Detecting multivariate interactions in spatial point patterns with Gibbs models and variable selection

We propose a method for detecting significant interactions in very large multivariate spatial point patterns. This methodology develops high dimensional data understanding in the point process setting. The method is based on modelling the patterns using a flexible Gibbs point process model to directly characterise point-to-point interactions at different spatial scales. By using the Gibbs framework significant interactions can also be captured at small scales. Subsequently, the Gibbs point process is fitted using a pseudo-likelihood approximation, and we select significant interactions automatically using the group lasso penalty with this likelihood approximation. Thus we estimate the multivariate interactions stably even in this setting. We demonstrate the feasibility of the method with a simulation study and show its power by applying it to a large and complex rainforest plant population data set of 83 species

Local dependence of ion temperature gradient on magnetic configuration, rotational shear and turbulent heat flux in MAST

Experimental data from the Mega Amp Spherical Tokamak (MAST) is used to show that the inverse gradient scale length of the ion temperature R/LTi (normalized to the major radius R) has its strongest local correlation with the rotational shear and the pitch angle of the magnetic field (or, equivalently, an inverse correlation with q/{\epsilon}, the safety factor/the inverse aspect ratio). Furthermore, R/LTi is found to be inversely correlated with the gyro-Bohm-normalized local turbulent heat flux estimated from the density fluctuation level measured using a 2D Beam Emission Spectroscopy (BES) diagnostic. These results can be explained in terms of the conjecture that the turbulent system adjusts to keep R/LTi close to a certain critical value (marginal for the excitation of turbulence) determined by local equilibrium parameters (although not necessarily by linear stability).Comment: 6 pages, 3 figures, submitted to PR

Directional genetic differentiation and asymmetric migration

Understanding the population structure and patterns of gene flow within species is of fundamental importance to the study of evolution. In the fields of population and evolutionary genetics, measures of genetic differentiation are commonly used to gather this information. One potential caveat is that these measures assume gene flow to be symmetric. However, asymmetric gene flow is common in nature, especially in systems driven by physical processes such as wind or water currents. Since information about levels of asymmetric gene flow among populations is essential for the correct interpretation of the distribution of contemporary genetic diversity within species, this should not be overlooked. To obtain information on asymmetric migration patterns from genetic data, complex models based on maximum likelihood or Bayesian approaches generally need to be employed, often at great computational cost. Here, a new simpler and more efficient approach for understanding gene flow patterns is presented. This approach allows the estimation of directional components of genetic divergence between pairs of populations at low computational effort, using any of the classical or modern measures of genetic differentiation. These directional measures of genetic differentiation can further be used to calculate directional relative migration and to detect asymmetries in gene flow patterns. This can be done in a user-friendly web application called divMigrate-online introduced in this paper. Using simulated data sets with known gene flow regimes, we demonstrate that the method is capable of resolving complex migration patterns under a range of study designs.Comment: 25 pages, 8 (+3) figures, 1 tabl

Optimizing passive acoustic sampling of bats in forests

Passive acoustic methods are increasingly used in biodiversity research and monitoring programs because they are cost-effective and permit the collection of large datasets. However, the accuracy of the results depends on the bioacoustic characteristics of the focal taxa and their habitat use. In particular, this applies to bats which exhibit distinct activity patterns in three-dimensionally structured habitats such as forests. We assessed the performance of 21 acoustic sampling schemes with three temporal sampling patterns and seven sampling designs. Acoustic sampling was performed in 32 forest plots, each containing three microhabitats: forest ground, canopy, and forest gap. We compared bat activity, species richness, and sampling effort using species accumulation curves fitted with the clench equation. In addition, we estimated the sampling costs to undertake the best sampling schemes. We recorded a total of 145,433 echolocation call sequences of 16 bat species. Our results indicated that to generate the best outcome, it was necessary to sample all three microhabitats of a given forest location simultaneously throughout the entire night. Sampling only the forest gaps and the forest ground simultaneously was the second best choice and proved to be a viable alternative when the number of available detectors is limited. When assessing bat species richness at the 1-km(2) scale, the implementation of these sampling schemes at three to four forest locations yielded highest labor cost-benefit ratios but increasing equipment costs. Our study illustrates that multiple passive acoustic sampling schemes require testing based on the target taxa and habitat complexity and should be performed with reference to cost-benefit ratios. Choosing a standardized and replicated sampling scheme is particularly important to optimize the level of precision in inventories, especially when rare or elusive species are expected

Making co-enrolment feasible for randomised controlled trials in paediatric intensive care.

Enrolling children into several trials could increase recruitment and lead to quicker delivery of optimal care in paediatric intensive care units (PICU). We evaluated decisions taken by clinicians and parents in PICU on co-enrolment for two large pragmatic trials: the CATCH trial (CATheters in CHildren) comparing impregnated with standard central venous catheters (CVCs) for reducing bloodstream infection in PICU and the CHIP trial comparing tight versus standard control of hyperglycaemia

High-severity wildfire leads to multi-decadal impacts on soil biogeochemistry in mixed-conifer forests.

During the past century, systematic wildfire suppression has decreased fire frequency and increased fire severity in the western United States of America. While this has resulted in large ecological changes aboveground such as altered tree species composition and increased forest density, little is known about the long-term, belowground implications of altered, ecologically novel, fire regimes, especially on soil biological processes. To better understand the long-term implications of ecologically novel, high-severity fire, we used a 44-yr high-severity fire chronosequence in the Sierra Nevada where forests were historically adapted to frequent, low-severity fire, but were fire suppressed for at least 70 yr. High-severity fire in the Sierra Nevada resulted in a long-term (44 +yr) decrease (>50%, P < 0.05) in soil extracellular enzyme activities, basal microbial respiration (56-72%, P < 0.05), and organic carbon (>50%, P < 0.05) in the upper 5 cm compared to sites that had not been burned for at least 115 yr. However, nitrogen (N) processes were only affected in the most recent fire site (4 yr post-fire). Net nitrification increased by over 600% in the most recent fire site (P < 0.001), but returned to similar levels as the unburned control in the 13-yr site. Contrary to previous studies, we did not find a consistent effect of plant cover type on soil biogeochemical processes in mid-successional (10-50 yr) forest soils. Rather, the 44-yr reduction in soil organic carbon (C) quantity correlated positively with dampened C cycling processes. Our results show the drastic and long-term implication of ecologically novel, high-severity fire on soil biogeochemistry and underscore the need for long-term fire ecological experiments