Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
98
datasets available to search
ShareScore release 0.9.0
Dataset results
98 results for “spring water”
Рис. 4. РаспреΑеΛение чистиковых птиц (А — тонкокΛювая и тоΛстокΛювая кайры, Б — боΛьшая конюга, В — конюга-крошка, Г — топорок) в Охотском море и сопреΑеΛьных воΑах Тихого океана и Японского моря по резуΛьтатам суΑовых учетов в февраΛе — мае 2020 г. (особей/км2 на 10-минутных трансектах). СпΛошными Λиниями показаны учетные трансекты, пунктиром — 200-метровая изобата Fig. 4. Distribution of alcids — (А) common and thick-billed murres, (Б) crested auklet, (В) least auklet, (Г) tufted puffin — in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan in February–May 2020 (birds/km2 on 10-minute transects). Solid lines indicate transects, dotted line indicates a 200 m isobath in Population of seabirds in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan during the winter-spring period of 2020
Рис. 4. РаспреΑеΛение чистиковых птиц (А — тонкокΛювая и тоΛстокΛювая кайры, Б — боΛьшая конюга, В — конюга-крошка, Г — топорок) в Охотском море и сопреΑеΛьных воΑах Тихого океана и Японского моря по резуΛьтатам суΑовых учетов в февраΛе — мае 2020 г. (особей/км2 на 10-минутных трансектах). СпΛошными Λиниями показаны учетные трансекты, пунктиром — 200-метровая изобата Fig. 4. Distribution of alcids — (А) common and thick-billed murres, (Б) crested auklet, (В) least auklet, (Г) tufted puffin — in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan in February–May 2020 (birds/km2 on 10-minute transects). Solid lines indicate transects, dotted line indicates a 200 m isobath
Fig. 1 in The Influence Of Spring Flood Water Levels On The Distribution And Numbers Of Terns (On The Example Of The Lower Desna River)
Fig. 1. The dynamics of spring FLood according to Landsat 8 satellite images (А — a fragment of Landsat 8 SI as of May 18, 2013; B — a fragment of Landsat 8 SI as of June 6, 2014).
Fig. 4 in The Influence Of Spring Flood Water Levels On The Distribution And Numbers Of Terns (On The Example Of The Lower Desna River)
Fig. 4. Changes in numbers of breeding pairs and colonies of Chlidonias and Sterna terns on the Lower Desna in 2013–2014.
Linked collectors and determiners for: First Canadian record of the water mite Thermacarus nevadensis Marshall, 1928 (Arachnida: Acariformes: Hydrachnidiae: Thermacaridae) from hot springs in British Columbia.
Natural history specimen data linked to collectors and determiners held within, "First Canadian record of the water mite Thermacarus nevadensis Marshall, 1928 (Arachnida: Acariformes: Hydrachnidiae: Thermacaridae) from hot springs in British Columbia". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/643d14c4-29be-4357-bbc6-ff2e5f88d55a">https://bionomia.net/dataset/643d14c4-29be-4357-bbc6-ff2e5f88d55a</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/643d14c4-29be-4357-bbc6-ff2e5f88d55a">https://gbif.org/dataset/643d14c4-29be-4357-bbc6-ff2e5f88d55a</a>. Formatted as a Frictionless Data package.
