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62 results for “erodability”
Decomposition of soil and permafrost organic matter eroding into the Beaufort Sea near Drew Point, Alaska
Arctic coastal erosion mobilizes large quantities of permafrost organic matter to the Arctic Ocean, where it may be decomposed, releasing carbon dioxide. To quantify the biodegradability of this eroding material, we designed an aerobic bottle incubation experiment to measure CO2 production from coastal soils/sediments submerged in seawater. Seasonally thawed active layer soils and permafrost were sampled near Drew Point along the Alaska Beaufort Sea coast. Cores were taken from three surface geomorphic classifications common in this area: primary surface that has not been reworked by thaw-lake cycles, a young drained lake basin, and an ancient drained lake basin. Core subsamples were chosen to represent three distinct horizons present in eroding bluffs at Drew Point: seasonally thawed active layer soils near the tundra surface, Holocene-age terrestrial soils and/or lake sediments, and late-Pleistocene age relict marine sediments. Soil/sediment subsamples were mixed with Beaufort Sea surface water and incubated in triplicate at 4C and 16C for 40 days. In addition, a subset of soil/sediment samples were incubated with and without seawater at 16C for 40 days. The data reported here summarizes the results of the incubation experiment for each soil sample: cumulative CO2-C production over 40 days normalized to dry weight and to organic carbon content (OC), average rate of CO2 production normalized to dry weight and to TOC, and the percent of OC remineralized over 40 days.
Composition and biodegradability of dissolved organic matter leached from eroding coastal soils and permafrost in seawater, from Drew Point, Alaska
Eroding permafrost coastlines export significant quantities of organic carbon (OC) to the marine environment, similar in magnitude to riverine particulate OC fluxes to the Arctic Ocean. Moreover, erosion rates are predicted to increase due to warming temperatures, declines in sea ice, and increasing waves. While erosion primarily mobilizes organic matter in the particulate form, this material can be leached to dissolved organic matter (DOM). This DOM may be incorporated by microbial communities and fuel marine food webs or decomposed to form greenhouse gases like carbon dioxide and methane. Many studies show that permafrost-derived organic matter can be rapidly decomposed in soils and freshwater, but few studies examine the fate of permafrost organic matter in seawater. To address this knowledge gap, we designed a laboratory experiment to leach coastal soils and permafrost in seawater and examine the composition and biodegradability of leached DOM. Coastal soil/sediment was cored near Drew Point, Alaska in 2019, representing three horizons found within rapidly eroding permafrost bluffs: seasonally thawed active layer soils, Holocene terrestrial soils and/or lacustrine sediments, and late-Pleistocene relict marine sediments. To measure dissolved organic carbon (DOC) leaching yields, we placed soil/sediments in Beaufort Sea seawater for 24 hours before filtering to remove particulates. To measure biodegradable dissolved organic carbon (BDOC), we conducted an aerobic incubation experiment following the methods suggested by Vonk et al. (2015). Briefly, leachates were incubated at approximately room temperature for 26 and 90 days to measure DOC loss due to remineralization and/or incorporation into microbial biomass. Additionally, we used chromophoric dissolved organic matter (CDOM) measurements and ultra-high resolution mass spectrometry (FT-ICR MS) to examine the initial leachate DOM composition. References: Vonk, J. E., Tank, S. E., Mann, P. J., Spencer, R. G. M., Tre
SERENA EJPSOIL PL EROSION CONTROL SOIL MASS NOT ERODED
<p>General description of SERENA</p> <p>The internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.</p> <p>Files description</p> <p>Data was prepared as a result of SERENA EJP SOIL. The attached files are a part of the analysis of Assessment of Soil Threats and Ecosystem Services from each MS with the harmonized procedures. SERENA deliverable 3.3 (https://doi.org/10.5281/zenodo.13991087). The RUSLE method was used to prepare the attached files. </p>
Disturbance and recovery at three headward-eroding creeks on Sapelo Island, Georgia, USA.
We studied the perturbation caused by the movement of headward-eroding creeks onto the marsh platform in southeastern USA salt marshes. Between May and November 2019, we measured the disturbance responses of 19 variables in terms of both magnitude (the difference between perturbed areas and control areas located on the marsh platform) and recovery trajectory (evaluated using a space for time substitution design along a marsh transect that ran the length of the newly-formed creek). Variables measured include stem density, stem height, burrow density, snail density, sediment redox, soil water content, soil salinity, soil organic content, soil pH, soil surface temperature, root biomass, rhizome biomass, concentration of green algae, concentration of cyanobacteria, concentration of diatoms, soil stiffness, light interception by the canopy, marsh soil surface elevation, and number of years since disturbed.
