Spatiotemporal Complexity Research Articles

‘You can’t just be a Muslim in outer space’: young people making sense of religion at local places in the city

ABSTRACT This paper demonstrates how young people make sense of religion through local places in the urban context while moving from youth to young adulthood. We draw on in-depth interviews – including a mental map-making exercise – with twenty-four young Muslims (18–30) from a wide range of cultural backgrounds living in Metro Vancouver (Canada). Their narratives reveal young people ‘live’ religion in various local places and how spatialities of lived religion change over time. We highlight how making sense of religion is reflected in the changing meaning of the mosque and relates to the increased salience of places shared with young Muslims in which our participants negotiate religion in the context of their everyday lives in the city. While many studies on Muslim identities have established the complexities and dynamics of negotiating religion at specific local places, we argue for a focus on relations between lived religion at various local places over time. These spatiotemporal complexities are able to capture how making sense of religion is spatially and fluidly manifested in the urban context of Metro Vancouver.

Multiscale Patterning from Competing Interactions and Length Scales

We live in a research era marked by impressive new tools powering the scientific method to accelerate the discovery, prediction, and control of increasingly complex systems. In common with many disciplines and societal challenges and opportunities, materials and condensed matter sciences are beneficiaries. The volume and fidelity of experimental, computational, and visualization data available, and tools to rapidly interpret them, are remarkable. Conceptual frameworks, including multiscale, multiphysics modeling of this complexity, are fueled by the data and, in turn, guide directions for future experimental and computational strategies. In this spirit, I discuss the importance of competing interactions, length scales, and constraints as pervasive sources of spatiotemporal complexity. I use representative examples drawn from materials and condensed matter, including the important role of elasticity in some technologically important quantum materials. Expected final online publication date for the Annual Review of Materials Research, Volume 50 is July 1, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Integrated energy scheduling and routing for a network of mobile prosumers

Due to the spatio-temporal complexity in energy consumption profiles of multiple consumers at different regions, it is expected that more cost savings and higher resiliency to power disruptions can be achieved using a network of mobile prosumers. In this paper, the prosumer is assumed to be an autonomous vehicle equipped with different distributed energy resources (e.g., solar panel, battery) that cannot only provide but also consume energy. An integrated vehicle routing and energy scheduling decision model is developed to adaptively dispatch vehicles to balance the temporally and spatially distributed energy requests subject to vehicle mobility constraints, and thus to maximally exploit the potentials of mobile prosumer network for cost savings and carbon emission reductions. The performances of the integrated decision model are evaluated using three metrics including operational costs, energy requested from power grids, and carbon emissions. The simulation results demonstrate that compared to disjoint vehicle routing and energy scheduling model, the proposed integrated decision model (i) is more efficient to shift energy loads at both temporal and spatial scales, and (ii) can save up to 38% of operational costs, reduce up to 29% of energy requested from power grids, and reduce up to 27% of carbon emissions.

Digital transformation of obtaining data for an express assessment of regional sustainable development

Sustainable development of the Russian Federation is impossible without the sustainable development of its regions. To make managerial decisions aimed at sustainable development of the regions, it is necessary to carry out appropriate monitoring. It is proposed to use the methodology and tools of an express assessment, which are based on the dynamics of wages at the enterprises of the region, as operational control over the processes taking place in the economy of the regions. This is due to the fact that in a market economy there is a clear direct relationship between the timeliness and size of wages paid to employees and the state of corporate businesses. The aim of this study is to select the optimal data acquisition scheme for an express assessment of the sustainable development of the regions. For this purpose, a comparative analysis of three schemes for obtaining paper-based data was applied, using personal accounts on the Internet and the information system of the Federal State Statistics Service using the system of interdepartmental electronic exchange in terms of the following indicators: completeness, delay and discreteness of the wages reflection and the number of enterprises in the region in the digital spatio-temporal model and complexity of organizational measures. It has been established that in the near future, it will the most effective to use the scheme for obtaining data from the Internet, which provides high completeness of reflection of the source data and minimizes the delay time of an express assessment relative to the real state of the regional economy. This creates objective conditions for the rapid identification of trends in the regional economy and contributes to the timely formation of legislative initiatives and the adoption of managerial decisions by the regional legislative and executive authorities to improve the legal framework conducive to business development in the region. The data collected by state statistics bodies as per the form No. P-4 “Information on the wages and number of employees” can also serve as a source for an express assessment. However, the federal law currently prohibits state statistics from providing access to this information to regional executive bodies.

