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Figures 1–2 in Culicoides Latreille and Leptoconops Skuse biting midges of the southwestern United States with emphasis on the Canyonlands of southeastern Utah (Diptera: Ceratopogonidae)

Figures 1–2. Female lateral habitus (in alcohol). 1) Leptoconops (Holoconops) Kerteszi group. 2) Culicoides (Monoculicoides) sonorensis.

Figures 94–99 in Culicoides Latreille and Leptoconops Skuse biting midges of the southwestern United States with emphasis on the Canyonlands of southeastern Utah (Diptera: Ceratopogonidae)

Figures 94–99. Male genitalia of Culicoides, ventral view. Ventral apodeme of gonocoxite and apex of paramere circled on Fig. 94–96. 94) C. sublettei (Gillespie County, TX [FSCA]). 95) C. usingeri. 96) C. vetustus (San Bernardino County, CA [BM]). 97) C. posoensis (paratype, Kern County, CA [FSCA]). 98) C. kibunensis. 99) C. travisi (VA [FSCA]).

Figures 27–32. Female Leptoconops. 27 in Culicoides Latreille and Leptoconops Skuse biting midges of the southwestern United States with emphasis on the Canyonlands of southeastern Utah (Diptera: Ceratopogonidae)

Figures 27–32. Female Leptoconops. 27) L. knowltoni flagellomeres 9–11, median black seta (s). Spermathecae (sp), diverticulum (d), neck (spn). 28) L. foulki. 29) L. americanus. 30) L. sublettei flagellomeres 3–6, flagellomere 4 seta bases (sb), hyaline sensory seta (hss). Palpal segment 3. 31) L. sublettei. 32) L. foulki.

Figures 79–80 in Culicoides Latreille and Leptoconops Skuse biting midges of the southwestern United States with emphasis on the Canyonlands of southeastern Utah (Diptera: Ceratopogonidae)

Figures 79–80. Male genitalia of Culicoides, ventral view, basal arms of aedeagus (Aa), submedian lobe on paramere (Pml), ventral apodeme of gonocoxite (Gcva), distal spines of paramere (Pds). 79) C. mohave, apex of aedeagus circled (San Bernardino County, CA [FSCA]). 80) C. kettlei (Riverside County, CA [BM]).

Figures 37–40 in Culicoides Latreille and Leptoconops Skuse biting midges of the southwestern United States with emphasis on the Canyonlands of southeastern Utah (Diptera: Ceratopogonidae)

Figures 37–40. Male genitalia of Culicoides, ventral view focused on aedeagus. 37) C. hieroglyphicus, basal arms of aedeagus (Aa), tip of median process of aedeagus (At), gonostylus (Gs), sternite 9 caudal lobes (S9cl). 38) C. jamesi. 39) C. jacksoni, paramere shoulder (Ps), apodeme of gonocoxite (Gca) tooth (t), tip of median process of paramere (Pt). 40) C. tenuistylus, parameres (P) (Ventura County, CA).

Figures 50–55. 50 in Culicoides Latreille and Leptoconops Skuse biting midges of the southwestern United States with emphasis on the Canyonlands of southeastern Utah (Diptera: Ceratopogonidae)

Figures 50–55. 50) Culicoides sonorensis male wing. 51) C. occidentalis male wing. Spermathecae. 52) C. crepuscularis. 53) C. grandensis (paratype). 54) C. sonorensis. 55) C. sonorensis, lateral view (anterior to left) of female mesonotum showing prescutal pit (presct pit) and dark patches around seta bases.