Geochemistry of soils and eroded suspended sediments from two large rural catchments in southern Brazil for studies on Suspended Sediment Fingerprinting
<p> <strong>1. Introduction</strong></p> <p>This dataset comes from a research project entitled "Water and pollutants, from cropfields to cities: evaluation and improved of soil management technologies in a catchment network " supported by the Foundation for Research Support of the State of Rio Grande do Sul (FAPERGS) and National Council for Scientific and Technological Development (CNPq) (process n°10/0034-0). The project was carried out between 2010 and 2014 under the coordination of José Miguel Reichert and Danilo Rheinheimer dos Santos, professors at the Federal University of Santa Maria. One of the aims of this project was to understand the main pollutant transfer process from hillslopes to fluvial systems in large rural catchments representative of the agricultural production system in Southern Brazil. In this context, the Suspended Sediment Fingerprinting (SSF) was extremely useful for quantifying the origin of the sediment yield monitored at the outlet of these catchments. Among the various works carried out in this project, we highlight Tales Tiecher's doctoral thesis (Tiecher, 2015) that explored the SSF in many catchments, including the Conceição and Guaporé river basins.</p> <p><strong>2. Material and Methods</strong></p> <p>The catchments represent the magnitude of erosive and hydrological processes representative of Southern Brazil. The Conceição catchment has a drainage area of 804 km<sup>2</sup> (28°27′22″S and 53°58′24″ W). According to Köppen, the climate is Cfa type, with an annual rainfall between 1,750 and 2,000 mm. Geology is riodacithe basalt, with a formation of deep and highly weathered soils (Oxisols, Ultisols, and Alfisols). The relief is characterized by gentle slopes (6–9 %) on top and hillside slopes and higher steepness (10–14%) near the drainage channels. Farming based on the production of soybeans (<em>Glycine max</em>) in summer and wheat (<em>Triticumspp.</em>), oats (<em>Avena strigosa</em>), and ryegrass (<em>Lolium multiflorum</em>) in winter. The Guaporé catchment has a drainage area of 1,980 km<sup>2</sup> (28°54′41″S and 51°57′10″W), it covers part of the meridional plateau border. The climate is classified as Cfa, with annual rainfall varies between 1,400 and 2,000 mm. Geology is characterized by volcanic lava flows, and topography is undulating to hilly. Due to variations in landscape, several classes of soils (Entisols, Luvisol, Cambisol, Oxisol, Ultisol, and Chernosol). The land use is highly heterogeneous. In the upper third of the catchment, there is a predominance of soybean cultivated under no-tillage soil management. In the other two-thirds (middle and lower parts), land use and soil management are very heterogeneous. The main land uses are tobacco (<em>Nicotiana tabacum</em>) and maize (<em>Zea mays</em>) crops, Eucalyptus (<em>Eucalyptus</em> spp.), as well as pastures for dairy cattle. The contribution of unpaved roads is relevant to the sediment yield in both catchments (Didoné et al., 2014). Composite samples of potential sediment sources (cropland, unpaved roads, and stream channel banks) were collected. Sediment source samples were taken from the surface soil layer (0–0.05 m) of cropland and unpaved roads and on exposed sites located along the river channel network. Each sample was composed of at least 10 subsamples. To obtain representative samples of suspended sediment transported in the catchment’s outlet were used three strategies: (1) to collect flood suspended sediments (FSS) through the manual sampling (USDH-48) at different periods during the rising and falling stages of floods; (2) to deploy time-integrated suspended sediment samplers (TISS), by installing the device developed by Phillips et al. (2000) at different sites within the catchments; to collect fine-bed sediment (FBS) with a suction stainless sampler limiting the loss of fine material at the bed river. Source and sediment samples were oven‐dried at 50 °C, gently disaggregated using a pestle and mortar, and then sieved to 62,5 μm. The geochemical tracers evaluated were total organic carbon estimated by wet oxidation (K<sub>2</sub>Cr<sub>2</sub>O<sub>7</sub> + H<sub>2</sub>SO<sub>4</sub>) and the total concentration of Al, Ba, Be, Ca, Co, Cr, Cu, Fe, K, La, Li, Mg, Mn, Na, Ni, P, Pb, Sr, Ti, V, and Zn using inductively coupled plasma optical emission spectrometry after microwave‐assisted digestion with concentrated HCl and HNO<sub>3</sub> (ratio 3:1) for 9.5 min at 182 °C (Tiecher, 2015; Tiecher et al. 2017, 2018).</p> <p> <strong>3. Final remarks</strong></p> <p> The SSF results provided by this dataset (Tiecher, 2015) combined with sediment yield monitoring were very important for the assessment and modeling studies in these two catchments that took place after that (Didoné et al., 2015; 2017). In addition, other studies have explored the same sample bank, expanding upon the array of tracer properties and increasing our understanding about the mechanisms of sediment and pollutant transfer in these catchments (Le Gall et al. 2017; Zafar et al., 2017; Ramon et al., 2020).</p> <p> <strong>4. References</strong></p> <p> Didoné, E. J., Minella, J. P. G., Reichert, J. M., Merten G. H., Dalbianco, L., Barros, C. A. P., Ramon, R. (2014) Impact of no-tillage agricultural systems on sediment yield in two large catchments in southern Brazil. J Soils Sediments 14:1287–1297.