Using ecological niche models to support tree species selection for forest restoration planning in largely deforested regions

Species selection for forest restoration is often supported by expert knowledge on local distribution patterns of native tree species. This approach is not applicable to largely deforested regions unless enough data on pre-human tree species distribution is available. In such regions, ecological niche models may provide essential information to support species selection in the framework of forest restoration planning. In this study we used ecological niche models to predict habitat suitability for native tree species in "Tierra de Campos" region, an almost totally deforested area of the Duero Basin (Spain). Previously available models provide habitat suitability predictions for dominant native tree species, but including non-dominant tree species in the forest restoration planning may be desirable to promote biodiversity, specially in largely deforested areas were near seed sources are not expected. We used the Forest Map of Spain as species occurrence data source to maximize the number of modeled tree species. Penalized logistic regression was used to train models using climate and lithological predictors. Using model predictions a set of tools were developed to support species selection in forest restoration planning. Model predictions were used to build ordered lists of suitable species for each cell of the study area. The suitable species lists were summarized drawing maps that showed the two most suitable species for each cell. Additionally, potential distribution maps of the suitable species for the study area were drawn. For a scenario with two dominant species, the models predicted a mixed forest (Quercus ilex and a coniferous tree species) for almost one half of the study area. According to the models, 22 non-dominant native tree species are suitable for the study area, with up to six suitable species per cell. The model predictions pointed to Crataegus monogyna, Juniperus communis, J.oxycedrus and J.phoenicea as the most suitable non-dominant native tree species in the study area. Our results encourage further use of ecological niche models for forest restoration planning in largely deforested regions.

Bases metodológicas para un sistema de apoyo a la selección de especies en la restauración de la vegetación

