A core challenge in global change biology is to predict how species will respond to future environmental change and to manage these responses. To make such predictions and management actions robust ...to novel futures, we need to accurately characterize how organisms experience their environments and the biological mechanisms by which they respond. All organisms are thermodynamically connected to their environments through the exchange of heat and water at fine spatial and temporal scales and this exchange can be captured with biophysical models. Although mechanistic models based on biophysical ecology have a long history of development and application, their use in global change biology remains limited despite their enormous promise and increasingly accessible software. We contend that greater understanding and training in the theory and methods of biophysical ecology is vital to expand their application. Our review shows how biophysical models can be implemented to understand and predict climate change impacts on species' behavior, phenology, survival, distribution, and abundance. It also illustrates the types of outputs that can be generated, and the data inputs required for different implementations. Examples range from simple calculations of body temperature at a particular site and time, to more complex analyses of species' distribution limits based on projected energy and water balances, accounting for behavior and phenology. We outline challenges that currently limit the widespread application of biophysical models relating to data availability, training, and the lack of common software ecosystems. We also discuss progress and future developments that could allow these models to be applied to many species across large spatial extents and timeframes. Finally, we highlight how biophysical models are uniquely suited to solve global change biology problems that involve predicting and interpreting responses to environmental variability and extremes, multiple or shifting constraints, and novel abiotic or biotic environments.
Predictions of how species respond to climate and other global changes should ideally be based explicitly on known processes. Here we review the field of biophysical ecology, which addresses the most fundamental thermodynamic processes by which organisms respond to environmental change. We contend that greater understanding and training in the theory and methods of biophysical models is vital to expand their application.
Toroidal moment is an electromagnetic excitation that lies outside the familiar picture of electric and magnetic multipoles. It has recently been a topic of intense research in the fields of ...nanophotonics and metamaterials due to its weakly radiating nature and its ability to confine electromagnetic energy. Among extensive studies on toroidal moments and their applications, high quality factor (Q) toroidal resonances have been experimentally realized only in a very limited set of geometries and wavelengths. In this study, we demonstrate that a metasurface consisting of arrays of hollow dielectric cuboids supports a high Q-factor resonances at near-infrared and visible wavelengths due to the destructive interference between toroidal dipoles and magnetic quadrupoles. Using silicon as the high index dielectric, an experimental Q-factor of 728 is realized at a wavelength of 1505 nm, which is one of the highest values reported in the near-infrared using a dielectric metasurface. Importantly, our resonator geometry enables very efficient coupling of the toroidal resonance to the environment. This makes our metasurface design useful for refractometric sensing, where we measure a sensitivity of 161 nm per refractive index unit with a line width of 2.01 nm, efficiently distinguishing an index change of less than 0.02. We also find that a metasurface made of a relatively low-index dielectric, titanium dioxide (n < 2.4), is also capable of supporting the same toroidal mode with an observed Q-factor of 160 at visible wavelengths. With the versatility and robustness that dielectric metasurfaces provide, toroidal resonances are expected to be a powerful tool for investigating strong light–matter interaction and nonlinear phenomena at the nanoscale.
Climate refugia are regions that animals can retreat to, persist in and potentially then expand from under changing environmental conditions. Most forecasts of climate change refugia for species are ...based on correlative species distribution models (SDMs) using long‐term climate averages, projected to future climate scenarios. Limitations of such methods include the need to extrapolate into novel environments and uncertainty regarding the extent to which proximate variables included in the model capture processes driving distribution limits (and thus can be assumed to provide reliable predictions under new conditions). These limitations are well documented; however, their impact on the quality of climate refugia predictions is difficult to quantify. Here, we develop a detailed bioenergetics model for the koala. It indicates that range limits are driven by heat‐induced water stress, with the timing of rainfall and heat waves limiting the koala in the warmer parts of its range. We compare refugia predictions from the bioenergetics model with predictions from a suite of competing correlative SDMs under a range of future climate scenarios. SDMs were fitted using combinations of long‐term climate and weather extremes variables, to test how well each set of predictions captures the knowledge embedded in the bioenergetics model. Correlative models produced broadly similar predictions to the bioenergetics model across much of the species' current range – with SDMs that included weather extremes showing highest congruence. However, predictions in some regions diverged significantly when projecting to future climates due to the breakdown in correlation between climate variables. We provide unique insight into the mechanisms driving koala distribution and illustrate the importance of subtle relationships between the timing of weather events, particularly rain relative to hot‐spells, in driving species–climate relationships and distributions. By unpacking the mechanisms captured by correlative SDMs, we can increase our certainty in forecasts of climate change impacts on species.