</p> <p>Didoné, E.J., Minella, J.P.G., Evrard, O. (2017). Measuring and modelling soil erosion and sediment yields in a large cultivated catchment under no-till of Southern Brazil. Soil Tillage Res. 174, 24-33. https://doi.org/10.1016/j.still.2017.05.011</p> <p>Didoné, E. J.; Minela, J. P. G.; Merten, G. H. (2015). Quantifying soil erosion and sediment yield in a catchment in southern Brazil and implications for land conservation. J. Soils Sediments 11, 2334-2346. https://doi.org/10.1007/s11368-015-1160-0</p> <p>le Gall, M., Evrard, O., Dapoigny, A., Tiecher, T., Zafar, M., Minella, J. P. G., Laceby, J. P., & Ayrault, S. (2017). Tracing sediment sources in a subtropical agricultural catchment of southern Brazil cultivated with conventional and conservation farming practices. Land Degradation and Development, 28(4). https://doi.org/10.1002/ldr.2662</p> <p>Ramon, R., Evrard, O., Laceby, J. P., Caner, L., Inda, A. v., Barros, C. A. P., Minella, J. P. G., & Tiecher, T. (2020). Combining spectroscopy and magnetism with geochemical tracers to improve the discrimination of sediment sources in a homogeneous subtropical catchment. Catena, 195, 104800. https://doi.org/10.1016/j.catena.2020.104800</p> <p>Tiecher, T. (2015). Fingerprinting sediment sources in agricultural catchments in Southern Brazil. Doctoral Dissertation in Soil Science. Universidade Federal de Santa Maria, Santa Maria, RS.</p> <p>Tiecher, T., Minella, J. P. G., Caner, L., Evrard, O., Zafar, M., Capoane, V., le Gall, M., & Santos, D. R. D. (2017). Quantifying land use contributions to suspended sediment in a large cultivated catchment of Southern Brazil (Guaporé River, Rio Grande do Sul). Agriculture, Ecosystems and Environment, 237. https://doi.org/10.1016/j.agee.2016.12.004</p> <p>Tiecher, T., Minella, J. P. G., Evrard, O., Caner, L., Merten, G. H., Capoane, V., Didoné, E. J., & dos Santos, D. R. (2018). Fingerprinting sediment sources in a large agricultural catchment under no-tillage in Southern Brazil (Conceição River). Land Degradation and Development, 29(4). https://doi.org/10.1002/ldr.2917.</p> <p>Zafar, M., Tiecher, T., Capoane, V., Troian, A., dos Santos, D.R. (2017). Characteristics, lability and distribution of phosphorus in suspended sediment from a subtropical catchment under diverse anthropic pressure in Southern Brazil. Ecol. Eng. 100, 28–45.</p>
Germination and early establishment of dryland grasses and shrubs on wind-eroded soils from the Jornada Basin LTER Scrape site, 2018-2019
In this dataset, we report germination and seedling growth of contrasting perennial grass (Bouteloua eriopoda, Sporobolus airoides, and Aristida purpurea) and shrub (Prosopis glandulosa, Atriplex canescens, and Larrea tridentata) functional groups grown on non-winnowed and winnowed soils collected from the Jornada Basin LTER Scrape Site at the Jornada Experimental Range (JER) in southern New Mexico, U.S.A. The soil physical and chemical properties of winnowed and non-winnowed soils were evaluated, and soil water retention curves were obtained for the two soil types. A controlled pot experiment was conducted under the well-watered greenhouse conditions at the University of Arizona campus, Tucson, AZ in 2018 and 2019 to test if topsoil "winnowing" by wind erosion would differentially affect grass and shrub seedling establishment to promote shrub recruitment over that of grass. Data include soil water retention curves, soil chemistry, nutrients, and texture, seedling germination, and seedling growth and biomass. This study is complete and the data are published in the article below. Niu, F., Pierce, N. A., Archer, S. R., & Okin, G. S. (2021). Germination and early establishment of dryland grasses and shrubs on intact and wind-eroded soils under greenhouse conditions. Plant and Soil, 1-16. DOI: 10.1007/s11104-021-05005-9
Surface retreat rate from gullies at an eroding blanket bog, Aberdeenshire, UK.
<p>Surface retreat rate (erosion rate) or peat from seven erosion gullies within an eroding blanket bog. The bog is on a large high-altitude plateau blanket bog in the eastern part of the Cairngorms National Park, Scotland, UK (56.93° N, − 3.16° E, 642 m asl). </p> <p> Within each erosion gully, 9 1m steel pins (threaded rod) were inserted into the peat until they reached bed rock or were almost competely submerged (but still visible). The pins were oriented in a 1m2 square with 0.5m between each pin. Approximately every 2-4 months the distance between the top of each pin and the top of the peat was measured (measuring to the lowest point at which peat surace intersects with the pin).</p> <p>The dataset shows:</p> <p>Date: date at which the measurement was taken</p> <p>Gully: The gully number (1-7)</p> <p>Pin: The pin number within each gully (1-9)</p> <p>dL: Change in exposed length of pin (cm) compared to the start date of 27/09/2022</p>
Data and code for: "Global Sampling Decline Erodes Science Potential of Natural History Collections"
