation sérielle dans les erreurs de régression. Le deuxième chapitre propose des méthodes bootstrap pour la construction des intervalles de prévision permettant de relâcher l'hypothèse de normalité des innovations. Nous y propo- sons des intervalles de prédiction bootstrap pour une observation h périodes dans le futur et sa moyenne conditionnelle. Nous supposons que ces prévisions sont faites en utilisant un ensemble de facteurs extraits d'un large panel de variables. Parce que nous traitons ces facteurs comme latents, nos prévisions dépendent à la fois des facteurs estimés et les coefficients de régres- sion estimés. Sous des conditions de régularité, Bai et Ng (2006) ont proposé la construction d'intervalles asymptotiques sous l'hypothèse de Gaussianité des innovations. Le bootstrap nous permet de relâcher cette hypothèse et de construire des intervalles de prédiction valides sous des hypothèses plus générales. En outre, même en supposant la Gaussianité, le bootstrap conduit à des intervalles plus précis dans les cas où la dimension transversale est relativement faible car il prend en considération le biais de l'estimateur des moindres carrés ordinaires comme le montre une étude récente de Gonçalves et Perron (2014). Dans le troisième chapitre, nous suggérons des procédures de sélection convergentes pour les regressions augmentées de facteurs en échantillons finis. Nous démontrons premièrement que la méthode de validation croisée usuelle est non-convergente mais que sa généralisation, la validation croisée «leave-d-out» sélectionne le plus petit ensemble de facteurs estimés pour l'espace généré par les vraies facteurs. Le deuxième critère dont nous montrons également la validité généralise l'approximation bootstrap de Shao (1996) pour les regressions augmentées de facteurs. Les simulations montrent une amélioration de la probabilité de sélectionner par- cimonieusement les facteurs estimés comparativement aux méthodes de sélection disponibles. L'application empirique revisite la relation entre les facteurs macroéconomiques et financiers, et l'excès de rendement sur le marché boursier américain. Parmi les facteurs estimés à partir d'un large panel de données macroéconomiques et financières des États Unis, les facteurs fortement correlés aux écarts de taux d'intérêt et les facteurs de Fama-French ont un bon pouvoir prédictif pour les excès de rendement.

Determining conservation priority areas for Palearctic passerine migrant birds in sub-Saharan Africa

Migratory bird species breeding in the Palearctic and overwintering in sub-Saharan Africa face multiple conservation challenges. As a result, many of these species have declined in recent decades, some dramatically. We therefore used the best available database for the distribution of 68 passerine migrants in sub-Saharan Africa to determine priority regions for their conservation. After modeling each species’ distribution using BIOMOD software, we entered the resulting species distributions at a 1° × 1° grid resolution into MARXAN software. We then used several different selection procedures that varied the boundary length modifier, species penalty factor, and the inclusion of grid cells with high human footprint and with protected areas. While results differed between selection procedures, four main regions were regularly selected: (1) one centered on southern Mali; (2) one including Eritrea, central Sudan, and northern Ethiopia; (3) one encompassing southwestern Kenya and much of Tanzania and Uganda; and (4) one including much of Zimbabwe and southwestern Zambia. We recommend that these four regions become priority regions for research and conservation efforts for the bird species considered in this study.