Cumulative weather effects can impact across the whole life cycle

Predicting how species will be affected by future climatic change requires the underlying environmental drivers to be identified. As vital rates vary over the lifecycle, structured population models derived from statistical environment-demography relationships are often used to inform such predictions. Environmental drivers are typically identified independently for different vital rates and demographic classes. However, these rates often exhibit positive temporal covariance, suggesting the vital rates respond to common environmental drivers. Additionally, models often only incorporate average weather conditions during a single, a priori chosen time window (e.g. monthly means). Mismatches between these windows and the period when the vital rates are sensitive to variation in climate decrease the predictive performance of such approaches. We used a demographic structural equation model (SEM) to demonstrate that a single axis of environmental variation drives the majority of the (co)variation in survival, reproduction, and twinning across six age-sex classes in a Soay sheep population. This axis provides a simple target for the complex task of identifying the drivers of vital rate variation. We used functional linear models (FLMs) to determine the critical windows of three local climatic drivers, allowing the magnitude and direction of the climate effects to differ over time. Previously unidentified lagged climatic effects were detected in this well-studied population. The FLMs had a better predictive performance than selecting a critical window a priori, but not than a large-scale climate index. Positive covariance amongst vital rates and temporal variation in the effects of environmental drivers are common, suggesting our SEM-FLM approach is a widely applicable tool for exploring the joint responses of vital rates to environmental change

Topographical variation reduces phenological mismatch between a butterfly and its nectar source

© 2014, Springer International Publishing Switzerland. The timing of many biological events, including butterfly imago emergence, has advanced under climate change, with the rate of these phenological changes often differing among taxonomic groups. Such inter-taxa variability can lead to phenological mismatches. For example, the timing of a butterfly’s flight period may become misaligned with a key nectar resource, potentially increasing the extinction risk to both species. Here we fit statistical models to field data to determine how the phenology of the marbled white butterfly, Melanargia galathea, and its main nectar source, greater knapweed, Centaurea scabiosa, have changed over recent years at three sites across the UK. We also consider whether topographical diversity affects C. scabiosa’s flowering period. At our focal site, on the species’ northern range limit, we find that over a 13-year period the onset of C. scabiosa’s flowering period has become later whilst there is no obvious trend over time in the onset of M. galathea’s flight period. In recent years, butterflies have started to emerge before their key nectar source was available across most of the site. This raises the intriguing possibility that phenological mismatch could be an unrecognised determinant of range limits for some species. However, the presence of topographical diversity within the site decreased the chance of a mismatch occurring by increasing the length of the flowering period by up to 14days. We suggest that topographical diversity could be an important component in minimising phenological mismatches under future climate change

Modeling Genomes to Phenomes to Populations in a Changing Climate: The Need for Collaborative Networks

Condensed Abstract Climate is changing globally and its impacts can arise at different levels of biological organization; yet, cross-level consequences of climate change are still poorly understood. Designing effective environmental management and adaptation plans requires implementation of mechanistic models that span the biological hierarchy. Because biological systems are inherently complex and dynamic in nature, dealing with complexities efficiently necessitates simplification of systems or approximation of relevant processes, but there is little consensus on mathematical approaches to scale from genes to populations. Here we present an effort that aims to bring together groups that often do not interact, but that are essential to illuminating the complexities of life: empirical scientists and mathematical modelers, spanning levels of biological organization from genomes to organisms to populations. Through interplay between theory, models, and data, we aim to facilitate the generation of a new synthesis and a conceptual framework for biology across levels

Investigation of shock waves in explosive blasts using fibre optic pressure sensors

The published version of this article may be accessed at the link below. Copyright @ IOP Publishing, 2006.We describe miniature all-optical pressure sensors, fabricated by wafer etching techniques, less than 1 mm(2) in overall cross-section with rise times in the mu s regime and pressure ranges typically 900 kPa (9 bar). Their performance is suitable for experimental studies of the pressure-time history for test models exposed to shocks initiated by an explosive charge. The small size and fast response of the sensors promises higher quality data than has been previously available from conventional electrical sensors, with potential improvements to numerical models of blast effects. Results from blast tests are presented in which up to six sensors were multiplexed, embedded within test models in a range of orientations relative to the shock front.Support from the UK Engineering&Physical Sciences Research Council and Dstl Fort Halstead through the MoD Joint Grants Scheme are acknowledged. WN MacPherson is supported by an EPSRC Advanced Research Fellowship

