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FIGURE 7 in One more and one less: a new species of large bromelicolous lizard (Gymnophthalmidae: Anadia) from the Andean cloud forests of northwestern Colombia and the phylogenetic status of Anadia antioquensis
FIGURE 7. Geographical distribution of the western and eastern groups of Anadia species in northwestern South America. Note that A. antioquensis, mapped together in the eastern group, is reassigned in this study to the genus Riama.
FIGURE 6 in One more and one less: a new species of large bromelicolous lizard (Gymnophthalmidae: Anadia) from the Andean cloud forests of northwestern Colombia and the phylogenetic status of Anadia antioquensis
FIGURE 6. Right hemipenis of Anadia hollandi sp. nov. MHUA-R13726 paratype in sulcate and asulcate views.
FIGURE 5 in One more and one less: a new species of large bromelicolous lizard (Gymnophthalmidae: Anadia) from the Andean cloud forests of northwestern Colombia and the phylogenetic status of Anadia antioquensis
FIGURE 5. The holotype of Anadia hollandi sp. nov. (MHUA-R 13725) in its branch-hanging posture (left). Detail of lateral, ventral, and dorsal head scales in photographs (middle) and drawing (right). Photos by Luis A. Mazariegos H.
FIGURE 4 in One more and one less: a new species of large bromelicolous lizard (Gymnophthalmidae: Anadia) from the Andean cloud forests of northwestern Colombia and the phylogenetic status of Anadia antioquensis
FIGURE 4. Known range of variation used to recognise Anadia hollandi sp. nov. against other species of the ocellata species group and the western group sensu Oftedal (1974).
FIGURE 2 in One more and one less: a new species of large bromelicolous lizard (Gymnophthalmidae: Anadia) from the Andean cloud forests of northwestern Colombia and the phylogenetic status of Anadia antioquensis
FIGURE 2. Two-dimensional visualisation of uncorrected (16S) genetic distances among both species and individuals of Anadia included in this study. Left: ordinary multidimensional scaling (MDS) including the species found to nest within the genus Riama, A. antioquensis. Right: non-metric multidimensional scaling (NMDS, stress value = 0.15) excluding A. antioquensis. X and Y dimensions are comparable within a single plot, but not between the plots.
FIGURE 1 in One more and one less: a new species of large bromelicolous lizard (Gymnophthalmidae: Anadia) from the Andean cloud forests of northwestern Colombia and the phylogenetic status of Anadia antioquensis
FIGURE 1. Phylogenetic hypothesis on the relationship between Anadia hollandi sp. nov. and other cercosaurine genera and species based on four gene regions (see Supplementary Table 1). Its relationship with other species of the Anadia is outlined in blue, whereas the paraphyletic position of A. antioquensis is outlined in orange. The label "other cercosaurines" denotes a clade with species of the genera Oreosaurus, Proctoporus, Cercosaura, Selvasaura, and Potamites. Numbers on nodes represent ultrafast bootstrap support values after 5000 pseudoreplicates, replaced by green-filled circles when the values are above 0.95. Photos: A. antioquensis by Carlos M. Marín, and A. hollandi sp. nov. by Luis A. Mazariegos H.
FIGURE 3 in One more and one less: a new species of large bromelicolous lizard (Gymnophthalmidae: Anadia) from the Andean cloud forests of northwestern Colombia and the phylogenetic status of Anadia antioquensis
FIGURE 3. Male individuals used as holotype and paratypes of Anadia hollandi sp. nov. from the Mesenia-Paramillo nature reserve. Photographs not to scale; see body size (snout-to-vent length, SVL). Photos by Luis A. Mazariegos H.
