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148 results for “coastal habitats”
FIGURE 6 in Four new species of the subterranean amphipod genus Stygobromus (Amphipoda: Crangonyctidae) from shallow groundwater habitats on the Coastal Plain and eastern margin of the Piedmont in Maryland and Virginia, USA
FIGURE 6. Stygobromus felleri, sp. n. Funks Pond Spring, Cecil County, Maryland.Paratype male (4.0–4.5 mm): (a, b) gnathopods 1, 2 (palmar margins enlarged). Gnathopods drawn to larger scale than antennae.
Dataset from: Parapatric and sympatric adaptation of Setaria viridis populations in Japan to heterogeneous coastal habitats via trait divergence of plant form, salt spray tolerance and flowering time
<p>This study aimed to determine how coastal variants of<em> </em>plants arise from local populations under natural selection by studying variations in phenotypic variations and survival of <em>Setaria viridis</em> populations inhabiting mosaic environments of two seashores in Japan. <em>S.viridis</em> populations comprised five coastal variants showing significantly higher salt spray tolerance than the inland variant: ST, short and tolerant (common variant); TM, tall and mid-tolerant (Inland Sea); TT, tall and tolerant; PT, prostrate and tolerant; L, extremely late flowering; I, inland and susceptible variants. These variations imply that maritime plants first acquired salt spray tolerance for survival, after which compact plants evolved in habitats where strong winds caused damage from salt spray. Results indicate that diverse intensities of salt spray and winds as well as summer drought generated various coastal variations in parapatry and sympatry.</p>
Habitat mapping of coastal dunes with deep learning - Scripts & Data
<p><strong>Authors</strong>: Eva M. Lansu, Valérie C. Reijers, Freek Daniëls, Rebecca James, Marjolijn J. A. Christianen, Tjisse van der Heide</p> <p> </p> <p><strong>Abstract</strong></p> <p><span lang="EN-GB">About one-third of the world's shoreline is defined by sandy coasts with developed dune ecosystems</span><span lang="EN-GB">. </span><span lang="EN-GB">These ecosystems </span><span lang="EN-GB">drastically degraded them due to anthropogenic pressures. </span><span lang="EN-GB">To develop strategic management that counteracts this degradation, it is essential to closely monitor ongoing habitat changes.</span><span lang="EN-GB"> Traditionally, coastal dune monitoring is based on field observations, which are labour intensive and costly. While automated analyses of aerial imagery could reduce monitoring efforts and enhance spatial coverage, t</span><span lang="EN-GB">o date, its application </span><span><span lang="EN-GB">has </span></span><span><span lang="EN-GB">remained limited to a single small-scale trial (<2 km</span></span><span><sup><span lang="EN-GB">2</span></sup></span><span><span lang="EN-GB">). </span></span><span><span lang="EN-GB">Here, we trained a Convolutional Neural Network to map the Dutch coastal dunes </span></span><span><span lang="EN-GB">(562 km<sup>2</sup>) </span></span><span><span lang="EN-GB">at 25 cm resolution using six habitat classes: bare sand, shrubs, fresh water, grass, broadleaf trees, and needleleaf trees. </span></span><span lang="EN-GB">Training the network on only RGB imagery resulted in predictions with 92% accuracy, 80% average recall and 70% precision. Model performance increased when the network was trained on all available data - RGB imagery, near-infrared, distance to sea, digital surface model, and canopy height - resulting in 95% accuracy, 88% averaged recall and 80% precision. Finally, we compared the predictions with 499 in-field observations across the Dutch coastal dunes and found 88% accuracy, 74% averaged recall and 62% precision. We used this model to create a map of the entire Dutch coastal dunes, which enables </span><span lang="EN-GB">rapid and precise </span><span lang="EN-GB">assessments of habitat diversity and extent</span><span lang="EN-GB">. As habitat and species diversity are intrinsically linked, our results showcase how automated image analysis can enable biodiversity monitoring on a national scale. </span></p> <p>==============================================</p> <p><strong>Methods</strong></p> <p>The analyses rely on the following datasets:</p> <ul> <li>Orthophoto mosaics including a near-infrared band (from <u><a href="http://geotiles.nl/">http://geotiles.nl/</a></u>)</li> <li>Digital surface model and a digital terrain model (from <a href="https://www.ahn.nl/">https://www.ahn.nl/</a>)</li> <li>A land-use map (from <u><a href="https://lgn.nl/basiskaart">https://lgn.nl/basiskaart)</a></u></li> </ul>
FIGURE 4 in Overlooked coastal habitats expose a new species: Ochthebius vilanovensis sp. nov. (Coleoptera, Hydraenidae)
FIGURE 4. Distribution map (A) and habitat of Ochthebius vilanovensisis sp. nov. (B and C) plus the known localities of Ochthebius evae Villastrigo, Hernando, Millán & Ribera, 2020 in Spain (red dots in Figure 3A).
