Neighborhood Effects Research Articles

A high‐performance cellular automata model for urban expansion simulation based on convolution and graphic processing unit

AbstractCellular automata (CA) models are effective tools for simulating future urban expansion. With the widespread use of high‐resolution geospatial data for CA simulation, the computational intensity of CA models has increased. Additionally, due to the continuous development of CA modeling research, many scholars have made improvements to the models to enhance their simulation accuracy, resulting in an increasing computational complexity of the model. Consequently, the simulation task based on CA requires vast computing time and memory space. In recent years, deep learning (DL) has experienced rapid development. Many open‐source DL frameworks support graphic processing unit (GPU) parallel computing and provide efficient application programming interfaces (APIs) that can be easily called to handle tasks of interest. In this study, a high‐performance CA model was constructed based on the similarity between the neighborhood effect calculation process of the CA model and the convolutional process in a convolutional neural network (CNN). The convolution function in the DL library is used to calculate the neighborhood effect of the CA model to reduce the time and memory consumption of CA‐based simulation. The experimental results show that compared with the conventional CA model, the execution time of the GPU‐convolution‐CA model proposed in this study has been reduced by more than 98%.

Does neighbourhood deprivation influence low back pain and arthritis: An empirical study using multilevel twin design.

Neighbourhood deprivation has been found to be associated with many health conditions, but its association with low back pain (LBP) and arthritis is unclear. This study aimed to examine the association between neighbourhood deprivation with LBP and arthritis, and its potential interaction with individual socioeconomic status (SES) on these outcomes. Monozygotic (MZ) twins from the Washington State Twin Registry were used to control for genetic and common environmental factors that could otherwise confound the purported relationship. Multilevel models were employed to examine the association between neighbourhood deprivation as well as individual-level SES with LBP/arthritis, adjusting for age, sex, body mass index (BMI) and residence rurality. There were 6,380 individuals in the LBP sample and 2,030 individuals in the arthritis sample. Neighbourhood deprivation was not associated with LBP (P = 0.26) or arthritis (P = 0.61), and neither was its interaction with individual-level SES. People without a bachelor's degree were more likely to report LBP (OR 1.44, 95% CI 1.26-1.65) or both LBP and arthritis (OR 1.67, 95% CI 1.14-2.45) than those with a bachelor's degree, but not for arthritis alone (P = 0.17). Household income was not significantly associated with LBP (P = 0.16) or arthritis (p = 0.23) independent of age, sex, and BMI. Our study did not find significant associations between neighbourhood deprivation and the presence of LBP or arthritis. More research using multilevel modelling to investigate neighbourhood effects on LBP and arthritis is recommended.

Enhancing outlying growth simulation in urban cellular automata via intelligent extraction-fusion of land suitability and neighborhood effects: a case study of Wuhan, China

ABSTRACT Urban growth has accelerated significantly in recent decades, categorized into two spatial patterns: adjacent and outlying growth. Traditional Cellular Automata (CA)-based models excel at simulating adjacent growth but exhibit limitations in modeling outlying growth, which can be summarized into two issues: 1) the overestimation of neighborhood effects caused by models’ excessive dependence on neighboring cell states; and 2) the ignorance of spatial heterogeneity in the relative importance of land suitability and neighborhood effects on urban growth. To address these problems, a novel CA model with Separate Extraction and Adaptive Fusion of land suitability and neighborhood effects (SEAF-CA) is proposed. In this model, a dual-path convolution structure is employed to extract spatial features from driving factors and cell states; geographical coordinates of each cell then input into a multilayer perceptron to derive spatially varying weights for feature fusion. Finally, the derived conversion probability is integrated with CA to simulate urban growth. Land use data collected from 2000 to 2020 in Wuhan are selected to evaluate the proposed model. Experimental results illustrate that SEAF-CA outperforms three typical CA models, achieving the closest outlying growth proportion to reality and the highest simulation accuracy. In addition, the source code of SEAF-CA is now available at GitHub (https://github.com/ohXu/SEAF-CA).

