Fog controls biological cycling of soil phosphorus in the Coastal Cordillera of the Atacama Desert

Soils in hyper-arid climates, such as the Chilean Atacama Desert, show indications of past and present forms of life despite extreme water limitations. We hypothesize that fog plays a key role in sustaining life. In particular, we assume that fog water is incorporated into soil nutrient cycles, with the inland limit of fog penetration corresponding to the threshold for biological cycling of soil phosphorus (P). We collected topsoil samples (0-10 cm) from each of 54 subsites, including sites in direct adjacency (<10 cm) and in 1 m distance to plants, along an aridity gradient across the Coastal Cordillera. Satellite-based fog detection revealed that Pacific fog penetrates up to 10 km inland, while inland sites at 10-23 km from the coast rely solely on sporadic rainfall for water supply. To assess biological P cycling we performed sequential P fractionation and determined oxygen isotope of HCl-extractable inorganicP δ 18 O HCl - P i $$ \mathrm{P}\ \left({\updelta}^{18}{\mathrm{O}}_{\mathrm{HCl}-{\mathrm{P}}_{\mathrm{i}}}\right) $$ . Total P (Pt ) concentration exponentially increased from 336 mg kg-1 to a maximum of 1021 mg kg-1 in inland areas ≥10 km. With increasing distance from the coast, soilδ 18 O HCl - P i $$ {\updelta}^{18}{\mathrm{O}}_{\mathrm{HCl}-{\mathrm{P}}_{\mathrm{i}}} $$ values declined exponentially from 16.6‰ to a constant 9.9‰ for locations ≥10 km inland. Biological cycling of HCl-Pi near the coast reached a maximum of 76%-100%, which could only be explained by the fact that fog water predominately drives biological P cycling. In inland regions, with minimal rainfall (<5 mm) as single water source, only 24 ± 14% of HCl-Pi was biologically cycled. We conclude that biological P cycling in the hyper-arid Atacama Desert is not exclusively but mainly mediated by fog, which thus controls apatite dissolution rates and related occurrence and spread of microbial life in this extreme environment.

Qualification of the PAVIN Fog and Rain Platform and Its Digital Twin for the Evaluation of a Pedestrian Detector in Fog

Vehicles featuring partially automated driving can now be certified within a guaranteed operational design domain. The verification in all kinds of scenarios, including fog, cannot be carried out in real conditions (risks or low occurrence). Simulation tools for adverse weather conditions (e.g., physical, numerical) must be implemented and validated. The aim of this study is, therefore, to verify what criteria need to be met to obtain sufficient data to test AI-based pedestrian detection algorithms. It presents both analyses on real and numerically simulated data. A novel method for the test environment evaluation, based on a reference detection algorithm, was set up. The following parameters are taken into account in this study: weather conditions, pedestrian variety, the distance of pedestrians to the camera, fog uncertainty, the number of frames, and artificial fog vs. numerically simulated fog. Across all examined elements, the disparity between results derived from real and simulated data is less than 10%. The results obtained provide a basis for validating and improving standards dedicated to the testing and approval of autonomous vehicles.

A Methodology to Model the Rain and Fog Effect on the Performance of Automotive LiDAR Sensors

In this work, we introduce a novel approach to model the rain and fog effect on the light detection and ranging (LiDAR) sensor performance for the simulation-based testing of LiDAR systems. The proposed methodology allows for the simulation of the rain and fog effect using the rigorous applications of the Mie scattering theory on the time domain for transient and point cloud levels for spatial analyses. The time domain analysis permits us to benchmark the virtual LiDAR signal attenuation and signal-to-noise ratio (SNR) caused by rain and fog droplets. In addition, the detection rate (DR), false detection rate (FDR), and distance error derror of the virtual LiDAR sensor due to rain and fog droplets are evaluated on the point cloud level. The mean absolute percentage error (MAPE) is used to quantify the simulation and real measurement results on the time domain and point cloud levels for the rain and fog droplets. The results of the simulation and real measurements match well on the time domain and point cloud levels if the simulated and real rain distributions are the same. The real and virtual LiDAR sensor performance degrades more under the influence of fog droplets than in rain.

Deep Camera-Radar Fusion with an Attention Framework for Autonomous Vehicle Vision in Foggy Weather Conditions

AVs are affected by reduced maneuverability and performance due to the degradation of sensor performances in fog. Such degradation can cause significant object detection errors in AVs' safety-critical conditions. For instance, YOLOv5 performs well under favorable weather but is affected by mis-detections and false positives due to atmospheric scattering caused by fog particles. The existing deep object detection techniques often exhibit a high degree of accuracy. Their drawback is being sluggish in object detection in fog. Object detection methods with a fast detection speed have been obtained using deep learning at the expense of accuracy. The problem of the lack of balance between detection speed and accuracy in fog persists. This paper presents an improved YOLOv5-based multi-sensor fusion network that combines radar object detection with a camera image bounding box. We transformed radar detection by mapping the radar detections into a two-dimensional image coordinate and projected the resultant radar image onto the camera image. Using the attention mechanism, we emphasized and improved the important feature representation used for object detection while reducing high-level feature information loss. We trained and tested our multi-sensor fusion network on clear and multi-fog weather datasets obtained from the CARLA simulator. Our results show that the proposed method significantly enhances the detection of small and distant objects. Our small CR-YOLOnet model best strikes a balance between accuracy and speed, with an accuracy of 0.849 at 69 fps.

Energy Efficient Node Selection in Edge-Fog-Cloud Layered IoT Architecture

Internet of Things (IoT) architectures generally focus on providing consistent performance and reliable communications. The convergence of IoT, edge, fog, and cloud aims to improve the quality of service of applications, which does not typically emphasize energy efficiency. Considering energy in IoT architectures would reduce the energy impact from billions of IoT devices. The research presented in this paper proposes an optimization framework that considers energy consumption of nodes when selecting a node for processing an IoT request in edge-fog-cloud layered architecture. The IoT use cases considered in this paper include smart grid, autonomous vehicles, and eHealth. The proposed framework is evaluated using CPLEX simulations. The results provide insights into mechanisms that can be used to select nodes energy-efficiently whilst meeting the application requirements and other network constraints in multi-layered IoT architectures.

Defect-Density-Controlled Phase-Change Phenomena

Juxtaposing hydrophilicity and hydrophobicity on the same surface, known as hybrid surface engineering, can enhance phase-change heat transfer. However, controlling hydrophilicity on hybrid surfaces in a scalable fashion is a challenge, limiting their application. Here, using widely available metal meshes with variable dimensions and by controlling the patterning pressure, we scalably fabricate hybrid surfaces having spot and gridlike patterns using stamping. Using fog harvesting in a controlled chamber, we show that optimized hybrid surfaces have a ∼37% higher fog harvesting rate when compared to homogeneous superhydrophobic surfaces. Furthermore, condensation frosting experiments reveal that, on grid-patterned hybrid surfaces, frost propagates at ∼160% higher velocity and provides ∼20% less frost coverage when compared to homogeneous superhydrophobic surfaces. During defrost, our hybrid surfaces retain more water when compared to superhydrophobic surfaces due to the presence of hydrophilic patterns and melt water pinning. We adapt our fabrication technique to roll-to-roll patterning, demonstrating wettability contrast on round metallic geometries via atmospheric water vapor condensation. This work provides guidelines for the rapid, substrate-independent, and scalable fabrication of hybrid wettability surfaces for a wide variety of applications.

