Estructura factorial y consistencia interna de la Escala de Severidad de Fatiga en población colombiana con enfermedades crónicas

El presente estudio de corte psicométrico, tuvo como objetivo analizar la estructura factorial y la consistencia interna versión en español del cuestionario Fatigue Severity Scale (FSS) en población colombiana de enfermos crónicos. Para ello se aplicó el cuestionario a 52 enfermos crónicos de la ciudad de Villavicencio. El análisis factorial denota tres factores: el factor 1 denominado como afectación física, el factor 2 denominado afectación social y finalmente el factor 3 denominado afectación motivacional de la fatiga, que explican el 76,324% de la varianza total acumulada, y un alfa de Cronbach de 870. Los resultados muestran una alta confiabilidad y concordancia en la estructura factorial con la versión original, lo que implica adecuada validez de la prueba en población colombiana de enfermos crónicos.The present study has a psychometric design, with the objective of analyzing the factorial structure and the internal consistency for the Spanish version of the Fatigue Severity Scale (FSS) Questionnaire for Colombian population with chronic disease. Was applied the questionnaire to 52 people with chronic disease in Villavicencio city. The factorial Analysis indicates three factors: Factor 1 named physical affectation, Factor 2 named social affectation and Factor 3 named motivational affectation of the fatigue, where they explain the 76.324% of the total cumulative variance with .870 of Cronbach's Alpha. The results present a high reliability and concordance for the factorial structure with the original version which indicates an adequate validity of the test for Colombian population with chronic disease. © Servicio de Publicaciones - Universidad de Murcia

A multi-trait multi-environment QTL mixed model with an application to drought and nitrogen stress trials in maize (Zea mays L.)

Despite QTL mapping being a routine procedure in plant breeding, approaches that fully exploit data from multi-trait multi-environment (MTME) trials are limited. Mixed models have been proposed both for multi-trait QTL analysis and multi-environment QTL analysis, but these approaches break down when the number of traits and environments increases. We present models for an efficient QTL analysis of MTME data with mixed models by reducing the dimensionality of the genetic variance¿covariance matrix by structuring this matrix using direct products of relatively simple matrices representing variation in the trait and environmental dimension. In the context of MTME data, we address how to model QTL by environment interactions and the genetic basis of heterogeneity of variance and correlations between traits and environments. We illustrate our approach with an example including five traits across eight stress trials in CIMMYT maize. We detected 36 QTLs affecting yield, anthesis-silking interval, male flowering, ear number, and plant height in maize. Our approach does not require specialised software as it can be implemented in any statistical package with mixed model facilities

Obtaining environmental favourability functions from logistic regression

Logistic regression is a statistical tool widely used for predicting species’ potential distributions starting from presence/absence data and a set of independent variables. However, logistic regression equations compute probability values based not only on the values of the predictor variables but also on the relative proportion of presences and absences in the dataset, which does not adequately describe the environmental favourability for or against species presence. A few strategies have been used to circumvent this, but they usually imply an alteration of the original data or the discarding of potentially valuable information. We propose a way to obtain from logistic regression an environmental favourability function whose results are not affected by an uneven proportion of presences and absences. We tested the method on the distribution of virtual species in an imaginary territory. The favourability models yielded similar values regardless of the variation in the presence/absence ratio. We also illustrate with the example of the Pyrenean desman’s (Galemys pyrenaicus) distribution in Spain. The favourability model yielded more realistic potential distribution maps than the logistic regression model. Favourability values can be regarded as the degree of membership of the fuzzy set of sites whose environmental conditions are favourable to the species, which enables applying the rules of fuzzy logic to distribution modelling. They also allow for direct comparisons between models for species with different presence/absence ratios in the study area. This makes themmore useful to estimate the conservation value of areas, to design ecological corridors, or to select appropriate areas for species reintroductions

Use of Coarse-resolution models of species' distributions to guide local conservation inferences