On following pages: 390. Robert's Arboreal Rice Rat (Oecomys robert); 391. Unicolored Arboreal Rice Rat (Oecomys concolor); 392. Guianan Arboreal Rice Rat (Oecomys auyantepui); 393. King Arboreal Rice Rat (Oecomys rex); 394. Red Arboreal Rice Rat (Oecomys rutilus); 395. Brazilian Arboreal Rice Rat (Oecomys paricola); 396. Foothill Arboreal Rice Rat (Oecomys superans); 397. Dusky Arboreal Rice Rat (Oecomys phaeotis); 398. Mamore Arboreal Rice Rat (Oecomys mamorae); 399. Anderson's Arboreal Rice Rat (Oecomys sydandersoni); 400. Francisco's Arboreal Rice Rat (Oecomys franciscorum); 401. Atlantic Forest Arboreal Rice Rat (Oecomys catherinae); 402. Cleber's Arboreal Rice Rat (Oecomys cleberi); 403. McConnell's Rice Rat (Euryoryzomys macconnelli); 404. Emmons's Rice Rat (Euryoryzomys emmonsae); 405. Big-headed Rice Rat (Euryoryzomys legatus); 406. Russet Rice Rat (Euryoryzomys russatus); 407. Buffy-sided Rice Rat (Euryoryzomys lamia); 408. Elegant Rice Rat (Euryoryzomys nitidus); 409. Long-whiskered Rice Rat (Transandinomys bolivaris); 410. Talamancan Rice Rat (Transandinomys talamancae); 411. Long-nosed Rice Rat (Handleyomys rostratus); 412. Chapman's Rice Rat (Handleyomys chapman); 413. Black-eared Rice Rat (Handleyomys melanotis); 414. Guerrero Rice Rat (Handleyomys guerrerensis); 415. Cloud Forest Rice Rat (Handleyomys saturation; 416. Highland Rice Rat (Handleyomys rhabdops); 417. Alfaro's Rice Rat (Handleyomys alfaroi); 418. Colombian Western Andes Cloud Forest Mouse (Handleyomys fuscatus); 419. Colombian Central Andes Cloud Forest Mouse (Handleyomys intectus). in Cricetidae
On following pages: 390. Robert's Arboreal Rice Rat (Oecomys robert); 391. Unicolored Arboreal Rice Rat (Oecomys concolor); 392. Guianan Arboreal Rice Rat (Oecomys auyantepui); 393. King Arboreal Rice Rat (Oecomys rex); 394. Red Arboreal Rice Rat (Oecomys rutilus); 395. Brazilian Arboreal Rice Rat (Oecomys paricola); 396. Foothill Arboreal Rice Rat (Oecomys superans); 397. Dusky Arboreal Rice Rat (Oecomys phaeotis); 398. Mamore Arboreal Rice Rat (Oecomys mamorae); 399. Anderson's Arboreal Rice Rat (Oecomys sydandersoni); 400. Francisco's Arboreal Rice Rat (Oecomys franciscorum); 401. Atlantic Forest Arboreal Rice Rat (Oecomys catherinae); 402. Cleber's Arboreal Rice Rat (Oecomys cleberi); 403. McConnell's Rice Rat (Euryoryzomys macconnelli); 404. Emmons's Rice Rat (Euryoryzomys emmonsae); 405. Big-headed Rice Rat (Euryoryzomys legatus); 406. Russet Rice Rat (Euryoryzomys russatus); 407. Buffy-sided Rice Rat (Euryoryzomys lamia); 408. Elegant Rice Rat (Euryoryzomys nitidus); 409. Long-whiskered Rice Rat (Transandinomys bolivaris); 410. Talamancan Rice Rat (Transandinomys talamancae); 411. Long-nosed Rice Rat (Handleyomys rostratus); 412. Chapman's Rice Rat (Handleyomys chapman); 413. Black-eared Rice Rat (Handleyomys melanotis); 414. Guerrero Rice Rat (Handleyomys guerrerensis); 415. Cloud Forest Rice Rat (Handleyomys saturation; 416. Highland Rice Rat (Handleyomys rhabdops); 417. Alfaro's Rice Rat (Handleyomys alfaroi); 418. Colombian Western Andes Cloud Forest Mouse (Handleyomys fuscatus); 419. Colombian Central Andes Cloud Forest Mouse (Handleyomys intectus).
