Find research datasets worth reusing

opencc-by-4.0Jun 2022View details →

Data release for "Scintillator ageing of the T2K near detectors from 2010 to 2021"

The data release is associated with the paper "Scintillator ageing of the T2K near detectors from 2010 to 2021”, published in the <a href="https://iopscience.iop.org/article/10.1088/1748-0221/17/10/P10028">Journal of Instrumentation</a> and <a href="https://arxiv.org/abs/2207.12982">arXiv:2207.12982 [physics]</a>. The data release contains the data points and associated fits from the paper within two root files: <ul> <li>The file T2KNearDetector_ScintAgeing_Standard_DataRelease.root contains the data points and fits shown in the standard ageing results described in Sections 4 and 5 of the paper.</li> <li>The file T2KNearDetector_ScintAgeing_ECalSupplemental_DataRelease.root contains the data points and fits shown in the supplemental ageing results described in Section 6 of the paper.</li> </ul> All data points are provided as ROOT TGraphError objects and fit as ROOT TF1 objects. A full description of the contents of each root file is provided in the README.txt.

opencc-zeroDec 2017View details →

Data from: Accuracy of node and bud-scar counts for aging two dominant conifers in western North America

Accurately aging trees is critical for understanding tree demography and tree responses to environmental change. Given the proliferation of studies aimed at understanding the effects of climate and disturbance on forest ecosystems, it is important to understand the tradeoffs between field-based age estimates and precise dendrochronological techniques. We assessed the accuracy of age estimates from node counts in the field against precise tree-ring counts at the root-shoot boundary, in 1279 ponderosa pine and 1268 Douglas-fir seedlings sampled from across three study regions in the western U.S. We also assessed the accuracy of age estimates from bud-scar counts in the field against node counts and precise tree-ring counts in a subset of 757 seedlings from the Northern Rockies. Node counts systematically underestimated ring counts by an average of 4.1 years, with bias increasing with tree age. At annual, ±1-, ±2-, and ±5-yr precision, the accuracy of node counts was 5%, 15%, 29%, and 74% across all regions and species, respectively. Similar results were found for bud scars. Given the magnitude of the bias between field-based methods and ring counts, it is critical to select appropriate aging methods, based on the precision required to answer specific ecological questions. To improve the accuracy of field-based age estimates in these species, we provide a tool for correcting for the bias when precise dendrochronological aging is not feasible.

opencc-by-4.0Mar 2022View details →

Investigation on anodes from anode supported cells manufactured by Solidpower and aged by IEES-BAS with electrochemical characterization.

samples are mounted in epoxy-resin and polished up to 250nm using diamond paste on specific tissue (MD-NAP, Struers). Observation by SEM (ZEISS EVO 40) using backscattered electrons as the contrast method. Chemical analysis performed using EDS after calibration with Co standard and using ZAF algorithm correction. The standard magnification is 5000. The pictures are further threated using ImageJ software for quantitative image analysis. Porosity and Nickel particles are highlighted by using Coreldraw software image enhancements.

opencc-by-4.0Jul 2022View details →

Age and phenology control photosynthesis and leaf traits in the understory woody species, Rhamnus cathartica and Prunus serotina

Dataset contains leaf physiological variables and leaf traits from Rhamnus cathartica (buckthorn) and Prunus serotina (Black cherry) measured in Summer 2019 at Macalester College's Ordway Field Station. All data were collected on understory individuals from 4 sites within the forest in late May and early July, 2019. We sampled from 'tree' individuals and seedlings of both species. All methods and measurement protocols are published in Heskel et al. 2022 in AoB-PLANTS, currently in revision. Data includes:  Vcmax (umol m2-s-1) Jmax (umol m2-s-1) Fv/Fm (no units) Leaf Stomatal Density (stomata mm-2) Dark respiration (umol m2-s-1) Asat (umol m2-s-1) A400 (umol m2-s-1) Carbon Gain Efficiency (CGE, no units) CGE_400 (CGE at 400 PAR, no units) Leaf Mass per Are (LMA, g m-2)