RESUMEN El apoyo a la selección de especies a la restauración de la vegetación en España en los últimos 40 años se ha basado fundamentalmente en modelos de distribución de especies, también llamados modelos de nicho ecológico, que estiman la probabilidad de presencia de las especies en función de las condiciones del medio físico (clima, suelo, etc.). Con esta tesis se ha intentado contribuir a la mejora de la capacidad predictiva de los modelos introduciendo algunas propuestas metodológicas adaptadas a los datos disponibles actualmente en España y enfocadas al uso de los modelos en la selección de especies. No siempre se dispone de datos a una resolución espacial adecuada para la escala de los proyectos de restauración de la vegetación. Sin embrago es habitual contar con datos de baja resolución espacial para casi todas las especies vegetales presentes en España. Se propone un método de recalibración que actualiza un modelo de regresión logística de baja resolución espacial con una nueva muestra de alta resolución espacial. El método permite obtener predicciones de calidad aceptable con muestras relativamente pequeñas (25 presencias de la especie) frente a las muestras mucho mayores (más de 100 presencias) que requería una estrategia de modelización convencional que no usara el modelo previo. La selección del método estadístico puede influir decisivamente en la capacidad predictiva de los modelos y por esa razón la comparación de métodos ha recibido mucha atención en la última década. Los estudios previos consideraban a la regresión logística como un método inferior a técnicas más modernas como las de máxima entropía. Los resultados de la tesis demuestran que esa diferencia observada se debe a que los modelos de máxima entropía incluyen técnicas de regularización y la versión de la regresión logística usada en las comparaciones no. Una vez incorporada la regularización a la regresión logística usando penalización, las diferencias en cuanto a capacidad predictiva desaparecen. La regresión logística penalizada es, por tanto, una alternativa más para el ajuste de modelos de distribución de especies y está a la altura de los métodos modernos con mejor capacidad predictiva como los de máxima entropía. A menudo, los modelos de distribución de especies no incluyen variables relativas al suelo debido a que no es habitual que se disponga de mediciones directas de sus propiedades físicas o químicas. La incorporación de datos de baja resolución espacial proveniente de mapas de suelo nacionales o continentales podría ser una alternativa. Los resultados de esta tesis sugieren que los modelos de distribución de especies de alta resolución espacial mejoran de forma ligera pero estadísticamente significativa su capacidad predictiva cuando se incorporan variables relativas al suelo procedente de mapas de baja resolución espacial. La validación es una de las etapas fundamentales del desarrollo de cualquier modelo empírico como los modelos de distribución de especies. Lo habitual es validar los modelos evaluando su capacidad predictiva especie a especie, es decir, comparando en un conjunto de localidades la presencia o ausencia observada de la especie con las predicciones del modelo. Este tipo de evaluación no responde a una cuestión clave en la restauración de la vegetación ¿cuales son las n especies más idóneas para el lugar a restaurar? Se ha propuesto un método de evaluación de modelos adaptado a esta cuestión que consiste en estimar la capacidad de un conjunto de modelos para discriminar entre las especies presentes y ausentes de un lugar concreto. El método se ha aplicado con éxito a la validación de 188 modelos de distribución de especies leñosas orientados a la selección de especies para la restauración de la vegetación en España. Las mejoras metodológicas propuestas permiten mejorar la capacidad predictiva de los modelos de distribución de especies aplicados a la selección de especies en la restauración de la vegetación y también permiten ampliar el número de especies para las que se puede contar con un modelo que apoye la toma de decisiones. SUMMARY During the last 40 years, decision support tools for plant species selection in ecological restoration in Spain have been based on species distribution models (also called ecological niche models), that estimate the probability of occurrence of the species as a function of environmental predictors (e.g., climate, soil). In this Thesis some methodological improvements are proposed to contribute to a better predictive performance of such models, given the current data available in Spain and focusing in the application of the models to selection of species for ecological restoration. Fine grained species distribution data are required to train models to be used at the scale of the ecological restoration projects, but this kind of data are not always available for every species. On the other hand, coarse grained data are available for almost every species in Spain. A recalibration method is proposed that updates a coarse grained logistic regression model using a new fine grained updating sample. The method allows obtaining acceptable predictive performance with reasonably small updating sample (25 occurrences of the species), in contrast with the much larger samples (more than 100 occurrences) required for a conventional modeling approach that discards the coarse grained data. The choice of the statistical method may have a dramatic effect on model performance, therefore comparisons of methods have received much interest in the last decade. Previous studies have shown a poorer performance of the logistic regression compared to novel methods like maximum entropy models. The results of this Thesis show that the observed difference is caused by the fact that maximum entropy models include regularization techniques and the versions of logistic regression compared do not. Once regularization has been added to the logistic regression using a penalization procedure, the differences in model performance disappear. Therefore, penalized logistic regression may be considered one of the best performing methods to model species distributions. Usually, species distribution models do not consider soil related predictors because direct measurements of the chemical or physical properties are often lacking. The inclusion of coarse grained soil data from national or continental soil maps could be a reasonable alternative. The results of this Thesis suggest that the performance of the models slightly increase after including soil predictors form coarse grained soil maps. Model validation is a key stage of the development of empirical models, such as species distribution models. The usual way of validating is based on the evaluation of model performance for each species separately, i.e., comparing observed species presences or absence to predicted probabilities in a set of sites. This kind of evaluation is not informative for a common question in ecological restoration projects: which n species are the most suitable for the environment of the site to be restored? A method has been proposed to address this question that estimates the ability of a set of models to discriminate among present and absent species in a evaluation site. The method has been successfully applied to the validation of 188 species distribution models used to support decisions on species selection for ecological restoration in Spain. The proposed methodological approaches improve the predictive performance of the predictive models applied to species selection in ecological restoration and increase the number of species for which a model that supports decisions can be fitted.

Multiple proportion case-basing driven CBRE and its application in the evaluation of possible failure of firms

Case-based reasoning (CBR) is a unique tool for the evaluation of possible failure of firms (EOPFOF) for its eases of interpretation and implementation. Ensemble computing, a variation of group decision in society, provides a potential means of improving predictive performance of CBR-based EOPFOF. This research aims to integrate bagging and proportion case-basing with CBR to generate a method of proportion bagging CBR for EOPFOF. Diverse multiple case bases are first produced by multiple case-basing, in which a volume parameter is introduced to control the size of each case base. Then, the classic case retrieval algorithm is implemented to generate diverse member CBR predictors. Majority voting, the most frequently used mechanism in ensemble computing, is finally used to aggregate outputs of member CBR predictors in order to produce final prediction of the CBR ensemble. In an empirical experiment, we statistically validated the results of the CBR ensemble from multiple case bases by comparing them with those of multivariate discriminant analysis, logistic regression, classic CBR, the best member CBR predictor and bagging CBR ensemble. The results from Chinese EOPFOF prior to 3 years indicate that the new CBR ensemble, which significantly improved CBRs predictive ability, outperformed all the comparative methods.