Dynamical complexities and pattern formation in an eco-epidemiological model with prey infection and harvesting

In this work, we have studied the emergence of complex dynamics in a hypertrophic lake ecosystem. We have proposed and analysed a three-tier spatio-temporal predator–prey model in which the prey population is influenced by infection, diffusion, and harvesting. In the absence of diffusion, existence conditions of biologically feasible equilibrium points with their stability properties and bifurcations have been discussed. We observe that the non-diffusive system exhibits a variety of bifurcations such as saddle-node, transcritical and undergoes for a supercritical Hopf-bifurcation. In the spatio-temporal system, all possible conditions for Turing instability are derived. The complex behaviour of the system is shown through some interesting numerical examples. Phase portraits, time evolution diagrams, and numerical bifurcation diagrams show the ecological complexity of the degraded lake ecosystem. Diffusion driven spatio-temporal complexity is investigated with the help of pattern formulation. Various spatial patterns reveal that degradation has the potential to alter fish spatial distributions in the lake.

Controlling the Multifractal Generating Measures of Complex Networks

Mathematical modelling of real complex networks aims to characterize their architecture and decipher their underlying principles. Self-repeating patterns and multifractality exist in many real-world complex systems such as brain, genetic, geoscience, and social networks. To better comprehend the multifractal behavior in the real networks, we propose the weighted multifractal graph model to characterize the spatiotemporal complexity and heterogeneity encoded in the interaction weights. We provide analytical tools to verify the multifractal properties of the proposed model. By varying the parameters in the initial unit square, the model can reproduce a diverse range of multifractal spectrums with different degrees of symmetry, locations, support and shapes. We estimate and investigate the weighted multifractal graph model corresponding to two real-world complex systems, namely (i) the chromosome interactions of yeast cells in quiescence and in exponential growth, and (ii) the brain networks of cognitively healthy people and patients exhibiting late mild cognitive impairment leading to Alzheimer disease. The analysis of recovered models show that the proposed random graph model provides a novel way to understand the self-similar structure of complex networks and to discriminate different network structures. Additionally, by mapping real complex networks onto multifractal generating measures, it allows us to develop new network design and control strategies, such as the minimal control of multifractal measures of real systems under different functioning conditions or states.

CityScapeLab Berlin: A Research Platform for Untangling Urbanization Effects on Biodiversity

Urban biodiversity conservation requires an understanding of how urbanization modulates biodiversity patterns and the associated ecosystem services. While important advances have been made in the conceptual development of urban biodiversity research over the last decades, challenges remain in understanding the interactions between different groups of taxa and the spatiotemporal complexity of urbanization processes. The CityScapeLab Berlin is a novel experimental research platform that allows the testing of theories on how urbanization affects biodiversity patterns and biotic interactions in general and the responses of species of conservation interest in particular. We chose dry grassland patches as the backbone of the research platform because dry grasslands are common in many urban regions, extend over a wide urbanization gradient, and usually harbor diverse and self-assembled communities. Focusing on a standardized type of model ecosystem allowed the urbanization effects on biodiversity to be unraveled from effects that would otherwise be masked by habitat- and land-use effects. The CityScapeLab combines different types of spatiotemporal data on (i) various groups of taxa from different trophic levels, (ii) environmental parameters on different spatial scales, and (iii) on land-use history. This allows for the unraveling of the effects of current and historical urban conditions on urban biodiversity patterns and the related ecological functions.

The Hierarchic Treatment of Marine Ecological Information from Spatial Networks of Benthic Platforms.