opencc-by-4.0Jul 2022View details →

Data set EC Age

Individual raw data for stages of entheseal changes for 30 appendicular entheses in four identified collections.  For the method used to record the changes, see Villotte 2006 For a presentation of the collections, see Villotte 2009, Villotte et al. 2010. Villotte S. 2006. Connaissances médicales actuelles, cotation des enthésopathies : nouvelle méthode. Bulletins et Mémoires de la Société d’Anthropologie de Paris n.s., 18: 65–85. Villotte S. 2009. Enthésopathies et activités des hommes préhistoriques Recherche méthodologique et application aux fossiles européens du Paléolithique supérieur et du Mésolithique. BAR International Series 1992, Archaeopress: Oxford, UK. Villotte S, Castex D, Couallier V, Dutour O, Knüsel CJ, Henry-Gambier D. 2010. Enthesopathies as occupational stress markers: evidence from the upper limb. American Journal of Physical Anthropology 142: 224–234.

opencc-by-4.0Apr 2022View details →

Discovering molecular regulators of ageing using mixture models with RNA-sequencing data

Identifying the molecular regulators that control ageing is challenging because the ageing process is influenced by a combination of genetic and environmental factors which makes it difficult to source the contribution of a single gene. Multiple studies have demonstrated that as humans age, increased gene expression heterogeneity results in the dysregulation of key regulators and pathways. Given the dynamic nature of gene expression, it is vital that this data be modelled by statistical approaches that can appropriately account for changes in variability to understand the contribution of heterogeneity during the aging process and properly identify its regulators. This study demonstrates the utility of using mixture models to model biological variability of gene expression occurring during ageing and how novel potential regulators of ageing can be identified. Our mixture modelling approach was applied to gene expression data from the Genotype-Tissue Expression (GTEx) cohort. For every gene, the expression profile was modelled using a mixture model across the cohort where the subset of donors corresponding to each mode was tested for a significant change in age group. The multi-tissue aspect of GTEx was leveraged to find ageing regulators based on this mixture model approach genes that were common across multiple tissues, suggesting that the regulation of ageing may also be controlled through a set of genes that have non-tissue-specific activity. Our approach identified well-documented ageing regulators mTOR and RICTOR and other potential ageing regulators such as IL4 and GPR4 which were detected only by our approach. Genes identified by edgeR, DESeq2 and the mixture model-based approach were enriched for similar biological pathways. This suggests that while the specific ageing regulators identified from our approach may be distinct, they generally belong in the same pathways as the genes identified by standard approaches. Overall, these results indicate that modelling gene expression variability using mixture models in conjunction with standard differential gene expression can help uncover new regulators that have a potential role for understanding human ageing. I

opencc-by-4.0Jul 2022View details →

Raw data for the manuscript entitled "Forest age and topographic position jointly shape the species richness and composition of vascular plants in karstic habitats"

Doline surveys from the Mecsek Mountains, Hungary. Transects were established with north to south orientation across each doline, traversing their deepest point. Transects began and ended on doline rims, and consisted of 1 m  × 1 m plots spaced at 2 m intervals (94, 89, 90 and 99 plots in the different forest age classes, respectively; 372 plots in total). We recorded the presence/absence data of shrubs and herbs in each plot. Fieldwork was carried out between 2007 and 2019 from June to August, at the peak of the growing season.

opencc-zeroJul 2022View details →

Triparental ageing in a laboratory population of an insect with maternal care

Parental age at reproduction influences offspring size and survival by affecting pre- and postnatal conditions in a wide variety of species, including humans. However, most investigations into this manifestation of ageing focus upon maternal age effects; the effects of paternal age and interactions between maternal and paternal age are often neglected. Furthermore, even when maternal age effects are studied, pre- and postnatal effects are often confounded. Using a cross-fostered experimental design, we investigated the joint effects of prenatal paternal and maternal and postnatal maternal ages on five traits related to offspring outcomes in a laboratory population of a species of burying beetle, Nicrophorus vespilloides. We found a significant positive effect of the age of the egg producer on larval survival to dispersal. We found more statistical evidence for interaction effects, which acted on larval survival and egg length. Both interaction effects were negative and involved the age of the egg-producer, indicating that age-related prenatal maternal improvements were mitigated by increasing age in fathers and foster mothers. These results agree with an early study that found little evidence for maternal senescence, but it emphasizes that parental age interactions may be an important contributor to ageing patterns. We discuss how the peculiar life history of this species may promote selection to resist the evolution of parental age effects, and how this might have influenced our ability to detect senescence.

