Artificial nest predation rates vary depending on visibility in the eastern Brazilian Amazon

Observational and experimental studies have shown that increased concealment of bird nests reduces nest predation rates. The objective of the present study was to evaluate differences in predation rates between two experimental manipulations of artificial ground nests (i.e., clearing an area around the artificial nest or leaving it as natural as possible), and test whether environmental variables also affected nest predation in an undisturbed area of Amazonian forest in eastern Brazil. A generalized linear model was used to examine the influence of five variables (manipulation type, perpendicular distance from the main trail, total basal area of trees surrounding the nest site, understorey density, and liana quantity) on nest predation rates. Model results, showed that manipulation type was the only variable that significantly affected nest predation rates. Thus, to avoid systematic biases, the influence of nest site manipulation must be taken into consideration when conducting experiments with artificial nests.

Acute myocardial infarction: clinical and epidemiological profile and factors associated with in-hospital death in the municipality of Rio de Janeiro

OBJECTIVE: To study the factors associated with the risk of in-hospital death in acute myocardial infarction in the Brazilian public health system in Rio de Janeiro, Brazil. METHODS: Sectional study of a sample with 391 randomly drawn medical records of the hospitalizations due to acute myocardial infarction recorded in the hospital information system in 1997. RESULTS: The diagnosis was confirmed in 91.7% of the cases; 61.5% males; age = 60.2 ± 2.4 years; delta time until hospitalization of 11 hours; 25.3% were diabetic; 58.1% were hypertensive; 82.6% were in Killip I class. In-hospital mortality was 20.6%. Thrombolysis was used in 19.5%; acetylsalicylic acid (ASA) 86.5%; beta-blockers 49%; angiotensin-converting enzyme (ACE) inhibitors 63.3%; calcium channel blockers 30.5%. Factors associated with increased death: age (61-80 years: OR=2.5; > 80 years: OR=9.6); Killip class (II: OR=1.9; III: OR=6; IV: OR=26.5); diabetes (OR=2.4); ventricular tachycardia (OR=8.5); ventricular fibrillation (OR=34); recurrent ischemia (OR=2.7). The use of ASA (OR=0.3), beta-blockers (OR=0.3), and ACE inhibitors (OR=0.4) was associated with a reduction in the chance of death. CONCLUSION: General lethality was high and some interventions of confirmed efficacy were underutilizated. The logistic model showed the beneficial effect of beta-blockers, and ACE inhibitors on the risk of in-hospital death.

Ireland’s understudied flatfish: reproduction, age and growth of the dab Limanda limanda (L.) in Irish coastal waters

In Ireland, although flatfish form a valuable fishery, little is known about the smallest, the dab Limanda limanda. In this study, a variety of parameters of reproductive development, including ovarian phase description, gonadosomatic index (GSI), hepatosomatic index (HSI), relative condition (Kn) and oocyte size were analysed to provide information on the dab’s reproductive cycle and spawning periods. Sampling were collected monthly over an 18-month period using bottom trawls of the Irish coastline. A six phase macroscopic guide was developed for both sexes of dab, and verified using histology. In comparisons of macroscopic and microscopic phases, there was high agreement in the proposed female guide (86%), with males demonstratively lower (62%). No significant bias was observed between the the two reproductive methods. When the male macroscopic guide was examined, misclassification was high in phase 5 and phase 5 (41%), with 96% of misclassification occurring in adjacent phases. The sampled population was primarily composed of females, with ratios of females to males 1:0.6, although the predominance of females was less noticeable during the reproductive season. Oocyte growth in dab follows asynchronous development, and spawn over a protracted period indicating a batch spawning strategy. Spawning occurred mainly in early spring, with total regeneration of gonads by May. The length at which 50% of the population was reproductively mature was identified as 14cm and 17cm, for male and female dab, respectively. Precision and bias in age determinations using whole otoliths to age dab was investigated using six age readers from various institutions. Low levels of precision were obtained (CV: 10-23%) inferring the need for an alternative methodology. Precision and bias was influence by the level of experience of the reader, with ageing error attributed to interpretative differences and difficulty in edge determination. Sectioned otolith age determinations were subsequently compared to whole otolith age determinations using two age readers experienced in dab ageing. Although increased precision was observed in whole otoliths from previous estimates (CV=0%, 0% APE), sectioned otoliths were used for growth models. This was based on multinominal logistic regression on age length keys developed using both ageing methods. Biological data (length and age) for both sexes was applied to four growth models, where the Akaike criterion and Multi model Inference indicated the logistic model as having the best fit to the collected data. In general, female dab attained a longer length then males, with growth rates significantly different between the two sexes. Length weight relationships between the two sexes were also significantly different.