SWEET: A Realistic Multiwavelength 3D Simulator for Automotive Perceptive Sensors in Foggy Conditions

Improving the reliability of automotive perceptive sensors in degraded weather conditions, including fog, is an important issue for road safety and the development of automated driving. Cerema has designed the PAVIN platform reproducing fog and rain conditions to evaluate optical automotive sensor performance under these conditions. In order to increase the variety of scenarios and technologies under test, the use of digital simulation becomes a major asset. The purpose of this paper is to revive the debate around the realism of the various models underlying the numerical methods. The simulation of the radiative transfer equation by Monte Carlo methods and by simplified noise models is examined. The results of this paper show some gaps in foggy scenes between the ray-tracing method, which is considered to be the most realistic, and simple models for contrast evaluation, which can have a particularly strong impact on obstacle detection algorithms.

Fog-Induced Alteration in Airborne Microbial Community: a Study over Central Indo-Gangetic Plain in India

Fog supports an increase in airborne microbial loading by providing water with nutrients and protecting it from harmful incoming solar radiation. To improve our present understanding of fog-induced alteration in an atmospheric microbial community, a study was conducted during 1 to 14 January 2021 for continuous investigation of airborne bacteria over a rural site, Arthauli (25.95°N, 85.10°E), in central Indo-Gangetic Plain (IGP) in India. An increase of 36% ± 0.4% in airborne bacterial loading was noticed under fog versus prefog conditions, and a decrease of 48% ± 0.4% was noticed under the postfog condition. Airborne bacterial loading had a strong correlation with RH (R² = 0.56; P < 0.05), temperature (R² = -0.55, P < 0.05), and wind speed (R² = -0.52, P < 0.05). Unique types of bacteria, representing about 29% of the whole community, were detected only under foggy conditions, likely by a continuous supply of nutrients and water from a cold, calm, and humid atmosphere. As a result, no significant diurnal variation of bacterial loading was noticed on a foggy day, with a higher daily mean concentration of about (8.4 ± 1.7) × 10⁵ cells · m^-3 than that on a typical winter day [(6.3 ± 3.8) × 10⁵ cells · m^-3]. A typical winter day experienced about a 60% decrease in bacterial loading in the afternoon in comparison to that in the morning. A 3-day back-trajectory analysis suggests a slow movement of airmass along with the wind blowing from west to central IGP. Fog pauses wind movement, which reduces continuous transportation of urban sources while increasing airborne bacteria from local sources. The abundances of Gp6 (14.8% ± 8.6%), Anaeromyxobacter (7.1% ± 2.8%), and Gp7 (6.8 ± 2.6%) have been observed to increase due to occurrences of fog over central IGP. IMPORTANCE Fog was investigated in the present study as a cause of alteration in the airborne microbial community. Occurrences of fog were responsible for an increase in airborne microbial loading (36%) over central IGP in India due to the easy availability of nutrients and water in the air and dimming of harmful solar radiation. More than 90% of unique bacteria were detected under fog (64%) and postfog (28%) conditions. A few bacteria, like Gp18 (0.5% ± 0.3%), Alicyclobacillus (0.5% ± 0.1%), Sinomonas (0.4% ± 0.2%), and Phenylobacterium (0.4% ± 0.2%), were detected only under foggy conditions. A strong correlation between meteorological parameters and bacterial loading was found in the current research work. The present study provides additional support toward a new direction in interdisciplinary science for the detailed investigations of the effects of meteorological conditions on airborne bacteria and their implications for society.

[Distribution of Bacterial Concentration and Viability in Atmospheric Bioaerosols Under Different Weather Conditions in the Coastal Region of Qingdao]

Bacteria are the most abundant microorganisms in atmospheric bioaerosols, widely distributed in the environment. Bioaerosol samples were collected using the FA-1 impact sampler from October 2013 to January 2021 in the coastal city of Qingdao, and samples stained with a BacLight^TM bacterial viability kit were used to measure the concentrations of viable and non-viable bacteria with an epifluorescence microscope. The viable and non-viable bacteria in bioaerosols were characterized during different seasons, with particular attention paid to the distribution characteristics of bacteria on foggy, hazy, and dust days. The results showed that the mean concentrations of total bacteria were (1.06±0.68)×10⁵ cells·m^-3 in Qingdao during the sampling period, and those of viable and non-viable bacteria were (8.20±4.88)×10³ cells·m^-3and (9.74±6.72)×10⁴ cells·m^-3, respectively. The seasonal concentrations of non-viable bacteria were the highest in spring and winter and the lowest in summer, whereas that of viable bacteria was highest in spring, followed by those in summer and autumn, and the lowest in winter. Atmospheric bacterial concentrations fluctuated with by month, and total bacteria presented a similar variation pattern with that of non-viable bacteria. The monthly average concentration of non-viable bacteria showed the highest value in March during the spring and the lowest in June during the summer in 2021, whereas the highest value for viable bacteria occurred in May during the spring in 2021 and the lowest in December during the winter in 2020. Viable bacteria concentrations were significantly positively correlated with temperature and significantly negatively correlated with NO₂, SO₂, and CO. Non-viable bacteria were significantly positively correlated with PM. The bacteria in bioaerosol particles showed bimodal, unimodal, and skewed size distributions, varying with season and month. Under different weather conditions, the concentration of non-viable bacteria on dusty days was significantly higher than that on sunny, foggy, or hazy days, but the bacteria viability was as low as 6.85% due to long-distance transport. Anthropogenic pollution resulted in the lowest viability of bacteria at 4.10% on hazy days, whereas the highest viability in bacteria was 16.26% on foggy days due to high humidity. The size distribution of bacteria in bioaerosol particles under different pollution days showed a bimodal distribution, and the peak size depended on the weather type.

New Proposal of Epiphytic Bromeliaceae Functional Groups to Include Nebulophytes and Shallow Tanks

The Bromeliaceae family has been used as a model to study adaptive radiation due to its terrestrial, epilithic, and epiphytic habits with wide morpho-physiological variation. Functional groups described by Pittendrigh in 1948 have been an integral part of ecophysiological studies. In the current study, we revisited the functional groups of epiphytic bromeliads using a 204 species trait database sampled throughout the Americas. Our objective was to define epiphytic functional groups within bromeliads based on unsupervised classification, including species from the dry to the wet end of the Neotropics. We performed a hierarchical cluster analysis with 16 functional traits and a discriminant analysis, to test for the separation between these groups. Herbarium records were used to map species distributions and to analyze the climate and ecosystems inhabited. The clustering supported five groups, C₃ tank and CAM tank bromeliads with deep tanks, while the atmospheric group (according to Pittendrigh) was divided into nebulophytes, bromeliads with shallow tanks, and bromeliads with pseudobulbs. The two former groups showed distinct traits related to resource (water) acquisition, such as fog (nebulophytes) and dew (shallow tanks). We discuss how the functional traits relate to the ecosystems inhabited and the relevance of acknowledging the new functional groups.