Measuring biodiversity simultaneously in different locations, at different temporal scales, and over wide spatial scales is of strategic importance for the improvement of our understanding of the functioning of marine ecosystems and for the conservation of their biodiversity. Monitoring networks of cabled observatories, along with other docked autonomous systems (e.g., Remotely Operated Vehicles [ROVs], Autonomous Underwater Vehicles [AUVs], and crawlers), are being conceived and established at a spatial scale capable of tracking energy fluxes across benthic and pelagic compartments, as well as across geographic ecotones. At the same time, optoacoustic imaging is sustaining an unprecedented expansion in marine ecological monitoring, enabling the acquisition of new biological and environmental data at an appropriate spatiotemporal scale. At this stage, one of the main problems for an effective application of these technologies is the processing, storage, and treatment of the acquired complex ecological information. Here, we provide a conceptual overview on the technological developments in the multiparametric generation, storage, and automated hierarchic treatment of biological and environmental information required to capture the spatiotemporal complexity of a marine ecosystem. In doing so, we present a pipeline of ecological data acquisition and processing in different steps and prone to automation. We also give an example of population biomass, community richness and biodiversity data computation (as indicators for ecosystem functionality) with an Internet Operated Vehicle (a mobile crawler). Finally, we discuss the software requirements for that automated data processing at the level of cyber-infrastructures with sensor calibration and control, data banking, and ingestion into large data portals.

Impact of Land-Use Changes on Spatiotemporal Suspended Sediment Dynamics within a Peri-Urban Catchment

Understanding sediment dynamics in peri-urban catchments constitutes a research challenge because of the spatiotemporal complexity and variability of land-uses involved. This study investigates differences in the concentration of total sediments (TSC) and suspended sediments (SSC) in the small peri-urban Mediterranean Ribeira dos Covões catchment (40% urban area) in central Portugal. Suspended sediment responses at the catchment outlet (E) and in three upstream sub-catchments, during periods of urbanization (2011–2013) and stabilizing land-use (2017–2018) are compared for storm-event datasets encompassing similar ranges of rainstorm sizes and antecedent rainfall condition. The Quinta sub-catchment, with the lowest urban area (22%) but subject to major construction activities affecting 17% of its area, led to highest TSC and SSC during urbanization (attaining 4320 mg/L and 4184 mg/L, respectively), and a median reduction of 38% and 69%, respectively, during stabilization. Espírito Santo sub-catchment, with highest urban area (49%) and minor construction activities, displayed similar median TSC in both periods (258–240 mg/L) but highest SSC reduction (76%), highlighting the impact of the anthropogenic disturbance mainly on fine-particle sediments and a good connectivity with the stream. Porto Bordalo sub-catchment, with 39% urban area and subject to the construction of a four-line road covering 1.5% of its area, showed the lowest TSC and SSC concentrations and the lowest median reductions in both periods (31% and 64%, correspondingly), mainly because of the impact of an unplanned retention basin established with soil from the construction site. Overall, median TSC and SSC reduced 14% and 59% at E, from urbanization to stabilization. Information about sediment dynamics should guide stakeholders in establishing strategies to reduce sediment loads and mitigate the impacts on urban aquatic ecosystems.

Random Fields Simplified: Preserving Marginal Distributions, Correlations, and Intermittency, With Applications From Rainfall to Humidity

AbstractNature manifests itself in space and time. The spatiotemporal complexity of processes such as precipitation, temperature, and wind, does not allow purely deterministic modeling. Spatiotemporal random fields have a long history in modeling such processes, and yet a single unified framework offering the flexibility to simulate processes that may differ profoundly does not exist. Here we introduce a blueprint to efficiently simulate spatiotemporal random fields that preserve any marginal distribution, any valid spatiotemporal correlation structure, and intermittency. We suggest a set of parsimonious yet flexible marginal distributions and provide a rule of thumb for their selection. We propose a new and unified approach to construct flexible spatiotemporal correlation structures by combining copulas and survival functions. The versatility of our framework is demonstrated by simulating conceptual cases of intermittent precipitation, double‐bounded relative humidity, and temperature maxima fields. As a real‐word case we simulate daily precipitation fields. In all cases, we reproduce the desired properties. In an era characterized by advances in remote sensing and increasing availability of spatiotemporal data, we deem that this unified approach offers a valuable and easy‐to‐apply tool for modeling complex spatiotemporal processes.

