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30,334 results for “Responsiveness”
Replication data for: Demographic declines and responses of breeding bird populations to human footprint in the Athabasca Oil Sands Region, Alberta, Canada
<p class="MsoNormal">This data package includes data files and an R script to reproduce results reported in the paper "Demographic declines and responses of breeding bird populations to human footprint in the Athabasca Oil Sands Region, Alberta, Canada". Analyses include hierarchical multispecies models applied to data from 31 bird species at 38 Monitoring Avian Productivity and Survivorship (MAPS) stations to assess 10-year (2011–2020) demographic trends and responses to energy sector disturbance (human footprint proportion) in the Athabasca oil sands region of Alberta, Canada. Adult captures, productivity, and residency probability all declined over the study period, and adult apparent survival probability also tended to decline. Trends in adult captures, productivity, and survival were all more negative at stations with larger increases in disturbance over the study period. Species associated with early seral stages were more commonly captured at more disturbed stations, while species typical of mature forests were more commonly captured at less disturbed stations. Productivity was positively correlated with disturbance within 5 km of stations after controlling for disturbance within 1 km of stations. Adult apparent survival showed relatively little response to disturbance; stresses experienced beyond the breeding grounds likely play a larger role in influencing survival. Residency probability was negatively related to disturbance within 1-km scale of stations and could reflect processes affecting the ability of birds to establish or maintain territories in disturbed landscapes.</p>
Geometries for "Linear Response Properties of Solvated Systems: A Computational Study"
<p>Geometry files (.xyz format) used in the paper "Linear Response Properties of Solvated Systems: A Computational Study"</p>
Biological and biogeochemical responses of benthic communities to marine heatwaves - BioHeat
<p>The dataset presents data from a laboratory experiment exploring the effect of heatwaves of different intensities on benhic bioturbation, community excretion and biogeochemical cycling of solutes. <span>We tested the effects of short-term, moderate and strong marine heatwaves on macrofauna bioturbation and associated solute fluxes as examples of ecosystem functioning. We also measured macrofaunal excretion rates to assess effects of temperature on macrofauna metabolism. For this experiment, we used unmanipulated sediment cores with natural animal communities collected from a muddy location at 32 m depth in the northern Baltic Sea. Despite the mechanistic effect of bioturbation remaining unchanged between the treatments, there were significant differences in oxygen consumption, solute fluxes and excretion. Biogeochemical and biological processes were boosted by the moderate heatwave, whereas biogeochemical cycling seemed to decrease under a strong heatwave.</span></p>
Aesthetic responses to the Covid-19 pandemic: The corona-performance No Problama. A case study
<p>The video files document the artistic content of the corona performance <em>No problama. </em>Each video presents music, verbal texts and photos from work processes and the final performance on 21 May 2021. The performance mirrors events, emotions and individuals' responses to the crisis during the first weeks of the lockdown in Norway in March 2020. Music students, children, teachers and dancers took part in the project.</p>
Plant secondary metabolic responses to global climate change: A meta-analysis in medicinal and aromatic plants
<p><span>Plant secondary metabolites (SMs) play crucial roles in plant-environment interactions and contribute greatly to human health. Global climate changes are expected to dramatically affect plant secondary metabolism, yet a systematic understanding of such influences is still lacking. Here, we employed medicinal and aromatic plants (MAAPs) as model plant taxa and performed a meta-analysis from 360 publications using 1828 paired observations to assess the responses of different SMs levels and the accompanying plant traits to elevated carbon dioxide (eCO<sub>2</sub>), elevated temperature (eT), elevated nitrogen deposition (eN), and decreased precipitation (dP). The overall results showed that phenolic and terpenoid levels generally respond positively to eCO<sub>2</sub> but negatively to eN, while the total alkaloid concentration was increased remarkably by eN. By contrast, dP promotes the levels of all SMs, while eT exclusively exerts a positive influence on the levels of phenolic compounds. Further analysis highlighted the dependence of SM responses on different moderators such as plant functional types, climate change levels or exposure durations, mean annual temperature and mean annual precipitation. Moreover, plant phenolic and terpenoid responses to climate changes could be attributed to the variations in C/N ratio and total soluble sugar levels, while the <em>trade-off</em> supposition contributed to SM responses to climate changes other than eCO<sub>2</sub>. Taken together, our results predicted the distinctive SM responses to diverse climate changes in MAAPs, and allowed us to define potential moderators responsible for these variations. Further, linking SM responses to C-N metabolism and growth-defence balance provided biological understandings in terms of plant secondary metabolic regulation.</span></p>