<p># GBIF Specimen Data Analysis and Forecasting<br><br>## Version 2 - modified date ranges for figures 1 and 2 in response to reviewer comments</p> <p>This repository contains the code and data for analysing and forecasting trends in Global Biodiversity Information Facility (GBIF) specimen records across three major taxonomic groups: Chordata, Arthropoda, and Plantae. <br>The analysis pipeline includes data cleaning, anomaly detection, primary analyses, and forecasting based on historical database snapshots.</p> <p>These scripts and data correspond to analyses in the following manuscript:</p> <p>Global Sampling Decline Erodes Science Potential of Natural History Collections</p> <p>Authors:<br>Owen Forbes<br>Andrew G. Young<br>Peter H. Thrall</p> <p><br>## Repository Structure</p> <p>The repository consists of three main Quarto (.qmd) scripts and associated data files:</p> <p>1. `1_DataCleaning_Forbes-et-al_2025.qmd`: Data cleaning and anomaly detection<br>2. `2_PrimaryAnalyses_Forbes-et-al_2025.qmd`: Primary analyses and visualisation<br>3. `3_SnapshotsForecasting_Forbes-et-al_2025.qmd`: Historical snapshot analysis and forecasting</p> <p>## Requirements</p> <p>- R (version 4.3.2 or later)<br>- Required R packages:<br> - tidyverse (v2.0.0) - for data manipulation and visualization<br> - readr (v2.1.5) - for reading CSV/TSV files<br> - ggplot2 (v3.4.0 or v3.5.0) - for creating visualizations<br> - rnaturalearth (v1.0.1) - for accessing natural earth map data<br> - dplyr (v1.1.0 or v1.1.4) - for data manipulation<br> - countrycode (v1.6.0) - for converting country names and codes<br> - spdep (v1.3-3) - for spatial dependence modeling<br> - sp (v1.6-0 or v2.1-3) - for spatial data manipulation<br> - sf (v1.0-15 or v1.0-16) - for simple features access<br> - data.table (v1.14.8) - for fast aggregation of large data<br> - lubridate (v1.9.2) - for date-time manipulation<br> - viridis (v0.6.3) - for color palettes<br> - gridExtra (v2.3) - for arranging multiple plots<br> - ggpubr (v0.6.0) - for creating publication-ready plots<br> - zoo (v1.8-12) - for time series, including moving averages<br> - scales (v1.3.0) - for graphical scales<br> - forecast (v8.22.0) - for ARIMA forecast models<br> - purrr (v1.0.2) - for mapping custom forecast function onto each dataset<br> - arrow - for working with parquet files</p> <p>Install these packages before running the scripts.</p> <p>## How to Use</p> <p>1. Download this repository to your local machine.<br>2. Set your working directory to the location of the scripts.<br>3. Download raw datasets from GBIF (as required)<br>4. Ensure all required R packages are installed.<br>5. Run the scripts in RStudio or your preferred R environment.</p> <p>### Data Cleaning (`1_DataCleaning_Forbes-et-al_2025.qmd`)</p> <p>This script cleans the raw GBIF data and identifies anomalies. It produces files containing indexes of dataset records to be removed, which are used in subsequent analyses.</p> <p>**Note**: The raw GBIF exported datasets for contemporary records are not included in this repository due to file size constraints. Download them from the GBIF links provided in the script and place them in the `data/` directory.</p> <p>### Primary Analyses (`2_PrimaryAnalyses_Forbes-et-al_2025.qmd`)</p> <p>This script performs the main analyses and generates visualisations. It uses the outputs from the data cleaning script to filter anomalous records.</p> <p>To reproduce all analysis stages from the original raw .csv files:<br>- Start at the chunks labelled "DATA LOAD AND FILTERING".<br>- Run the pipeline for non-spatial analyses before spatial analyses.<br>- Due to memory constraints, it's recommended to run analyses for one taxonomic group and one analysis stream at a time.</p> <p>To skip to plot generation:<br>- Navigate to sections tagged as "@! SKIP TO PLOTTING !@".<br>- Ensure all required analysis output files are in the `data/` directory.</p> <p>### Forecasting (`3_SnapshotsForecasting_Forbes-et-al_2025.qmd`)</p> <p>This script analyses historical GBIF database snapshots and forecasts future growth. It uses the cleaned snapshot data produced by the data cleaning script.</p> <p>## Data Files</p> <p>### GBIF Exports - Raw Data (not included on Zenodo due to file size, please download directly from GBIF)<br>- `0016915-240425142415019.csv` for Chordata - https://www.gbif.org/occurrence/download/0016915-240425142415019</p> <p>- `0016914-240425142415019.csv` for Plantae - https://www.gbif.org/occurrence/download/0016914-240425142415019 </p> <p>- `0016913-240425142415019.csv` for Arthropoda - https://www.gbif.org/occurrence/download/0016913-240425142415019</p> <p>### Included Data Files</p> <p>#### Raw Data<br>- `GBIF_snapshots.parquet` # Historical snapshots RAW dataset (arrow/parquet format)<br>- `GBIF_integer_to_datasetKey.tsv` # Mapping old dataset IDs onto new datasetKey field</p> <p>#### Contemporary Datasets - data cleaning outputs<br>- `chordata_counts_to_highlight_030724` # List of anomalous Chordata dataset + year indexes to filter<br>- `arthropoda_counts_to_highlight_OG_030724` # List of anomalous Arthropoda dataset + year indexes to filter<br>- `plantae_counts_to_highlight_030724` # List of anomalous Plantae dataset + year indexes to filter</p> <p>#### Cleaned Snapshots<br>- `plantae_snapshots_filter_threshold_IN_040924` # Cleaned Plantae snapshots<br>- `arthropoda_snapshots_filter_threshold_IN_040924` # Cleaned Arthropoda snapshots<br>- `chordata_snapshots_filter_threshold_IN_040924` # Cleaned Chordata snapshots<br>- `gbif_dates_df_anomaly_filtered_090724` # Anomaly-filtered snapshots (combined dataset)<br>- `gbif_dates_df_anomalies_highlighted_090724` # Anomalies highlighted snapshots (combined dataset)</p> <p>#### Analysis Outputs - for skipping straight to plot/figure generation<br>- `arthropoda_specimens_per_year_080724` # Arthropoda specimen counts per