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7,883 results for “Tropic”
On following pages: 223. Mohave Ground Squirrel (Xerospermophilus mohavensis); 224. Perote Ground Squirrel (Xerospermophilus perotensis); 225. Ring-tailed Ground Squirrel (Notocitellus annulatus); 226. Tropical Ground Squirrel (Notocitellus adocetus); 227. European Ground Squirrel (Spermophilus citellus); 228. Russet Ground Squirrel (Spermophilus major); 229. Speckled Ground Squirrel (Spermophilus suslicus); 230. Yellow Ground Squirrel (Spermophilus fulvus); 231. Little Ground Squirrel (Spermophilus pygmaeus); 232. Caucasian Mountain Ground Squirrel (Spermophilus musicus); 233. Asia Minor Ground Squirrel (Spermophilus xanthoprymnus); 234. Tauren Ground Squirrel (Spermophilus taurensis); 235. Red-cheeked Ground Squirrel (Spermophilus erythrogenys); 236. Relict Ground Squirrel (Spermophilus relictus); 237. Tian Shan Ground Squirrel (Spermophilus nilkaensis); 238. Brandt's Ground Squirrel (Spermophilus brevicauda); 239. Pallid Ground Squirrel (Spermophilus pallidicauda); 240. Alashan Ground Squirrel (Spermophilus alashanicus); 241. Daurian Ground Squirrel (Spermophilus dauricus). in Sciuridae
On following pages: 223. Mohave Ground Squirrel (Xerospermophilus mohavensis); 224. Perote Ground Squirrel (Xerospermophilus perotensis); 225. Ring-tailed Ground Squirrel (Notocitellus annulatus); 226. Tropical Ground Squirrel (Notocitellus adocetus); 227. European Ground Squirrel (Spermophilus citellus); 228. Russet Ground Squirrel (Spermophilus major); 229. Speckled Ground Squirrel (Spermophilus suslicus); 230. Yellow Ground Squirrel (Spermophilus fulvus); 231. Little Ground Squirrel (Spermophilus pygmaeus); 232. Caucasian Mountain Ground Squirrel (Spermophilus musicus); 233. Asia Minor Ground Squirrel (Spermophilus xanthoprymnus); 234. Tauren Ground Squirrel (Spermophilus taurensis); 235. Red-cheeked Ground Squirrel (Spermophilus erythrogenys); 236. Relict Ground Squirrel (Spermophilus relictus); 237. Tian Shan Ground Squirrel (Spermophilus nilkaensis); 238. Brandt's Ground Squirrel (Spermophilus brevicauda); 239. Pallid Ground Squirrel (Spermophilus pallidicauda); 240. Alashan Ground Squirrel (Spermophilus alashanicus); 241. Daurian Ground Squirrel (Spermophilus dauricus).
