Spatial Scales Research Articles

Relational geographies of urban unsustainability: The entanglement of California’s housing crisis with WUI growth and climate change

One of California’s most pressing social and environmental challenges is the rapid expansion of the wildlands–urban interface (WUI). Multiple issues associated with WUI growth compared to more dense and compact urban form are of concern—including greatly increased fire risk, greenhouse gas emissions, and fragmentation of habitat. However, little is understood about the factors driving this growth in the first place and, specifically, its relationship to urban–regional housing dynamics. This paper connects work in urban social science, urban and regional planning, and natural sciences to highlight the potential role of housing crises in driving displacement from the urban core to relatively more affordable exurbs, and with this, WUI growth. We analyze this relationship in California, which leads the nation in lack of affordable housing, scale of WUI growth, and many associated WUI hazards, including wildfire. We offer three related arguments: first, that California’s affordable housing crisis, with its effect of driving migration to exurban areas, should be recognized as a significant urban form-related sustainability challenge; second, that to understand this challenge scholars must expand the spatial scale and analytic toolkit of both urban and WUI analysis through relational, mixed methods research; and third, that political and programmatic efforts to address California’s housing crisis should undergird efforts to address WUI growth and climate change. Ultimately, we argue that expanding access to affordable urban housing can produce a more sustainable and just urban form that mitigates WUI-related climate and environmental impacts and reduces the vulnerability of growing numbers of WUI residents living in harm’s way.

STAGE: a spatiotemporal-knowledge enhanced multi-task generative adversarial network (GAN) for trajectory generation

Individual trajectory data play a pivotal role in various application fields, such as urban planning, traffic control, and epidemic simulation. Despite the diverse means for data collection in current times, the real-world trajectory data in practical application remains severely limited due to concerns over personal privacy. In this study, we designed a Spatiotemporal-knowledge enhanced multi-TAsk GEnerative adversarial network (GAN), named STAGE, to generate synthetic trajectories that statistically resemble the real data without recycling personal information. In STAGE, we designed a multi-task generator with three stages of spatio-temporal generation tasks, i.e. activity-sequence generation task, township-level trajectory generation task, and neighborhood-level trajectory generation task, with the last one as the main task while the other two as auxiliary tasks. Meanwhile, we designed a spatial consistency loss in the adversarial training process to assess the spatial consistency of generated trajectories at different spatial scales. Experiment results show that compared to the baselines, trajectories generated by our method have closer data distributions to the real ones. We argued that the designs of spatiotemporal-knowledge enhanced generation tasks and training loss benefit the spatiotemporal generation processes, which help reproduce the temporal patterns of human daily activities and spatial distribution of human movements.

Transitions between colour mechanisms affect speciation dynamics and range distributions of birds.

Several ecogeographical 'rules' have been proposed to explain colour variation at broad spatial and phylogenetic scales but these rarely consider whether colours are based on pigments or structural colours. However, mechanism can have profound effects on the function and evolution of colours. Here, we combine geographic information, climate data and colour mechanism at broad phylogenetic (9,409 species) and spatial scales (global) to determine how transitions between pigmentary and structural colours influence speciation dynamics and range distributions in birds. Among structurally coloured species, we find that rapid dispersal into tropical regions drove the accumulation of iridescent species, whereas the build-up of non-iridescent species in the tropics was driven by a combination of dispersal and faster in situ evolution in the tropics. These results could be explained by pleiotropic links between colouration and dispersal behaviour or ecological factors influencing colonization success. These data elucidate geographic patterns of colouration at a global scale and provide testable hypotheses for future work on birds and other animals with structural colours.

