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103 results for “Temperature Gradient”
Urban Heat and Desert Wildlife: Rodent Body Condition Across a Gradient of Surface Temperatures in the greater Phoenix, Arizona (USA) metropolitan area (2019-2020)
We live-trapped wild rodents from seven field sites spanning three strata of land-surface temperatures in the Phoenix, Arizona (USA) metropolitan area. We captured 116 adult pocket mice (Chaetodipus spp. and Perognathus spp.) and Merriam’s kangaroo rats (Dipodomys merriami) during 2019 and 2020 from mountainous urban parks and open spaces. Animal body condition was quantified as percent body fat (i.e., fat mass divided by body mass). We used a noninvasive quantitative magnetic resonance instrument to measure body condition.
Baltimore Ecosystem Study: Soil moisture and temperature along an urban to rural gradient, 2011 - present
Soil temperature and soil moisture have been measured at multiple locations in and around Baltimore Maryland to provide data on these variables in forests and lawns across an urban to rural gradient. In July 2011, we installed one Decagon Em50 Datalogger with five 5TM VWC/Temperature probes at four established forested, upslope, 20 x 20-m plots, two rural (ORU1, ORU2) and two urban (LEA1, LEA2), at 2 forested riparian sites at two transects along a stream (ORUR, ORLR), and two lawn plots on the campus of the University of Maryland Baltimore County campus (UMBC1, UMBC 2). Probes were buried horizontally at 10cm depth (except UMBC1 and UMBC2 where the five probes are mounted horizontally at a single location at depths of 50, 40, 30, 20 and 10 cm depth). At the upslope forested plots, the five probes are replicates. At the two riparian sites, probes are deployed in either "hummocks (drier, higher)" or in "hollows (lower, wetter)". Soil temperature and soil moisture were measured at hourly intervals on these plots beginning in July 2011. In March 2017, an additional data logger was installed at Hillsdale Park (HD1) in a forested urban area. The five probes at HD1 were buried horizontally at 10cm depth and are replicates. Earlier soil moisture data were collected monthly (1999-2011), and can be found in https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-bes&identifier=417
Eight Mile Lake Research Watershed, Thaw Gradient: half-hourly soil temperature 2004-2024
In this larger study, we are asking the question: Is old carbon that comprises the bulk of the soil organic matter pool released in response to thawing of permafrost? We are answering this question by using a combination of field and laboratory experiments to measure radiocarbon isotope ratios in soil organic matter, soil respiration, and dissolved organic carbon, in tundra ecosystems. The objective of these proposed measurements is to develop a mechanistic understanding of the SOM sources contributing to C losses following permafrost thawing. We are making these measurements at an established tundra field site near Healy, Alaska in the foothills of the Alaska Range. Field measurements center on a natural experiment where permafrost has been observed to warm and thaw over the past several decades. This area represents a gradient of sites each with a different degree of change due to permafrost thawing. As such, this area is unique for addressing questions at the time and spatial scales relevant for change in arctic ecosystems. This data set includes soil temperature at multiple depths in the profile at different locations within gradient of sites described.
