Uncertainty In Environmental Conditions Research Articles

The Effect of Spatially Correlated Errors on Sea Surface Height Retrieval from SWOT Altimetry

The upcoming technology of wide-swath altimetry from space will enable monitoring the ocean surface at 4–5 times better spatial resolution and 2–3 times better accuracy than traditional nadir altimeters. This development will provide a chance to directly observe submesoscale sea surface height (SSH) variations that have a typical magnitude of a few centimeters. Taking full advantage of this opportunity requires correct treatment of the correlated SSH errors caused by uncertainties in environmental conditions beneath the satellite and in the geometry and orientation of the on-board interferometer. These observation errors are highly correlated both along and across the surface swath scanned by the satellite, and this presents a significant challenge for accurate processing. In particular, the SWOT precision matrix has off-diagonal elements that are too numerous to allow standard approaches to remain tractable. In this study, we explore the utility of a block-diagonal approximation to the SWOT precision matrix in order to reconstruct SSH variability in the region east of Greenland. An extensive set of 2dVar assimilation experiments demonstrates that the sparse approximation proposed for the precision matrix provides accurate SSH retrievals when the background-to-observation error ratio ν does not exceed 3 and significant wave height is below 2.5 m. We also quantify the range of ν and significant wave heights over which the retrieval accuracy of the exact spatially correlated SWOT error model will outperform the uncorrelated model. In particular, the estimated range is found to be substantially wider (ν<10 with significant wave heights below 8–10 m), indicating the potential benefits of further improving the accuracy of approximations for the SWOT precision matrix.

Exploring environmental and physiological drivers of the annual carbon budget of biocrusts from various climatic zones with a mechanistic data-driven model

Abstract. Biocrusts are a worldwide phenomenon, contributing substantially to ecosystem functioning. Their growth and survival depend on multiple environmental factors, including climatic ones, and the relations of these factors to physiological processes. Responses of biocrusts to individual environmental factors have been examined in a large number of field and laboratory experiments. These observational data, however, have rarely been assembled into a comprehensive, consistent framework that allows quantitative exploration of the roles of multiple environmental factors and physiological properties for the performance of biocrusts, in particular across climatic regions. Here we used a data-driven mechanistic modelling framework to simulate the carbon balance of biocrusts, a key measure of their growth and survival. We thereby assessed the relative importance of physiological and environmental factors for the carbon balance at six study sites that differ in climatic conditions. Moreover, we examined the role of seasonal acclimation of physiological properties using our framework, since the effects of this process on the carbon balance of biocrusts are poorly constrained so far. We found substantial effects of air temperature, CO2 concentration, and physiological parameters that are related to respiration on biocrust carbon balance, which differ, however, in their patterns across regions. The ambient CO2 concentration is the most important factor for biocrusts from drylands, while air temperature has the strongest impact at alpine and temperate sites. Metabolic respiration cost plays a more important role than optimum temperature for gross photosynthesis at the alpine site; this is not the case, however, in drylands and temperate regions. Moreover, we estimated a small annual carbon gain of 1.5 gm-2yr-1 by lichen-dominated biocrust and 1.9 gm-2yr-1 by moss-dominated biocrust at a dryland site, while the biocrusts lost a large amount of carbon at some of the temperate sites (e.g. −92.1 for lichen-dominated and −74.7 gm-2yr-1 for moss-dominated biocrust). These strongly negative values contradict the observed survival of the organisms at the sites and may be caused by the uncertainty in environmental conditions and physiological parameters, which we assessed in a sensitivity analysis. Another potential explanation for this result may be the lack of acclimation in the modelling approach, since the carbon balance can increase substantially when testing for seasonally varying parameters in the sensitivity analysis. We conclude that the uncertainties in air temperature, CO2 concentration, respiration-related physiological parameters, and the absence of seasonal acclimation in the model for humid temperate and alpine regions may be a relevant source of error and should be taken into account in future approaches that aim at estimating the long-term biocrust carbon balance based on ecophysiological data.

