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FIGURES 37–46. Tephritis ochroptera new species 37 in Revision of species of the genus Tephritis Latreille 1804 (Diptera: Tephritidae) with entire apical spot
FIGURES 37–46. Tephritis ochroptera new species 37. Total view, holotype Ƥ. 38. Wing, paratype Ƥ 39. Epandrium and hypandrium, lateral right view. 40. Same, posterior view. 41. Glans of phallus, lateral. 42. Ejaculatory apodeme. 43. Male abdomen, dissected, dorsal view. 44. Aculeus, ventral view. 45. Apex of oviscape and eversible membrane, ventral view. 46. Spermathecae.
FIGURES 47–51. Tephritis robusta new species 47 in Revision of species of the genus Tephritis Latreille 1804 (Diptera: Tephritidae) with entire apical spot
FIGURES 47–51. Tephritis robusta new species 47. Total view, paratype Ƥ. 48. Wing. 49. Spermathecae. 50. Aculeus, ventral view. 51. Apex of oviscape and eversible membrane, ventral view.
FIGURES 22–31. Tephritis cameo new species 22 in Revision of species of the genus Tephritis Latreille 1804 (Diptera: Tephritidae) with entire apical spot
FIGURES 22–31. Tephritis cameo new species 22. Total view, holotype Ƥ. 23–26. Wing (23, holotype, 24, paratype from Kyrgyzstan, Talas, 25, paratype from Afghanistan, Bande-Amir, 26, paratype from Iran, Kerman). 27. Epandrium, posterior view. 28. Glans of phallus, lateral. 29. Apex of oviscape and eversible membrane, ventral view. 30. Aculeus, ventral view. 31. Spermatheca (one of the two). Wing crossbands: D—discal; M—medial; PA—preapical; A—apical. S—shoulder of aculeus.
FIGURES 17–21. Tephritis angulatofasciata. 17 in Revision of species of the genus Tephritis Latreille 1804 (Diptera: Tephritidae) with entire apical spot
FIGURES 17–21. Tephritis angulatofasciata. 17. Total view, Ƥ (Iran Khorassan). 18. Wing, lectotype Ƥ (Iran: Shah-Khuh). 19. Aculeus, ventral view. 20. Apex of oviscape and eversible membrane, ventral view. 21. Spermathecae. Wing crossbands: D—discal; M—medial; PA—preapical; A—apical.
FIGURES 32–36. Tephritis gladius new species 32. Total view, paratype 3. 33. Wing. 34. Aculeus, ventral view. 35 in Revision of species of the genus Tephritis Latreille 1804 (Diptera: Tephritidae) with entire apical spot
FIGURES 32–36. Tephritis gladius new species 32. Total view, paratype 3. 33. Wing. 34. Aculeus, ventral view. 35. Apex of oviscape and eversible membrane, ventral view. 36. Spermathecae. Wing crossbands: D—discal; M—medial; PA—preapical; A—apical.
FIGURES 6–16. Tephritis afrostriata new species 6. Total view, paratype 3. 7. Wing. 8 in Revision of species of the genus Tephritis Latreille 1804 (Diptera: Tephritidae) with entire apical spot
FIGURES 6–16. Tephritis afrostriata new species 6. Total view, paratype 3. 7. Wing. 8. Glans of phallus, lateral. 9. Epandrium and hypandrium, lateral right view. 10. Epandrium, posterior view. 11. Abdomen, dissected, dorsal view. 12. Ejaculatory apodeme. 13. Aculeus, ventral view. 14. Same, apex. 15. Apex of oviscape and eversible membrane, ventral view. 16. Spermatheca (one of the two).
FIGURES 56–65. Tephritis tatarica. 56 in Revision of species of the genus Tephritis Latreille 1804 (Diptera: Tephritidae) with entire apical spot
FIGURES 56–65. Tephritis tatarica. 56. Total view, Ƥ. 57. Wing, lectotype Ƥ. 58. Epandrium and hypandrium, lateral right view. 59. Same, posterior view. 60. Glans of phallus, lateral. 61. Ejaculatory apodeme. 62. Aculeus, ventral view. 63. Same, apex. 64. Apex of oviscape and eversible membrane, ventral view.65. Spermathecae.
