Distance Decay Research Articles

Terroir and farming practices drive arbuscular mycorrhizal fungal communities in French vineyards

BackgroundNature-based management of vineyards is at the heart of a sustainable development for the next decades. Although much is known about grapevine benefits from Arbuscular Mycorrhizal Fungi (AMF), little is known about the influence of vineyard terroir and farming practices on AMF communities.MethodsWe examined the relative effect of wine terroir and agricultural practices (organic, conversion, and conventional) on AMF abundance and diversity across 75 vineyards distributed over 14 wine terroirs in 6 winegrowing regions in France. We estimate AMF abundance by measuring spore density and root mycorrhization rates, and characterize AMF communities composition using metabarcoding by sampling both root and spore compartments for each vineyard.ResultsOrganic farming slightly increases AMF abundance (spore density and mycorrhization rate). Vineyards under conversion and using organic practices display a higher AMF diversity than conventional ones. Terroirs vary widely in terms of AMF abundance and diversity, with the median of OTUs count per sample ranging from 9 (Côte des Blancs) to 35 (Gigondas). The composition of AMF communities is structured mainly by terroir and in a lesser extent by practice. The effect of terroir on AMF communities is partially explained by distance decay and soil properties, but the majority of variation is still explained only by the terroir identity. Organic practices improve both abundance and diversity of AMF in vineyards, possibly leading to more productivity and resilience of grapevines.ConclusionThis large-scale study highlights the importance of terroir in our understanding of vineyard microbiome and paves the way to incorporation of AMF in microbial terroir studies and applications.

Does quantity matter for distance decay? Evidence from two choice experiments on urban green

The value of environmental goods to individuals often depends on spatial features such as distance. The most common approach of accounting for distance decay is to model utility as some function of distance. It has been suggested to instead model the value as a function of the quantity of an environmental good within a certain distance. We develop three novel quantity-within-distance models that may be more suited for evaluating quantity changes in an environmental good. We argue that these models could capture spatial patterns better than distance-based models when i) secondary benefits are a relevant source of welfare, ii) the environmental change is spatially scattered, iii) the distribution of the endowment, i.e. the present availability of the environmental good, matters. Using data from choice experiments on the extension of green space and trees in two urban areas, we compare required assumptions, model fit, and size and precision of aggregated welfare estimates. Our results indicate limited differences in model fit. However, the quantity-within-distance models consistently produce aggregate welfare estimates roughly half of common distance decay models and have narrower confidence intervals. While it is not possible to infer which is more accurate, the large differences can have considerable policy implications.

Organic Micropollutants in Waterways of a Large-Scale Water Diversion Project: Insights from Nontarget Screening and "Community" Analysis.

Large-scale water diversion projects are essential for meeting the needs of water-stressed regions, necessitating an evaluation of their impact on water quality and aquatic ecosystems. This study provides the first snapshots of organic micropollutants (OMPs) along the 1466 km Eastern Route of China's South-to-North Water Diversion Project. Using nontarget analysis with ultrahigh-performance liquid chromatography and high-resolution mass spectrometry, we identified and quantified 357 OMPs from water samples collected during the water diversion period (WDP) and the nonwater diversion period (NWDP). The OMPs included 136 household compounds, 112 agricultural compounds, 102 industrial compounds, and 7 traffic markers. Significant regional variations in OMP concentrations and compositions were observed during the NWDP due to diverse local pollution sources along the route. However, such differences were reduced during the WDP, likely due to water transfer. OMP diversity varied substantially during the NWDP but was more stable with less distance decay during the WDP. Network analysis indicated closer relationships between the OMPs during the WDP, suggesting a more consistent spatial distribution. The source water overwhelmingly influenced the water quality along the diversion route. These findings underscore the need for ongoing assessments of the impact of water diversion on regional water quality and ecosystems.