Changing Climate Drives Divergent and Nonlinear Shifts in Flowering Phenology across Elevations

Climate change is known to affect regional weather patterns and phenology; however, we lack understanding of how climate drives phenological change across local spatial gradients. This spatial variation is critical for determining whether subpopulations andmetacommunities are changing in unison or diverging in phenology. Divergent responses could reduce synchrony both within species (disrupting gene flow among subpopulations) and among species (disrupting interspecific interactions in communities). We also lack understanding of phenological change in environments where life history events are frequently aseasonal, such as the tropical, arid, and semi-arid ecosystems that cover vast areas. Using a 33-year-long dataset spanning a 1,267-m semi-arid elevational gradient in the southwestern United States, we test whether flowering phenology diverged among subpopulations within species andamong five communities comprising 590 species. Applying circular statistics to test for changes in year-round flowering, we show flowering has become earlier for all communities except at the highest elevations. However, flowering times shifted at different rates across elevations likely because ofelevation-specific changes in temperature and precipitation, indicating diverging phenologies of neighboring communities. Subpopulations of individual species also diverged at mid-elevation but converged in phenology at high elevation. These changes in flowering phenology among communities and subpopulations are undetectable when data are pooled across the gradient. Furthermore, we show that nonlinear changes in flowering times over the 33-year record are obscured by traditional calculations of long-term trends. These findings reveal greater spatiotemporal complexity in phenological responses than previously recognized and indicate climate is driving phenological reshuffling across local spatial gradients.

Spatiotemporal complexity of a diffusive planktonic system with prey-taxis and toxic effects

In this paper, we propose a three-species reaction-diffusion planktonic system with prey-taxis and toxic effects, in which the zooplankton can recognize the nontoxic and toxin-producing phytoplankton and can make proper response. We first establish the existence and stability of the unique positive constant equilibrium solution by utilizing the linear stability theory for partial differential equations. Then we obtain the existence and properties of nonconstant positive solutions by detailed steady state bifurcation analysis. In addition, we obtain that change of taxis rate will result in the appearance of time-periodic solutions. Finally, we conduct some numerical simulations and give the conclusions.

Comprehensive Criteria-Based Generalized Steganalysis Feature Selection Method

Redundant steganalysis feature components in high-dimensional steganalysis feature of images increase the spatio-temporal complexity of steganalysis and even reduce the detection accuracy of the stego images. In order to reduce the image steganalysis feature dimension, improve the detection accuracy of the stego images and achieve fast feature selection, this paper proposes a general method for image steganalysis feature selection. Firstly, a feature metric algorithm based on the difference function is given, and this algorithm measures the difference of the steganalysis feature components between the cover image class and the stego image class, which provides the basis for selecting the steganalysis feature components contributing greatly to detect the stego images. Secondly, the Pearson correlation coefficient is improved and used to measure the correlation between the steganalysis feature components and the image classification results to provide the basis for removing the redundant steganalysis feature components. And then, by setting thresholds, the steganalysis feature components with a large difference function value are selected and with a small Pearson correlation coefficient are deleted. Finally, the steganalysis feature components retained are trained and detected as the final steganalysis feature. A series of experimental results indicate that this method can reduce the feature dimension effectively and the spatio-temporal complexity of steganalysis, while maintaining or even improving the detection accuracy of the stego images. Compared to existing steganalysis feature selection methods such as Fisher-GFR and Improved-Fisher, this method has a higher detection accuracy of the stego images after simplification.

On the Necessary Conditions for Non-Equivalent Solutions of the Rotlet-Induced Stokes Flow in a Sphere: Towards a Minimal Model for Fluid Flow in the Kupffer’s Vesicle

The emergence of left–right (LR) asymmetry in vertebrates is a prime example of a highly conserved fundamental process in developmental biology. Details of how symmetry breaking is established in different organisms are, however, still not fully understood. In the zebrafish (Danio rerio), it is known that a cilia-mediated vortical flow exists within its LR organizer, the so-called Kupffer’s vesicle (KV), and that it is directly involved in early LR determination. However, the flow exhibits spatio-temporal complexity; moreover, its conversion to asymmetric development has proved difficult to resolve despite a number of recent experimental advances and numerical efforts. In this paper, we provide further theoretical insight into the essence of flow generation by putting together a minimal biophysical model which reduces to a set of singular solutions satisfying the imposed boundary conditions; one that is informed by our current understanding of the fluid flow in the KV, that satisfies the requirements for left–right symmetry breaking, but which is also amenable to extensive parametric analysis. Our work is a step forward in this direction. By finding the general conditions for the solution to the fluid mechanics of a singular rotlet within a rigid sphere, we have enlarged the set of available solutions in a way that can be easily extended to more complex configurations. These general conditions define a suitable set for which to apply the superposition principle to the linear Stokes problem and, hence, by which to construct a continuous set of solutions that correspond to spherically constrained vortical flows generated by arbitrarily displaced infinitesimal rotations around any three-dimensional axis.