FIGURES 1–5. Tephritis admissa. 1 in Revision of species of the genus Tephritis Latreille 1804 (Diptera: Tephritidae) with entire apical spot
FIGURES 1–5. Tephritis admissa. 1. Total view Ƥ. 2. Wing. 3. Aculeus, ventral view. 4. Apex of oviscape and eversible membrane, ventral view. 5. Spermatheca.
Predator biomass, prey biomass landcover and climate data from spotted hyaena and lion sites in Africa
<p class="Thesisnormal">The spotted hyaena (<i>Crocuta crocuta</i> Erxleben) and the lion (<i>Panthera leo</i> Linnaeus) are two of the most abundant and charismatic large mammalian carnivores in Africa and yet both are experiencing declining populations and significant pressures from environmental change. However, with few exceptions, most studies have focused on influences upon spotted hyaena and lion populations within individual sites, rather than synthesising data from multiple locations. This has impeded the identification of over-arching trends behind the changing biomass of these large predators.</p> <p class="Thesisnormal">Using Partial Least Squares regression models, influences upon population biomass were therefore investigated, focusing upon prey biomass, temperature, precipitation and vegetation cover. Additionally, as both species are in competition with one other for food, the influence of competition and evidence of environmental partitioning were assessed.</p> <p class="Thesisnormal">Our results indicate that spotted hyaena<i> </i>biomass is more strongly influenced by environmental conditions than lion, with larger hyaena populations in areas with warmer winters, cooler summers, less drought and more semi-open vegetation cover.</p> <p class="Thesisnormal">Competition was found to have a negligible influence upon spotted hyaena and lion populations, and environmental partitioning is suggested, with spotted hyaena population biomass greater in areas with more semi-open vegetation cover. Moreover, spotted hyaena is most heavily influenced by the availability of medium-sized prey biomass, whereas lion is influenced more by large size prey biomass. Given the influences identified upon spotted hyaena populations in particular, the results of this study could be used to highlight populations potentially at greatest risk of decline, such as in areas with warming summers and increasingly arid conditions.</p>
Processing steps to generate a Digital Surface Model based on SPOT-7 tri-stereo images published in the study "An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar inundation areas at volcan Copahue (Argentina & Chile)" in the Journal of South American Earth Sciences https://doi.org/10.1016/j.jsames.2022.104138
<p>The Digital Surface Model (DSM) was created from SPOT-7 tri-stereo images for the Copahue volcano between the border of Argentina and Chile. Two versions of the DSM are provided: an unfiltered product and a final, filtered product. The final product has a spatial resolution of 5-m and was used for lahar inundation modeling for the Copahue volcano (Viotto, Toyos, and Bookhagen 2022, <a href="https://doi.org/10.1016/j.jsames.2022.104138">https://doi.org/10.1016/j.jsames.2022.104138</a> : An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar hazard inundation at Volcán Copahue (Argentina & Chile). <em>Journal of South American Earth Sciences</em> ). The dataset provided should be cited together with the article. </p> <p><strong>DSM processing </strong></p> <p>The source images were given by a SPOT-7 snow- and cloud-free triplet (Nadir, Backward and Forward) of 1.5 m spatial resolution from 19 April 2018 (SPOT Image, Airbus Defence and Space GmbH, distributed by CONAE; Dataset ID: <em>SEN_SPOT7_20180419_142955500_000</em>, delivered by CONAE as <em>DS_SPOT7_20180419</em>).</p> <p>The data were processed with the suite of digital photogrammetry tools AMES Stereo Pipeline ASP (Beyer et al., 2018). The procedure for the generation of the DSM is summarized by following steps: </p> <ol> <li> <p>The orbital parameters (RCP models) were adjusted using the bundle adjustment tool with no ground control points, since they were unavailable.