On following pages: 558. Arguedas''s Grass Mouse (Akodon josemariarguedasi); 559. Junin Grass Mouse (Akodon juninensis); 560. Puno Grass Mouse (Akodon subfuscus); 561. Cloud Forest Grass Mouse (Akodon torques); 562. Silent Grass Mouse (Akodon surdus); 563. Kotosh Grass Mouse (Akodon kotosh); 564. White-bellied Grass Mouse (Akodon albiventen; 565. Bolivian Grass Mouse (Akodon boliviensis); 566. Lindbergh's Grass Mouse (Akodon lindberghi); 567. Cursorial Grass Mouse (Akodon curson; 568. Montane Grass Mouse (Akodon montensis); 569. Altiplano Grass Mouse (Akodon lutescens); 570. Thespian Grass Mouse (Akodon mimus); 571. Koford's Grass Mouse (Akodon kofordl); 572. Smoky Grass Mouse (Akodon fumeus); 573. Day's Grass Mouse (Akodon dayi); 574. Cochabamba Grass Mouse (Akodon siberiae); 575. Unicolored Grass Mouse (Akodon caenosus); 576. Tarija Grass Mouse (Akodon pervalens), 577. Gray-bellied Grass Mouse (Akodon simulator); 578. Budin's Grass Mouse (Akodon budini); 579. Variable Grass Mouse (Akodon varius); 580. Caparao Grass Mouse (Akodon mystax); 581. Parana Grass Mouse (Akodon paranaensis); 582. Sao Paulo Grass Mouse (Akodon sanctipaulensis); 583. Forest Grass Mouse (Akodon sylvanus); 584. Spegazzini's Grass Mouse (Akodon spegazzinii); 585. Toba Grass Mouse (Akodon toba); 586. Azara's Grass Mouse (Akodon azarae); 587 Philip Myers's Grass Mouse (Akodon philipmyersi); 588. Reig's Grass Mouse (Akodon reigi); 589. Polop's Grass Mouse (Akodon polopi); 590. Dolores Grass Mouse (Akodon dolores); 591. Intelligent Grass Mouse (Akodon iniscatus). in Cricetidae
On following pages: 558. Arguedas''s Grass Mouse (Akodon josemariarguedasi); 559. Junin Grass Mouse (Akodon juninensis); 560. Puno Grass Mouse (Akodon subfuscus); 561. Cloud Forest Grass Mouse (Akodon torques); 562. Silent Grass Mouse (Akodon surdus); 563. Kotosh Grass Mouse (Akodon kotosh); 564. White-bellied Grass Mouse (Akodon albiventen; 565. Bolivian Grass Mouse (Akodon boliviensis); 566. Lindbergh's Grass Mouse (Akodon lindberghi); 567. Cursorial Grass Mouse (Akodon curson; 568. Montane Grass Mouse (Akodon montensis); 569. Altiplano Grass Mouse (Akodon lutescens); 570. Thespian Grass Mouse (Akodon mimus); 571. Koford's Grass Mouse (Akodon kofordl); 572. Smoky Grass Mouse (Akodon fumeus); 573. Day's Grass Mouse (Akodon dayi); 574. Cochabamba Grass Mouse (Akodon siberiae); 575. Unicolored Grass Mouse (Akodon caenosus); 576. Tarija Grass Mouse (Akodon pervalens), 577. Gray-bellied Grass Mouse (Akodon simulator); 578. Budin's Grass Mouse (Akodon budini); 579. Variable Grass Mouse (Akodon varius); 580. Caparao Grass Mouse (Akodon mystax); 581. Parana Grass Mouse (Akodon paranaensis); 582. Sao Paulo Grass Mouse (Akodon sanctipaulensis); 583. Forest Grass Mouse (Akodon sylvanus); 584. Spegazzini's Grass Mouse (Akodon spegazzinii); 585. Toba Grass Mouse (Akodon toba); 586. Azara's Grass Mouse (Akodon azarae); 587 Philip Myers's Grass Mouse (Akodon philipmyersi); 588. Reig's Grass Mouse (Akodon reigi); 589. Polop's Grass Mouse (Akodon polopi); 590. Dolores Grass Mouse (Akodon dolores); 591. Intelligent Grass Mouse (Akodon iniscatus).
Distribution. Known only from Siberia Cloud Forest in Cochabamba and W Santa Cruz departments, C Bolivia. in Cricetidae
Distribution. Known only from Siberia Cloud Forest in Cochabamba and W Santa Cruz departments, C Bolivia.