opencc-by-4.0Jul 2018View details →

United Kingdom results from the monitoring of pesticide residues in food

This dataset contains the analytical results of pesticide residues measured in the food products analysed by the national competent authorities. Pesticide residues resulting from the use of plant protection products on crops that are used for food or feed production may pose a risk factor for public health. For this reason, a comprehensive legislative framework has been established in the European Union (EU), which defines rules for the approval of active substances used in plant protection products, the use of plant protection products and for pesticide residues in food. In order to ensure a high level of consumer protection, legal limits, so called “maximum residue levels” or briefly “MRLs”, are established in Regulation (EC) No 396/2005. EU-harmonised MRLs are set for all pesticides covering all types of food products. A default MRL of 0.01 mg/kg is applicable for pesticides not explicitly mentioned in the MRL legislation. Regulation (EC) No 396/2005 imposes on Member States the obligation to carry out controls to ensure that food placed on the market is compliant with the legal limits. A sample is considered free of quantifiable residues if the analytes were not present in concentrations at or above the limit of quantification (LOQ). The LOQ is the smallest concentration of an analyte that can be quantified with the analytical method used to analyse the sample. It is commonly defined as the minimum concentration of the analyte in the test sample that can be determined with acceptable precision and accuracy. If a sample contains quantifiable residues but within the legally permitted limit (maximum residue level, MRL), it is described as a sample  with quantified residue levels within the legal limits (below or at the MRL) A sample is considered non-compliant with the legal limit (MRL), if the measured residue concentrations clearly exceed the legal limits, taking into account the measurement uncertainty. It is current practice that the uncertainty of the analytical measurement is taken into account before legal or administrative sanctions are imposed on food business operators for infringement of the MRL legislation.   REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: MOPER_2020 - Chemicals Regulation Directorate, Health and Safety Executive MOPER_2019 - Chemicals Regulation Directorate, Health and Safety Executive MOPER_2018 - Chemicals Regulation Directorate, Health and Safety Executive MOPER_2017 - Chemicals Regulation Directorate, Health and Safety Executive MOPER_2016 - Chemicals Regulation Directorate, Health and Safety Executive MOPER_2015 - Chemicals Regulation Directorate, Health and Safety Executive MOPER_2014 - Chemicals Regulation Directorate, Health and Safety Executive MOPER_2013 - Chemicals Regulation Directorate, Health and Safety Executive MOPER_2012 - Chemicals Regulation Directorate, Health and Safety Executive MOPER_2011 - Chemicals Regulation Directorate, Health and Safety Executive   We are seeking feedback on our open data please complete the survey at the link below: https://ec.europa.eu/eusurvey/runner/9344dfa0-f384-cb72-65f6-6c187a6d0f14

Dataset for "WUS256: An Adjoint Waveform Tomography Model of the Crust and Upper Mantle of the Western United States for Improved Waveform Simulations"

This dataset contains the WUS256 seismic model and auxiliary data used in the creation of the model (Rodgers et al., 2022).  WUS256 is a three-dimensional model of the seismic properties of crust and upper mantle of the western United States.  The WUS256 model is provided in NetCDF format (readable by for example, xarray, Hoyer & Hamman, <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JB022930#jgrb55516-bib-0057">2017</a>) and HDF5 format for viewing with ParaView (Ahrens et al., <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JB022930#jgrb55516-bib-0002">2005</a>) and interaction with Salvus (Afanasiev et al., <a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JB022930#jgrb55516-bib-0001">2019</a>). Also included are the earthquake source parameters for the 72 inversion events and 18 validation events in ASCII text format.  Lastly, we include a list of all waveforms used in the creation of WUS256.  This is a simple ASCII file with the event name and receiver name (composed of the network_code and station_code). This effort was support by Lawrence Livermore National Laboratory’s Laboratory Directed Research and Development project 20-ERD-008.  This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-MI-833624

An ensemble of 48 perturbed-physics model (Noah-MP) estimates of the 1/8° runoff over the conterminous United States, 1980–2015

This dataset contains the 1980–2015 monthly evapotranspiration simulated by a 48-member perturbed-physics ensemble configured from the Noah LSM with multi-physics options (Noah‑MP v3.6). Simulation outputs include the surface and subsurface runoff. The file name has four parts: the variable collection, the used parameterization, the time scale, and the suffix. The 48 physics configurations are generated by combining four runoff parameterizations (run1: SIMGM, run2: SIMTOP, run3: NOAHR, run4: BATS), two parameterizations of stomatal conductance (can1: Ball–Berry, can2: Jarvis), three parameterizations of soil moisture stress factor (btr1:NOAHB, btr2: CLM, btr3: SSiB), and two parameterizations of near-surface atmospheric turbulence (tub1: M-O, tub2: Chen97). The simulation domain covers the all of conterminous United States (25°–53°N, 125°–67°W), which is also called the NLDAS-2 testbed (Xia et al., 2012a, b). The simulations were performed at a spatial resolution of 0.125°, which is the same as for NLDAS-2 models. Details of the simulation settings and spin-up run can be found in Section 2.3 of Zheng et al. (2019) and Section 2.2 of Fei et al. (2021).