Soil temperature along an elevation gradient at the Hubbard Brook Experimental Forest, 2010 - ongoing
Soil temperature and soil moisture have been measured at multiple locations at the Hubbard Brook Experimental Forest (HBEF), as part of a study of the relationships between snow depth, soil freezing and nutrient cycling (http://www.ecostudies.org/people_sci_groffman_snow_summary.html). In October 2010, we established 6, 20 x 20-m plots (intensive plots) and 14 10 x 10-m plots (extensive plots) along an elevation gradient, with eight of the plots on north-facing slopes and twelve on south-facing slopes. Soil temperature and soil moisture were measured at hourly intervals on these plots beginning in November 2010. Six locations were discontinued in September 2012 (E04, E05, E06, E11-B, E13, and E14). Previous versions of this dataset included both temperature and moisture. These data are now available as temperature (this dataset) and moisture (https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-hbr&identifier=137). These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Northeastern Puerto Rico open-canopy and under-canopy temperature and moisture data on an elevational gradient
The data archive is here:https://doi.org/10.2737/RDS-2022-0051 please use this DOI when citing this dataset. This data publication contains monthly means of temperature and moisture data collected from August 2006 through September 2021 from 22 locations along an elevational gradient, from 0 to 1045 meters, in Northeastern Puerto Rico. The higher elevational data are in the Luquillo Experimental Forest (El Yunque National Forest). Five kinds of data are included: air temperature and precipitation measured in the open (not under canopy) at 20 locations, air temperature and soil temperature both measured under the canopy at all 22 locations, and soil moisture under the canopy at 4 locations. Two locations have 3 sites each, measured in different canopy types at the same location. The other 20 locations have one site each, making a total of 26 measurement sites. Data are provided as monthly averages at each site. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Range expansion is slower and more variable with rapid evolution across a spatial gradient in temperature
<p><span>Rapid evolution in colonizing populations can alter our ability to predict future range expansions. Recent theory suggests that the dynamics of replicate range expansions are less variable, and hence more predictable, with increased selection at the expanding range front. Here, we test whether selection from environmental gradients across space produces more consistent range expansion speeds, using the experimental evolution of replicate duckweed populations colonizing landscapes with and without a temperature gradient. We found that range expansion across a temperature gradient was slower on average, with range-front populations displaying higher population densities, and genetic signatures and trait changes consistent with directional selection. Despite this, we found that with a spatial gradient range expansion speed became more variable and less consistent among replicates over time. Our results therefore challenge current theory, highlighting that chance can still shape the genetic response to selection to influence our ability to predict range expansion speeds.</span></p>
Environmental and physiochemical controls on coral calcification along a latitudinal temperature gradient in Western Australia
<p>Supplementary data for: Environmental and physiochemical controls on coral calcification along a latitudinal temperature gradient in Western Australia</p>
What Controls the Mean East–West Sea Surface Temperature Gradient in the Equatorial Pacific: The Role of Cloud Albedo
<p>Climatologies for the climate model simulations performed by Burls and Fedorov 2014, Journal of Climate, <a href="https://doi.org/10.1175/JCLI-D-13-00255.1">https://doi.org/10.1175/JCLI-D-13-00255.1</a>. This table shows how the names of the simulation files provided in this dataset relate to the experiment names provided in Table 1 of Burls and Fedorov (2014, JOC).</p> <table> <thead> <tr> <th scope="col">Experiment # in Article (Table 1)</th> <th scope="col">Name of Files</th> </tr> </thead> <tbody> <tr> <td>1</td> <td>PreInd_T31_gx3v7*.nc</td> </tr> <tr> <td>2</td> <td>80p_op_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>3</td> <td>60p_op_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>4</td> <td>40p_op_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>5</td> <td>20p_op_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>6</td> <td>20p_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>7</td> <td>40p_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>8</td> <td>60p_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>9</td> <td>80p_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>10</td> <td>20p_ILWP_1590deg_tropx2_T31_gx3v7*.nc</td> </tr> <tr> <td>11</td> <td>40p_ILWP_1590deg_tropx2_T31_gx3v7*.nc</td> </tr> <tr> <td>12</td> <td>60p_ILWP_1590deg_tropx2_T31_gx3v7*.nc</td> </tr> <tr> <td>13</td> <td>80p_ILWP_1590deg_tropx2_T31_gx3v7*.nc</td> </tr> <tr> <td>14</td> <td>20p_ILWP_1590deg_tropx4_T31_gx3v7*.nc</td> </tr> <tr> <td>15</td> <td>40p_ILWP_1590deg_tropx4_T31_gx3v7*.nc</td> </tr> <tr> <td>16</td> <td>60p_ILWP_1590deg_tropx4_T31_gx3v7*.nc</td> </tr> <tr> <td>17</td> <td>80p_ILWP_1590deg_tropx4_T31_gx3v7*.nc</td> </tr> <tr> <td>18</td> <td>20p_ILWP_3060deg_tropx8_T31_gx3v7*.nc</td> </tr> <tr> <td>19</td> <td>40p_ILWP_3060deg_tropx8_T31_gx3v7*.nc</td> </tr> <tr> <td>20</td> <td>60p_ILWP_3060deg_tropx8_T31_gx3v7*.nc</td> </tr> <tr> <td>21</td> <td>80p_ILWP_3060deg_tropx8_T31_gx3v7*.nc</td> </tr> <tr> <td>22</td> <td>PreInd_0.9x1.25_gx1v6*.nc</td> </tr> <tr> <td>23</td> <td>40p_LWP_1590deg_0.9x1.25_gx1v6*.nc</td> </tr> <tr> <td>24</td> <td>60p_LWP_1590deg_0.9x1.25_gx1v6*.nc</td> </tr> <tr> <td>25</td> <td>40p_ILWP_1590deg_tropx2_0.9x1.25_gx1v6*.nc</td> </tr> <tr> <td>26</td> <td>60p_ILWP_1590deg_tropx2_0.9x1.25_gx1v6*.nc</td> </tr> </tbody> </table> <p>Article abstract:</p> <p>The mean east–west sea surface temperature gradient along the equator is a key feature of tropical climate. Tightly coupled to the atmospheric Walker circulation and the oceanic east–west thermocline tilt, it effectively defines tropical climate conditions. In the Pacific, its presence permits the El Niño–Southern Oscillation phenomenon. What determines this temperature gradient within the fully coupled ocean–atmosphere system is therefore a central question in climate dynamics, critical for understanding past and future climates. Using a comprehensive coupled model [Community Earth System Model (CESM)], the authors demonstrate how the meridional gradient in cloud albedo between the tropics and midlatitudes (Δα) sets the mean east–west sea surface temperature gradient in the equatorial Pacific. To change Δα in the numerical experiments, the authors change the optical properties of clouds by modifying the atmospheric water path, but only in the shortwave radiation scheme of the model. When Δα is varied from approximately −0.15 to 0.1, the east–west SST contrast in the equatorial Pacific reduces from 7.5°C to less than 1°C and the Walker circulation nearly collapses. These experiments reveal a near-linear dependence between Δα and the zonal temperature gradient, which generally agrees with results from the Coupled Model Intercomparison Project phase 5 (CMIP5) preindustrial control simulations. The authors explain the close relation between the two variables using an energy balance model incorporating the essential dynamics of the warm pool, cold tongue, and Walker circulation complex.</p>
Soil temperature in Black Spruce Carbon cycling study along a temperature gradient in interior Alaska
Study conducted on black spruce C cycling study along a temperature gradient in interior Alaska from 1999 to 2002. The temperature gradient was established by locating sites in the Fairbanks area that varied in elevation and aspect. Measurements include:soil temperature, forest aboveground production, litterfall, decomposition of litter and cellulose proxies, soil carbon dioxide efflux, moss photosynthesis, soil moisture, foliar isotopes (15N and 13C).
Bonanza Creek moisture gradient physical data at BZBS: hourly temperature, moisture and photosynthetically active radiation.
This dataset contains the hourly output from temperature, moisture and PAR sensors at five unique vegetative sites at the Bonanza Creek moisture gradient. This data can be sorted and viewed by site, year, hour and depth of probe below surface. Data from each site within this transect will be update yearly. Start dates for the probes at each site vary depending on when they were installed.
Bonanza Creek moisture gradient physical data at BZWB: hourly temperature, moisture and photosynthetically active radiation.
This dataset contains the hourly output from temperature, moisture and PAR sensors at five unique vegetative sites at the Bonanza Creek moisture gradient. This data can be sorted and viewed by site, year, hour and depth of probe below surface. Data from each site within this transect will be update yearly. Start dates for the probes at each site vary depending on when they were installed.
Bonanza Creek moisture gradient physical data at BZTG: hourly temperature, moisture and photosynthetically active radiation.
This dataset contains the hourly output from temperature, moisture and PAR sensors at five unique vegetative sites at the Bonanza Creek moisture gradient. This data can be sorted and viewed by site, year, hour and depth of probe below surface. Data from each site within this transect will be update yearly. Start dates for the probes at each site vary depending on when they were installed.
Bonanza Creek moisture gradient physical data at BZEC: hourly temperature, moisture and photosynthetically active radiation.
This dataset contains the hourly output from temperature, moisture and PAR sensors at five unique vegetative sites at the Bonanza Creek moisture gradient. This data can be sorted and viewed by site, year, hour and depth of probe below surface. Data from each site within this transect will be update yearly. Start dates for the probes at each site vary depending on when they were installed.