FIGURE 1 in Overlooked coastal habitats expose a new species: Ochthebius vilanovensis sp. nov. (Coleoptera, Hydraenidae)
FIGURE 1. Selected Bayesian analysis of the subgenus Cobalius. White circles on nodes for support values higher than 0.95. Blue branches represent the Ochthebius biltoni species group.
FIGURE 3 in Overlooked coastal habitats expose a new species: Ochthebius vilanovensis sp. nov. (Coleoptera, Hydraenidae)
FIGURE 3. Comparison of the male genitalia of Ochthebius evae Villastrigo, Hernando, Millán & Ribera, 2020 (A and C) and Ochthebius vilanovensis sp. nov. (B and D).
FIGURE 2 in Overlooked coastal habitats expose a new species: Ochthebius vilanovensis sp. nov. (Coleoptera, Hydraenidae)
FIGURE 2. Ochthebius vilanovensis sp. nov.: (A) male habitus, (B) female habitus and (C) aedeagus in lateral view.
Subspecies and Distribution. S. s. scrofa Linnaeus, 1758 — W Europe, from Denmark, Germany, Poland, and Czech Republic to N Italy and N Iberian Peninsula; possibly also Albania. The taxonomic status of animals in Austria, Switzerland, Slovenia, and Slovakia is unclear but presumably these populations are included in scrofa, as are the populations of Sweden, Finland, and the Baltic states. However, restocking of once depleted populations, for example in Italy, has likely involved the introduction and mixing of this subspecies with other subspecies, such as attila. S. s. affinis Gray, 1847 — S India and Sri Lanka. S. s. algirus Loche, 1867 — Tunisia, Algeria, and Morocco, on the coastal side of the mountains or in the low montane areas. S. s. attila Thomas, 1912 — Hungary, Ukraine, C & S Belarus, Romania, Moldova, and S Russia towards the N flank of the Caucasus, but not including the Transcaucasian countries of Georgia, Armenia, and Azerbaijan. The range possibly extends as far S as the Mesopotamian Delta in Iraq, in which case it would likely include W & SW Iran, and possibly E Turkey and Syria, where it borders with lybicus. Such a range could not be easily reconciled with a statement by Groves that "the difference between pigs from N and S of the Caucasus is quite striking; Transcaucasian boars are certainly not attila." This subspecies may also extend into C Asia and include Kazakhstan, Uzbekistan, and Turkmenistan, but no data exist to support this. S. s. baeticus Thomas, 1912 — originally described from Coto Donana, S Spain, and later merged with meridionalis; also S Portugal. Unless evidence is found that these Italian and Iberian populations are the relics of a much larger formerly contiguous range, this subspecies should be kept as distinct. S. s. coreanus Heude, 1897 — Korean Peninsula. S. s. eristatus Wagner, 1839 — Himalayas S to C India and E to Indochina (N of the Kra Isthmus). S. s. davidi Groves, 1981 — the arid zone from E Iran to Gujarat, including Pakistan and NW India, and perhaps N to Tajikistan. S. s. leucomystax Temminck, 1842 — main Is ofJapan (Honshu, Shikoku, Kyushu, Nakadori, Hiburijima, Tojima, Kushima, and other smaller Is). S. s. lybicus Gray, 1868 — Bulgaria, Greece, Turkey, Syria, Jordan, Israel, Palestine, in the past also in Lybia, and Egypt. The former Yugoslavia was included in its range, which would suggest that now Slovenia, Serbia, Croatia, Bosnia and Herzegovina, Montenegro, and Kosovo are within the range of this subspecies, although the exact boundaries are unclear. Pigs from Albania have been assigned to S. s. scrofa. S. s. majori De Beaux & Festa, 1927 — C & S Italian Peninsula. S. s. menidionalis Forsyth Major, 1882 — Corsica and Sardinia, with the proviso that the two populations are very likely to be introduced or feral. S. s. moupinensis Milne-Edwards, 1871 — China, S to Vietnam and W to Sichuan. S. s. nigripes Blanford, 1875 — the flanks of the Tianshan mountains in Kyrgyzstan and NW China (Xinjiang). An animal photographed in NE Iran (Golestan) looked like this subspecies. S. s. nukiuanus Kuroda, 1924 — Iriomote, Ishigaki, Okinawa, Tokunoshima, Amamioshima, and Kakerome Is in the Ryukyu chain in extreme S Japan, though some of these populations have hybridized with introduced