Cropland abandonment in mountainous China: Patterns and determinants at multiple scales and policy implications

Understanding the formation and causes of cropland abandonment is crucial for developing effective strategies to mitigate this process. However, studies on cropland abandonment often look at one spatial scale, although the relationship between abandonment and evaluated factors may change depending on the specific scale, which limits our understanding of the process of cropland abandonment. Taking mountainous Southern Sichuan of China as an example, we utilized satellite-derived cropland abandonment maps to assess the evolving patterns of cropland abandonment from 2003 to 2018 across various scales. We then carried out a multi-scale (parcel, local and regional) assessment of the relationships between selected 17 variables representing natural, location and socioeconomic conditions and cropland abandonment. Results showed, the cropland abandonment rate increased from 2 % in 2003 to 15 % by 2018, and cropland abandonment always showed a higher concentration in the central part of the study area. At different scales, a combination of factors, which determined cropland abandonment, differed. We also found the distance to the nearest county center was scale-dependent factor and statistically significant factor of cropland abandonment only at the local scale. Among the factors with large contributions, topography mattered at all three scales; cropland per capita, aging and agricultural labor per unit of cropland mattered at the parcel and regional scales. Cropland fragmentation, air temperature and distance to the nearest settlement mattered at the local scale; the distance to the nearest water system, the distance to nearest county center and agricultural mechanization mattered at the regional scale. This multi-scale assessment framework embodied with multi-variable and multi-temporal could provide a new perspective to reveal the complex nonlinear relationship between the determinants and cropland abandonment, and further help to predict future cropland abandonment hotspots and identify relevant land-use policies.

A continuum mechanics framework for wear simulations of sliding surfaces

Wear resulting from sliding motion is a complex physics problem with multiple spatial and temporal scales of interest. The novel model involves solving contact mechanics problems in multiple positions concurrently, followed by an averaging process to calculate the average wear of all asperities in the domain, which effectively mimics the physics of sliding. The model accounts for anisotropic surfaces, including arbitrarily rough surfaces. The novel sliding solution method enables good accuracy, while maintaining computational time at a reasonable level. Results of the model are presented and discussed, with a focus on the further usage of the model.

Variable-order fractional diffusion: Physical interpretation and simulation within the multiple trapping model

The physical interpretation of a variable-order fractional diffusion equation within the framework of the multiple trapping model is presented. This interpretation enables the development of a numerical Monte Carlo algorithm to solve the associated subdiffusion equation. An important feature of the model is variation in energy density of localized states, when the detailed balance condition between localized and mobile particles is satisfied. The variable order anomalous diffusion equations under consideration can be applied to the description of transient subdiffusion in inhomogeneous materials, the order of which depends on the considered spatial and/or time scale. Examples of numerical solutions for different situations are demonstrated. Considering variable-order fractional drift, we calculate and analyze the transient current curves of the time-of-flight method for samples with varying density of localized states.

High-resolution urban air pollution mapping.

Variation in urban air pollution arises because of complex spatial, temporal, and chemical processes, which profoundly affect population exposure, human health, and environmental justice. This Review highlights insights from two popular in situ measurement methods-mobile monitoring and dense sensor networks-that have distinct but complementary strengths in characterizing the dynamics and impacts of the multidimensional urban air quality system. Mobile monitoring can measure many pollutants at fine spatial scales, thereby informing about processes and control strategies. Sensor networks excel at providing temporal resolution at many locations. Increasingly sophisticated studies leveraging both methods can vividly identify spatial and temporal patterns that affect exposures and disparities and offer mechanistic insight toward effective interventions. This Review summarizes the strengths and limitations of these methods and discusses their implications for understanding fine-scale processes and impacts.

Drug-loaded nanoparticles for cancer therapy: a high-throughput multicellular agent-based modeling study.

Interactions between biological systems and engineered nanomaterials have become an important area of study due to the application of nanomaterials in medicine. In particular, the application of nanomaterials for cancer diagnosis or treatment presents a challenging opportunity due to the complex biology of this disease spanning multiple time and spatial scales. A system-level analysis would benefit from mathematical modeling and computational simulation to explore the interactions between anticancer drug-loaded nanoparticles (NPs), cells, and tissues, and the associated parameters driving this system and a patient's overall response. Although a number of models have explored these interactions in the past, few have focused on simulating individual cell-NP interactions. This study develops a multicellular agent-based model of cancer nanotherapy that simulates NP internalization, drug release within the cell cytoplasm, "inheritance" of NPs by daughter cells at cell division, cell pharmacodynamic response to the intracellular drug, and overall drug effect on tumor dynamics. A large-scale parallel computational framework is used to investigate the impact of pharmacokinetic design parameters (NP internalization rate, NP decay rate, anticancer drug release rate) and therapeutic strategies (NP doses and injection frequency) on the tumor dynamics. In particular, through the exploration of NP "inheritance" at cell division, the results indicate that cancer treatment may be improved when NPs are inherited at cell division for cytotoxic chemotherapy. Moreover, smaller dosage of cytostatic chemotherapy may also improve inhibition of tumor growth when cell division is not completely inhibited. This work suggests that slow delivery by "heritable" NPs can drive new dimensions of nanotherapy design for more sustained therapeutic response.