Quantifying the role of arrival infrastructures in the labor market integration of refugees

ABSTRACT Across Europe, refugees face significant difficulties in finding employment. Many studies have attributed the disadvantaged labor market position of refugees to factors on the individual level, such as language barriers or health issues related to the experience of fleeing. While such explanations emphasize individual responsibility, ethnographic studies are increasingly contending that opportunities to integrate into the labor market can be restricted or enabled by arrival infrastructures. We contribute to this discussion by taking a quantitative perspective. Focusing on the Netherlands, we used extensive national register data that allowed us to follow refugees over time and break the concept of arrival infrastructures down into four dimensions, namely job access, neighborhood effects, enclave effects, and the local migration regime. In addition, because the Dutch dispersal policy distributed refugees – to a considerable extent – randomly across municipalities during the period under study, we were able to counteract problems of self-selection and reversed causality. We studied the labor market integration of refugees using competing risks analysis, taking educational enrollment and residential mobility into account. Our findings show that economic, social, and institutional arrival infrastructures manifest themselves at different scales but all matter in the labor market integration of refugees.

No‐choice oviposition preferences predict neighborhood effects among host plants in a model system

Abstract Neighbouring plant species can indirectly affect each other's fitness through insect herbivores. For instance, the number of eggs an insect deposits on a focal plant can be influenced by the presence of a neighbouring plant species because of the herbivore's relative host plant preferences. Yet, the relationship between oviposition preferences (measured in no‐choice tests) and the strength and direction of such indirect effects among neighbouring plants remains poorly understood. We performed a lab experiment using bean beetles (Callosobruchus maculatus) and five species of beans to determine if beetles' no‐choice preferences for a neighbouring bean species correlated with the number of eggs laid on a focal species in two‐species environments (diculture). We predicted that as the preference for the neighbouring beans increased compared to the focal host, beetles would lay fewer eggs on the focal bean host. Across all pair‐wise combinations, our prediction was supported: as the relative no‐choice preference of neighbouring beans increased, the number of eggs laid on focal beans decreased. However, this relationship was relatively weak. We also found that beetles tended to lay more eggs in diculture compared to arenas with one bean species. These results provide empirical evidence linking herbivores' no‐choice preferences to the strength of neighbourhood effects and suggest that even within a relatively controlled environment, neighbourhood effects can be weak. Our results also highlight that unexpected changes to the total number of eggs laid by herbivores in mixed‐plant patches relative to monoculture can complicate predictions.

Unleashing the power of social media: examining farmers’ adoption for agriculture knowledge exchange

Purpose This study uses a comprehensive theoretical framework that combines social cognitive theory and neighborhood effect to investigate the influence of neighborhood effects on farmers’ outcome expectations, observational learning and self-efficacy. This study aims is to analyze the mechanisms that underlie the adoption of social media by farmers for knowledge exchange in the agricultural context. Specifically, this research explores the role of neighborhood effects, outcome expectations, observational learning and self-efficacy in shaping farmers’ decision-making process regarding the use of social media platforms for exchanging agricultural knowledge. Design/methodology/approach The study data was collected through a sample survey conducted among 570 agricultural households residing in the provinces of Thai Nguyen, Cao Bang, Bac Kan and Phu Tho, located in the northern region of Vietnam. To analyze the data, structural equation modeling was used as the statistical technique of choice. Findings The findings of the study indicate a significant influence of neighborhood effects on outcome expectations, observational learning and self-efficacy. These factors, derived from social cognitive theory, also exhibit a positive association with farmers’ adoption of social media for knowledge exchange. Additionally, the study highlights that neighborhood contribute to a favorable adoption of social media among farmers via outcome expectations, observational learning, and self-efficacy. Research limitations/implications The study is limited in examining farmers’ social media adoption for agriculture knowledge exchange in Northern mountainous area of Vietnam. This study could be replicated across various regions or nations, providing comparative insights into the adoption of social media among farmers for knowledge exchange. Practical implications The study findings suggest practical and innovative means to promote farmers’ social media adoption for agriculture knowledge exchange. Originality/value This study presents a pioneering approach by integrating social cognitive theory and neighborhood effect to elucidate the factors influencing farmers’ adoption of social media for the purpose of agriculture knowledge exchange.

