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67 results for “Larval Habitats”

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edi52/100

Larval transport pathways from three prominent sand lance habitats in the Gulf of Maine: otolith data, model data, and post-processed model data products

This dataset includes hatch and larval period for sand lance collected in 2019 and results from particle tracking runs of simulated sand lance larvae throughout the Northeast U.S. Shelf as part of Long-Term Ecological Research (NES-LTER). Release dates vary by region, corresponding to hatch and settlement dates of settling sand lance collected in 2019. Particles were depth-keeping throughout the upper 40 m to best replicate our understanding of the vertical distribution of sand lance larvae. Data were used to determine the average particle transport pathways from these sand lance habitats, including connectivity among the three hotspots, and spatial variability of connectivity within each hotspot. Further information can be found within the manuscript: Suca, J. J., Ji, R., Baumann, H., Pham, K., Silva, T. L., Wiley, D. N., Feng, Z., & Llopiz, J. K. (2022). Larval transport pathways from three prominent sand lance habitats in the Gulf of Maine. Fisheries Oceanography, 31( 3), 333-352. https://doi.org/10.1111/fog.12580

openCC (other)Jun 2022View details →
zenodo40/100

Fig. 3 in Diversity Of Mosquitoes (Diptera, Culicidae) And Physico-Chemical Characterization Of Their Larval Habitats In Tizi-Ouzou Area, Algeria

Fig. 3. Mosquito breeding sites (site 01, a; site 02, b; site 03, c; site 04, d; site 05, e; site 06, f); site 07, g).

opencc-by-4.0Dec 2021View details →
zenodo40/100

"LARVAL FISH HABITATS AND DEOXYGENATION IN THE NORTHERN LIMIT OF THE OXYGEN MINIMUM ZONE OFF MEXICO"

<p>Dataset associated with the submitted publication - &quot;LARVAL FISH HABITATS AND DEOXYGENATION IN THE NORTHERN LIMIT OF THE OXYGEN MINIMUM ZONE OFF MEXICO&quot;</p> <p>Created: 10/10/2019 by Victor M. God&iacute;nez (CICESE). Ver. 1.0</p> <p>Authors: Laura S&aacute;nchez-Velasco, Victor M. God&iacute;nez, Erick D. Ruvalcaba-Aroche, Amaru M&aacute;rquez-Artavia, Emilio Beier, Eric D. Barton and S. Patricia A. Jim&eacute;nez-Rosenberg.<br> Project_info: This data base has been obtained during the project funded by the financial support of SEP-CONACyT (contracts 2014-236864, L. Sanchez-Velasco) and Fronteras de la Ciencia-CONACyT (contracts 2015-2-280, L. Sanchez-Velasco).<br> License: The authors appreciate that users of these data: 1) Contact Laura S&aacute;nchez-Velasco (lsvelasc@gmail.com) to follow the uses of the data, and 2) Include the requested acknowledgment (cite using the DOI of this dataset) in any presentations or publications.</p> <p>Variables:<br> five structures for the four surveys&nbsp; (Survey_Feb2010, Survey_Apr2012, Survey_Jun2015, Survey_Mar2016, Survey_Oct2017)&nbsp; with the following variables:<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Name&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Units<br> &nbsp;&nbsp;&nbsp; ___________&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ________<br> &nbsp;&nbsp;&nbsp; &#39;Latitude&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;degrees&#39;<br> &nbsp;&nbsp;&nbsp; &#39;Longitude&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;degrees&#39;<br> &nbsp;&nbsp;&nbsp; &#39;XX&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;Distance (km)&#39;<br> &nbsp;&nbsp;&nbsp; &#39;YY&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;Distance (m)&#39;<br> &nbsp;&nbsp;&nbsp; &#39;Pressure&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;decibars&#39;<br> &nbsp;&nbsp;&nbsp; &#39;Temperature&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;conservative temperature (oC)&#39;&nbsp; &nbsp;<br> &nbsp;&nbsp;&nbsp; &#39;Salinity&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;Absolute Salinity (g/Kg)&#39;<br> &nbsp;&nbsp;&nbsp; &#39;Oxigen&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;dissolved oxygen (mL/L)&#39;<br> &nbsp;&nbsp;&nbsp; &#39;Fluorescence&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;(mg/m^3)&#39;<br> &nbsp;&nbsp;&nbsp; &#39;xlar&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;Distance (km)&#39;&nbsp; &nbsp;<br> &nbsp;&nbsp;&nbsp; &#39;ylar&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;Distance (m)&#39;<br> &nbsp;&nbsp;&nbsp; &#39;Bb&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;Bregmaceros bathymaster (Larvae/10m^2)&#39;<br> &nbsp;&nbsp;&nbsp; &#39;Bp&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;Benthosema panamense (Larvae/10m^2)&#39;<br> &nbsp;&nbsp;&nbsp; &#39;Dl&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;Diogenichthys laternatus (Larvae/10m^2)&#39;<br> &nbsp;&nbsp;&nbsp; &#39;Asp&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;Auxis spp (Larvae/10m^2)&#39;</p> <p><br> One structures for the oldest data with the following variables:<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Name&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Units<br> &nbsp;&nbsp;&nbsp; ___________&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ________<br> &nbsp;&nbsp;&nbsp; &#39;Latitude&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;degrees&#39;<br> &nbsp;&nbsp;&nbsp; &#39;Longitude&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;degrees&#39;<br> &nbsp;&nbsp;&nbsp; &#39;Time&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;absolute julian day&#39;<br> &nbsp;&nbsp;&nbsp; &#39;Pressure&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;decibars&#39;<br> &nbsp;&nbsp;&nbsp; &#39;Temperature&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;conservative temperature (oC)&#39;&nbsp; &nbsp;<br> &nbsp;&nbsp;&nbsp; &#39;Salinity&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;Absolute Salinity (g/Kg)&#39;<br> &nbsp;&nbsp;&nbsp; &#39;Oxigen&#39;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &#39;dissolved oxygen (mL/L)</p>