The importance of biotic interactions in distribution models of wild bees depends on the type of ecological relations, spatial scale and range

The importance of biotic interactions in distribution models of wild bees depends on the type of ecological relations, spatial scale and range

Study on the contributions of 2D and 3D urban morphologies to the thermal environment under local climate zones

With the changes in global climate and rapid urbanization, identifying the contribution of urban morphology to the thermal environment under different scenarios could be helpful in proposing differentiated optimization responses of different scenarios for improving the thermal environment by means of natural cooling. This study calculated 2D and 3D metrics and retrieved surface temperature based on building vector data, land use, electronic map, the remote sensing images. Then, the study of spatial scale sensitivity was developed to build a nested multi-scale Local Climate Zone (LCZ) (NMSLCZ) map. Finally, the eXtreme Gradient Boost (XGBoost) regression model was performed to explore the relative contributions of 2D and 3D morphologies of different LCZ scenarios to surface temperatures. The results of scale sensitivity analysis showed the size of the optimal spatial scale decreased with the increase in building height. The 3D morphologies show more significant effects on LST variations than 2D morphologies. The surface temperature mainly by built type is significantly higher than that mainly by land cover type. Scenarios representing dense trees, shrubs, low vegetation, and water have significant cooling effects. In the scenarios of built types, the surface temperature of compact and large low-rise buildings is higher than that of the other building forms. Our findings provide a new perspective for LCZ mapping of scale optimization of the thermal environment. Meanwhile, the contributions of 2D and 3D morphologies on LSTs could help urban planners and managers understand the impacts of climate change and propose relevant strategies toward sustainable cities.

Spatial and temporal variation of PM2.5 and the influence of vegetation in the Yangtze River Delta region

With rapid urbanisation in China, PM2.5 has become a limiting factor for the sustainable development of cities. Taking the Yangtze River Delta as the experimental area, this study analysed the spatial and temporal changes of PM2.5 concentrations from 2001 to 2020. It also examined the variations, dispersion, and correlation with NDVI of PM2.5 concentrations in different vegetation zones at different temporal and spatial scales. The results showed that: (1) The PM2.5 concentration in the Yangtze River Delta showed an overall decreasing trend during 2001–2020, and the change was divided into two phases, starting with an increasing phase and entering a decreasing phase after 2013. (2) In terms of spatial distribution, PM2.5 concentrations in the Yangtze River Delta show a pattern of low in the south and high in the north, with the spatial focus shifting to the north over time. There is a concentration of high levels of particulate matter in the Hefei-Nanjing-Wuxi area. (3) The effect of natural vegetation on the reduction and stabilization of atmospheric particulate matter concentration is better than that of artificial vegetation. (4) Needleleaf forests, broadleaf forests, and shrubs in natural vegetation are more capable of reducing and stabilizing atmospheric particulate matter than grasses. The study can provide a reference for regional air pollution control and regional plant system construction.

Interface area density model for Large-Eddy Simulation of assisted atomization in fiber regime

In the context of simulating liquid rocket engines (LREs), accurately reproducing the complex combustion chamber environment poses a significant challenge. Recent works have shown that Direct Numerical Simulation has made good progress in achieving the simulation of the whole range of temporal and spatial two-phase flow scales involved. However, due to the computational costs, it is currently out of reach in an industrial context. Large-Eddy Simulations (LES) considerably reduce the computational cost but require modeling the two-phase flow at sub-grid level. A promising approach for such modeling is the interface area density (IAD) approach, which was developed initially for LES of flame fronts and subsequently adapted to Diesel jet atomization to recover spray droplet size distributions. In this method, a subgrid density of interface area is transported with an advection equation, while opportune source terms simulate its growth by breakup or its reduction by coalescence effects. In the context of the LREs assisted atomization, the complex mechanism of the assisted atomization in fiber regime must be taken into account by the subgrid model to recover the correct spray size distribution. The present work proposes a new interface area density evolution modeling for two-phase LES of coaxial assisted atomization in fiber regime. The proposed model focuses on recovering a realistic liquid-gas relative velocity at all the scales, enabling accurate modeling of sub-grid scales by using the IAD as a measure of liquid structure sizes.