The ghost of past species occurrence: improving species distribution models for presence-only data

1. Model-based approaches have been used increasingly in conservation biology over recent years. Species presence data used for predictive species distribution modelling are abundant in natural history collections, whereas reliable absence data are sparse, most notably for vagrant species such as butterflies and snakes. As predictive methods such as generalized linear models (GLM) require absence data, various strategies have been proposed to select pseudo-absence data. However, only a few studies exist that compare different approaches to generating these pseudo-absence data. 2. Natural history collection data are usually available for long periods of time (decades or even centuries), thus allowing historical considerations. However, this historical dimension has rarely been assessed in studies of species distribution, although there is great potential for understanding current patterns, i.e. the past is the key to the present. 3. We used GLM to model the distributions of three 'target' butterfly species, Melitaea didyma, Coenonympha tullia and Maculinea teleius, in Switzerland. We developed and compared four strategies for defining pools of pseudo-absence data and applied them to natural history collection data from the last 10, 30 and 100 years. Pools included: (i) sites without target species records; (ii) sites where butterfly species other than the target species were present; (iii) sites without butterfly species but with habitat characteristics similar to those required by the target species; and (iv) a combination of the second and third strategies. Models were evaluated and compared by the total deviance explained, the maximized Kappa and the area under the curve (AUC). 4. Among the four strategies, model performance was best for strategy 3. Contrary to expectations, strategy 2 resulted in even lower model performance compared with models with pseudo-absence data simulated totally at random (strategy 1). 5. Independent of the strategy model, performance was enhanced when sites with historical species presence data were not considered as pseudo-absence data. Therefore, the combination of strategy 3 with species records from the last 100 years achieved the highest model performance. 6. Synthesis and applications. The protection of suitable habitat for species survival or reintroduction in rapidly changing landscapes is a high priority among conservationists. Model-based approaches offer planning authorities the possibility of delimiting priority areas for species detection or habitat protection. The performance of these models can be enhanced by fitting them with pseudo-absence data relying on large archives of natural history collection species presence data rather than using randomly sampled pseudo-absence data.

History matters: relating paths and rates of landscape change to butterfly species decline

Western European landscapes have drastically changed since the 1950s, with agricultural intensifications and the spread of urban settlements considered the most important drivers of this land-use/land-cover change. Losses of habitat for fauna and flora have been a direct consequence of this development. In the present study, we relate butterfly occurrence to land-use/land-cover changes over five decades between 1951 and 2000. The study area covers the entire Swiss territory. The 10 explanatory variables originate from agricultural statistics and censuses. Both state as well as rate was used as explanatory variables. Species distribution data were obtained from natural history collections. We selected eight butterfly species: four species occur on wetlands and four occur on dry grasslands. We used cluster analysis to track land-use/land-cover changes and to group communes based on similar trajectories of change. Generalized linear models were applied to identify factors that were significantly correlated with the persistence or disappearance of butterfly species. Results showed that decreasing agricultural areas and densities of farms with more than 10 ha of cultivated land are significantly related with wetland species decline, and increasing densities of livestock seem to have favored disappearance of dry grassland species. Moreover, we show that species declines are not only dependent on land-use/land-cover states but also on the rates of change; that is, the higher the transformation rate from small to large farms, the higher the loss of dry grassland species. We suggest that more attention should be paid to the rates of landscape change as feasible drivers of species change and derive some management suggestions.

A dynamic assessment of medication-taking behavior during pregnancy and postpartum: should cART adherence be reinforced during postpartum?