On following pages: 90. Grizzled Small-eared Shrew (Cryptotis obscurus); 91. Phillips's Small-eared Shrew (Cryptotis phillipsii); 92. Eastern Cordillera Small-eared Shrew (Cryptotis brachyonyx); 93. Colombian Small-eared Shrew (Cryptotis colombianus); 94. Honduran Small-eared Shrew (Cryptotis hondurensis); 95. Darien Small-eared Shrew (Cryptotis merus); 96. Blackish Small-eared Shrew (Cryptotis nigrescens); 97. Lacandona Small-eared Shrew (Cryptotis lacandonensis); 98. Yucatan Small-eared Shrew (Cryptotis mayensis); 99. Merriam''s Small-eared Shrew (Cryptotis merriami); 100. Berlandier's Least Shrew (Cryptotis berlandieri); 101. Central American Least Shrew (Cryptotis orophilus); 102. North American Least Shrew (Cryptotis parvus); 103. Puebla Least Shrew (Cryptotis pueblensis); 104. Mexican Least Shrew (Cryptotis soricinus); 105. Tropical Least Shrew (Cryptotis tropicalis); 106. Popocatepetl Broad-clawed Shrew (Cryptotis alticola); 107. Goldman's Broad-clawed Shrew (Cryptotis goldmani); 108. Oaxacan Broad-clawed Shrew (Cryptotis peregrinus); 109. Talamancan Broad-clawed Shrew (Cryptotis gracilis); 110. Santa Barbara Broad-clawed Shrew (Cryptotis cavatorculus); 111. Celaque Broad-clawed Shrew (Cryptotis celague); 112. Dark Mexican Broad-clawed Shrew (Cryptotis griseoventris); 113. Omoa Broad-clawed Shrew (Cryptotis mccarthy); 114. Muscular Broad-clawed Shrew (Cryptotis lacertosus); 115. Honduran Broad-Clawed Shrew (Cryptotis magnimana); 116. Mam Broad-clawed Shrew (Cryptotis mam); 117. Goodwin's Broad-clawed Shrew (Cryptotis goodwini); 118. Highland Broad-clawed Shrew (Cryptotis oreoryctes); 119. Monteverde Small-eared Shrew (Cryptotis monteverdensis); 120. Enders's Small-eared Shrew (Cryptotis endersi); 121. Aroa Small-eared Shrew (Cryptotis aroensis); 122. Thomas's Small-eared Shrew (Cryptotis thomasi); 123. Dinira Small-eared Shrew (Cryptotis dinirensis), 124. Venezuelan Small-eared Shrew (Cryptotis venezuelensis), 125. Merida Small-eared Shrew (Cryptotis meridensis); 126. Tama Small-eared Shrew (Cryptotis tamensis); 127. Perija Small-eared Shrew (Cryptotis perijensis); 128. Medellin Small-eared Shrew (Cryptotis medellinius); 129. Western Colombian Small-eared Shrew (Cryptotis squamipes); 130. Ecuadorean Small-eared Shrew (Cryptotis equatoris); 131. Osgood's Small-eared Shrew (Cryptotis osgoodi); 132. Wandering Small-eared Shrew (Cryptotis montivagus); 133. Blind Small-eared Shrew (Cryptotis niausa); 134. Evaristo's Small-eared Shrew (Cryptotis evaristoi); 135. Peruvian Small-eared Shrew (Cryptotis peruviensis). in Soricidae
On following pages: 90. Grizzled Small-eared Shrew (Cryptotis obscurus); 91. Phillips's Small-eared Shrew (Cryptotis phillipsii); 92. Eastern Cordillera Small-eared Shrew (Cryptotis brachyonyx); 93. Colombian Small-eared Shrew (Cryptotis colombianus); 94. Honduran Small-eared Shrew (Cryptotis hondurensis); 95. Darien Small-eared Shrew (Cryptotis merus); 96. Blackish Small-eared Shrew (Cryptotis nigrescens); 97. Lacandona Small-eared Shrew (Cryptotis lacandonensis); 98. Yucatan Small-eared Shrew (Cryptotis mayensis); 99. Merriam''s Small-eared Shrew (Cryptotis merriami); 100. Berlandier's Least Shrew (Cryptotis berlandieri); 101. Central American Least Shrew (Cryptotis orophilus); 102. North American Least Shrew (Cryptotis parvus); 103. Puebla Least Shrew (Cryptotis pueblensis); 104. Mexican Least Shrew (Cryptotis soricinus); 105. Tropical Least Shrew (Cryptotis tropicalis); 106. Popocatepetl Broad-clawed Shrew (Cryptotis alticola); 