cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc26kpbt
title: CCDC 2042786: Experimental Crystal Structure Determination

description: Related Article: Max Widemann, Klaus Eichele, Hartmut Schubert, Christian P. Sindlinger, Steffen Klenner, Rainer Pöttgen, Lars Wesemann|2021|Angew.Chem.,Int.Ed.|60|5882|doi:10.1002/anie.202015725
DOI: 10.5517/ccdc.csd.cc26kpcv
title: CCDC 2042787: Experimental Crystal Structure Determination

description: Related Article: Max Widemann, Klaus Eichele, Hartmut Schubert, Christian P. Sindlinger, Steffen Klenner, Rainer Pöttgen, Lars Wesemann|2021|Angew.Chem.,Int.Ed.|60|5882|doi:10.1002/anie.202015725
DOI: 10.5517/ccdc.csd.cc26kpdw
title: CCDC 2042788: Experimental Crystal Structure Determination

description: Related Article: Max Widemann, Klaus Eichele, Hartmut Schubert, Christian P. Sindlinger, Steffen Klenner, Rainer Pöttgen, Lars Wesemann|2021|Angew.Chem.,Int.Ed.|60|5882|doi:10.1002/anie.202015725
DOI: 10.5517/ccdc.csd.cc26kpfx
title: CCDC 2042789: Experimental Crystal Structure Determination

description: Related Article: Max Widemann, Klaus Eichele, Hartmut Schubert, Christian P. Sindlinger, Steffen Klenner, Rainer Pöttgen, Lars Wesemann|2021|Angew.Chem.,Int.Ed.|60|5882|doi:10.1002/anie.202015725
DOI: 10.5517/ccdc.csd.cc26kpgy
title: CCDC 2042790: Experimental Crystal Structure Determination

description: Related Article: Max Widemann, Klaus Eichele, Hartmut Schubert, Christian P. Sindlinger, Steffen Klenner, Rainer Pöttgen, Lars Wesemann|2021|Angew.Chem.,Int.Ed.|60|5882|doi:10.1002/anie.202015725
DOI: 10.5517/ccdc.csd.cc26kphz
title: CCDC 2042791: Experimental Crystal Structure Determination

description: Related Article: Max Widemann, Klaus Eichele, Hartmut Schubert, Christian P. Sindlinger, Steffen Klenner, Rainer Pöttgen, Lars Wesemann|2021|Angew.Chem.,Int.Ed.|60|5882|doi:10.1002/anie.202015725
DOI: 10.5517/ccdc.csd.cc26kpj0
title: CCDC 2042792: Experimental Crystal Structure Determination

description: Related Article: Max Widemann, Klaus Eichele, Hartmut Schubert, Christian P. Sindlinger, Steffen Klenner, Rainer Pöttgen, Lars Wesemann|2021|Angew.Chem.,Int.Ed.|60|5882|doi:10.1002/anie.202015725
DOI: 10.5517/ccdc.csd.cc26kpk1
title: CCDC 2042793: Experimental Crystal Structure Determination

description: Related Article: Max Widemann, Klaus Eichele, Hartmut Schubert, Christian P. Sindlinger, Steffen Klenner, Rainer Pöttgen, Lars Wesemann|2021|Angew.Chem.,Int.Ed.|60|5882|doi:10.1002/anie.202015725
DOI: 10.5517/ccdc.csd.cc26kpl2
title: CCDC 2042794: Experimental Crystal Structure Determination

description: Related Article: Max Widemann, Klaus Eichele, Hartmut Schubert, Christian P. Sindlinger, Steffen Klenner, Rainer Pöttgen, Lars Wesemann|2021|Angew.Chem.,Int.Ed.|60|5882|doi:10.1002/anie.202015725
DOI: 10.5517/ccdc.csd.cc26pxhb
title: CCDC 2046852: Experimental Crystal Structure Determination

description: Related Article: Hongtai Chen, Liming Fan, Tuoping Hu, Xiutang Zhang|2021|Inorg.Chem.|60|3384|doi:10.1021/acs.inorgchem.0c03736
DOI: 10.5517/ccdc.csd.cc26qsnd
title: CCDC 2047694: Experimental Crystal Structure Determination