Measuring the Influence of Environmental Conditions on Automotive Lidar Sensors

Safety validation of automated driving functions is a major challenge that is partly tackled by means of simulation-based testing. The virtual validation approach always entails the modeling of automotive perception sensors and their environment. In the real world, these sensors are exposed to adverse influences by environmental conditions such as rain, fog, snow, etc. Therefore, such influences need to be reflected in the simulation models. In this publication, a novel data set is introduced and analyzed. This data set contains lidar data with synchronized reference measurements of weather conditions from a stationary long-term experiment. Recorded weather conditions comprise fog, rain, snow, and direct sunlight. The data are analyzed by pairing lidar values, such as the number of detections in the atmosphere, with weather parameters such as rain rate in mm/h. This results in expectation values, which can directly be utilized for stochastic modeling or model calibration and validation. The results show vast differences in the number of atmospheric detections, range distribution, and attenuation between the different sensors of the data set.

Single-Pixel Near-Infrared 3D Image Reconstruction in Outdoor Conditions

In the last decade, the vision systems have improved their capabilities to capture 3D images in bad weather scenarios. Currently, there exist several techniques for image acquisition in foggy or rainy scenarios that use infrared (IR) sensors. Due to the reduced light scattering at the IR spectra it is possible to discriminate the objects in a scene compared with the images obtained in the visible spectrum. Therefore, in this work, we proposed 3D image generation in foggy conditions using the single-pixel imaging (SPI) active illumination approach in combination with the Time-of-Flight technique (ToF) at 1550 nm wavelength. For the generation of 3D images, we make use of space-filling projection with compressed sensing (CS-SRCNN) and depth information based on ToF. To evaluate the performance, the vision system included a designed test chamber to simulate different fog and background illumination environments and calculate the parameters related to image quality.

Internet of Things Framework for Oxygen Saturation Monitoring in COVID-19 Environment

The pandemic/epidemic of COVID-19 has affected people worldwide. A huge number of lives succumbed to death due to the sudden outbreak of this corona virus infection. The specified symptoms of COVID-19 detection are very common like normal flu; asymptomatic version of COVID-19 has become a critical issue. Therefore, as a precautionary measurement, the oxygen level needs to be monitored by every individual if no other critical condition is found. It is not the only parameter for COVID-19 detection but, as per the suggestions by different medical organizations such as the World Health Organization, it is better to use oximeter to monitor the oxygen level in probable patients as a precaution. People are using the oximeters personally; however, not having any clue or guidance regarding the measurements obtained. Therefore, in this article, we have shown a framework of oxygen level monitoring and severity calculation and probabilistic decision of being a COVID-19 patient. This framework is also able to maintain the privacy of patient information and uses probabilistic classification to measure the severity. Results are measured based on latency of blockchain creation and overall response, throughput, detection, and severity accuracy. The analysis finds the solution efficient and significant in the Internet of Things framework for the present health hazard in our world.

On the benefits of wearable devices for Parkinson's disease

Freezing of gait (FOG) is defined as episodic inability to generate an effective movement without any known cause other than parkinson-ism or gait disturbance. FOG is one of the most disabling symptoms of Parkinson's disease (PD), it affects mobility and increases the risk of falling in people with PD, making it a leading cause of hospitalization and of significantly worsening the quality of life (1). In recent years, new non-invasive intervention strategies have been implemented to decrease FOG symptoms. Thanks to technological progress, several devices have been developed as a support for the patients during diag-nosis, treatments and also everyday life. These types of interventions are based on cueing systems that rely on active stimulation. These devices are able to identify FOG states and to operate when this motor blocks occur, providing external stimuli to overcome these episodes. Hence, this work aims to provide a technological review of the literature related to wearable devices and focuses on auditory, visual, virtual and soma-tosensory cueing systems, which can provide a suitable intervention for patients with PD. The paper describes the technical functioning and effectiveness of the different reporting systems in overcoming FOG episodes. Moreover, a classification of existing devices, highlighting their advantages and disadvantages, will be provided in order to identify the ones with the best performance.

An overview of data reduction solutions at the edge of IoT systems: a systematic mapping of the literature

Internet of Things (IoT) is a technology that connects devices of different types and characteristics through a network. The massive quantity of the heterogeneous generated data by the sensors imposes many challenges in making these data available to IoT applications. Data reduction and preprocessing are promising concepts that help to handle these data efficiently before storing them. Applying data reduction methods at the edge has emerged as an efficient solution. In such context, this systematic mapping is intended to investigate the data reduction solutions performed exclusively at the edge through a set of research questions. To reach this objective, we performed a Systematic Literature Mapping (SLM) in which 35 papers were strictly analyzed among a total of 853 articles. Finally, we present the results of these analyses answering questions that relate to the researcher’s used techniques, hardware technologies, used data type, and contributed objects to perform the data reduction techniques on the edge of the IoT systems.

A Systematic Survey on the Role of Cloud, Fog, and Edge Computing Combination in Smart Agriculture

Cloud Computing is a well-established paradigm for building service-centric systems. However, ultra-low latency, high bandwidth, security, and real-time analytics are limitations in Cloud Computing when analysing and providing results for a large amount of data. Fog and Edge Computing offer solutions to the limitations of Cloud Computing. The number of agricultural domain applications that use the combination of Cloud, Fog, and Edge is increasing in the last few decades. This article aims to provide a systematic literature review of current works that have been done in Cloud, Fog, and Edge Computing applications in the smart agriculture domain between 2015 and up-to-date. The key objective of this review is to identify all relevant research on new computing paradigms with smart agriculture and propose a new architecture model with the combinations of Cloud–Fog–Edge. Furthermore, it also analyses and examines the agricultural application domains, research approaches, and the application of used combinations. Moreover, this survey discusses the components used in the architecture models and briefly explores the communication protocols used to interact from one layer to another. Finally, the challenges of smart agriculture and future research directions are briefly pointed out in this article.

Aqueous Photochemistry of 2-Oxocarboxylic Acids: Evidence, Mechanisms, and Atmospheric Impact

Atmospheric organic aerosols play a major role in climate, demanding a better understanding of their formation mechanisms by contributing multiphase chemical reactions with the participation of water. The sunlight driven aqueous photochemistry of small 2-oxocarboxylic acids is a potential major source of organic aerosol, which prompted the investigations into the mechanisms of glyoxylic acid and pyruvic acid photochemistry reviewed here. While 2-oxocarboxylic acids can be contained or directly created in the particles, the majorities of these abundant and available molecules are in the gas phase and must first undergo the surface uptake process to react in, and on the surface, of aqueous particles. Thus, the work also reviews the acid-base reaction that occurs when gaseous pyruvic acid meets the interface of aqueous microdroplets, which is contrasted with the same process for acetic acid. This work classifies relevant information needed to understand the photochemistry of aqueous pyruvic acid and glyoxylic acid and motivates future studies based on reports that use novel strategies and methodologies to advance this field.

Fear of Missing Out Predicts Distraction by Social Reward Signals Displayed on a Smartphone in Difficult Driving Situations

Smartphones are particularly likely to elicit driver distraction with obvious negative repercussions on road safety. Recent selective attention models lead to expect that smartphones might be very effective in capturing attention due to their social reward history. Hence, individual differences in terms of Fear of Missing Out (FoMO) – i.e., of the apprehension of missing out on socially rewarding experiences – should play an important role in driver distraction. This factor has already been associated with self-reported estimations of greater attention paid to smartphones while driving, but the potential link between FoMO and smartphone-induced distraction has never been tested empirically. Therefore, we conducted a preliminary study to investigate whether FoMO would modulate attentional capture by reward distractors displayed on a smartphone. First, participants performed a classical visual search task in which neutral stimuli (colored circles) were associated with high or low social reward outcomes. Then, they had to detect a pedestrian or a roe deer in driving scenes with various levels of fog density. The social reward stimuli were displayed as distractors on the screen of a smartphone embedded in the pictures. The results showed a significant three-way interaction between FoMO, social reward distraction, and task difficulty. More precisely, under attention-demanding conditions (i.e., high-fog density), individual FoMO scores predicted attentional capture by social reward distractors, with longer reaction times (RTs) for high rather than low social reward distractors. These results highlight the importance to consider reward history and FoMO when investigating smartphone-based distraction. Limitations are discussed, notably regarding our sample characteristics (i.e., mainly young females) that might hamper the generalization of our findings to the overall population. Future research directions are provided.