107. Goldman's Broad-clawed Shrew (Cryptotis goldmani); 108. Oaxacan Broad-clawed Shrew (Cryptotis peregrinus); 109. Talamancan Broad-clawed Shrew (Cryptotis gracilis); 110. Santa Barbara Broad-clawed Shrew (Cryptotis cavatorculus); 111. Celaque Broad-clawed Shrew (Cryptotis celague); 112. Dark Mexican Broad-clawed Shrew (Cryptotis griseoventris); 113. Omoa Broad-clawed Shrew (Cryptotis mccarthy); 114. Muscular Broad-clawed Shrew (Cryptotis lacertosus); 115. Honduran Broad-Clawed Shrew (Cryptotis magnimana); 116. Mam Broad-clawed Shrew (Cryptotis mam); 117. Goodwin's Broad-clawed Shrew (Cryptotis goodwini); 118. Highland Broad-clawed Shrew (Cryptotis oreoryctes); 119. Monteverde Small-eared Shrew (Cryptotis monteverdensis); 120. Enders's Small-eared Shrew (Cryptotis endersi); 121. Aroa Small-eared Shrew (Cryptotis aroensis); 122. Thomas's Small-eared Shrew (Cryptotis thomasi); 123. Dinira Small-eared Shrew (Cryptotis dinirensis), 124. Venezuelan Small-eared Shrew (Cryptotis venezuelensis), 125. Merida Small-eared Shrew (Cryptotis meridensis); 126. Tama Small-eared Shrew (Cryptotis tamensis); 127. Perija Small-eared Shrew (Cryptotis perijensis); 128. Medellin Small-eared Shrew (Cryptotis medellinius); 129. Western Colombian Small-eared Shrew (Cryptotis squamipes); 130. Ecuadorean Small-eared Shrew (Cryptotis equatoris); 131. Osgood's Small-eared Shrew (Cryptotis osgoodi); 132. Wandering Small-eared Shrew (Cryptotis montivagus); 133. Blind Small-eared Shrew (Cryptotis niausa); 134. Evaristo's Small-eared Shrew (Cryptotis evaristoi); 135. Peruvian Small-eared Shrew (Cryptotis peruviensis).
Distribution. Widespread in tropical Africa from Ghana (Volta River) S to Gabon and E to SW Kenya (Kakamega Forest). in Muridae
Distribution. Widespread in tropical Africa from Ghana (Volta River) S to Gabon and E to SW Kenya (Kakamega Forest).
Distribution. Widespread in tropical W Africa from Senegal (Basse Casamance) to Ivory Coast—-Ghana border. in Muridae
Distribution. Widespread in tropical W Africa from Senegal (Basse Casamance) to Ivory Coast—-Ghana border.
Distribution. Widespread in tropical Africa in Guinea-Bissau and from Sierra Leone and Guinea E to S South Sudan and W Kenya, and S to N Angola, S DR Congo, NE Zambia, SW Tanzania, and extreme N Malawi; isolated populations occur in SW Sudan and SW Ethiopia. in Muridae
Distribution. Widespread in tropical Africa in Guinea-Bissau and from Sierra Leone and Guinea E to S South Sudan and W Kenya, and S to N Angola, S DR Congo, NE Zambia, SW Tanzania, and extreme N Malawi; isolated populations occur in SW Sudan and SW Ethiopia.
Distribution. Widely distributed in tropical Africa from Dahomey Gap E to Ethiopia and S to N Angola, S DR Congo, and SW Tanzania. in Muridae
Distribution. Widely distributed in tropical Africa from Dahomey Gap E to Ethiopia and S to N Angola, S DR Congo, and SW Tanzania.
Distribution. Widespread in tropical Africa from Volta River(Ghana) E through Congo Basin to the Albertine Rift (Uganda) and S to NW Angola (Cabinda) and SC DR Congo; occurs also on Bioko I. in Muridae
Distribution. Widespread in tropical Africa from Volta River(Ghana) E through Congo Basin to the Albertine Rift (Uganda) and S to NW Angola (Cabinda) and SC DR Congo; occurs also on Bioko I.
Distribution. Patchily distributed in tropical Africa from SE Guinea (Mt Nimba) E to C Kenya and S to N Malawi. in Muridae
Distribution. Patchily distributed in tropical Africa from SE Guinea (Mt Nimba) E to C Kenya and S to N Malawi.
