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FIGURES 12–19 in Taxonomic synopsis of Notiospathius Matthews & Marsh, 1973 (Hymenoptera: Braconidae) from Colombia

FIGURES 12–19. Quantitative characters: 12) first tergum width (1tw), 13) basal sternal plate length (bsp), 14) first tergum length (1tl), 15) ovipositor length/ first tergum length ratio (ol/1tl), 16) hind coxa length/ hind femur length (hcxl/hfl), 17) ovipositor length/metasoma length ratio (ol/mtl), 18) fore wing veins, and 19) hind wing veins.

FIGURE 20 in Taxonomic synopsis of Notiospathius Matthews & Marsh, 1973 (Hymenoptera: Braconidae) from Colombia

FIGURE 20. Projection of the 24 quantitative characters on the first two components of a principal components analysis. Characters within squares indicate redundant information content (see text for details and table 1 for variables names).

FIGURES 34–36 in Taxonomic synopsis of Notiospathius Matthews & Marsh, 1973 (Hymenoptera: Braconidae) from Colombia

FIGURES 34–36. Characters of the wings for genus Notiospathius: 34) fore wing wing veins, 35) hind wing veins, and 36) fore wing cells.

FIGURES 1–11 in Taxonomic synopsis of Notiospathius Matthews & Marsh, 1973 (Hymenoptera: Braconidae) from Colombia

FIGURES 1–11. Quantitative characters: 1) scape length/first flagellomere length (sl/ff), 2) head height/width in frontal view ratio (hh/hw), 3) eye length/width in lateral view ratio (el/ew), 4) ocell-ocular distance/ocellar diameter ratio (ocod/ocd), 5) face minimum width/maximum width ratio (fiw/faw), 6) temple length/eye length in dorsal view ratio (tl/eld), 7) malar space length/ eye length in lateral view ratio (msl/el), 8) malar space length/mandible width basally ratio (msl/mwb), 9) supraclypeal area/supra-antennal area (sca/saa), 10) precoxal sulcus length/mesopleuron length (pxs/ml), and 11) fore wing length/width ratio (fwl/fww).

FIGURES 22–27. Notiospathius ugaldei and N. columbianus holotypes. N in Taxonomic synopsis of Notiospathius Matthews & Marsh, 1973 (Hymenoptera: Braconidae) from Colombia

FIGURES 22–27. Notiospathius ugaldei and N. columbianus holotypes. N. ugaldei: 22) habitus, 24) head in anterior view, and 26) mesosoma in lateral view. N. columbianus: 23) habitus, 25) head in anterior view, and 27) mesosoma in lateral-ventral view. Scale bar: 1 mm.

FIGURE 21 in Taxonomic synopsis of Notiospathius Matthews & Marsh, 1973 (Hymenoptera: Braconidae) from Colombia

FIGURE 21. Principal components analysis: projection of specimens of Notiospathius badius (spb) and N. rugonotum (spr) in the first two components.

FIGURE 6 in The marsh crab, Sartoriana rokitanskyi (Pretzmann, 1971) (Decapoda, Brachyura, Gecarcinucidae) from southern Iran

FIGURE 6. Carapace width and frequency relationships for males and females of Sartoriana rokitanskyi.

FIGURE 4. Left gonopods. A–C in The marsh crab, Sartoriana rokitanskyi (Pretzmann, 1971) (Decapoda, Brachyura, Gecarcinucidae) from southern Iran

FIGURE 4. Left gonopods. A–C, Sartoriana rokitanskyi (Pretzmann, 1971), male (28.2 × 21.8 mm) (ZRC), Rudan, Iran; D–F, Sartoriana blanfordi (Alcock, 1909), male (35.3 × 26.9 mm) (ZRC), Punjgoor, Beluchistan, Pakistan. A, D, ventral views of G1s; B, E, dorsal views of G1s; C, F, G2s. Scales = 1.0 mm.

FIGURE 2 in The marsh crab, Sartoriana rokitanskyi (Pretzmann, 1971) (Decapoda, Brachyura, Gecarcinucidae) from southern Iran

FIGURE 2. Sartoriana blanfordi (Alcock, 1909). Male (35.3 × 26.9 mm) (ZRC), Punjgoor, Beluchistan, Pakistan. A, overall dorsal view; B, frontal carapace view; C, ventral sternal view.

