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174 results for “seahorse”
Seahorse Dockers School
<p>The documentary video on grassroot primary school - Seahorse Dockers School in Seahorse Village, Kilifi County, founded by Mramba Mweni and Saidi Chengo - where TPAAE researchers are conducting workshops in visual education, supporting the development of children's creativity in intercultural dialogue.</p>
Home range use in the West Australian seahorse Hippocampus subelongatus is influenced by sex and partner’s home range but not by body size or paired status
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Fig. 3 in A New Pygmy Seahorse (Pisces: Syngnathidae: Hippocampus) from Lord Howe Island
Fig. 3. Hippocampus colemani, this specimen not collected, sex not determined. The single gill
Granite Seahorse
**About the sculpture**  This sculpture, created in 1989 by Patrig Ar Goarnig and Lucien Crenn, is located near the cove of "Porz Ar Streat" in Plouescat, in France. For those of you who prefer Google Maps, you'll find it [here](https://goo.gl/maps/ESzuX8LEXkx) ;) It represents a Seahorse, which tail is wrapped around a sleeping cat on one side, and a Yin-Yang symbol on the other. **Process**  The scan was made from 140 pictures (the last of them under a heavy rain), reconstructed with Colmap and OpenMVS and optimized to a lowpoly version (10k triangles) with Blender and [BakeMyScan](http://bakemyscan.org). I also used a weight-painted metric for the retopology to keep the important details: do not hesitate to check the wireframe view. Finally, and due to parts of the statue being wet, I also decided to ditch the computed albedo map and used a mix of granite PBR textures instead. Source: Objaverse 1.0 / Sketchfab
Elastic energy storage in seahorses leads to a unique suction flow dynamics compared to other actinopterygian
<p></p><p>Suction feeding is a dominant prey-capture strategy across actinopterygians, consisting of a rapid expansion of the mouth cavity that drives a flow of water containing the prey into the mouth. Suction feeding is a power-hungry behavior, involving the actuation of cranial muscles as well as the anterior third of the fish's swimming muscles. Seahorses, which have reduced swimming muscles, evolved a unique mechanism for elastic energy storage that powers their suction flows. This mechanism allows seahorses to achieve head rotation speeds that are 50 times faster than fish lacking such a mechanism. However, it is unclear how the dynamics of suction flows in seahorses differ from the conserved pattern observed across other actinopterygians, nor how differenced in snout length across seahorses affect these flows. Using flow visualization experiments, we show that seahorses generate suction flows that are 8 times faster than similar-sized fish, and that the temporal patterns of cranial kinematics and suction flows in seahorses differs from the conserved pattern observed across other actinopterygians. However, the spatial patterns retain the conserved actinopterygian characteristics, where suction flows impact a radially symmetric region of ∼1 gape diameter outside the mouth. Within seahorses, increases in snout length were associated with slower suction flows and faster head rotation speeds, resulting in a trade-off between pivot feeding and suction feeding. Overall, this study shows how the unique cranial kinematics in seahorses are manifested in their suction feeding performance, and highlights the trade-offs associated with their unique morphology and mechanics.</p><p></p>
A power amplification dyad in seahorses
<p><span>Throughout evolution, organisms repeatedly developed elastic elements to power explosive body motions, overcoming ubiquitous limits on the power capacity of fast-contracting muscles. Seahorses evolved such a latch-mediated spring actuation (LaMSA) mechanism; however, it is unclear how this mechanism powers the two complementary functions necessary for feeding: rapidly swinging the head towards the prey, and sucking water into the mouth to entrain it. Here, we combine flow visualization and hydrodynamic modeling to estimate the net power required for accelerating the suction-feeding flows in 13 fish species. We show that the mass-specific power of suction feeding in seahorses is ~3 times higher than the maximum recorded from any vertebrate muscle, resulting in suction flows that are ~8 times faster than similar-sized fish. Using material testing, we reveal that the rapid contraction of the sternohyoideus tendon can release ~72% of the power needed to accelerate the water into the mouth. We conclude that the LaMSA system in seahorses is powered by two elastic elements, the sternohyoideus and epaxial tendons. These elements jointly actuate the coordinated acceleration of the head and the fluid in front of the mouth. These findings extend the known function, capacity, and design of LaMSA systems.</span></p>
Database underlying the scientific publication: A global database of seahorse research and innovation, from the beginning to 2022
