Multirate GARK Schemes for Multiphysics Problems

Didymosphenia geminata is an alga of major concern in temperate regions due to ongoing spread and unprecedented bloom formation. The aim of this study was to identify physical and chemical habitat conditions which affect D. geminata at catchment to patch scales. To examine this, we conducted a field-based survey of 55 distinct waterways across the South Island of New Zealand. D. geminata was detected at 82 % of waterways, grew within the periphyton at 54 % and at 25 % occurred as blooms. We tested 137 variables at scales ranging from catchment to small patches. The primary predictors of D. geminata waterway presence were still waterbodies (positive effect P < 0.05) and nitrate + nitrite (negative effect P = 0.08). D. geminata biomass was best explained by increasing river stability (P < 0.01) and decreasing nitrate + nitrite concentrations (P < 0.01). A patch-scale subsidy–stress relationship was also apparent with water velocity (P < 0.05). Our large-scale survey showed D. geminata was influenced by varied conditions at multiple spatial scales, preferentially occurring and blooming within stable, lake or dam-fed oligotrophic habitats. This work supports the finding that D. geminata blooms in response to nutrient limitation; however, results here reinforce that accrual is constrained by physical processes at multiple scales.

This article seeks to contribute to the gender and 'development' literature by showing how gender struggles over women's economic autonomy from cotton growing are played out at multiple geographical scales. The main argument is that 'men' and 'women' do not simply negotiate over cash cropping within the household. Women in particular find it necessary to 'jump' the scale of the household in order to secure productive resources for cash cropping. Drawing upon the notion of 'scalar politics,' this article illuminates the multiple processes and scaled spaces in which women's economic autonomy expands and contracts around the cultivation of cotton. It is inspired by feminist political ecological approaches to examine how the micro-politics of gender interact with meso- and macro-level agroecological and political economic processes affecting women's poverty and empowerment. Based on longitudinal research in northern Côte d'Ivoire, it shows how women of different sociocultural and economic standing negotiate access to productive resources at multiple scales, and how some men seek to restrict these initiatives. As women search for solutions to contradictions in gendered social relations of production, at different geographical scales, they have simultaneously dispersed the site of gender struggles to other locations (the marketplace and women's personal fields). Male household heads now find it necessary to contest women's cotton growing in these gendered spaces in their attempt to control their wives' labor.

Structures and infrastructures in modern industries are very large in size and complex in geometry. Their consequences in extreme conditions and accidents are highly nonlinear in association with multiple physical processes, multiple scales, and multiple criteria. To accurately identify nonlinear structural consequences, multidisciplinary approaches should be applied in conjuction with advanced computational models and large-scale physical model testing. This chapter presents methods and facilities for the large-scale physical model testing of structures and infrastructures in extreme and accidental conditions and for testing at the material level.