Data for the publication: A parameterization of cirrus cloud formation: Revisiting competing ice nucleation
<p>The files contain the data sets shown in the publication "A parameterization of cirrus cloud formation: Revisiting competing ice nucleation" to appear in J. Geophys. Res. Atmos. in 2022 (revised manuscript submitted) The files include a power point slide containing the schematic and xmgrace plot files containing the research data (ASCII) shown in all other figures that appear in the paper and its appendix.</p>
Graph-based Leaf–Wood Separation Method for Individual Trees Using Terrestrial Lidar Point Clouds: Labeled validation data
<p>Set of 10 manually labeled point clouds used in the performance assessment of "Graph-based Leaf–Wood Separation Method for Individual Trees Using Terrestrial Lidar Point Clouds". This dataset is a collection of single trees scanned from different regions covering tropical, temperate, and boreal species—with heights ranging from 5.4 to 43.7 m, using the Riegl VZ-400 and Leica ScanStation C10 terrestrial laser scanner. These data have been preprocessed. For the original data, see https://doi.org/10.5061/dryad.10hq7;<br> https://doi.org/10.5061/dryad.np5hqbzp6;<br> https://doi.org/10.1594/PANGAEA.942856.</p>
Responses of Surface Evaporative Fluxes in Montane Cloud Forests to the Climate Change Scenario
<p>CL_surfobs_raw.mat and LHC_nodew_new_raw.mat are the analyzed CLM simulation output with atmospheric observations in Chi-Lan and Lien-Hua-Chih as input forcings.</p> <p>CLatm_LHC_prec*.mat are the analyzed CLM simulation output in sensitivity tests for the rainfall pattern.</p> <p>CL_*_transform_raw.mat are the analyzed CLM simulation output in CTL simulation and climate change sensitivity tests. </p> <p>Fig_*.m are matlab code files to reproduce figures in the article.</p> <p>Fig_11_ttest.m and Fig_11_LE_p_value.mat are the t-test for the decrease of latent heat flux in the diurnal cycle under climate change scenario and the resulting p-value.</p> <p>Fig_quantile.m and Fig_4_6_7_8_9_10_11_quantile.mat are to obtain first and third quantile of the changes of canopy water and surface heat fluxes in the diurnal cycle under climate change scenarios.</p>
Data for "Dependence of Convective Cloud Properties and Their Transport on Cloud Fraction and GCM Resolution Diagnosed from a Cloud-Resolving Model Simulation"
<p>The datasets for the manuscript "Dependence of Convective Cloud Properties and Their Transport on Cloud Fraction and GCM Resolution Diagnosed from a Cloud-Resolving Model Simulation".</p> <p>model: WRF3.1.1</p> <p>location: Southern Great Plains</p> <p>time: from 2100 UTC 23 May to 0600 UTC 24 May</p> <p>time interval: 6 minutes</p> <p>domain size: 512km x 512km</p> <p>vertical layer: 500hpa</p> <p>variables: P, PB, PH, PHB, U, V, W, T, QCLOUD, QICE, QVAPOR</p> <p>calculated data: mse, up_only(only consider updraft), up_down(consider both updrafts and downdrafts)</p> <p> </p>
On following pages: 164. Mount Anacuao Tree Mouse (Musseromys anacuao); 165. Mount Pulag Tree Mouse (Musseromys beneficus); 166. Mount Banahaw Tree Mouse (Musseromys gulantang); 167. Mount Amuyao Tree Mouse Musseromys inopinatus); 168. Southern Luzon Giant Cloud Rat (Phloeomys cumingi); 169. Northern Luzon Giant Cloud Rat (Phloeomys pallidus); 170. Large-toothed Hairy-tailed Rat (Batomys dentatus); 171. Luzon Cordillera Hairy-tailed Rat (Batomys granti); 172. Hamiguitan Hairy-tailed Rat (Batomys hamiguitan); 173. Russet Hairy-tailed Rat (Batomys russatus); 174. Mindanao Hairy-tailed Rat (Batomys salomonseni); 175. Mount Isarog Hairy-tailed Rat (Batomys uragon), 176. Black-tailed Dwarf Cloud Rat (Carpomys melanurus); 177. Brown-tailed Dwarf Cloud Rat (Carpomys phaeurus); 178. Dinagat Bushy-tailed Cloud Rat (Crateromys australis); 179. Panay Bushy-tailed Cloud Rat (Crateromys heaneyi), 180. llin Bushy-tailed Cloud Rat (Crateromys paulus); 181. Luzon Bushy-tailed Cloud Rat (Crateromys schadenbergi). in Muridae
On following pages: 164. Mount Anacuao Tree Mouse (Musseromys anacuao); 165. Mount Pulag Tree Mouse (Musseromys beneficus); 166. Mount Banahaw Tree Mouse (Musseromys gulantang); 167. Mount Amuyao Tree Mouse Musseromys inopinatus); 168. Southern Luzon Giant Cloud Rat (Phloeomys cumingi); 169. Northern Luzon Giant Cloud Rat (Phloeomys pallidus); 170. Large-toothed Hairy-tailed Rat (Batomys dentatus); 171. Luzon Cordillera Hairy-tailed Rat (Batomys granti); 172. Hamiguitan Hairy-tailed Rat (Batomys hamiguitan); 173. Russet Hairy-tailed Rat (Batomys russatus); 174. Mindanao Hairy-tailed Rat (Batomys salomonseni); 175. Mount Isarog Hairy-tailed Rat (Batomys uragon), 176. Black-tailed Dwarf Cloud Rat (Carpomys melanurus); 177. Brown-tailed Dwarf Cloud Rat (Carpomys phaeurus); 178. Dinagat Bushy-tailed Cloud Rat (Crateromys australis); 179. Panay Bushy-tailed Cloud Rat (Crateromys heaneyi), 180. llin Bushy-tailed Cloud Rat (Crateromys paulus); 181. Luzon Bushy-tailed Cloud Rat (Crateromys schadenbergi).
