Diet–demography relationships in a long‐lived predator: from territories to populations

Understanding the mechanisms that shape animal population dynamics is of fundamental interest in ecology, evolution and conservation biology. Food supply is an important limiting factor in most animal populations and may have demographic consequences. Optimal foraging theory predicts greater consumption of preferred prey and less diet diversity when food is abundant, which may benefit key fitness parameters such as productivity and survival. Nevertheless, the correspondence between individual resource use and demographic processes in populations of avian predators inhabiting large geographic areas remains largely unexplored, particularly in complex ecosystems such as those of the Mediterranean basin. Based on a long‐term monitoring program of the diet and demography of Bonelli's eagle Aquila fasciata in western Europe, here we test the hypothesis that a predator's diet is correlated to its breeding productivity and survival at both the territorial and population levels, and ultimately to its population growth rate. At the territorial level, we found that productivity increased with greater consumption of European rabbits Oryctolagus cuniculus, the Bonelli's eagle's preferred prey, and pigeons, an important alternative prey for this predator. The survival of territorial pairs was negatively affected by higher diet diversity, which probably reflected the inability to find sufficient high quality prey. Diet effects at the population level were similar but more noticeable than at the territorial level, i.e. a greater consumption of rabbits, together with lesser consumption of small‐to‐medium avian species (‘other birds’; non‐preferred prey), increased productivity, while greater diet diversity and lower consumption of rabbits was associated with reduced survival and population growth rate. Overall, our study illustrates how the diet of a predator species can be closely related to key individual vital rates, which, in turn, leave a measurable fingerprint on population dynamics within and among populations across large spatial scales.     

Yeast GPCR signaling reflects the fraction of occupied receptors,not the number

According to receptor theory, the effect of a ligand depends on the amount of agonist–receptor complex. Therefore, changes in receptor abundance should have quantitative effects. However, the response to pheromone in Saccharomyces cerevisiae is robust (unaltered) to increases or reductions in the abundance of the G‐protein‐coupled receptor (GPCR), Ste2, responding instead to the fraction of occupied receptor. We found experimentally that this robustness originates during G‐protein activation. We developed a complete mathematical model of this step, which suggested the ability to compute fractional occupancy depends on the physical interaction between the inhibitory regulator of G‐protein signaling (RGS), Sst2, and the receptor. Accordingly, replacing Sst2 by the heterologous hsRGS4, incapable of interacting with the receptor, abolished robustness. Conversely, forcing hsRGS4:Ste2 interaction restored robustness. Taken together with other results of our work, we conclude that this GPCR pathway computes fractional occupancy because ligand‐bound GPCR–RGS complexes stimulate signaling while unoccupied complexes actively inhibit it. In eukaryotes, many RGSs bind to specific GPCRs, suggesting these complexes with opposing activities also detect fraction occupancy by a ratiometric measurement. Such complexes operate as push‐pull devices, which we have recently described.     

Mercury in mercury(II)-spiked soils is highly susceptible to plant bioaccumulation

Heavy metal phytotoxicity assessments usually use soluble metal compounds in spiked soils to evaluate metal bioaccumulation, growth inhibition and adverse effects on physiological parameters. However, exampling mercury phytotoxicity for barley (Hordeum vulgare) this paper highlights unsuitability of this experimental approach. Mercury(II) in spiked soils is extremely bioavailable, and there experimentally determined bioaccumulation is significantly higher compared to reported mercury bioaccumulation efficiency from soils collected from mercury-polluted areas. Our results indicate this is not affected by soil sorption capacity, thus soil ageing and formation of more stable mercuric complexes with soil fractions is necessary for reasonable metal phytotoxicity assessments.     

Effects of Bark Beetle Disturbance on Soil Nutrient Retention and Lake Chemistry in Glacial Catchment

Ecosystems - Forest ecosystems worldwide are subjected to human-induced stressors, including eutrophication and acidification, and to natural disturbances (for example, insect infestation,...     