year<br>- `arthropoda_unique_species_per_year_080724` # Arthropoda unique species counts per year<br>- `arthropoda_grid_counts_080724` # Arthropoda grid counts<br>- `chordata_specimens_per_year_080724` # Chordata specimen counts per year<br>- `chordata_unique_species_per_year_080724` # Chordata unique species counts per year<br>- `chordata_grid_counts_080724` # Chordata grid counts<br>- `plantae_specimens_per_year_080724` # Plantae specimen counts per year<br>- `plantae_unique_species_per_year_080724` # Plantae unique species counts per year<br>- `plantae_grid_counts_080724` # Plantae grid counts<br>- `chordata_continent_count_080724` # Chordata continent-specific counts<br>- `arthropoda_continent_count_080724` # Arthropoda continent-specific counts<br>- `plantae_continent_count_080724` # Plantae continent-specific counts</p> <p> </p>
Text-fig. 7. Cornacaeae (a–j), Icacinaceae (k–o). a–e: Mastixia. USNM PAL 772364. Scale bar = 1 cm. a: Lateral view of eroded endocarp – the opposite side being missing and the endocarp broken near its mid point, reflected light, palladium coated. b–e: Micro-CT scan surface renderings. b: Rotated 90° from the view in (a). c: Rotated 90° from the view in (b). d: Rotated 90° from (c), exhibiting the damaged "back" face of the endocarp. e: Axillary view of the endocarp; the opposite end missing as apparent in (d). f–j: Cf. Nyssa. DMNH EPI.47808. Scale bar = 1 cm. Micro-CT scan surface renderings. f: Intact face of the endocarp; note ridges and "apical" point. g: Eroded (?gnawed; note horizontal grooving) opposite face of the endocarp. h: Lateral view of the endocarp, eroded/gnawed face to left. i: Apical view, eroded/gnawn portion below. j: Basal view of endocarp. k–o: Iodes DMNH-EPI.47807. Micro-CT scan surface renderings. Scale bar = 1 cm. k: Face view of endocarp. l: Opposite face of endocarp. m: Lateral view demonstrating the compressed nature of the endocarp, note thickened suture marking the probable track of the primary bundle. n: Apical view, primary bundle trace to right. o: Basal view, primary bundle trace to right. in The Early Middle Eocene Wagon Bed Carpoflora Of Central Wyoming, U.S.A.
Text-fig. 7. Cornacaeae (a–j), Icacinaceae (k–o). a–e: Mastixia. USNM PAL 772364. Scale bar = 1 cm. a: Lateral view of eroded endocarp – the opposite side being missing and the endocarp broken near its mid point, reflected light, palladium coated. b–e: Micro-CT scan surface renderings. b: Rotated 90° from the view in (a). c: Rotated 90° from the view in (b). d: Rotated 90° from (c), exhibiting the damaged "back" face of the endocarp. e: Axillary view of the endocarp; the opposite end missing as apparent in (d). f–j: Cf. Nyssa. DMNH EPI.47808. Scale bar = 1 cm. Micro-CT scan surface renderings. f: Intact face of the endocarp; note ridges and "apical" point. g: Eroded (?gnawed; note horizontal grooving) opposite face of the endocarp. h: Lateral view of the endocarp, eroded/gnawed face to left. i: Apical view, eroded/gnawn portion below. j: Basal view of endocarp. k–o: Iodes DMNH-EPI.47807. Micro-CT scan surface renderings. Scale bar = 1 cm. k: Face view of endocarp. l: Opposite face of endocarp. m: Lateral view demonstrating the compressed nature of the endocarp, note thickened suture marking the probable track of the primary bundle. n: Apical view, primary bundle trace to right. o: Basal view, primary bundle trace to right.
Text-fig. 6. Cornaceae. Alangium (a–e), Mastixia (f–r). a–e: Alangium, DMNH EPI.47806. Scale bar = 1 cm. b, e: Reflected light, palladium coated. a, c, d: Micro-CT scan surface rendering. a: Locule cast, face view of slightly larger locule. b: Face view of slightly smaller locule. c: Lateral view of the endocarp, the slightly enlarged left carpel separated from the smaller carpel by a longitudinal septal groove; the faint pitting in the groove suggestive of the septal vasculature. d, e: Views of either end of the endocarp, illustrating the size difference between the two carpels and the pitting in the septal groove suggestive of the septal vasculature. f–k: Mastixia USNM PAL 772362. Scale bar = 1 cm. f, g, j, k: reflected light, palladium coated; h, i: micro-CT scan surface rendering. f: Lateral view of endocarp, inferred dorsal germination valve groove facing the viewer. Note irregular, rugose, longitudinal ridges. g: Lateral view of endocarp, inferred germination valve with median longitudinal groove to left. h: Lateral view of endocarp reoriented with the same longitudinal groove to the right. i: Lateral view, rotated to ventral surface. j: View of one end of the endocarp, germination valve groove up. k: Opposite end view, with prominent radial ridges and intervening grooves, germination valve groove up. l–r: Mastixia USNM PAL 772363. Scale bar = 1 cm. l: View of one face of endocarp, displaying a groove that may represent the surficial expression of the dorsal infold of a Mastixia-like germination valve. Surface badly eroded, reflected light, palladium coated. m: Opposite face of endocarp displaying extensive erosion and a central hole interpreted as feeding damage. n: Lateral view; m, n micro-CT scan surface renderings. o: A view of one end, displaying the prominent groove, reflected light, palladium coated. p: Opposite end to (o). q: View as in (o); p, q micro-CT scan surface renderings. r: Virtual transverse section showing curved locule (arrows). in The Early Middle Eocene Wagon Bed Carpoflora Of Central Wyoming, U.S.A.