FIGURE 1 in The marsh crab, Sartoriana rokitanskyi (Pretzmann, 1971) (Decapoda, Brachyura, Gecarcinucidae) from southern Iran

FIGURE 1. Sartoriana rokitanskyi (Pretzmann, 1971). Male (28.2 × 21.8 mm) (ZRC), Rudan, Iran. A, overall dorsal view; B, frontal carapace view; C, ventral sternal view.

FIGURE 3 in The marsh crab, Sartoriana rokitanskyi (Pretzmann, 1971) (Decapoda, Brachyura, Gecarcinucidae) from southern Iran

FIGURE 3. Outer views of chelae. A, Sartoriana rokitanskyi (Pretzmann, 1971), male (28.2 × 21.8 mm) (ZRC), Rudan, Iran; B, Sartoriana blanfordi (Alcock, 1909), male (35.3 × 26.9 mm) (ZRC), Punjgoor, Beluchistan, Pakistan.

opencc-by-4.0Aug 2024View details →

Data analysis scripts for Marsh et al. 2024 'Tropical forest clearance impacts biodiversity and function whereas logging changes structure'

<p>Data analysis scripts for the manuscript <strong>Marsh<em> </em>et<em> </em>al. 2024 'Tropical forest clearance impacts biodiversity and function whereas logging changes structure'</strong></p> <p><strong>Update for Version 2:</strong> The calculation of confidence intervals around the mean effects in Figure 2 has been updated to use the <code>marginaleffects</code> package (many thanks to Biao Wang and Shuang Zhang for pointing out an error in the original code). Using the Satterthwaite method for determining degrees of freedom, the updated confidence intervals are around 32% smaller than our original estimates (MLF = 32.0%, HLF = 32.1%, OP = 21.6%). Note, this change is only relevant to fig. 2 and figs. S2-4; the mean effect sizes and trends along the disturbance gradient, all statistical comparisons, and the constrast analyses in fig. 3 remain unaffected. The updated figures S2-4 and Table S6 can be seen in the file 'Updated figures S2-4 with recalculated confidence intervals.pdf'.</p> <p>In the zip file 'BALI_synthesis_analysis.zip' there are outputs from RMarkdown scripts that include all steps of the analysis for each dataset, including R code, incorporating data visualisation, exploration and standardisation, model building and evaluation, and visualisation of results. Fig. 2b can be regenerated using code in the zip file 'Marsh_etal_2024_Science_fig1b_chm_and_canopy_profiles-main.zip'.</p> <p>Each dataset presented in the manuscript has an html file within the folder 'Analyses'. For datasets involving bat, bird, dung beetle and tree traits additional markdown documents are available for steps take during data preparation in the folder 'Data preparation'.</p> <p>In the zip file 'BALI_synthesis_data.zip' are .rds data files that have been cleaned, prepared and z-score standardised following the procedures outlined in the respective markdown files.</p> <p>To repeat any given analysis, follow the respective rmarkdown document, excluding the data manipulation steps:</p> <ol> <li>Read in the data file as described above: dd <- readRDS(paste0("path/to/rds/file/", "name_of_file.rds"))</li> <li>Run the code at the top of the markdown workflow (sections "Data information" and "Load in necessary libraries")</li> <li>Do not run the sections "Read in data" through to "Visual inspection of the data"</li> <li>Continue the analysis from the 'Modelling' section</li> </ol> <div> <h3> </h3> <h3>Level 1 - Structure & Environment</h3> </div> <table> <tbody> <tr> <th>Dataset</th> <th>Label</th> <th>Filename</th> <th>Collector</th> </tr> </tbody> <tbody> <tr> <td>Above-ground carbon</td> <td>Above ground carbon</td> <td>Above_ground_carbon</td> <td>Terhi Riutta</td> </tr> <tr> <td>Leaf-area index</td> <td>Leaf-area index</td> <td>Leaf_area_index</td> <td>Terhi Riutta</td> </tr> <tr> <td>Soil temperature</td> <td>Soil temp.