Home range dynamics and movement are central to a species' ecology and strongly mediate both intra‐ and interspecific interactions. Numerous methods have been introduced to describe animal home ranges, but most lack predictive ability and cannot capture the effects of dynamic environmental patterns, such as the impacts of air and water flow on movement. Here, we develop a practical, multi‐stage approach for statistical inference into the behavioural mechanisms underlying how habitat and dynamic energy landscapes—in this case how airflow increases or decreases the energetic efficiency of flight—shape animal home ranges based around central places. We validated the new approach using simulations, then applied it to a sample of 12 adult golden eagles Aquila chrysaetos tracked with satellite telemetry. The application to golden eagles revealed the effects of habitat variables that align with predicted behavioural ecology. Further, we found that males and females partition their home ranges dynamically based on uplift. Specifically, changes in wind and sun angle drove differential space use between sexes, especially later in the breeding season when energetic demands of growing nestlings require both parents to forage more widely. This method is easily implemented using widely available programming languages and is based on a hierarchical multistate Ornstein–Uhlenbeck space use process that incorporates habitat and energy landscapes. The underlying mathematical properties of the model allow straightforward computation of predicted utilization distributions, permitting estimation of home range size and visualization of space use patterns under varying conditions.

Uniformly most powerful Bayesian tests (UMPBTs) are a new class of Bayesian tests in which null hypotheses are rejected if their Bayes factor exceeds a specified threshold. The alternative hypotheses in UMPBTs are defined to maximize the probability that the null hypothesis is rejected. Here, we generalize the notion of UMPBTs by restricting the class of alternative hypotheses over which this maximization is performed, resulting in restricted most powerful Bayesian tests (RMPBTs). We then derive RMPBTs for linear models by restricting alternative hypotheses to g priors. For linear models, the rejection regions of RMPBTs coincide with those of usual frequentist F -tests, provided that the evidence thresholds for the RMPBTs are appropriately matched to the size of the classical tests. This correspondence supplies default Bayes factors for many common tests of linear hypotheses. We illustrate the use of RMPBTs for ANOVA tests and t-tests and compare their performance in numerical studies.With this notation, Johnson (2013a) defined a uniformly most powerful Bayesian test for evidence threshold ı [UMPBT(ı)] against a fixed null hypothesis H 0 to be the hypothesis test in Scand J Statist 43 RMPBTs for linear models 1163 favor of an alternative hypothesis H 1 that maximized the probability that its Bayes factor in favor of H 1 exceeded its evidence threshold ı. That is, the UMPBT(ı) test satisfies P Ât OEBF 10 .y/ > ı P Ât OEBF 20 .y/ > ı;for all possible values of  t and all alternative hypotheses H 2 . An important property of UMPBTs is that the rejection regions for these tests (i.e. the values of y for which BF 10 > ı) can often be made to coincide with the rejection regions for classical UMPTs by choosing ı to match the size of the classical test. Unfortunately, UMPBTs exist in a relatively limited number of testing scenarios (e.g. one parameter exponential families), and in particular they cannot be defined for tests of parameters in the normal general linear model when variance parameters are not known a priori. This is because the alternative hypothesis that maximizes the probability that the resulting Bayes factor exceeds a given threshold depends on the unknown variance parameter, so that different UMPBTs are obtained for different values of the variance parameters. Thus, a unique UMPBT cannot be defined for all data-generating parameters. To remedy this situation, we define an extension of UMPBTs that we call restricted most powerful Bayesian tests. The extension is obtained by restricting the class of prior densities on  that define the hypotheses to a parametric class, say . j /.

The present study sought novel changes to the hamster testicular transcriptome during modulation of fertility by well-characterized photoperiodic stimuli. Transition from long days (LD, 14 h light/day) to short days (SD, 10 h light/day) triggered testicular regression (61% reduction of testis weight, relative to LD) in SD-sensitive (SD-S) hamsters within 16 weeks. After 22 weeks of SD exposure, a third cohort of hamsters became SD-refractory (SD-R), and exhibited testicular recrudescence (137% testis weight gain, relative to SD-S). Partial interrogation of the testicular transcriptome by annealing-control-primer-modified differential display PCR provided several candidates for regulation of testicular functions. Multiple linear regression modeling indicated the best correlation for aquaporin 11 (Aqp11) with changes in testis weight. Correlations were also strongest for Aqp11 with expression levels of reference cDNAs that control spermatogenesis (Hspa2 and Tnp2), steroidogenesis (Cox2, 3βHsd, and Srebp2), sperm motility (Catsper1, Pgk2, and Tnp2), inflammation (Cox2), and apoptosis (Bax and Bcl2). Moreover, siRNA-mediated knockdown of testicular Aqp11 mRNA and protein reduced Hspa2 and Tnp2 mRNA levels, and it increased 3βHsd mRNA levels. It also reduced mRNA levels for Sept12, which is a testis-specific inducer of spermatogenesis. These results suggest a central role for testicular Aqp11 signaling in the coordinate regulation of crucial components of fertility.

Electrical utility system operators must plan resources so that electricity supply matches demand throughout the day. As the proportion of wind‐generated electricity in the US grows, changes in daily wind patterns have the potential either to disrupt the utility or increase the value of wind to the system over time. Wind power projects are designed to last many years, so at this timescale, climate change may become an influential factor on wind patterns. We examine the potential effects of climate change on the average diurnal power production cycles at 12 locations in North America by analyzing averaged and individual output from nine high‐resolution regional climate models comprising historical (1971–1999) and future (2041–2069) periods. A semi‐parametric mixed model is fit using cubic B‐splines, and model diagnostics are checked. Then, a likelihood ratio test is applied to test for differences between the time periods in the seasonal daily averaged cycles, and agreement among the individual regional climate models is assessed. We investigate the significant changes by combining boxplots with a differencing approach and identify broad categories of changes in the amplitude, shape, and position of the average daily cycles. We then discuss the potential impact of these changes on wind power production. Copyright © 2015 John Wiley & Sons, Ltd.

Monsanto Co. has developed two sweet corn hybrids, MON 88017 and MON 89034, that contain biotechnology-derived (biotech) traits designed to enhance sustainability and improve agronomic practices. MON 88017 confers benefits of glyphosate tolerance and protection against corn rootworm. MON 89034 provides protection against European corn borer and other lepidopteran insect pests. The purpose of this assessment was to compare the kernel compositions of MON 88017 and MON 89034 sweet corn with that of a conventional control that has a genetic background similar to the biotech sweet corn but does not express the biotechnology-derived traits. The sweet corn samples were grown at five replicated sites in the United States during the 2010 growing season and the conventional hybrid and 17 reference hybrids were grown concurrently to provide an estimate of natural variability for all assessed components. The compositional analysis included proximates, fibers, amino acids, sugars, vitamins, minerals, and selected metabolites. Results highlighted that MON 88017 and MON 89034 sweet corns were compositionally equivalent to the conventional control and that levels of the components essential to the desired properties of sweet corn, such as sugars and vitamins, were more affected by growing environment than the biotech traits. In summary, the benefits of biotech traits can be incorporated into sweet corn with no adverse effects on nutritional quality.