Text-fig. 6. Cornaceae. Alangium (a–e), Mastixia (f–r). a–e: Alangium, DMNH EPI.47806. Scale bar = 1 cm. b, e: Reflected light, palladium coated. a, c, d: Micro-CT scan surface rendering. a: Locule cast, face view of slightly larger locule. b: Face view of slightly smaller locule. c: Lateral view of the endocarp, the slightly enlarged left carpel separated from the smaller carpel by a longitudinal septal groove; the faint pitting in the groove suggestive of the septal vasculature. d, e: Views of either end of the endocarp, illustrating the size difference between the two carpels and the pitting in the septal groove suggestive of the septal vasculature. f–k: Mastixia USNM PAL 772362. Scale bar = 1 cm. f, g, j, k: reflected light, palladium coated; h, i: micro-CT scan surface rendering. f: Lateral view of endocarp, inferred dorsal germination valve groove facing the viewer. Note irregular, rugose, longitudinal ridges. g: Lateral view of endocarp, inferred germination valve with median longitudinal groove to left. h: Lateral view of endocarp reoriented with the same longitudinal groove to the right. i: Lateral view, rotated to ventral surface. j: View of one end of the endocarp, germination valve groove up. k: Opposite end view, with prominent radial ridges and intervening grooves, germination valve groove up. l–r: Mastixia USNM PAL 772363. Scale bar = 1 cm. l: View of one face of endocarp, displaying a groove that may represent the surficial expression of the dorsal infold of a Mastixia-like germination valve. Surface badly eroded, reflected light, palladium coated. m: Opposite face of endocarp displaying extensive erosion and a central hole interpreted as feeding damage. n: Lateral view; m, n micro-CT scan surface renderings. o: A view of one end, displaying the prominent groove, reflected light, palladium coated. p: Opposite end to (o). q: View as in (o); p, q micro-CT scan surface renderings. r: Virtual transverse section showing curved locule (arrows).
Text-fig. 9. Carpolithes (a–r). a–d: Carpolithes sp. 5. USNM PAL 772370. Scale bar = 5 mm, reflected light, palladium coated. a: Lateral view of seed, apex up, possible raphe descending from apex toward viewer. b: Lateral view of seed, apex up, possible raphe on right. c: Lateral view, opposite side, apex up, possible raphe on left. d: Apical view, note central pit with raphe descending towards bottom margin. e–h: Carpolithes sp. 6. USNM PAL 772371. Scale bar = 5 mm. e: Basal view illustrating depression and keel in plane of bisymmetry, reflected light, palladium coated. f–h: Micro-CT scan surface rendering. f: Lateral view showing relatively smooth rounded surface. g: Specimen rotated 180° from (f), surface partially eroded. h: Longitudinal view, showing median keel. i–m: Carpolithes sp. 7 USNM PAL 772372. Scale bar = 5 mm. i: View of intact face of globose fruit, possible apical constriction at top. j: Lateral view, intact surface to right, possible apical constriction at top, both micro-CT scan surface renderings. k: Apical view. l: Face view illustrating the mineral filling and the fine, radiating structure of the fruit wall on the left and right margins, both reflected light, palladium coated. m: Closeup of the cellular layer on the left of (l), micro-CT scan surface rendering. n–p: Carpolithes sp. 8. USNM PAL 772373. Scale bar = 3 mm, reflected light, palladium coated. n: Lateral view of pyrene-like structure, one ridge running vertically in the center of view, the other two forming the left and right margins. o: Lateral view of pyrene-like structure, ridge in (n) on the left. p: End-on view illustrating one convex, one concave, and one relatively flat to very slightly concave face. q, r: Carpolithes sp. 9 USNM PAL 772374. Scale bar = 5 mm, reflected light, palladium coated. q: Exterior of the smooth broken half-sphere. r: Interior of the broken half-sphere. in The Early Middle Eocene Wagon Bed Carpoflora Of Central Wyoming, U.S.A.