Neural Density Functional Theory of Liquid-Gas Phase Coexistence

We use supervised machine learning together with the concepts of classical density functional theory to investigate the effects of interparticle attraction on the pair structure, thermodynamics, bulk liquid-gas coexistence, and associated interfacial phenomena in many-body systems. Local learning of the one-body direct correlation functional is based on Monte Carlo simulations of inhomogeneous systems with randomized thermodynamic conditions, randomized planar shapes of the external potential, and randomized box sizes. Focusing on the prototypical Lennard-Jones system, we test predictions of the resulting neural attractive density functional across a broad spectrum of physical behavior associated with liquid-gas phase coexistence in bulk and at interfaces. We analyze the bulk radial distribution function g(r) obtained from automatic differentiation and the Ornstein-Zernike route and determine (i) the Fisher-Widom line, i.e., the crossover of the asymptotic (large distance) decay of g(r) from monotonic to oscillatory, (ii) the (Widom) line of maximal correlation length, (iii) the line of maximal isothermal compressibility, and (iv) the spinodal by calculating the poles of the structure factor in the complex plane. The bulk binodal and the density profile of the free liquid-gas interface are obtained from density functional minimization and the corresponding surface tension from functional line integration. We also show that the neural functional describes accurately the phenomena of drying at a hard wall and of capillary evaporation for a liquid confined in a slit pore. Our neural framework yields results that improve significantly upon standard mean-field treatments of interparticle attraction. Comparison with independent simulation results demonstrates a consistent picture of phase separation even when restricting the training to supercritical states only. We argue that phase coexistence and its associated signatures can be discovered as emerging phenomena via functional mappings and educated extrapolation. Published by the American Physical Society 2025

Capturing the distance decay effect of amenities on housing price using explainable artificial intelligence

Capturing the distance decay effect of amenities on housing price using explainable artificial intelligence

Critical Behavior of Cobalt-doped van der Waals Ferromagnet (Fe0.74Co0.26)3GeTe2

Two-dimensional (2D) van der Waals (vdW) ferromagnet Fe3GeTe2 (FGT) demonstrates considerable potential for applications in spintronics due to its relatively high Curie temperature (TC) and strong perpendicular magnetic anisotropy. Moreover, these demanding magnetic properties are sensitive to the Fe contents and can be effectively tuned by substituting Fe with other elements, especially the cobalt (Co) doping. Here, we delve into the magnetic critical behavior of the Co-doped vdW ferromagnet (Fe0.74Co0.26)3GeTe2 (FCGT). Utilizing a range of techniques including modified Arrott plots, Widom scaling method, the Kouvel-Fisher approach, and critical isotherm analysis, we derived reliable and self-consistent critical exponents: β = 0.360, γ = 1.043, δ = 3.87, with a TC of 134.3K. These critical exponents of FCGT do not conform to a single theoretical model but instead lie between the Mean-field model and the three-dimensional Heisenberg one. Despite the distinct critical exponents, Co doping does not alter the critical behavior intrinsic to the FGT. Further investigation implies the FCGT sustains long-range magnetic interactions, as evidenced by the magnetic exchange distance decay of J(r) ≈ r-4.566. Our work could offer insights for the understanding of the macroscopic magnetic behavior of vdW ferromagnets doped with other transition metals.

Non-consumptive value of hilsa fishery restoration in West Bengal, India: An application of contingent valuation method.

The study focuses on the socio-cultural importance of hilsa fishery in West Bengal, which extends beyond mere sustenance, symbolising heritage, identity, and community spirit, particularly in South 24 Parganas district. As the state fish and a crucial livelihood source for many fishers, grave concerns have recently been flagged due to reduced catches and increased prices, highlighting the need for restoration. This study seeks to measure the non-consumptive value of hilsa fishery by involving 200 participants, 100 fishers and 100 consumers, utilising the Contingent Valuation Method (CVM) with a payment card. Tobit model, income and price elasticity analysis, Mann-Whitney U test, and Independent Student's t-test were applied. The yearly non-consumptive value for hilsa fishery restoration in South 24 Parganas spans from INR 42.75 crore to INR 104.54 crore (approximately US$ 5.13M to US$ 12.54M per annum). The presence of distance decay, evident from the negative relation of willingness to pay (WTP) with distance, invalidated statewide WTP aggregation. Extrapolating estimates to nine neighbouring hilsa-producing districts gave estimates ranging from INR 315.63 crore to INR 771.88 crore (approximately US$ 37.9 million to US$ 92.8 million). Results highlight statistical socio-economic differences between fishermen and consumers, signifying diverse perspectives. The Tobit model identifies common factors influencing WTP, including income earners, average family income, and respondents' involvement with NGOs, emphasising the role of socio-economic factors in shaping WTP. Both income and price elasticity of WTP were below one, indicating that economically weaker groups demonstrate a relatively higher willingness to pay for hilsa fish restoration, underscoring their reliance on this fishery for livelihoods. The study proposes that investment of a portion of the estimated non-consumptive value could significantly bolster hilsa restoration, benefiting economically weaker groups, improving overall livelihoods, and safeguarding the cultural heritage.