opencc-by-4.0May 2022View details →

Spectral flow cytometric tracking of mitochondria transfer in adipose tissue by age and diet

Unmixed fcs files for the stromal vascular fraction of epididymal (eWAT), inguinal (iWAT), and brown adipose tissue (BAT) in mtD2F/+AdipoqCre+/- and different ages or diets.  For a breakdown of samples and code, please see: <a href="https://github.com/ncborcherding/mtD2">https://github.com/ncborcherding/mtD2</a>. The full github repository at time of manuscript acceptance is also in the Zenodo repository under mtD2_GitHubRepo.zip. Antibody Panel:  <table align="center"> <tbody> <tr> <td> Laser </td> <td> Channel </td> <td> Antigen </td> <td> Fluorophore </td> <td> Final Dilution Factor </td> <td> Vendor </td> <td> Clone </td> <td> Catalog Number </td> </tr> <tr> <td> Violet </td> <td> V1 </td> <td> SiglecF </td> <td> BV 421 </td> <td> 1:400 </td> <td> BD Biosciences </td> <td> E50-2440 </td> <td> 562681 </td> </tr> <tr> <td> </td> <td> V2 </td> <td> CD44 </td> <td> Super Bright 436 </td> <td> 1:300 </td> <td> eBioscience </td> <td> IM7 </td> <td> 62-044-180 </td> </tr> <tr> <td> </td> <td> V3 </td> <td> CD11b </td> <td> Pacific Blue </td> <td> 1:300 </td> <td> BioLegend </td> <td> M1/70 </td> <td> 101224 </td> </tr> <tr> <td> </td> <td> V5 </td> <td> IL-33R⍺-biotin </td> <td> n/a </td> <td> 1:300 </td> <td> BioLegend </td> <td> DIH9 </td> <td> 145308 </td> </tr> <tr> <td> </td> <td> V5 </td> <td> Streptavidin (2°) </td> <td> BV 480 </td> <td> 1:300 </td> <td> BD Horizon </td> <td> n/a </td> <td> 564876 </td> </tr> <tr> <td> </td> <td> V7 </td> <td> MHC-II (I-A/I-E) </td> <td> BV 510 </td> <td> 1:300 </td> <td> BioLegend </td> <td> M5/114.15.2 </td> <td> 107636 </td> </tr> <tr> <td> </td> <td> V8 </td> <td> Ly6C </td> <td> BV 570 </td> <td> 1:400 </td> <td> BioLegend </td> <td> HK1.4 </td> <td> 128030 </td> </tr> <tr> <td> </td> <td> V10 </td> <td> KLRG1 </td> <td> BV 605 </td> <td> 1:300 </td> <td> BioLegend </td> <td> 2F1/KLRG1 </td> <td> 138419 </td> </tr> <tr> <td> </td> <td> V11 </td> <td> F4/80 </td> <td> BV 650 </td> <td> 1:300 </td> <td> BioLegend </td> <td> BM8 </td> <td> 123149 </td> </tr> <tr> <td> </td> <td> V13 </td> <td> Ly6G </td> <td> BV 711 </td> <td> 1:300 </td> <td> BioLegend </td> <td> 1A8 </td> <td> 127643 </td> </tr> <tr> <td> </td> <td> V14 </td> <td> CD3 </td> <td> BV 750 </td> <td> 1:300 </td> <td> BioLegend </td> <td> 17A2 </td> <td> 100249 </td> </tr> <tr> <td> </td> <td> V15 </td> <td> CD206 </td> <td> BV 785 </td> <td> 1:200 </td> <td> BioLegend </td> <td> C068C2 </td> <td> 141729 </td> </tr> <tr> <td> Blue </td> <td> B1 </td> <td> mtDendra2 </td> <td> n/a </td> <td> n/a </td> <td> n/a </td> <td> n/a </td> <td> n/a </td> </tr> <tr> <td> </td> <td> B2 </td> <td> TCRb </td> <td> AF 488 </td> <td> 1:300 </td> <td> BioLegend </td> <td> H57-597 </td> <td> 109215 </td> </tr> <tr> <td> </td> <td> B3 </td> <td> CD8 </td> <td> Spark Blue 550 </td> <td> 1:300 </td> <td> BioLegend </td> <td> 53-6.7 </td> <td> 100780 </td> </tr> <tr> <td> </td> <td> B8 </td> <td> CD45 </td> <td> PerCP </td> <td> 1:200 </td> <td> BioLegend </td> <td> 30-F11 </td> <td> 103130 </td> </tr> <tr> <td> </td> <td> B9 </td> <td> CD71 </td> <td> PerCP-Cy5.5 </td> <td> 1:200 </td> <td> BioLegend </td> <td> RI7217 </td> <td> 113816 </td> </tr> <tr> <td> </td> <td> B10 </td> <td> NKp46 </td> <td> PerCP-eFluor710 </td> <td> 1:200 </td> <td> eBioscience </td> <td> 29A1.4 </td> <td> 46-3351-82 </td> </tr> <tr> <td> Green </td> <td> YG1 </td> <td> TCRgd </td> <td> PE </td> <td> 1:300 </td> <td> BioLegend </td> <td> GL3 </td> <td> 118108 </td> </tr> <tr> <td> </td> <td> YG3 </td> <td> CD64 </td> <td> PE/Dazzle 594 </td> <td> 1:300 </td> <td> BioLegend </td> <td> X54-5/7.1 </td> <td> 139320 </td> </tr> <tr> <td> </td> <td> YG4 </td> <td> CD4 </td> <td> PE/Fire 640 </td> <td> 1:300 </td> <td> BioLegend </td> <td> GK1.5 </td> <td> 100482 </td> </tr> <tr> <td> </td> <td> YG5 </td> <td> CD62L </td> <td> PE-Cyanine5 </td> <td> 1:300 </td> <td> BioLegend </td> <td> MEL-14 </td> <td> 104410 </td> </tr> <tr> <td> </td> <td> YG7 </td> <td> CD11c </td> <td> PE-Cyanine5.5 </td> <td> 1:300 </td> <td> eBioscience </td> <td> N418 </td> <td> 35-0114-82 </td> </tr> <tr> <td> </td> <td> YG9 </td> <td> CD25 </td> <td> PE/Cyanine7 </td> <td> 1:200 </td> <td> BioLegend </td> <td> PC61 </td> <td> 102016 </td> </tr> <tr> <td> Red </td> <td> R1 </td> <td> CD9 </td> <td> APC </td> <td> 1:300 </td> <td> BioLegend </td> <td> MZ3 </td> <td> 124812 </td> </tr> <tr> <td> </td> <td> R2 </td> <td> CD127 </td> <td> AF 647 </td> <td> 1:200 </td> <td> BioLegend </td> <td> A7R34 </td> <td> 135020 </td> </tr> <tr> <td> </td> <td> R3 </td> <td> CD19 </td> <td> Spark NIR 550 </td> <td> 1:300 </td> <td> BioLegend </td> <td> 6D5 </td> <td> 115568 </td> </tr> <tr> <td> </td> <td> R4 </td> <td> CD90.2 </td> <td> AF 700 </td> <td> 1:300 </td> <td> BioLegend </td> <td> 30-H12 </td> <td> 105320 </td> </tr> <tr> <td> </td> <td> R5 </td> <td> CD5 </td> <td> BUV 737 </td> <td> 1:300 </td> <td> BD Horizon </td> <td> 53-7-3 </td> <td> 612809 </td> </tr> <tr> <td> </td> <td> R6 </td> <td> Viability dye </td> <td> Zombie NIR </td> <td> 1:1,000 </td> <td> BioLegend </td> <td> n/a </td> <td> 423106 </td> </tr> <tr> <td> </td> <td> R7 </td> <td> NK1.1 </td> <td> APC/Fire 750 </td> <td> 1:300 </td> <td> BioLegend </td> <td> PK136 </td> <td> 108752 </td> </tr> <tr> <td> </td> <td> R8 </td> <td> B220 </td> <td> APC/Fire 810 </td> <td> 1:300 </td> <td> BioLegend </td> <td> RA3-6B2 </td> <td> 103278 </td> </tr> </tbody> </table>