domesticates. S. s. sibiricus Staffe, 1922 — Mongolia and Transbaikal (S & E of Lake Baikal). S. s. tawvanus Swinhoe, 1863 — Taiwan. S. s. ussuricus Heude, 1888 — far E Russia and the Manchurian region (China). Korean populations were previously included in this subspecies, but based on new evidence, the Korean taxon seems more similar to moupinensis. S. s. vittatus Boie, 1828 — Malay Peninsula, S of the Isthmus of Kra, the offshore islands of Terutai and Langkawi, Sumatra, Riau Archipelago, Java, Bali, and a range of smaller islands around these, including Babi, Bakong, Batam, Bawean, Bengkalis, Bintan, Bulan, Bunguran, Cuyo, Deli, Durian, Enggano, Galang, Jambongan, Karimon (Riau Is), Kundur, Lagong, Laut, Lingga, Lingung, Mapor, Moro Kecil, North Pagai, Nias, Panaitan, Payong, Penang, Pinie, Rupat, Siantan, Siberut, Simeulue, Singkep, Sugi, Sugi Bawa, Telibon, Tinggi, Tuangku, and the Tambelan Is. This species was originally present from the British Is in the extreme W, through Eurasia from S Scandinavia to S Siberia, extending as far E as Korea and Japan, and SE into some of the Sunda Is and Taiwan. In the S the species ranged along the Nile Valley to Khartoum, and N of the Sahara in Africa, more orless following the continental coasts of S, E, and SE Asia. Within this range it was absent only from extremely dry deserts, e.g. the driest regions of Mongolia and in China W of Sichuan; and alpine zones, such as the high altitudes of Pamir and Tien Shan. In recent centuries, the range of S. scrofa has changed dramatically because of hunting and changes in available habitat. The species disappeared from the British Is in the 17" century, from Denmark in the 19" century, and was greatly reduced in range and numbers in the 20" century from areas as distant as Tunisia, Sudan, Germany, and Russia. Following these severe declines, there were some slight population recoveries in Russia, Italy, Spain, and Germany in the mid-20™ century, and natural and assisted range expansions in Denmark and Sweden. The species has also been inadvertently reintroduced in various locations in the Great Britain via escapees of mixed origin from commercial farming enterprises. Ex-S. scrofa stocks also occur as introduced feral populations in various other parts of the world, including Australia, New Zealand, the eastern Malay Archipelago, and in North, Central, and South America. In all of these areas they are now generally recognized as a major pest. in Suidae
Subspecies and Distribution. S. s. scrofa Linnaeus, 1758 — W Europe, from Denmark, Germany, Poland, and Czech Republic to N Italy and N Iberian Peninsula; possibly also Albania. The taxonomic status of animals in Austria, Switzerland, Slovenia, and Slovakia is unclear but presumably these populations are included in scrofa, as are the populations of Sweden, Finland, and the Baltic states. However, restocking of once depleted populations, for example in Italy, has likely involved the introduction and mixing of this subspecies with other subspecies, such as attila. S. s. affinis Gray, 1847 — S India and Sri Lanka. S. s. algirus Loche, 1867 — Tunisia, Algeria, and Morocco, on the coastal side of the mountains or in the low montane areas. S. s. attila Thomas, 1912 — Hungary, Ukraine, C & S Belarus, Romania, Moldova, and S Russia towards the N flank of the Caucasus, but not including the Transcaucasian countries of Georgia, Armenia, and Azerbaijan. The range possibly extends as far S as the Mesopotamian Delta in Iraq, in which case it would likely include W & SW Iran, and possibly E Turkey and Syria, where it borders with lybicus. Such a range could not be easily reconciled with a statement by Groves that "the difference between pigs from N and S of the Caucasus is quite striking; Transcaucasian boars are certainly not attila." This subspecies may also extend into C Asia and include Kazakhstan, Uzbekistan, and Turkmenistan, but no data exist to support this. S. s. baeticus Thomas, 1912 — originally described from Coto Donana, S Spain, and later merged with meridionalis; also S Portugal. Unless evidence is found that