Climate Variability over the Maritime Continent and Its Role in Global Climate Variation: A Review

The Maritime Continent (MC) consists of multiple islands with varying sizes and topography, and surrounding seas. It is characterized by rainfall (convection) variability on multiple spatial and temporal scales. Various large-scale atmospheric, oceanic, and coupled climate systems, such as the El Nino–Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Madden–Julian Oscillation (MJO), and cold surge, exert significant influences on the spatio-temporal complexity of the MC climate and climate variability. As a major tropical heat source located within the warmest oceanic area (the western Pacific warm pool), the MC has been identified as a region of great importance for climate variation on the global scale. However, prediction of climate variability over the MC and its surrounding areas and the relationships to large-scale atmospheric circulation patterns are big challenges, even for state-of-the-art climate models. In this paper, we provide a thorough review on current understanding of the spatiotemporal complexity and prediction of climate variability over this important region, and its influence on global climate variation.

Multiscale trends and precipitation extremes in the Central American Midsummer Drought

Anecdotal evidence suggests that the timing and intensity of the Central American Midsummer Drought (MSD) may be changing, while observations from limited meteorological station data and paleoclimate reconstructions show neither significant nor consistent trends in seasonal rainfall. Climate model simulations project robust future drying across the region, but internal variability is expected to dominate until the end of the century. Here we use a high-resolution gridded precipitation dataset to investigate these apparent discrepancies and to quantify the spatiotemporal complexities of the MSD. We detect spatially variable trends in MSD timing, the amount of rainy season precipitation, the number of consecutive and total dry days, and extreme wet events at the local scale. At the regional scale, we find a positive trend in the duration, but not the magnitude of the MSD, which is dominated by spatially heterogeneous trends and interannual variability linked to large-scale modes of ocean-atmosphere circulation. Although the current climate still reflects predominantly internal variability, some Central American communities are already experiencing significant changes in local characteristics of the MSD. A detailed spatiotemporal understanding of MSD trends and variability can contribute to evidence-based adaptation planning and help reduce the vulnerability of Central American communities to both natural rainfall variability and anthropogenic change.

Unmodeled error mitigation for single-frequency multi-GNSS precise positioning based on multi-epoch partial parameterization

In global navigation satellite system (GNSS) precise positioning, some residual systematic errors inevitably exist in GNSS observations. These residual systematic errors can be regarded as the unmodeled errors that cannot be easily mitigated by traditional parameterization, modeling or other methods, mainly due to their spatiotemporal complexity. In a multi-GNSS scenario, there are enough redundant observations to reveal the unmodeled errors to a great extent, according to the behaviors of observation residuals. However, in the case of single frequency, the first-order ionospheric delays cannot be eliminated by the ionosphere-free combination in terms of two or more carrier phases with different frequencies, thus resulting in significant unmodeled effects more frequently. We therefore propose a method for real-time mitigation of the unmodeled errors in single-frequency multi-GNSS precise positioning. The proposed method has two main aspects. First, considering the estimability and property of unmodeled error parameters, the method of multi-epoch partial parameterization is proposed. Second, an iterative procedure is given, which can be applied in real time. The experiment is conducted using a four-station network of real single-frequency and combined global positioning system (GPS) and BeiDou navigation satellite system (BDS) observations, with baseline lengths from approximately 5 to 25 km. The results show that the GPS/BDS unmodeled errors are indeed mitigated and the positioning precision is improved after using the proposed method, where the precision of the up direction can be improved by a maximum of 56.90%.