Lago Argentino age-depth models

Lago Argentino age-depth model data Each file has 1002 columns Column  1     = depth Column  2     = median pixel intensity of this varve Columns 3-1002     = ensemble age-depth model for this core

Effects of Reanalysis Forcing Fields on Ozone Trends and Age of Air from a Chemical Transport Model

This dataset is based on the global off-line 3-D chenmical transport model (TOMCAT/SLIMCAT) forced with ECMWF reanalyses (ERA-Interim and ERA5) to compare the performance of the stratospheric ozone simulations. Each field is separately saved as NETCDF file. Each field is show on geographic coordinates, which can be longitude, latitude, vertical hybrid-pressure level (for zonal mean fields, such as ozone, temperature and age-of-air). The dimensions in each field are: lat --> latitude lon --> longitude lev --> hydrid pressure level time --> months of the simulation The output of the total column ozone from the TOMCAT/SLIMCAT simulations forced with ERA-Interim and ERA5 for Figures 1-4 and  Figure S2 in the supplement are in files: toz_A_ERAI.nc toz_B_ERA5.nc The output of the stratospheric column ozone (SCO) in Figure S1 in the supplement are in the file (levels1-3 are SWOOSH, B_ERA5 and A_ERAI SCO data, respectively): sco_SWOOSH_A_ERAI_B_ERA5.nc The output of zonal mean ozone profiles from the TOMCAT/SLIMCAT simulations forced with ERA-Interim and ERA5 for Figures 5-7, 9 and Figures S3-4 are in files: O3_mm_A_ERAI.nc O3_mm_B_ERA5.nc The output of zonal mean temperature from the TOMCAT/SLIMCAT simulations forced with ERA-Interim and ERA5 for Figure 8 are in files: te_mm_A_ERAI.nc te_mm_B_ERA5.nc The output of zonal mean age-of-air from the TOMCAT/SLIMCAT simulations forced with ERA-Interim and ERA5 for Figures 10-12 are in files: Age_mm_A_ERAI.nc Age_mm_B_ERA5.nc The output of the zonal mean ozone, temperature and age-of-air from the ERA5.1 reanalysis corrected simulations during the period from 2000 to 2006 in all Figures above using ERA5 are in files: ERA5_1_O3_2000_18.nc ERA5_1_te_2000_18.nc ERA5_1_Age_2000_18.nc

Environmental Reconstructions Based on Aquatic and Terrestrial Snails Originating from the Early Bronze Age and the Late Islamic Period– A Stable Isotope Case Study from the Al-Khashbah Archaeological Site, Sultanate of Oman

Supplementary data for the article: "Environmental Reconstructions Based on Aquatic and Terrestrial Snails Originating from the Early Bronze Age and the Late Islamic Period– A Stable Isotope Case Study from the Al-Khashbah Archaeological Site, Sultanate of Oman"

opencc-zeroAug 2022View details →

Diverse aging rates in ectothermic tetrapods provide insights for the evolution of aging and longevity

Comparative studies of mortality in the wild are necessary to understand the evolution of aging, yet ectothermic tetrapods are under-represented in this comparative landscape despite their suitability for testing evolutionary hypotheses. We present a study of aging rates and longevity across wild tetrapod ectotherms, utilizing data from 107 populations (77 species) of non-avian reptiles and amphibians. We test hypotheses of how thermoregulatory mode, temperature, protective phenotypes, and pace of life history contribute to demographic aging. Controlling for phylogeny and body size, ectotherms display a higher diversity of aging rates than endotherms and include phylogenetically widespread evidence of negligible aging. Protective phenotypes and life-history strategies further explain macroevolutionary patterns of aging. By adding ectothermic tetrapods, our comparative analyses enhance our understanding of the evolution of aging.