In vitro penetration assay of boar sperm fertility: effect of various factors on the penetrability of immature pig oocytes

The present study was designed 1) to examine the influence of cumulus cells, ovary storage time and oocyte size on the penetrability of immature pig oocytes, and 2) to investigate the effect of 2 methods of treating the semen from different boars on the inter-assay variability of homologous in vitro penetration tests of boar sperm fertility. In Experiment 1, cumulus oocyte complexes, oocytes with spontaneous loss of the cumulus cells during collection, and oocytes mechanically stripped of cumulus cells were used. No differences were observed in oocyte penetrability among the 3 types of oocyte, although mechanical removal of the cumulus caused an increase (P < 0.005) in the degeneration rate compared with the other oocyte types. In Experiment 2, the oocytes were recovered from ovaries kept in PBS (30 degrees C) for 2, 4 or 6 h after slaughter of prepuberal gilts. Ovary storage did not modify the penetrability of oocytes but increased (P < 0.02) their degeneration rates. In Experiment 3, the diameters of fresh oocytes were determined after co-incubation with spermatozoa. They were classified into 4 groups according to diameter: A) < 105 microm, B) 105-115 microm, C) 116-120 microm and D) > 120 microm. Oocytes from Groups C and D exhibited higher (P < 0.05) penetrability than oocytes from the other groups. In Experiment 4, stored, diluted spermatozoa from 4 boars were pretreated by centrifugation at 50 x g for 3 min and subsequent concentration of the supernatants at 1,200 x g for 3 min. The pellets were treated (washed twice and preincubated for 40 minutes) before co-incubation with immature oocytes or used directly as untreated samples (unwashed and non-preincubated). A boar effect (P < 0.001) was evident for the parameters of in vitro penetration, independently of sperm treatment. When the oocytes were inseminated with untreated spermatozoa, the effects of the replicate and the boar-by-replicate interaction on the variability in oocyte penetrability were not significant. The results of this study indicate that the use of standardized immature pig oocytes and stored untreated, diluted spermatozoa can provide a useful method for optimizing the homologous in vitro penetration (hIVP) assay of boar fertility.     

Developing optimal prediction models for cancer classification using gene expression data

Microarrays can provide genome-wide expression patterns for various cancers, especially for tumor sub-types that may exhibit substantially different patient prognosis. Using such gene expression data, several approaches have been proposed to classify tumor sub-types accurately. These classification methods are not robust, and often dependent on a particular training sample for modelling, which raises issues in utilizing these methods to administer proper treatment for a future patient. We propose to construct an optimal, robust prediction model for classifying cancer sub-types using gene expression data. Our model is constructed in a step-wise fashion implementing cross-validated quadratic discriminant analysis. At each step, all identified models are validated by an independent sample of patients to develop a robust model for future data. We apply the proposed methods to two microarray data sets of cancer: the acute leukemia data by Golub et al. and the colon cancer data by Alon et al. We have found that the dimensionality of our optimal prediction models is relatively small for these cases and that our prediction models with one or two gene factors outperforms or has competing performance, especially for independent samples, to other methods based on 50 or more predictive gene factors. The methodology is implemented and developed by the procedures in R and Splus. The source code can be obtained at http://hesweb1.med.virginia.edu/bioinformatics.     

Bioremediation of PAH-contaminated soil by composting: A case study

Composting technique was used for bioremediation of industrial soil originating from a former tar-contaminated site. The composting process was regulated by aeration to keep optimal temperature gradient and concentrations of O₂ and CO₂ inside the composting pile. The efficiency of bioremediation was evaluated by performing analysis of 11 individual three- to six-ring unsubstituted aromatic hydrocarbons (PAH) and estimating of changes in ecotoxicity of the contaminated soil. After 42 d of composting, PAH with 3–4 rings were removed from 42 to 68%, other higher-molar mass PAH from 35 to 57%. Additional 100 d of compost maturation in open-air field did not result in a further decrease of PAH. Ecotoxicity tests performed with bioluminescent bacteriaVibrio fischerii showed a decrease in toxicity both after composting and maturation phases. However, toxicity tests on mustard-seed germination did not reveal any significant changes during composting and maturation phases.