This study compared adherence (persistence and execution) during pregnancy and postpartum in HIV-positive women having taken part in the adherence-enhancing program of the Community Pharmacy of the Department of Ambulatory Care and Community Medicine in Lausanne between 2004 and 2012. This interdisciplinary program combined electronic drug monitoring and semi-structured, repeated motivational interviews. This was a retrospective, observational study. Observation period spread over from first adherence visit after last menstruation until 6 months after childbirth. Medication-taking was recorded by electronic drug monitoring. Socio-demographic and delivery data were collected from Swiss HIV Cohort database. Adherence data, barriers and facilitators were collected from pharmacy database. Electronic data were reconciled with pill-count and interview notes in order to include reported pocket-doses. Execution was analyzed over 3-day periods by a mixed effect logistic model, separating time before and after childbirth. This model allowed us to estimate different time slopes for both periods and to show a sudden fall associated with childbirth. Twenty-five pregnant women were included. Median age was 29 (IQR: 26.5, 32.0), women were in majority black (n_17,68%) and took a cART combining protease and nucleoside reverse transcriptase inhibitors (n_24,96%). Eleven women (44%) were ART-naı¨ve at the beginning of pregnancy. Twenty women (80%) were included in the program because of pregnancy. Women were included at all stages of pregnancy. Six women (24%) stopped the program during pregnancy, 3 (12%) at delivery, 4 (16%) during postpartum and 12 (48%) stayed in program at the end of observation time. Median number of visits was 4 (3.0, 6.3) during pregnancy and 3 (0.8, 6.0) during postpartum. Execution was continuously high during pregnancy, low at beginning of postpartum and increased gradually during the 6 months of postpartum. Major barriers to adherence were medication adverse events and difficulties in daily routine. Facilitators were motivation for promoting child-health and social support. The dramatic drop and very slow increase in cART adherence during postpartum might result in viral rebound and drug resistance. Although much attention is devoted to pregnant women, interdisciplinary care should also be provided to women in the community during first trimester of postpartum to support them in sustaining cART adherence.

Quantitative genetic modeling and inference in the presence of nonignorable missing data.

Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

Organizational resources and intrapreneurial activities: a cross-country study

The importance of entrepreneurship for social and economic growth is generally accepted. In addition, intrapreneurship or corporate entrepreneurship is recognized as one of the key elements for organizational development. In this context, corporate culture and, specifically, entrepreneurial competences are considered to be catalysts for intrapreneurship. The main purpose of this paper is to analyse the influence of resources and capabilities on the probability of becoming an intrapreneur. Using data obtained from the Global Entrepreneurship Monitor (GEM) for 39 countries, and a logistic model, the study shows that entrepreneurial resources and capabilities, such as previous entrepreneurial experience, entrepreneurial competences and the ability to detect business opportunities, influence intrapreneurial behaviour. The contributions of this research are both conceptual (advancing corporate entrepreneurship theory) and practical (relating to the design of policies to foster intrapreneurial activities).

Population density and offspring size in the cladoceran Simocephalus vetulus (Müller)

r/K theory classically predicts that offspring size should increase under density-dependent selection. However, this is questionable, being based on implicit rather than explicit assumption (the logistic model does not include offsring size as a parameter). From recent models of optimal offspring size (Sibly & Calow, 1983; Taylor & Williams, 1984) it can be shown that density should select for larger offspring if density-dependence in the per capita rate of increase is mainly due to a reduction of the juvenile growth rate or survivorship. In contrast, density should select for smaller offspring if such density-dependence is mainly due to a reduction of adult fecundity or survivorship. Therfore, the outcome of selection cannot be predicted without precise knowledge of the density-dependence of age-specific reproduction and mortality rates. To test the above models, genetically identical individuals of Simocephalus vetulus (Müller) were reared in a density gradient; density-dependence in the per capita rate of increase was shown to be mainly due to a reduction of the juvenile growth rate, thereby selecting for larger offspring; offspring size at birth appeared to be phenotypically plastic and to increase with density. Models were therefore qualitatively supported. However, a discrepancy occurred in quantitative predictions; offspring were produced larger than predicted. Field and laboratory studies are suggested to address this.