these Italian and Iberian populations are the relics of a much larger formerly contiguous range, this subspecies should be kept as distinct. S. s. coreanus Heude, 1897 — Korean Peninsula. S. s. eristatus Wagner, 1839 — Himalayas S to C India and E to Indochina (N of the Kra Isthmus). S. s. davidi Groves, 1981 — the arid zone from E Iran to Gujarat, including Pakistan and NW India, and perhaps N to Tajikistan. S. s. leucomystax Temminck, 1842 — main Is ofJapan (Honshu, Shikoku, Kyushu, Nakadori, Hiburijima, Tojima, Kushima, and other smaller Is). S. s. lybicus Gray, 1868 — Bulgaria, Greece, Turkey, Syria, Jordan, Israel, Palestine, in the past also in Lybia, and Egypt. The former Yugoslavia was included in its range, which would suggest that now Slovenia, Serbia, Croatia, Bosnia and Herzegovina, Montenegro, and Kosovo are within the range of this subspecies, although the exact boundaries are unclear. Pigs from Albania have been assigned to S. s. scrofa. S. s. majori De Beaux & Festa, 1927 — C & S Italian Peninsula. S. s. menidionalis Forsyth Major, 1882 — Corsica and Sardinia, with the proviso that the two populations are very likely to be introduced or feral. S. s. moupinensis Milne-Edwards, 1871 — China, S to Vietnam and W to Sichuan. S. s. nigripes Blanford, 1875 — the flanks of the Tianshan mountains in Kyrgyzstan and NW China (Xinjiang). An animal photographed in NE Iran (Golestan) looked like this subspecies. S. s. nukiuanus Kuroda, 1924 — Iriomote, Ishigaki, Okinawa, Tokunoshima, Amamioshima, and Kakerome Is in the Ryukyu chain in extreme S Japan, though some of these populations have hybridized with introduced domesticates. S. s. sibiricus Staffe, 1922 — Mongolia and Transbaikal (S & E of Lake Baikal). S. s. tawvanus Swinhoe, 1863 — Taiwan. S. s. ussuricus Heude, 1888 — far E Russia and the Manchurian region (China). Korean populations were previously included in this subspecies, but based on new evidence, the Korean taxon seems more similar to moupinensis. S. s. vittatus Boie, 1828 — Malay Peninsula, S of the Isthmus of Kra, the offshore islands of Terutai and Langkawi, Sumatra, Riau Archipelago, Java, Bali, and a range of smaller islands around these, including Babi, Bakong, Batam, Bawean, Bengkalis, Bintan, Bulan, Bunguran, Cuyo, Deli, Durian, Enggano, Galang, Jambongan, Karimon (Riau Is), Kundur, Lagong, Laut, Lingga, Lingung, Mapor, Moro Kecil, North Pagai, Nias, Panaitan, Payong, Penang, Pinie, Rupat, Siantan, Siberut, Simeulue, Singkep, Sugi, Sugi Bawa, Telibon, Tinggi, Tuangku, and the Tambelan Is. This species was originally present from the British Is in the extreme W, through Eurasia from S Scandinavia to S Siberia, extending as far E as Korea and Japan, and SE into some of the Sunda Is and Taiwan. In the S the species ranged along the Nile Valley to Khartoum, and N of the Sahara in Africa, more orless following the continental coasts of S, E, and SE Asia. Within this range it was absent only from extremely dry deserts, e.g. the driest regions of Mongolia and in China W of Sichuan; and alpine zones, such as the high altitudes of Pamir and Tien Shan. In recent centuries, the range of S. scrofa has changed dramatically because of hunting and changes in available habitat. The species disappeared from the British Is in the 17" century, from Denmark in the 19" century, and was greatly reduced in range and numbers in the 20" century from areas as distant as Tunisia, Sudan, Germany, and Russia. Following these severe declines, there were some slight population recoveries in Russia, Italy, Spain, and Germany in the mid-20™ century, and natural and assisted range expansions in Denmark and Sweden. The species has also been inadvertently reintroduced in various locations in the Great Britain via escapees of mixed origin from commercial farming enterprises. Ex-S. scrofa stocks also occur as introduced feral populations in various other parts of the world, including Australia, New Zealand, the eastern Malay Archipelago, and in North, Central, and South America. In all of these areas they are now generally recognized as a major pest.