Gravity Model Approach to Model Epidemic with Human Dispersal Behaviors

The gravity model which is based on Newton’s gravitational law, has been widely used as a spatial interaction model in the past few decades. Spatial interactions are important in epidemic modeling as different populations in the world are interconnected by them. Human dispersal behaviors are spatial interactions and they are crucial aspects of infectious disease spread. However, many existing compartmental models model epidemics in a single area. Hence, a gravity model approach to model epidemics incorporated with a multipatch compartmental model is studied here. Both human dispersal behaviors within a patch and between patches are considered. When the human dispersal behaviors within a patch are modeled, the denominator of the general gravity model becomes zero. An alternative power-based distance decay function is introduced to the gravity model to address that research gap. The parameters of the modified gravity model are estimated using a hybrid method combining ordinary least squares (OLS) and nonlinear least squares (NLS) methods (Hybrid OLS-NLS method).

Optimal drag-based collision avoidance: Balancing miss distance and orbital decay

The increasing number of objects in Low Earth Orbit makes active collision avoidance imperative for satellites operating in this region. For satellites non equipped with propulsion systems, the collision risk can be mitigated by exploiting the active modulation of aerodynamic forces through the ballistic coefficient. This article proposes a novel and high-fidelity optimal control approach for collision avoidance via aerodynamic drag modulation for an unpropelled SmallSat. Central to this approach is a cost function that jointly maximizes the miss distance while minimizing orbital decay during the maneuver. Moreover, the proposed approach has been rigorously tested through its application to the real-world scenario of the SOURCE satellite, slated for launch in 2025. For the satellite under investigation and a maneuver altitude of 350km, an in-track separation distance of around 22km can be accomplished within a warning time of 24h, which is large enough to conclude that the collision was successfully avoided. As a downside, however, this results in an additional loss in the semi-major axis of 165m and thus a reduced lifetime of the satellite. This balance between separation distance and additional loss in altitude can be flexibly adjusted by the user, which is demonstrated extensively in the article by means of a parameter study. Compared to the widespread use of chemical propulsion systems, this strategy naturally demands longer warning times due to the significantly lower available forces, and also radial offsets to the potential collision object cannot be in this case. Nevertheless, it offers a very promising alternative for active collision avoidance, especially for low-altitude applications.

A Multi-Source Data-Driven Analysis of Building Functional Classification and Its Relationship with Population Distribution

Buildings, as key factors influencing population distribution, have various functional attributes. Existing research mainly focuses on the relationship between land functions and population distribution at the macro scale, while neglecting the finer-grained, micro-scale impact of building functionality on population distribution. To address this issue, this study integrates multi-source geospatial and spatio-temporal big data and employs the XGBoost algorithm to classify buildings into five functional categories: residential, commercial, industrial, public service, and landscape. The proposed model innovatively incorporates texture, geometric, and temporal features of building images, as well as socio-economic characteristics extracted using the distance decay algorithm. The results yield the following conclusions: (1) The proposed method achieves an overall classification accuracy of 0.77, which is 0.12 higher than that of the random forest-based approach. (2) The introduction of time features and the distance decay method further improved the model performance, increasing the accuracy by 0.04 and 0.03, respectively. (3) The correlation between the building functions and population distribution varies significantly across different scales. At the district and county levels, residential, commercial, and industrial buildings show a strong correlation with population distribution, whereas this correlation is relatively weak at the street scale. This study advances the understanding of building functions and their role in shaping population distribution, providing a robust framework for urban planning and population modeling.

What determines travel time and distance decay in spatial interaction and accessibility?