opencc-by-4.0Oct 2019View details →
zenodo40/100

Fig. 4 in Characterization of artificial larval habitats of Anopheles darlingi (Diptera: Culicidae) in the Brazilian Central Amazon

Fig. 4. Monthly variation of malaria cases in relation to rainfall in 2011 and 2012 in the dry and rainy season in Manaus.

opencc-by-4.0Aug 2018View details →
zenodo40/100

Fig. 3 in Characterization of artificial larval habitats of Anopheles darlingi (Diptera: Culicidae) in the Brazilian Central Amazon

Fig. 3. Ordering diagram of the canonical correlation analysis (CCA) between environmental factors "limnological parameters" and larval habitat type with Anopheles species: At (Anopheles triannulatus); Aa (Anopheles albitarsis s.l.); Ad (Anopheles darlingi); An (Anopheles nuneztovari); Ao (Anopheles oswaldoi); Ap (Anopheles peryassui); Ab (Anopheles braziliensis); An2 (Anopheles nimbus); Ad2 (Anopheles deaneorum); Ae (Anopheles evansae); DO (dissolved oxygen); NO3 (nitrate); pH (hydrogenionic potential); Temp (temperature); Cond (electrical conductivity); P (phosphorus); TSS (total suspended solids).

opencc-by-4.0Aug 2018View details →
zenodo40/100

Fig. 2 in Characterization of artificial larval habitats of Anopheles darlingi (Diptera: Culicidae) in the Brazilian Central Amazon

Fig. 2. Artificial larval habitats evaluated herein and their local structural characteristics: (A) fish ponds, (B) clay pits and (C) dams.

opencc-by-4.0Aug 2018View details →
zenodo40/100

Fig. 2 in Larval Development And Habitat Usage Of Stream-Breeding Fire Salamanders In An Urban Environment

Fig. 2. Changes in the number of salamander larvae and rainfall. The bold black continuous line shows the mean number of salamander larvae detected during the surveys in the three 10 day intervals of months in Hűvös-ér stream, 2011–2014. The bar graph shows the mean amount (and SD) of precipitation (mm) during the three 10-day intervals of months

opencc-by-4.0Oct 2022View details →
zenodo40/100

Fig. 3 in Larval Development And Habitat Usage Of Stream-Breeding Fire Salamanders In An Urban Environment