Variation in arthropod responses to tropical landscape transformation: spiders 2015
<b>Description: </b><p>Postdoctoral project</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/61"><b>Ecosystem quality and herbivore dynamics in tropical rainforests fragmented by deforestation</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>Australian Research Council (ARC Discovery Project, DP140101541)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=7252200">here</a></p><p><b>Files: </b>This consists of 1 file: Maunsell_spiders_220811.xlsx</p><p><b>Maunsell_spiders_220811.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>Spider assemblage composition data 2015</b> (described in worksheet SpiderAssem)</p><p>Description: Spider assemblage composition data collected at the SAFE Project in 2015. Worksheet contains a site by morphospecies abundance matrix. Spiders were collected by beating plant foliage for a period of 20 minutes per location. Spiders were identified to family and seperated into morphospecies using a combination of genitalia dissections and DNA barcoding (CO1). </p><p>Number of fields: 219</p><p>Number of data rows: 48</p><p>Fields: </p><ul><li><b>Date</b>: Date of the collection (Field type: date)</li><li><b>Location</b>: SAFE Project location 2nd order (Field type: location)</li><li><b>Type</b>: Disturbance gradient (Field type: ordered categorical)</li><li><b>ANA01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ARA01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ARA02_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ARA03_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ARA04_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ARA05_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ARA06_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ARA07_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ARA08_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ARA09_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ARA10_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ARA11_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ARA12_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ARA13_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ARA14_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ARA15_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ARA16_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>COR01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>COR02_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>COR03_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>COR04_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>COR05_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>DIC01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>EUT01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>EUT02_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>EUT03_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>EUT04_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>EUT05_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>EUT06_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>GNA01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>HAH01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>HAH02_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>HER01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>LIN01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>LIN02_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>MIM01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>MIM02_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>MIM03_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>MYS01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>MYS02_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>MYS03_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>OON01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>OON02_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>OON03_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>OON05_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>OON06_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>OON08_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>OON09_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>OON10_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>OON11_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>OXY01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>OXY02_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>OXY03_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>OXY04_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>OXY05_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>OXY06_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>PHO01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>PHO02_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>PHO03_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>PHO04_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>PHO05_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>PHO06_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>PHO07_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>PHO08_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>PHO09_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>PHO11_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>PHO13_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>PIS01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL02_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL03_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL04_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL05_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL06_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL07_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL08_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL09_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL10_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL11_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL12_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL13_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL14_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL15_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL16_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL17_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL18_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL19_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL20_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL21_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL22_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL23_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL24_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL25_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL26_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL27_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL28_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL29_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL30_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL31_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL32_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL33_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL34_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL35_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL36_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL37_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL38_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL39_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL40_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL41_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL42_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL43_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL44_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL45_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL46_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SAL47_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>SCY01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>TEB01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>TET01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>TET02_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>TET03_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>TET04_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>TET05_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>TET06_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD02_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD03_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD04_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD05_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD06_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD07_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD08_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD09_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD10_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD11_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD12_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD13_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD14_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD15_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD16_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD17_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD18_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD19_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD20_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD21_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD22_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD23_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD24_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD25_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD26_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD27_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD28_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD29_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD30_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD31_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD32_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD33_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD34_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD35_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD36_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD37_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD38_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD39_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD40_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD41_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD42_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD43_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD44_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD45_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD46_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD47_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD48_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD49_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD50_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD51_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD52_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD53_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD54_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD55_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD56_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD57_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD58_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD59_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD60_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD61_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD62_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD63_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD64_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD65_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD66_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THD67_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO02_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO03_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO04_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO05_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO06_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO07_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO08_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO09_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO10_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO11_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO12_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO13_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO14_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO15_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO16_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO17_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO18_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO19_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THO20_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>THS01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ULO01_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ULO02_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ULO03_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ULO04_count</b>: Number collected in twenty minute period (Field type: abundance)</li><li><b>ULO05_count</b>: Number collected in twenty minute period (Field type: abundance)</li></ul></li></ol><p><b>Date range: </b>2015-03-10 to 2015-04-11</p><p><b>Latitudinal extent: </b>4.6373 to 4.7714</p><p><b>Longitudinal extent: </b>116.9549 to 117.7021</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div> -  Animalia <br> -  -  Arthropoda <br> -  -  -  Arachnida <br> -  -  -  -  Araneae <br> -  -  -  -  -  Linyphiidae <br> -  -  -  -  -  -  [LIN01] <br> -  -  -  -  -  -  [LIN02] <br> -  -  -  -  -  Uloboridae <br> -  -  -  -  -  -  [ULO01] <br> -  -  -  -  -  -  [ULO02] <br> -  -  -  -  -  -  [ULO03] <br> -  -  -  -  -  -  [ULO04] <br> -  -  -  -  -  -  [ULO05] <br> -  -  -  -  -  Pisauridae <br> -  -  -  -  -  -  [PIS01] <br> -  -  -  -  -  Hersiliidae <br> -  -  -  -  -  -  [HER01] <br> -  -  -  -  -  Corinnidae <br> -  -  -  -  -  -  [COR01] <br> -  -  -  -  -  -  [COR02] <br> -  -  -  -  -  -  [COR03] <br> -  -  -  -  -  -  [COR04] <br> -  -  -  -  -  -  [COR05] <br> -  -  -  -  -  Salticidae <br> -  -  -  -  -  -  [SAL01] <br> -  -  -  -  -  -  [SAL02] <br> -  -  -  -  -  -  [SAL03] <br> -  -  -  -  -  -  [SAL04] <br> -  -  -  -  -  -  [SAL05] <br> -  -  -  -  -  -  [SAL06] <br> -  -  -  -  -  -  [SAL07] <br> -  -  -  -  -  -  [SAL08] <br> -  -  -  -  -  -  [SAL09] <br> -  -  -  -  -  -  [SAL10] <br> -  -  -  -  -  -  [SAL11] <br> -  -  -  -  -  -  [SAL12] <br> -  -  -  -  -  -  [SAL13] <br> -  -  -  -  -  -  [SAL14] <br> -  -  -  -  -  -  [SAL15] <br> -  -  -  -  -  -  [SAL16] <br> -  -  -  -  -  -  [SAL17] <br> -  -  -  -  -  -  [SAL18] <br> -  -  -  -  -  -  [SAL19] <br> -  -  -  -  -  -  [SAL20] <br> -  -  -  -  -  -  [SAL21] <br> -  -  -  -  -  -  [SAL22] <br> -  -  -  -  -  -  [SAL23] <br> -  -  -  -  -  -  [SAL24] <br> -  -  -  -  -  -  [SAL25] <br> -  -  -  -  -  -  [SAL26] <br> -  -  -  -  -  -  [SAL27] <br> -  -  -  -  -  -  [SAL28] <br> -  -  -  -  -  -  [SAL29] <br> -  -  -  -  -  -  [SAL30] <br> -  -  -  -  -  -  [SAL31] <br> -  -  -  -  -  -  [SAL32] <br> -  -  -  -  -  -  [SAL33] <br> -  -  -  -  -  -  [SAL34] <br> -  -  -  -  -  -  [SAL35] <br> -  -  -  -  -  -  [SAL36] <br> -  -  -  -  -  -  [SAL37] <br> -  -  -  -  -  -  [SAL38] <br> -  -  -  -  -  -  [SAL39] <br> -  -  -  -  -  -  [SAL40] <br> -  -  -  -  -  -  [SAL41] <br> -  -  -  -  -  -  [SAL42] <br> -  -  -  -  -  -  [SAL43] <br> -  -  -  -  -  -  [SAL44] <br> -  -  -  -  -  -  [SAL45] <br> -  -  -  -  -  -  [SAL46] <br> -  -  -  -  -  -  [SAL47] <br> -  -  -  -  -  Dictynidae <br> -  -  -  -  -  -  [DIC01] <br> -  -  -  -  -  Tetragnathidae <br> -  -  -  -  -  -  [TET01] <br> -  -  -  -  -  -  [TET02] <br> -  -  -  -  -  -  [TET03] <br> -  -  -  -  -  -  [TET04] <br> -  -  -  -  -  -  [TET05] <br> -  -  -  -  -  -  [TET06] <br> -  -  -  -  -  Mimetidae <br> -  -  -  -  -  -  [MIM01] <br> -  -  -  -  -  -  [MIM02] <br> -  -  -  -  -  -  [MIM03] <br> -  -  -  -  -  Scytodidae <br> -  -  -  -  -  -  [SCY01] <br> -  -  -  -  -  Pholcidae <br> -  -  -  -  -  -  [PHO01] <br> -  -  -  -  -  -  [PHO02] <br> -  -  -  -  -  -  [PHO03] <br> -  -  -  -  -  -  [PHO04] <br> -  -  -  -  -  -  [PHO05] <br> -  -  -  -  -  -  [PHO06] <br> -  -  -  -  -  -  [PHO07] <br> -  -  -  -  -  -  [PHO08] <br> -  -  -  -  -  -  [PHO09] <br> -  -  -  -  -  -  [PHO11] <br> -  -  -  -  -  -  [PHO13] <br> -  -  -  -  -  Mysmenidae <br> -  -  -  -  -  -  [MYS01] <br> -  -  -  -  -  -  [MYS02] <br> -  -  -  -  -  -  [MYS03] <br> -  -  -  -  -  Araneidae <br> -  -  -  -  -  -  [ARA01] <br> -  -  -  -  -  -  [ARA02] <br> -  -  -  -  -  -  [ARA03] <br> -  -  -  -  -  -  [ARA04] <br> -  -  -  -  -  -  [ARA05] <br> -  -  -  -  -  -  [ARA06] <br> -  -  -  -  -  -  [ARA07] <br> -  -  -  -  -  -  [ARA08] <br> -  -  -  -  -  -  [ARA09] <br> -  -  -  -  -  -  [ARA10] <br> -  -  -  -  -  -  [ARA11] <br> -  -  -  -  -  -  [ARA12] <br> -  -  -  -  -  -  [ARA13] <br> -  -  -  -  -  -  [ARA14] <br> -  -  -  -  -  -  [ARA15] <br> -  -  -  -  -  -  [ARA16] <br> -  -  -  -  -  Cheiracanthiidae <br> -  -  -  -  -  -  [EUT01] <br> -  -  -  -  -  -  [EUT02] <br> -  -  -  -  -  -  [EUT03] <br> -  -  -  -  -  -  [EUT04] <br> -  -  -  -  -  -  [EUT05] <br> -  -  -  -  -  -  [EUT06] <br> -  -  -  -  -  Gnaphosidae <br> -  -  -  -  -  -  [GNA01] <br> -  -  -  -  -  Oxyopidae <br> -  -  -  -  -  -  [OXY01] <br> -  -  -  -  -  -  [OXY02] <br> -  -  -  -  -  -  [OXY03] <br> -  -  -  -  -  -  [OXY04] <br> -  -  -  -  -  -  [OXY05] <br> -  -  -  -  -  -  [OXY06] <br> -  -  -  -  -  Tetrablemmidae <br> -  -  -  -  -  -  [TEB01] <br> -  -  -  -  -  Theridiosomatidae <br> -  -  -  -  -  -  [THS01] <br> -  -  -  -  -  Oonopidae <br> -  -  -  -  -  -  [OON01] <br> -  -  -  -  -  -  [OON02] <br> -  -  -  -  -  -  [OON03] <br> -  -  -  -  -  -  [OON05] <br> -  -  -  -  -  -  [OON06] <br> -  -  -  -  -  -  [OON08] <br> -  -  -  -  -  -  [OON09] <br> -  -  -  -  -  -  [OON10] <br> -  -  -  -  -  -  [OON11] <br> -  -  -  -  -  Anapidae <br> -  -  -  -  -  -  [ANA01] <br> -  -  -  -  -  Thomisidae <br> -  -  -  -  -  -  [THO01] <br> -  -  -  -  -  -  [THO02] <br> -  -  -  -  -  -  [THO03] <br> -  -  -  -  -  -  [THO04] <br> -  -  -  -  -  -  [THO05] <br> -  -  -  -  -  -  [THO06] <br> -  -  -  -  -  -  [THO07] <br> -  -  -  -  -  -  [THO08] <br> -  -  -  -  -  -  [THO09] <br> -  -  -  -  -  -  [THO10] <br> -  -  -  -  -  -  [THO11] <br> -  -  -  -  -  -  [THO12] <br> -  -  -  -  -  -  [THO13] <br> -  -  -  -  -  -  [THO14] <br> -  -  -  -  -  -  [THO15] <br> -  -  -  -  -  -  [THO16] <br> -  -  -  -  -  -  [THO17] <br> -  -  -  -  -  -  [THO18] <br> -  -  -  -  -  -  [THO19] <br> -  -  -  -  -  -  [THO20] <br> -  -  -  -  -  Hahniidae <br> -  -  -  -  -  -  [HAH01] <br> -  -  -  -  -  -  [HAH02] <br> -  -  -  -  -  Theridiidae <br> -  -  -  -  -  -  [THD01] <br> -  -  -  -  -  -  [THD02] <br> -  -  -  -  -  -  [THD03] <br> -  -  -  -  -  -  [THD04] <br> -  -  -  -  -  -  [THD05] <br> -  -  -  -  -  -  [THD06] <br> -  -  -  -  -  -  [THD07] <br> -  -  -  -  -  -  [THD08] <br> -  -  -  -  -  -  [THD09] <br> -  -  -  -  -  -  [THD10] <br> -  -  -  -  -  -  [THD11] <br> -  -  -  -  -  -  [THD12] <br> -  -  -  -  -  -  [THD13] <br> -  -  -  -  -  -  [THD14] <br> -  -  -  -  -  -  [THD15] <br> -  -  -  -  -  -  [THD16] <br> -  -  -  -  -  -  [THD17] <br> -  -  -  -  -  -  [THD18] <br> -  -  -  -  -  -  [THD19] <br> -  -  -  -  -  -  [THD20] <br> -  -  -  -  -  -  [THD21] <br> -  -  -  -  -  -  [THD22] <br> -  -  -  -  -  -  [THD23] <br> -  -  -  -  -  -  [THD24] <br> -  -  -  -  -  -  [THD25] <br> -  -  -  -  -  -  [THD26] <br> -  -  -  -  -  -  [THD27] <br> -  -  -  -  -  -  [THD28] <br> -  -  -  -  -  -  [THD29] <br> -  -  -  -  -  -  [THD30] <br> -  -  -  -  -  -  [THD31] <br> -  -  -  -  -  -  [THD32] <br> -  -  -  -  -  -  [THD33] <br> -  -  -  -  -  -  [THD34] <br> -  -  -  -  -  -  [THD35] <br> -  -  -  -  -  -  [THD36] <br> -  -  -  -  -  -  [THD37] <br> -  -  -  -  -  -  [THD38] <br> -  -  -  -  -  -  [THD39] <br> -  -  -  -  -  -  [THD40] <br> -  -  -  -  -  -  [THD41] <br> -  -  -  -  -  -  [THD42] <br> -  -  -  -  -  -  [THD43] <br> -  -  -  -  -  -  [THD44] <br> -  -  -  -  -  -  [THD45] <br> -  -  -  -  -  -  [THD46] <br> -  -  -  -  -  -  [THD47] <br> -  -  -  -  -  -  [THD48] <br> -  -  -  -  -  -  [THD49] <br> -  -  -  -  -  -  [THD50] <br> -  -  -  -  -  -  [THD51] <br> -  -  -  -  -  -  [THD52] <br> -  -  -  -  -  -  [THD53] <br> -  -  -  -  -  -  [THD54] <br> -  -  -  -  -  -  [THD55] <br> -  -  -  -  -  -  [THD56] <br> -  -  -  -  -  -  [THD57] <br> -  -  -  -  -  -  [THD58] <br> -  -  -  -  -  -  [THD59] <br> -  -  -  -  -  -  [THD60] <br> -  -  -  -  -  -  [THD61] <br> -  -  -  -  -  -  [THD62] <br> -  -  -  -  -  -  [THD63] <br> -  -  -  -  -  -  [THD64] <br> -  -  -  -  -  -  [THD65] <br> -  -  -  -  -  -  [THD66] <br> -  -  -  -  -  -  [THD67] <br></div><p></p>
Thermal design and full-scale thermal response test on Energy Walls
<p>This folder contains a spreadsheet that includes the underlying data referred to the publication mentioned in the title.</p> <p>For each figure, the underlying data are listed in a dedicated sub-sheet.</p>
Hydrologic Response of the Columbia River System to Climate Change
<p>Hydrologic projections for the Columbia River Basin and coastal drainages in the Pacific Northwest, United States.</p> <p>See http://www.hydro.washington.edu/CRCC/ for more information.</p> <p> </p>
Data supplementing article "Tidal response to sea-level rise in different types of estuaries: the importance of length, bathymetry, and geometry" submitted to Geophysical Research Letters
