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3D-VoCC: 3D vortex correlation clustering on spatial data based on masked hough transform
No full textThe discovery of patterns in spatial and spatio-temporal data is crucial across scientific disciplines studying natural phenomena to enhance our understanding of the real world. These phenomena display complex patterns, necessitating novel specialized pattern mining techniques. In this paper, we introduce Vortex Correlation Clustering which aims to identify a subgroup of such complex pattern, namely correlated groups of objects oriented along a vortex. This can be achieved by adapting the Circle Hough Transform, already known from image analysis. The presented adaptations not only allow to cluster objects depending on their relative location next to each other, but also allows to take the orientation of individual objects into consideration. A multi-step approach allows to analyze and aggregate cluster candidates, allowing a certain deviation from the reference shape in the final clusters. Further adaptations allow to analyze clusters along a third dimension, which allows to reflect the shape of real-world objects in a three dimensional space. We evaluate our approach upon a real world application, to cluster particle simulations composing such shapes. Our approach outperforms comparable methods for this application, both in terms of effectiveness and efficiency. Additionally, we discuss how the adaptation enables further analysis capabilities. For instance, in the presented use case, the introduced approach allows to additionally analyze clusters throughout the depth of the water. So far, this is not feasible with existing approaches
Refining the Eruption Chronology of Atitlán Caldera Through Zircon Double‐Dating
No full textPrecise dating of Quaternary volcanism is vital for risk mitigation, understanding volcano‐climate interactions, and deciphering the evolution of large silicic magmatic systems. The Atitlán caldera in Guatemala has experienced major eruptions that challenge radiometric dating techniques and complicate eruption chronology in this densely populated area. This study refines the eruptive history of Atitlán caldera using zircon double‐dating (ZDD: combined [U‐Th]/He and 238 U‐ 230 Th disequilibrium dating). We present new ZDD eruption ages for previously undated events, including the I‐tephra and the newly discovered Atitlán Early Tephra (AET). Additionally, we provide crystallization dates for the Los Chocoyos (LCY) supereruption, utilizing ultra‐distal samples from the Pacific Ocean, Lake Petén Itzá, and Mexico. ZDD was also applied to the 40 Ar/ 39 Ar sanidine‐dated W‐tephra confirming its reliability. Our findings yield an internally consistent chronology, with the first radiometric ages of 64 ± 8 ka for the I‐tephra and 497 ± 12 ka for AET. The ZDD eruption age of 160 ± 9 ka for W‐tephra corroborates the existing 40 Ar/ 39 Ar sanidine age. Bayesian eruption age modeling (BEAM) of new LCY 238 U‐ 230 Th disequilibrium dates consistently yields ages younger than previous estimates based on overdispersed zircon and plagioclase dates. Regardless of the prescribed zircon age distribution, BEAM results indicate the youngest zircon crystallization at ca. 88–76 ka, supporting the established ZDD eruption age of 75 ± 2 ka for LCY. This refined chronology provides insights into the Atitlán caldera volcanic activity, enhances hazard assessment and understanding of regional geological evolution, and highlights the pitfalls of Bayesian age modeling when integrating different chronometers.
Plain Language Summary
Large volcanic eruptions that occurred in Guatemala within the past several hundred thousand years are difficult to date using traditional methods, particularly in the case of the Atitlán caldera, the largest volcano in Central America near the densely populated city of Guatemala. By utilizing a relatively new dating technique involving micron‐scale zircon crystals, we have established the ages of previously undated eruptions from this major volcanic center and re‐evaluated those that already existed, offering valuable insights into the poorly understood eruptive history of this supervolcano.
Key Points
Large‐volume explosive eruptions of Atitlán caldera, Guatemala, constrained between 64 and 497 ka
New zircon crystallization ages for Los Chocoyos supereruption from distal and ultra‐distal tephra
Bayesian modeling of zircon crystallization ages indicates that Los Chocoyos eruption postdates 83 ka, consistent with previous ZDD eruption ag
Editorial: Time-series observations of ocean acidification: a key tool for documenting impacts on a changing planet
No full textEditorial on the Research Topic
Time-series observations of ocean acidification: a key tool for documenting impacts on a changing planet
Ocean acidification (OA) is a pressing global issue characterized by fundamental changes in ocean chemistry, including the reduction of pH levels, due to the absorption of increased atmospheric CO2. This phenomenon poses significant threats to marine ecosystems, affecting biodiversity, food security, and coastal economies. Time-series observations remain indispensable for documenting these changes, offering insights into the drivers and consequences of OA over temporal and spatial scales. This editorial summarizes the 17 studies in this Research Topic, highlighting the advancements in understanding OA dynamics and their broader implications
Ambiguity of early warning signals for climate tipping points
No full textThere is concern that climate change might lead to abrupt and irreversible changes in parts of the Earth system at so-called tipping points. Theoretical considerations suggest that statistical measures can be used to detect early warning signals (EWSs) for reduced resilience, which could be interpreted as an increased proximity to climate tipping points. Here we discuss limitations of commonly used EWSs and their detection and discuss how alternative explanations can lead to resilience loss in the absence of tipping points. We argue for better testing of the existence of tipping points, beyond the application of EWSs, and propose a method to better quantify the probability of approaching tipping points using EWSs