<p>The present database supports the study "A global database of seahorse research and innovation, from the beginning to 2022". </p> <p>Scientific knowledge on seahorses is rapidly expanding in response to declines in wild populations due to habitat loss and fishing. A plethora of information has accumulated and up until now, a global, publicly available, curated database has never been produced in a transparent and systematic way. Here, we present the largest open-access repository of scientific publications addressing seahorses and, for the first time, of theses and patents. Compilation followed the “Preferred Reporting Items for Systematic reviews and Meta-Analyses” (PRISMA) Statement for systematic reviews and meta-analyses, with modifications. The current repository duplicates the number of scientific publication records found from previous bibliometric/literature/review studies, using three extra repositories of source publications, and a lifetime window, <em>e.i</em>. from the beginning to March 2022. A total of 977 scientific publications, 101 theses and 533 patents are gathered in the dataset, covering 41 seahorse species out of 48 currently recognized. In addition, current work presents for the first time new metrics on authors, institutions, and research subject/field/discipline/thematic, as well as the organism’s stage of development (embryo, newborn, juvenile, subadult and adult). To expand metadata usage, the database was also made available in the Dublin Core™ Metadata Initiative format. This contribution can be used as a core reference for scientists, aquaculturists and conservationists, and is useful to rapidly identify relevant literature and knowledge gaps, better understand seahorse research and discover new trends in seahorse research and innovation.</p> <p>The database is available in two formats:</p> <p>1) <a href="https://zenodo.org/api/files/5651b70d-a7a0-45e6-8ce6-cb92bbe6f7e5/SeahorseBibliometricDatabase.xlsx">SeahorseBibliometricDatabase.xlsx</a></p> <p>and</p> <p>2) <a href="https://zenodo.org/api/files/5651b70d-a7a0-45e6-8ce6-cb92bbe6f7e5/SeahorseBibliometricDatabase_DublinCore.xlsx">SeahorseBibliometricDatabase_DublinCore.xlsx</a>, which is a vocabulary standardized (Dublin Core™ Metadata Initiative) version of the previous one, for metadata reuse.</p>
A power amplification dyad in seahorses
Open the record for dataset details and reuse information.
Elastic energy storage in seahorses leads to a unique suction flow dynamics compared to other actinopterygian
Open the record for dataset details and reuse information.
Supplementary material 1 from: Short G, Claassens L, Smith R, De Brauwer M, Hamilton H, Stat M, Harasti D (2020) Hippocampus nalu, a new species of pygmy seahorse from South Africa, and the first record of a pygmy seahorse from the Indian Ocean (Teleostei, Syngnathidae). ZooKeys 934: 141-156. https://doi.org/10.3897/zookeys.934.50924
Genetic distance analysis (uncorrected p distances) of COI sequence data from H. nalu, H. bargibanti, H. denise, H. japapigu, and H. pontohi
Data from: Navigating the southern seas with small fins: Genetic connectivity of seahorses (Hippocampus abdominalis) across the Tasman Sea
Aim Historical patterns of ocean circulation in the Southern Hemisphere have been well studied, but the effects of coastal oceanography on marine biogeography in this region remain poorly understood relative to northern latitudes. Our study investigates historical and contemporary patterns of migration and dispersal across the Tasman Sea. Location Coastal regions of the Tasman Sea including southeastern Australia, Tasmania and New Zealand. Taxon Hippocampus abdominalis, the pot-bellied seahorse, one of the most broadly distributed seahorse species, and the only seahorse to have successfully colonized New Zealand from Australia across 2,000 km of open ocean. Methods We used a multilocus genetic dataset to measure population diversity and differentiation from seahorses across the full species range to investigate contemporary and historical demography, and to reconstruct colonization routes across the Tasman Sea. Results Genetic data indicate that seahorses colonized New Zealand from Australia during the previous interglacial-glacial cycle (12,000-120,000 ybp), and have evolved in relative isolation since the initial establishment event. Contemporary effective population sizes in the newly colonized range are substantially larger than those inferred in Australia, and both appear to be reduced relative to ancestral levels. Australian seahorses are genetically diverse and show high levels of population connectivity, while the distribution of genetic variation in New Zealand suggests an initial colonization of the South Island following by northward migration. Importantly, despite clear evidence that New Zealand seahorses are descendent from Australian ancestors, patterns of contemporary genetic diversity are consistent with trans-Tasman migration from New Zealand to Australia, suggesting that genetic variation accumulated in the newly colonized range is contributing to the genetic diversity of Australian seahorses. Main conclusions Despite a largely independent evolutionary trajectory of seahorses separated by the Tasman Sea, haplotype sharing between populations in Australia and New Zealand suggests that secondary genetic exchange is contributing to the contemporary phylogeography of the species. Patterns of genetic structure in H. abdominalis mirror those found in other rafting species, suggesting that adult dispersal via rafting has been an important vector of marine dispersal in this species.