Intercomparison of Convective-Aggregation States with two Cloud Resolving Models: DATASET
<p>Radiative-Convective Equilibrium (RCE) is an important modeling paradigm for the tropical atmosphere. In this paradigm, cloud clustering can occur spontaneously, affecting the energy budget of the atmosphere. Here, two models, run in RCE, exhibiting this convective aggregation have been compared with each other and with the results of the Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP). The two models studied, the SAM (System for Atmospheric Modeling) and the ARPS (Advanced Regional Prediction System), are different in the physical and numerical formulation, allowing us to compare the sensitivity to processes related to the phenomenon of convective organization. In General, the two models present similarities in what concerns precipitation, warming, and drying of the atmosphere and anvil cloud area reduction. All these factors are also within the spread of the RCEMIP values. However, the two models differ both in the convective organization feedback and in the degree of organization. SAM is strongly organized and ARPS is weakly organized. SAM achieves convective organization through clouds-radiative feedback and ARPS achieves it through moisture-convection feedback. These differences can be traced back to the interaction between the microphysics and the sub-cloud layer properties. We suggest that when studying climate sensitivity, climate models should include both types of convective organization mechanisms.</p>
Intercomparison of Convective-Aggregation States with two Cloud Resolving Models: DATASET
<p>Radiative-Convective Equilibrium (RCE) is an important modeling paradigm for the tropical atmosphere. In this paradigm, cloud clustering can occur spontaneously, affecting the energy budget of the atmosphere. Here, two models, run in RCE, exhibiting this convective aggregation have been compared with each other and with the results of the Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP). The two models studied, the SAM (System for Atmospheric Modeling) and the ARPS (Advanced Regional Prediction System), are different in the physical and numerical formulation, allowing us to compare the sensitivity to processes related to the phenomenon of convective organization. In General, the two models present similarities in what concerns precipitation, warming, and drying of the atmosphere and anvil cloud area reduction. All these factors are also within the spread of the RCEMIP values. However, the two models differ both in the convective organization feedback and in the degree of organization. SAM is strongly organized and ARPS is weakly organized. SAM achieves convective organization through clouds-radiative feedback and ARPS achieves it through moisture-convection feedback. These differences can be traced back to the interaction between the microphysics and the sub-cloud layer properties. We suggest that when studying climate sensitivity, climate models should include both types of convective organization mechanisms.</p>
Data for "Cloud thinning in the mixed-phase regime as geoengineering concept" : Satellite data, ICON-LES simulations, and ECHAM-HAM simulations
<p><br> This repository contains:</p> <p>- Satellite product combination: Used to evaluate the cloud radiative effect of mixed-phase regime clouds.</p> <p>- ICON-LES simulations: Mixed-phase stratocumulus deck during M-PACE simulated with artificial droplet freezing.<br> - ref: reference.<br> - 0P1Nd:1% per hour<br> - 0P01Nd:0.1% per hour<br> - 0P001Nd:0.01% per hour</p> <p>- ECHAM-HAM 2-year simulations: Different scenarios with enhanced droplet freezing and with seeding concentrations of dust ice-nucleating particles.<br> - ori: reference<br> - ABS_1e4: 1e1 per Liter<br> - ABS_1e8: 1e5 per Liter<br> - CDNCx1e_7: 1e-4% per hour<br> - CDNCx1e_0 : 1e3% per hour</p> <p>- ECHAM-HAM 25-year simulations of Mixed-phase regime Cloud Thinning (MCT) including a mixed-layer ocean.<br> - ori: reference<br> - CDNCx1e_3: SEED simulation</p>
Supporting dataset of Balloon-bore Aerosol-Cloud Interaction Studies (BACIS): Field campaigns to understand and quantiy aerosol effects on clouds
<p>The upload comprises raw dataset of supporting instruments from BACIS Campaigns conducted from NARL, Gadanki.</p>
Cloud masks of GAN-CDM based models
<p>This is the result of GAN-CDM based models reported in Li, J., Wu, Z., Sheng, Q., Wang, B., Hu, Z., Zheng, S., Camps-Vall, G., Molinier, M., 2022. A hybrid generative adversarial network for weakly-supervised cloud detection in multispectral images. Remote Sens. Environ. 280, 113197. https://doi.org/10.1016/j.rse.2022.113197</p> <p>The file name means: dataset-binary mask under certain threshold-modelversion</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.