Compression-Aware Aggregation and Energy-Aware Routing in IoT-Fog-Enabled Forest Environment

Forest fire monitoring is very much needed for protecting the forest from any kind of disaster or anomaly leading to the destruction of the forest. Now, with the advent of Internet of Things (IoT), a good amount of research has been done on energy consumption, coverage, and other issues. These works did not focus on forest fire management. The IoT-enabled environment is made up of low power lossy networks (LLNs). For improving the performance of routing protocol in forest fire management, energy-efficient routing protocol for low power lossy networks (E-RPL) was developed where residual power was used as an objective function towards calculating the rank of the parent node to form the destination-oriented directed acyclic graph (DODAG). The challenge in E-RPL is the scalability of the network resulting in a long end-to-end delay and less packet delivery. Additionally, the energy of sensor nodes increased with different transmission range. So, for obviating the above-mentioned drawbacks in E-RPL, compressed data aggregation and energy-based RPL routing (CAA-ERPL) is proposed. The CAA-ERPL is compared with E-RPL, and the performance is analyzed resulting in reduced packet transfer delay, less energy consumption, and increased packet delivery ratio for 10, 20, 30, 40, and 50 nodes. This has been evaluated using a Contiki Cooja simulator.

Photosynthetic heat tolerance in plants with different foliar water -uptake strategies

PREMISE

The distribution and even the survival of plant species are influenced by temperature. In an old climatically buffered infertile landscape (OCBIL) in Brazil, we previously characterized different strategies for foliar water uptake (FWU). It is possible that photosystem II tolerance to heat and excessive light intensity varies among species with different FWU capacities.

METHODS

The relationship between FWU, photoinhibition, and thermotolerance was investigated in seven species from this ecosystem.

RESULTS

The species with slow water absorption and high water absorption are those that presented less photoinhibition. Contrastingly, the species that have fast and low water absorption presented greater thermotolerance when their leaves are totally hydrated. However, when there is greater leaf dehydration, the most thermotolerant species were those with slow but high water absorption.

CONCLUSIONS

Foliar water uptake is an important trait for plants to tolerate excessive light intensity and higher temperatures. Plants in this OCBIL may be differentially affected by future global warming, and the best strategy to deal with this expected climate change is with slow and high absorption of water.

Habitat-islands in the coastal Atacama Desert: loss of functional redundancy, but not of functional diversity, with decreased precipitation

BACKGROUND AND AIMS

Aridity is increasing in many regions of the world, but microclimatic conditions may buffer plant communities from the direct effects of decreased precipitation, creating habitat islands. However, reduced precipitation can also impact these communities indirectly by decreasing the suitability of the surrounding habitat, thus limiting incoming propagules and increasing the chances of population decline and species loss. We test whether decreased precipitation results in loss of species and functional diversity within habitat islands, evaluating in particular whether declines in species diversity and abundance are less likely to result in loss of functional diversity if species/individual loss is stochastic (i.e. independent of species/individual traits) and communities/populations are functionally redundant.

METHODS

Lomas communities are discrete plant communities embedded in the Atacama Desert, maintained by the microclimatic conditions created by fog. We recorded species and functional diversity in six Lomas communities along a 500 km long precipitation gradient in northern Chile. Functional traits were measured in 20 individuals per species, in those species that accounted for approx. 75 % of the abundance at each site. We calculated functional diversity and functional redundancy of the community, and intraspecific functional variation.

KEY RESULTS

Decreased precipitation was associated with lower species diversity and lower species abundances. However, no traits or functional strategies increased or decreased consistently with precipitation, suggesting stochastic species/individual loss. Species with stress-tolerant strategies were predominant in all sites. Although species diversity decreased with decreasing precipitation, functional diversity remained unchanged. Lower functional redundancy in the drier sites suggests that mainly functionally redundant species were lost. Likewise, intraspecific functional variation was similar among communities, despite the lower species abundance in drier sites.

CONCLUSIONS

Decreased precipitation can impact habitat island communities indirectly by decreasing the suitability of the surrounding habitat. Our results support the idea that a stochastic loss of species/individuals from functionally redundant communities and populations does not result in loss of functional diversity.

Fungal Communities on Standing Litter Are Structured by Moisture Type and Constrain Decomposition in a Hyper-Arid Grassland

Non-rainfall moisture (fog, dew, and water vapor; NRM) is an important driver of plant litter decomposition in grasslands, where it can contribute significantly to terrestrial carbon cycling. However, we still do not know whether microbial decomposers respond differently to NRM and rain, nor whether this response affects litter decomposition rates. To determine how local moisture regimes influence decomposer communities and their function, we examined fungal communities on standing grass litter at an NRM-dominated site and a rain-dominated site 75 km apart in the hyper-arid Namib Desert using a reciprocal transplant design. Dominant taxa at both sites consisted of both extremophilic and cosmopolitan species. Fungal communities differed between the two moisture regimes with environment having a considerably stronger effect on community composition than did stage of decomposition. Community composition was influenced by the availability of air-derived spores at each site and by specialization of fungi to their home environment; specifically, fungi from the cooler, moister NRM Site performed worse (measured as fungal biomass and litter mass loss) when moved to the warmer, drier rain-dominated site while Rain Site fungi performed equally well in both environments. Our results contribute to growing literature demonstrating that as climate change alters the frequency, magnitude and type of moisture events in arid ecosystems, litter decomposition rates may be altered and constrained by the composition of existing decomposer communities.

[Distribution Characteristics and Source Analysis of Water-soluble Ions in Particulate Matter Under Different Weather Processes in Nanjing]

From November 16 to 28 2018, water-soluble ions in particulate matter and some trace gases in Nanjing City were observed using the online gas composition and aerosol monitoring system MARGA ADI 2080. Combined with meteorological elements and sounding data, the distribution characteristics and day-night differences of pollutants and water-soluble ions during haze, fog, clear, and precipitation processes were analyzed. The results show that the average concentration of PM_2.5 varied from 26.9μg·m^-3 (precipitation) to 96.4μg·m^-3 (haze) while total water-soluble ions varied between 23.7μg·m^-3 (precipitation) and 89.7μg·m^-3 (haze). The ranked order of ion concentrations was NO₃^- > NH₄⁺ > SO₄^2- > Cl^- > K⁺ > Ca²⁺ > Na⁺ > Mg²⁺ during haze and fog events, and NO₃^- > SO₄^2- > NH₄⁺ > Cl^- > Ca²⁺ > K⁺ > Na⁺ > Mg²⁺ during clear weather and precipitation period. The diurnal distributions of water-soluble ions were quite different under the four conditions, although SO₄^2-, NO₃^-, and NH₄⁺(SNA) were ranked haze > fog > clear > precipitation for both day and night periods. According to the PMF source analysis, secondary sources were the main factors affecting haze; secondary sources, sea salt, and combustion sources were the main pollution sources to foggy conditions; and the removal effect of precipitation on coal-fired sources and secondary sources was more notable than during clear conditions.