Bonanza Creek moisture gradient physical data at BZDE: hourly temperature, moisture and photosynthetically active radiation.
This dataset contains the hourly output from temperature, moisture and PAR sensors at five unique vegetative sites at the Bonanza Creek moisture gradient. This data can be sorted and viewed by site, year, hour and depth of probe below surface. Data from each site within this transect will be update yearly. Start dates for the probes at each site vary depending on when they were installed.
Stem temperature at watershed 18, cove 218 gradient plot at the Coweeta Hydrologic Laboratory from 1996 to 1999
Tree stem temperature is currently being collected to determine both diurnal and seasonal variation in tree stem temperatures for all species and sizes present at the Coweeta Watershed 18 Cove 218 Gradient Plot. The purpose of the data is to characterize the tree stem temperature regimes as they relate to tree stem respiration. Data will continue to be collected until approximately December 1997. Data will then be subsequently summarized and published.
Hubbard Brook Experimental Forest: Hourly soil oxygen, moisture and temperature across soil depths and an elevation gradient in the Bear Brook watershed; 2018-2019
Denitrification is potentially a significant process of soil nitrogen removal from the Hubbard Brook Experimental Forest (HBEF) ecosystem. Its magnitude and variation can depend on physical conditions within the soil, particularly oxygen concentration, moisture, and temperature. This dataset contains continuous measurement of soil oxygen, moisture and temperature near the biogeochemical reference Watershed 6 at (HBEF). Data were collected from Campbell Scientific CR1000 dataloggers with sensors installed at 3 depths, each at a soil horizon transition and at an hourly time interval. The timeframe of the dataset is 1 year starting in July 2018 and ending in July 2019. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Crack channelling mechanisms in brittle coating systems under moisture or temperature gradients.
<p>Crack channelling is predicted in a brittle coating-substrate system that is subjected to a moisture or temperature gradient in the thickness direction. Competing failure scenarios are identified, and are distinguished by the degree to which the coating-substrate interface delaminates, and whether this delamination is finite or unlimited in nature. Failure mechanism maps are constructed, and illustrate the sensitivity of the active crack channelling mechanism and associated channelling stress to the ratio of coating toughness to interfacial toughness, to the mismatch in elastic modulus and to the mismatch in coefficient of hygral or thermal expansion. The effect of the ratio of coating to substrate thickness upon the failure mechanism and channelling stress is also explored. Closed-form expressions for the steady-state delamination stress are derived, and are used to determine the transition value of moisture state that leads to unlimited delamination. Although the results are applicable to coating-substrate systems in a wide range of applications, the study focusses on the prediction of cracking in historical paintings due to indoor climate fluctuations, with the objective of helping museums developing strategies for the preservation of art objects. For this specific application, crack channelling with delamination needs to be avoided under all circumstances, as it may induce flaking of paint material. In historical paintings, the substrate thickness is typically more than ten times larger than the thickness of the paint layer; for such a system, the failure maps constructed from the numerical simulations indicate that paint delamination is absent if the delamination toughness is larger than approximately half of the mode I toughness of the paint layer. Further, the transition between crack channelling with and without delamination appears to be relatively insensitive to the mismatch in the elastic modulus of the substrate and paint layer. The failure maps developed in this work may provide a useful tool for museum conservators to identify the allowable indoor humidity and temperature fluctuations for which crack channelling with delamination is prevented in historical paintings.</p>
Effects of Tide-Induced Mixing on the Surface Temperature Gradients Between the Equator and Poles During the Middle Miocene Climate Optimum -- Dataset