Legacy Seismic and Gravity Data in the Vicinity of Great Meteor Seamount and Its Tectonic Implications
No full textThe Great Meteor seamounts are located in the eastern Atlantic Ocean, about 750 km south of the Azores. Conjugate to the Corner seamounts in the western Atlantic Ocean, it has been suggested they formed at the same hotspot that generated the New England Seamount chain. However, isotopic data suggest the Great Meteor seamounts are genetically linked to the Azores rather than to the New England hotspot. To test this, we have used seismic, gravity and bathymetry data acquired onboard M/V Meteor in 1990 to reassess the crustal structure, elastic thickness, T e , and tectonic setting of the seamounts. The most prominent is Great Meteor, the largest seamount in the Atlantic Ocean. We show that the guyot comprises a pelagic, limestone (2.0–4.5 km s −1 ) and extrusive basaltic lava (5.0–6.0 km s −1 ) drape that overlies a relatively high P ‐wave velocity (6.0–6.5 km s −1 ) intrusive “core” of mafic and possibly ultramafic rocks. The seismic structure has been verified by gravity modeling assuming a Gardner and Nafe‐Drake relationship between P ‐wave velocity and density. The best fit between the observed and calculated gravity anomaly based on a plate flexure model is for an elastic thickness, T e , of ∼20 km which implies an edifice age of ∼43 Ma, assuming a 450°C controlling oceanic isotherm. While the edifice age is greater than the sample age (∼17 Ma), it explains the subsidence history of Great Meteor and is compatible with dynamic models of plume‐ridge interactions that predict the Azores hotspot has migrated north during the Cenozoic.
Plain Language Summary
The seafloor is littered by seamounts most of which are volcanic in origin. They are important as oceanographic “dip‐sticks,” biodiversity “hotspots” and tectonic “tape recorders” of plate motions, plate strength, and Earth's long magmatic history. Yet, we know little about how many seamounts there are in the world's oceans or their origin, internal structure and subsidence and uplift history. Great Meteor Seamount is the largest flat‐topped seamount in the Atlantic Ocean and one of only a few world‐wide which have been both sampled and surveyed using seismic imaging techniques. The seismic data was acquired, however, more than 30 years ago when onboard processing was not available and as a result only a small part of the data on Great Meteor and its neighboring seamounts have been previously published. Here, we report on the results of reprocessing this legacy data and its use, together with gravity and flexure modeling, to image the internal velocity and density structure of the seamounts and to speculate on their age, subsidence and uplift history, and origin at a migrating deep mantle hotspot.
Key Points
Great Meteor Seamount is characterized by a high velocity intrusive core of mafic rocks that are draped by low velocity extrusive basalts
The elastic thickness at the seamount is ∼20 km which is less than expected and implies an edifice age that is greater than the sample age
The edifice age at the seamount is consistent with its emplacement on a mid‐ocean ridge flank at a northward migrating Azores hotspo
Garnet megacrysts in oceanic crust of the Troodos Ophiolite, Cyprus
No full textGarnets have been reported only very rarely from the in-situ oceanic crust or ophiolites, and invariably these occurrences comprise very small mineral grains (Bertrand and Vuagnat 1980; Plümper et al. 2014; Faryad and Dianiska 2003). With this geosite, we present an exceptional outcrop containing up to fist-sized garnets as rock-forming mineral in former oceanic crust in the Cyprus Troodos Ophiolite Complex
NBS-Wissenschaftsforum
No full textFunktion im Gremium:
Berufung zum NBS-Wissenschaftsforum zur Begleitung der Umsetzung der Nationalen Strategie zur biologischen Vielfalt 2030 (NBS 2030)
Hauptfokus:
Science-policy interfac
Supervised and unsupervised machine learning methods for modelling current and future habitat of Peruvian anchovy
No full textUnderstanding the drivers and potential impacts of environmental variability on the distribution of Peruvian anchovies, the largest single-species fishery on the planet, is essential for their proper management in a changing world. However, the intricate interactions of these organisms and environmental variability require the use of complex models such as machine learning methods. In this study, we compared three methods for producing habitat maps of anchovies: the traditional Generalised Additive Models, the XGBoost which is a form of supervised machine learning and a new method based on clustering water types as a form of unsupervised machine learning. We optimised the three methods with a parameter grid search algorithm and compared their capability to replicate the mean state of anchovies by comparing them with presence-absence observations along the Peruvian coastline between 1990 and 2010. We used the output of a physical-biogeochemical model as input for the habitat models to produce distribution maps of anchovy. All models successfully simulated the distribution of anchovies along the Peruvian coastline in normal years and a reduced area of distribution with most of the anchovies in the southern part of the domain during the canonical El Niño 97/98. We then applied the models to predict potential changes in the distribution of anchovies under projected temperature and wind conditions by the end of the century. We observed a reduction in the probability of anchovy occurrence under conditions of higher temperature and weaker winds. Two of the three habitat models predicted a severe maximum decline by 90% (GAM) and 75% (XGBoost) whereby the clustering model predicted a moderate maximum decline in anchovy occurrence by 20%