The concept of ‘distance decay’ curves is used in spatial interaction and accessibility analysis to represent the diminishing likelihood of visiting places with increasing travel impedance, mainly distance and travel time. The shape of the resulting impedance decay curves varies by several factors, but these influential factors are often dismissed in favor of just travel mode. In this study, we examine which factors should be used to distinguish impedance functions for use. Using data from a large national travel survey, we first show that the impedance curves are well approximated by functions of the exponential family and the related Tanner function. We use two methods – variable-wise function fit and Shapley additive explanations – to conclude the importance of four factors for developing impedance functions. These are travel mode, trip purpose, urbanity class of trip origin and destination, and the socioeconomic status grouping of the travelers. We then show that the use of a generalized impedance function can significantly over- or underestimate spatial accessibility compared to factor-specific impedance function, with up to 80 % overestimation on average in the case of public transit and 16 % overestimation for low socio-economic status travelers. These findings highlight the importance of the choice of impedance function which has applications in spatial economics, transportation planning, and human mobility analyses.

Do Theoretical Assumptions of Geographic Profiling Hold When Scrutinising Commuter Serial Rape Offenders in South Africa?

ABSTRACTGeographic profiling (GP) can be regarded as vital within the apparatus of investigating serial offenders. Since prevailing theories focus on offenders emanating from developed countries, the aim of this study was to examine, amongst others, the uncertainty that exists regarding their relevance in the South African context. This study, therefore, focused on South African commuter serial rapists and, in particular, their correlation with distance decay, the least effort principle, and buffer zones. While the overall data revealed a strong link between theories related to crime pattern, routine activity, awareness, and activity space, theories about distance decay, buffer zones, and the least effort principle had far weaker associations. Fundamentally, the study challenged existing assumptions that a commuter serial rapist profile could not be determined prematurely in an investigation, highlighting the ability to distinguish commuter offenders based on their directional behaviour within their convex hull(s). The research found that understanding these distinctions underscores the need for a theoretical perspective that better grasps the spatial reality of crime in this context.

Contrasting pollution responses of native and non-native fish communities in anthropogenically disturbed estuaries unveiled by eDNA metabarcoding

Understanding the influence of environmental pollutants on the assembly mechanisms of estuarine fish communities is vital for addressing conservation challenges in these biodiverse ecosystems. Although significant research has explored the toxic impacts of pollutants such as petroleum, heavy metals, and eutrophication on individual species and populations, their effects on community assembly processes and the differential responses of native versus non-native fish at the meta-community level remain inadequately understood. This study utilized environmental DNA (eDNA) metabarcoding to analyze fish community diversity across 28 subtropical estuaries in China, assessing how these pollutants affect community composition and assembly mechanisms. Results indicated that eDNA was 2.54 times more effective than traditional methods in species identification, while also enabling the detection of a higher number of non-native fish species and more diverse functional guilds within estuarine ecosystems. A significant distance decay pattern (p < 0.05) was observed among native fish, whereas non-native species exhibited non-significant patterns. Neutral and null models showed that non-native species had significantly higher migration rates (0.005939 vs 0.001757) and a greater contribution of stochastic processes (82.38 % vs 70.59 %) compared to native species. Additionally, distance-based redundancy analysis (db-RDA), variance partitioning analysis (VPA), and correlation analyses revealed that native species were strongly constrained by environmental factors, particularly oil, Hg, Zn, Pb, Cr6+, and NH4+, while non-native species displayed notable resilience to these pollutants. These findings highlight the potential for non-native species to disproportionately influence community dynamics and assembly through unrestricted random dispersal amid environmental disturbances. This research clarifies the contrasting ecological responses of native and non-native fish communities to anthropogenic pressures in estuarine environments, offering essential insights into ecosystem resilience and informing biodiversity conservation strategies in rapidly changing coastal ecosystems.