<p>The files contain the data related to the figures in this paper.</p><p>-- Fig.1 The topographic roughness of the PI and MMCO before and after reconstruction</p><p>-- Fig.2 The 300-year time series of the annual mean SAT and SST</p><p>-- Fig.3 The data of SSH for PI_TF experiment</p><p>-- Fig.4 The tidal dissipation and mixing for MMCO_TM, and the ocean vertical mixing</p><p>-- Fig.5 The annual mean SAT and SST for the MMCO_TM and<i> </i>MMCO<i>_</i>noTM</p><p>-- Fig.6 The global meridional heat transport for the MMCO_TM and<i> </i>MMCO<i>_</i>noTM</p><p>-- Fig.7 The net sea surface heat flux for the MMCO_TM and<i> </i>MMCO<i>_</i>noTM</p><p>-- Fig.8 The GMOC and AMOC for the MMCO_TM and<i> </i>MMCO<i>_</i>noTM</p>
Data files for manuscript "Coral growth along a natural gradient of seawater temperature, pH, and oxygen in a nearshore seagrass bed on Dongsha Atoll, Taiwan"
<p>Data files and README file for the manuscript "Coral growth along a natural gradient of seawater temperature, pH, and oxygen in a nearshore seagrass bed on Dongsha Atoll, Taiwan" by Ariel K. Pezner, Travis A. Courtney, Wen-Chen Chou, Hui-Chuan Chu, Benjamin W. Frable, Samuel A. H. Kekuewa, Keryea Soong, Yi Wei, and Andreas J. Andersson.</p> <p>Data files include carbonate chemistry data from discrete seawater samples taken over a shallow seagrass bed, <em>Porites</em> skeletal extension, density, and calcification rates from 15 coral cores collected in the seagrass bed (as well as collection locations), and data from an autonomous CTD sensor deployed in the shallow seagrass. </p>
Tightly linked zonal and meridional sea surface temperature gradients over the past five million years
<p>Climatologies for the climate model simulations performed by Fedorov et al., Nature Geoscience, <a href="https://www.nature.com/articles/ngeo2577">https://www.nature.com/articles/ngeo2577</a>. This table shows how the names of the simulation files provided in this dataset relate to the experiment names provided in Table S2 of Fedorov et al., (2015, Nature Geoscience). Note that experiments 1-26 are from Burls and Fedorov (2014) and published in <a href="https://doi.org/10.5281/zenodo.6762450">https://doi.org/10.5281/zenodo.6762450</a></p> <table> <tbody> <tr> <td><strong>Experiment # in Article (Table S2)</strong></td> <td><strong>Name of Files</strong></td> </tr> <tr> <td>27</td> <td> <p>abrupt2xCO2_T31_gx3v7*.nc</p> </td> </tr> <tr> <td>28</td> <td> <p>abrupt4xCO2_T31_gx3v7*.nc</p> </td> </tr> <tr> <td>29</td> <td> <p>abrupt8xCO2_T31_gx3v7*.nc</p> </td> </tr> <tr> <td>30</td> <td> <p>abrupt16xCO2_T31_gx3v7*.nc</p> </td> </tr> <tr> <td>Extended Exp 11</td> <td>40p_ILWP_1590deg_tropx2_T31_gx3v7*.nc</td> </tr> <tr> <td>Extended Exp 16</td> <td>60p_ILWP_1590deg_tropx4_T31_gx3v7*.nc</td> </tr> </tbody> </table> <p>Article abstract:</p> <p>The climate of the tropics and surrounding regions is defined by pronounced zonal (east–west) and meridional (equator to mid-latitudes) gradients in sea surface temperature. These gradients control zonal and meridional atmospheric circulations, and thus the Earth’s climate. Global cooling over the past five million years, since the early Pliocene epoch, was accompanied by the gradual strengthening of these temperature gradients. Here we use records from the Atlantic and Pacific oceans, including a new alkenone palaeotemperature record from the South Pacific, to reconstruct changes in zonal and meridional sea surface temperature gradients since the Pliocene, and assess their connection using a comprehensive climate model. We find that the reconstructed zonal and meridional temperature gradients vary coherently over this time frame, showing a one-to-one relationship between their changes. In our model simulations, we systematically reduce the meridional sea surface temperature gradient by modifying the latitudinal distribution of cloud albedo or atmospheric CO<sub>2</sub> concentration. The simulated zonal temperature gradient in the equatorial Pacific adjusts proportionally. These experiments and idealized modelling indicate that the meridional temperature gradient controls upper-ocean stratification in the tropics, which in turn controls the zonal gradient along the equator, as well as heat export from the tropical oceans. We conclude that this tight linkage between the two sea surface temperature gradients posits a fundamental constraint on both past and future climates.</p>
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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.