Heterogeneous neighbourhood effects on the educational attainments of native Norwegian and immigrant-descendant female and male young adults

Using longitudinal register data from Oslo, Norway, this article examines how cumulative childhood exposure to family and neighbourhood contexts influences the educational attainments of young adults, paying special attention to how these determinants vary by gender and immigrant status. Specifically, we examine how neighbourhood socioeconomic and immigrant context experienced during childhood affects the completion of secondary school and university enrolment during young adulthood. We assess the extent of effect heterogeneity for three immigrant status groups stratified by gender. We control for geographical selection using a recently developed technique that first models parental selection of neighbourhood attributes and then uses the resulting predicted probabilities of selection as instruments in the neighbourhood-effects-on-education model. We find that neighbourhood affluence, educational levels and non-Western immigrant composition have important impacts on young adult educational outcomes, though results differ sharply by gender and immigrant status.

Investigating the neighborhood effect of urban morphological metrics on summertime land surface temperature variations in Istanbul, Turkey

Investigating the neighborhood effect of urban morphological metrics on summertime land surface temperature variations in Istanbul, Turkey

Chasing the heat: Unraveling urban hyperlocal air temperature mapping with mobile sensing and machine learning

Many cities face unprecedented high temperatures with increasing extreme events. Heatwaves pose significant health risks, including cardiovascular diseases, heatstroke, and dehydration. Mapping urban near-surface air temperature (Tair) is crucial for understanding thermal exposure and addressing climate change. Previous studies relied on satellite-derived land surface temperature (LST) and stationary monitoring, but high spaio-temporal Tair mapping is still a challenge. This study optimized a mobile sensing scheme using an electric bicycle platform with environmental and image sensors, and deep learning captured local-scale urban factors. A spatio-temporal data fusion model that consisted of three parts, temporal trend extraction, locality analysis, and neighborhood effect analysis, generated hyperlocal Tair maps. The Results from Beijing demonstrated the effectiveness of the framework, achieving the lowest MAE of 0.02 °C. Optimized data collection and the new model achieved accurate temperature predictions and thermal exposure assessment. Efficiency enhanced sensing strategy was also proposed. The study highlights local-scale factors and spatio-temporal dependencies in addressing heatwaves and climate change impacts in urban areas.

Neighborhood features moderate genetic and environmental influences on children's social information processing.

Neighborhood is a key context where children learn to process social information; however, the field has largely overlooked the ways children's individual characteristics might be moderated by neighborhood effects. We examined 1,030 six- to 11-year-olds (48.7% female; 82% White) twin pairs oversampled for neighborhood disadvantage from the Twin Study of Behavioral and Emotional Development in Children. We evaluated neighbor reports (N = 1,880) of neighborhood structural and social characteristics as moderators of genetic and environmental influences on children's social processing. Although there was no evidence of moderation for children's hostile attributions, there was robust evidence that the social and structural characteristics of the neighborhood moderated the genetic and environmental origins of children's positive expectations of aggressive behavior. Specifically, we found that genetic influences on aggressive expectations increased in the presence of neighborhood deprivation and decreased in the presence of protective social processes and availability of resources. Such findings suggest that protective neighborhood social processes may buffer against the development of aggressive expectations during middle childhood by suppressing the expression of genetic influences on those outcomes. In doing so, they suggest that neighborhood social processes may be able to promote youth resilience to neighborhood deprivation "under the skin." (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Graded phonological neighborhood effects on lexical retrieval: Evidence from Mandarin Chinese