Environmental supervision distance, government-enterprise collusion and corporate environmental information disclosure

Based on the framework of government-enterprise collusion and proactive government regulation, this study examines the impact of the Environmental Protection Agency (EPA) regulatory distance on corporate environmental information disclosure (EID) using data from listed companies in China from 2009 to 2021. The results of the study show that: (1) The closer the geographical distance between the local EPA and the company, the poorer the quality, which verifies the collusion effect. Our results are robust after a series of robustness checks. (2) The collusion effect of geographical distance primarily works by enhancing the ability of companies to seek environmental protection. (3) The impact is greater when the sample company belongs to non-sub-provincial municipal, pollution industry, state-owned, large-scale, and mature enterprises. (4) The central environmental inspections and media attention can alleviate the collusion effect of environmental regulatory distance. This study provides new empirical evidence for the " distance decay effect " in geo-economics and offers new insights from the perspective of geo-economics for measuring government-enterprise collusion.

Potential and Observed Supply–Demand Characteristics of Medical Services: A Case Study of Nighttime Visits in Shenzhen

Hospital selection patterns are essential for evaluating medical accessibility and optimizing resource management. In the absence of medical records, early studies primarily used accessibility functions to estimate potential selection probabilities (PSPs). With the advent of travel data, data-driven functions have enabled the calculation of observed selection probabilities (OSPs). Comparing PSP and OSP helps to leverage travel data to understand hospital selection preferences and improve medical service evaluation models. This study proposes a selection probability-based accessibility model for calculating PSP and OSP accessibility. A case study in Shenzhen employed nighttime navigation data to reduce interference from different travel modes. The distance decay function was validated, with exponential and Gaussian functions performing best. For hospitals, the PSP distribution closely aligned with OSP, except in areas with high hospital density. This discrepancy may result from the PSP function overestimating the selection probability for nearby hospitals, a limitation that could be addressed by fitting the distance decay function to actual data. PSP-based accessibility and Gini coefficients differ from those of OSP. However, when parameters are fitted to actual data, the PSP- and OSP-based functions produce nearly identical results. Fitting to actual data can notably improve the accuracy of PSP and the corresponding accessibility outcomes. These findings may provide valuable references for medical service evaluation methodologies and offer insights for planning and management.

A Novel Interpolation Method for Soil Parameters Combining RBF Neural Network and IDW in the Pearl River Delta

Soil fertility is a critical factor in agricultural production, directly impacting crop growth, yield, and quality. To achieve precise agricultural management, accurate spatial interpolation of soil parameters is essential. This study developed a new interpolation prediction framework that combines Radial Basis Function (RBF) neural networks with Inverse Distance Weighting (IDW), termed the IDW-RBFNN. This framework initially uses the IDW method to apply preliminary weights based on distance to the data points, which are then used as input for the RBF neural network to form a training dataset. Subsequently, the RBF neural network further trains on these data to refine the interpolation results, achieving more precise spatial data interpolation. We compared the interpolation prediction accuracy of the IDW-RBFNN framework with ordinary Kriging (OK) and RBF methods under three different parameter settings. Ultimately, the IDW-RBFNN demonstrated lower error rates in terms of RMSE and MRE compared to direct RBF interpolation methods when adjusting settings based on different power values, even with a fixed number of data samples. As the sample size decreases, the interpolation accuracy of OK and RBF methods is significantly affected, while the error of IDW-RBFNN remains relatively low. Considering both interpolation accuracy and resource limitations, we recommend using the IDW-RBFNN method (p = 2) with at least 60 samples as the minimum sampling density to ensure high interpolation accuracy under resource constraints. Our method overcomes limitations of existing approaches that use fixed steady-state distance decay parameters, providing an effective tool for soil fertility monitoring in delta regions.

Bridging the education gap: A comprehensive analysis of travel distance and education quality based spatial accessibility of early childhood education in Metropolitan Melbourne

In Australia, Melbourne's population is growing rapidly and will soon overtake Sydney, fuelled by a COVID-19 baby boom that has increased demand for early childhood education (ECE). In response, the Victorian Government has announced transformational reforms to improve the accessibility and quality of ECE for the growing urban population. This study aims to addresses the evolution and effectiveness of ECE reforms in Melbourne from 2021 to 2036 by proposing an innovative approach that integrates spatial accessibility and educational quality into ECE evaluations. Using the distance decay function, the Floating Catchment Area (FCA) method and the Huff model, it extends traditional geographical analyses by highlighting the importance of educational quality in parental choice and providing a refined technique for simulating local demand based on educational quality and travel distance. Overall, inequalities in educational resources have been identified, with a concentration of ECE services near the CBD, despite high population density, while peripheral areas have significant service deficits. Furthermore, the projected poor accessibility scores for 2026, 2031 and 2036 highlight the urgent need for educational infrastructure development, even in areas rated as having better accessibility in 2021.

