Francesco Mazzarini , Nicolas Le Corvec , Ilaria Isola
{"title":"自相似的火山口空间聚类:来自全球火山场的岩浆储存深度洞察","authors":"Francesco Mazzarini , Nicolas Le Corvec , Ilaria Isola","doi":"10.1016/j.jvolgeores.2025.108431","DOIUrl":null,"url":null,"abstract":"<div><div>The spatial distribution of volcanic vents in volcanic fields provides critical insights into the structure of underlying magma plumbing systems and the influence of crustal structures and state of stress on magma ascent. This study investigates self-similar clustering of vents in 46 volcanic fields from diverse geotectonic settings to assess whether vent distribution consistently follows fractal patterns, regardless of parametric statistical classifications. Spatial analyses using Nearest Neighbour Distance, Vent-to-Vent Distance and Kernel Density Estimation confirm that the vent self-similar clustering is a fundamental characteristic of distributed volcanism.</div><div>The analysis reveals that self-similar clustering is present in all volcanic fields, even in cases where parametric methods suggest a random or over-dispersed distribution. The vent self-similar clustering is defined within a length range bounded by two thresholds, the lower (Lco) and the upper (Uco) cut-offs. They correspond to the shallow depth (< 5 km) at which magma may accumulate without leading to eruption and the depth of the magma reservoir or dike propagation zone, respectively. A strong positive correlation between Uco and magma reservoir depth (H) suggests that vent clustering reflects subsurface magma transport dynamics. Statistical tests confirm that γ₁ and γ₂ parameters, previously defined for volcanic fields in the Main Ethiopian Rift, are effective indicators of vent clustering, with γ₁ consistently ≤0.1 for clustered fields.</div><div>These findings underscore the role of fracture networks as efficient pathways for magma ascent, supporting the hypothesis that magma effusion sites are intrinsically linked to crustal mechanical properties. Future research should explore how fracture network evolution influences vent distribution over time and whether the vent self-similar clustering analysis can improve constraints on magma reservoir dynamics and eruption forecasting. Furthermore, applying this framework to extraterrestrial volcanic fields (e.g., Mars) could provide new insights into universal processes governing vent clustering in different planetary environments.</div></div>","PeriodicalId":54753,"journal":{"name":"Journal of Volcanology and Geothermal Research","volume":"467 ","pages":"Article 108431"},"PeriodicalIF":2.3000,"publicationDate":"2025-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Self-similar spatial clustering of volcanic vents: Insights into magma storage depth from global volcanic fields\",\"authors\":\"Francesco Mazzarini , Nicolas Le Corvec , Ilaria Isola\",\"doi\":\"10.1016/j.jvolgeores.2025.108431\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The spatial distribution of volcanic vents in volcanic fields provides critical insights into the structure of underlying magma plumbing systems and the influence of crustal structures and state of stress on magma ascent. This study investigates self-similar clustering of vents in 46 volcanic fields from diverse geotectonic settings to assess whether vent distribution consistently follows fractal patterns, regardless of parametric statistical classifications. Spatial analyses using Nearest Neighbour Distance, Vent-to-Vent Distance and Kernel Density Estimation confirm that the vent self-similar clustering is a fundamental characteristic of distributed volcanism.</div><div>The analysis reveals that self-similar clustering is present in all volcanic fields, even in cases where parametric methods suggest a random or over-dispersed distribution. The vent self-similar clustering is defined within a length range bounded by two thresholds, the lower (Lco) and the upper (Uco) cut-offs. They correspond to the shallow depth (< 5 km) at which magma may accumulate without leading to eruption and the depth of the magma reservoir or dike propagation zone, respectively. A strong positive correlation between Uco and magma reservoir depth (H) suggests that vent clustering reflects subsurface magma transport dynamics. Statistical tests confirm that γ₁ and γ₂ parameters, previously defined for volcanic fields in the Main Ethiopian Rift, are effective indicators of vent clustering, with γ₁ consistently ≤0.1 for clustered fields.