How phonological neighborhood affects lexical retrieval can shed important light on lexical organization and processing. Yet these effects are unclear, particularly in Mandarin Chinese. This is likely because the working definition of phonological neighbors (i.e., the one-phoneme edit rule) used in Indo-European languages inadequately characterizes the phonological similarity among Mandarin words, which have simpler syllable structures and lexical tones. The current study proposes a graded Mandarin phonological neighborhood and investigates the impacts of near-to-distant Mandarin phonological neighbors on lexical retrieval. In Study 1, we investigated how Mandarin phonological similarity is influenced by the editing of lexical tone, constituent (onset/rime, initial/final) and phoneme. Native Mandarin speakers rated the similarity between the edited monosyllabic words. We found that constituent-edit neighbors were rated as the most dissimilar, followed by phoneme-edit neighbors, while tone-edit neighbors were the most similar. In Study 2, we calculated the constituent-, phoneme- and tone-edit phonological neighborhood densities and frequencies for 4,706 monosyllabic Mandarin words. We then utilized extant datasets to examine how the density and frequency of neighbors at varied distances, as well as of homophonic neighbors, impact response latencies in word naming, visual lexical decision, and picture naming tasks. The results showed that graded phonological neighbors had differential impacts on lexical retrieval efficiency: distant (constituent-edit) neighbors facilitated word retrieval, while near (phoneme-, tone-edit and homophonic) neighbors had inhibitory effects. We discuss these findings within an interactive activation and competition framework and suggest future directions to study the representation and processing of the Mandarin phonological lexicon.

The neighborhood effects on the online financial investment of rural households: Evidence from China.

Neighborhood effects are a common strategy for rural households to deal with irrational situations such as deficient information and ability. Based on the 2019 CHFS survey data, we designed a Probit model to verify whether neighborhood effects exist in the online financial investment of rural households. Our paper constructs a multiple mediation model to explore its mechanism. Otherwise, we execute the heterogeneity analysis by dividing the total sample into groups. Our paper proved that (1) Rural households have significant neighborhood effects on online financial investment. (2) Heterogeneity analysis shows that neighborhood effects are stronger among women, the younger, low-education, and low-income rural households. (3) Through the multiple mediation model, we proved that the neighborhood effects on online financial investment of the peasant household work by the financial knowledge spillover and risk-taking enhancement. Our study conduces to a better understanding of the financial decision-making of rural households, which may provide a practical implication for the popularization of new financial products and the optimal design of policy interventions.

Abstract 4833: Impact of poverty in surrounding neighborhoods in cancer mortality in the US: A nationwide study among US women

Abstract Background: Poverty at the individual and county levels is known to lead to worse cancer outcomes. We believe the relationship between poverty and cancer may involve individual-level factors including tumor biology, socioeconomic status, and community measures that alter cancer outcomes such as death. We aim to understand to what extent poverty in the surrounding neighborhood may identify counties at the highest risk of cancer mortality and whether it is modifiable. Methods: This study used data collected by SEER to examine the association between neighborhood effects of poverty on the top three sites of cancer mortality among women. We included women >= 20 years of age diagnosed with breast, lung, and colorectal cancer between 2005-2009 and 2010-2014 who survived more than one year after diagnosis. We determined county-level neighborhood poverty environments using local spatial autocorrelation (LISA) analysis with Local Moran’s I of five-year county-level poverty estimates from the American Community Survey. US counties with poverty estimates above or below the national median were defined as high (H)- or low (L)- poverty counties, respectively. We defined neighborhood poverty environments as H-counties among H-counties (HH), L-counties among L-counties (LL), H-counties among LL-counties (HL), and L-counties among HH-counties (LH). We used a Poisson regression model adjusting for age at diagnosis, race/ethnicity, cancer stage, year of diagnosis, treatment, and cancer type to assess county-level neighborhood poverty environment effects on cancer mortality. We also used stratified analyses to explore the effect of cancer type, stage, and race/ethnicity strata on the association between neighborhood poverty environments and cancer death. Results: Our analysis includes 36,481 women with 4,740 cancer deaths. In total 7,182 women were in HH counties; 21,112 women were in LL counties; 6,476 women were in HL counties; and 1,711 women were in LH counties. Women in HH, LH, and HL counties had a respective 1.23 [95%CI:1.14,1.32], 1.20 [95%CI:1.05,1.36], and 0.95 [95%CI: 0.88,1.03] relative risk (RR) of cancer death when compared to deaths in LL counties. In our stratified analyses, women with breast cancer in HH and HL counties had higher cancer deaths (RR = 1.21 [95%CI:1.03,1.42] and 1.37 [95%CI:1.13,1.65], respectively) when compared to women with lung cancer. We also observed higher cancer deaths from counties that were LL in 2005-2009 and changed to HH counties in 2010-2014 (RR = 1.60 [95%CI:0.85,2.68]) when compared to unchanged LL counties. Conclusion: We used LISA spatial clustering to demonstrate the effects HH and LH environments have on cancer mortality. We also demonstrate the impact that changes in neighborhood environments can have on cancer mortality. Our findings suggest that prioritization of resource allocations to HH neighborhoods could improve the burden of women with cancer. Citation Format: Ifeoma Nwigwe, Michael Desjardins, Kala Visvanathan. Impact of poverty in surrounding neighborhoods in cancer mortality in the US: A nationwide study among US women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4833.