Fig. 3. Mean density of salamander larvae (number of larvae/m2) detected in the 16 segments during surveys every 10 days in "Hűvös-ér" stream, 2011–2014 (2011: thin line, 2012:

opencc-by-4.0Oct 2022View details →
zenodo40/100

Fig. 5 in Larval Development And Habitat Usage Of Stream-Breeding Fire Salamanders In An Urban Environment

Fig. 5. Mean number of salamander larvae detected per a year in the "releasing" 2–6 upper segments (continuous bold line), in the "strong collector" middle segments: 7–9 (dashed line) and the "weak collector" lower segments: 10–13 (dotted line) during surveys every 10 days in "Hűvös-ér" stream between 2011–2014. Data from segment 1 have not been plotted because larvae were present at only one time point

opencc-by-4.0Oct 2022View details →
zenodo40/100

Fig. 1 in Larval Development And Habitat Usage Of Stream-Breeding Fire Salamanders In An Urban Environment

Fig. 1. Segments of "Hűvös-ér" stream, where Salamandra salamandra larvae were surveyed. (Numbers indicate individual stream segments, bold meandering line = main branch of the stream, thin branch- ing line = tributaries of the stream, straight lines = segment boundaries, four-pointed stars at segment boundaries and in the stream bed = water steps, double line = main road between Budapest and Solymár, P = "Paprikás"-stream)

opencc-by-4.0Oct 2022View details →
zenodo36/100

Aerial Images_Part 2_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria

<p>Aerial Images_Part 2_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria</p>

opencc-by-4.0Nov 2024View details →
zenodo36/100

Aerial Images_Part 1_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria

<p>Aerial Images_Part 1_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria</p>

opencc-by-4.0Nov 2024View details →
zenodo36/100

Fig. 2 in Diversity Of Mosquitoes (Diptera, Culicidae) And Physico-Chemical Characterization Of Their Larval Habitats In Tizi-Ouzou Area, Algeria

Fig. 2. Study sites location (1— Irdjen; 2 — Ouadhia; 3 — Beni Yenni; 4 — Iboudraren).

opencc-by-4.0Dec 2021View details →
zenodo36/100

Supplemental data for "Investigating the Impact of Irrigation on Malaria Vector Larval Habitats and Transmission using a Hydrology-based Model"

<p>Supplemental data for &quot;Investigating the Impact of Irrigation on Malaria Vector Larval Habitats and Transmission using a Hydrology-based Model&quot;</p>

opencc-by-4.0May 2023View details →
dryad36/100

Heterocypris incongruens maintains an egg bank in stormwater habitats and influences the development of larval mosquito, Culex restuans

<p>Dormant propagules can provide a rapid colonization source for temporary aquatic habitats and set the trajectory for community dynamics, yet the egg banks of stormwater management systems have received little attention. We asked which species hatched from the sediment of drainage ditches in Champaign County, IL, and found bdelloid rotifers and ostracods (<em>Heterocypris incongruens</em>) to be the most common taxa. These sites also are colonized by mosquitoes, and we established laboratory experiments to examine interspecific interactions between common co-occurring taxa. Culex restuans larvae were reared in the presence or absence of <em>H. incongruens</em> at two intra- and interspecific densities (20 or 40 total individuals) and their survivorship to adulthood, development time to adulthood, adult body size, and sex ratio were determined. Survival for Cx. restuans was significantly lower at high larval density than at low larval density in both treatments. Culex restuans larvae reared in the presence of H. incongruens had a shorter development time to adulthood and emerged as larger adults compared to those reared in the absence of <em>H. incongruens</em>. The sex ratios in the <em>H. incongruens</em> treatments were female-biased whereas those in the Culex-only treatments were male-biased. These differences may have epidemiological implications, as only female mosquitoes serve as disease vectors. Our results emphasize the importance of understanding interspecific interactions in influencing larval mosquito development traits.</p>

opencc-zeroSep 2023View details →
dryad36/100

Habitat Suitability Analysis of Larval Pacific Lamprey Habitat in the Columbia River Estuary

Open the record for dataset details and reuse information.

publicMay 2022View details →
dryad36/100

Data from: A habitat and a parasite: Adult and larval parasitic freshwater mussels impact habitat choice and predator-prey interactions of a host fish and its prey