This article presents an overview of a theory for performing temporal smoothing on temporal signals in such a way that: (i) temporally smoothed signals at coarser temporal scales are guaranteed to constitute simplifications of corresponding temporally smoothed signals at any finer temporal scale (including the original signal) and (ii) the temporal smoothing process is both time-causal and time-recursive, in the sense that it does not require access to future information and can be performed with no other temporal memory buffer of the past than the resulting smoothed temporal scale-space representations themselves. For specific subsets of parameter settings for the classes of linear and shift-invariant temporal smoothing operators that obey this property, it is shown how temporal scale covariance can be additionally obtained, guaranteeing that if the temporal input signal is rescaled by a uniform temporal scaling factor, then also the resulting temporal scale-space representations of the rescaled temporal signal will constitute mere rescalings of the temporal scale-space representations of the original input signal, complemented by a shift along the temporal scale dimension. The resulting time-causal limit kernel that obeys this property constitutes a canonical temporal kernel for processing temporal signals in real-time scenarios when the regular Gaussian kernel cannot be used, because of its non-causal access to information from the future, and we cannot additionally require the temporal smoothing process to comprise a complementary memory of the past beyond the information contained in the temporal smoothing process itself, which in this way also serves as a multi-scale temporal memory of the past. We describe how the time-causal limit kernel relates to previously used temporal models, such as Koenderink’s scale-time kernels and the ex-Gaussian kernel. We do also give an overview of how the time-causal limit kernel can be used for modelling the temporal processing in models for spatio-temporal and spectro-temporal receptive fields, and how it more generally has a high potential for modelling neural temporal response functions in a purely time-causal and time-recursive way, that can also handle phenomena at multiple temporal scales in a theoretically well-founded manner. We detail how this theory can be efficiently implemented for discrete data, in terms of a set of recursive filters coupled in cascade. Hence, the theory is generally applicable for both: (i) modelling continuous temporal phenomena over multiple temporal scales and (ii) digital processing of measured temporal signals in real time. We conclude by stating implications of the theory for modelling temporal phenomena in biological, perceptual, neural and memory processes by mathematical models, as well as implications regarding the philosophy of time and perceptual agents. Specifically, we propose that for A-type theories of time, as well as for perceptual agents, the notion of a non-infinitesimal inner temporal scale of the temporal receptive fields has to be included in representations of the present, where the inherent nonzero temporal delay of such time-causal receptive fields implies a need for incorporating predictions from the actual time-delayed present in the layers of a perceptual hierarchy, to make it possible for a representation of the perceptual present to constitute a representation of the environment with timing properties closer to the actual present.

PurposeSimultaneously interacting rhizosphere processes determine emergent plant behaviour, including growth, transpiration, nutrient uptake, soil carbon storage and transformation by microorganisms. However, these processes occur on multiple scales, challenging modelling of rhizosphere and plant behaviour. Current advances in modelling and experimental methods open the path to unravel the importance and interconnectedness of those processes across scales.MethodsWe present a series of case studies of state-of-the art simulations addressing this multi-scale, multi-process problem from a modelling point of view, as well as from the point of view of integrating newly available rhizosphere data and images.ResultsEach case study includes a model that links scales and experimental data to explain and predict spatial and temporal distribution of rhizosphere components. We exemplify the state-of-the-art modelling tools in this field: image-based modelling, pore-scale modelling, continuum scale modelling, and functional-structural plant modelling. We show how to link the pore scale to the continuum scale by homogenisation or by deriving effective physical parameters like viscosity from nano-scale chemical properties. Furthermore, we demonstrate ways of modelling the links between rhizodeposition and plant nutrient uptake or soil microbial activity.ConclusionModelling allows to integrate new experimental data across different rhizosphere processes and scales and to explore more variables than is possible with experiments. Described models are tools to test hypotheses and consequently improve our mechanistic understanding of how rhizosphere processes impact plant-scale behaviour. Linking multiple scales and processes including the dynamics of root growth is the logical next step for future research.

