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11.
Recent research has revealed extensive pheromonal parsimony within the large beetle family Cerambycidae, with closely related species producing the same or very similar pheromone components. This article summarizes research that evaluated attraction of cerambycids to individual pheromone components, blends of pheromone components, and combinations of pheromones with host plant volatiles. Field bioassays were carried out, in collaboration with the Pennsylvania Department of Agriculture and the USDA Cooperative Agricultural Pest Survey program, in 10–25 counties of Pennsylvania over 3 years. A total of 15,438 cerambycids of 134 species were captured, including two exotic species. Semiochemical lures attracted significant numbers of beetles in species of the subfamilies Cerambycinae, Lamiinae, and Spondylidinae, but were not attractive to species in the Lepturinae, Parandrinae, and Prioninae. These experiments reconfirmed the behavioral roles of semiochemicals for a number of species that have been studied previously, and yielded new information about semiochemistry of several species. The host plant volatile α-pinene enhanced attraction of species that were conifer specialists, whereas ethanol enhanced attraction of some species of hardwood specialists. The data suggest that species which share dominant pheromone components avoid cross attraction by differing in seasonal activity period, and by antagonistic effects of minor pheromone components on attraction of heterospecifics. This study further supports the concept that with careful choice of components, multiple pheromones can be deployed as single blends, and paired with host plant volatiles, to maximize the number and taxonomic diversity of cerambycid beetles that are attracted to a single lure, so that the number of different lures that must be deployed can be minimized. 相似文献
12.
Changes in the physical and chemical structure of estuaries control the aerobic scope for activity of coastal fishes and thereby
influence the quality and extent of nursery habitats. We evaluated the effects of temperature, dissolved oxygen, and salinity
on the ecophysiology of a species that completes its life cycle in estuaries: white perch (Morone americana), which were reared at treatment levels that emulated nursery conditions in the Chesapeake Bay. Salinity influenced only
consumption rate and energy density, which were diminished at the highest salinity level (16). In hypoxic environments (≤40%
saturation), routine metabolic rates increased as much as fourfold while growth rate decreased threefold and consumption rate
decreased twofold. Experimental growth rates were within the range of growth rates observed in the field. Results indicate
that hypoxia substantially reduces potential nursery production for a dominant estuarine species, through its influence on
diminished aerobic capacity for growth and activity. 相似文献
13.
Summary. The purpose of this study was to identify plant volatiles that provide host location cues for adult females of the gall wasp Antistrophus rufus Gillette (Hymenoptera: Cynipidae). Larvae of this species inhabit flowering stems of the prairie perennial Silphium laciniatum L. (Asteraceae). Adult females responded to volatile compounds emitted by stems of S. laciniatum in field olfactometer bioassays. Plant volatiles were monoterpenes, including, in descending order of abundance, racemic - and -pinene (~50% + enantiomer for both), (+)-limonene, (–)-camphene, and -myrcene. In laboratory bioassays, females responded to aeration extracts of plant stems, the full blend of synthetic monoterpenes, and the four-component blend of -pinene, -pinene, (+)-limonene, and (–)-camphene. This monoterpene blend apparently serves as an olfactory cue for host plant location for female A. rufus and is the first such cue to be reported for a cynipid gall wasp. Species-specific ratios of plant monoterpenes may provide cues for gall wasp females to distinguish between plant species and choose appropriate hosts for oviposition. The olfactometer and bioassay techniques developed for this research may be useful for field bioassays of other types of minute arthropods. 相似文献
14.
Mevin B. Hooten Frances E. Buderman Brian M. Brost Ephraim M. Hanks Jacob S. Ivan 《Environmetrics》2016,27(6):322-333
New methods for modeling animal movement based on telemetry data are developed regularly. With advances in telemetry capabilities, animal movement models are becoming increasingly sophisticated. Despite a need for population‐level inference, animal movement models are still predominantly developed for individual‐level inference. Most efforts to upscale the inference to the population level are either post hoc or complicated enough that only the developer can implement the model. Hierarchical Bayesian models provide an ideal platform for the development of population‐level animal movement models but can be challenging to fit due to computational limitations or extensive tuning required. We propose a two‐stage procedure for fitting hierarchical animal movement models to telemetry data. The two‐stage approach is statistically rigorous and allows one to fit individual‐level movement models separately, then resample them using a secondary MCMC algorithm. The primary advantages of the two‐stage approach are that the first stage is easily parallelizable and the second stage is completely unsupervised, allowing for an automated fitting procedure in many cases. We demonstrate the two‐stage procedure with two applications of animal movement models. The first application involves a spatial point process approach to modeling telemetry data, and the second involves a more complicated continuous‐time discrete‐space animal movement model. We fit these models to simulated data and real telemetry data arising from a population of monitored Canada lynx in Colorado, USA. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
15.
Ephraim M. Hanks Erin M. Schliep Mevin B. Hooten Jennifer A. Hoeting 《Environmetrics》2015,26(4):243-254
In spatial generalized linear mixed models (SGLMMs), covariates that are spatially smooth are often collinear with spatially smooth random effects. This phenomenon is known as spatial confounding and has been studied primarily in the case where the spatial support of the process being studied is discrete (e.g., areal spatial data). In this case, the most common approach suggested is restricted spatial regression (RSR) in which the spatial random effects are constrained to be orthogonal to the fixed effects. We consider spatial confounding and RSR in the geostatistical (continuous spatial support) setting. We show that RSR provides computational benefits relative to the confounded SGLMM, but that Bayesian credible intervals under RSR can be inappropriately narrow under model misspecification. We propose a posterior predictive approach to alleviating this potential problem and discuss the appropriateness of RSR in a variety of situations. We illustrate RSR and SGLMM approaches through simulation studies and an analysis of malaria frequencies in The Gambia, Africa. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献