</p> </li> <li> <p>The scenes were map-projected onto the NASADEM (spatial resolution of 30 m) elevation dataset, assisted by the results of the orbital adjustment in Step 1.</p> </li> <li>The stereo correlation of the map-projected scenes including the results of the adjusted orbital parameters, was performed three times, using as first scene (i.e., primary image) the nadir (N), backward (B), and forward (F) images . In each run, the order of images to perform the stereo correlation was: N-F-B, F-N-B, and B-N-F. Thus, three point clouds were generated. Specific ASP correlator settings (other than defaults parameters; for details see the provided stereo-default file) were set in the following way: <em>Correlation Kernel</em>: 15 x 15 pixels; <em>Sub-pixel Refinement Kernel</em>: 21 x 21 pixels; <em>Subpixel Refinement Mode</em>: 2 (Weighted Affine Adaptive Window Correlator EM)</li> <li> <p>The three point clouds were merged into one point cloud with a regular grid of 5 m (unfiltered product, known as <em>DSM_Copahue_UTM19S_WGS84_5m_raw.tif</em>).</p> </li> </ol> <p>The quality of the final point cloud was assessed by comparing the unfiltered DSM with a spatial resolution of 12-m against the WorldDEM<sup>TM</sup> elevation dataset (Collins et al., 2015). The WorldDEM was provided by Airbus Defence and Space GmbH under license for the scope of the Viotto et al., 2022 study. The comparison of the pixel-to-pixel heights above the ellipsoid (WGS84) between the two datasets resulted in a mean difference of 0.67 m and a standard deviation of +/- 4.82 m. </p> <p>Comprehensive details on the methodologies evaluated to create the dataset with ASP, can be found in the corresponding master's thesis “Topografía digital y modelado de lahares en el Volcán Copahue, Argentina-Chile” from S. Viotto (link: https://rdu.unc.edu.ar/handle/11086/15384). Recommended literature about processing DEMs from SPOT imagery is given by Mueting et al., 2021 (<a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JF006330">https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JF006330</a>). </p> <p><strong>Creation of the Final, Filtered DSM product</strong></p> <p>The corrections and improvements applied to the unfiltered product to create the final, filtered DSM (named DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif) are summarized by following steps. </p> <p> </p> <ol> <li> <p><em>Water Bodies Delineation</em></p> </li> </ol> <p>The delineation of the water bodies was based on a mask created from the free access water bodies datasets provided by the Instituto Geográfico Nacional of Argentina (<a href="https://www.ign.gob.ar/NuestrasActividades/InformacionGeoespacial/CapasSIG">https://www.ign.gob.ar/ NuestrasActividades/InformacionGeoespacia l/CapasSIG</a>) and by the Ministerio de Bienes Nacionales in Chile ( <a href="https://www.ide.cl/index.php/aguas-continentales/item/1508-catastro-de-lagos">https://www.ide.cl/index.php /aguas-continentales/item/1508-catastro-de-lagos</a>). A total of 45 lakes within the area of interest were considered. Lakes with areas below or equal to 25 m2 were smoothed with a median filter in the last step. Lakes with areas above this threshold were filled in with a constant value and their borders were smoothed with a median filter to provide smooth shorelines.</p> <p><em>2 . Void Filling</em></p> <p>Voids (other than water bodies) were filled with the tool “Close Gaps” from Saga GIS software. </p> <p><em>3. Smoothing</em></p> <p>Finally, the elevation dataset was smoothed with a median filter using a 3 x 3 pixel window, excluding water bodies filled in the step 1. </p> <p><strong>Final Remarks and Suggestion</strong></p> <p>The quality assessment of the final version by visual inspection of the hillshades suggested an improvement of the signal to noise ratio. However, the void filling process may be improved.