<p>These data supplement the article "Tidal response to sea-level rise in different types of estuaries: the importance of length, bathymetry, and geometry". </p> <p>contact: Jiabi Du, jiabi.du@gmail.com</p> <p>Below are descriptions of the data files included here:</p> <p>1. ReadMe.txt</p> <p>- the description of each model configuration is listed in this file, inlcuding the estuarine geometry type, length, and bathymetry type. </p> <p>2. model grid and surface elevation output</p> <p>- In each directory named after the grid_name, a grid file with .gr3 format is included. <br> The .gr3 file contains two parts: the location of each node (first part), and the node number for each triangle grid (second part).</p> <p>- Two sub_directory name 'base' and 'slr' contains the time series of water level. </p> <p>3. MatlaScript ExtractWL</p> <p>- a function named "f_extract_wl.m" are used to extract the station output</p> <p> </p>
Matrimid-JUC-62 and Matrimid-PCN-250 mixed matrix membranes displaying light-responsive gas separation and beneficial ageing characteristics for CO2/N2 separation
<p>FTIR, TGA, XRD and gas permeation results for our study of Matrimid-JUC-62 and Matrimid-PCN-250 mixed matrix membranes, including light-responsive properties.</p> <p>Published in: Prasetya, N., Teck, A.A., Ladewig, B.P., <em>Matrimid-JUC-62 and Matrimid-PCN-250 mixed matrix membranes displaying light-responsive gas separation and beneficial ageing characteristics for CO<sub>2</sub>/N<sub>2</sub> separation</em>, (2018) <strong>Scientific Reports</strong>, 8 (1), 2944. </p> <p>doi:<a href="http://dx.doi.org/10.1038/s41598-018-21263-7">10.1038/s41598-018-21263-7</a></p>
Data from "Effects of a brief mindfulness-meditation intervention on neural measures of response inhibition in cigarette smokers", Plos One 2017
<p>32-channel(+8) raw data (Biosemi Active two, 10-20, 512Hz) unfiltered from the 2018 Plos ONE paper "Effects of a brief mindfulness-meditation intervention on neural measures of response inhibition in cigarette smokers"</p>
Data for "Multifractal comparison of reflectivity and polarimetric rainfall data from C- and X-band radars and respective hydrological responses of a complex catchment model"
<p>The data files arranged here correspond to the data used in the paper: “Multifractal comparison of reflectivity and polarimetric rainfall data from C- and X-band radars and respective hydrological responses of a complex catchment model”, submitted to <em>Water</em>.</p> <p>The data organized as follows:</p> <ul> <li>Data_type_20150912_time_steps.mat: the rainfall data for 3 different products of the X-band radar (FIR filter, a=200, b=1.6; FIR filter, a=150, b=1.3; simple filter, a=150, b=1.3) for the event of 12-13 September 2015, over an area of 64 km x 64 km.</li> <li>Data_type_Event_time_steps.mat: X-band radar data (FIR filter, a=150, b=1.3) for the events of 16 September 2015 and 5-6 October 2015, over an area of 64 km x 64 km.</li> <li>Sub-catchment_name_Data_type_Event.txt: the rainfall series for each of 26 sub-catchments of the model, for 3 different types of rainfall data (C-band, X-band and rain gauges) for the events of 12-13 September 2015, 16 September 2015 and 5-6 October 2015.</li> <li>X-band_Pixels_Event.txt: the rainfall series for all 6 X-band radar pixels corresponding to the 6 rain gauges for the 3 studied events (12-13 September 2015, 16 September 2015, and 5-6 October 2015).</li> <li>X-Band_Optim 20150916_Measurement_point_name.txt: flow simulated at each of the 4 measurement points with X-band data for the 16 September 2015 event, with the implementation of the tool mimicking the regulation optimization.</li> <li>Data_type_Event_Measurement_point_name.txt: flow simulated at each of the 4 measurement points with 3 different types of rainfall data (C-band, X-band and rain gauges) for the 3 studied events (12-13 September 2015, 16 September 2015, and 5-6 October 2015), without the implementation of the tool mimicking the regulation optimization.</li> </ul> <p>The original C-band radar data remains property of Météo-France and was provided to the authors for this research study, without any possibility of data disclosure.</p> <p>The details on how the rainfall series were generated over each sub-catchment could be found in the paper.</p> <p>The authors greatly acknowledge partial financial supports of the Chair “Hydrology for resilient cities” endowed by Veolia, and of the Department of Science and Technology of the Brazilian Army. The authors are thankful to M Bernard Urban (Météo-France) for providing access to the C-band radar data and documentation in the framework of the INTERREG NWE RainGain project.</p>
Response of surface temperature to afforestation in the Kubuqi Desert, Inner Mongolia
<p>This is the data used in “Response of surface temperature to afforestation in the Kubuqi Desert, Inner Mongolia” by Wang et al, for Journal of Geophysical Research - Atmospheres [MS#2017JD027522].</p>
A Numerical Study of Tropical Cyclone and Ocean Responses to Air-sea Momentum Flux at High Winds
<p>The simulation data output from FIO-AOW for tropical cyclone study</p>
Supplementary material: Mammal diversity responses to anthropic, environmental, and seasonal changes within Caatinga seasonal dry forest landscapes
