Global impacts of climate change on avian functional diversity.

Climate change is predicted to drive geographical range shifts, leading to fluctuations in species richness (SR) worldwide. However, the effect of these changes on functional diversity (FD) remains unclear, in part because comprehensive species-level trait data are generally lacking at global scales. Here, we use morphometric and ecological traits for 8268 bird species to estimate the impact of climate change on avian FD. We show that future bird assemblages are likely to undergo substantial shifts in trait structure, with a magnitude of change greater than predicted from SR alone, and a direction of change varying according to geographical location and trophic guild. For example, our models predict that FD of insect predators will increase at higher latitudes with concurrent losses at mid-latitudes, whereas FD of seed dispersing birds will fluctuate across the tropics. Our findings highlight the potential for climate change to drive continental-scale shifts in avian FD with implications for ecosystem function and resilience.

Impacts of invasive plants on animal behaviour.

The spread of invasive species is a threat to ecosystems worldwide. However, we know relatively little about how invasive species affect the behaviour of native animals, even though behaviour plays a vital role in the biotic interactions which are key to understanding the causes and impacts of biological invasions. Here, we explore how invasive plants - one of the most pervasive invasive taxa - impact the behaviour of native animals. To promote a mechanistic understanding of these behavioural impacts, we begin by introducing a mechanistic framework which explicitly considers the drivers and ecological consequences of behavioural change, as well as the moderating role of environmental context. We then synthesise the existing literature within this framework. We find that while some behavioural impacts of invasive plants are relatively well-covered in the literature, others are supported by only a handful of studies and should be explored further in the future. We conclude by identifying priority topics for future research, which will benefit from an interdisciplinary approach uniting invasion ecology with the study of animal behaviour and cognition.

Modelling the rheology of living cell cytoplasm: poroviscoelasticity and fluid-to-solid transition.

Eukaryotic cell rheology has important consequences for vital processes such as adhesion, migration, and differentiation. Experiments indicate that cell cytoplasm can exhibit both elastic and viscous characteristics in different regimes, while the transport of fluid (cytosol) through the cross-linked filamentous scaffold (cytoskeleton) is reminiscent of mass transfer by diffusion through a porous medium. To gain insights into this complex rheological behaviour, we construct a computational model for the cell cytoplasm as a poroviscoelastic material formulated on the principles of nonlinear continuum mechanics, where we model the cytoplasm as a porous viscoelastic scaffold with an embedded viscous fluid flowing between the pores to model the cytosol. Baseline simulations (neglecting the viscosity of the cytosol) indicate that the system exhibits seven different regimes across the parameter space spanned by the viscoelastic relaxation timescale of the cytoskeleton and the poroelastic diffusion timescale; these regimes agree qualitatively with experimental measurements. Furthermore, the theoretical model also allows us to elucidate the additional role of pore fluid viscosity, which enters the system as a distinct viscous timescale. We show that increasing this viscous timescale hinders the passage of the pore fluid (reducing the poroelastic diffusion) and makes the cytoplasm rheology increasingly incompressible, shifting the phase boundaries between the regimes.

Model selection in occupancy models: Inference versus prediction.

Occupancy models are a vital tool for ecologists studying the patterns and drivers of species occurrence, but their use often involves selecting among models with different sets of occupancy and detection covariates. The information-theoretic approach, which employs information criteria such as Akaike's information criterion (AIC) is arguably the most popular approach for model selection in ecology and is often used for selecting occupancy models. However, the information-theoretic approach risks selecting models that produce inaccurate parameter estimates due to a phenomenon called collider bias, a type of confounding that can arise when adding explanatory variables to a model. Using simulations, we investigated the consequences of collider bias (using an illustrative example called M-bias) in the occupancy and detection processes of an occupancy model, and explored the implications for model selection using AIC and a common alternative, the Schwarz criterion (or Bayesian information criterion, BIC). We found that when M-bias was present in the occupancy process, AIC and BIC selected models that inaccurately estimated the effect of the focal occupancy covariate, while simultaneously producing more accurate predictions of the site-level occupancy probability than other models in the candidate set. In contrast, M-bias in the detection process did not impact the focal estimate; all models made accurate inferences, while the site-level predictions of the AIC/BIC-best model were slightly more accurate. Our results show that information criteria can be used to select occupancy covariates if the sole purpose of the model is prediction, but must be treated with more caution if the purpose is to understand how environmental variables affect occupancy. By contrast, detection covariates can usually be selected using information criteria regardless of the model's purpose. These findings illustrate the importance of distinguishing between the tasks of parameter inference and prediction in ecological modeling. Furthermore, our results underline concerns about the use of information criteria to compare different biological hypotheses in observational studies.