Neocortical maturation during adolescence: change in neuronal soma dimension.

During adolescence, cognitive abilities increase robustly. To search for possible related structural alterations of the cerebral cortex, we measured neuronal soma dimension (NSD = width times height), cortical thickness and neuronal densities in different types of neocortex in post-mortem brains of five 12-16 and five 17-24 year-olds (each 2F, 3M). Using a generalized mixed model analysis, mean normalized NSD comparing the age groups shows layer-specific change for layer 2 (p < .0001) and age-related differences between categorized type of cortex: primary/primary association cortex (BA 1, 3, 4, and 44) shows a generalized increase; higher-order regions (BA 9, 21, 39, and 45) also show increase in layers 2 and 5 but decrease in layers 3, 4, and 6 while limbic/orbital cortex (BA 23, 24, and 47) undergoes minor decrease (BA 1, 3, 4, and 44 vs. BA 9, 21, 39, and 45: p = .036 and BA 1, 3, 4, and 44 vs. BA 23, 24, and 47: p = .004). These data imply the operation of cortical layer- and type-specific processes of growth and regression adding new evidence that the human brain matures during adolescence not only functionally but also structurally.

Estandarización de la captura por unidad de esfuerzo (CPUE) de la flota industrial de cerco del stock norte-centro de la anchoveta peruana (Engraulis ringens Jenyns)

Se trabajó utilizando una metodología basada en Modelos Lineales Generalizados (MLG). La CPUE fue expresada en toneladas por duración de viaje. Las variables explicativas utilizadas fueron el año, mes, capacidad de bodega, latitud, inercia espacial y distancia a la costa. El modelo tuvo un coeficiente de determinación de 0,485, explicando casi la mitad de la variabilidad de la CPUE observada. La variable con mayor influencia en el modelo fue la capacidad de bodega (49% de la varianza explicada), debido posiblemente a que la flota anchovetera posee una capacidad elevada de captura y que los recursos pelágicos tienden a hiper-agregarse, incluso cuando están siendo fuertemente explotados. La correlación entre la CPUE estandarizada y biomasa estimada por un modelo de captura a la edad (r=0,74) indica que el método basado en MLG es recomendable para la estandarización de la CPUE. Se propone a esta CPUE como una alternativa para monitorear la biomasa de la anchoveta.

Which is the optimal sampling strategy for habitat suitability modelling

Designing an efficient sampling strategy is of crucial importance for habitat suitability modelling. This paper compares four such strategies, namely, 'random', 'regular', 'proportional-stratified' and 'equal -stratified'- to investigate (1) how they affect prediction accuracy and (2) how sensitive they are to sample size. In order to compare them, a virtual species approach (Ecol. Model. 145 (2001) 111) in a real landscape, based on reliable data, was chosen. The distribution of the virtual species was sampled 300 times using each of the four strategies in four sample sizes. The sampled data were then fed into a GLM to make two types of prediction: (1) habitat suitability and (2) presence/ absence. Comparing the predictions to the known distribution of the virtual species allows model accuracy to be assessed. Habitat suitability predictions were assessed by Pearson's correlation coefficient and presence/absence predictions by Cohen's K agreement coefficient. The results show the 'regular' and 'equal-stratified' sampling strategies to be the most accurate and most robust. We propose the following characteristics to improve sample design: (1) increase sample size, (2) prefer systematic to random sampling and (3) include environmental information in the design'

Relaciones ontogénicas y espacio-temporales en la dieta del calamar gigante (Dosidicus gigas) en Perú, utilizando un Modelo Aditivo Generalizado