Distribution. Restricted to a small range within the monsoon tropics of N Northern Territory, Australia, with almost all records from Kakadu and Litchfield National Parks. in Muridae
Distribution. Restricted to a small range within the monsoon tropics of N Northern Territory, Australia, with almost all records from Kakadu and Litchfield National Parks.
The first comprehensive revision of all the species attributed to Melomys led J. I. Menzies in 1996 to resurrect the genus Paramelomys and to redefine its morphologicallimits and species content. Menzies created P. gressitti as a new species belonging to a group displaying morphological similarities and including also P. lorentzii and P. moncktoni. Monotypic Distribution. E New Guinea. Descriptive notes. Head-body 135-162 mm, hindfoot 30-34 mm; no specific data are available for body weight. Gressitt's Mosaic-tailed Rat is a medium-sized Paramelomys with a soft, thick and woolly pelage, a long narrow foot, and a tail with three hairs per scale. It exhibits a medium-sepia dorsal pelage and a gray-buff ventral one. Tail is slightly shorter (99%) than head-body length. The skull has a narrow zygomatic plate. Habitat. Moist tropical mountain forest between 2300 m and 2400 m. Food and Feeding. No information. Breeding. No information. Activity patterns. Gressitt's Mosaic-tailed Rat is terrestrial. Movements, Home range and Social organization. No information. Status and Conservation. Classified as Endangered on The IUCN Red List owing to its small geographic range (less than 3500 km?*) and the destruction ofits habitat by mining and logging activities. The major threat to Gressitt's Mosaic-tailed Rat is ongoing habitat degradation caused by nearby human populations; habitat on Mount Kandy has been destroyed by gold-miners and wood-cutters. Bibliography. Menzies (1996). in Muridae
The first comprehensive revision of all the species attributed to Melomys led J. I. Menzies in 1996 to resurrect the genus Paramelomys and to redefine its morphologicallimits and species content. Menzies created P. gressitti as a new species belonging to a group displaying morphological similarities and including also P. lorentzii and P. moncktoni. Monotypic Distribution. E New Guinea. Descriptive notes. Head-body 135-162 mm, hindfoot 30-34 mm; no specific data are available for body weight. Gressitt's Mosaic-tailed Rat is a medium-sized Paramelomys with a soft, thick and woolly pelage, a long narrow foot, and a tail with three hairs per scale. It exhibits a medium-sepia dorsal pelage and a gray-buff ventral one. Tail is slightly shorter (99%) than head-body length. The skull has a narrow zygomatic plate. Habitat. Moist tropical mountain forest between 2300 m and 2400 m. Food and Feeding. No information. Breeding. No information. Activity patterns. Gressitt's Mosaic-tailed Rat is terrestrial. Movements, Home range and Social organization. No information. Status and Conservation. Classified as Endangered on The IUCN Red List owing to its small geographic range (less than 3500 km?*) and the destruction ofits habitat by mining and logging activities. The major threat to Gressitt's Mosaic-tailed Rat is ongoing habitat degradation caused by nearby human populations; habitat on Mount Kandy has been destroyed by gold-miners and wood-cutters. Bibliography. Menzies (1996).