</td> <td>Soil_temperature</td> <td>Terhi Riutta</td> </tr> <tr> <td>Soil moisture</td> <td>Soil moisture</td> <td>Soil_moisture</td> <td>Dafydd Elias</td> </tr> <tr> <td>Air temperature: Minimum</td> <td>Air temp.: Min.</td> <td>Air_temperature_minimum</td> <td>Benjamin Blonder</td> </tr> <tr> <td>Air temperature: Mean</td> <td>Air temp.: Mean</td> <td>Air_temperature_mean</td> <td>Benjamin Blonder</td> </tr> <tr> <td>Air temperature: Maximum</td> <td>Air temp.: Max.</td> <td>Air_temperature_maximum</td> <td>Benjamin Blonder</td> </tr> <tr> <td>Soil bulk density</td> <td>Soil bulk density</td> <td>Soil_bulk_density</td> <td>Dafydd Elias</td> </tr> <tr> <td>Soil horizon depth</td> <td>Soil horizon depth</td> <td>Soil_horizon_depth</td> <td>Dafydd Elias</td> </tr> <tr> <td>Soil pH</td> <td>Soil pH</td> <td>Soil_pH</td> <td>Dafydd Elias</td> </tr> <tr> <td>Soil nutrients: Carbon</td> <td>Soil nutrients (C)</td> <td>Soil_nutrients_C</td> <td>Dafydd Elias</td> </tr> <tr> <td>Soil nutrients: Nitrogen</td> <td>Soil nutrients (N)</td> <td>Soil_nutrients_N</td> <td>Dafydd Elias</td> </tr> <tr> <td>Soil nutrients: Inorganic Phosporous</td> <td>Soil nutrients (Inorganic P)</td> <td>Soil_nutrients_Inorganic_P</td> <td>Dafydd Elias</td> </tr> <tr> <td>Soil nutrients: Carbon:Phosphorous</td> <td>Soil nutrients (C:P)</td> <td>Soil_nutrients_C_P</td> <td>Dafydd Elias</td> </tr> <tr> <td>Soil nutrients: Carbon:Nitrogen</td> <td>Soil nutrients (C:N)</td> <td>Soil_nutrients_C_N</td> <td>Dafydd Elias</td> </tr> </tbody> </table> <div> <h3> </h3> <h3>Level 2 - Tree traits</h3> </div> <p>All tree traits were collected as part of the following study (details in this table have been extracted from table S1 of that publication): S. Both, T. Riutta, C.E.T. Paine, D.M.O. Elias, R.S. Cruz, A. Jain, D. Johnson, U.H. Kritzler, M. Kuntz, N. Majalap-Lee, N. Mielke, M.X. Montoya Pillco, N.J. Ostle, Y. Arn Teh, Y. Malhi, D.F.R.P. Burslem (2019) Logging and soil nutrients independently explain plant trait expression in tropical forests. New Phytologist. 221:4, 1853–1865.</p> <p> </p> <p><em><strong>Photosynthesis Traits</strong></em></p> <table> <tbody> <tr> <th>Dataset</th> <th>Label</th> <th>Filename</th> </tr> </tbody> <tbody> <tr> <td>Aggregated photosynthesis traits</td> <td>Photosyn. traits</td> <td>Photosynthesis traits</td> </tr> <tr> <td>δ<sup>13</sup>C</td> <td>δ<sup>13</sup>C</td> <td>Traits_13C</td> </tr> <tr> <td>Light-saturated photosynthetic rate</td> <td>Photosyn. rate: A<sub>sat</sub></td> <td>Traits_Asat</td> </tr> <tr> <td>Maximum photosynthetic rate</td> <td>Photosyn. rate: A<sub>max</sub></td> <td>Traits_Amax</td> </tr> <tr> <td>Maximum photosynthetic rate: Nitrogen concentration</td> <td>Max. photosyn. rate: N(%)</td> <td>Traits_N_conc</td> </tr> <tr> <td>Maximum photosynthetic rate: Phosphorous mass (area)</td> <td>Max. photosyn. rate: P(mass)</td> <td>Traits_Phos_area</td> </tr> <tr> <td>Dark respiration (Rd)</td> <td>Dark respiration</td> <td>Traits_Dark_resp</td> </tr> <tr> <td>Specific leaf area (SLA)</td> <td>Specific leaf area</td> <td>Traits_SLA</td> </tr> <tr> <td>Carotenoids (area)</td> <td>Carotenoids: Area</td> <td>Traits_Carot_area</td> </tr> <tr> <td>Carotenoids (mass)</td> <td>Carotenoids: Mass</td> <td>Traits_Carot_mass</td> </tr> <tr> <td>Chlorophyll a (area)</td> <td>Chlorophyll a: Area</td> <td>Traits_Chl_a_area</td> </tr> <tr> <td>Chlorophyll a (mass)</td> <td>Chlorophyll a: Mass</td> <td>Traits_Chl_a_mass</td> </tr> <tr> <td>Chlorophyll b (area)</td> <td>Chlorophyll b: Area</td> <td>Traits_Chl_b_area</td> </tr> <tr> <td>Chlorophyll b (mass)</td> <td>Chlorophyll b: Mass</td> <td>Traits_Chl_b_mass</td> </tr> </tbody> </table> <p> </p> <p><em><strong>Nutrient Traits</strong></em></p> <table> <tbody> <tr> <th>Dataset</th> <th>Label</th> <th>Filename</th> </tr> </tbody> <tbody> <tr> <td>Aggregated nutrient traits</td> <td>Nutrient traits</td> <td>Nutrient_traits</td> </tr> <tr> <td>δ<sup>15</sup>N</td> <td>δ<sup>15</sup>N</td> <td>Traits_15N</td> </tr> <tr> <td>Carbon concentration</td> <td>Carbon conc.