The Influence Of Technological Capability, Social Capital, and Entrepreneurial Orientation On Firm Performance Through Absorptive Capacity In Food and Beverage Packaging Industry Companies

The purpose of this study is to present a model that illustrates the general influence of technological capability, social capital, entrepreneurial orientation on firm performance through absorptive capacity in the food and beverage packaging industry in Indonesia. The model proposed in this study was tested with a structural equation model. This study processed data from 168 respondents of manager-level employees to the company owner level in the food and beverage packaging industry. This study found that technological capability, social capital and absorptive capacity have a positive and significant effect on firm performance. Meanwhile, entrepreneurial orientation has a positive but not significant effect on firm performance. This study found that technological capability, social capital and absorptive capacity have a positive and significant effect on firm performance. Meanwhile, entrepreneurial orientation has a positive but not significant effect on firm performance. Absorptive capacity mediates the relationship between technological capability and social capital to firm performance and absorptive capacity fully mediates the relationship between entrepreneurial orientation and firm performance. This research model only limits the factors that affect company performance to four main variables, namely technological capability, social capital, entrepreneurial orientation and absorptive capacity. Further research is suggested to use samples in other industries and add other variables such as uncertainty or uncertainty of environmental conditions as moderation variables. The practical implications of this research are that companies need to do three things if they want to get the benefits of entrepreneurial orientation and absorptive capacity to improve firm performance. Further research is suggested to use samples in other industries and add other variables such as uncertainty or uncertainty of environmental conditions as moderation variables. The practical implications of this research are that companies need to do three things if they want to get the benefits of entrepreneurial orientation and absorptive capacity to improve firm performance. The new knowledge gained is very helpful for companies to determine strategies, levels of innovation, proactiveness and high-risk decisions, especially when there is uncertainty in the industrial environment. This study presents the mediating function of absorptive capability tested simultaneously with the variables technological capability, social capital, entrepreneurial orientation is something new from this study compared to previous studies. The findings in this study also provide an additional contradictory list of previous studies on the relationship between entrepreneurial orientation and firm performance.

Characterization of continuum robot arms under reinforcement learning and derived improvements.

In robotics, soft continuum robot arms are a promising prospect owing to their redundancy and passivity; however, no comprehensive study exists that examines their characteristics compared to rigid manipulators. In this study, we examined the advantages of a continuum robot arm as compared to a typical and rigid seven-degree-of-freedom (7-DoF) robot manipulator in terms of performing various tasks through reinforcement learning. We conducted simulations for tasks with different characteristics that require control over position and force. Common tasks in robot manipulators, such as reaching, crank rotation, object throwing, and peg-in-hole were considered. The initial conditions of the robot and environment were randomized, aiming for evaluations including robustness. The results indicate that the continuum robot arm excels in the crank-rotation task, which is characterized by uncertainty in environmental conditions and cumulative rewards. However, the rigid robot arm learned better motions for the peg-in-hole task than the other tasks, which requires fine motion control of the end-effector. In the throwing task, the continuum robot arm scored well owing to its good handling of anisotropy. Moreover, we developed a reinforcement-learning method based on the comprehensive experimental results. The proposed method successfully improved the motion learning of a continuum robot arm by adding a technique to regulate the initial state of the robot. To the best of our knowledge, ours is the first reinforcement-learning experiment with multiple tasks on a single continuum robot arm and is the first report of a comparison between a single continuum robot arm and rigid manipulator on a wide range of tasks. This simulation study can make a significant contribution to the design of continuum arms and specification of their applications, and development of control and reinforcement learning methods.

Multiple-batch spawning: a risk-spreading strategy disarmed by highly intensive size-selective fishing rate.

Can the advantage of risk-managing life-history strategies become a disadvantage under human-induced evolution? Organisms have adapted to the variability and uncertainty of environmental conditions with a vast diversity of life-history strategies. One such evolved strategy is multiple-batch spawning, a spawning strategy common to long-lived fishes that ‘hedge their bets' by distributing the risk to their offspring on a temporal and spatial scale. The fitness benefits of this spawning strategy increase with female body size, the very trait that size-selective fishing targets. By applying an empirically and theoretically motivated eco-evolutionary mechanistic model that was parameterized for Atlantic cod (Gadus morhua), we explored how fishing intensity may alter the life-history traits and fitness of fishes that are multiple-batch spawners. Our main findings are twofold; first, the risk-spreading strategy of multiple-batch spawning is not effective against fisheries selection, because the fisheries selection favours smaller fish with a lower risk-spreading effect; and second, the ecological recovery in population size does not secure evolutionary recovery in the population size structure. The beneficial risk-spreading mechanism of the batch spawning strategy highlights the importance of recovery in the size structure of overfished stocks, from which a full recovery in the population size can follow.

