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1. From the ashes of VEI: Decoding explosivity, mass eruption rate and hazards in real time

   https://doi.org/10.22541/essoar.176967627.71453176/v1  

   Sahagian, Dork (January 2026, AGU)

   Ash-producing volcanic eruptions are a major natural hazard. The explosivity of these eruptions has been described for decades by a semi-quantitative “Volcanic Explosivity Index (VEI)” based on a number of interdependent factors (eruption duration, volume of ejected material, eruptive column height, tropospheric and stratospheric injection, and many qualitative descriptors), most of which could only be assessed after eruption had ceased. The utility of this semi-quantitative index has been questioned since then, yet its common usage persists. We suggest that if VEI is to be used in the future, it may as well be an index that can be determined in real time during an eruption, and one that strictly reflects eruption intensity. We find that the same value for the “traditional” Volcanic Explosivity Index of past eruptions can be estimated in real time during an eruption, based solely on eruption column height. This approach is not intended to replace the traditional VEI scale or supplant more detailed mechanistic approaches to mass eruption rate (MER); rather it can be used to provide a more immediate way of calculating the VEI and linking to MER, in real time while an eruption is taking place. As such, if the easily observed height can be measured, both MER and VEI can be estimated. This may facilitate emergency response by aviation, hazard management, and others to mitigate societal impact of hazardous eruptions. This scheme can be inverted to use volume-based VEI of ancient eruptions to roughly retrodict unobserved column height for key historic and pre-historic eruptions. Further, ash particle morphology reflects explosivity in terms of decompression rate at the vent of unobserved eruptions. With sufficiently rapid decompression, this could result in an observable bi-modal bubble size distribution. The morphology of ash particles reveals a threshold between VEI 3 and 4, above which there is sufficiently rapid decompression to trigger a second nucleation event near the vent. 

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2. Data accompanying "Drought Characterization with GPS: Insights into Groundwater and Reservoir Storage in California" [Young et al., (2024)]

   https://doi.org/10.6084/m9.figshare.25898044.v1  

   Young, Zachary M; Martens, Hilary R; Hoylman, Zachary H; Gardner, W Payton (June 2024, figshare)