<p>Caatinga's conservation and biodiversity are threatened due to the intensification of anthropic activities and climate change. The mammals have different responses to seasonal and anthropic changes, however particularly in Caatinga, these effects are still poorly understood. We assessed the influence of anthropic (distance from urban areas and wind farms), environmental (distance from water), and seasonal (Normalized Difference Vegetation Index – NDVI and land surface temperature - LST) variables on the number of records and richness of medium and large-sized mammals in Brazilian Caatinga. We used camera traps in 2016/2017 and 2018/2019, estimated the variation (cv) of NDVI and LST, and generated Euclidean distance maps to anthropic and environmental variables at 250, 500, and 1000 m spatial scales. We performed Generalized Linear Models, used the Akaike information criterion, and calculated model averaging to assess the strength and direction of effect and the uncertainties of the winner models, respectively. The distance from wind farms and maximum LST had a noticeable effect on the number of records and total richness. The distance from wind farms had a negative effect on the records of <em>Dicotyles tajacu</em> and a positive effect on the records of <em>Leopardus pardalis</em> and richness. The maximum LST had a negative effect on the records of<em> Leopardus pardalis </em>and a positive<em> </em>effect on the records of <em>Puma concolor </em>and<em> Cerdocyon thous</em>. Our results emphasize that an unsustainable expansion of wind farms is likely to compromise mammal diversity. We found an opposite pattern for some species regarding LST. However, it is important to highlight that the conservation of vegetation areas on the top of mountains and springs, and the installation of artificial water sources are important strategies to mitigate the impacts of high temperatures on mammals' biodiversity in Caatinga.</p>
Survey responses from stakeholders managing, growing, advising or assessing UK populations of Juniperus communis
<p>Increased imports of plants and timber through global trade networks provide frequent opportunities for introduction of novel plant pathogens that can cross-over from commercial to natural environments, threatening native species and ecosystem functioning. Prevention or management of such outbreaks relies on a diversity of cross-sectoral stakeholders acting along the invasion pathway. Yet guidelines are often only produced for a small number of stakeholders, missing opportunities to consider ways to control outbreaks in other parts of the pathway. We used the infection of common juniper with the invasive pathogen <em>Phytophthora austrocedri</em> as a case study to explore the utility of decision tools for managing outbreaks of plant pathogens in the wider environment. We invited stakeholders who manage or monitor juniper populations or supply plants or management advice to participate in a survey exploring their awareness of, and ability to use, an existing decision tree produced by a coalition of statutory agencies augmented with new distribution maps designed by the authors. Awareness of the decision tree was low across all stakeholder groups including those planting juniper for restoration purposes. Stakeholders requested that decision tools contain greater detail about environmental conditions that increase host vulnerability to the pathogen, and clearer examples of when management practices implicated in pathogen introduction or spread should not be adopted. The results demonstrate the need to set clear objectives for the purpose of decision tools and to frame and co-produce them with many different stakeholders, including overlooked groups such as growers and advisory agents, to improve management of pathogens in the wider environment.</p>
Heritability and genome-wide association study of vaccine-induced immune response in Beagles: A pilot study
<p>Both genetic and non-genetic factors contribute to individual variation in the immune response to vaccination. Understanding how genetic background influences variation in both the magnitude and persistence of vaccine-induced immunity is vital for improving vaccine development and identifying possible causes of vaccine failure. Dogs provide a relevant biomedical model for investigating mammalian vaccine genetics; canine breed structure and long linkage disequilibrium simplify genetic studies in this species compared to humans. The objective of this study was to estimate the heritability of the antibody response to vaccination against viral and bacterial pathogens and to identify genes driving variation of the immune response to vaccination in Beagles. Sixty puppies were immunized following a standard vaccination schedule with an attenuated combination vaccine containing antigens for canine adenovirus type 2, canine distemper virus, canine parainfluenza virus, canine parvovirus, and four strains of <em>Leptospira</em> bacteria. Serum antibody measurements for each viral and bacterial component were measured at multiple time points. Heritability estimations and GWAS were conducted using SNP genotypes at 279,902 markers together with serum antibody titer phenotypes. The heritability estimates were: (1) to <em>Leptospira</em> antigens, ranging from 0.178 to 0.628; and (2) to viral antigens, ranging from 0.199 to 0.588. There was not a significant difference between the overall heritability of vaccine-induced immune response to <em>Leptospira</em> antigens compared to viral antigens. Genetic architecture indicates that SNPs of low to high effect contribute to immune response to vaccination. GWAS identified two genetic markers associated with vaccine-induced immune response phenotypes. Collectively, these findings indicate that genetic regulation of the immune response to vaccination is antigen-specific and influenced by multiple genes of small effect.</p>