Strategic flood risk management over time. Applying a temporal lens to see how flood risk management measures are (or are not) implemented

ABSTRACT Strategic flood risk management of river catchments involves significant increases in the complexity both of the contents (e.g. the aims and measures) of a given strategy and also its social, spatial, and temporal scales. Conceptually, flood risk management research to date has underestimated the importance of time and temporality. This paper, which is based on ‘historical Institutionalism,’ introduces a temporal lens to focus on strategic flood risk management; it highlights issues of duration and timing as well as tempo and change in tempo with respect to the implementation of measures to reduce flood risk at catchment level. The application of a temporal lens is illustrated through empirical research into strategic flood risk management for the medium-sized Aist river catchment in Austria. The paper uses a longitudinal qualitative research design to analyze the changes in strategic flood risk management in the catchment. The analysis shows that strategy efforts in reaction to an extreme flood event in the catchment in August 2002 can be differentiated into three phases. Phase 1 is characterized by the design of ambitious catchment-wide management; Phase 2 by struggles to implement the strategy due to institutional conditions and protests by citizens; and Phase 3 by redesign of the initial strategic plan to make it less ambitious and by changes to the actor constellation supporting the plan. The present paper offers a process-oriented institutional explanation for this pattern of phases, and it highlights issues of timing and tempo. It concludes with general suggestions for enhancing the temporal dimension in flood risk management.

Breaking the resource curse: The impact of digital economy on the sustainable transformation of resource-based cities

Resource-based cities (RBCs) depend heavily on the extraction and processing of natural resources, resulting in relatively simple economic structures. However, the rise of the digital economy (DIGITAL) presents numerous opportunities for economic diversification and sustainable development. Further investigation is necessary to explore DIGITAL's potential to overcome the resource curse. This study examined the influence of digital economic development on the sustainable transformation of 115 RBCs in China from 2011 to 2019. Robustness and heterogeneity tests were conducted to ensure reliability of the findings. This study concluded that DIGITAL plays a pivotal role in driving the sustainable transformation of resource-based cities (STRBC). This conclusion was supported by various robustness tests. Urban economic efficiency and the vitality of innovation and entrepreneurship were identified as key channels through which DIGITAL contributes to STRBC. Moreover, governmental environmental concern can enhance DIGITAL's role in promoting STRBC. Furthermore, DIGITAL is particularly crucial for mature, declining, and regenerating cities, and has a stronger impact on cities with larger spatial scales. This may be attributed to factors such as the levels of economic development, infrastructure construction, and policy support in these regions.

Quantifying urban spatial resilience using multi-criteria decision analysis (MCDA) and back propagation neural network (BPNN)

In the face of rapid urbanization and increasing environmental risks, building resilient cities has become a global priority. This study introduces a novel methodology for quantifying urban spatial resilience by integrating multi-criteria decision analysis (MCDA) and back propagation neural network (BPNN). The urban spatial resilience assessment system encompasses five critical criteria layers (urban spatial scale, structure, form, function, and network resilience) and 29 indicator layers. An empirical study of Yinchuan City, China, demonstrates the effectiveness of the MCDA-BPNN model in quantifying urban spatial resilience. The models identified significant disparities in resilience between central and peripheral urban zones, with central areas showing higher resilience scores compared to peripheral areas. This spatial pattern was most pronounced in structure, functional and network resilience. These results contribute to the field of urban environmental science by advancing the fundamental understanding of urban spatial resilience mechanisms and their spatial distribution. The study has significant implications for urban planners, policymakers, and risk management authorities, enabling data-driven decision-making and the development of targeted, resilience-oriented urban policies and strategies. The MCDA-BPNN approach offers a promising tool for comprehensive urban resilience assessment in diverse urban contexts.