Changing value system, shifting geography of opportunity: Trajectory of migrant workers in the garment industry in Beijing

Research on the geography of metropolitan opportunities has focused on a set of opportunities in different urban areas over time to justify policy interventions. The Beijing government implemented large-scale policy interventions to achieve structural industrial changes in order to stop the downward spiral of poverty and segregation in “urban villages.” Beijing has accelerated the redevelopment of urban villages and helped tens of thousands of low-wage migrant workers in garment villages move to surrounding secondary cities or small towns in Hebei Province with better opportunities. However, low-wage migrant workers did not respond linearly to the intervention. This study analyzes the reasons underlying the response of low-wage migrant workers to these policy interventions. First, the antipoverty policy is a geographic exercise, moving low-end industries from a global center to peripheral locations. This study considers why this mobility strategy for improving opportunity has become the arena for opportunistic behavior and conceptualizes the logic of opportunism and the self-worth of low-wage migrant workers in a metropolitan area. Second, the Beijing government is attempting to disperse the low-end informal industries into formal industrial bases in Hebei. Dispersal campaigns inevitably involve circuitous mobility and the outcome of dispersal is inherently unstable. One of the crucial questions in dispersal strategies is scale. Would an upscaled Beijing-Tianjin-Hebei (BTH) City Region or a downscaled “neighborhood effect” better implement the antipoverty strategy? This dispersal strategy can break up the concentration of migrants, but their perceived opportunities remain in Beijing. One of the obstacles to the full implementation of the dispersal strategy is grassroots opposition. This study uses a three-year survey conducted prior to the COVID−19 lockdown to analyze how displaced migrant workers perceive these opportunities in their processual and networked decision-making. Garment villages are important “anchor places” where migrants can mobilize their social capital and facilitate upward mobility outside a dominant institution in Beijing. This study reveals how garment workers replicated informal habitats in more remote locations in Beijing as the old habitats disappeared.

VST-PCA: A Land Use Change Simulation Model Based on Spatiotemporal Feature Extraction and Pre-Allocation Strategy

Land use/cover change (LUCC) refers to the phenomenon of changes in the Earth’s surface over time. Accurate prediction of LUCC is crucial for guiding policy formulation and resource management, contributing to the sustainable use of land, and maintaining the health of the Earth’s ecosystems. LUCC is a dynamic geographical process involving complex spatiotemporal dependencies. Existing LUCC simulation models suffer from insufficient spatiotemporal feature learning, and traditional cellular automaton (CA) models exhibit limitations in neighborhood effects. This study proposes a cellular automaton model based on spatiotemporal feature learning and hotspot area pre-allocation (VST-PCA). The model utilizes the video swin transformer to acquire transformation rules, enabling a more accurate capture of the spatiotemporal dependencies inherent in LUCC. Simultaneously, a pre-allocation strategy is introduced in the CA simulation to address the local constraints of neighborhood effects, thereby enhancing the simulation accuracy. Using the Chongqing metropolitan area as the study area, two traditional CA models and two deep learning-based CA models were constructed to validate the performance of the VST-PCA model. Results indicated that the proposed VST-PCA model achieved Kappa and FOM values of 0.8654 and 0.4534, respectively. Compared to other models, Kappa increased by 0.0322–0.1036, and FOM increased by 0.0513–0.1649. This study provides an accurate and effective method for LUCC simulation, offering valuable insights for future research and land management planning.