Open the record for dataset details and reuse information.

publicDec 2025View details →
dryad36/100

Heterocypris incongruens maintains an egg bank in stormwater habitats and influences the development of larval mosquito, Culex restuans

Open the record for dataset details and reuse information.

publicSep 2023View details →
dryad32/100

Data from: Benefits of turbid river plume habitat for Lake Erie yellow perch (Perca flavescens) recruitment determined by juvenile to larval genotype assignment

Nutrient-rich, turbid river plumes that are common to large lakes and coastal marine ecosystems have been hypothesized to benefit survival of fish during early life stages by increasing food availability and (or) reducing vulnerability to visual predators. However, evidence that river plumes truly benefit the recruitment process remains meager for both freshwater and marine fishes. Here, we use genotype assignment between juvenile and larval yellow perch (Perca flavescens) from western Lake Erie to estimate and compare recruitment to the age-0 juvenile stage for larvae residing inside the highly turbid, south-shore Maumee River plume versus those occupying the less turbid, more northerly Detroit River plume. Bayesian genotype assignment of a mixed assemblage of juvenile (age-0) yellow perch to putative larval source populations established that recruitment of larvae was higher from the turbid Maumee River plume than for the less turbid Detroit River plume during 2006 and 2007, but not in 2008. Our findings add to the growing evidence that turbid river plumes can indeed enhance survival of fish larvae to recruited life stages, and also demonstrate how novel population genetic analyses of early life stages can contribute to determining critical early life stage processes in the fish recruitment process.

opencc-zeroDec 2014View details →
dryad32/100

Data from: Widespread and persistent invasions of terrestrial habitats coincident with larval feeding behavior transitions during snail-killing fly evolution (Diptera: Sciomyzidae)

Background: Transitions in habitats and feeding behaviors were fundamental to the diversification of life on Earth. There is ongoing debate regarding the typical directionality of transitions between aquatic and terrestrial habitats and the mechanisms responsible for the preponderance of terrestrial to aquatic transitions. Snail-killing flies (Diptera: Sciomyzidae) represent an excellent model system to study such transitions because their larvae display a range of feeding behaviors, being predators, parasitoids or saprophages of a variety of mollusks in freshwater, shoreline and dry terrestrial habitats. The remarkable genus Tetanocera (Tetanocerini) occupies five larval feeding groups and all of the habitat types mentioned above. This study has four principal objectives: (i) construct a robust estimate of phylogeny for Tetanocera and Tetanocerini, (ii) estimate the evolutionary transitions in larval feeding behaviors and habitats, (iii) test the monophyly of feeding groups and (iv) identify mechanisms underlying sciomyzid habitat and feeding behavior evolution. Results: Bayesian inference and maximum likelihood analyses of molecular data provided strong support that the Sciomyzini, Tetanocerini and Tetanocera are monophyletic. However, the monophyly of many behavioral groupings was rejected via phylogenetic constraint analyses. We determined that (i) the ancestral sciomyzid lineage was terrestrial, (ii) there was a single terrestrial to aquatic habitat transition early in the evolution of the Tetanocerini and (iii) there were at least 10 independent aquatic to terrestrial habitat transitions and at least 15 feeding behavior transitions during tetanocerine phylogenesis. The ancestor of Tetanocera was aquatic with five lineages making independent transitions to terrestrial habitats and seven making independent transitions in feeding behaviors. Conclusions: The preponderance of aquatic to terrestrial transitions in sciomyzids goes against the trend generally observed across eukaryotes. Damp shoreline habitats are likely transitional where larvae can change habitat but still have similar prey available. Transitioning from aquatic to terrestrial habitats is likely easier than the reverse for sciomyzids because morphological characters associated with air-breathing while under the water's surface are lost rather than gained, and sciomyzids originated and diversified during a general drying period in Earth's history. Our results imply that any animal lineage having aquatic and terrestrial members, respiring the same way in both habitats and having the same type of food available in both habitats could show a similar pattern of multiple independent habitat transitions coincident with changes in behavioral and morphological traits.

opencc-zeroDec 2012View details →

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Allen Brain Atlas

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allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

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abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record