Hull Springs Wetland Water Depth and Temperature Data from 2021-06-11 to 2021-07-16
<pre># General Metadata for Hull Springs Restored Wetland Sampling Station ## Files Specific metadata for each deployment and sensor can be found as text files with the file format of: HS_wetland_DO_YYYY-MM-DD_metadata.txt HS_wetland_pressure_trans_YYYY-MM-DD_metadata.txt HS_wetland_CT_YYYY-MM-DD_metadata.txt Where YYYY-MM-DD is the date that the sampling period ended. NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab [https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts](https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts). ## File Created * 2021-06-16 by KF ## File Modified * 2021-07-22 by KF - added general metadata for the pressure transducer and the CT sensor. ## Description These data are from the sampling station in the restored wetland at Hull Springs. The sensors are in the NE corner of the shallow pond portion of the restored wetland (38.119289, -76.667252). All data are CC-BY and should be cited using the DOI available at https://zenodo.org/communities/leo/ ## Station Specifics The specific at each site are: * Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Temperature (dC) and Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger The sensors are sampled every 15 minutes ## Measurement Parameters, units, and Variable Names * date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * date.time.adj - the date and time of the pressure measurement that was adjusted to match the barometric pressure measurement from the weather station. * observation - the incremental number of each observation * timestamp - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp - the temperature of the water (dC) * Pressure - the pressure recorded by the underwater pressure transducer (kPa) * press_mmHg - the pressure recorded by the underwater pressure transducer (mm Hg) * BP_mmHg - the barometric pressure recorded by the weather station at the Yellow House (mm Hg) * Z - the depth of the water at the wetland sampling station (cm) * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) </pre>
Hull Springs Wetland Dissolved Oxygen and Water Temperature Data from 2021-05-04 to 2021-06-11
<pre># General Metadata for Hull Springs Restored Wetland Sampling Station ## Files Specific metadata for each deployment and sensor can be found as text files with the file format of: HS_wetland_DO_YYYY-MM-DD_metadata.txt HS_wetland_pressure_trans_YYYY-MM-DD_metadata.txt HS_wetland_CT_YYYY-MM-DD_metadata.txt Where YYYY-MM-DD is the date that the sampling period ended. NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab [https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts](https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts). ## File Created * 2021-06-16 by KF ## File Modified * 2021-07-22 by KF - added general metadata for the pressure transducer and the CT sensor. ## Description These data are from the sampling station in the restored wetland at Hull Springs. The sensors are in the NE corner of the shallow pond portion of the restored wetland (38.119289, -76.667252). All data are CC-BY and should be cited using the DOI available at https://zenodo.org/communities/leo/ ## Station Specifics The specific at each site are: * Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Temperature (dC) and Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger The sensors are sampled every 15 minutes ## Measurement Parameters, units, and Variable Names * date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * date.time.adj - the date and time of the pressure measurement that was adjusted to match the barometric pressure measurement from the weather station. * observation - the incremental number of each observation * timestamp - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp - the temperature of the water (dC) * Pressure - the pressure recorded by the underwater pressure transducer (mmHg) * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) </pre>
Hull Springs Wetland Conductivity and Water Temperature Data from 2021-05-04 to 2021-06-11
<pre># General Metadata for Hull Springs Restored Wetland Sampling Station ## Files Specific metadata for each deployment and sensor can be found as text files with the file format of: HS_wetland_DO_YYYY-MM-DD_metadata.txt HS_wetland_pressure_trans_YYYY-MM-DD_metadata.txt HS_wetland_CT_YYYY-MM-DD_metadata.txt Where YYYY-MM-DD is the date that the sampling period ended. NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab [https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts](https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts). ## File Created * 2021-06-16 by KF ## File Modified * 2021-07-22 by KF - added general metadata for the pressure transducer and the CT sensor. ## Description These data are from the sampling station in the restored wetland at Hull Springs. The sensors are in the NE corner of the shallow pond portion of the restored wetland (38.119289, -76.667252). All data are CC-BY and should be cited using the DOI available at https://zenodo.org/communities/leo/ ## Station Specifics The specific at each site are: * Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Temperature (dC) and Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger The sensors are sampled every 15 minutes ## Measurement Parameters, units, and Variable Names * date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * date.time.adj - the date and time of the pressure measurement that was adjusted to match the barometric pressure measurement from the weather station. * observation - the incremental number of each observation * timestamp - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp - the temperature of the water (dC) * Pressure - the pressure recorded by the underwater pressure transducer (mmHg) * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) </pre>
Hull Springs Wetland Water Depth and Water Temperature Data from 2021-05-04 to 2021-06-11