Competition between sympatric hare species in the Alps is boostered by climate change and hybridisation

Climatic variation along the elevation gradient promotes the natural parapatric occurrence of the European hare (Lepus europaeus) and Alpine mountain hare (Lepus timidus varronis) in the Alps. Recent data indicate a displacement of mountain hares caused by competition with the European hare. Competitive exclusion might take place at a fine spatial scale and hybrids may sharpen competition. Genetic non-invasive sampling (gNIS) demonstrates to be effective to retrieve information from wild animals. However, based on the accuracy of the differing genetic analysis methods, the selection of the method might decisively influence results. To examine habitat preferences of Alpine mountain hares, European hares and their hybrids with particular interest in the influence of the accuracy of the genetic analysis method on the results, we performed gNIS in Grisons (Switzerland) for four years and compared habitat associations of the genotyped samples. We recorded 137 individuals (i.e., 35 hybrids, 49 European hares, 53 Alpine mountain hares). Combined nuclear and mitochondrial DNA analysis including individual identification revealed to be the most accurate indirect method for the study of habitat preferences of hares. Alpine mountain hares had a narrow habitat breadth and used little habitat diversity. Hybrids showed great similarities in their habitat preferences to European hares. Hybrids might increase the competition in favour of European hares and the displacement of Alpine mountain hares, since they show similar patterns of habitat use to European hares. Ongoing climate change potentiate the niche overlap between species, increasing the risk of Alpine hare decline due to hybridisation and displacement.

Impact of the numerical conversion to optical depth on the transfer of polarized radiation

Making the conversion from the geometrical spatial scale to the optical depth spatial scale is useful in obtaining numerical solutions for the radiative transfer equation. This is because it allows for the use of exponential integrators, while enforcing numerical stability. Such a conversion involves the integration of the total opacity of the medium along the considered ray path. This is usually approximated by applying a piecewise quadrature in each spatial cell of the discretized medium. However, a rigorous analysis of this numerical step is lacking. This work is aimed at clearly assessing the performance of different optical depth conversion schemes with respect to the solution of the radiative transfer problem for polarized radiation, out of the local thermodynamic equilibrium. We analyzed different optical depth conversion schemes and their combinations with common formal solvers, both in terms of the rate of convergence as a function of the number of spatial points and the accuracy of the emergent Stokes profiles. The analysis was performed in a 1D semi-empirical model of the solar atmosphere, both in the absence and in the presence of a magnetic field. We solved the transfer problem of polarized radiation in different settings: the continuum, the photospheric Sr i AA modeled under the assumption of complete frequency redistribution, and the chromospheric Ca i AA taking the partial frequency redistribution effects into account during the modeling. High-order conversion schemes generally outperform low-order methods when a sufficiently high number of spatial grid points is considered. In the synthesis of the emergent Stokes profiles, the convergence rate, as a function of the number of spatial points, is impacted by both the conversion scheme and formal solver. The use of low-order conversion schemes significantly reduces the accuracy of high-order formal solvers. In practical applications, the use of low-order optical depth conversion schemes introduces large numerical errors in the formal solution. To fully exploit high-order formal solvers and obtain accurate synthetic emergent Stokes profiles, it is necessary to use high-order optical depth conversion schemes.

Catching some air: a method to spatially quantify aerial triazole resistance in Aspergillus fumigatus.