</td> <td>Traits_Carbon_conc</td> </tr> <tr> <td>Nitrogen concentration</td> <td>Max. photosyn. rate: N(%)</td> <td>Traits_N_perc</td> </tr> <tr> <td>Phosphorous concentration</td> <td>Max. photosyn. rate: P(mass)</td> <td>Traits_Phos_mass</td> </tr> <tr> <td>Magnesium concentration</td> <td>Regulat. nutrients: Total Mg</td> <td>Traits_Total_Mg</td> </tr> <tr> <td>Potassium concentration</td> <td>Regulat. nutrients: Total K</td> <td>Traits_Total_K</td> </tr> <tr> <td>Calcium concentration</td> <td>Regulat. nutrients: Total Ca</td> <td>Traits_Total_Ca</td> </tr> </tbody> </table> <p> </p> <p><em><strong>Structural Traits</strong></em></p> <table> <tbody> <tr> <th>Dataset</th> <th>Label</th> <th>Filename</th> </tr> </tbody> <tbody> <tr> <td>Aggregated structural traits</td> <td>Structural traits</td> <td>Structural_traits</td> </tr> <tr> <td>Branch specific density</td> <td>Branch wood density</td> <td>Traits_Branch_WD</td> </tr> <tr> <td>Leaf cellulose concentration</td> <td>Leaf fibre conc.: Cellul.</td> <td>Traits_Cellulose</td> </tr> <tr> <td>Leaf lignin concentration</td> <td>Leaf fibre conc.: Lignin</td> <td>Traits_Lignin</td> </tr> <tr> <td>Leaf hemicellulose concentration</td> <td>Leaf fibre conc.: Hemicel.</td> <td>Traits_Hemicellulose</td> </tr> <tr> <td>Leaf area</td> <td>Leaf size: Area</td> <td>Traits_Leaf_area</td> </tr> <tr> <td>Leaf dry weight</td> <td>Leaf size: Dry wgt</td> <td>Traits_Dry_weight</td> </tr> <tr> <td>Leaf force to punch</td> <td>Leaf strength: Tough.</td> <td>Traits_Leaf_toughness</td> </tr> <tr> <td>Leaf thickness</td> <td>Leaf strength: Thick.</td> <td>Traits_Leaf_thickness</td> </tr> <tr> <td>Leaf dry matter content</td> <td>Leaf strength: Dry mat.</td> <td>Traits_LDMC</td> </tr> <tr> <td>Total phenol concentration</td> <td>Leaf defence: Phenol</td> <td>Traits_Phenol</td> </tr> <tr> <td>Total tannin concentration</td> <td>Leaf defenct: Tannin</td> <td>Traits_Tannin</td> </tr> </tbody> </table> <div> <h3> </h3> <h3>Level 3 - Biodiversity</h3> </div> <table> <tbody> <tr> <th>Dataset</th> <th>Label</th> <th>Filename</th> <th>Collector</th> </tr> </tbody> <tbody> <tr> <td>Soil bacterial richness</td> <td>Soil microbial richness: Bacteria</td> <td>Soil_richness_Bacteria</td> <td>Dafydd Elias</td> </tr> <tr> <td>Soil protist richness</td> <td>Soil microbial richness: Protists</td> <td>Soil_richness_Protist</td> <td>Dafydd Elias</td> </tr> <tr> <td>Soil ectomycorrhizal richness</td> <td>Soil fungal richness: Ectomycorrhiza</td> <td>Soil_richness_Ectomycorrhiza</td> <td>Dafydd Elias</td> </tr> <tr> <td>Soil fungal richness</td> <td>Soil fungal richness: Fungi</td> <td>Soil_richness_Fungi</td> <td>Dafydd Elias</td> </tr> <tr> <td>Soil arbuscular mycorrhizal richness</td> <td>Soil fungal richness: Arbuscular mycorrhiza</td> <td>Soil_richness_Arbuscular_mycorrhizal</td> <td>Dafydd Elias</td> </tr> <tr> <td>Leaf spectral diversity</td> <td>Spectral diversity</td> <td>Spectral_diversity</td> <td>Matheus Nunes</td> </tr> <tr> <td>Liana abundance</td> <td>Liana abundance</td> <td>Liana_abundance</td> <td>Boris Bongalov</td> </tr> <tr> <td>Dung beetle abundance</td> <td>Dung beetle abund.</td> <td>Dung_beetle_abundance</td> <td>Eleanor Slade</td> </tr> <tr> <td>Dung beetle diversity: richness</td> <td>Dung beetle diversity: q=0</td> <td>Dung_beetle_diversity_q=0</td> <td>Eleanor Slade</td> </tr> <tr> <td>Dung beetle diversity: Shannon diversity</td> <td>Dung beetle diversity: q=1</td> <td>Dung_beetle_diversity_q=1</td> <td>Eleanor Slade</td> </tr> <tr> <td>Dung beetle diversity: Simpson diversity</td> <td>Dung beetle diversity: q=2</td> <td>Dung_beetle_diversity_q=2</td> <td>Eleanor Slade</td> </tr> <tr> <td>Bird abundance</td> <td>Bird abund.