<pre># General Metadata for Hull Springs Restored Wetland Sampling Station ## Files Specific metadata for each deployment and sensor can be found as text files with the file format of: HS_wetland_DO_YYYY-MM-DD_metadata.txt HS_wetland_pressure_trans_YYYY-MM-DD_metadata.txt HS_wetland_CT_YYYY-MM-DD_metadata.txt Where YYYY-MM-DD is the date that the sampling period ended. NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab [https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts](https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts). ## File Created * 2021-06-16 by KF ## File Modified * 2021-07-22 by KF - added general metadata for the pressure transducer and the CT sensor. ## Description These data are from the sampling station in the restored wetland at Hull Springs. The sensors are in the NE corner of the shallow pond portion of the restored wetland (38.119289, -76.667252). All data are CC-BY and should be cited using the DOI available at https://zenodo.org/communities/leo/ ## Station Specifics The specific at each site are: * Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Temperature (dC) and Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger The sensors are sampled every 15 minutes ## Measurement Parameters, units, and Variable Names * date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * date.time.adj - the date and time of the pressure measurement that was adjusted to match the barometric pressure measurement from the weather station. * observation - the incremental number of each observation * timestamp - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp - the temperature of the water (dC) * Pressure - the pressure recorded by the underwater pressure transducer (mmHg) * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) </pre>
Hull Springs Wetland Dissolved Oxygen and Water Temperature Data from 2021-06-11 to 2021-07-16
<pre># General Metadata for Hull Springs Restored Wetland Sampling Station ## Files Specific metadata for each deployment and sensor can be found as text files with the file format of: HS_wetland_DO_YYYY-MM-DD_metadata.txt HS_wetland_pressure_trans_YYYY-MM-DD_metadata.txt HS_wetland_CT_YYYY-MM-DD_metadata.txt Where YYYY-MM-DD is the date that the sampling period ended. NOTE: The metadata in the above file is collected from the data logger and does not have all of fields present in the final data set, because some were created during data cleaning. Details on how the data were cleaned and variables created can be found at in the cleaning scripts on Gitlab [https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts](https://gitlab.com/leo147/leo/-/tree/master/lab_notebook/data_processing/cleaning_scripts). ## File Created * 2021-06-16 by KF ## File Modified * 2021-07-22 by KF - added general metadata for the pressure transducer and the CT sensor. ## Description These data are from the sampling station in the restored wetland at Hull Springs. The sensors are in the NE corner of the shallow pond portion of the restored wetland (38.119289, -76.667252). All data are CC-BY and should be cited using the DOI available at https://zenodo.org/communities/leo/ ## Station Specifics The specific at each site are: * Temperature (dC) and Dissolved Oxygen (mg/l) are collected with a Onset HOBO U26-001 Dissolved Oxygen Logger * Temperature (dC) and Pressure (mmHg) are collected with an Onset HOBO U20-001-01 Water Level Logger * Temperature (dC) and Conductivity are collected with an Onset HOBO U24-001 Conductivity Logger The sensors are sampled every 15 minutes ## Measurement Parameters, units, and Variable Names * date.time - the date and time that the record was collected, reported in POSIX standard time (YYYY-MM-DD HH:MM:SS) * date.time.adj - the date and time of the pressure measurement that was adjusted to match the barometric pressure measurement from the weather station. * observation - the incremental number of each observation * timestamp - the data and time that the record was collected, as reported by the data logger (MM/DD/YY HH:MM:SS A/PM) * DO - the concentration of dissolved oxygen in the water (mg/L) * Temp - the temperature of the water (dC) * Pressure - the pressure recorded by the underwater pressure transducer (mmHg) * Low_Range_CT - the conductivity read from 0 - 2500 uS/cm (uS/cm) * Full_Range_CT - the conductivity read from 0 - 15000 uS/cm (mmHg) </pre>
Warming effects of spring rainfall increase methane emissions from thawing permafrost: Site-level data from bog complex I - Water Table Depth 2014-2016
Methane emissions regulate the near-term global warming potential of permafrost thaw, particularly where loss of ice-rich permafrost converts forest and tundra into wetlands. Northern latitudes are expected to get warmer and wetter, and while there is consensus that warming will increase thaw and methane emissions, effects of increased precipitation are uncertain. At a thawing wetland complex in Interior Alaska, we found that interactions between rain and deep soil temperatures controlled methane emissions. In rainy years, recharge from the watershed rapidly altered wetland soil temperatures, warming the top ~80 cm of soil in spring and summer, and cooling it in autumn. When soils were warmed by spring rainfall, methane emissions increased by ~30%. The warm, deep soils early in the growing season likely supported both microbial and plant processes that enhanced emissions. Our study identifies an important and unconsidered role of rain in governing the radiative forcing of thawing permafrost landscapes. All site-level data from the studied bog, eddy covariance and micrometeorological data referenced in the published manuscript are available in the LTER data repository. These data are related to the following data package: Surface carbon, water and energy fluxes measured by eddy covariance at 3 sites within the Alaska Peatlands Experiment and Bonanza Creek Experimental Forest 2013-2016 (http://dx.doi.org/10.6073/pasta/4fabab3846113a1866b06f1b3d6d52a3).