Laser and LIDAR in a System for Visibility Distance Estimation in Fog Conditions

Visibility is a critical factor for transportation, even if we refer to air, water, or ground transportation. The biggest trend in the automotive industry is autonomous driving, the number of autonomous vehicles will increase exponentially, prompting changes in the industry and user segment. Unfortunately, these vehicles still have some drawbacks and one, always in attention and topical, will be treated in this paper-visibility distance issue in bad weather conditions, particularly in fog. The way and the speed with which vehicles will determine objects, obstacles, pedestrians, or traffic signs, especially in bad visibility, will determine how the vehicle will behave. In this paper, a new experimental set up is featured, for analyzing the effect of the fog when the laser and LIDAR (Light Detection And Ranging) radiation are used in visibility distance estimation on public roads. While using our experimental set up, in the laboratory, the information offered by these measurement systems (laser and LIDAR) are evaluated and compared with results offered by human observers in the same fog conditions. The goal is to validate and unitarily apply the results regarding visibility distance, based on information arrives from different systems that are able to estimate this parameter (in foggy weather conditions). Finally, will be notifying the drivers in case of unexpected situations. It is a combination of stationary and of moving systems. The stationary system will be installed on highways or express roads in areas prone to fog, while the moving systems are, or can be, directly installed on the vehicles (autonomous but also non-autonomous).

Hardware Security of Fog End-Devices for the Internet of Things

The proliferation of the Internet of Things (IoT) caused new application needs to emerge as rapid response ability is missing in the current IoT end-devices. Therefore, Fog Computing has been proposed to be an edge component for the IoT networks as a remedy to this problem. In recent times, cyber-attacks are on the rise, especially towards infrastructure-less networks, such as IoT. Many botnet attack variants (Mirai, Torii, etc.) have shown that the tiny microdevices at the lower spectrum of the network are becoming a valued participant of a botnet, for further executing more sophisticated attacks against infrastructural networks. As such, the fog devices also need to be secured against cyber-attacks, not only software-wise, but also from hardware alterations and manipulations. Hence, this article first highlights the importance and benefits of fog computing for IoT networks, then investigates the means of providing hardware security to these devices with an enriched literature review, including but not limited to Hardware Security Module, Physically Unclonable Function, System on a Chip, and Tamper Resistant Memory.

A Multitiered Solution for Anomaly Detection in Edge Computing for Smart Meters

In systems connected to smart grids, smart meters with fast and efficient responses are very helpful in detecting anomalies in realtime. However, sending data with a frequency of a minute or less is not normal with today's technology because of the bottleneck of the communication network and storage media. Because mitigation cannot be done in realtime, we propose prediction techniques using Deep Neural Network (DNN), Support Vector Regression (SVR), and k-Nearest Neighbors (KNN). In addition to these techniques, the prediction timestep is chosen per day and wrapped in sliding windows, and clustering using Kmeans and intersection Kmeans and HDBSCAN is also evaluated. The predictive ability applied here is to predict whether anomalies in electricity usage will occur in the next few weeks. The aim is to give the user time to check their usage and from the utility side, whether it is necessary to prepare a sufficient supply. We also propose the latency reduction to counter higher latency as in the traditional centralized system by adding layer Edge Meter Data Management System (MDMS) and Cloud-MDMS as the inference and training model. Based on the experiments when running in the Raspberry Pi, the best solution is choosing DNN that has the shortest latency 1.25 ms, 159 kB persistent file size, and at 128 timesteps.

Spatial Patterns and Trends of Summertime Low Cloudiness for the Pacific Northwest, 1996-2017

Summertime low clouds are common in the Pacific Northwest (PNW), but spatiotemporal patterns have not been characterized. We show the first maps of low cloudiness for the western PNW and North Pacific Ocean using a 22-year satellite-derived record of monthly mean low cloudiness frequency for May through September and supplemented by airport cloud base height observations. Domain-wide cloudiness peaks in midsummer and is strongest over the Pacific. Empirical orthogonal function (EOF) analysis identified four distinct PNW spatiotemporal modes: oceanic, terrestrial highlands, coastal, and northern coastal. There is a statistically significant trend over the 22-year record toward reduced low cloudiness in the terrestrial highlands mode, with strongest declines in May and June; however, this decline is not matched in the corresponding airport records. The coastal mode is partly constrained from moving inland by topographic relief and migrates southward in late summer, retaining higher late-season low cloud frequency than the other areas.

Vision-Based Safety-Related Sensors in Low Visibility by Fog

Mobile service robots are expanding their use to outdoor areas affected by various weather conditions, but the outdoor environment directly affects the functional safety of robots implemented by vision-based safety-related sensors (SRSs). Therefore, this paper aims to set the fog as the environmental condition of the robot and to understand the relationship between the quantified value of the environmental conditions and the functional safety performance of the robot. To this end, the safety functions of the robot built using SRS and the requirements for the outdoor environment affecting them are described first. The method of controlling visibility for evaluating the safety function of SRS is described through the measurement and control of visibility, a quantitative means of expressing the concentration of fog, and wavelength analysis of various SRS light sources. Finally, object recognition experiments using vision-based SRS for robots are conducted at low visibility. Through this, it is verified that the proposed method is a specific and effective method for verifying the functional safety of the robot using the vision-based SRS, for low visibility environmental requirements.

Design of water harvesting towers and projections for water collection from fog and condensation

Fresh water sustains human life and is vital for human health. It is estimated that about 800 million people worldwide lack basic access to drinking water. About 2.2 billion people (nearly one-third of the global population) do not have access to a safe water supply, free of contamination. Also, over 2 billion people live in countries experiencing high water stress. Current supply of fresh water needs to be supplemented to meet future needs. Living nature has evolved species which can survive in the most arid regions of the world by water collection from fog and condensation in the night. Before the collected water evaporates, species have mechanisms to transport water for storage or consumption. These species possess unique chemistry and structures on or within the body for collection and transport of water. In this paper, an overview of arid desert conditions, water sources and plants and animals, lessons from nature for water harvesting, and water harvesting data from fog and condensation are presented. Consumer, emergency and defence applications are discussed and various designs of water harvesting towers and projections for water collection are presented. This article is part of the theme issue 'Bioinspired materials and surfaces for green science and technology (part 3)'.

The 18 O-signal transfer from water vapour to leaf water and assimilates varies among plant species and growth forms

The ¹⁸ O signature of atmospheric water vapour (δ¹⁸ O_V ) is known to be transferred via leaf water to assimilates. It remains, however, unclear how the ¹⁸ O-signal transfer differs among plant species and growth forms. We performed a 9-hr greenhouse fog experiment (relative humidity ≥ 98%) with ¹⁸ O-depleted water vapour (-106.7‰) on 140 plant species of eight different growth forms during daytime. We quantified the ¹⁸ O-signal transfer by calculating the mean residence time of O in leaf water (MRT_LW ) and sugars (MRT_Sugars ) and related it to leaf traits and physiological drivers. MRT_LW increased with leaf succulence and thickness, varying between 1.4 and 10.8 hr. MRT_Sugars was shorter in C₃ and C₄ plants than in crassulacean acid metabolism (CAM) plants and highly variable among species and growth forms; MRT_Sugars was shortest for grasses and aquatic plants, intermediate for broadleaf trees, shrubs, and herbs, and longest for conifers, epiphytes, and succulents. Sucrose was more sensitive to δ¹⁸ O_V variations than other assimilates. Our comprehensive study shows that plant species and growth forms vary strongly in their sensitivity to δ¹⁸ O_V variations, which is important for the interpretation of δ¹⁸ O values in plant organic material and compounds and thus for the reconstruction of climatic conditions and plant functional responses.

