University of Exeter

About: University of Exeter is a education organization based out in Exeter, United Kingdom. It is known for research contribution in the topics: Population & Context (language use). The organization has 15820 authors who have published 50650 publications receiving 1793046 citations. The organization is also known as: Exeter University & University of the South West of England.

Measuring acoustic habitats

Abstract: Summary 1. Many organisms depend on sound for communication, predator/prey detection and navigation. The acoustic environment can therefore play an important role in ecosystem dynamics and evolution. A growing number of studies are documenting acoustic habitats and their influences on animal development, behaviour, physiology and spatial ecology, which has led to increasing demand for passive acoustic monitoring (PAM) expertise in the life sciences. However, as yet, there has been no synthesis of data processing methods for acoustic habitat monitoring, which presents an unnecessary obstacle to would-be PAM analysts. 2. Here, we review the signal processing techniques needed to produce calibrated measurements of terrestrial and aquatic acoustic habitats. We include a supplemental tutorial and template computer codes in MATLAB and R, which give detailed guidance on how to produce calibrated spectrograms and statistical analyses of sound levels. Key metrics and terminology for the characterisation of biotic, abiotic and anthropogenic sound are covered, and their application to relevant monitoring scenarios is illustrated through example data sets. To inform study design and hardware selection, we also include an up-to-date overview of terrestrial and aquatic PAM instruments. 3. Monitoring of acoustic habitats at large spatiotemporal scales is becoming possible through recent advances in PAM technology. This will enhance our understanding of the role of sound in the spatial ecology of acoustically sensitive species and inform spatial planning to mitigate the rising influence of anthropogenic noise in these ecosystems. As we demonstrate in this work, progress in these areas will depend upon the application of consistent and appropriate PAM methodologies.

Reproductive effects of long-term exposure to Bisphenol A in the fathead minnow (Pimephales promelas).

Abstract: Bisphenol A (BPA), a high-volume chemical used to make polycarbonate plastic, epoxy resins, and other chemicals has been reported to be weakly estrogenic. To investigate the effects of long-term exposure to Bisphenol A, a multigeneration study was conducted in which fathead minnows (Pimephales promelas) were exposed to water concentrations of BPA in the range from 1 to 1280 micrograms/L. In this paper, we report the growth and reproductive effects of BPA on sexually mature adults in the F0 generation (after 43, 71, and 164 d of exposure) and the effects on hatchability in the F1 generation. Mean measured concentrations of BPA in the water for all doses, over a 164-d exposure period, were between 70% and 96% of nominal. An inhibitory effect of BPA on somatic growth (length and weight) occurred in adult male fish exposed to 640 and 1280 micrograms/L (after 71 and 164 d). BPA induced vitellogenin synthesis (VTG; a biomarker for estrogen exposure) in males at concentrations of 640 and 1280 micrograms/L after 43 d and 160 micrograms/L after 71 d. In females, plasma VTG concentrations were elevated above controls only after 164-d exposure to 640 micrograms/L. Inhibition of gonadal growth (as measured by the gonadosomatic index) occurred in both males and females at concentrations of 640 and 1280 micrograms/L after 164 d. In males, a concentration of 16 micrograms/L altered the proportion of sex cell types in the testis, suggesting inhibition of spermatogenesis. Concentrations of BPA that induced VTG synthesis and affected gonadal development were lower than those that resulted in discernible effects on reproductive output. Egg production was inhibited at a BPA concentration of 1280 micrograms/L, and hatchability in the F1 generation was reduced at a BPA concentration of 640 micrograms/L (there were not enough eggs spawned in the 1280 micrograms/L group for hatchability studies to be conducted). The results demonstrate that BPA acts as a weak estrogen to fish when administered via the water, with effects on breeding at and above 640 micrograms/L.

Observing terrestrial ecosystems and the carbon cycle from space

Abstract: Terrestrial ecosystem and carbon cycle feedbacks will significantly impact future climate, but their responses are highly uncertain. Models and tipping point analyses suggest the tropics and arctic/boreal zone carbon-climate feedbacks could be disproportionately large. In situ observations in those regions are sparse, resulting in high uncertainties in carbon fluxes and fluxes. Key parameters controlling ecosystem carbon responses, such as plant traits, are also sparsely observed in the tropics, with the most diverse biome on the planet treated as a single type in models. We analyzed the spatial distribution of in situ data for carbon fluxes, stocks and plant traits globally and also evaluated the potential of remote sensing to observe these quantities. New satellite data products go beyond indices of greenness and can address spatial sampling gaps for specific ecosystem properties and parameters. Because environmental conditions and access limit in situ observations in tropical and arctic/boreal environments, use of space-based techniques can reduce sampling bias and uncertainty about tipping point feedbacks to climate. To reliably detect change and develop the understanding of ecosystems needed for prediction, significantly, more data are required in critical regions. This need can best be met with a strategic combination of remote and in situ data, with satellite observations providing the dense sampling in space and time required to characterize the heterogeneity of ecosystem structure and function.

Long-range seasonal migration in insects: mechanisms, evolutionary drivers and ecological consequences

Abstract: Myriad tiny insect species take to the air to engage in windborne migration, but entomology also has its ‘charismatic megafauna’ of butterflies, large moths, dragonflies and locusts. The spectacular migrations of large day-flying insects have long fascinated humankind, and since the advent of radar entomology much has been revealed about high-altitude night-time insect migrations. Over the last decade, there have been significant advances in insect migration research, which we review here. In particular, we highlight: (1) notable improvements in our understanding of lepidopteran navigation strategies, including the hitherto unsuspected capabilities of high-altitude migrants to select favourable winds and orientate adaptively, (2) progress in unravelling the neuronal mechanisms underlying sun compass orientation and in identifying the genetic complex underpinning key traits associated with migration behaviour and performance in the monarch butterfly, and (3) improvements in our knowledge of the multifaceted interactions between disease agents and insect migrants, in terms of direct effects on migration success and pathogen spread, and indirect effects on the evolution of migratory systems. We conclude by highlighting the progress that can be made through inter-phyla comparisons, and identify future research areas that will enhance our understanding of insect migration strategies within an eco-evolutionary perspective.

A Gaussian process framework for modelling instrumental systematics: application to transmission spectroscopy

Abstract: Transmission spectroscopy, which consists of measuring the wavelength-dependent absorption of starlight by a planet’s atmosphere during a transit, is a powerful probe of atmospheric composition. However, the expected signal is typically orders of magnitude smaller than instrumental systematics and the results are crucially dependent on the treatment of the latter. In this paper, we propose a new method to infer transit parameters in the presence of systematic noise using Gaussian processes, a technique widely used in the machine learning community for Bayesian regression and classification problems. Our method makes use of auxiliary information about the state of the instrument, but does so in a non-parametric manner, without imposing a specific dependence of the systematics on the instrumental parameters, and naturally allows for the correlated nature of the noise. We give an example application of the method to archival NICMOS transmission spectroscopy of the hot Jupiter HD 189733, which goes some way towards reconciling the controversy surrounding this data set in the literature. Finally, we provide an appendix giving a general introduction to Gaussian processes for regression, in order to encourage their application to a wider range of problems.