   The data provided here accompany the publication "Drought Characterization with GPS: Insights into Groundwater and Reservoir Storage in California" [Young et al., (2024)] which is currently under review with Water Resources Research. (as of 28 May 2024)Please refer to the manuscript and its supplemental materials for full details. (A link will be appended following publication)File formatting information is listed below, followed by a sub-section of the text describing the Geodetic Drought Index Calculation. The longitude, latitude, and label for grid points are provided in the file "loading_grid_lon_lat".Time series for each Geodetic Drought Index (GDI) time scale are provided within "GDI_time_series.zip".The included time scales are for 00- (daily), 1-, 3-, 6-, 12- 18- 24-, 36-, and 48-month GDI solutions.Files are formatted following...Title: "grid point label L****"_"time scale"_monthFile Format: ["decimal date" "GDI value"]Gridded, epoch-by-epoch, solutions for each time scale are provided within "GDI_grids.zip".Files are formatted following...Title: GDI_"decimal date"_"time scale"_monthFile Format: ["longitude" "latitude" "GDI value" "grid point label L****"]2.2 GEODETIC DROUGHT INDEX CALCULATION We develop the GDI following Vicente-Serrano et al. (2010) and Tang et al. (2023), such that the GDI mimics the derivation of the SPEI, and utilize the log-logistic distribution (further details below). While we apply hydrologic load estimates derived from GPS displacements as the input for this GDI (Figure 1a-d), we note that alternate geodetic drought indices could be derived using other types of geodetic observations, such as InSAR, gravity, strain, or a combination thereof. Therefore, the GDI is a generalizable drought index framework. A key benefit of the SPEI is that it is a multi-scale index, allowing the identification of droughts which occur across different time scales. For example, flash droughts (Otkin et al., 2018), which may develop over the period of a few weeks, and persistent droughts (>18 months), may not be observed or fully quantified in a uni-scale drought index framework. However, by adopting a multi-scale approach these signals can be better identified (Vicente-Serrano et al., 2010). Similarly, in the case of this GPS-based GDI, hydrologic drought signals are expected to develop at time scales that are both characteristic to the drought, as well as the source of the load variation (i.e., groundwater versus surface water and their respective drainage basin/aquifer characteristics). Thus, to test a range of time scales, the TWS time series are summarized with a retrospective rolling average window of D (daily with no averaging), 1, 3, 6, 12, 18, 24, 36, and 48-months width (where one month equals 30.44 days). From these time-scale averaged time series, representative compilation window load distributions are identified for each epoch. The compilation window distributions include all dates that range ±15 days from the epoch in question per year. This allows a characterization of the estimated loads for each day relative to all past/future loads near that day, in order to bolster the sample size and provide more robust parametric estimates [similar to Ford et al., (2016)]; this is a key difference between our GDI derivation and that presented by Tang et al. (2023). Figure 1d illustrates the representative distribution for 01 December of each year at the grid cell co-located with GPS station P349 for the daily TWS solution. Here all epochs between between 16 November and 16 December of each year (red dots), are compiled to form the distribution presented in Figure 1e. This approach allows inter-annual variability in the phase and amplitude of the signal to be retained (which is largely driven by variation in the hydrologic cycle), while removing the primary annual and semi-annual signals. Solutions converge for compilation windows >±5 days, and show a minor increase in scatter of the GDI time series for windows of ±3-4 days (below which instability becomes more prevalent). To ensure robust characterization of drought characteristics, we opt for an extended ±15-day compilation window. While Tang et al. (2023) found the log-logistic distribution to be unstable and opted for a normal distribution, we find that, by using the extended compiled distribution, the solutions are stable with negligible differences compared to the use of a normal distribution. Thus, to remain aligned with the SPEI solution, we retain the three-parameter log-logistic distribution to characterize the anomalies. Probability weighted moments for the log-logistic distribution are calculated following Singh et al., (1993) and Vicente-Serrano et al., (2010). The individual moments are calculated following Equation 3. These are then used to calculate the L-moments for shape (), scale (), and location () of the three-parameter log-logistic distribution (Equations 4 – 6). The probability density function (PDF) and the cumulative distribution function (CDF) are then calculated following Equations 7 and 8, respectively. The inverse Gaussian function is used to transform the CDF from estimates of the parametric sample quantiles to standard normal index values that represent the magnitude of the standardized anomaly. Here, positive/negative values represent greater/lower than normal hydrologic storage. Thus, an index value of -1 indicates that the estimated load is approximately one standard deviation dryer than the expected average load on that epoch. *Equations can be found in the main text. 

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3. Phosphorus chemistry in plant charcoal: interplay between biomass composition and thermal condition

   https://doi.org/10.1071/WF23096  

   Wu, Yudi; Pae, Lois M; Huang, Rixiang (January 2024, International Journal of Wildland Fire)

   Background Vegetation fire may change Phosphorus (P) cycling in terrestrial ecosystems through converting biomass into fire residues. Aim The aim of this study was to understand the chemistry and mobility of P in fire residues to help reveal P thermochemistry during biomass burning and post-fire P cycling. Methods A combination of sequential extraction, liquid 31P NMR and P K-edge XANES was used to obtain quantitative P speciation and explain P solubilisation behaviours of charcoal. Key results Despite varying diverse P species existing in raw biomass, only two P structural moieties – orthophosphate and pyrophosphate – were identified in charcoal. However, relative abundance of pyrophosphate differs greatly among charcoal samples from different biomass types, ranging between 0 and 40% of total extractable P. Although P K-edge XANES data indicates abundant soluble phosphate minerals, most P (70–90%) is likely occluded physically in the charcoal. The bicarbonate-extractable P (the Olsen-P) varies significantly and cannot be explained by surface P concentration or elemental stoichiometry alone. Conclusion and implications The results suggest the importance of starting biomass P speciation (i.e. molecular structure and complexation environment) and thermal conditions in controlling P speciation and availability in charcoal. The different P chemistry between charcoal and ash suggests the importance of fire types and severity in disturbing the P cycle. 