An ensemble of 48 perturbed-physics model (Noah-MP) estimates of the 1/8° ET over the conterminous United States, 1980–2015

This dataset contains the 1980–2015 monthly evapotranspiration simulated by a 48-member perturbed-physics ensemble configured from the Noah LSM with multi-physics options (Noah‑MP v3.6). Simulation outputs include total evapotranspiration and its constituents (canopy evaporation, soil evaporation, and transpiration). The file name has four parts: the variable collection, the used parameterization, the time scale, and the suffix. The 48 physics configurations are generated by combining four runoff parameterizations (run1: SIMGM, run2: SIMTOP, run3: NOAHR, run4: BATS), two parameterizations of stomatal conductance (can1: Ball–Berry, can2: Jarvis), three parameterizations of soil moisture stress factor (btr1:NOAHB, btr2: CLM, btr3: SSiB), and two parameterizations of near-surface atmospheric turbulence (tub1: M-O, tub2: Chen97). The simulation domain covers the all of conterminous United States (25°–53°N, 125°–67°W), which is also called the NLDAS-2 testbed (Xia et al., 2012a, b). The simulations were performed at a spatial resolution of 0.125°, which is the same as for NLDAS-2 models. Details of the simulation settings and spin-up run can be found in Section 2.3 of Zheng et al. (2019) and Section 2.2 of Fei et al. (2021).

An ensemble of 48 perturbed-physics model (Noah-MP) estimates of the 1/8° terrestrial water storage over the conterminous United States, 1980–2015

This dataset contains the 1980–2015 monthly terrestrial water storage simulated by a 48-member perturbed-physics ensemble configured from the Noah LSM with multi-physics options (Noah‑MP v3.6). Simulation outputs include the total terrestrial water storage and its constituents (snow water equivalent, four-layer soil water content from the surface down to 2 m, and the groundwater storage anomaly). The file name has four parts: the variable collection, the used parameterization, the time scale, and the suffix. The 48 physics configurations are generated by combining four runoff parameterizations (run1: SIMGM, run2: SIMTOP, run3: NOAHR, run4: BATS), two parameterizations of stomatal conductance (can1: Ball–Berry, can2: Jarvis), three parameterizations of soil moisture stress factor (btr1:NOAHB, btr2: CLM, btr3: SSiB), and two parameterizations of near-surface atmospheric turbulence (tub1: M-O, tub2: Chen97). The simulation domain covers the all of conterminous United States (25°–53°N, 125°–67°W), which is also called the NLDAS-2 testbed (Xia et al., 2012a, b). The simulations were performed at a spatial resolution of 0.125°, which is the same as for NLDAS-2 models. Details of the simulation settings and spin-up run can be found in Section 2.3 of Zheng et al. (2019) and Section 2.2 of Fei et al. (2021).

FIG. 3 in First occurrences of Palaeogale von Meyer, 1846 in the Pacific Northwest, United States

FIG. 3. — Dentaries of Palaeogale dorothiae MacDonald, 1963: A, lingual view (JODA 6177); B, occlusal view (JODA 6177); C, buccal view (JODA 6177); D, lingual view (JODA 5893); E, occlusal view (JODA 5893); F, buccal view (JODA 5893). Scale bars: 1 cm.

FIG. 2 in First occurrences of Palaeogale von Meyer, 1846 in the Pacific Northwest, United States

FIG. 2. — Skull of Palaeogale sp. (JODA 13221): A, dorsal view; B, ventral view; C, left lateral view; D, right lateral view. Scale bars: 1 cm.