El calamar gigante Dosidicus gigas (d'Orbigny, 1835) es un depredador importante en el ecosistema del Perú. Se postula que el papel del calamar gigante varía teniendo en cuenta la talla, tiempo, hora, temperatura y distribución espacial. Para comprobar esta hipótesis se aplicó un modelo aditivo generalizado (GAM) en datos biológicos de alimentación de 4178 calamares gigantes capturados por la flota industrial pesquera a lo largo del litoral peruano (3ºS a 18ºS) desde 2 a 299 millas náuticas (mn) de distancia a la costa desde el año 2004 a 2009 realizados por el Laboratorio de Ecología Trófica del Instituto del Mar del Perú (IMARPE). La talla de los calamares estudiados fluctuó entre 14 y 112 cm de longitud de manto (LM). En total 43 item-presa fueron registrados, los grupos más importantes fueron los cefalópodos (Dosidicus gigas), Teleosteii (Photichthyidae, Myctophidae y Nomeidae) y Malacostraca crustáceos (Euphausiidae). Las presas principales fueron D. gigas (indicando canibalismo) en términos gravimétricos (% W=35.4), los otros cephalopodos en frecuencia de ocurrencia (FO=14.4), y los eufáusidos en términos de abundancia relativa (% N=62.2). Estos resultados reflejan una alta variabilidad de la dieta, y un espectro trófico similar en comparación con otras latitudes en ambos hemisferios (México y Chile). Los modelos GAM muestran que todas las variables predictoras fueron significativas en relación a la variable respuesta llenura estomacal (p <0.0001). La llenura estomacal fue mayor en los individuos juveniles, también durante la noche hubo mayor consumo, mientras no se reflejaron tendencias en la alimentación con relación a la temperatura superficial del mar (TSM), pero espacialmente se observan cambios en la dieta, aumentando el porcentaje de llenura a medida que esta especie se aleja de la costa. Por lo tanto se concluye que la dieta del calamar gigante depende de la talla y su distribución espacio-temporal.

Diagnostic value of vestibulo-ocular reflex parameters in the detection and characterization of labyrinthine lesions.

OBJECTIVE: To evaluate the power of various parameters of the vestibulo-ocular reflex (VOR) in detecting unilateral peripheral vestibular dysfunction and in characterizing certain inner ear pathologies. STUDY DESIGN: Prospective study of consecutive ambulatory patients presenting with acute onset of peripheral vertigo and spontaneous nystagmus. SETTING: Tertiary referral center. PATIENTS: Seventy-four patients (40 females, 34 males) and 22 normal subjects (11 females, 11 males) were included in the study. Patients were classified in three main diagnoses: vestibular neuritis: 40; viral labyrinthitis: 22; Meniere's disease: 12. METHODS: The VOR function was evaluated by standard caloric and impulse rotary tests (velocity step). A mathematical model of vestibular function was used to characterize the VOR response to rotational stimulation. The diagnostic value of the different VOR parameters was assessed by uni- and multivariable logistic regression. RESULTS: In univariable analysis, caloric asymmetry emerged as the most powerful VOR parameter in identifying unilateral vestibular deficit, with a boundary limit set at 20%. In multivariable analysis, the combination of caloric asymmetry and rotational time constant asymmetry significantly improved the discriminatory power over caloric alone (p&lt;0.0001) and produced a detection score with a correct classification of 92.4%. In discriminating labyrinthine diseases, different combinations of the VOR parameters were obtained for each diagnosis (p&lt;0.003) supporting that the VOR characteristics differ between the three inner ear disorders. However, the clinical usefulness of these characteristics in separating the pathologies was limited. CONCLUSION: We propose a powerful logistic model combining the indices of caloric and time constant asymmetries to detect a peripheral vestibular loss, with an accuracy of 92.4%. Based on vestibular data only, the discrimination between the different inner ear diseases is statistically possible, which supports different pathophysiologic changes in labyrinthine pathologies.

Population density and optimal body size.

The population density of an organism is one of the main aspects of its environment, and shoud therefore strongly influence its adaptive strategy. The r/K theory, based on the logistic model, was developed to formalize this influence. K-selectioon is classically thought to favour large body sizes. This prediction, however, cannot be directly derived from the logistic model: some auxiliary hypotheses are therefor implicit. These are to be made explicit if the theory is to be tested. An alternative approach, based on the Euler-Lotka equation, shows that density itself is irrelevant, but that the relative effect of density on adult and juvenile features is crucial. For instance, increasing population will select for a smaller body size if the density affects mainly juvenile growth and/or survival. In this case, density shoud indeed favour large body sizes. The theory appears nevertheless inconsistent, since a probable consequence of increasing body size will be a decrease in the carrying capacity