Patterns of recruitment and injury in a heterogeneous airway network model.

In respiratory distress, lung airways become flooded with liquid and may collapse due to surface-tension forces acting on air-liquid interfaces, inhibiting gas exchange. This paper proposes a mathematical multiscale model for the mechanical ventilation of a network of occluded airways, where air is forced into the network at a fixed tidal volume, allowing investigation of optimal recruitment strategies. The temporal response is derived from mechanistic models of individual airway reopening, incorporating feedback on the airway pressure due to recruitment. The model accounts for stochastic variability in airway diameter and stiffness across and between generations. For weak heterogeneity, the network is completely ventilated via one or more avalanches of recruitment (with airways recruited in quick succession), each characterized by a transient decrease in the airway pressure; avalanches become more erratic for airways that are initially more flooded. However, the time taken for complete ventilation of the network increases significantly as the network becomes more heterogeneous, leading to increased stresses on airway walls. The model predicts that the most peripheral airways are most at risk of ventilation-induced damage. A positive-end-expiratory pressure reduces the total recruitment time but at the cost of larger stresses exerted on airway walls.

pH Oscillator Stretched in Space but Frozen in Time.

Chemical oscillations are studied using a continuous-flow microfluidic system transforming the time domain of chemical oscillators into a spatial domain. This system allows one (i) to monitor the dynamics of chemical oscillators with the accuracy of vigorously stirred batch reactors but with the ease and speed of CSTRs and (ii) to rapidly screen the phase space of chemical oscillators in just one experiment versus a traditional series of batch measurements.

Vortex flows impart chirality-specific lift forces.

Recent reports that macroscopic vortex flows can discriminate between chiral molecules or their assemblies sparked considerable scientific interest both for their implications to separations technologies and for their relevance to the origins of biological homochirality. However, these earlier results are inconclusive due to questions arising from instrumental artifacts and/or insufficient experimental control. After a decade of controversy, the question remains unresolved-how do vortex flows interact with different stereoisomers? Here, we implement a model experimental system to show that chiral objects in a Taylor-Couette cell experience a chirality-specific lift force. This force is directed parallel to the shear plane in contrast to previous studies in which helices, bacteria and chiral cubes experience chirality-specific forces perpendicular to the shear plane. We present a quantitative hydrodynamic model that explains how chirality-specific motions arise in non-linear shear flows through the interplay between the shear-induced rotation of the particle and its orbital translation. The scaling laws derived here suggest that rotating flows can be used to achieve chiral separation at the micro- and nanoscales.

A theoretical model to allow prediction of the CSF pressure from observations of the retinal venous pulse.

PURPOSE: There is no easy way to estimate the intracranial pressure (ICP) noninvasively. The retinal vein can exhibit large amplitude oscillations at the level of the lamina cribrosa under certain circumstances. The aims of this study were to develop a theoretical understanding of the conditions required to establish this vigorous oscillatory behavior and to determine whether observations of it could lead to a noninvasive estimate of the ICP. METHODS: A mathematical model was constructed in which the central retinal vein was modeled as 2 Starling resistors in series, 1 located in the eye and the other in the cerebrospinal fluid (CSF) space, separated by a region where it was not collapsible, corresponding to its course within the optic nerve itself. Intraocular pressure (IOP) and ICP were modeled as sinusoidal wave forms. RESULTS: The model predicted an approximately linear relationship between the IOP and the ICP at the point of onset of oscillatory behavior. The predicted onset IOP also depended weakly on the retinal blood flow rate and on vein diameter and was only mildly sensitive to the phase difference between the two pressure waveforms. The predicted onset curve showed encouraging agreement with measurements in canines. CONCLUSIONS: The model suggested that it may be possible to estimate the ICP from observations of the retinal venous pulse by using a modified form of ophthalmodynamometry.

Is the Donnan effect sufficient to explain swelling in brain tissue slices?

Brain tissue swelling is a dangerous consequence of traumatic injury and is associated with raised intracranial pressure and restricted blood flow. We consider the mechanical effects that drive swelling of brain tissue slices in an ionic solution bath, motivated by recent experimental results that showed that the volume change of tissue slices depends on the ionic concentration of the bathing solution. This result was attributed to the presence of large charged molecules that induce ion concentration gradients to ensure electroneutrality (the Donnan effect), leading to osmotic pressures and water accumulation. We use a mathematical triphasic model for soft tissue to characterize the underlying processes that could lead to the volume changes observed experimentally. We suggest that swelling is caused by an osmotic pressure increase driven by both non-permeating solutes released by necrotic cells, in addition to the Donnan effect. Both effects are necessary to explain the dependence of the tissue slice volume on the ionic bath concentration that was observed experimentally.