FIG. 1 in First occurrences of Palaeogale von Meyer, 1846 in the Pacific Northwest, United States

FIG. 1. — Map of distributions of North American Palaeogale von Meyer, 1846 specimens both published and from museum records. Localities are colour coded by North American Land Mammal Age. Black shaded area represents Oregon. Distribution data downloaded from Paleobiology Database (https://paleobiodb. org/) and iDigBio (https://www.idigbio.org/) on 23 April 2020. The Texas occurrence is reported in Albright (1996).

FIG. 4 in First occurrences of Palaeogale von Meyer, 1846 in the Pacific Northwest, United States

FIG. 4. — Bivariate plot of anterior-posterior length (APL) and transverse width (TW) of Palaeogale carnassials: A, upper fourth premolar (P4); B, lower first molar (m1). Points are colour coded by species and labelled with their specimen numbers. All measurements are in mm and can be found in Tables 1 and 2.

dryad40/100

Flows of invasive ants worldwide to the United States

International trade and human movements have accidentally transported thousands of species worldwide at an unprecedented scale. The resulting biological invasions are among the greatest drivers of species extinctions and can cause enormous economic losses. Understanding how globalization affects the accidental transport of species is urgent to prevent new invasions. However, global trade networks have had mixed success so far in explaining intercontinental species movements. Here, we show that commonly used proxies of global trade flows such as general imports and agricultural imports differed greatly from flows of alien ants from their donor regions to the United States. The analysis of 97 individual commodity flows revealed instead that plants and fruit imports, which are a small subset of all agricultural commodities, were associated with invasion flows. All 95 other commodities differed from flows of alien ants, including most "agricultural" commodities which had extremely heterogenous geographic origins. This highlights the need to know precisely which commodities serve as introduction pathways for a particular taxonomic group in order to explain invasion flows and identify likely source regions of future invasions in a world of changing trade relationships.

Sequencing data of RNA editing, RNA modifications, and transcriptional units in Listeria monocytogenes

Sequencing data for "RNA editing, RNA modifications, and transcriptional units in Listeria monocytogenes" manuscript, which is submitted to BMC genomics.

MD simulation of the crystal unit cell of the second PDZ domain of LNX2 protein

This molecular dynamics simulation data is provided as part of the manuscript  "LAWS: Local Alignment for Water Sites - a method to analyze crystallographic water in simulations". The code for the algorithm is provided: <a href="https://github.com/rauscher-lab/LAWS">on github</a> The system contains one unit cell of the crystal (PDB ID: 5E11) with 4 symmetrically related protein chains. The total simulation length is 1 microsecond.  Force field + water model: CHARMM36m + CHARMM-modified TIP3P Number of atoms: 9650 Number of time frames:  100,000 with 10-ps stride The details of the simulations are provided in the manuscript.

Figs 11–24 in Soft-winged flower beetles (Coleoptera: Malachiidae) of the United Arab Emirates

Figs 11–24. Tonycolotes kovari (Švihla, 1987) gen. et. comb. nov., ♂ (SCH_ISEA). 11. External appearance, dorsal view. 12. External appearance, lateral view. 13. Head and pronotum, subdorsal view. 14. Head and pronotum, dorsal view. 15. Right antenna. 16–18. Scapus in different positions. 19. Left palp. 20. Left anterior leg. 21. Pygidium. 22. Ultimate abdominal ventrite. 23. Aedeagus, lateral view. 24. Tegmen. Scale bars: 0.5 mm.

Figs 1–10 in Soft-winged flower beetles (Coleoptera: Malachiidae) of the United Arab Emirates

Figs 1–10. Tonyattalus vanharteni gen. et sp. nov., holotype (SCH_ISEA_000133), ♂ (1–8), ♀ (9– 10). 1, 9. External appearance, dorsal view. 2, 10. External appearance, lateral view. 3. Left antenna. 4. Head and pronotum, dorsal view. 5. Left anterior tarsus. 6. Pygidium. 7. Ultimate abdominal ventrite. 8. Aedeagus, and tegmen, lateral view. Scale bars: 0.5 mm.