From the Sensor to the Cloud: Intelligence Partitioning for Smart Camera Applications

The Internet of Things has grown quickly in the last few years, with a variety of sensing, processing and storage devices interconnected, resulting in high data traffic. While some sensors such as temperature, or humidity sensors produce a few bits of data periodically, imaging sensors output data in the range of megabytes every second. This raises a complexity for battery operated smart cameras, as they would be required to perform intensive image processing operations on large volumes of data, within energy consumption constraints. By using intelligence partitioning we analyse the effects of different partitioning scenarios for the processing tasks between the smart camera node, the fog computing layer and cloud computing, in the node energy consumption as well as the real time performance of the WVSN (Wireless Vision Sensor Node). The results obtained show that traditional design space exploration approaches are inefficient for WVSN, while intelligence partitioning enhances the energy consumption performance of the smart camera node and meets the timing constraints.

Bioinspired triangular patterns for water collection from fog

Cacti use spines with conical geometry to transport water to its base. A conical shape with curvature gradient generates a Laplace pressure gradient along the droplet, which is responsible for droplet motion. In this study, the triangular shape was used which also generates a Laplace pressure gradient along the droplet. A bioinspired surface, composed of a hydrophilic triangular pattern surrounded by a rim of superhydrophobic region, was used to transport water collected from the fog on the hydrophilic pattern. The growing droplets start to coalesce into bigger ones. Eventually, they are big enough to touch the superhydrophobic borders, which trigger the transport motion. Droplet mobility and water collection measurements were made on triangular patterns with various geometries to determine the most efficient configurations. Results from this study can be used to enhance the performance of water collection systems from fog. This article is part of the theme issue 'Bioinspired materials and surfaces for green science and technology (part 2)'.

Water droplet dynamics on bioinspired conical surfaces

Cacti use the Laplace pressure gradient due to conical geometry as a mechanism for collecting water from fog. Bioinspired surfaces using conical geometry can be developed for water collection from fog for human consumption. A systematic study is presented which investigates the dynamics of water droplets on a bioinspired conical surface. A series of experiments was conducted where a known volume of droplets was deposited on the cone. This was followed by an investigation into droplet dynamics where the droplets are deposited from fog and the volume is unknown. This includes a study on the macroscopic level as well as the microscopic level. The main parameters that were varied for these tests were the tip angle and the cone orientation. The droplet movement observed was compared relatively. Based on captured videos of droplet movement, distance travelled and velocities were measured. The Laplace pressure gradient, gravity and droplet coalescence were found to be the mechanisms of droplet movement on a conical surface. The findings of this study should be of interest in designing bioinspired surfaces with high water collection. This article is part of the theme issue 'Bioinspired materials and surfaces for green science and technology (part 2)'.

Bioinspired water collection methods to supplement water supply

Fresh water sustains human life and is vital for human health. Water scarcity affects more than 40% of the global population and is projected to rise. For some of the poorest countries, 1 in 10 people do not have access to safe and easily accessible water sources. Water consumption by man continues to grow with increasing population. Furthermore, population growth and unsafe industrial practices, as well as climate change, have put strain on 'clean' water supply in many parts of the world, including the Americas. Current supply of fresh water needs to be supplemented to meet future needs. Living nature provides many lessons for water source. It has evolved species, which can survive in the most arid regions of the world by water collection from fog and condensation in the night. Before the collected water evaporates, species have mechanisms to transport water for storage or consumption. These species possess unique chemistry and structures on or within the body for collection and transport of water. In this paper, an overview of arid desert conditions and water collection from fog, and lessons from living nature for water collection are provided. Data on various bioinspired surfaces for water collection are also presented. Some bioinspired water purification approaches are presented. Next, consumer to military and emergency applications are discussed and water collection projections are presented. This article is part of the theme issue 'Bioinspired materials and surfaces for green science and technology (part 2)'.

Bioinspired conical design for efficient water collection from fog

Nature is known for using conical shapes to transport the collected water from fog for consumption or storage. The curvature gradient of the conical shape creates a Laplace pressure gradient in the water droplets which drives them towards the region of lower curvature. Linear cones with linearly increasing radii have been studied extensively. A smaller tip angle cone transports water droplets farther because of higher Laplace pressure gradient. Whereas a larger tip angle with a larger surface slope transports water droplets because of higher gravitational forces. In this study, for the first time, a nonlinear cone with a concave profile has been designed with small tip angle and nonlinearly increasing radius to maximize water collection. This article is part of the theme issue 'Bioinspired materials and surfaces for green science and technology (part 2)'.

Dutch fog: On the observed spatio-temporal variability of fog in the Netherlands

The Netherlands is characterized by highly variable land use within a small area, and a strong influence of the North Sea on national climate. Devoid of significant topography, it is an excellent location for assessing the relative influence of various factors on fog occurrence in the absence of terrain effects. Using observations from a dense network of weather stations throughout the country, the climatology of fog in the Netherlands is assessed over a period of 45 years. On a national scale, interannual variability is linked to changes in synoptic pressure-gradient forcing. Within the country, a comprehensive in-depth analysis of regional differences between fog occurrence is made, together with an assessment of local physical factors which could bias fog formation in one location over another. Regional variability is shown to be strongly related to the mesoscale influences of urbanization and the North Sea. In fact, some locations experience over twice as much fog as others. From this finding, a simple index is presented, which combines the water and urban fraction surrounding a station. This "Regionally Weighted Index" (RWI) is able to accurately sort the stations according to their relative fogginess. Its practical use is encouraged for assessing a given site's climatological favourability, even when in situ meteorological observations are unavailable.

Fog Computing Model to Orchestrate the Consumption and Production of Energy in Microgrids

Energy advancement and innovation have generated several challenges for large modernized cities, such as the increase in energy demand, causing the appearance of the small power grid with a local source of supply, called the Microgrid. A Microgrid operates either connected to the national centralized power grid or singly, as a power island mode. Microgrids address these challenges using sensing technologies and Fog-Cloudcomputing infrastructures for building smart electrical grids. A smart Microgrid can be used to minimize the power demand problem, but this solution needs to be implemented correctly so as not to increase the amount of data being generated. Thus, this paper proposes the use of Fog computing to help control power demand and manage power production by eliminating the high volume of data being passed to the Cloud and decreasing the requests’ response time. The GridLab-d simulator was used to create a Microgrid, where it is possible to exchange information between consumers and generators. Thus, to understand the potential of the Fog in this scenario, a performance evaluation is performed to verify how factors such as residence number, optimization algorithms, appliance shifting, and energy sources may influence the response time and resource usage.