Broadband terahertz heterodyne spectrometer exploiting synchrotron radiation at megahertz resolution

International audienceA new spectrometer allowing both high resolution and broadband coverage in the terahertz (THz) domain is proposed. This instrument exploits the heterodyne technique between broadband synchrotron radiation and a quantum cascade laser (QCL) based molecular THz laser that acts as the local oscillator (LO). Proof of principle for exploitation for spectroscopy is provided by the recording of molecular absorptions of hydrogen sulfide (H 2 S) and methanol (CH 3 OH) around 1.073 THz. Ultimately, the spectrometer will enable to cover the 1-4 THz region in 5 GHz windows at Doppler resolution

Motor phenotypes, medication and mood: further associations with impulsive behaviours in Parkinson's disease

BACKGROUND: Dopaminergic drugs are the primary risk factor for Impulse Control Behaviours (ICB) in Parkinson's disease (PD), others being early-onset disease and gender. OBJECTIVE: This report further explores ICB symptom relationships with motor and mood phenotypes, the complex relationship with dopaminergic medications, and hypothesizes a model with potential clinical implications. METHODS: Data from 500 PD patients were analyzed. Hypersexuality, gambling and shopping behaviour were assessed using selected questions from the Minnesota Impulsive Disorders Interview questionnaire. Local questions assessed hobbyism. Motor characteristics considered were akinetic-rigid/gait disturbance (PIGD) and 'non-PIGD' phenotypes, motor severity, motor progression, and presence/absence of motor fluctuations. Other variables included anxiety, depression, current levodopa and agonist use, age, gender and cognition. RESULTS: Overall, ICB symptom frequency was 17.8%. There was no relationship between PIGD/non-PIGD motor phenotypes and ICB symptoms. Those with ICB symptoms had higher total combined levodopa/agonist equivalent intake, but not current agonist-only equivalent intake. ICB symptoms were reported by 23.1% of those taking combined levodopa and agonist compared to 19.2% on agonist monotherapy and 11.6% levodopa monotherapy. Compared with non-ICB patients, patients with ICB symptoms were more likely to show an anxious mood phenotype, reported more motor fluctuations, and were younger. CONCLUSIONS: Both PIGD and non-PIGD phenotypes are equally affected. Dose-related risk applies to total anti-parkinsonian medication and not just current agonist-only. Anxious mood phenotypes may carry increased risk. A role of anxiety, either as a marker of risk, indirect causal factor, or maintaining factor is incorporated into a preliminary model. We discuss implications for clinical management

Anxiety and anxious-depression in Parkinson's disease over a 4-year period: A latent transition analysis

Background: Depression and anxiety in Parkinson's disease are common and frequently co-morbid, with significant impact on health outcome. Nevertheless, management is complex and often suboptimal. The existence of clinical subtypes would support stratified approaches in both research and treatment. Method: Five hundred and thirteen patients with Parkinson's disease were assessed annually for up to 4 years. Latent transition analysis (LTA) was used to identify classes that may conform to clinically meaningful subgroups, transitions between those classes over time, and baseline clinical and demographic features that predict common trajectories. Results: In total, 64.1% of the sample remained in the study at year 4. LTA identified four classes, a 'Psychologically healthy' class (approximately 50%), and three classes associated with psychological distress: one with moderate anxiety alone (approximately 20%), and two with moderate levels of depression plus moderate or severe anxiety. Class membership tended to be stable across years, with only about 15% of individuals transitioning between the healthy class and one of the distress classes. Stable distress was predicted by higher baseline depression and psychiatric history and younger age of onset of Parkinson's disease. Those with younger age of onset were also more likely to become distressed over the course of the study. Conclusions: Psychopathology was characterized by relatively stable anxiety or anxious-depression over the 4-year period. Anxiety, with or without depression, appears to be the prominent psychopathological phenotype in Parkinson's disease suggesting a pressing need to understanding its mechanisms and improve management

Beyond data mining; towards "idea engineering"

Abstract—SE data mining tools can be reconfigured to define and explore the space of decisions made by a community. Index Terms—Data mining, software engineering, artificial intelligenc