opencc-by-4.0Sep 2022View details →

Data used in the article "Variable rate of ageing within species: insights from Darwin's frogs"

Data used in the article "Variable rate of ageing within species: insights from Darwin’s frogs" published by the Biological Journal of the Linnean Society. This includes four population-specific .csv files formatted as required by the R's BaSTA package (https://cran.r-project.org/web/packages/BaSTA/index.html). The variables in each file are: ID (number of each individual), Birth (estimated year of birth), Death (in our study this variable is unknown for all individuals), and each year of capture-recapture data from 2014 to 2020 (a 1 indicates that individual was captured a given year, while a 0 indicates the individual was not captured that year). If you plan to use this dataset, we strongly recommned to contact the project leader, Andrés Valenzuela-Sánchez, at: andresvalenzuela.zoo@gmail.com or avalenzuela@ranitadedarwin.org.

opencc-by-4.0Sep 2022View details →

ODP Site 1249, ODP Site 1252, and IODP Site U1325: X-ray fluoresence core scanning, laser diffraction grain size, CNS elemental/isotopic, environmental magnetism, and age model data

We present data used as part of an integrative early diagenesis study (submitted September 2022 to Marine Geology) focused on identifying zones of magnetite dissolution and pyrite precipitation in which magnetic susceptibility records are altered in gas-hydrate bearing sediments on the Cascadia Margin using archived cores from the Ocean Drilling Program (ODP) and Integrated Ocean Drilling Program (IODP). We analyzed the upper 85 to 100 m below seafloor (mbsf) from ODP Sites 1249 and 1252, and IODP Site U1325. ODP 1249 is at the summit of Hydrate Ridge in an area of active methane seepage and massive gas hydrate accumulations and ODP 1252 is in a nearby slope basin with little occurrence of hydrate. IODP Site U1325 is on the northern Cascadia Margin in a slope basin, with turbidite-hosted gas hydrate. We also include XRF data from the upper sections of ODP Site 1251, IODP U1327, and U1328. We measured X-ray fluorescence using an Avaatech core scanner at the IODP Gulf Coast Repository at Texas A&M University. We measured total carbon, total organic carbon (TOC), total nitrogen, and total sulfur using a Perkin Elmer 2400 Series CHNS/O Analyzer at the university of New Hampshire (ODP Site 1249 and 1252 only). A subset was analyzed for δ13C-TOC using a Costech ECS 4010 elemental analyzer interfaced with a Thermo Finnegan Delta Plus XP continuous flow isotope ratio mass spectrometer at Washington State University. Grain size was measured with a Malvern Mastersizer 2000 laser diffraction particle size analyzer and Hydro 2000G dispersal unit at the University of New Hampshire. Mass frequency-dependent magnetic susceptibility was measured using a Bartington MS2 Magnetic Susceptibility Meter and Bartington MS2B dual frequency sensor (Site U1325 only). Isothermal remanent magnetization and thermal demagnetization curves were measured using a HSM2 SQUID-based Spinner Magnetometer with an ASC Scientific IM-10-30 Impulse Magnetizer and ASC Scientific TD-48SC magnetically-shielded oven (Site U1325 only). Radiocarbon was measured on mixed planktic foraminifers at the Radiocarbon was measured at National Ocean Sciences Accelerator Mass Spectrometry (NOSAMS) facility at Woods Hole Oceanographic Institution (ODP Site 1252 and IODP Site U1325).. Radiocarbon ages were calibrated to calendar ages using CALIB 8.2 and the Marine20 calibration curve. For ODP Site 1252 we used a reservoir correction of 230 ± 50 years (Yaquina Bay, Oregon, USA) and for IODP Site U1325 we used a reservoir correction of 202 ± 50 years (Amphitrite Point, British Columbia, Canada).  δ18O was measured on benthic foraminifer Uvigerina peregrina tests using a Finnegan MAT 252 isotope ratio mass spectrometer with Kiel III device at the Oregon State University Stable Isotope Laboratory (ODP 1252) and a Finnegan MAT 253 isotope ratio mass spectrometer with Kiel IV device at the University of Michigan Stable Isotope Laboratory (ODP Site 1249 and IODP Site U1325).