Can Precursory Moment Release Scale With Earthquake Magnitude? A View From the Laboratory

AbstractToday, earthquake precursors remain debated. While precursory slow slip is an important feature of earthquake nucleation, foreshock sequences are not always observed, and their temporal evolution remains poorly constrained. We report on laboratory earthquakes conducted under upper‐crustal stress and fluid pressure conditions. The dynamics of precursors (slip, seismicity, and fault coupling) prior to the mainshock are dramatically affected by slight changes in fault conditions (fluid pressure and slip history). A relationship between precursory moment release and mainshock magnitude is systematically observed, independent of fault conditions. Based on nucleation theory, we derive a semiempirical scaling relationship which explains this trend for laboratory earthquakes. Several natural observations of earthquakes ranging from ~Mw 6.0–9.0, where precursory moment release could be estimated, seem to follow the extrapolation of the laboratory‐derived scaling law. Notwithstanding spatiotemporal complexity in natural seismicity, some moderate to large earthquake magnitudes might be estimated through integrated seismological and geodetic measurements of both seismic and aseismic slips during nucleation.

Macro-HyProS: A new macro-scale hydrologic processes simulator for depression-dominated cold climate regions

This study introduces a new Macro-scale Hydrologic Processes Simulator (Macro-HyProS), tailored for cold climate regions and depression-dominated terrains. Macro-HyProS is a grid-based hydrologic model of a unique structure to deal with hydrologic complexities in depression-dominated cold climate regions. The model runs on a daily time step and incorporates a LEGO-fashion horizontal layout to account for sub-grid land use heterogeneity. On the vertical layout, each grid consists of different bands, each of which is responsible for simulating specific hydrologic processes. Macro-HyProS employs improved methodologies to account for snow accumulation and ablation, depressions, and frozen ground condition. The Red River of the North Basin (RRB) was selected to highlight the capabilities of Macro-HyProS in describing the spatiotemporal complexities associated with depression-dominated cold climate regions. Results indicated that the model provided a satisfactory performance, having the Nash–Sutcliffe efficiency coefficients of 0.56 and 0.72 in the calibration and validation periods, respectively. The modeling results accentuated the impacts of frozen ground, snowmelt, and depressions in the generation of surface runoff over the basin. On average, the RRB experienced 145 days of frozen or partially frozen ground conditions per year, which coincided with early spring rainfall and snowmelt events. Due to the widespread frozen ground conditions over the basin, up to 60% of the generated snowmelt on specific days contributed to surface runoff, whereas infiltration had a smaller portion. Also, the results revealed that the depression-dominated areas acted as “regulators” of surface runoff, particularly in early springs. Macro-HyProS provides spatiotemporal simulations of various hydrologic processes to facilitate a better understanding of macro-scale hydrologic trends.

The Possible Stimulation of the Mid-Holocene Period’s Initial Hydrological Recession on the Development of Neolithic Cultures along the Margin of the East Asian Summer Monsoon

A better understanding of past East Asian summer monsoonal (EASM) variations, which play a key role in the development of the largely rain-watered agriculture in China, could contribute to better appraising potential impacts on EASM with regard to global climate change. However, our knowledge of the relationship between mid-Holocene hydrological recession and the development of Neolithic culture is limited due to a lack of joint studies and a compilation of spatiotemporal data, especially on the episode of ~6–5 ka from the mid-Holocene Optimum (HO) along the peripheral realm of the EASM. Here, we suggest that the hydrological recession between ~6–5 ka, on the basis of lithology and geochemical element analysis, occurred not only in the Horqin sandy land, but also in other fluvial-lacustrine, stalagmitic, loess, and aeolian records across the whole monsoon-influenced boundary belt. These records indicated varied, more or less synchronous, and coherent moisture changes, yet with not entirely consistent onsets, durations, and degrees. We attributed this spatiotemporal complexity to the orbit-induced weakening of summer solar insolation, and the interactions of the Asian monsoon (AM) and westerlies, as well as topography and regional vegetation factors. Furthermore, the mid-Holocene initial hydroclimatic recession during ~6–5 ka within the thresholds of an eco-environment bearing a capacity system, might have facilitated the development of mid–late Neolithic culture and stimulated the north and northwest expansion and integration of region-specific Neolithic culture.