Can the operating limits of biogas plants operated under non-isothermal conditions be defined with certainty? Modeling self-optimizing attainable regions

Uncertainty in operating parameters such as temperature undermines the reliability of using kinetic models in performance projections for plants operated under ambient non-isothermal conditions. This study develops a theoretical framework, which uses process kinetics, uncertainty quantification to define robust operating limits known as self-optimizing attainable regions, where by instead of defining a very large operating limit, which will be achieved some of the times for some of the reactor configurations, we define a self-optimizing limit, which will be achieved all the times for all possible reactor configurations (despite variations in temperature). Using a temperature range of 20 – 60∘C, , the results indicate that decreasing temperature uncertainty, increasing process temperature or using a multistage digester structure increases the self-optimizing operating limits: 1.53×10−4, 4.95×10−4 and 6.32×10−4(g/L)2 obtained for temperatures of 20.00, 31.60 and 52.40∘C respectively. The findings highly important in defining performance targets especially when there is uncertainty in environmental conditions.

Estimating the predictability of evolution

Evolutionary Ecology Evolution results from expected effects, such as selection driving alleles toward fixation, and stochastic effects, such as unusual environmental variation and genetic drift. To determine the potential to predict evolutionary change, Nosil et al. examined three naturally occurring morphs of stick insects (see the Perspective by Reznick and Travis). They wanted to determine which selective parameters could be used to foresee changes, despite varying environmental conditions. One morph fit a model of negative frequency-dependent selection, likely owing to predation, but changes in other morph frequencies remained unpredictable. Thus, for specific cases, we can forecast short-term changes within populations, but evolution is more difficult to predict when it involves a balance between multiple selective factors and uncertainty in environmental conditions. Science , this issue p. [765][1]; see also p. [738][2] [1]: /lookup/doi/10.1126/science.aap9125 [2]: /lookup/doi/10.1126/science.aas9043

Natural selection and the predictability of evolution in Timema stick insects.

Predicting evolution remains difficult. We studied the evolution of cryptic body coloration and pattern in a stick insect using 25 years of field data, experiments, and genomics. We found that evolution is more difficult to predict when it involves a balance between multiple selective factors and uncertainty in environmental conditions than when it involves feedback loops that cause consistent back-and-forth fluctuations. Specifically, changes in color-morph frequencies are modestly predictable through time (r2 = 0.14) and driven by complex selective regimes and yearly fluctuations in climate. In contrast, temporal changes in pattern-morph frequencies are highly predictable due to negative frequency-dependent selection (r2 = 0.86). For both traits, however, natural selection drives evolution around a dynamic equilibrium, providing some predictability to the process.

Distributed Control Method for Economic Dispatch in Islanded Microgrids With Renewable Energy Sources

The economic dispatch in islanded microgrids (MGs) is a thorny problem due to the low equivalent inertia and the uncertainty of environmental conditions. In this paper, a two-layer model is proposed for economic dispatch in islanded MGs, in which an MG is considered as the lower layer, while a communication network is considered as the upper layer. Furthermore, a systematic method is presented to derive fully distributed control laws from any given communication network. On the communication network, there are two subgraphs, G̃ and Ĝ, one of which consists of all agents, while the other of which consists of only controllable agents. Correspondingly, two sets of control laws are derived from the two subgraphs, where the control laws from the subgraph G̃ ensure the supply-demand balance in the MG, while the control laws from the subgraph Ĝ realize the economic dispatch. Moreover, the economic operation in MGs can be satisfied, only if agents on the communication network regulate distributed generators iteratively according to the control laws. Finally, three cases are designed to evaluate the performance of the method, and the simulation results verify the effectiveness of the proposed method.