Towards future directions in data-integrative supervised prediction of human aging-related genes

Corresponding author: <a href="http://www.nd.edu/~tmilenko">Prof. Tijana Milenković</a>, tmilenko AT nd DOT edu. Detailed descriptions of the data and program: check <a href="https://nd.edu/~cone/DirectionsAging/">our paper's website</a>. Reference: Qi Li, Khalique Newaz, and Tijana Milenković (2022). Towards future directions in data-integrative supervised prediction of human aging-related genes. under review

opencc-zeroSep 2022View details →

Can age-related changes in parental care modulate inbreeding depression? A test using the burying beetle, Nicrophorus orbicollis

Parental care has been shown to reduce the magnitude of inbreeding depression in some species with facultative care. However, parents often vary in the quality or amount of care they provide to their offspring and it is less clear whether this variation also impacts the magnitude of inbreeding depression. Here, we tested whether age related changes in parental care modulate the expression of inbreeding depression in the burying beetle, Nicrophorus orbicollis. Consistent with previous studies, we found that older parents produced larger broods of offspring than younger parents without sacrificing mean larval mass. Inbreeding depression was evident in several fitness-related traits: brood size at dispersal, the proportion of the brood that survived to eclosion, and mean age at death were all reduced in inbred broods compared to outbred broods. Surprisingly, inbred offspring were heavier at dispersal than outbred offspring. This was likely due to reduced sibling competition in inbred broods. Despite evidence for age related changes in parental investment and the existence of inbreeding depression, there was no evidence that an interaction between the two influenced any of the traits we measured. Our results suggest that age-related changes in parental care may be too slight to influence the expression of inbreeding depression.

opencc-zeroOct 2022View details →

Two notorious nodes: A critical examination of relaxed molecular clock age estimates of the bilaterian animals and placental mammals

The popularity of relaxed clock Bayesian inference of clade origin timings has generated several recent publications with focal results considerably older than the fossils of the clades in question. Here we critically examine two such clades: the animals (with focus on the bilaterians); and the mammals (with focus on the placentals). Each example displays a set of characteristic pathologies which, although much commented on, are rarely corrected for. We conclude that in neither case does the molecular clock analysis provide any evidence for an origin of the clade deeper than what is suggested by the fossil record. In addition, both these clades have other features (including, in the case of the placental mammals, proximity to a large mass extinction) that allow us to generate precise expectations of the timings of their origins. Thus, in these instances the fossil record can provide a powerful test of molecular clock methodology, and why it goes astray; and we have every reason to think these problems are general.

opencc-byOct 2016View details →

Nant Yr Eira Bronze Age Copper Mine, Powys

Nant Yr Eira is a remote lead and copper mine high on the slopes of Plynlimon in west Montgomeryshire. The earliest working here is the deep open-cut (95 metres long by 6 metres wide and 7 metres deep) on the upper section of the stream which mined a vein of copper ore. Trench excavations across the old spoil tips lining the open-cut revealed broken hammer stones, charcoal and antler pick fragments indicating mining in the Bronze Age between 2000 and 1500 BC. Lower down the hillside can be seen the remains of the Snowbrook Lead Mine (1858 - 87) with a single ore bin and sorting platform and a stone tramway embankment leading to the head of the prominent wheel pit of the crusher house. Below the crusher house there is a formerly roofed over platform and down by the stream there are buddle and jigger processing tips with remains of the jigger platforms and circular buddles. On the slope above the crusher house are grass covered tips leading from the main shaft and a possible barrack and office building. Source: Objaverse 1.0 / Sketchfab