description: Related Article: Meng Jia Yin, Xiao Hong Xiong, Xue Feng Feng, Wen Yuan Xu, Rajamani Krishna, Feng Luo|2021|Inorg.Chem.|60|3447|doi:10.1021/acs.inorgchem.1c00033
DOI: 10.5517/ccdc.csd.cc26rd2g
title: CCDC 2048265: Experimental Crystal Structure Determination

description: Related Article: Xuan Kan, Jian-Cheng Wang, Jing-Lan Kan, Jin-Yan Shang, Hua Qiao, Yu-Bin Dong|2021|Inorg.Chem.|60|3393|doi:10.1021/acs.inorgchem.0c03783
DOI: 10.5517/ccdc.csd.cc26x2lt
title: CCDC 2052776: Experimental Crystal Structure Determination

description: Related Article: Mohammad Aslam, Sonaimuthu Mohandoss, Palanisamy Subramanian, SangGuan You, Won-Guen Yang, Sung Hong Kim, Yong Rok Lee|2021|Org.Lett.|23|1383|doi:10.1021/acs.orglett.1c00042
DOI: 10.5517/ccdc.csd.cc26x2nw
title: CCDC 2052778: Experimental Crystal Structure Determination

description: Related Article: Mohammad Aslam, Sonaimuthu Mohandoss, Palanisamy Subramanian, SangGuan You, Won-Guen Yang, Sung Hong Kim, Yong Rok Lee|2021|Org.Lett.|23|1383|doi:10.1021/acs.orglett.1c00042
DOI: 10.5517/ccdc.csd.cc26r3y1
title: CCDC 2048013: Experimental Crystal Structure Determination

description: Related Article: Ze-Ran Jing, Dong-Dong Liang, Jin-Miao Tian, Fu-Min Zhang, Yong-Qiang Tu|2021|Org.Lett.|23|1258|doi:10.1021/acs.orglett.0c04241
DOI: 10.6073/pasta/bcde678d31b6528f7297ceff0306b7d0
title: Jornada Basin LTER: Wireless meteorological station at NPP C-CALI site: 5-minute summary wind and air temperature data: 2013 - ongoing

description: 5-minute summary data at NPP C-CALI met station. Average air temperature, wind speed and wind direction are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP C-CALI site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature at approximate 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.6073/pasta/d347a2cd5e6df4f50400b784652a4754
title: Jornada Basin LTER: Wireless meteorological station at NPP C-CALI site: 1-hour summary data: 2013 - ongoing

description: Hourly summary data at NPP C-CALI met station. Average/maximum/minimum air temperature; average relative humidity and wind direction; average/maximum wind speed. These are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP C-CALI site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.6073/pasta/4fbd9c4625f512c1db58abe6ad750cfe
title: Jornada Basin LTER: Wireless meteorological station at NPP C-CALI site: 30-minute summary data: 2013 - ongoing

description: 30-minute summary data at NPP C-CALI met station. Average air temperature, relative humidity, wind speed and wind direction are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP C-CALI site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.6073/pasta/b1bffa4e515638dd484c4b35541cd100
title: Jornada Basin LTER: Wireless meteorological station at NPP C-CALI site: Daily summary data: 2013 - ongoing

description: Daily summary data at NPP C-CALI met station. Average/maximum/minimum air temperature; average/maximum relative humidity and wind speed and average wind direction. These are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP C-CALI site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.6073/pasta/0bad8dad396dbd5ab0b94e6ac7882cd4
title: Jornada Basin LTER: Wireless meteorological station at NPP C-CALI site: 1-second summary precipitation data: 2013 - ongoing

description: 1-second summary precipitation data at NPP C-CALI met station. Total precipitation per second is recorded only if there is measurable precipitation. This is recorded at an automated meteorological station installed at Jornada LTER NPP C-CALI site.. This climate station is operated by the Jornada LTER Program. IMPORTANT: Rainfall is only recorded when a bucket tip occurs on the tipping bucket rain gauge. If there is missing data due to equipment or other problems, there will be no indication of this within this dataset. The user needs to review precipitation values in the 30 minute, hourly, or data summary datasets to determine if there are missing periods in this 1 second detailed precipitation dataset. Reference the package i.d.'s knb-lter-jrn.210437016, knb-lter-jrn.210437031, and knb-lter-jrn.210437046 for the NPP C-CALI met station 30 minute, hourly, and daily summary datasets, respectively. This is an ONGOING dataset.
DOI: 10.6073/pasta/49e7a6ae75debdbf4a84714dd902cac3
title: Jornada Basin LTER: Wireless meteorological station at NPP C-CALI site: 30-minute soil volumetric water content data: 2013 - ongoing