Data from: Water the odds? Spring rainfall and emergence-related seed traits drive plant recruitment
<p>Recruitment of new individuals from seed is a critical component of plant community assembly and reassembly, especially in the context of ecosystem disturbance and recovery. While frameworks typically aim to predict how communities will be filtered on the basis of traits influencing established plant responses to the environment, assembly from seed is more complex: the responses of seeds (affected by dormancy and germination function) and establishing plants (affected by root and leaf function) can both influence outcomes within a single growing season. This creates a potential role for a more diverse set seed and seedling traits, and for environmental variability on shorter timescales (e.g., seasonal versus annual dynamics), than are typically considered. We followed thousands of individual seeds comprising eleven herbaceous grassland species through the first growing season, seeking to uncover critical environmental (precipitation amount and timing) and trait-based filters on seedling emergence and survival in assembling communities. We saw the biggest recruitment limitation when seeds failed to emerge, driven independently by a dry spring and interspecific variation in seed mass (positive effect) and seed dormancy (negative effect). Seedling survival rates were higher than emergence, with weaker predictive roles for traits like seedling root mass allocation (positive effect) and seed mass (positive under spring drought), and lesser impacts of summer rainfall on soil moisture and survival. Interestingly, most trait relationships were not conditional on rainfall, suggesting water-independent mechanisms of their respective advantages. Although recruitment is a complex process, our findings suggest that trait-based assembly frameworks can be a useful way to anticipate outcomes, particularly if dynamic early-stage conditions (e.g., spring rainfall) and attributes (e.g., seed dormancy) receive greater attention. Given the importance of recruitment for community turnover in the context of global change and land management efforts, this is an area ripe for continued expansion in trait-based and applied ecology.</p>
Spring tropical cyclones modulate near-surface isotopic compositions of atmospheric water vapour at Kathmandu, Nepal
<p>All these data have been published in a ACP paper. If you use these data in any conditions, please cite the following publicaiton: Adhikari, N., Gao, J., Zhao, A., Xu, T., Chen, M., Niu, X., and Yao, T.: Spring tropical cyclones modulate near-surface isotopic compositions of atmospheric water vapour at Kathmandu, Nepal, EGUsphere, https://doi.org/10.5194/egusphere-2023-2186, 2023.</p>
Seasonal precipitation distribution determines ecosystem CO₂ and H₂O exchange by regulating spring soil water-salt dynamics in a brackish wetland
<p>The intensification of the global hydrological cycle is anticipated to increase the variability of precipitation patterns. Brackish wetlands respond to changes in precipitation patterns by regulating the absorption and release of CO<sub>2</sub> and H<sub>2</sub>O to maintain the stability of ecosystem functions. However, there is limited understanding of how the inter-seasonal precipitation distribution affects ecosystem CO<sub>2</sub> and H<sub>2</sub>O exchange compared to annual precipitation totals. Here, we conducted four consecutive years of field experiments in a brackish wetland, manipulating the proportion of precipitation across different seasons while maintaining a constant annual precipitation total. We utilized five inter-seasonal precipitation distribution proportions (+73%, +56%, control (CK), -56%, and -73%) to examine the effects of seasonal precipitation distribution (SPD) on ecosystem CO<sub>2</sub> and H<sub>2</sub>O exchange. Our findings revealed that the ecosystem CO<sub>2</sub> and H<sub>2</sub>O fluxes showed a trend of decreasing with the decrease of spring precipitation distribution. Among them, the annual net ecosystem CO<sub>2 </sub>exchange (NEE), evapotranspiration (ET), carbon use efficiency (CUE), and water use efficiency (WUE) were shown to be more sensitive to decrease in spring precipitation distribution and increase in summer and autumn precipitation distribution. This negative asymmetric response pattern suggests that annual ecosystem CO<sub>2</sub> and H<sub>2</sub>O exchange is primarily governed by seasonal precipitation variability, with spring soil water-salt dynamics identified as the key driver. Therefore, this association can be explained by the fact that drought of the early growth stage exacerbates soil salinization and inhibits vegetation colonization and growth, thereby greatly impairing the annual CO<sub>2</sub>-H<sub>2</sub>O exchange capacity of brackish wetlands. Our results emphasized that the spring's extreme precipitation-induced soil water-salt conditions will greatly influence CO<sub>2</sub> and H<sub>2</sub>O exchange in brackish wetlands in the future. These findings are crucial for improving predictions of the carbon sequestration and water-holding capacity of brackish wetlands.</p>
Μονή Θάρρι Moni Thari, Ρόδος Rodos. Spring and water channel running east of the church.
