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Abstract Tidal disruption events (TDEs) offer a unique probe of supermassive black hole (SMBH) demographics, but their observed rates remain difficult to reconcile with standard single-SMBH models. In this work, we use simulations of SMBH binaries, including the combined effects of eccentric Kozai–Lidov oscillations and two-body relaxation, to explore how TDE rates scale with SMBH mass and redshift. We find that binary systems exhibit increasing TDE rates with mass, in contrast to the declining trend expected for single SMBHs. These binary-driven rates match those observed in post-starburst galaxies, suggesting that a subset of TDE hosts may contain SMBH binaries. TDE light curves in some massive galaxies exhibit unexpectedly short durations, suggesting that the disrupting SMBH may be less massive than implied by host galaxy scaling relations, consistent with disruptions by the less massive black hole in a binary. By convolving our mass-dependent rates with the SMBH mass function, we predict redshift-dependent TDE rates, which we show can be used to constrain the SMBH binary fraction. Our results provide a testable framework for interpreting TDE demographics in upcoming wide-field surveys such as Legacy Survey of Space and Time and Roman. 

Abstract This study characterizes the main ionospheric trough (MIT) using a newly implemented detection method applied to ground‐based Global Navigation Satellite System data. The MIT is a region of plasma depletion occurring primarily in the nighttime sub‐auroral F‐region ionosphere. Analysis is based on ground‐based ionosphere total electron content (TEC) measurements from 2012 to 2024 and is applied to both hemispheres. The data are sorted by geomagnetic condition and season. We characterize MIT dynamics and compare the results with previous studies. Detection algorithm limitations, hemispheric asymmetry, trough depth, boundary wall steepness and position are statistically quantified and visualized. Main conclusions include: (a) Automatic trough detection is highest during geomagnetically active winter in the northern hemisphere (NH). (b) This detection method creates synoptic views of the trough which we can use to demonstrate control of sub‐auroral polarization streams (SAPS) over the dusk/afternoon sector and influence of storm onset on the MIT. (c) There is a noticeable morning preference for the southern hemisphere (SH) trough. (d) The dawn‐side SH trough appears equatorward relative to the NH, potentially due to influence from polar convection patterns. The dusk‐side NH trough appears slightly equatorward of the SH trough as a response to SAPS. (e) The deepest trough occurs during dawn hours and demonstrates more consistent longitudinal patterns during quiet local winter. (f) The steepest trough boundary is at the poleward wall with a positive gradient at 12–15 local time in NH summer. Synoptic maps illustrate asymmetries in the trough structure and the influence of density plumes. 

Abstract Projections for population viability under climate change are often made using estimates of thermal lethal thresholds. These estimates vary across life history stages and can be valuable for explaining or forecasting shifts in population viability. However, sublethal temperatures can also depress vital rates and shape fluctuations in the reproductive viability of populations. For example, heatwaves may suppress reproduction, causing recruitment failure before lethal temperatures are reached. Despite a growing awareness of this issue, tying sublethal effects to observed recruitment failure remains a challenge especially in marine environments. For the urchinStrongylocentrotus purpuratus, larval supply is known to decline near the southern edge of the range during marine heatwaves despite temperatures remaining below temperatures thought to limit larval survival. We experimentally show that sublethal suppression of gametogenesis by marine heatwaves can partially explain these historical collapses in recruitment. This response differs by sex: male spermatogenesis is less sensitive to elevated temperatures and marine heatwaves than females who exhibit substantial reductions in production of mature oocytes. Results were similar between animals from warmer and cooler regions of their range. Overall, we show sublethal thermal sensitivities of reproduction can narrow the thermal envelope for population viability compared to predictions from lethal limits. 

Abstract Melt composition, temperature, and crystallinity are often seen as the three most important characteristics driving lava rheology, which controls eruptive behavior. Traditional methods of measuring the viscosity of crystallizing basalts often yield different mineral characteristics to natural samples and are typically bubble-free. To quantify the viscosity of basalts inclusive of bubble and crystal cargo, we developed a new technique to measure high-temperature three-phase isothermal lava viscosity and applied it to samples from the 2018 eruption of Kīlauea. This new experimental technique begins at subliquidus temperatures, preserving original phenocrysts. A short experimental duration allows for the retention of most of the original bubble population (19%–31% vs. 36% in the original lava) and accurate replication of crystal textures from field samples, as documented in quenched postexperiment samples. The observed rheological behavior in these experiments, conducted at syneruptive temperatures (1150–1105 °C) and strain rates (0.4–18 s–1), should therefore be representative of the lava flows. We measured average viscosities of 116 Pa·s at 1150 °C to 167 Pa·s at 1115 °C (i.e., only 10%–25% higher than calculated liquid viscosities at those temperatures) and a maximum of 1800 Pa·s at 1105 °C. These results are much lower than viscosity measured in traditional bubble-free experiments, which plateaued at ~14,000 Pa·s at 1115 °C. Our results suggest the effect of bubbles in three-phase magmas may be greater than predicted by models based on two-phase bubbly liquids, and this effect must be included in realistic lava flow rheology models. The method proposed here supplies a framework for providing the necessary experimental constraints. 