</div><div>These findings underscore the role of fracture networks as efficient pathways for magma ascent, supporting the hypothesis that magma effusion sites are intrinsically linked to crustal mechanical properties. Future research should explore how fracture network evolution influences vent distribution over time and whether the vent self-similar clustering analysis can improve constraints on magma reservoir dynamics and eruption forecasting. Furthermore, applying this framework to extraterrestrial volcanic fields (e.g., Mars) could provide new insights into universal processes governing vent clustering in different planetary environments.</div></div>\",\"PeriodicalId\":54753,\"journal\":{\"name\":\"Journal of Volcanology and Geothermal Research\",\"volume\":\"467 \",\"pages\":\"Article 108431\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2025-08-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Volcanology and Geothermal Research\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0377027325001672\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Volcanology and Geothermal Research","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0377027325001672","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
Self-similar spatial clustering of volcanic vents: Insights into magma storage depth from global volcanic fields
The spatial distribution of volcanic vents in volcanic fields provides critical insights into the structure of underlying magma plumbing systems and the influence of crustal structures and state of stress on magma ascent. This study investigates self-similar clustering of vents in 46 volcanic fields from diverse geotectonic settings to assess whether vent distribution consistently follows fractal patterns, regardless of parametric statistical classifications. Spatial analyses using Nearest Neighbour Distance, Vent-to-Vent Distance and Kernel Density Estimation confirm that the vent self-similar clustering is a fundamental characteristic of distributed volcanism.
The analysis reveals that self-similar clustering is present in all volcanic fields, even in cases where parametric methods suggest a random or over-dispersed distribution. The vent self-similar clustering is defined within a length range bounded by two thresholds, the lower (Lco) and the upper (Uco) cut-offs. They correspond to the shallow depth (< 5 km) at which magma may accumulate without leading to eruption and the depth of the magma reservoir or dike propagation zone, respectively. A strong positive correlation between Uco and magma reservoir depth (H) suggests that vent clustering reflects subsurface magma transport dynamics. Statistical tests confirm that γ₁ and γ₂ parameters, previously defined for volcanic fields in the Main Ethiopian Rift, are effective indicators of vent clustering, with γ₁ consistently ≤0.1 for clustered fields.
These findings underscore the role of fracture networks as efficient pathways for magma ascent, supporting the hypothesis that magma effusion sites are intrinsically linked to crustal mechanical properties. Future research should explore how fracture network evolution influences vent distribution over time and whether the vent self-similar clustering analysis can improve constraints on magma reservoir dynamics and eruption forecasting. Furthermore, applying this framework to extraterrestrial volcanic fields (e.g., Mars) could provide new insights into universal processes governing vent clustering in different planetary environments.
期刊介绍:
An international research journal with focus on volcanic and geothermal processes and their impact on the environment and society.
Submission of papers covering the following aspects of volcanology and geothermal research are encouraged:
(1) Geological aspects of volcanic systems: volcano stratigraphy, structure and tectonic influence; eruptive history; evolution of volcanic landforms; eruption style and progress; dispersal patterns of lava and ash; analysis of real-time eruption observations.
(2) Geochemical and petrological aspects of volcanic rocks: magma genesis and evolution; crystallization; volatile compositions, solubility, and degassing; volcanic petrography and textural analysis.
(3) Hydrology, geochemistry and measurement of volcanic and hydrothermal fluids: volcanic gas emissions; fumaroles and springs; crater lakes; hydrothermal mineralization.
(4) Geophysical aspects of volcanic systems: physical properties of volcanic rocks and magmas; heat flow studies; volcano seismology, geodesy and remote sensing.
(5) Computational modeling and experimental simulation of magmatic and hydrothermal processes: eruption dynamics; magma transport and storage; plume dynamics and ash dispersal; lava flow dynamics; hydrothermal fluid flow; thermodynamics of aqueous fluids and melts.
(6) Volcano hazard and risk research: hazard zonation methodology, development of forecasting tools; assessment techniques for vulnerability and impact.