La presencia de mobbing y sus determinantes laborales en profesores universitarios

En este artículo se analiza la presencia de mobbing en el profesorado universitario como parte de un estudio trasversal más amplio sobre su calidad de vida, trabajo y salud. Los objetivos del estudio son tres: 1) conocer la frecuencia del mobbing en un contexto universitario, 2) examinar la asociación existente entre mobbing y la edad, el género y la categoría académica de los profesores, y 3) estudiar los mejores predictores del mobbing. Respondieron el cuestionario 252 profesores a tiempo completo, lo que ha significado una tasa de respuesta del 61,6%. Nuestros resultados muestran que casi el veintitrés por ciento (22,6%) de los profesores se sintieron víctimas de mobbing. No hemos encontrado diferencias estadísticamente significativas en mobbing debidas a la edad, género o categoría académica de los profesores. Según diversos análisis de regresión logística jerárquica por bloques que hemos realizado, los mejores predictores del mobbing han resultado ser: el grado de autonomía en el trabajo y la satisfacción experimentada en las relaciones con los supervisores. Estas 2 variables han explicado, en nuestro estudio, casi un 37% de la variabilidad del mobbing. Serían necesarios estudios longitudinales o experimentales para poder establecer relaciones de causalidad entre mobbing y contexto laboral.

Auto-atribuciones académicas: diferencias de género y curso en estudiantes de educación secundaria

El análisis de las autoatribuciones académicas constituye un aspecto esencial del componente afectivo y emocional de la motivación escolar en estudiantes de educación secundaria obligatoria (ESO). El objetivo de este estudio fue analizar, mediante un diseño transversal, las diferencias de género y curso y el papel predictivo de estas variables en las atribuciones causales académicas de los alumnos medidas a través de las escalas generales de la Sydney Attribution Scale (SAS). El cuestionario fue administrado a 2.022 estudiantes (51.08% chicos) de 1º a 4º de ESO. El rango de edad fue de 12 a 16 años (M = 13.81; DT = 1.35). Los resultados derivados de los análisis de varianza y de los tamaños del efecto (índice d) revelaron que los chicos atribuyeron sus éxitos significativamente más a su capacidad, mientras las chicas los atribuyeron significativamente más al esfuerzo. Respecto a las atribuciones de fracaso escolar, los resultados indicaron que los chicos los atribuyeron significativamente más a la falta de esfuerzo que las chicas. Asimismo, se hallaron diferencias de curso académico en la mayoría de las atribuciones causales analizadas. Los análisis de regresión logística indicaron que el género y el curso fueron predictores significativos de las atribuciones causales académicas, aunque los resultados variaron para cada una de las escalas de la SAS. Los resultados son discutidos en relación a la necesidad de diseñar programas de intervención que tengan en cuenta las variables sexo y curso académico.

Comparative analysis of the relationship between anterior and posterior corneal shape analyzed by Scheimpflug photography in normal and keratoconus eyes