</p> <p><br> </p> <p><strong>Dataset Description</strong></p> <table align="center"> <caption> </caption> <tbody> <tr> <td>Digital Surface Models</td> <td> <p>No Data Value = -9999</p> <p>Format = float 32 bit</p> <p>File Format = GeoTiff</p> <p>Vertical Datum: WGS84</p> <p>Projection information: EPSG 32719 (UTM19S)</p> <p>Spatial Resolution: 5m (subfix: <em>_5m</em>) </p> <p>Versions: </p> <ul> <li> <p>Unfiltered product: without corrections <em>DSM_Copahue_UTM19S_WGS84_5m_raw.tif</em></p> </li> <li> <p>Final, filtered product: smoothed and void filled <em>DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif</em></p> </li> </ul> </td> </tr> <tr> <td>Water Bodies Mask</td> <td> <p>No Lake Value = 0</p> <p>Lakes Values = 1 to 45</p> <p>File Format= GeoTiff</p> <p>Spatial Resolution: 5m (subfix: <em>_5m</em>)</p> <p>Projection information : EPSG 32719 (UTM19S)</p> <p><em>WB_mask_5m_UTM19S.tif</em></p> </td> </tr> </tbody> </table> <p> </p> <p> </p> <p><strong>Repository structure</strong></p> <p>|__ 01_Scripts</p> <p> |+ run21_CopahueDSM_AMES_sviotto.sh</p> <p> |+ stereo.default</p> <p>|__ 02_DSMs</p> <p> |+ DSM_Copahue_UTM19S_WGS84_5m_raw.tif</p> <p> |+ DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif</p> <p> |+ WB_mask_5m_UTM19S.tif</p> <p><strong>References</strong></p> <p>Beyer, R. A., Alexandrov, O., & McMichael, S. (2018). The Ames Stereo Pipeline: NASA's open source software for deriving and processing terrain data. <em>Earth and Space Science</em>, 5, 537– 548. <a href="https://doi.org/10.1029/2018EA000409">https://doi.org/10.1029/2018EA000409</a></p> <p>Collins, J., Riegler, G., Schrader, H., Tinz, M., 2015. Applying terrain and hydrological editing to TanDEM-X data to create a consumer-ready worlddem product. Int. Arch. Photogram. Rem. Sens. Spatial Inf. Sci. 40 (7), 1149. https://doi.org/10.5194/isprsarchives-XL-7-W3-1149-2015.</p> <p>Mueting, A., Bookhagen, B., & Strecker, M. R. (2021). Identification of debris-flow channels using high-resolution topographic data: A case study in the Quebrada del Toro, NW Argentina. <em>Journal of Geophysical Research: Earth Surface</em>, 126, e2021JF006330. <a href="https://doi.org/10.1029/2021JF006330">https://doi.org/10.1029/2021JF006330</a></p> <p>Viotto, S., Toyos, G., & Bookhagen, B. (2022). An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar hazard inundation at volcán copahue (Argentina & Chile). Journal of South American Earth Sciences, 104138. https://doi.org/10.1016/j.jsames.2022.104138</p> <p> </p> <p> </p>
FIG. 3 in A Long-term Demographic Study of a Spotted Salamander (Ambŋstoma maculatum) Population in Central Ohio
FIG. 3.—Relationships between percent mass loss and number of days spent in Taylor–Ochs Pond, Ohio, for individually marked female (R2 ¼ 0.57, P ¼ 0.001; y ¼ 1.25x þ 6.76) and male (R2 ¼ 0.18, P ¼ 0.001, y ¼ 0.29x þ 3.39) Ambŋstoma maculatum sampled from 2005 to 2014.
F. 1 in A Long-term Demographic Study of a Spotted Salamander (Ambŋstoma maculatum) Population in Central Ohio
F. 1.—Numbers of (a) breeding Ambŋstoma maculatum adults (R2 ¼ IG 0.46, P ¼ 0.03), (b) split by sex (females, R2 ¼ 0.02, P ¼ 0.67; males, R2 ¼ 0.68, P ¼ 0.003), and (c) counts of breeding females plotted alongside egg mass counts and numbers of emerging juveniles from 2005 to 2014 in Taylor–Ochs Pond, Ohio. Numbers near the bottom of (b) reflect sex ratios (male:female), and numbers near the bottom of (c) reflect recruitment rates (emerging juveniles per breeding female) for each year. Significant negative linear relationships of overall breeding adults (a) and breeding males (b) over time are represented by the equations y ¼ 46.1x þ 93246.0 and y ¼ 41.6x þ 84148.9, respectively.
FIG. 2 in A Long-term Demographic Study of a Spotted Salamander (Ambŋstoma maculatum) Population in Central Ohio
FIG. 2.—Mean values (±1 SE) for mass (a) and snout–vent length (SVL, b) of inbound female and male Ambŋstoma maculatum sampled from 2005 to 2014 in Taylor–Ochs Pond, Ohio. See Table 3 for the sample size contributing to each depicted value. In all years, for both body-size indicators, females were larger than males (P <0.05). For simplicity, only differences among years (sexes combined) are reflected by different letter(s) above each pair of bars.