Soil respiration in a successional tropical forest in Thailand
<p class="p1">Soil respiration (SR) in forests contributes significant emissions of carbon from terrestrial ecosystems into the atmosphere. Soil respiration is highly sensitive to environmental changes because it is affected by many factors, including soil temperature, soil moisture, microbial community, surface litter and vegetation type. Indeed, a small change in SR may have large impacts on the global carbon balance, further influencing feedbacks to climate change. Thus, detailed characterization of SR responses to changes in environmental conditions is needed to accurately estimate carbon dioxide emissions from forest ecosystems. However, data for such analyses are still limited, especially in tropical forests of Southeast Asia where various stages of forest succession exist due to previous land-use changes. In this preliminary study, we measured SR and some environmental factors including soil temperature (ST), soil moisture (SM) and organic matter content (OM) in three successional tropical forests in both wet and dry seasons. We also analyzed the relationships between SR and the three environmental variables. Results showed that SR was higher in the wet season and in older forests. While no response of SR to ST was found in younger forest stages, SR of the old-growth forest significantly responded to ST, plausibly due to the non-uniform forest structure, including gaps, that resulted in a wide range of ST. Across forest stages, SM was the limiting factor for SR in the wet season whereas SR significantly varied with OM in the dry season. Overall, our results indicated that the responses of SR to environmental factors were mediated by seasons and forest succession. These findings call for further investigations on SR and its variations with environmental factors in tropical forests with detailed temporal and spatial scales, particularly in Southeast Asia where patches of successional stages dominate.</p>
Dataset - modelled CO2 emissions from tropical peat-draining rivers and coastal waters based on enhanced weathering scenarios.
<p>Dataset related to the manuscript "Destabilization of carbon in tropical peatlands by enhanced weathering" (DOI: <a href="https://doi.org/10.1038/s43247-022-00544-0">10.1038/s43247-022-00544-0</a>).</p> <p>Model runs for enhanced leaching of dissolved inorganic carbon (DIC) and of dissolved organic carbon (DOC) were conducted.</p> <p>Results include in-river carbon dioxide (CO2), DIC, DOC, oxygen (O2) and pH as well as CO2 emissions from rivers and from coastal waters.</p> <p>Main results are in "River_And_Coastal_Response_To_Enhanced_Weathering.xlsx".<br> Results for uncertainty study are in "River_And_Coastal_Response_To_Enhanced_Weathering_Uncertainty_Scenarios.xlsx".</p>
Allochthonous resources are less important for faunal communities on highly productive, small tropical islands
<p><span>Ecosystems are interconnected by energy fluxes that provide resources for the inhabiting organisms along the transition zone. Especially where in-situ production is low, ecosystems can become highly dependent on external resources. The dependency on external input becomes less pronounced in systems with elevated in-situ production, where only consumer species close to the site of external input remain subsidized, whereas species distant to the input site rely on the in-situ production of the ecosystem. It is largely unclear though if this pattern is consistent over different consumer species and trophic levels in one ecosystem, and whether consumer species that occur both proximate to and at a distance from the input site differ in their dependency on external resource inputs between sites. Using stable isotope analysis, we investigated the dependency on external marine input for common ground-associated consumer taxa on small tropical islands with high in-situ production. We show that marine input is only relevant for strict beach-dwelling taxa, while the terrestrial vegetation is the main carbon source for inland-dwelling taxa. Consumer species that occurred both close (beach) and distant (inland) to the site of marine input showed similar proportions of marine input in their diets. This supports earlier findings that the relevance of external resources becomes limited to species close to the input site in systems with sufficient in-situ production. However, it also indicates that the relevance of external input is also species-dependent, as consumers occurring close and distant to the input site depended equally strong or weak on marine input.</span></p>