了解流域水文过程（水量和水质）是流域综合管理的基础。城市化引起的生态环境问题已成为目前和未来一段相当长的时期内人类社会面临的重大问题。然而，城市化（土地利用/覆被变化、新污染物产生）、水文（降水、入渗、蒸散、径流过程）和生态系统服务（产水服务、调节气候、土壤保持、初级生产力、维持生物多样性等）在不同时空尺度之间的相互作用还存在知识空白。从城市化对流域生态系统结构和功能的影响、城市化对地表能量平衡与水量平衡的影响、城市化对水质和水生生物的影响、以及城市土地利用/覆被变化的大气环境效应等多方面系统总结了城市化影响流域生态水文过程的研究进展。研究发现，城市"热岛"、"干岛"、暴雨径流引起的城市内涝、水污染等环境现象都与生态水文过程密切相关。强调现代城市规划需要遵循生态水文学规律，从全流域生态系统角度认识近年来新出现的不同尺度的城市环境效应。城市最佳管理措施应以流域为单元实施，以调节土地利用/覆被、保护湿地（包括自然与人工湿地）为手段，充分发挥自然生态系统调节功能（如植被蒸散和净化水质）。未来城市生态水文学应围绕"低影响开发"以及"基于自然的解决方案"等城市流域管理措施，在稳定城市小气候、缓解洪涝干旱等极端水文气象灾害风险以及减轻城市水污染等方面开展多尺度综合研究。;Ecohydrology is the most basic science for guiding integrated watershed management. Rapid urbanization permanently alters land cover and the structure and functions of terrestrial ecosystems in a short period of time. Consequently, urbanization affects hydrological processes such as surface evaporation, runoff, and local and regional climate, and ecosystem services (e.g., water supply, carbon sequestration, biodiversity). Urbanization directly affects the physical properties of the near-surface atmosphere, the energy exchange between land and atmosphere, and the water budget of the ecosystems. These changes bring or aggravate a series of water quantity, water quality, and climatic effects, e.g., heat island, dry island, wet island, rain island, and turbid island. This study systematically summarized the research progress in understanding the impacts of urbanization on watershed ecohydrological processes with a focus on the consequences of urbanization on surface energy balance, water balance, water quality and aquatic organisms, and the meteorological effects of urban land use/cover change. The most direct impact of urban land use/cover change on the environment is the alternation of the energy and water balance at multiple scales. The unique physical properties of the urban surface and associated energy balance distribution characteristics are different from natural ecosystems, resulting in unique microclimate and eco-hydrology in an urban environment. Urbanization-driven surface processes have direct or indirect impacts on hydrological processes such as runoff, infiltration, evapotranspiration, groundwater recharge, and river network confluence at different scales by increasing impervious surface and changing vegetation cover conditions. Large-scale urbanization aggravates the peak flow, rainstorm runoff, and annual total water yield as a result of evapotranspiration reduction caused by the significant reduction of vegetation and surface soil infiltration rate. The influence of urbanization on non-point source water pollution is mainly reflected in the change of ‘source’, ‘process’, and ‘sink’ of non-point source pollutants. Urbanization aggravates water quality problems by the increase in impervious surface that elevates pollutant concentration and load and alters physical and chemical processes in aquatic systems. Large-scale conversion of forest lands to urban uses leads to a significant reduction in evapotranspiration, which reduces its ‘biological drainage’ function, coupled with an increase in the impervious surface, and is likely to exacerbate the risk of flooding or the risk of ‘light rainstorms, heavy waterlogging’ phenomena in urban watersheds. The conversions of vegetated ecosystems reduce their ‘air conditioner’ functions and are likely to exacerbate the ‘urban heat island’ and ‘urban dry island’ effects. We summarized measures and strategies centered on ‘Low Impact Development’ to mitigate the urbanization risks through reducing extreme hydrological effects of impervious surface, enhancing the regulating function of natural ecosystems, and implementing the Urban Best Management Practices at a watershed scale. We concluded that future urban ecohydrological science should focus on the studying the mechanisms of ‘Low Impact Development’ and ‘Nature-based Solutions’ in mitigating environmental impacts from the perspectives of water and energy balances and biogeochemical cycling at multiple scales.

Spatial models show that genetic differentiation between populations can be explained by factors ranging from geographic distance to environmental resistance across the landscape. However, genomes exhibit a landscape of differentiation, indicating that multiple processes may mediate divergence in different portions of the genome. We tested this idea by comparing alternative geographic predctors of differentiation in ten bird species that co-occur in Sonoran and Chihuahuan Deserts of North America. Using population-level genomic data, we described the genomic landscapes across species and modeled conditions that represented historical and contemporary mechanisms. The characteristics of genomic landscapes differed across species, influenced by varying levels of population structuring and admixture between deserts, and the best-fit models contrasted between the whole genome and partitions along the genome. Both historical and contemporary mechanisms were important in explaining genetic distance, but particularly past and current environments, suggesting that genomic evolution was modulated by climate and habitat There were also different best-ftit models across genomic partitions of the data, indicating that these regions capture different evolutionary histories. These results show that the genomic landscape of differentiation can be associated with alternative geographic factors operating on different portions of the genome, which reflect how heterogeneous patterns of genetic differentiation can evolve across species and genomes.