Text-fig. 9. Carpolithes (a–r). a–d: Carpolithes sp. 5. USNM PAL 772370. Scale bar = 5 mm, reflected light, palladium coated. a: Lateral view of seed, apex up, possible raphe descending from apex toward viewer. b: Lateral view of seed, apex up, possible raphe on right. c: Lateral view, opposite side, apex up, possible raphe on left. d: Apical view, note central pit with raphe descending towards bottom margin. e–h: Carpolithes sp. 6. USNM PAL 772371. Scale bar = 5 mm. e: Basal view illustrating depression and keel in plane of bisymmetry, reflected light, palladium coated. f–h: Micro-CT scan surface rendering. f: Lateral view showing relatively smooth rounded surface. g: Specimen rotated 180° from (f), surface partially eroded. h: Longitudinal view, showing median keel. i–m: Carpolithes sp. 7 USNM PAL 772372. Scale bar = 5 mm. i: View of intact face of globose fruit, possible apical constriction at top. j: Lateral view, intact surface to right, possible apical constriction at top, both micro-CT scan surface renderings. k: Apical view. l: Face view illustrating the mineral filling and the fine, radiating structure of the fruit wall on the left and right margins, both reflected light, palladium coated. m: Closeup of the cellular layer on the left of (l), micro-CT scan surface rendering. n–p: Carpolithes sp. 8. USNM PAL 772373. Scale bar = 3 mm, reflected light, palladium coated. n: Lateral view of pyrene-like structure, one ridge running vertically in the center of view, the other two forming the left and right margins. o: Lateral view of pyrene-like structure, ridge in (n) on the left. p: End-on view illustrating one convex, one concave, and one relatively flat to very slightly concave face. q, r: Carpolithes sp. 9 USNM PAL 772374. Scale bar = 5 mm, reflected light, palladium coated. q: Exterior of the smooth broken half-sphere. r: Interior of the broken half-sphere.
Fig. 3 in Epizoic Anthoathecate Species (Cnidaria, Hydrozoa) Growing on Eroded Shells of Live Gastropods (Nassarius festivus) in Japan
Fig. 3. Hydroid species found on old eroded shells of N. festivus in each collection locality. A. polyps of Dicoryne conybearei (Koajiro); B. gonophores of D. conybearei; C. polyps of Stylactaria misakiensis (Kisarazu); D. gonophores of S. misakiensis; E. polyps of Leuckartiara sp. (Torinosu); F. a medusa of Leuckartiara sp. The yellow arrows indicate the polyps of each hydroid species. Scales=5 mm (A, C, E), 0.5 mm (D, F), 0.1 mm (B).
Fig. 1 in Epizoic Anthoathecate Species (Cnidaria, Hydrozoa) Growing on Eroded Shells of Live Gastropods (Nassarius festivus) in Japan
Fig. 1. Sampling locations of shells of living Nassarius festivus bearing epizoic hydroid polyps. A. Kisarazu, Chiba Pref. (Stylactaria misakiensis), B. Koajiro, Kanagawa Pref. (Dicoryne conybearei), C. Torinosu, Shirahama, Wakayama Pref. (Leuckartiara sp.), D. Isozaki, Ibaraki Pref. (Koellikerina bouilloni in Namikawa and Kawamura, 2021), E. Takehara, Hiroshima Pref. (Leuckartiara sp. in Kondo et al., 2020).
Fig. 2 in Epizoic Anthoathecate Species (Cnidaria, Hydrozoa) Growing on Eroded Shells of Live Gastropods (Nassarius festivus) in Japan
Fig. 2. Nassarius festivus collected from Torinosu, Shirahama, Wakayama Pref., showing erosion of older shells. A–B. fresh shells; C–E. old eroded shells. Scale=5 mm.
Text-fig. 3. Geological map and schematic geological section of the discovery site of the Late Upper Palaeolithic skull from Moča (southern Slovakia). I. – Primary position (?), II. – The discovery site (secondary position), A – B – The schematic geological section of the discovery site 1. H – Fluvial clayey to sandy loams (subordinately humolites) – Holocene; secondary discovery site layer, 2. lm-pH – Loam – peat – Holocene, 3. e Wl – Eolian sands – Late Würm (Late glacial of Würm), 4. lm,sWl – Fluvial clayey (to humic) loams or fine sands – Late Würm (Late glas cial of Würm); original discovery site layer, now eroded, 4a. fe Wl – Fluvial – aeolian silty sands (calcareous) – Late Würm (Late glacial s-lm of Würm), 5. lmW3 – Fluvial loams, sandy loams – final Würm (W3), 5a. W3 – Fluvial sands – final (?) Würm (?W3), 6. gW2+3 – Fluvial gravs els, sandy gravels, sands with gravel – Pleniglacial of Würm (W2+3), 7. lW – Aeolian loess and loess loams – Würm (undivided) in A Late Upper Palaeolithic Skull From Moča (The Slovak Republic) In The Context Of Central Europe
Text-fig. 3. Geological map and schematic geological section of the discovery site of the Late Upper Palaeolithic skull from Moča (southern Slovakia). I. – Primary position (?), II. – The discovery site (secondary position), A – B – The schematic geological section of the discovery site 1. H – Fluvial clayey to sandy loams (subordinately humolites) – Holocene; secondary discovery site layer, 2. lm-pH – Loam – peat – Holocene, 3. e Wl – Eolian sands – Late Würm (Late glacial of Würm), 4. lm,sWl – Fluvial clayey (to humic) loams or fine sands – Late Würm (Late glas cial of Würm); original discovery site layer, now eroded, 4a. fe Wl – Fluvial – aeolian silty sands (calcareous) – Late Würm (Late glacial s-lm of Würm), 5. lmW3 – Fluvial loams, sandy loams – final Würm (W3), 5a. W3 – Fluvial sands – final (?) Würm (?W3), 6. gW2+3 – Fluvial gravs els, sandy gravels, sands with gravel – Pleniglacial of Würm (W2+3), 7. lW – Aeolian loess and loess loams – Würm (undivided)
Text-fig. 7. Steinkerns of the land snail Arabicolaria omanensis eroding from indurated dark green-brown sands of Bed C above the Omanitherium type locality (the pen is 14.5 cm long). in Large Mammals From The Rupelian Of Oman - Recent Finds
Text-fig. 7. Steinkerns of the land snail Arabicolaria omanensis eroding from indurated dark green-brown sands of Bed C above the Omanitherium type locality (the pen is 14.5 cm long).