</td> <td>Bird_abundance</td> <td>Simon Mitchell</td> </tr> <tr> <td>Bird diversity: richness</td> <td>Bird diversity: q=0</td> <td>Bird_diversity_q=0</td> <td>Simon Mitchell</td> </tr> <tr> <td>Bird diversity: Shannon diversity</td> <td>Bird diversity: q=1</td> <td>Bird_diversity_q=1</td> <td>Simon Mitchell</td> </tr> <tr> <td>Bird diversity: Simpsons diversity</td> <td>Bird diversity: q=2</td> <td>Bird_diversity_q=2</td> <td>Simon Mitchell</td> </tr> <tr> <td>Bat abundance</td> <td>Bat abund.</td> <td>Bat_abundance</td> <td>David Hemprich-Bennett</td> </tr> <tr> <td>Bat diversity (small scale)</td> <td>Bat diversity (sm scale)</td> <td>Bat_diversity_small_scale</td> <td>David Hemprich-Bennett</td> </tr> <tr> <td>Bat diversity (large scale): richness</td> <td>Bat diversity (lg scale): q=0</td> <td>Bat_diversity_large_scale_q=0</td> <td>David Hemprich-Bennett</td> </tr> <tr> <td>Bat diversity (large scale): Shannon diversity</td> <td>Bat diversity (lg scale): q=1</td> <td>Bat_diversity_large_scale_q=1</td> <td>David Hemprich-Bennett</td> </tr> <tr> <td>Bat diversity (large scale): Simpson diversity</td> <td>Bat diversity (lg scale): q=2</td> <td>Bat_diversity_large_scale_q=2</td> <td>David Hemprich-Bennett</td> </tr> <tr> <td>Bat β-diversity: Nestedness</td> <td>Bat β-diversity: Nested.</td> <td>Bat_beta_diversity_Nestedness</td> <td>David Hemprich-Bennett</td> </tr> <tr> <td>Bat β-diversity: Turnover</td> <td>Bat β-diversity: Turn.</td> <td>Bat_beta_diversity_Turnover</td> <td>David Hemprich-Bennett</td> </tr> <tr> <td>Bat β-diversity: Total</td> <td>Bat β-diversity: Total</td> <td>Bat_beta_diversity_Total</td> <td>David Hemprich-Bennett</td> </tr> </tbody> </table> <div> <h3> </h3> <h3>Level 4 - Functioning</h3> </div> <table> <tbody> <tr> <th>Dataset</th> <th>Label</th> <th>Filename</th> <th>Collector</th> </tr> </tbody> <tbody> <tr> <td>Soil respiration</td> <td>Respiration: Soil</td> <td>Soil_respiration</td> <td>Terhi Riutta</td> </tr> <tr> <td>Stem respiration</td> <td>Respiration: Stem</td> <td>Stem_respiration</td> <td>Terhi Riutta</td> </tr> <tr> <td>Net primary productivity</td> <td>NPP</td> <td>NPP</td> <td>Terhi Riutta</td> </tr> <tr> <td>Litterfall</td> <td>Litterfall</td> <td>Litterfall</td> <td>Terhi Riutta</td> </tr> <tr> <td>Leaf litter decomposition</td> <td>Litter decomposition</td> <td>Litter_decomposition</td> <td>Sabine Both</td> </tr> <tr> <td>Soil mycelial production</td> <td>Mycelial production</td> <td>Hyphal_length</td> <td>Samuel Robinson</td> </tr> <tr> <td>Dung removal</td> <td>Dung removal</td> <td>Dung_removal</td> <td>Eleanor Slade</td> </tr> </tbody> </table> <p> </p> <h2>Funding</h2> <p>Analyses were carried out, and data were collected, as part of the BALI (Biodiversity And Land-use Impacts on tropical ecosystem function) and LOMBOK (Land-use Options for Maintaining BiOdiversity & eKosystem functions) projects using the following funding:</p> <ul> <li>NERC Human-modified Tropical Forests Programme (NE/K016377/1, NE/K016261/1, NE/K016148/1, NE/K016407/1);</li> <li>NERC grant (NE/I028068/1);</li> <li>British Ecological Society Small Ecological Project Grant (No.: 3256/4035);</li> <li>Varley-Gradwell Travelling Fellowship in Insect Ecology;</li> <li>Bat Conservation International Student Research Scholarship;</li> <li>NOMIS Foundation;</li> <li>ERC European Union's Horizon 2020 research and innovation programme (grant agreement No 865403);</li> <li>ERC Advanced Investigator Grant, GEM-TRAIT (321131);</li> <li>The SAFE Project is funded by the Sime Darby Foundation.</li> </ul>