Purpose In this work, it is presented a locally conservative multiscale algorithm accounting the mineralization process during the supercritical carbon dioxide injection into a deep saline aquifer. The purpose of this study is to address numerically the geological storage of CO2 in a highly heterogeneous reservoir, leading with interactions among several phenomena in multiple scales. Design/methodology/approach This algorithm have features that distinguish it from the presently available solvers which are: (i) an appropriate combination of a coupled transport system solver using a high-order non-oscillatory central-scheme finite volume method and, elliptic numerical approach applying a locally conservative finite element method for Darcy’s law and, (ii) the capability of leading with interactions among several phenomena in multiple scales. Findings As a result, this approach was able to quantify the precipitation of the carbonate crystals at the solid interface.

Conventional methods to solve the time-harmonic elastic wave equations usually rely on either direct solvers or iterative solvers. The former are very efficient for treating multiple right hand side problems, as the matrix factorization needs to be done only once for all the right hand sides. However, it suffers from a significant shortcoming associated with high memory consumption and lack of scalability. The latter are matrix-free, and therefore much lighter in memory and scalable. However, dedicated preconditioners are required to converge these methods. The efficiency of existing preconditioners quickly deteriorates as the frequency increases. Another approach to compute time-harmonic solution to elastic wave equations is to consider timedomain solvers. Instead of computing the stationary solution, which convergence is shown to be dependent on the presence of trapped waves and complex wave phenomenon, we develop here a numerical strategy based on a controllability method. The method has been recently analyzed in the frame of acoustic propagation and we extend it here in the frame of linear elasticity. We rely on a spectral element space discretization and a fourth order Runge Kutta time integration. We present the basic properties and formulation of the method, before investigating its scalability and its memory requirement on canonical three-dimensional numerical experiments. The method is shown to be scalable for a problem involving approximately 250 millions degrees of freedom up to more than fifteen hundred computational units.

Stochastic dynamic systems with continuous state space and time scale may be defined as diffusion processes or as real physical processes described by ordinary differential equations with right hand sides containing 'coloured' noise. The relation between real and diffusion processes is established by a convergence theorem. By this theorem filter and prediction problems for real processes are reduced to the corresponding problems for diffusion processes. The same theorem shows how to approximate numerically economic models defined by diffusion processes and how to use simulation in forecasting.

Biological processes, such as predator-prey or competitive interactions, occur at multiple spatial and temporal scales, but their impacts on the distribution, abundance, and fitness of organisms may only be detectable at some scales. This is because 1) small scale (local) processes may be constrained by large-scale (regional) processes, 2) the influence of organism movement changes with spatial scale, and 3) multiple small-scale processes may interact and produce variation that obscures large-scale patterns. Most ecologists would like to know the relevance of small-scale observations and experiments for large-scale patterns and processes acting over long time periods. In this paper we consider whether patterns of individual behavior translate in a straightforward way to patterns in population dynamics, community structure, or individual fitness at larger spatial and longer temporal scales. We illustrate our discussion with data from communities living in high altitude streams in western Colorado, coastal ...

This paper reports on a large‐scale quantitative psychometric study conducted in very remote and remote Indigenous communities in the Northern Territory Australia. Thirteen school sites and 1,044 participants contributed to the study. The full study is concerned with examining the inter‐relationships between multiple achievement goals, future goals, self‐regulation, and learning processes and their relationship to achievement outcomes in communities that are very remote geographically and culturally from Western settings. The study reported in this paper sets out to examine four key issues: the construct validity and reliability of the multiple motivational scales drawn from Personal Investment theory for very remote and remote Indigenous students in Australia; the level of endorsement of these motivational scales for remote and very remote Indigenous students; any differences between groups considered collectivist and individualist on these multiple goals, and lastly, the theoretical, methodological, cultural, and logistical difficulties encountered in conducting the research that may have impacted on its external validity.

Adaptation to selective visual scaling of short time scale processes in isometric force

Through a glass less darkly—New approaches for studying the distribution, abundance and biology of Euphausiids

Snow cover spatial variability at multiple scales: Characteristics of a layer of buried surface hoar