Distribution models are used increasingly for species conservation assessments over extensive areas, but the spatial resolution of the modeled data and, consequently, of the predictions generated directly from these models are usually too coarse for local conservation applications. Comprehensive distribution data at finer spatial resolution, however, require a level of sampling that is impractical for most species and regions. Models can be downscaled to predict distribution at finer resolutions, but this increases uncertainty because the predictive ability of models is not necessarily consistent beyond their original scale. We analyzed the performance of downscaled, previously published models of environmental favorability (a generalized linear modeling technique) for a restricted endemic insectivore, the Iberian desman (Galemys pyrenaicus), and a more widespread carnivore, the Eurasian otter ( Lutra lutra), in the Iberian Peninsula. The models, built from presence–absence data at 10 × 10 km resolution, were extrapolated to a resolution 100 times finer (1 × 1 km). We compared downscaled predictions of environmental quality for the two species with published data on local observations and on important conservation sites proposed by experts. Predictions were significantly related to observed presence or absence of species and to expert selection of sampling sites and important conservation sites. Our results suggest the potential usefulness of downscaled projections of environmental quality as a proxy for expensive and time-consuming field studies when the field studies are not feasible. This method may be valid for other similar species if coarse-resolution distribution data are available to define high-quality areas at a scale that is practical for the application of concrete conservation measure

Modelling the distribution of Bonelli's eagle in Spain: Implications for conservation planning

Bonelli’s eagle, Hieraaetus fasciatus , has recently suffered a severe population decline and is currently endangered. Spain supports about 70% of the European population. We used stepwise logistic regression on a set of environmental, spatial and human variables to model Bonelli’s eagle distribution in the 5167 UTM 10 × 10 km quadrats of peninsular Spain. We obtained a model based on 16 variables, which allowed us to identify favourable and unfavourable areas for this species in Spain, as well as intermediate favourability areas. We assessed the stepwise progression of the model by comparing the model’s predictions in each step with those of the final model, and selected a parsimonious explanatory model based on three variables — slope, July temperature and precipitation — comprising 76% of the predictive capacity of th

Otter (Lutra lutra) distribution modeling at two resolution scales suited to conservation planning in the Iberian Peninsula

We used the results of the Spanish Otter Survey of 1994–1996, a Geographic Information System and stepwise multiple logistic regression to model otter presence/absence data in the continental Spanish UTM 10 10-km squares. Geographic situation, indicators of human activity such as highways and major urban centers, and environmental variables related with productivity, water availability, altitude, and environmental energy were included in a logistic model that correctly classified about 73% of otter presences and absences. We extrapolated the model to the adjacent territory of Portugal, and increased the model’s spatial resolution by extrapolating it to 1 1-km squares in the whole Iberian Peninsula. The model turned out to be rather flexible, predicting, for instance, the species to be very restricted to the courses of rivers in some areas, and more widespread in others. This allowed us to determine areas where otter populations may be more vulnerable to habitat changes or harmful human interventions. # 2003 Elsevier Ltd. All rights reserved

Pb, Sr, and Nd isotopic characteristics of a variety of lithologies from the Guerrero composite terrane, west-central Mexico: constraints on their origin

Lead, Sr, and Nd isotope analyses of Mesozoic and Cenozoic rocks from the southern part of Guerrero terrane in Mexico provide a better understanding of their origin. Metamorphic rocks collected south of Arteaga (Zihuatanejo terrane) have similar Pb isotope values to basement rocks from Nevado de Toluca, indicating a possible connection of the basement in these areas. Lead isotope ratios of rocks from the Mesozoic Guerrero and Paleozoic Mixteca terranes are similar to those of north Peruvian Mesozoic Olmos and Paleozoic Marañón complexes, but more radiogenic than Grenville-age basement of southeast Mexico (Guichicovi complex) and north Colombia (Garzón massif and Santa Marta massif). Present-day Pb, Sr, and Nd isotope ratios of Mesozoic sedimentary rocks from Zihuatanejo and Teloloapan terranes define two clusters: rock from the Huetamo region (Zihuatanejo terrane), with less evolved isotopic signatures, and rocks from the Coastal belt (Colima and Purificación areas in Zihuatanejo terrane) and from the Teloloapan area (Teloloapan terrane) with higher isotopic ratios. Pb, Sr, and Nd isotopic ratios suggest the involvement of a more evolved component, possibly the basement rocks, in the generation of the sedimentary rocks from the Coastal belt and south of Teloloapan area compared to the sedimentary rocks from the Huetamo area. Cenozoic plutonic rocks from La Verde have more radiogenic isotopic ratios than samples from Inguarán, El Malacate, and La Esmeralda. These differences could result from assimilation of different rocks (Arteaga complex or sedimentary rocks) or different extents of contamination. Initial Sr and Nd isotopic values of the Cretaceous granitoids from Manzanillo and Jilotlán plot very close to the igneous samples from Inguarán, El Malacate, and La Esmeralda; this similarity may indicate that they had a common source. Isotopic compositions of Cenozoic plutonic rocks are consistent with subduction-related magmatism and suggest involvement of crustal material by assimilation during the rise of the magma, or by incorporation of subducted sediments, or both