Access to urban community mental health services: does geographical distance play a role?

Mental health challenges are a pressing concern in Australia, which account for a significant portion of the disease burden and economic costs, yet a substantial number of those affected do not utilise necessary professional support. This study evaluates distance decay effect on adults' community mental health services in North Metropolitan Western Australia and explores factors influencing service use. Data were extracted from the Mental Health Information Data Collections including the records of consumers receiving face-to-face services from the Community Mental Health Clinics in the North Metro Health Service during March 2022 to March 2023. Additionally, socio-demographic information for each suburb and population data were obtained from the Australian Bureau of Statistics. The distance between residential suburbs and clinic locations was calculated. Descriptive statistics were used to describe the characteristics of the study population. A hierarchical linear regression analysis was used to explore whether the distance of suburb to the nearest community clinic was related to service utilisation. A total of 3,453 consumers received direct services across the North Metro Health Service Community Mental Health Clinics. Findings highlighted the impact of proximity to clinics on service utilisation, with suburbs closer to clinics exhibiting higher visit rates (p = 0.004). The data also showed a strong positive correlation between gender (percentage of females in the suburb) and living in socially and economically disadvantaged areas with consumer visits per thousand residents. These findings underscore the importance of addressing accessibility barriers and tailoring mental health services to meet the diverse needs of the community.

Discovering implicit role of tourists’ perceived distance and emotions in decision-making: combing grounded theory and sentiment analysis

ABSTRACT Analysing the attitudes and emotions behind tourists’ perceptions of distance provides powerful assistance for destination marketers and scholars. However, there is yet to be a universally adopted scale of tourists’ perceived distance. It is hard to effectively extract tourists’ attitudes from the distance scale toward a destination. This paper identifies the critical dimensions of perceived distance voiced by 19 Chinese tourists with grounded analysis, an inductive, comparative, and interactive method that effectively captures nuanced information. Advanced techniques for linguistic analysis provide the opportunity to extract emotional meaning from tourists’ textual data through the Latent Dirichlet Allocation (LDA) algorithm. The results identify a set of appraisal dimensions as antecedents to perceived distance. With cognitive appraisal theory (CAT), different evaluations on these dimensions provide multiple paths to eliciting emotion change. The findings contrast with previous research in the distance decay model, which noted a single distance involving tourism demand. We also find differences based on demographic segments. Social network analysis helps further identify the relationship between dimensions. We conclude by discussing the study's implications for future studies and practice.

Effect of environmental DNA sampling resolution in detecting nearshore fish biodiversity compared to capture surveys.

Sampling and sequencing marine environmental DNA (eDNA) provides a tool that can increase our ability to monitor biodiversity, but movement and mixing of eDNA after release from organisms before collection could affect our inference of species distributions. To assess how conditions at differing spatial scales influence the inferred species richness and compositional turnover, we conducted a paired eDNA metabarcoding and capture (beach seining) survey of fishes on the coast of British Columbia. We found more taxa were typically detected using eDNA compared to beach seining. eDNA identified more taxa with alternative habitat preferences, and this richness difference was greater in areas of high seawater movement, suggesting eDNA has a larger spatial grain influenced by water motion. By contrast, we found that eDNA consistently missed low biomass species present in seining surveys. Spatial turnover of communities surveyed using beach seining differed from that of the eDNA and was better explained by factors that vary at small (10-1000s meters) spatial scales. Specifically, vegetation cover and shoreline exposure explained most species turnover from seining, while eDNA turnover was not explained by those factors and showed a distance decay pattern (a change from 10% to 25% similarity from 2 km to 10 km of distance), suggesting unmeasured environmental variation at larger scales drives its turnover. Our findings indicate that the eDNA sample grain is larger than that of capture surveys. Whereas seining can detect differences in fish distributions at scales of 10s-100s of meters, eDNA can best summarize fish biodiversity at larger scales possibly more relevant to regional biodiversity assessments.