Niche differentiation along multiple functional-trait dimensions contributes to high local diversity of Euphorbiaceae in a tropical tree assemblage
<p><span>Understanding the mechanisms that drive community assembly in species-rich tropical forest remains a fundamental challenge in ecology. Here, we integrated multivariate functional trait dimensions, phylogeny, and metabolomics to test fundamental predictions concerning the role of differentiation with respect to abiotic and biotic niche axes in the maintenance of high local diversity of woody plants in the Euphorbiaceae.</span></p> <p><span>We measured 40 functional traits related to resource acquisition, photosynthetic capacity, hydraulic efficiency, and secondary-metabolite profiles generated using untargeted metabolomics in all 26 Euphorbiaceae species in a 20-ha forest dynamics plot in tropical southwestern China. We examined the correlation structure of 40 traits using a trait networking approach. We coupled these traits with variation in soil nutrients, light environment, soil water content and herbivore pressure within the plot to assess niche differentiation in space. We compared phylogenetic signal among </span><span>multivariate trait dimensions and secondary metabolites to assess niche differentiation in evolutionary time.</span></p> <p><span>Network analysis revealed that a small number of traits with high network centrality reflected variation in ecological strategy among the Euphorbiaceae. Using these high-centrality traits, we observed significant functional turnover along environmental gradients defined by light, soil moisture, soil nutrients and leaf herbivory, respectively. Most resource utilization traits showed significant phylogenetic signal, whereas almost all defensive traits lacked phylogenetic signal, including species similarity with respect to plant secondary metabolites.</span></p> <p><span>Synthesis</span><span>.</span><span> </span><span>Our results suggest that resource-utilization traits and the habitat associations play a significant role in the </span><span>niche segregation</span><span> of co-occurring woody plants in the Euphorbiaceae. Secondary metabolites, however, may enhance diversity at a finer spatial scale by allowing closely related species with similar functional traits to partition biotic niche space within shared habitats in tropical</span><span> rainforest.</span></p>
The role of tropical cyclone on Changjiang River subaqueous delta geomorphology: a numerical investigation of Tropical Cyclone Danas (2019)
<p>ecs_mesh: Model domain used for numerical simulation in Matlab data format.</p> <p>Variable description of ecs_mesh.mat:</p> <p>nodex/nodey: Longitude/Latitude of the vertices of the triangles</p> <p>cellx/celly: Longitude/Latitude of the faces of the triangles</p> <p>nodeh: Bathymetry of the vertices</p> <p>nv: Vertices composition of the triangles</p> <p> </p> <p>model_result_baroclinic: Used FVCOM model output from 2019-07-01 to 2019-08-01 in Matlab data format.</p> <p>Variable description of model_result_baroclinic.mat:</p> <p>SSC: Total suspended sediment concentration of all sediment classes, units: g/L</p> <p>deposition_flux: Deposition flux of suspended sediment, units: kg/m^2/h</p> <p>divergence_sed_flux: depth-integrated divergence of sediment flux, units: kg/m^2/h</p> <p>erosion_flux: Erosion flux of sea-bed surface sediment, units: kg/m^2/h</p> <p>salinity: sea water salinity, units: psu</p> <p>taub: Total bed stress, units: Pa</p> <p>time_model: Time of the results, time zone: LST</p> <p>u: Eastward water velocity, units: m/s</p> <p>v: Northward water velocity, units: m/s</p> <p>zeta: Water surface elevation</p> <p> </p> <p>model_verify: Bed elevation data from ADV, wave parameters from buoy, and bottom suspended sediment concentration from OBS in Matlab data format.