On the Combination of Multi-Cloud and Network Coding for Cost-Efficient Storage in Industrial Applications

The adoption of both Cyber–Physical Systems (CPSs) and the Internet-of-Things (IoT) has enabled the evolution towards the so-called Industry 4.0. These technologies, together with cloud computing and artificial intelligence, foster new business opportunities. Besides, several industrial applications need immediate decision making and fog computing is emerging as a promising solution to address such requirement. In order to achieve a cost-efficient system, we propose taking advantage from spot instances, a new service offered by cloud providers, which provide resources at lower prices. The main downside of these instances is that they do not ensure service continuity and they might suffer from interruptions. An architecture that combines fog and multi-cloud deployments along with Network Coding (NC) techniques, guarantees the needed fault-tolerance for the cloud environment, and also reduces the required amount of redundant data to provide reliable services. In this paper we analyze how NC can actually help to reduce the storage cost and improve the resource efficiency for industrial applications, based on a multi-cloud infrastructure. The cost analysis has been carried out using both real AWS EC2 spot instance prices and, to complement them, prices obtained from a model based on a finite Markov chain, derived from real measurements. We have analyzed the overall system cost, depending on different parameters, showing that configurations that seek to minimize the storage yield a higher cost reduction, due to the strong impact of storage cost.

Designing bioinspired surfaces for water collection from fog

A systematic study is presented on various water collectors, bioinspired by desert beetles, desert grass and cacti. Three water collecting mechanisms including heterogeneous wettability, grooved surfaces, and Laplace pressure gradient, were investigated on flat, cylindrical, conical surfaces, and conical array. It is found that higher water repellency in flat surfaces results in higher water collection rate and inclination angle (with respect to the vertical axis) has little effect. Surfaces with heterogeneous wettability have higher water collection rate than surfaces with homogeneous wettability. Both cylindrical and conical surfaces resulted in comparable water collection rate. However, only the cone transported the water droplets to its base. Heterogeneity, higher inclination and grooves increased the water collection rate. A cone has a higher collection rate per unit area than a flat surface with the same wettability. An array of cones has higher collection rate per unit area than a single cone, because droplets in a conical array coalesce, leading to higher frequency of droplets falling. Adding heterogeneity further increases the difference. Based on the findings, scaled-up designs of beetle-, grass- and cactus-inspired surfaces and nets are presented. This article is part of the theme issue 'Bioinspired materials and surfaces for green science and technology'.

Fog and Dew as Potable Water Resources: Maximizing Harvesting Potential and Water Quality Concerns

Fog and dew are often viewed as economic nuisances causing significant financial losses in the transportation industry and agricultural sector. However, they are also critical components of the hydrological cycle, especially in water scarce environments. Water scarcity is one of the major threats to mankind in the 21st century, and this can be due to development pressures, pollution, and/or expanding populations. In water scarce environments, fog and dew represent potentially exploitable ancillary water resources that could ameliorate the water scarce situation, if efficiently harvested. However, two important issues are often overlooked in relation to fog and dew harvesting and potability. First, current fog and dew harvesting technologies are low yielding with great potential for improvements. Second and more importantly, the potability of these water resources is often based on simple analyses that often omit trace metal and biological analyses. The few studies that report trace metal or biological measurements suggest elevated trace metal concentrations or biological contamination that could be of concern to public health. We discuss the potential for fog and dew harvesting technologies and the need for trace metal and biological analyses of these waters before use.

Strategies of leaf water uptake based on anatomical traits

The ability of leaves to absorb fog water can positively contribute to the water and carbon balance of plants in montane ecosystems, especially in periods of soil water deficit. However, the ecophysiological traits and mechanisms responsible for variations in the speed and total water absorption capacity of leaves are still poorly known. This study investigated leaf anatomical attributes of seven species occurring in seasonal tropical high-altitude ecosystems (rocky outcrop and forest), which could explain differences in leaf water uptake (LWU) capacities. We tested the hypothesis that different sets of anatomical leaf attributes will be more marked in plant individuals living under these contrasting environmental conditions. Anatomical variations will affect the initial rate of water absorption and the total storage capacity, resulting in different strategies for using the water supplied by fog events. Water absorption by leaves was inferred indirectly, based on leaf anatomical structure and visual observation of the main access routes (using an apoplastic marker), the diffusion of water through the cuticle, and non-glandular or glandular trichomes in all species. The results suggest that three LWU strategies coexist in the species studied. The different anatomical patterns influenced the speed and maximum LWU capacity. The three LWU strategies can provide different adaptive advantages to adjust to temporal and spatial variations of water availability in these tropical high-altitude environments.

The effect of 18 O-labelled water vapour on the oxygen isotope ratio of water and assimilates in plants at high humidity

Our understanding of how temporal variations of atmospheric water vapour and its isotopic composition (δ¹⁸ O_V ) influence water and assimilates in plants remains limited, restricting our ability to use δ¹⁸ O as a tracer of ecophysiological processes. We exposed oak (Quercus robur) saplings under wet and dry soil moisture conditions to ¹⁸ O-depleted water vapour (c. - 200‰) at high relative humidity (c. 93%) for 5 h, simulating a fog event. We then traced the step change in δ¹⁸ O_V into water and assimilates (e.g. sucrose, hexoses, quercitol and starch) in the leaf lamina, main veins and twigs over 24 h. The immediate δ¹⁸ O_V effect was highest for δ¹⁸ O of leaf lamina water, but 40% lower on δ¹⁸ O of main vein water. To a smaller extent, we also observed changes in δ¹⁸ O of twig xylem water. Depending on the individual assimilation rate of each plant, the ¹⁸ O-label was partitioned among different assimilates, with highest changes in δ¹⁸ O of starch/sucrose and lowest in δ¹⁸ O of quercitol. Additionally, ¹⁸ O-label partitioning and allocation towards leaf starch and twig phloem sugars was influenced by the plant water status. Our results have important implications for water isotope heterogeneity in plants and for our understanding of how the δ¹⁸ O signal is incorporated into biomarkers.

Hydrologic refugia, plants, and climate change

Climate, physical landscapes, and biota interact to generate heterogeneous hydrologic conditions in space and over time, which are reflected in spatial patterns of species distributions. As these species distributions respond to rapid climate change, microrefugia may support local species persistence in the face of deteriorating climatic suitability. Recent focus on temperature as a determinant of microrefugia insufficiently accounts for the importance of hydrologic processes and changing water availability with changing climate. Where water scarcity is a major limitation now or under future climates, hydrologic microrefugia are likely to prove essential for species persistence, particularly for sessile species and plants. Zones of high relative water availability - mesic microenvironments - are generated by a wide array of hydrologic processes, and may be loosely coupled to climatic processes and therefore buffered from climate change. Here, we review the mechanisms that generate mesic microenvironments and their likely robustness in the face of climate change. We argue that mesic microenvironments will act as species-specific refugia only if the nature and space/time variability in water availability are compatible with the ecological requirements of a target species. We illustrate this argument with case studies drawn from California oak woodland ecosystems. We posit that identification of hydrologic refugia could form a cornerstone of climate-cognizant conservation strategies, but that this would require improved understanding of climate change effects on key hydrologic processes, including frequently cryptic processes such as groundwater flow.

Simulation of Driving in Low-Visibility Conditions: Does Stereopsis Improve Speed Perception?

Laboratory-based studies of perceived speed show that, under most circumstances, perceived speed is reduced as a function of contrast. However, a recent investigation of perceived vehicular speed while driving around a closed road circuit showed no such effect (Owens, Wood, & Carberry, 2010, Perception, 39: , 1199-1215). We sought to probe the source of this discrepancy, asking whether the presence or absence of stereoscopic motion information might account for the difference in results. In a two-alternative forced-choice psychophysical speed-discrimination task, observers compared the speed of high- and low-contrast driving clips filmed with a 3-D camera and presented either stereoscopically (3-D) or monoscopically (2-D). Although perceived speed was reduced at low contrast, the size of this misperception was equivalent for 2-D and 3-D presentations. However, the inclusion of stereoscopic cues to vehicular speed caused significant improvements in the precision of speed judgments. It is concluded that although stereopsis can provide access to valuable information on perceived speed, contrast-independent speed estimation as demonstrated by Owens et al. (2010) is more likely to reflect the use of the full visual field in a real driving situation (compared with limited field of view simulations), or the additional contributions of nonvisual cues rather than stereopsis.