Airborne triazole-resistant spores of the human fungal pathogen Aspergillus fumigatus are a significant human health problem as the agricultural use of triazoles has been selecting for cross-resistance to life-saving clinical triazoles. However, how to quantify exposure to airborne triazole-resistant spores remains unclear. Here, we describe a method for cost-effective wide-scale outdoor air sampling to measure both spore abundance as well as antifungal resistance fractions. We show that prolonged outdoor exposure of sticky seals placed in delta traps, when combined with a two-layered cultivation approach, can regionally yield sufficient colony-forming units (CFUs) for the quantitative assessment of aerial resistance levels at a spatial scale that was up to now unfeasible. When testing our method in a European pilot sampling 12 regions, we demonstrate that there are significant regional differences in airborne CFU numbers, and the triazole-resistant fraction of airborne spores is widespread and varies between 0 and 0.1 for itraconazole (∼4 mg/L) and voriconazole (∼2 mg/L). Our efficient and accessible air sampling protocol opens up extensive options for fine-scale spatial sampling and surveillance studies of airborne A. fumigatus.IMPORTANCEAspergillus fumigatus is an opportunistic fungal pathogen that humans and other animals are primarily exposed to through inhalation. Due to the limited availability of antifungals, resistance to the first choice class of antifungals, the triazoles, in A. fumigatus can make infections by this fungus untreatable and uncurable. Here, we describe and validate a method that allows for the quantification of airborne resistance fractions and quick genotyping of A. fumigatus TR-types. Our pilot study provides proof of concept of the suitability of the method for use by citizen-scientists for large-scale spatial air sampling. Spatial air sampling can open up extensive options for surveillance, health-risk assessment, and the study of landscape-level ecology of A. fumigatus, as well as investigating the environmental drivers of triazole resistance.

A flux-independent increase in outflows prior to the emergence of active regions on the Sun

Abstract Emerging active regions are associated with convective flows on the spatial scale and lifetimes of supergranules. To understand how these flows are involved in the formation of active regions, we aim to identify where active regions emerge in the supergranulation flow pattern. We computed supergranulation scale flow maps at the surface for all active regions in the Solar Dynamics Observatory Helioseismic Emerging Active Region Survey. We classified each of the active regions into four bins, based on the amplitude of their average surface flow divergence at emergence. We then averaged the flow divergence over the active regions in each bin as a function of time. We also considered a corresponding set of control regions. We found that, on average, the flow divergence increases during the day prior to emergence at a rate independent of the amount of flux that emerges. By subtracting the averaged flow divergence of the control regions, we found that active region emergence is associated with a remaining converging flow at 0.5-1 days prior to emergence. This remnant flow, Δ div vh = ( − 4.9 ± 1.7) × 10−6 s−1 , corresponds to a flow speed of 10-20 m s−1 (an order of magnitude less than supergranulation flows) out to a radius of about 10 Mm. We show that these observational results are qualitatively supported by simulations of a small bipole emerging through the near-surface convective layers of the Sun. The question remains whether these flows are driving the emergence, or are caused by the emergence.

Cloud structure and young star distribution in the Dragonfish complex

Star formation is a complex process involving several physical mechanisms that interact with each other at different spatial scales. One way to shed some light on this process is to analyse the relation between the spatial distributions of gas and newly formed stars. In order to obtain robust results, it is necessary for this comparison to be made using quantitative and consistent descriptors that are applied to the same star-forming region. We used fractal analysis to characterise and compare in a self-consistent way the structure of the cloud and the distribution of young stellar objects (YSO) in the Dragonfish star-forming complex. Different emission maps of the Dragonfish nebula were retrieved from the NASA/IPAC Infrared Science and the Planck Legacy archives. Moreover, we used photometric information from the AllWISE catalogue to select a total of 1082 YSOs in the region. We derived the physical properties for some of these from their spectral energy distributions (SEDs). For the cloud images and YSOs, the three-dimensional fractal dimension ($D_f$) was calculated using previously developed and calibrated algorithms. The fractal dimension of the Dragonfish nebula ($D_f = 2.6-2.7$) agrees very well with values previously obtained for the Orion, Ophiuchus, and Perseus clouds. On the other hand, YSOs exhibit a significantly lower value on average ($D_f = 1.9-2.0$), which indicates that their structure is far more clumpy than the material from which they formed. Younger Class I and Class II sources have lower values ($D_f = 1.7 0.1$) than more evolved transition disk objects ($D_f = 2.2 0.1$), which shows a certain evolutionary effect according to which an initially clumpy structure tends to gradually disappear over time. The structure of the Dragonfish complex is similar to that of other molecular clouds in the Galaxy. However, we found clear and direct evidence that the clustering degree of the newly born stars is significantly higher than that of the parent cloud from which they formed. The physical mechanism behind this behaviour is still not clear.