A Temporally Explicit Production Efficiency Model for Fuel Load Allocation in Southern Africa

Abstract We present a regional fuel load model (1 km² spatial resolution) applied in the southern African savanna region. The model is based on a patch-scale production efficiency model (PEM) scaled up to the regional level using empirical relationships between patch-scale behavior and multi-source remote sensing data (spatio-temporal variability of vegetation and climatic variables). The model requires the spatial distribution of woody vegetation cover, which is used to determine separate respiration rates for tree and grass. Net primary production, grass and tree leaf death, and herbivory are also taken into account in this mechanistic modeling approach. The fuel load model has been calibrated and validated from independent measurements taken from savanna vegetation in Africa southward from the equator. A sensitivity analysis on the effect of climate variables (incoming radiation, air temperature, and precipitation) has been conducted to demonstrate the strong role that water availability has in determining productivity and subsequent fuel load over the southern African region. The model performance has been tested in four different areas representative of a regional increasing rainfall gradient—Etosha National Park, Namibia, Mongu and Kasama, Zambia, as well as in Kruger National Park, South Africa. Within each area, we analyze model output from three different magnitudes of canopy coverage (<5, 30, and 50%). We find that fuel load ranges predicted by the model are globally in agreement with field measurements for the same year. High rainfall sustains green herbaceous production late in the dry season and delays tree leaf litter production. Effect of water on production varies across the rainfall gradient with delayed start of green material production in more arid regions.     

Function and genetics of long versus short copulations in the cactophilic fruit fly,drosophila mojavensis (diptera: drosophilidae)

Variation in copulation duration of Drosophila mojavensisstrains was influenced by both sexes. Males maintained predominant control, as copulation duration of pairs from different strains was more similar to that of the strain from which the male was derived, but female origin also contributed significantly to the duration of copulation. Variation among strains was controlled by genes acting additively in both sexes. The size of both males and females also affected copulation duration. Small males copulated longer on average than large males, while males paired with large females copulated longer than those paired with small females. The importance of copulation duration to fitness was tested by correlation analyses with male size, female size, female remating latency, and number of eggs laid prior to female remating. Longer copulations stimulated earlier oviposition, possibly by increasing accessory gland secretions that are passed by males during copulation.     

Body size and area‐incidence relationships: is there a general pattern?

Aim This paper tests firstly for the existence of a general relationship between body size of terrestrial animals and their incidence across habitat patches of increasing size, and secondly for differences in this relationship between insects and vertebrates. Location The analysis was based on the occupancy pattern of 50 species from 15 different landscapes in a variety of ecosystems ranging from Central European grassland to Asian tropical forest. Methods The area‐occupancy relationship was described by incidence functions that were calculated using logistic regression. A correlation analysis between body size of the species and the patch area referring to the two given points of the incidence function was performed. In order to test for an effect of taxon (insects vs. vertebrates), an analysis of covariance was conducted. Results In all species, the incidence was found to increase with increasing patch area. The macroecological analysis showed a significant relationship between the incidence in habitat patches and the body size of terrestrial animals. The area requirement was found to increase linearly with increasing body size on a log‐log scale. This relationship did not differ significantly between insects and vertebrates. Conclusions The approach highlighted in this paper is to associate incidence functions with body size. The results suggest that body size is a general but rather rough predictor for the area requirements of animals. The relationship seems valid for a wide range of body sizes of terrestrial animals. However, further studies including isolation of habitats as well as additional species traits into the macroecological analysis of incidence functions are needed.     

Lower Neighborhood Socioeconomic Status Associated with Reduced Diversity of the Colonic Microbiota in Healthy Adults

In the United States, there are persistent and widening socioeconomic gaps in morbidity and mortality from chronic diseases. Although most disparities research focuses on person-level socioeconomic-status, mounting evidence suggest that chronic diseases also pattern by the demographic characteristics of neighborhoods. Yet the biological mechanisms underlying these associations are poorly understood. There is increasing recognition that chronic diseases share common pathogenic features, some of which involve alterations in the composition, diversity, and functioning of the gut microbiota. This study examined whether socioeconomic-status was associated with alpha-diversity of the colonic microbiota. Forty-four healthy adults underwent un-prepped sigmoidoscopy, during which mucosal biopsies and fecal samples were collected. Subjects’ zip codes were geocoded, and census data was used to form a composite indicator of neighborhood socioeconomic-status, reflecting household income, educational attainment, employment status, and home value. In unadjusted analyses, neighborhood socioeconomic-status explained 12–18 percent of the variability in alpha-diversity of colonic microbiota. The direction of these associations was positive, meaning that as neighborhood socioeconomic-status increased, so did alpha-diversity of both the colonic sigmoid mucosa and fecal microbiota. The strength of these associations persisted when models were expanded to include covariates reflecting potential demographic (age, gender, race/ethnicity) and lifestyle (adiposity, alcohol use, smoking) confounds. In these models neighborhood socioeconomic-status continued to explain 11–22 percent of the variability in diversity indicators. Further analyses suggested these patterns reflected socioeconomic variations in evenness, but not richness, of microbial communities residing in the sigmoid. We also found indications that residence in neighborhoods of higher socioeconomic-status was associated with a greater abundance of Bacteroides and a lower abundance of Prevotella, suggesting that diet potentially underlies differences in microbiota composition. These findings suggest the presence of socioeconomic variations in colonic microbiota diversity. Future research should explore whether these variations contribute to disparities in chronic disease outcomes.     

Automated extraction of bank angles from bird‐borne video footage using open‐source software

The use of miniaturized video cameras to study the at‐sea behavior of flying seabirds has increased in recent years. These cameras allow researchers to record several behaviors that were not previously possible to observe. However, video recorders produce large amounts of data and videos can often be time‐consuming to analyze. We present a new technique using open‐source software to extract bank angles from bird‐borne video footage. Bank angle is a key facet of dynamic soaring, which allows albatrosses and petrels to efficiently search vast areas of ocean for food. Miniaturized video cameras were deployed on 28 Wandering Albatrosses (Diomedea exulans) on Marion Island (one of the two Prince Edward Islands) from 2016 to 2018. The OpenCV library for the Python programming language was used to extract the angle of the horizon relative to the bird’s body (= bank angle) from footage when the birds were flying using a series of steps focused on edge detection. The extracted angles were not significantly different from angles measured manually by three independent observers, thus being a valid method to measure bank angles. Image quality, high wind speeds, and sunlight all influenced the accuracy of angle estimates, but post‐processing eliminated most of these errors. Birds flew most often with cross‐winds (58%) and tailwinds (39%), resulting in skewed distributions of bank angles when birds turned into the wind more often. Higher wind speeds resulted in extreme bank angles (maximum observed was 94°). We present a novel method for measuring postural data from seabirds that can be used to describe the fine‐scale movements of the dynamic‐soaring cycle. Birds appeared to alter their bank angle in response to varying wind conditions to counter wind drift associated with the prevailing westerly winds in the Southern Ocean. These data, in combination with fine‐scale positional data, may lead to new insights into dynamic‐soaring flight.