Background To analyze and compare the relationship between anterior and posterior corneal shape evaluated by a tomographic system combining the Scheimpflug photography and Placido-disc in keratoconus and normal healthy eyes, as well as to evaluate its potential diagnostic value. Methods Comparative case series including a sample of 161 eyes of 161 subjects with ages ranging from 7 to 66 years and divided into two groups: normal group including 100 healthy eyes of 100 subjects, and keratoconus group including 61 keratoconus eyes of 61 patients. All eyes received a comprehensive ophthalmologic examination including an anterior segment analysis with the Sirius system (CSO). Antero-posterior ratios for corneal curvature (k ratio) and shape factor (p ratio) were calculated. Logistic regression analysis was used to evaluate if some antero–posterior ratios combined with other clinical parameters were predictors of the presence of keratoconus. Results No statistically significant differences between groups were found in the antero–posterior k ratios for 3-, 5- and 7-mm diameter corneal areas (p ≥ 0.09). The antero–posterior p ratio for 4.5- and 8-mm diameter corneal areas was significantly higher in the normal group than in the keratoconus group (p < 0.01). The k ratio for 3, 5, and 7 mm was significantly higher in the keratoconus grade IV subgroup than in the normal group (p < 0.01). Furthermore, significant differences were found in the p ratio between the normal group and the keratoconus grade II subgroup (p ≤ 0.01). Finally, the logistic regression analysis identified as significant independent predictors of the presence of keratoconus (p < 0.01) the 8-mm anterior shape factor, the anterior chamber depth, and the minimal corneal thickness. Conclusions The antero-posterior k and p ratios are parameters with poor prediction ability for keratoconus, in spite of the trend to the presence of more prolate posterior corneal surfaces compared to the anterior in keratoconus eyes.

Individual differences in predicting occupational success: The effect of population heterogeneity

Using a sample of 339 university graduates from the University of Alicante (Spain) three years after completion of their studies, we studied the relationships between general intelligence (GI), personality traits, emotional intelligence (EI), academic performance, and occupational attainment and compared the results of conventional regression analysis with the results obtained from applying regression mixture models. The results reveal the influence of unobserved population heterogeneity (latent class) on the relationship between predictors and criteria and the improvement in the prediction obtained from applying regression mixture models compared to applying a conventional regression model.

Power, privilege and HIV prevalence: examination of sexual HIV-risk factors in MSM and transgender women who engage in transactional sex

Thesis (Master's)--University of Washington, 2016-06

Satisfaction with medical rehabilitation after spinal cord injury

Study Design. Retrospective Objective. To predict satisfaction with medical rehabilitation. Summary of Background Data. While spinal cord injury (SCI) patient satisfaction with life and community services has been investigated, satisfaction with medical rehabilitation has not. Methods. Information submitted to the Uniform Data System for Medical Rehabilitation ( 1998 - 2001) by 134 hospitals/rehabilitation facilities in the United States (n = 6,205 patients with SCI) was examined. Predictors were sociodemographic variables, Case Mix Groupings (CMG) ( 401 - 505, 5001), length of stay, rehospitalization, followup therapy, and health maintenance. Satisfaction was assessed at a mean of 92.2 days (SD 11.9 days) postdischarge. Data were analyzed according to who reported the outcome ( patient, n = 3,858 or family/other, n = 1,869). Statistical modeling was conducted using logistic regression. Results. High overall satisfaction was reported (94%). Significant predictors for the patient report data were CMG and rehospitalization. Compared with CMG 5001 ( short stay,

Prevalence of whole-body skin self-examination in a population at high risk for skin cancer (Australia)

Objective: Whole-body skin self-examination (SSE) with presentation of suspicious lesions to a physician may improve early detection of melanoma. The aim of this study was to establish the prevalence and determinants of SSE in a high-risk population in preparation for a community-based randomised controlled trial of screening for melanoma. Methods: A telephone survey reached 3110 residents older than 30 years (overall response rate of 66.9%) randomly selected from 18 regional communities in Queensland, Australia. Results: Overall, 804 (25.9%) participants reported whole-body SSE within the past 12 months and 1055 (33.9%) within the past three years. Whole-body SSE was associated in multivariate logistic regression analysis with younger age (< 50 years); higher education; having received either a whole-body skin examination, recommendation or instruction on SSE by a primary care physician; giving skin checks a high priority; concern about skin cancer and a personal history of skin cancer. Conclusion: Overall, the prevalence of SSE in the present study is among the highest yet observed in Australia, with about one-third of the adult population reporting whole-body SSE in the past three years. People over 50 years, who are at relatively higher risk for skin cancer, currently perform SSE less frequently than younger people.