Identifying conceptual neural responses to symbolic numerals
<p>The goal of measuring conceptual processing in numerical cognition is distanced by the possibility that neural responses to symbolic numerals are influenced by physical stimulus confounds. Here, we targeted conceptual responses to parity (even <em>vs. </em>odd), using electroencephalographic (EEG) frequency-tagging with a symmetry/asymmetry design. Arabic numerals (2–9) were presented at 7.5 Hz in 50-s sequences; odd and even numbers were alternated to target differential, "asymmetry" responses to parity at 3.75 Hz (7.5 Hz/2). Parity responses were probed with four different stimulus sets, increasing in intra-numeral stimulus variability, and with two control conditions comprised of non-conceptual numeral alternations. Significant asymmetry responses were found over the occipitotemporal cortex to all conditions, even for the arbitrary controls. The large physical-differences control condition elicited the largest response in the stimulus set with the lowest level of variability (1 font). Only in the stimulus set with the highest level of variability (20 drawn, colored exemplars/numeral) did the response to parity surpass both control conditions. These findings show that physical differences across small sets of Arabic numerals can strongly influence, and even account for, automatic brain responses. However, carefully designed control conditions and highly variable stimulus sets may be used towards identifying truly conceptual neural responses.</p>
Data from: Response to food restriction, but not social information use, varies seasonally in captive cardueline finches
<p>Temperate winters can impose severe conditions on songbirds that threaten survival, including shorter days and often lower temperature and food availability. One well-studied mechanism by which songbirds cope with such conditions is seasonal acclimatization of thermal metabolic traits, with strong evidence for both preparative and responsive changes in thermogenic capacity (i.e., the ability to generate heat) to low winter temperature. However, a bird's ability to cope with seasonal extremes or unpredictable events is likely dependent on a combination of behavioral and physiological traits that function to maintain allostatic balance. The ability to cope with reduced food availability may be an important component of organismal response to temperate winters in songbirds. Here we compare responses to experimentally reduced food availability at different times of year in captive red crossbills (<em>Loxia curvirostra</em>) and pine siskins (<em>Spinus pinus</em>) – two species that cope with variable food resources and live in cold places – to investigate seasonal changes in the organismal response to food availability. Further, red crossbills are known to use social information to improve response to reduced food availability, so we also examine whether use of social information in this context varies seasonally in this species. We find that pine siskins and red crossbills lose less body mass during time-restricted feedings in late winter compared to summer, and that red crossbills further benefit from social information gathered from observing other food-restricted red crossbills in both seasons. Observed changes in body mass were only partially explained by seasonal differences in food intake. Our results demonstrate seasonal acclimation to food stress and social information use across seasons in a controlled captive environment and highlight the importance of considering diverse physiological systems (e.g., thermogenic, metabolic, digestive, etc) to understand organismal responses to environmental challenges.</p>
Data from: Testing frameworks for early life effects: The developmental constraints and adaptive response hypotheses do not explain key fertility outcomes in wild female baboons
<p>In evolutionary ecology, two classes of explanations are frequently invoked to explain "early life effects" on adult outcomes. Developmental constraints (DC) explanations contend that costs of early adversity arise from limitations adversity places on optimal development. Adaptive response (AR) hypotheses propose that later life outcomes will be worse when early and adult environments are poorly "matched." Here, we use recently proposed mathematical definitions for these hypotheses and a quadratic-regression based approach to test the long-term consequences of variation in developmental environments on fertility in wild baboons. We evaluate whether low rainfall and/or dominance rank during development predict three female fertility measures in adulthood, and whether any observed relationships are consistent with DC and/or AR. Neither rainfall during development nor the difference between rainfall in development and adulthood predicted any fertility measures. Females who were low-ranking during development had an elevated risk of losing infants later in life, and greater change in rank between development and adulthood predicted greater risk of infant loss. However, both effects were statistically marginal and consistent with alternative explanations, including adult environmental quality effects. Consequently, our data do not provide compelling support for either of these common explanations for the evolution of early life effects.</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.