Abstract 19: Time-Varying Exposure to Food Retailers and Cardiovascular Disease Incidence and Mortality in the Netherlands: A Nationwide Prospective Cohort Study

Background: The food environment is suggested as a risk factor of cardiovascular disease (CVD), but current evidence is inconsistent and does not account for changes in the food environment. We aimed to explore if time-varying exposure to the food environment was associated with hospitalisation and mortality due to total and specific types of CVD in The Netherlands. We hypothesized that favourable time-varying trends in food environment exposure would be associated with decreased risk of CVD, stroke, heart failure (HF), and coronary heart disease (CHD) morbidity and mortality among the Dutch general population. Methods: A prospective cohort study was performed among all Dutch residents aged 35+ years who did not change residence in 2002-2018 without CVD in 2004, identified through registry data from Statistics Netherlands (n=4,641,435; 51.3% female, 91.2% Dutch). Time-varying Food Environment Healthiness Index (FEHI) scores (range: -5 to 5) and time-varying Kernel density of six specific food retailers (food delivery outlets, fast food outlets, restaurants, local food shops, supermarkets and convenience stores) around the home location were based on bi-annual updates between 2004-2018. Hospitalisation and mortality due to overall CVD, stroke, HF, and CHD occurring between 2004 and 2020 were used as outcomes, based on hospital and death registries. Models were adjusted for age, sex, ethnic origin, household composition, income, marital status and neighbourhood urbanisation level and effect modification by age, sex, urbanization and income was studied. Results: Each unit increase in the FEHI, representing a 10% improvement, was associated with a lower hospitalisation and mortality of CVD (hospitalization Hazard Ratio (HR h )=0.90, 0.89-0.91, mortality Hazard Ratio (HR m )=0.85, 0.82-0.89), CHD (HR h =0.88, 0.85-0.91, HR m =0.80, 0.75-0.86), stroke (HR h =0.89, 0.84-0.93, HR m =0.89, 0.82-0.98), and HF (HR h =0.90, 0.84-0.96, HR m =0.84, 0.76-0.92). Increased density of local food shops, fast food outlets, supermarkets and convenience stores, and decreased density of food delivery outlets and restaurants were associated with a higher risk of CVD, CHD, stroke and HF incidence and mortality, albeit with small effect sizes. Stratified analyses suggest slightly stronger associations in highly urbanized areas, younger adults and those with higher incomes. Conclusions: Favourable trends in time-varying food retailer exposure were associated with a risk reduction in CVD hospitalisation and mortality, in particular in urbanized areas and for younger adults and those with higher incomes.

Legitimising displacement: Academic discourse, territorial stigmatisation and gentrification

This article explores the territorial stigmatisation–gentrification nexus and how it is advanced by an intellectual pipeline between academics and policymakers in the USA. Despite much research revealing the pathologising narratives latent within displacement-inducing urban policies, little work has explicitly sought to underscore the influence of academic discourses in promoting these policies. Centring a triad of discourses surrounding concentrated disadvantage, social mix and neighbourhood effects – emergent namely from the academic fields of urban sociology, criminology, urban planning and urban economics – I provide an evidential linkage between academic discourse and displacement-causing US policymaking by conducting a document analysis of official reports related to two major US government programmes: the Moving to Opportunity for Fair Housing (MTO) Demonstration programme and the Housing Opportunities for People Everywhere (HOPE) VI programme. I suggest that these academic discourses operate to legitimise displacement via neighbourhood-centric framings which advance territorial stigmatisation and related gentrification. These discourses, I argue, reinforce the real estate state and the destructive capitalist force of uneven geographical development while working to facilitate the disregard of propositions that would effect structural change. I conclude with an explanation for the present configuration of the academy-to-policy pipeline and why it has failed to onboard critical, macro-structurally orientated scholarship, and issue a call for a direction forward.