Physical and psychological factors predict outcome following whiplash injury

Predictors of outcome following whiplash injury are limited to socio-demographic and symptomatic factors, which are not readily amenable to secondary and tertiary intervention. This prospective study investigated the predictive capacity of early measures of physical and psychological impairment on pain and disability 6 months following whiplash injury. Motor function (ROM; kinaesthetic sense; activity of the superficial neck flexors (EMG) during cranio-cervical flexion), quantitative sensory testing (pressure, thermal pain thresholds, brachial plexus provocation test), sympathetic vasoconstrictor responses and psychological distress (GHQ-28, TSK, IES) were measured in 76 acute whiplash participants. The outcome measure was Neck Disability Index scores at 6 months. Stepwise regression analysis was used to predict the final NDI score. Logistic regression analyses predicted membership to one of the three groups based on final NDI scores (< 8 recovered, 10-28 mild pain and disability, > 30 moderate/severe pain and disability). Higher initial NDI score (1.007-1.12), older age (1.03-1.23), cold hyperalgesia (1.05-1.58), and acute post-traumatic stress (1.03-1.2) predicted membership to the moderate/severe group. Additional variables associated with higher NDI scores at 6 months on stepwise regression analysis were: ROM loss and diminished sympathetic reactivity. Higher initial NDI score (1.03-1.28), greater psychological distress (GHQ-28) (1.04-1.28) and decreased ROM (1.03-1.25) predicted subjects with persistent milder symptoms from those who fully recovered. These results demonstrate that both physical and psychological factors play a role in recovery or non-recovery from whiplash injury. This may assist in the development of more relevant treatment methods for acute whiplash. (c) 2004 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Length of Stay, Discharge Destination, and Functional Improvement: Utility of the Australian National Subacute and Nonacute Patient Casemix Classification

Background and Purpose - Although implemented in 1998, no research has examined how well the Australian National Subacute and Nonacute Patient (AN-SNAP) Casemix Classification predicts length of stay (LOS), discharge destination, and functional improvement in public hospital stroke rehabilitation units in Australia. Methods - 406 consecutive admissions to 3 stroke rehabilitation units in Queensland, Australia were studied. Sociode-mographic, clinical, and functional data were collected. General linear modeling and logistic regression were used to assess the ability of AN-SNAP to predict outcomes. Results - AN-SNAP significantly predicted each outcome. There were clear relationships between the outcomes of longer LOS, poorer functional improvement and discharge into care, and the AN-SNAP classes that reflected poorer functional ability and older age. Other predictors included living situation, acute LOS, comorbidity, and stroke type. Conclusions - AN-SNAP is a consistent predictor of LOS, functional change and discharge destination, and has utility in assisting clinicians to set rehabilitation goals and plan discharge.

Psychosocial and non-psychosocial risk factors for the new diagnosis of diabetes in elderly women

Objectives: Determine psychosocial variables associated with the new diagnosis of diabetes in elderly women. Examine whether variables remained significant predictors after controlling for non-psychosocial risk factors and the frequency of doctor visits. Research design and methods: A longitudinal cohort study was conducted using data from 10 300 women who completed a survey in 1996 and 1999. The women were aged between 70 and 74 years of age in 1996. The were asked to provide self-reports on a number of psychosocial and non-psychosocial variables in 1996 and on whether they had been diagnosed for the first time with diabetes in the 3-year period. The relationships between the potential risk factors and new diagnosis of diabetes were examined using binary logistic regression analysis. Results: Univariate results showed that not having a current partner, having low social support and having a mental health index score in the clinical range were all associated with higher risks of being diagnosed with diabetes for the first time. However the multivariate results showed that only a mental health index score in the clinical range and not having a current partner provided unique prediction of being newly diagnosed with diabetes. Of the non-psychosocial variables measured, only having a high BMI and hypertension were associated with increased risks of new diagnosis, while there was also evidence of a U shaped relationship between alcohol consumption and new diagnosis. Even after adjusting for frequency of doctor visits and non-psychosocial risk factors, a mental health index in the clinical range proved to still be a significant risk factor. Conclusions: A score on the mental health index that is within the clinical range is an independent risk factor for the new diagnosis of diabetes in elderly women. (c) 2006 Elsevier Ireland Ltd. All rights reserved.