Probabilistic lifetime performance and structural capacity analysis of continuous reinforced concrete slab bridges

A reliability-based method was developed for predicting the initiation time and the probability of flexural failure for continuous slab bridges with load-induced cracks exposed to chloride environment resulting from de-icing salts. A practical methodology was used for predicting the diffusion coefficient of chloride ingress into the pre-existing load-induced cracks in concrete. The reduction in the cross-sectional area of the reinforcement due to corrosion was included in the model. The proposed methodology accounts for uncertainties in the strength demand, structural capacity, and corrosion models, as well as uncertainties in environmental conditions, material properties, and structural geometry. All probabilistic data on uncertainties were estimated from the information contained in previous experimental and statistical studies. As an application of the proposed model, a three-span continuous slab bridge in Ohio is presented for demonstration of the developed methodology. A comparison of results clearly shows the importance of considering the effects of the load-induced cracks for correct prediction of the initiation of corrosion time and the critical time to maintain structural integrity.

The importance of biotic interactions for the prediction of macroinvertebrate communities under multiple stressors

Summary The community assembly of macroinvertebrates in streams depends on the regional taxon pool, dispersal limitations, local habitat conditions and biotic interactions. By integrating existing knowledge about these processes from theoretical ecology in a mechanistic model, we can test our mechanistic understanding and disentangle multiple stressor effects on community assembly. To assess to which degree we can predict the community composition of macroinvertebrates, we integrated these processes in the mechanistic food web model Streambugs and tested it on 36 sites in the Glatt catchment on the Swiss plateau. The model predicts the observation probability of taxa from a regional taxon pool at each site taking into account uncertain knowledge on parameters, environmental conditions at the sites and sampling errors. We use allometric scaling according to the metabolic theory of ecology, ecological stoichiometry and autecological data from trait databases that include the current knowledge on habitat requirements of the different taxa to parameterize their growth, respiration and death. Without any calibration, for the majority of taxa at the 36 sites, the difference between the observed and predicted relative frequency of occurrence is <50% when taking prior parameter uncertainty and the uncertainty of environmental conditions into account (79% compared to 61% for the random model). By calibrating taxon‐specific modification factors for the growth rate, we can increase the model compliance with data. Analysing the influence of different ecological traits and their corresponding environmental influence factors reveals that feeding types and sensitivity to organic toxicants contribute most to the predictive capabilities of the model in this catchment. The influence of temperature stress and oxygen depletion due to pollution with organic matter on the community composition is negligible. These results confirm our expectations regarding the most important water quality issues of streams on the Swiss plateau. Current velocity plays an intermediate role in this model application. The contribution of the feeding types to model performance highlights the importance of taking biotic interactions (competition for food sources and predator–prey interactions) into account to predict the coexistence of taxa. Better knowledge of the actual feeding links in the food web (e.g. from gut content or stable isotope data) that are currently inferred from feeding types, body size and food availability could further improve this approach.

Reliability-based design method of suppressing chloride ingress for reinforced concrete buildings located in coastal regions of Taiwan

The main purpose of this work is to propose an estimating procedure that building designers can use to choose methods of suppressing chloride ingress, i.e. concrete-cover thickness, concrete-surface coating and concrete mix (water–cement ratio), for reinforced concrete (RC) buildings with a specified durability performance. At first, the authors build equations for estimating airborne chloride concentrations in coastal regions in Taiwan by regressing measurement data. Then, an analytical model incorporates these data into a deterioration model for chloride-induced corrosion and to estimate corrosion of reinforcing steel bars. This work also presents a novel computational procedure to calculate the risk of corrosion for reinforcing steel bars embedded in concrete, while considering uncertainties in environmental conditions, material properties and model error. Using risk curves of corrosion, building designers can set an allowable durable reliability to determine the minimal required concrete-cover thickness for RC members. Finally, this work adopts coastal regions in Taiwan as an example to determine the minimum required concrete-cover thicknesses. Furthermore, reliability-based methods of suppressing chloride ingress for RC buildings are also suggested for each division zone of Taiwan.