Uncoupling apical constriction from tissue invagination

Apical constriction is a widely utilized cell shape change linked to folding, bending and invagination of polarized epithelia. It remains unclear how apical constriction is regulated spatiotemporally during tissue invagination and how this cellular process contributes to tube formation in different developmental contexts. Using Drosophila salivary gland (SG) invagination as a model, we show that regulation of folded gastrulation expression by the Fork head transcription factor is required for apicomedial accumulation of Rho kinase and non-muscle myosin II, which coordinate apical constriction. We demonstrate that neither loss of spatially coordinated apical constriction nor its complete blockage prevent internalization and tube formation, although such manipulations affect the geometry of invagination. When apical constriction is disrupted, compressing force generated by a tissue-level myosin cable contributes to SG invagination. We demonstrate that fully elongated polarized SGs can form outside the embryo, suggesting that tube formation and elongation are intrinsic properties of the SG.

DOI:http://dx.doi.org/10.7554/eLife.22235.001

Many organs in the human body – like the kidneys, lungs, and salivary glands – are organized as a single layer of cells that surround a hollow tube. There are a number of ways that cells can achieve this particular arrangement. In one mechanism, a small group of cells bud out of a single cell layer to become the end of a new tube or a new branch of an existing tube. Since all the cells are still connected, the first cells bring their neighbouring cells along behind them, rearranging these cells to form the walls of a tube.

In addition to changing position, the cells must change their shape to form a tube. One crucial change in cell shape is called apical constriction, and involves the side of the cell facing the inside of the tube becoming smaller than the other sides. This creates cells with a wedge-like shape that can fit together to form the curved wall of the tube, similar to shaped bricks in an archway. Apical constriction has been widely studied and is controlled by proteins that act like motors moving along protein-based filaments; however the roles of apical constriction in tube formation have not been fully explained.

Using the developing salivary glands of the fruit fly Drosophila melanogaster, Chung et al. confirmed that the motor protein known as myosin II controls apical constriction during tissue invagination. Further examination showed that proteins (called Fork Head and Fog) activate and localize an enzyme (Rho kinase) to control the localized accumulation of myosin II and thereby control apical constriction. Chung et al. then showed that salivary glands could still form tubes if apical constriction was blocked, indicating that it is not an essential part of tissue invagination in this organ. However, blocking apical constriction led the tube to develop unusual shapes at intermediate stages.

More work is now needed to better understand the links between apical constriction, cell rearrangement and tissue invagination. These processes are fundamental for organs to form correctly in many organisms and understanding their control could have wide-ranging impacts. A better understanding of these processes may provide insight into how the tubes can form while keeping all the cells adequately supplied with oxygen and nutrients, and into diseases that result if there are defects in the invagination process.

DOI:http://dx.doi.org/10.7554/eLife.22235.002

Emergency Department Visits for Asthma Exacerbation due to Weather Conditions and Air Pollution in Chuncheon, Korea: A Case-Crossover Analysis

Purpose

This retrospective study was conducted to estimate the effects of climate factors and air pollution on asthma exacerbations using a case-crossover analysis.

Methods

Patients who visited the emergency department (ED) of 2 university hospitals in Chuncheon for asthma exacerbations from January 1, 2006, to December 31, 2011, were enrolled. Daily average data for meteorological factors (temperature, daily temperature range, relative humidity, wind speed, atmospheric pressure, presence of rain, solar irradiation, and presence of fog) and the daily average levels of gaseous air pollutants (SO₂, NO₂, O₃, CO, and PM₁₀) were obtained. A case-crossover analysis was performed using variables about the weather and air pollution at 1-week intervals between cases and controls before and after ED visits.

Results

There were 660 ED visits by 583 patients with asthma exacerbations. Low relative humidity (lag 1 and 2) and high wind speed (lag 1, 2, and 3) were associated with ED visits for asthma. Fog (lag 2) showed protective effects against asthma exacerbations in Chuncheon (risk increase: -29.4% [95% CI=-46.3% to -7.2%], P=0.013). These relationships were stronger in patients ≤19 years old than in those >60 years old. High levels of ambient CO (lag 1, 2, and 3) and NO₂ (lag 2 and 3) were associated with decreased ED visits for asthma. However, there were no significant relationships among levels of ambient CO or NO₂ and asthma exacerbations after adjusting for wind speed and relative humidity.

Conclusions

High wind speed and low humidity were associated with an increased risk of asthma ED visits. Fog was associated with a decreased risk of asthma ED visits after controlling for seasonal variations in weather and air pollution.

Cloud forest trees with higher foliar water uptake capacity and anisohydric behavior are more vulnerable to drought and climate change

Many tropical montane cloud forest (TMCF) trees are capable of foliar water uptake (FWU) during leaf-wetting events. In this study, we tested the hypothesis that maintenance of leaf turgor during periods of fog exposure and soil drought is related to species' FWU capacity. We conducted several experiments using apoplastic tracers, deuterium labeling and leaf immersion in water to evaluate differences in FWU among three common TMCF tree species. We also measured the effect of regular fog exposure on the leaf water potential of plants subjected to soil drought and used these data to model species' response to long-term drought. All species were able to absorb water through their leaf cuticles and/or trichomes, although the capacity to do so differed between species. During the drought experiment, the species with higher FWU capacity maintained leaf turgor for a longer period when exposed to fog, whereas the species with lower FWU exerted tighter stomatal regulation to maintain leaf turgor. Model results suggest that without fog, species with high FWU are more likely to lose turgor during seasonal droughts. We show that leaf-wetting events are essential for trees with high FWU, which tend to be more anisohydric, maintaining leaf turgor during seasonal droughts.

Bark water uptake promotes localized hydraulic recovery in coastal redwood crown

Coastal redwood (Sequoia sempervirens), the world's tallest tree species, rehydrates leaves via foliar water uptake during fog/rain events. Here we examine if bark also permits water uptake in redwood branches, exploring potential flow mechanisms and biological significance. Using isotopic labelling and microCT imaging, we observed that water entered the xylem via bark and reduced tracheid embolization. Moreover, prolonged bark wetting (16 h) partially restored xylem hydraulic conductivity in isolated branch segments and whole branches. Partial hydraulic recovery coincided with an increase in branch water potential from about -5.5 ± 0.4 to -4.2 ± 0.3 MPa, suggesting localized recovery and possibly hydraulic isolation. As bark water uptake rate correlated with xylem osmotic potential (R(2)  = 0.88), we suspect a symplastic role in transferring water from bark to xylem. Using historical weather data from typical redwood habitat, we estimated that bark and leaves are wet more than 1000 h per year on average, with over 30 events being sufficiently long (>24 h) to allow for bark-assisted hydraulic recovery. The capacity to uptake biologically meaningful volumes of water via bark and leaves for localized hydraulic recovery throughout the crown during rain/fog events might be physiologically advantageous, allowing for relatively constant transpiration.