description: 30-minute Soil Moisture data at NPP C-CALI met station. Collection of soil volumetric water content data at Jornada LTER NPP sites, New Mexico, supports the environmental monitoring objectives of the Jornada LTER monitoring program that look at plant-soil water dynamics. Volumetric water content, bulk electrical conductivity, soil temperature, and bulk dielectric permittivity are measured every 30 minutes at an automated meteorological station installed at Jornada LTER NPP C-CALI site. Measurements are made every 30 minutes at 10 cm, 20 cm, and 30 cm soil depths. This is an ONGOING dataset.
DOI: 10.6073/pasta/aea268dbda295189794379467b0ceed6
title: Jornada Basin LTER: Wireless meteorological station at NPP C-CALI site: Daily average soil volumetric water content data: 2013 - ongoing

description: Daily average of 30-minute Volumetric Water Content at NPP C-CALI met station. Collection of soil volumetric water content data at Jornada LTER NPP sites, New Mexico, supports the environmental monitoring objectives of the Jornada LTER monitoring program that look at plant-soil water dynamics. Volumetric water content, bulk electrical conductivity, soil temperature, and bulk dielectric permittivity are measured and calculated at an automated meteorological station installed at Jornada LTER NPP C-CALI site. The daily average at 3 soil depths is calculated from measurements made every 30 minutes at 10 cm, 20 cm, and 30 cm. This is an ONGOING dataset.
DOI: 10.6084/m9.figshare.14166995
title: Taxonomy assignment for OTUs - ITS amplicon sequences

description: ITS Taxonomy assignation for OTUs from soil samples of seedlings with fungal inoculate, seedlings without inoculate and control condition.
DOI: 10.6084/m9.figshare.14166995.v1
title: Taxonomy assignment for OTUs - ITS amplicon sequences

description: ITS Taxonomy assignation for OTUs from soil samples of seedlings with fungal inoculate, seedlings without inoculate and control condition.
DOI: 10.18112/openneuro.ds003382.v1.1.0
title: Monash vis-fPET-fMRI
DOI: 10.6084/m9.figshare.13140482
title: Processed data

description: Processed data corresponding to the following manuscript: <br><b>Temporal and spatial lags between wind, coastal upwelling, and blue whale occurrence</b><b><br></b><b>Authors: </b>Dawn R. Barlow<sup>1</sup>*, Holger Klinck<sup>2,3</sup>, Dimitri Ponirakis<sup>2</sup>, Christina Garvey<sup>4</sup>, Leigh G. Torres<sup>1</sup><sup></sup><br><sup>1</sup>Geospatial Ecology of Marine Megafauna Lab, Marine Mammal Institute, and Department of Fisheries and Wildlife, Oregon State University, Newport, Oregon, USA<sup>2</sup>Center for Conservation Bioacoustics, Cornell University, Ithaca, New York, USA<sup>3</sup>Marine Mammal Institute, Department of Fisheries and Wildlife, Oregon State University, Newport, Oregon, USA<sup>4</sup>University of Maryland, College Park, Maryland, USA*dawn.barlow@oregonstate.edu<br><b>Abstract: </b>Understanding relationships between physical drivers and biological response is central to advancing ecological knowledge. Wind is the physical forcing mechanism in coastal upwelling systems, however lags between wind input and biological responses are seldom quantified for marine predators. Lags were examined between wind at an upwelling source, decreased temperatures along the upwelling plume’s trajectory, and blue whale occurrence in New Zealand’s South Taranaki Bight region (STB). Wind speed and sea surface temperature (SST) were extracted for austral spring-summer months between 2009-2019. A hydrophone recorded blue whale vocalizations October 2016-March 2017. Timeseries cross-correlation analyses were conducted between wind speed, SST at different locations along the upwelling plume, and blue whale downswept vocalizations (“D calls”). Results document increasing lag times (0-2 weeks) between wind speed and SST consistent with the spatial progression of upwelling, culminating with increased D call density at the distal end of the plume three weeks after increased wind speeds at the upwelling source. Lag between wind events and blue whale aggregations (n = 34 aggregations 2013-2019) was 2.09 ± 0.43 weeks. Variation in lag was significantly related to the amount of wind over the preceding 30 days, which likely influences stratification. This study enhances knowledge of physical-biological coupling in upwelling ecosystems and enables improved forecasting of species distribution patterns for dynamic management.
DOI: 10.6084/m9.figshare.13140476
title: Timeseries cross-correlation outputs