Spot_fare_Inspections_Experiments
<p>In this repository you will find the data and codes used for all the experiments, generation of tables and graphs of the publication and .</p>
The genetic basis of wing spots in Pieris canidia butterflies
<p>Spots in pierid butterflies and eyespots in nymphalid butterflies are likely non-homologous wing colour pattern elements, yet they share a few features in common. Both develop black scales that depend on the function of the gene spalt, and both might have central signalling cells. This suggests that both pattern elements may be sharing common genetic circuitry. Hundreds of genes have already been associated with the development of nymphalid butterfly eyespot patterns, but the genetic basis of the simpler spot patterns on the wings of pierid butterflies has not been investigated. To facilitate studies of pierid wing patterns, we report a high-quality draft genome assembly for <em>Pieris canidia,</em> the Indian cabbage white. We then conducted transcriptomic analyses of pupal wing tissues sampled from the spot and non-spot regions of <em>P. canidia</em> at 3-6h post-pupation. A total of 1,352 genes were differentially regulated between wing tissues with and without the black spot, including <em>spalt</em>, <em>Krüppel-like factor 10</em>, genes from the Toll, Notch, TGF-β, and FGFR signalling pathways, and several genes involved in the melanin biosynthetic pathway. We identified 21 genes that are up-regulated in both pierid spots and nymphalid eyespots and propose that spots and eyespots share regulatory modules despite their likely independent origins.</p>
FIG. 1 in Habitat Usage, Dietary Niche Overlap, and Potential Partitioning between the Endangered Spotted Turtle (Clemmys guttata) and Other Turtle Species
FIG. 1. The path analysis shows the relationship between habitat parameters associated with PC1 (which was strongly positively loaded with salinity, depth, dissolved O2, canopy cover, and pH) and three turtle species: Chrysemys picta, Kinosternon subrubrum, and Clemmys guttata on the Atlantic Coastal Plain. The solid and dashed lines represent direct and indirect effects, respectively, and black lines indicate positive effects while gray lines indicate negative effects. The numbers associated with each line represent the direction and magnitude of each effect, with the strength of the interaction increasing as the values approach 1.
FIG. 2 in Habitat Usage, Dietary Niche Overlap, and Potential Partitioning between the Endangered Spotted Turtle (Clemmys guttata) and Other Turtle Species
FIG. 2. Biplots of d15N and d13C for four turtle species at all sites with ellipses around each species (filled squares/solid black line ¼ Kinosternon subrubrum, filled triangles/solid gray line ¼ Chrysemys picta, open circles/gray dashed line¼ Chelydra serpentina, filled diamonds/ lack dashed line ¼ Clemmys guttata). There is a large overlap in isotopic compositions for all species, resulting in no significant differences in isotopic niche space between species (see text).
FIG. 3 in Habitat Usage, Dietary Niche Overlap, and Potential Partitioning between the Endangered Spotted Turtle (Clemmys guttata) and Other Turtle Species
FIG. 3. Bivariate SIBER (Stable Isotope Bayesian Ellipses in R) plots of ellipses estimating isotopic niche based on the d13C and d15N compositions with all species, excluding C. serpentina. The black circles represent the mode, while the three ellipses from the center outwards show where 50%, 75%, and 95% of the data lie, respectively. The numbers indicate the site numbers, while the letter codes indicate species names (MUDT ¼ Kinosternon subrubrum, PATU ¼ Chrysemys picta, SPTU ¼ Clemmys guttata). Together, these bivariate data of the isotopic compositions create ellipses which represent the relative sizes of the isotopic niche of each turtle species at all of our sites on the Atlantic Coastal Plain. Despite the lack of any significant differences in isotopic niche, these ellipses allow us to see some degree of niche overlap among C. guttata at all sites.
FIG. 3. A in A Successful Reintroduction of Columbia Spotted Frog (Rana luteiventris) through Repatriation of Recently Hatched Larvae
FIG. 3. A satellite image and the approximate locations of CSF egg mass deposition locations at the Taylors Fork repatriation site.
FIG. 1 in A Successful Reintroduction of Columbia Spotted Frog (Rana luteiventris) through Repatriation of Recently Hatched Larvae
FIG. 1. Location of Taylors Fork CSF repatriation site and North Fork (CSF donor site) in the United States Uinta-Wasatch-Cache National Forest, Utah, including the location of historic CSF locations in the Weber River watershed.
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