When more is not merrier: using wild population dynamics to understand the effect of density on ex situ seahorse mating behaviors
Seahorses are one of the most iconic examples of a monogamous species in the animal kingdom. Documenting monogamous behaviors of seahorses have proven to be quite complicated to study in the wild because of their low population densities and cryptic habits. Another challenge involves interpreting these behaviors in captivity because recreating realistic densities of wild populations in the laboratory can be difficult due to their patchy distributions. This study investigates the relationship between stocking density and mating and competitive behavior from the context of the field biology of the dwarf seahorse, Hippocampus zosterae (Jordan & Gilbert). Animals were housed in 38 liter tanks at a range of densities and sex ratios (from 2-8 animals per tank), and their reproductive and other social behaviors were monitored from tank introduction through copulation. At low tank densities and even sex ratios but comparatively high field densities, activity level in trials was low. A higher level of males in tanks across all densities increased competition, activity levels, and aggression leading to partial egg transfers and failed pregnancies, resulting in lower reproductive success. Across seahorse species, mean and maximum wild densities were consistently lower than those used in captive breeding, with adult sex ratios that were significantly female biased. However, significant variation exists in wild seahorse densities across species, with higher densities detected in focal/mark recapture studies and on artificial habitat structures than reported with belt transect sampling techniques. Interchange of knowledge gained in both captive and wild contexts will allow us to better understand the biology of this genus, and improve reproduction in captivity. Interpreting captive reproductive behaviors of seahorses within various densities reported from natural populations will help us predict the impact of conservation efforts and increase the likelihood of long-term persistence of populations for this threatened genus.
Data from: Population genomics reveals seahorses (Hippocampus erectus) of the western mid-Atlantic coast to be residents rather than vagrants
Understanding population structure and areas of demographic persistence and transients is critical for effective species management. However, direct observational evidence to address the geographic scale and delineation of ephemeral or persistent populations for many marine fishes is limited. The Lined seahorse (Hippocampus erectus) can be commonly found in three western Atlantic zoogeographic provinces, though inhabitants of the temperate northern Virginia Province are often considered tropical vagrants that only arrive during warm seasons from the southern provinces and perish as temperatures decline. Although genetics can locate regions of historical population persistence and isolation, previous evidence of Virginia Province persistence is only provisional due to limited genetic sampling (i.e., mitochondrial DNA and five nuclear loci). To test alternative hypotheses of historical persistence versus the ephemerality of a northern Virginia Province population we used a RADseq generated dataset consisting of 11,708 single nucleotide polymorphisms (SNP) sampled from individuals collected from the eastern Gulf of Mexico to Long Island, NY. Concordant results from genomic analyses all infer three genetically divergent subpopulations, and strongly support Virginia Province inhabitants as a genetically diverged and a historically persistent ancestral gene pool. These results suggest that individuals that emerge in coastal areas during the warm season can be considered "local" and supports offshore migration during the colder months. This research demonstrates how a large number of genes sampled across a geographical range can capture the diversity of coalescent histories (across loci) while inferring population history. Moreover, these results clearly demonstrate the utility of population genomic data to infer peripheral subpopulation persistence in difficult-to-observe species.
FIGURE 4 in A new species of seahorse (Teleostei: Syngnathidae) from the South China Sea
FIGURE 4. Map generated by Surfer ® for Windows (Keckler, 1997) showing the sampling locations for the specimen of new seahorse species, H. casscsio sp. nov., along China’s coast. Holotype location indicated by triangle.
FIGURE 3 in A new species of seahorse (Teleostei: Syngnathidae) from the South China Sea
FIGURE 3. Neighbor-joining (NJ) trees based on cytb (a) and CR (b) from seahorses haplotypes of Hippocampus along China's coast.
FIGURE 2 in A new species of seahorse (Teleostei: Syngnathidae) from the South China Sea
FIGURE 2. Comparison of morphological characteristics and body sizes among the three seahorses H. kuda, H. casscsio sp. nov., and H. mohinikei (a), and the principal components analysis (PCA) of the three species according to the morphological data (b).
FIGURE 2 in A new seahorse (Teleostei: Syngnathidae: Hippocampus) from south-western Australia
FIGURE 2. Radiographs of Hippocampus paradoxus holotype (A) and H. minotaur paratype AMS IA.3509 (B).
FIGURE 3 in A new seahorse (Teleostei: Syngnathidae: Hippocampus) from south-western Australia
FIGURE 3. Reconstruction of Hippocampus paradoxus skeleton from CT scan of holotype. Ventrolateral view, showing inferior trunk ridge remnants (A) and anal fin pterygiophores (B).
FIGURE 4 in A new species of seahorse (Teleostei: Syngnathidae) from the South China Sea
FIGURE 4. Map generated by Surfer® for Windows (Keckler, 1997) showing the sampling locations for the specimen of new seahorse species, H. casscsio sp. nov., along China's coast. Holotype location indicated by triangle.
FIGURE 2 in A global revision of the Seahorses Hippocampus Rafinesque 1810 (Actinopterygii: Syngnathiformes): Taxonomy and biogeography with recommendations for further research
FIGURE 2. Range map for Hippocampus abdominalis based on museum specimens, authors' personal observations, and online data from GBIF, FishBase, and iSeahorse. The shaded coastline is a representative visualization of the species' coastal range that extends offshore to 200 m depth (the real range would not be readily visible at this scale as it only extends to the seahorse species' maximum depth—20–40 m or less for most species). Black dots represent author-vetted GBIF data points. Efforts were made to extend the range some distance from the outermost known points, as observed locations are not likely to represent the absolute furthest extent of the range).
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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.