opencc-zeroNov 2019View details →

MH_WATERLAND - Western marsh harriers (Circus aeruginosus, Accipitridae) breeding near the Belgium-Netherlands border

<p><em>MH_WATERLAND - Western marsh harriers (Circus aeruginosus, Accipitridae) breeding near the Belgium-Netherlands border</em> is a bird tracking dataset published by the <a href="https://www.inbo.be/en">Research Institute for Nature and Forest (INBO)</a>. It contains animal tracking data collected by the LifeWatch GPS tracking network for large birds (<a href="http://lifewatch.be/en/gps-tracking-network-large-birds">http://lifewatch.be/en/gps-tracking-network-large-birds</a>) for the project/study <strong>MH_WATERLAND</strong>, using trackers developed by the University of Amsterdam Bird Tracking System (UvA-BiTS, <a href="http://www.uva-bits.nl">http://www.uva-bits.nl</a>). The study was operational from 2013 until 2018. In total 7 individuals of western marsh harrier (<em>Circus aeruginosus</em>) have been tagged in their breeding area near the Belgium-Netherlands border (provinces of East Flanders in Belgium and Zeeland in the Netherlands), mainly to study their habitat use and migration behaviour. Data are uploaded from the UvA-BiTS database to Movebank and from there archived on Zenodo (see <a href="https://github.com/inbo/bird-tracking">https://github.com/inbo/bird-tracking</a>). No new data are expected.</p> <p>See Milotic et al. (2020, <a href="https://doi.org/10.3897/zookeys.947.52570">https://doi.org/10.3897/zookeys.947.52570</a>) for a more detailed description of this dataset.</p> <h2>Files</h2> <p>Data in this package are exported from Movebank study <a href="https://www.movebank.org/cms/webapp?gwt_fragment=page=studies,path=study604806671">604806671</a>. Fields in the data follow the <a href="http://vocab.nerc.ac.uk/collection/MVB">Movebank Attribute Dictionary</a> and are described in <code>datapackage.json</code>. Files are structured as a <a href="https://specs.frictionlessdata.io/data-package/">Frictionless Data Package</a>. You can access all data in R via <code>https://zenodo.org/records/10053583/files/datapackage.json</code> using <a href="https://frictionlessdata.github.io/frictionless-r/">frictionless</a>.</p> <ul> <li><strong>datapackage.json</strong>: technical description of the data files.</li> <li><strong>MH_WATERLAND-reference-data.csv</strong>: reference data about the animals, tags and deployments.</li> <li><strong>MH_WATERLAND-gps-yyyy.csv.gz</strong>: GPS data recorded by the tags, grouped by year.</li> </ul> <h2>Acknowledgements</h2> <p>This dataset was collected using infrastructure provided by INBO and funded by Research Foundation - Flanders (FWO) as part of the Belgian contribution to LifeWatch.</p>