description: Time series cross-correlation analysis output files, corresponding to the following manuscript: <br>Processed data corresponding to the following manuscript:<br><b>Temporal and spatial lags between wind, coastal upwelling, and blue whale occurrence</b><b><br></b><b>Authors: </b>Dawn R. Barlow<sup>1</sup>*, Holger Klinck<sup>2,3</sup>, Dimitri Ponirakis<sup>2</sup>, Christina Garvey<sup>4</sup>, Leigh G. Torres<sup>1</sup><sup></sup><br><sup>1</sup>Geospatial Ecology of Marine Megafauna Lab, Marine Mammal Institute, and Department of Fisheries and Wildlife, Oregon State University, Newport, Oregon, USA<sup>2</sup>Center for Conservation Bioacoustics, Cornell University, Ithaca, New York, USA<sup>3</sup>Marine Mammal Institute, Department of Fisheries and Wildlife, Oregon State University, Newport, Oregon, USA<sup>4</sup>University of Maryland, College Park, Maryland, USA*dawn.barlow@oregonstate.edu<br><b>Abstract: </b>Understanding relationships between physical drivers and biological response is central to advancing ecological knowledge. Wind is the physical forcing mechanism in coastal upwelling systems, however lags between wind input and biological responses are seldom quantified for marine predators. Lags were examined between wind at an upwelling source, decreased temperatures along the upwelling plume’s trajectory, and blue whale occurrence in New Zealand’s South Taranaki Bight region (STB). Wind speed and sea surface temperature (SST) were extracted for austral spring-summer months between 2009-2019. A hydrophone recorded blue whale vocalizations October 2016-March 2017. Timeseries cross-correlation analyses were conducted between wind speed, SST at different locations along the upwelling plume, and blue whale downswept vocalizations (“D calls”). Results document increasing lag times (0-2 weeks) between wind speed and SST consistent with the spatial progression of upwelling, culminating with increased D call density at the distal end of the plume three weeks after increased wind speeds at the upwelling source. Lag between wind events and blue whale aggregations (n = 34 aggregations 2013-2019) was 2.09 ± 0.43 weeks. Variation in lag was significantly related to the amount of wind over the preceding 30 days, which likely influences stratification. This study enhances knowledge of physical-biological coupling in upwelling ecosystems and enables improved forecasting of species distribution patterns for dynamic management.
DOI: 10.6084/m9.figshare.13140476.v2
title: Timeseries cross-correlation outputs

description: Time series cross-correlation analysis output files, corresponding to the following manuscript: <br>Processed data corresponding to the following manuscript:<br><b>Temporal and spatial lags between wind, coastal upwelling, and blue whale occurrence</b><b><br></b><b>Authors: </b>Dawn R. Barlow<sup>1</sup>*, Holger Klinck<sup>2,3</sup>, Dimitri Ponirakis<sup>2</sup>, Christina Garvey<sup>4</sup>, Leigh G. Torres<sup>1</sup><sup></sup><br><sup>1</sup>Geospatial Ecology of Marine Megafauna Lab, Marine Mammal Institute, and Department of Fisheries and Wildlife, Oregon State University, Newport, Oregon, USA<sup>2</sup>Center for Conservation Bioacoustics, Cornell University, Ithaca, New York, USA<sup>3</sup>Marine Mammal Institute, Department of Fisheries and Wildlife, Oregon State University, Newport, Oregon, USA<sup>4</sup>University of Maryland, College Park, Maryland, USA*dawn.barlow@oregonstate.edu<br><b>Abstract: </b>Understanding relationships between physical drivers and biological response is central to advancing ecological knowledge. Wind is the physical forcing mechanism in coastal upwelling systems, however lags between wind input and biological responses are seldom quantified for marine predators. Lags were examined between wind at an upwelling source, decreased temperatures along the upwelling plume’s trajectory, and blue whale occurrence in New Zealand’s South Taranaki Bight region (STB). Wind speed and sea surface temperature (SST) were extracted for austral spring-summer months between 2009-2019. A hydrophone recorded blue whale vocalizations October 2016-March 2017. Timeseries cross-correlation analyses were conducted between wind speed, SST at different locations along the upwelling plume, and blue whale downswept vocalizations (“D calls”). Results document increasing lag times (0-2 weeks) between wind speed and SST consistent with the spatial progression of upwelling, culminating with increased D call density at the distal end of the plume three weeks after increased wind speeds at the upwelling source. Lag between wind events and blue whale aggregations (n = 34 aggregations 2013-2019) was 2.09 ± 0.43 weeks. Variation in lag was significantly related to the amount of wind over the preceding 30 days, which likely influences stratification. This study enhances knowledge of physical-biological coupling in upwelling ecosystems and enables improved forecasting of species distribution patterns for dynamic management.
DOI: 10.6084/m9.figshare.13140476.v1
title: Timeseries cross-correlation outputs