Phylogeographic Triangulation: Using Predator-Prey-Parasite Interactions to Infer Population History from Partial Genetic Information

Phylogeographic studies, which infer population history and dispersal movements from intra-specific spatial genetic variation, require expensive and time-consuming analyses that are not always feasible, especially in the case of rare or endangered species. On the other hand, comparative phylogeography of species involved in close biotic interactions may show congruent patterns depending on the specificity of the relationship. Consequently, the phylogeography of a parasite that needs two hosts to complete its life cycle should reflect population history traits of both hosts. Population movements evidenced by the parasite’s phylogeography that are not reflected in the phylogeography of one of these hosts may thus be attributed to the other host. Using the wild rabbit (Oryctolagus cuniculus) and a parasitic tapeworm (Taenia pisiformis) as an example, we propose comparing the phylogeography of easily available organisms such as game species and their specific heteroxenous parasites to infer population movements of definitive host/predator species, independently of performing genetic analyses on the latter. This may be an interesting approach for indirectly studying the history of species whose phylogeography is difficult to analyse directly

Land use and environmental factors affecting red-legged partridge (Alectoris rufa) hunting yields in southern Spain

The red-legged partridge is a small game species widely hunted in southern Spain. Its commercial use has important socioeconomic effects in rural areas where other agrarian uses are of marginal importance. The aims of the present work were to identify areas in Andalusia (southern Spain) where game yields for the red-legged partridge reach high values and to establish the environmental and land use factors that determine them. We analysed 32,134 annual hunting reports (HRs) produced by 6,049 game estates during the hunting seasons 1993/1994 to 2001/2002 to estimate the average hunting yields of red-legged partridge in each Andalusian municipality (n=771). We modelled the favourability for obtaining good hunting yields using stepwise logistic regression on a set of climatic, topographical, land use and vegetation variables that were available as digital coverages or tabular data applied to municipalities. Good hunting yields occur mainly in plain areas located in the Guadalquivir valley, at the bottom of Betic Range and in the Betic depressions. Favourable areas are related to highly mechanised, lowelevation areas mainly dedicated to intensive dry crops. The most favourable areas predicted by our model are mainly located in the Guadalquivir valley

Distribution modelling of wild rabbit hunting yields in its original area (S Iberian Peninsula)

In this work we used the information of the Annual Hunting Reports (AHRs) to obtain a high-resolution model of the potential favourableness for wild rabbit harvesting in Andalusia (southern Spain), using environmental and land-use variables as predictors. We analysed 32,134 AHRs from the period 1993/2001 reported by 6049 game estates to estimate the average hunting yields of wild rabbit in each Andalusian municipality (n5771). We modelled the favourableness for obtaining good hunting yields using stepwise logistic regression on a set of climatic, orographical, land use, and vegetation variables. The favourability equation was used to create a downscaled image representing the favourableness of obtaining good hunting yields for the wild rabbit in 161 km squares in Andalusia, using the Idrisi Image Calculator. The variables that affected hunting yields of wild rabbit were altitude, dry wood crops (mainly olive groves, almond groves, and vineyards), temperature, pasture, slope, and annual number of frost days. The 161 km squares with high favourableness values are scattered throughout the territory, which seems to be caused mainly by the effect of vegetation. Finally, we obtained quality categories for the territory by combining the probability values given by logistic regression with those of the environmental favourability function