FIGURE 4 in Musicians in the marsh: a new species of music frog (Anura: Ranidae: Nidirana) from Arunachal Pradesh, India

FIGURE 4. Holotype of Nidirana noadihing sp. nov. (WII-ADA1766) in preserved condition. A. dorsal view, B. ventral view, C. right side lateral view of the head, D. left side lateral view of the head, E. ventral view of palm, F. ventral view of feet, G. showing the nuptial pads on first finger marked with yellow arrow. Scale bar= 10 mm.

FIGURE 7 in Musicians in the marsh: a new species of music frog (Anura: Ranidae: Nidirana) from Arunachal Pradesh, India

FIGURE 7. Habitats of Nidirana noadihing sp. nov. at Gandhigram. A. Landscape view of the Noa-Dihing river basin where the population of the new species was discovered. B. Microhabitat of Nidirana noadihing sp. nov. Water filled pits where calling males were observed are indicated with yellow arrows.

FIGURE 3 in Musicians in the marsh: a new species of music frog (Anura: Ranidae: Nidirana) from Arunachal Pradesh, India

FIGURE 3. Holotype (WII-ADA1766) of Nidirana noadihing sp. nov. in life. A. dorsal view of full body, B. ventral view of full body, C, D. dorsolateral view of left and right side respectively, inset image showing rictal gland (rg) and suprabrachial gland (sbg), E. groin, F. showing vent and outer lateral side of thighs.

FIGURE 2 in Musicians in the marsh: a new species of music frog (Anura: Ranidae: Nidirana) from Arunachal Pradesh, India

FIGURE 2. Phylogenetic tree based on concatenated mitochondrial 16S and COI dataset. A. Maximum Likelihood (ML) tree with bootstrap vaues, B. Bayesian Inference (BI) tree with Bayesian posterior probability (BPP) values. Scale bar = substutution per site. Bootstrap support values <80 and BPP support values <0.80 are not shown in the figure.

FIGURE 1 in Musicians in the marsh: a new species of music frog (Anura: Ranidae: Nidirana) from Arunachal Pradesh, India

FIGURE 1. Map showing the type localities of Nidirana species. 1. Nidirana noadihing sp. nov., 2. referred material locality of N. noadihing sp. nov., 3. N. occidentalis, 4. N. daunchina, 5. N. pleuraden, 6. N. lini, 7. N. chapaensis, 8. N. yeae, 9. N. chongqingensis, 10. N. leishanensis, 11. N. guanxiensis, 12. N. shiwandashanensis, 13. N. guibeiensis, 14. N. yaoica, 15. N. hainanensis, 16. N. xiangica, 17. N. guangdongensis, 18. N. nankunensis, 19. N. mangveni, 20. N. adenopleura, 21. N. okinavana. Insert map: 1. Gandhigram, 2. Glaw lake, Kamlang Tiger Reserve. Inset image: Nidirana noadihing sp. nov..

opencc-by-4.0Dec 2023View details →

Dataset of the paper "Modeling the Flow and Geomorphic Heterogeneity Induced by Salt Marsh Vegetation Patches Based on Convolutional Neural Network UNet-Flow"

<p>Modeling the Flow and Geomorphic Heterogeneity Induced by Salt Marsh Vegetation Patches Based on Convolutional Neural Network UNet-Flow</p>