</p> <p>Variable description of model_verify.mat:</p> <p>ADV_BEC_xx: Bed Elevation measurement from ADV at Station xx, units: mm</p> <p>ADV_time_xx: Measurement time of bed elevation of ADV at Station xx, time zone: LST</p> <p>Buoy_hs_S1: Significant wave height measurement from Buoy at Station S1, units: m</p> <p>Buoy_time_S1: Measurement time of Buoy at Station S1, time zone: LST</p> <p>Buoy_tpeak_S1: Peak wave period measurement from Buoy at Station S1, units: s</p> <p>OBS_SSC_S1: Suspended sediment concentration measurement from OBS at Station S1, units: g/L</p> <p>OBS_time_S1: Measurement time of OBS at Station S1, time zone: LST</p> <p>tauc_mtke_S1: In-situ bottom shear stress calculated from turbulence kinetic energy method, units: Pa</p> <p>time_mtke_S1: Time of calculated bottom shear stress, time zone: LST</p> <p>time_wind: Time of surface wind at S1 from CFSv2 model from 2019-06-01 to 2019-08-01 time zone: LST</p> <p>u_wind: Eastward velocity of surface wind at S1 from CFSv2 model, units: m/s</p> <p>v_wind: Northward velocity of surface wind at S1 from CFSv2 model, units: m/s</p>
Modulation of Cyclones with Tropical and Extratropical Origins by Mesoscale SSTs in the Kuroshio Extension Region
<p>Datasets for <strong>Modulation of Cyclones with T</strong><strong>ropical and Extratropical </strong><strong>Origins </strong><strong>by Mesoscale SSTs in the Kuroshio Extension Region.</strong></p>
E3SM simulations to assess the projected changes in tropical cyclone activity during active and inactive North Atlantic hurricane seasons
<p>This dataset compiles the results of high resolutions E3SM experiments performed to assess the projected changes in the North Atlantic tropical cyclone activity in a warming climate. The results of these experiments are currently in revision under the title "<strong>Future Changes in Active and Inactive Atlantic Hurricane Seasons in the Energy Exascale Earth System Model</strong>" </p> <p>The file tracks_teca.zip compiles the TC tracks detected in the experiments, using the Toolkit for Extreme Climate Analysis (TECA), available at https://teca.readthedocs.io/en/latest/applications.html#teca-tc-stats</p> <p>GPI_LaNinaAMMp.zip and GPI_ElNinoAMMn.zip includes the genesis potential index and its components for each of the experiments.</p> <p>For further information, please contact the author at anasena@iastate.edu</p> <p>Acknowledgements:</p> <p><strong>This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, operated under Contract No. DE-AC02-05CH11231. E3SM simulations were performed using BER Earth System Modeling program’s Compy computing cluster located at Pacific Northwest National Laboratory. PNNL is operated by Battelle for the U.S. Department of Energy under Contract DE-AC05-76RL01830. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (BER), Earth and Environmental Systems Modeling (EESM) Program, under Early Career Research Program Award Number DE‐SC0021109.</strong></p>
Figure 5 in Biofouling hydroids (Cnidaria: Hydrozoa) from a Tropical Eastern Pacific island, with remarks on their biogeography
Figure 5. Leptothecata: Phialellidae, Cirrholovenia, Clytiidae. (a) Phialellidae (undetermined): three hydrothecae and pedicels, #240565. (b) Cirrholovenia tetranema: two hydrothecae and stolons, and a nematotheca, #240629. (c) Clytia brevithecata: hydrotheca and distal end of pedicel, #240600. (d) Clytia brevithecata: proximal end of pedicel and stolon, #240600. (e) Clytia linearis: hydrotheca and distal end of pedicel, #307693. (f) Clytia linearis: gonotheca, #307693. (g) Clytia obliqua: hydrotheca and distal end of pedicel, #240629. (h) Clytia obliqua: hydrotheca and distal end of pedicel, #253541. (i) Clytia obliqua: gonotheca, #253541. (j) Clytia obliqua: gonotheca, #240629. Scale bars: a, c–j = 0.1 mm; b = 0.05 mm.
Figure 4 in Biofouling hydroids (Cnidaria: Hydrozoa) from a Tropical Eastern Pacific island, with remarks on their biogeography
Figure 4. Eudendriidae. Eudendrium cf. certicaule, nematocysts. (a) microbasic eurytele, small, #240636. (b) microbasic eurytele, small, #240566. (c) microbasic eurytele, large, #240637. (d)?microbasic mastigophore, 240634. (e), haploneme, #240566. (f) haploneme, h#240566.
Figure 7 in Biofouling hydroids (Cnidaria: Hydrozoa) from a Tropical Eastern Pacific island, with remarks on their biogeography
Figure 7. Leptothecata: Halopterididae and Aglaopheniidae. (a) Halopteris alternata: part of hydrocaulus with a hydrotheca (stippled), nematothecae and base of a cladium, #240555. (b) Halopteris alternata: part of a hydrocladium with two hydrothecae and nematothecae, #240555. (c) Macrorhynchia philippina: part of a cladium with two hydrothecae and nematothecae, #266335. Scale bars: 0.1 mm.
ScienceDex guides
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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.