CitationSnead, A.A., Meng, F., Largotta, N. et al. Diploid chromosome-level genome assembly and annotation for Lycorma delicatula. Sci Data 12, 579 (2025). https://doi.org/10.1038/s41597-025-04854-8AbstractThe spotted lanternfly (Lycorma delicatula) is a planthopper species (Hemiptera: Fulgoridae) native to China but invasive in South Korea, Japan, and the United States where it is a significant threat to agriculture. Hence, genomic resources are critical to both management and understand the genomic characteristics of successful invaders. Here, we report a haplotype-phased genome assembly and annotation using PacBio long-read sequencing, Hi-C technology, and RNA-seq data. The 2.2 Gbp genome comprises 13 chromosomes, and our whole genome sequencing of eighty-two adults indicated chromosome four as the sex chromosome and anXO sex-determination system.We identified over 12,000 protein coding genes and performed functional annotation, facilitating identification of several candidate genes which may hold importance for spotted lanternfly control. Both the assemblies and annotations were highly complete with over 96% of BUSCO genes complete regardless of the database employed (i.e., Eukaryota, Arthropoda, Insecta). This reference-quality genome will serve as an important resource for both development and optimization of management practices for the spotted lanternfly and invasive genomics as a whole.Description of the data and file structureThis dataset contains the haplotype-phased chromosome-level genome assembly of the spotted lanternfly (Lycorma delicatula) described and published in Snead & Meng et al. (in review). The genome combined long-read data and HiC data (SRA31402152-SRA31402153) to assembly and scaffold each haplotype. The annotation uses RNAseq data from 12 adults (SRA31411873-SRA31411894) to structurally annotate both haplotypes. Finally, whole-genome sequencing of 82 adult spotted lanternfly (bioproject PRJNA1136004) described in the metadata csv provided was used to identify punitive sex chromosomes. The dataset also include GO results for each chromosome not explicitly described in the results of the manuscript.Files and variablesFile: SLF_Hap1.fastaDescription: A fasta file of the assembled genome for the cleaned 13 chromosome haplotype 1 assembly.File: SLF_Hap2.fastaDescription: A fasta file of the assembled genome for the cleaned 13 chromosome haplotype 2 assembly.File: SLF_Hap1_Repeats.gffDescription: A gff file of the repeats annotated in the cleaned 13 chromosome haplotype 1 assembly.File: SLF_Hap2_Repeats.gffDescription: A gff file of the repeats annotated in the cleaned 13 chromosome haplotype 2 assembly.File: SLF_Hap1.gffDescription: A structural annotation of the 13 chromosome haplotype 1 assembly with functional annotations.File: SLF_Hap2.gffDescription: A structural annotation of the 13 chromosome haplotype 2 assembly with functional annotations.File: GO_plot_chr_1.pngDescription: An image of the top 20 GO term results for chromosome 1.File: GO_plot_chr_2.pngDescription: An image of the top 20 GO term results for chromosome 2.File: GO_plot_chr_3.pngDescription: An image of the top 20 GO term results for chromosome 3.File: GO_plot_chr_8.pngDescription: An image of the top 20 GO term results for chromosome 8.File: GO_plot_chr_5.pngDescription: An image of the top 20 GO term results for chromosome 5.File: GO_plot_chr_4.pngDescription: An image of the top 20 GO term results for chromosome 4.File: GO_plot_chr_6.pngDescription: An image of the top 20 GO term results for chromosome 6.File: GO_plot_chr_7.pngDescription: An image of the top 20 GO term results for chromosome 7.File: GO_plot_chr_11.pngDescription: An image of the top 20 GO term results for chromosome 11.File: GO_plot_chr_9.pngDescription: An image of the top 20 GO term results for chromosome 9.File: GO_plot_chr_10.pngDescription: An image of the top 20 GO term results for chromosome 10.File: GO_plot_chr_12.pngDescription: An image of the top 20 GO term results for chromosome 12.File: GO_plot_chr_13.pngDescription: An image of the top 20 GO term results for chromosome 13.File: SLF_Samples_SRA.csvDescription: A csv with the sequencing information, SRA numbers, and sexes of the adults used in to identify the putative sex chromosome.File: SLF_RNAseq_Metadata.csvDescription: A csv with the sequencing information, SRA numbers, and other metadata for the RNAseq used to annotation the genomes.Variablesaccession: The SRA accession numberstudy: The studyobject_status: If the NCBI submission was new or not.bioproject_accession: The bioproject accession numberbiosample_accession: The Biosample accession numberlibrary_ID: The ID used to identify that genomic library.title: The title of the study (the bioproject)library_strategy: Specific sequencing technique used to prepare the library.library_source: The biological material used to create the sequencing library.library_selection: The library preparation method.library_layout: The arrangement of reads within the sequencing library.platform: The sequencing platform.instrument_model: The model of the sequences.design_description: Description of the study design.filetype: Type of filefilename: First filefilename2: Second filesex: The biological sex of the adult.Code/softwareThe initial haplotype-phased scaffolded genome was assembled by Dovetail Genomics (Cantata Bio) with standard software outlined in the methods with default settings. Scripts for the remaining work including annotation, gene ontology enrichment, and other analyses are located in the Github repository (https://github.com/anthonysnead/SLF-Genome-Assembly(opens in new window)).Access informationOther publicly accessible locations of the data:The raw sequencing data and the annotated haplotype-phased genome assembly of Lycorma delicatula have been deposited at the National Center for Biotechnology Information (NCBI). The Hi-C and HiFi data can be found under SRA31402152 and SRA31402153. The RNA-seq data can be found under SRA31411873-SRA31411894, while the DNA-seq data can be found under bioproject PRJNA1136004.