Spatiotemporal variation in the negative effect of neighbourhood crowding on stem growth

Abstract Neighbourhood interactions drive tree growth and forest ecosystem functioning. The strength of interactions depends on the climate. However, it remains unclear how plant–plant interactions are modified by environmental conditions operating both spatially and temporally, which is crucial for predicting forest dynamics under climate change and for effective forest management. In this study, we used annual growth data for 4139 stems from 2010 to 2021 across 50 permanent forest plots located at six sites in eastern China. We quantified the effect of neighbourhood crowding on the annual basal area increment. We explored how interactions among neighbouring trees vary with water availability and temperature gradients in the spatial (across sites) and temporal (across time within sites) dimensions. Our findings revealed a negative impact of neighbourhood crowding on stem basal area growth, which is size‐ and trait‐dependent at some sites. The negative effects of light competition tended to be more intense at warmer sites, supporting the stress‐gradient hypothesis (SGH) in a spatial dimension. However, the patterns of crowding effects along interannual climate anomalies are inconsistent across sites, making it difficult to predict crowding effects under the SGH framework in a temporal dimension. Synthesis: Our study demonstrated that tree interactions depend on the climate context. The climate dependence of interactions may be inconsistent between the spatial and temporal dimensions. Light competition across sites supported the SGH in the spatial dimension but not in the temporal dimension. These results further highlight the complexity of biotic interactions and the need for caution when extrapolating findings from the spatial to the temporal dimension.

Environmental regulation and carbon emissions: New mechanisms in game theory

The effective implementation of environmental regulations is crucial for mitigating environmental pollution. During the regulatory process, local governments engage in an interactive game. Based on sample data from 275 Chinese cities between 2012 and 2020, our findings demonstrate that local governments adopt imitative strategies, resulting in a “race to the top competition” in environmental regulation. The attention given by local governments to environmental protection, combined with the central government's restrictions on emission reduction targets, enhances the effectiveness of carbon emission reduction through environmental regulation. However, the inhibitory effect of environmental regulation on carbon emissions is diminished when local governments attract low-quality foreign direct investment (FDI). Additionally, both local and neighborhood effects of environmental regulation exhibit significantly positive impacts on carbon emissions in the eastern and central regions. In contrast, the western regions show significantly negative effects. Finally, our study reveals that environmental regulation has positive carbon emission reduction effects in non-pollution and pollution-prevention cities, as well as resource and non-resource cities. This study provides insight for China's “double‑carbon goal” and offers positive implications for the effective implementation of environmental regulations.

Revealing per-grain and neighbourhood stress interactions of a deforming ferritic steel via three-dimensional X-ray diffraction

The structural performance of polycrystalline alloys is strongly controlled by the characteristics of individual grains and their interactions, motivating this study to understand the dynamic micromechanical response within the microstructure. Here, a high ductility single-phase ferritic steel during uniaxial deformation is explored using three-dimensional X-ray diffraction. Grains well aligned for dislocation slip are shown to possess a wide intergranular stress range, controlled by per-grain dependent hardening activity. Contrariwise, grains orientated poorly for slip have a narrow stress range. A grain neighbourhood effect is observed of statistical significance: the Schmid factor of serial adjoining grains influences the stress state of a grain of interest, whereas parallel neighbours are less influential. This phenomenon is strongest at low plastic strains, with the effect diminishing as grains rotate during plasticity to eliminate any orientation dependent load shedding. The ability of the ferrite to eliminate such neighbourhood interactions is considered key to the high ductility possessed by these materials.