<p>Μονή Θάρρι Moni Thari, Ρόδος Rodos. Spring and water channel running east of the church.</p>
Winds aloft over three water bodies influence spring stopover distributions of migrating birds along the Gulf of Mexico coast
<p>Migrating birds contend with dynamic wind conditions that ultimately influence most aspects of their migration, from broad-scale movements to individual decisions about where to rest and refuel. We used weather surveillance radar data to measure spring stopover distributions of northward migrating birds along the northern Gulf of Mexico coast and found a strong influence of winds over non-adjacent water bodies, the Caribbean Sea and Atlantic Ocean, along with the contiguous Gulf of Mexico. Specifically, we quantified the relative influence of meridional (north-south) and zonal (west-east) wind components over the three water bodies on weekly spring stopover densities along western, central, and eastern regions of the northern Gulf of Mexico coast. Winds over the Caribbean Sea and Atlantic Ocean were just as, or more, influential than winds over the Gulf of Mexico, with the highest stopover densities in the central and eastern regions of the coast following the fastest winds from the east over the Caribbean Sea. In contrast, stopover density along the western region of the coast was most influenced by winds over the Gulf of Mexico, with the highest densities following winds from the south. Our results elucidate the important role of wind conditions over multiple water bodies on region-wide stopover distributions and complement tracking data showing Nearctic-Neotropical birds flying non-stop from South America to the northern Gulf of Mexico coast. Smaller-bodied birds may be particularly sensitive to prevailing wind conditions during non-stop flights over water, with probable orientation and energetic consequences that shape subsequent terrestrial stopover distributions. In the future, the changing climate is likely to alter wind conditions associated with migration, so birds that employ non-stop over-water flight strategies may face growing challenges. </p>
Data from: Water the odds? Spring rainfall and emergence-related seed traits drive plant recruitment
Open the record for dataset details and reuse information.
Winds aloft over three water bodies influence spring stopover distributions of migrating birds along the Gulf of Mexico coast
Open the record for dataset details and reuse information.
Seasonal precipitation distribution determines ecosystem CO₂ and H₂O exchange by regulating spring soil water-salt dynamics in a brackish wetland
Open the record for dataset details and reuse information.
Data from: Hot spring frogs (Buergeria japonica) prefer cooler water to hot water
<p>"Hot spring frog" is an informal name used for the Japanese stream tree frog (<i>Buergeria japonica</i>), which is widely distributed in Taiwan and the Ryukyu Archipelago in Japan. Some populations of the species are known to inhabit hot springs. However, water temperature can be extremely high around the sources of hot springs. Thus, it is questionable whether <i>B. japonica</i> selectively inhabits such dangerous environments. To address this question, we conducted a series of observations of water temperature preferences of a hot spring population of <i>B. japonica</i> in Kuchinoshima Island in Japan: (1) a field observation of tadpole density in water pools of different temperatures, (2) a field observation of water temperatures where adult males appear for breeding, and (3) an indoor observation of water temperatures selected by adult females for oviposition. As a result, tadpoles showed a higher density in cooler water. Adult males avoided water pools hotter than 37 °C, and adult females selected cooler pools for oviposition. Camera records also showed that adult individuals tend to appear around cooler pools. Thus, we did not find any support for the hypothesis that hot spring frogs prefer hot water. Conversely, they apparently tended to prefer cooler water if it was available. Water temperatures around the sources of the hot spring exceed thermal tolerances of the species and could be a strong selective pressure on the population. Thus, the ability to sense and avoid lethal temperatures may be a key ecological and physiological characteristic for the species that inhabit hot springs.</p>
FIGURES 50–54. Fig. 50 in On the morphology and classification of larval water mites (Hydrachnidia, Acari) from springs in Luxembourg
FIGURES 50–54. Fig. 50: Pseudofeltria scourfieldi, ventral idiosoma (from Martin 2000), Fig. 51: Tiphys sp., ventral idiosoma (redrawn and modified after Smith et al. 2001), Fig. 52: Ljania bipapillata, ventral idiosoma (from Martin 2000), Fig. 53: Aturus fontinalis, dorsal idiosoma, Fig. 54: A. fontinalis, ventral idiosoma (Figs. 53–54 from Martin 2000).
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.