Inflammation, complement activation and endothelial function in stable and unstable coronary artery disease

Background: Endothelial dysfunction plays an important role in the pathogenesis of coronary artery disease (CAD). Apart from traditional risk factors complement activation and inflammation may trigger and sustain endothelial dysfunction. We sought to assess the association between endothelial function, high sensitivity C-reactive protein (hs-CRP) and markers of complement activation in patients with either stable or unstable coronary artery disease. Methods: We prospectively recruited 78 patients, 35 patients with stable angina pectoris (SAP) and 43 patients with unstable angina pectoris (UAP). Endothelial function was assessed as brachial artery reactivity (BAR). Hs-CRP, C3a, C5a, and C1-Inhibitor (C1 inh.) were measured enzymatically. Results: Patients with IJAP showed higher median levels of hs-CRP and C3a compared to patients with SAP, while BAR was not significantly different between patient groups. In UAP patients, hs-CRP was significantly correlated with cholesterol (r = 0.27, p < 0.02), C3a (r = 0.32, p < 0.001) and C1 INH.(r = 0.41, p < 0.003), but not with flow mediated dilatation (r = 0.09, P = 0.41). Hs-CRP and C1 INH.were found to be independant predictors of IJAP in a backward stepwise logistic regression model. Conclusions: We conclude that both hs-CRP, a marker of inflammation and C3a, a marker of complement activation are elevated in patients with UAP, but not in patients with SAP. (c) 2005 Elsevier B.V. All rights reserved.

Patient anxiety and experiences associated with an outpatient "one-stop" "see and treat" hysteroscopy clinic

BACKGROUND: "One-stop" outpatient hysteroscopy clinics have become well established for the investigation and treatment of women with abnormal uterine bleeding. However, the advantages of these clinics may be offset by patient factors such as anxiety, pain, and dissatisfaction. This study aimed to establish patients' views and experiences of outpatient service delivery in the context of a one-stop diagnostic and therapeutic hysteroscopy clinic, to determine the amount of anxiety experienced by these women and compare this with other settings, and to determine any predictors for patient preferences. METHODS: The 20-item State-Trait Anxiety Inventory was given to 240 women attending a one-stop hysteroscopy clinic: to 73 consecutive women before their appointment in a general gynecology clinic and to 36 consecutive women attending a chronic pelvic pain clinic. The results were compared with published data for the normal female population, for women awaiting major surgery, and for women awaiting a colposcopy clinic appointment. In addition, a questionnaire designed to ascertain patients' views and experiences was used. Logistic regression analysis was used to delineate the predictive values of diagnostic or therapeutic hysteroscopy, and to determine their effect on the preference of patients to have the procedure performed under general anesthesia in the future. RESULTS: Women attending the hysteroscopy clinic in this study reported significantly higher levels of anxiety than those attending the general gynecology clinic (median, 45 vs 39; p = 0.004), but the levels of anxiety were comparable with those of women attending the chronic pelvic pain clinic (median, 45 vs 46; p = 0.8). As compared with the data from the normal female population (mean, 35.7) and those reported for women awaiting major surgery (mean, 41.2), the levels of anxiety experienced before outpatient hysteroscopy clinic treatment were found to be higher (mean, 45.7). Only women awaiting colposcopy (6-item mean score, 51.1 +/- 13.3) experienced significantly higher anxiety scores than the women awaiting outpatient hysteroscopy (6-item mean score, 47.3 +/- 13.9; p = 0.002). Despite their anxiety, most women are satisfied with the outpatient hysteroscopy "see and treat" service. High levels of anxiety, particularly concerning pain but not operative intervention, were significant predictors of patients desiring a future procedure to be performed under general anesthesia. CONCLUSIONS: Outpatient hysteroscopy is associated with significant anxiety, which increases the likelihood of intolerance for the outpatient procedure. However, among those undergoing operative therapeutic procedures, dissatisfaction was not associated with the outpatient setting.