Combining population genomics with demographic analyses highlights habitat patchiness and larval dispersal as determinants of connectivity in coastal fish species
<p>Gene flow shapes spatial genetic structure as well as the potential for local adaptation of populations. Among marine animals with non-migratory adults, the presence or absence of a pelagic larval stage is thought to be a key determinant in shaping gene flow and the genetic structure of populations. In addition, the spatial distribution of suitable habitats will influence the distribution of biological populations and their pattern of gene flow. We used whole genome sequencing to study demographic history and reduced representation (ddRAD) sequencing data to analyze spatial genetic structure in the broadnosed pipefish (<em>Syngnathus typhle</em>). Its main habitat are seagrass meadows, which along the study coast (SW Norway) have a patchy distribution. Combining the results from several analyses including scans for selection, suggests that stochastic genetic drift has shaped the observed population structure largely due to its patchy habitat distribution. The restricted gene flow is further driven by life history traits such as the presence of parental care combined with no pelagic life stages, resulting in a clear isolation-by-distance pattern spanning 100s of kilometers.</p> <p>The spatial scale of demographic connectivity was inferred from long-term (~30 year) census population counts that uncovered a sharp decline in spatial correlations in abundance with distance (37% decorrelation over 2 km). These findings were contrasted with data from two other fish species sampled along the same coastline, both having pelagic larval stages lasting ~20 days (corkwing wrasse, <em>Symphodus melops</em>, and black goby, <em>Gobus niger</em>) where the population structure is not that evident. For these species, we found a wider spatial scale of demographic connectivity (decorrelation distances of 14 and 28 km, respectively), and weaker isolation-by-distance except at one point along the coast where both species revealed a strong barrier to gene flow, seemingly due to a lack of suitable habitat. Combined, these findings suggest that habitat fragmentation and absence of a pelagic larval stage in pipefish strongly increases geographic structuring, while the pelagic larvae of wrasse and goby increase genetic and demographic connectivity, except over extensive habitat shifts.</p>
Data from: Habitat fragmentation in coastal southern California disrupts genetic connectivity in the Cactus Wren (Campylorhynchus brunneicapillus)
Achieving long-term persistence of species in urbanized landscapes requires characterizing population genetic structure to understand and manage the effects of anthropogenic disturbance on connectivity. Urbanization over the past century in coastal southern California has caused both precipitous loss of coastal sage scrub habitat and declines in populations of the cactus wren (Campylorhynchus brunneicapillus). Using 22 microsatellite loci, we found that remnant cactus wren aggregations in coastal southern California comprised 20 populations based on strict exact tests for population differentiation, and 12 genetic clusters with hierarchical Bayesian clustering analyses. Genetic structure patterns largely mirrored underlying habitat availability, with cluster and population boundaries coinciding with fragmentation caused primarily by urbanization. Using a habitat model we developed, we detected stronger associations between habitat-based distances and genetic distances than Euclidean geographic distance. Within populations, we detected a positive association between available local habitat and allelic richness and a negative association with relatedness. Isolation-by-distance patterns varied over the study area, which we attribute to temporal differences in anthropogenic landscape development. We also found that genetic bottleneck signals were associated with wildfire frequency. These results indicate that habitat fragmentation and alterations have reduced genetic connectivity and diversity of cactus wren populations in coastal southern California. Management efforts focused on improving connectivity among remaining populations may help to ensure population persistence.
Distribution. SE Australia: coastal habitats up to 100 km inland in SE Queensland, E New South Wales, SE Victoria, and Tasmania, including Flinders I and Three Hummock I. in Muridae
Distribution. SE Australia: coastal habitats up to 100 km inland in SE Queensland, E New South Wales, SE Victoria, and Tasmania, including Flinders I and Three Hummock I.
Supplementary material 1 from: Lazzarini Wolff L, Segatti Hahn N (2017) Fish habitat associations along a longitudinal gradient in a preserved coastal Atlantic stream, Brazil. Zoologia 34: 1-13. https://doi.org/10.3897/zoologia.34.12975
Figure S1. Hydrological and structural characteristics of the sampling reaches of the Vermelho River, state of Paraná, Brazil : Data type: specimens data
FIGURE 9 in New records of cotylean flatworms (Platyhelminthes: Polycladida: Rhabditophora) from coastal habitats of Israel
FIGURE 9. Maritigrella fuscopunctata. (A) Dorsal view, in vivo. (B) Ventral view of the live specimen showing the pharynx and sucker. (C) Close-up of the anterior region showing the marginal tentacles and cerebral eyes. ce: cerebral eyes; ph: pharynx; pt: pseudotentacles; su: sucker.