Uncertainty and confidence from the triple-network perspective: Voxel-based meta-analyses

Our subjective confidence about particular events is related to but independent from the objective certainty of the stimuli we encounter. Surprisingly, previous investigations of the neurophysiological correlates of confidence and uncertainty have largely been carried out separately. After systematically reviewing the blood oxygenation-level dependent functional magnetic resonance imaging (BOLD fMRI) literature, and splitting studies on the basis of their task requirements, a voxel-based meta-analysis was performed to identify: (i) those regions which are replicably modulated by the uncertainty of environmental conditions; (ii) those regions whose activity is robustly affected by our subjective confidence; and (iii) those regions differentially activated at these contrasting times. In further meta-analyses the consistency of activation between these judgement types was assessed. Increased activation was consistently observed in the salience (anterior cingulate cortex and insula) and central executive network (dorsolateral prefrontal and posterior parietal cortices) in conditions of increased uncertainty; by contrast, default mode network (midline cortical and medial temporal lobe) regions robustly exhibited a positive relationship with subjective confidence. Regions including right parahippocampal gyrus were positively modulated by magnitude across both certainty and confidence judgements. This region was also shown to be more significantly modulated by confidence magnitude as compared with degree of environmental certainty. The functional and methodological implications of these findings are discussed with a view to improving future investigation of the neural basis of metacognitive judgement.

A review of and some comments on the attempts to construct an overarching theory of ecosystems plasticity

It is generally accepted that life uses two distinct mechanisms during adaptation to the environment: evolutionary and individual. The latter is known as phenotypic plasticity. However, several decades ago, a conviction emerged and later strengthened that populations and ecological communities also tend to stabilize the essential variables (total biomass, productivity, adaptability, etc.) to a certain degree, regardless of uncertainty of environmental conditions. A response to this uncertainty is a change in the frequency of preadapted genotypes and compensatory fluctuations in population sizes. Adaptation can be regarded as a never-ending multilevel hierarchical process of individual-, population- and community-level adjustments to a changing environment. According to these concepts, adaptation is like a process during which individuals, populations and entire communities can adjust their optima to the ever-changing environmental conditions. Individual and populational rearrangements are means for a more subtle adjustment of the community optimum and the lines of defence, one following the other, on the road of stressful impacts towards the essential variables of an ecosystem. The authors of this conception, e. g. M. Conrad, V. N. Novoseltsev, H.-R. Gregorius, E. Lekevicius, also believe that these mechanisms should interact in a quite determined manner; this brings us hope that a unified theory on the plasticity of ecosystems will be developed. In this review an attempt is made to describe these concepts which are still in development and to reveal their strong, well-founded aspects as well as weak points. It is concluded that the multifarious attempts to falsify the conception are needed.

Probabilistic capacity models and seismic fragility estimates for RC columns subject to corrosion

In this paper, probabilistic drift and shear force capacity models are developed for corroding reinforced concrete (RC) columns. The developments represent a merger between a probabilistic model for chloride-induced corrosion, a time-dependent corrosion rate, and previously developed probabilistic models for drift and shear force capacity of pristine (undamaged) RC columns. Fragility estimates are obtained for an example corroding column by applying the developed models at given shear and drift demands. Model uncertainties in both the capacity and corrosion models are considered in the fragility estimation, in addition to uncertainties in environmental conditions, material properties, and structural geometry. Sensitivity analyses of the corroding RC column are carried out to identify the parameters to which the reliability of the example column is most sensitive. The developed models consider different combinations of chloride exposure condition, environmental oxygen availability, water-to-cement ratios, and curing conditions. They are applicable to both existing and new RC columns and may be employed for the prediction of service-life and life-cycle cost analysis of RC structures.

Long-Term Behavior of Timber–Concrete Composite Beams. I: Finite Element Modeling and Validation

This first part of two companion papers deals with the numerical modeling of timber–concrete composite beams (TCCs) under long-term loading. All phenomena affecting the long-term behavior of timber, concrete, and the connection system, such as creep, mechanosorptive creep, shrinkage/swelling, and temperature variations, are fully considered. The structural problem is solved through a uniaxial finite element model with flexible connection and a step-by-step numerical procedure over time. The important role played by the environmental thermohygrometric variations on TCCs is highlighted through some analyses. The proposed numerical procedure is validated on two long-term experimental tests in outdoor conditions. Despite some uncertainties in environmental conditions and material properties, a good fit between experimental and numerical results is obtained. A parametric analysis is performed in the second part, showing the contribution of different rheological phenomena and thermohygrometric variations on beam deflection and connection slip. Based on results carried out, a simplified approach for long-term evaluation of TCCs is then proposed.