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4. High species richness in the lichen genus Peltigera (Ascomycota, Lecanoromycetes): 34 species in the dolichorhizoid and scabrosoid clades of section Polydactylon, including 24 new to science

   https://doi.org/10.3767/persoonia.2023.51.01  

   Magain, N.; Miadlikowska, J.; Goffinet, B.; Goward, T.; Pardo-De la Hoz, C.J.; Jüriado, I.; Simon, A.; Mercado-Díaz, J.A.; Barlow, T.; Moncada, B.; et al (August 2023, Persoonia - Molecular Phylogeny and Evolution of Fungi)

   Applying molecular methods to fungi establishing lichenized associations with green algae or cyanobacteria has repeatedly revealed the existence of numerous phylogenetic taxa overlooked by classical taxonomic approaches. Here, we report taxonomical conclusions based on multiple species delimitation and validation analyses performed on an eight-locus dataset that includes world-wide representatives of the dolichorhizoid and scabrosoid clades in section Polydactylon of the genus Peltigera . Following the recommendations resulting from a consensus species delimitation approach and additional species validation analysis (BPP) performed in this study, we present a total of 25 species in the dolichorhizoid clade and nine in the scabrosoid clade, including respectively 18 and six species that are new to science and formally described. Additionally, one combination and three varieties (including two new to science) are proposed in the dolichorhizoid clade. The following 24 new species are described: P. appalachiensis , P. asiatica , P. borealis , P. borinquensis , P. chabanenkoae , P. clathrata , P. elixii , P. esslingeri , P. flabellae , P. gallowayi , P. hawaiiensis , P. holtanhartwigii , P. itatiaiae , P. hokkaidoensis , P. kukwae , P. massonii , P. mikado , P. nigriventris , P. orientalis , P. rangiferina , P. sipmanii , P. stanleyensis , P. vitikainenii and P. willdenowii ; the following new varieties are introduced: P. kukwae var. phyllidiata and P. truculenta var. austroscabrosa ; and the following new combination is introduced: P. hymenina var. dissecta . Each species from the dolichorhizoid and scabrosoid clades is morphologically and chemically described, illustrated, and characterised with ITS sequences. Identification keys are provided for the main biogeographic regions where species from the two clades occur. Morphological and chemical characters that are commonly used for species identification in the genus Peltigera cannot be applied to unambiguously recognise most molecularly circumscribed species, due to high variation of thalli formed by individuals within a fungal species, including the presence of distinct morphs in some cases, or low interspecific variation in others. The four commonly recognised morphospecies: P. dolichorhiza , P. neopolydactyla , P. pulverulenta and P. scabrosa in the dolichorhizoid and scabrosoid clades represent species complexes spread across multiple and often phylogenetically distantly related lineages. Geographic origin of specimens is often helpful for species recognition; however, ITS sequences are frequently required for a reliable identification. 

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5. Ethane dehydrogenation performance and high temperature stability of silica supported cobalt phosphide nanoparticles

   https://doi.org/10.1039/D1CY01737C  

   Muhlenkamp, Jessica A.; LiBretto, Nicole J.; Miller, Jeffrey T.; Hicks, Jason C. (February 2022, Catalysis Science & Technology)

   A series of Co–P materials with varying P : Co ratio from 0 to 4 supported on SBA-15 were evaluated for ethane dehydrogenation (EDH) performance. In comparison to monometallic Co, the Co–P materials have improved ethylene selectivity from 41% for Co to 88–90% for Co–P, which was attributed to the segregation of Co atoms and the formation of partial positive Co δ + sites in the Co–P materials due to charge transfer. Among the Co–P materials studied, an optimum in stability was observed in those containing a P : Co ratio in the range 1 to 2. Below this range, limited P is available to adequately separate Co atoms. Above this range, the excess P promotes coke formation through possible acid catalyzed pathways. The stability of two of the Co–P materials containing the Co 2 P and CoP phase, respectively, were further tested for EDH at 700 °C. Under these conditions, the ethylene selectivity was 98%, and both materials remained active with little to no deactivation for over 4 h. In comparison to a Pt–Sn reference, both Co–P materials showed vastly improved stability. Additionally, both Co–P materials showed no signs of sintering after EDH at 700 °C and maintained their respective Co 2 P and CoP phases. These results demonstrate the catalytic improvement with P incorporation and highlights the high stability of Co–P, and possibly other metal phosphides, as high temperature EDH catalysts. 

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