FIGURE 8 in New records of cotylean flatworms (Platyhelminthes: Polycladida: Rhabditophora) from coastal habitats of Israel
FIGURE 8. Pericelis byerleyana. (A) Dorsal view, in vivo. (B) Ventral view of the live specimen showing the pharynx, uteri, and sucker. (C) Close-up of the anterior region showing the pseudoentacles and the cerebral, pre-cerebral, and marginal eyes; ce: cerebral eyes; me: marginal eyes; mt: marginal tentacles; pe: pre-cerebral eyes; ph: pharynx; su: sucker; u: uteri.
FIGURE 7 in New records of cotylean flatworms (Platyhelminthes: Polycladida: Rhabditophora) from coastal habitats of Israel
FIGURE 7. Thysanozoon brocchii. (A, B) Dorsal view, in vivo showing color variation. (C) Close-up of the anterior region showing the pseudotentacles and the pseudotentacular and cerebral eyes. (D) Close- up of the ventral view of a preserved specimen showing the pharynx, reproductive structures, and sucker. ce: cerebral eyes; fg: female gonopore; mg: male gonopore; pe: pseudotentacular eyes ph: pharynx; pt: pseudotentacles; su: sucker; u: uteri.
FIGURE 6 in New records of cotylean flatworms (Platyhelminthes: Polycladida: Rhabditophora) from coastal habitats of Israel
FIGURE 6. Pseudobiceros stellae. (A) Dorsal view, in vivo. (B) Ventral view of the live specimen showing the pharynx, reproductive structures, and sucker. (C) Close-up of the anterior region showing the pseudotentacles and cerebral eyes. Inset showing the shape of the cerebral eyespot. Scale bar: 1mm. ce: cerebral eyes; fg: female gonopore; mg: male gonopore; ph: pharynx; pt: pseudotentacles; su: sucker.
FIGURE 5 in New records of cotylean flatworms (Platyhelminthes: Polycladida: Rhabditophora) from coastal habitats of Israel
FIGURE 5. Pseudobiceros murinus. (A, B) Dorsal and ventral view, in vivo. (C) Close-up of the anterior region of a preserved animal showing the pseudotentacles, pseudotentacular eyes, and cerebral eyes. (D) Close-up of the ventral side of a preserved animal showing the pharynx, reproductive structures, and sucker. ce: cerebral eyes; fg: female gonopore; mg: male gonopore; pe: pseudotentacular eyes; ph: pharynx; pt: pseudotentacles; su: sucker; u: uteri.
FIGURE 4 in New records of cotylean flatworms (Platyhelminthes: Polycladida: Rhabditophora) from coastal habitats of Israel
FIGURE 4. Pseudobiceros damawan. (A) Dorsal view, in vivo. (B) Close-up of the anterior region showing the pseudotentacles and cerebral eyes. (C) Ventral view of the live specimen showing the pharynx, sucker, and the reproductive structures. ce: cerebral eyes; fg: female gonopore; mg: male gonopore; ph: pharynx; pt: pseudotentacles; su: sucker.
FIGURE 3 in New records of cotylean flatworms (Platyhelminthes: Polycladida: Rhabditophora) from coastal habitats of Israel
FIGURE 3. Pseudobiceros apricus. (A) Dorsal view, in vivo. (B) Close-up of the anterior region in a preserved animal showing the pseudotentacles and cerebral eyes. (C) Ventral view of the preserved specimen showing the pharynx, reproductive structures, and sucker. ce: cerebral eyes; fg: female gonopore; m: mouth; mg: male gonopore; ph: pharynx; pt: pseudotentacles; su: sucker.
FIGURE 2 in New records of cotylean flatworms (Platyhelminthes: Polycladida: Rhabditophora) from coastal habitats of Israel
FIGURE 2. Pseudoceros duplicinctus. (A) Dorsal view, in vivo. (B) Ventral view of the live specimen showing the reproductive structures and sucker. (C) Close-up of the anterior region showing the pseudotentacles, pseudotentacular eyes and cerebral eyes. ce: cerebral eyes; fg: female gonopore; mg: male gonopore; pe: pseudotentacular eyes; pt: pseudotentacles; su: sucker.
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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.