Improved teamwork and communication have been associated with improved quality of care. Early Warning Scores (EWS) and rapid response algorithms are a way of identifying deteriorating patients and ...providing a common framework for communication and response between physicians and nurses. The impact of EWS implementation on interprofessional collaboration (IPC) has been minimally studied, especially in resource-limited settings. The study took place in the Pediatric Department of the main academic referral hospital in Rwanda between April 2019 and January 2020. Pediatric nurses and residents were trained on the use of the Pediatric Warning Score for Resource-Limited Settings (PEWS-RL) and a rapid response algorithm. Training included vital sign collection, PEWS-RL calculation, IPC and rapid response algorithm implementation. Prior to training, participants completed surveys on IPC with Likert scale responses (from "strongly disagree" to "strongly agree"). Follow-up surveys were then administered nine months later and also included an open-response question on the impact of the PEWS-RL implementation on IPC. Sixty-five (96%) nurses were trained and completed the pre-survey and thirty-seven (54%) of the trained nurses completed the post-survey. Twenty-two (59%) pediatric residents were trained in the workshop and completed the pre-survey and twenty-four physicians (4 pediatricians (40%) and 20 pediatric residents (53%)) completed the post-implementation survey. There was a statistically significant increase in the percent of nurses indicating strong agreement across all domains of communication and collaboration from the pre- to the post-survey. Although the percent of physicians indicating strong agreement increased in the post-survey for all items, only the "share information" item was statistically significant. Training and implementation of a PEWS-RL and a rapid response algorithm at a tertiary hospital in Rwanda resulted in significant improvement of nurse and physician ratings of IPC nine months later.
How climate constrains species’ distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to ...incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat‐balance model, to convert macroclimate data to pika‐specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8–19% less habitat loss in response to annual temperature increases of ~3–5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate‐imposed restrictions on activity. This more complete understanding is necessary to inform climate adaptation actions, management strategies, and conservation plans.
Hyaline cartilage is a strong durable material that lubricates joint movement. Due to its avascular structure, cartilage has a poor self-healing ability, thus, a challenge in joint recovery. When ...severely damaged, cartilage may need to be replaced. However, currently we are unable to replicate the hyaline cartilage, and as such, alternative materials with considerably different properties are used. This results in undesirable side effects, including inadequate lubrication, wear debris, wear of the opposing articular cartilage, and weakening of the surrounding tissue. With the number of surgeries for cartilage repair increasing, a need for materials that can better mimic cartilage, and support the surrounding material in its typical function, is becoming evident. Here, we present a brief overview of the structure and properties of the hyaline cartilage and the current methods for cartilage repair. We then highlight some of the alternative materials under development as potential methods of repair; this is followed by an overview of the development of tough hydrogels. In particular, double network (DN) hydrogels are a promising replacement material, with continually improving physical properties. These hydrogels are coming closer to replicating the strength and toughness of the hyaline cartilage, while offering excellent lubrication. We conclude by highlighting several different methods of integrating replacement materials with the native joint to ensure stability and optimal behaviour.
Selection on floral traits in hermaphroditic plants is determined by both male and female reproductive success. However, predictions regarding floral trait and mating system evolution are often based ...solely on female fitness. Selection via male fitness has the potential to affect the outcomes of floral evolution. In this study, we used paternity analysis to assess individual selfing rates and selection on floral traits via male and female fitness in an experimental population of Clarkia xantiana where pollen limitation of seed set was strong. We detected selection through both female and male fitness with reinforcing or noninterfering patterns of selection through the two sex functions. For female fitness, selection favored reduced herkogamy and protandry, traits that promote increased autonomous selfing. For male fitness, selection on petal area was disruptive, with higher trait values conferring greater pollinator attraction and outcross siring success and smaller trait values leading to higher selfed siring success. Combining both female and male fitness, selection on petal area and protandry was disruptive because intermediate phenotypes were less successful as both males and females. Finally, functional relationships among male and female fertility components indicated that selfing resulted in seed discounting and pollen discounting. Under these functional relationships, the evolutionarily stable selfing rate can be intermediate or predominantly selfing or outcrossing, depending on the segregating load of deleterious mutations.
The spatial organization of cell fates in developing tissues often involves the control of transcriptional networks by morphogen gradients. A well-studied example of this is the Sonic-hedgehog (Shh) ...controlled pattern of neuronal subtype differentiation in the vertebrate neural tube. Here we discuss recent studies involving genome wide analyses, functional experiments and theoretical models that have begun to characterise the molecular logic by which neural cells interpret Shh signalling. The view that emerges from this work is that cell identity results from the combined input of Shh signalling, uniformly expressed neural factors and the cross-regulatory network of downstream Shh target genes. A similar logic is also likely to underpin the patterning of many developing tissues.
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