Text-fig. 7. a. Worn section through a horizontally bedded body-chamber and phragmocone, body-chamber showing oyster attached to inside of aperture as well as burrow mottling. Tape measure provides scale. b. Body-chamber and crushed phragmocone with body-chamber and phragmocone entirely filled with bioturbated matrix containing stringers of crinoid and molluscan debris. Flank of phragmocone encrusted by oysters. Tape measure for scale. c. Complex of Thallassinoides and Diplocraterion burrows associated with conch that has been eroded out by wave action. A few 'Ghostly' fragments of ammonite are also present. Original scope of the image approximately 400 mm. c. Verically embedded conch with largely intact septa and camera infilled with burrowed matrix containing crinoid debris. Tape measure for scale. in 'Cenoceras Islands' In The Blue Lias Formation (Lower Jurassic) Of West Somerset, Uk: Nautilid Dominance And Influence On Benthic Faunas
Text-fig. 7. a. Worn section through a horizontally bedded body-chamber and phragmocone, body-chamber showing oyster attached to inside of aperture as well as burrow mottling. Tape measure provides scale. b. Body-chamber and crushed phragmocone with body-chamber and phragmocone entirely filled with bioturbated matrix containing stringers of crinoid and molluscan debris. Flank of phragmocone encrusted by oysters. Tape measure for scale. c. Complex of Thallassinoides and Diplocraterion burrows associated with conch that has been eroded out by wave action. A few 'Ghostly' fragments of ammonite are also present. Original scope of the image approximately 400 mm. c. Verically embedded conch with largely intact septa and camera infilled with burrowed matrix containing crinoid debris. Tape measure for scale.
Food limitation erodes the thermal tolerance of larvae in an ecologically influential marine herbivore
Open the record for dataset details and reuse information.
Crossing extreme habitat boundaries: Jack-of-all-trades facilitates invasion but is eroded by adaptation to a master-of-one
<ol> <li>The invasion of new environments can be a key instigator of adaptive diversification, but the likelihood of such invasions succeeding can depend on the attributes of would-be invaders. Chief among these seems to be a generalist or 'jack-off-all-trades' phenotype.</li> <li>Yet, despite the obvious link between habitat transitions and adaptation, we know surprisingly little about how phenotypes that might initially allow taxa to transition between habitats subsequently evolve or influence post-invasion differentiation.</li> <li>We tested how a generalist phenotype of a broad diet and behavioral plasticity in marine blenny fishes has facilitated the repeated invasion of extreme environments—particularly land—and how the conditions post-invasion have impacted that generalist phenotype and associated trophic morphology.</li> <li>Our data show that a wide diet and plasticity in being able to shift between environments freely has been instrumental in the progressive invasion of land by amphibious blennies. Once established, however, terrestrial blennies have experienced strong stabilising selection for a restricted diet, little to no plasticity and a highly specialised morphology. Instead of promoting diversification, the invasion of land appears to offer only a limited niche for survival, constraining descendent blennies to a specific adaptive phenotype.</li> <li>While our study supports the view that generalism facilitates invasion and that habitat transitions instigate adaptation, it also shows a generalist strategy is not optimal for successful establishment and new environments may offer fewer (not more) opportunities for diversification. This has broad implications for how taxa might be expected to respond or adapt to abrupt environmental change more generally.</li> </ol>
Data from: Direct effects of a non-native invader erode native plant fitness in the forest understory
1. The direct role of non-native plant invaders in driving negative population- and community-level processes of native species has been recently questioned. Addressing this controversy requires determining quantitatively if invaders negatively affect native population fitness. Because the invasion of non-natives often coincides with other anthropogenic stressors, experiments that partition the putative impact of non-natives from other known stressors and assess their potential synergies are required. While many studies have examined the effects of non-natives on components of native plant performance, studies that decompose the net fitness effects of non-natives from other anthropogenic stressors on population growth rate are lacking. 2. We used six years of detailed demographic data to parameterize a size-dependent integral projection model to examine the individual and combined effects of an allelochemical-producing invader (Alliaria petiolata) and an overabundant ungulate herbivore (Odocoileus virginianus) on the population dynamics of an understory perennial (Trillium erectum). 3. We show that Alliaria consistently and negatively affects the population dynamics of Trillium. Specifically, this invader reduces native population growth rate and alters the size distribution of the population at equilibrium. Alliaria also works in concert with the known negative impacts of overabundant white-tailed deer, illustrating the additive effects of anthropogenic stressors on native plant dynamics. 4. Synthesis. Alliaria's effects on vital rates differed in magnitude and sign across the native's lifecycle, highlighting the importance of detailed demographic analyses. Globally, our study provides novel empirical support for the claim that non-native invasive species can significantly and directly reduce the fitness of native plants.
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