description: Time series cross-correlation analysis output files, corresponding to the following manuscript: <br><b>Fashionably late: Temporal and spatial lags between wind and blue whales in a coastal upwelling system</b><b><br></b><b>Authors: </b>Dawn R. Barlow<sup>1</sup>*, Holger Klinck<sup>2,3</sup>, Dimitri Ponirakis<sup>2</sup>, Christina Garvey<sup>4</sup>, Leigh G. Torres<sup>1</sup><sup></sup><br><sup>1</sup>Geospatial Ecology of Marine Megafauna Lab, Marine Mammal Institute, and Department of Fisheries and Wildlife, Oregon State University, Newport, Oregon, USA<sup>2</sup>Center for Conservation Bioacoustics, Cornell University, Ithaca, New York, USA<sup>3</sup>Marine Mammal Institute, Department of Fisheries and Wildlife, Oregon State University, Newport, Oregon, USA<sup>4</sup>University of Maryland, College Park, Maryland, USA*dawn.barlow@oregonstate.edu<br><b>Abstract: </b>Understanding relationships between physical drivers and biological response is central to advancing ecological knowledge. Wind is the physical forcing mechanism in coastal upwelling systems, however lags between wind input and biological responses are seldom quantified for marine predators. Lags were examined between wind at an upwelling source, decreased temperatures along the upwelling plume’s trajectory, and blue whale occurrence in New Zealand’s South Taranaki Bight region (STB). Wind speed and sea surface temperature (SST) were extracted for austral spring-summer months between 2009-2019. A hydrophone recorded blue whale vocalizations October 2016-March 2017. Timeseries cross-correlation analyses were conducted between wind speed, SST at different locations along the upwelling plume, and blue whale D call vocalizations. Results document increasing lag times (0-2 weeks) between wind speed and SST consistent with the spatial progression of upwelling, culminating with increased D call density at the distal end of the plume three weeks after increased wind speeds at the upwelling source. Lag between wind events and blue whale aggregations (n=34 aggregations 2013-2019) was 2.09±0.43 weeks. Variation in lag was significantly related to the amount of wind over the preceding 30 days, which likely influences stratification. This study enhances knowledge of physical-biological coupling in upwelling ecosystems and enables improved forecasting of species distribution patterns for dynamic management.
DOI: 10.6084/m9.figshare.14167403
title: Discharge and nitrate concentration

description: metadata on nitrate load estimation in the Huai River basin
DOI: 10.6084/m9.figshare.14167403.v2
title: Discharge and nitrate concentration

description: metadata on nitrate load estimation in the Huai River basin
DOI: 10.6084/m9.figshare.14167403.v1
title: 流量浓度.xlsx

description: metadata on nitrate load estimation in the Huai River basin
DOI: 10.6084/m9.figshare.14167397
title: Scan sampled behaviour during playpen sessions

description: Scan sampled observations for mice in standard cages (control) or playpens (treatment). Mice were each observed a total of 25 times, spaced 2-5 minutes apart. Full behaviour names are included on the second spreadsheet.
DOI: 10.6084/m9.figshare.14167391
title: Playpen agonism focal sampling

description: Focal sampling of agonistic interactions in a temporary playpen environment for standard-housed lab mice. Number of mice was either 2 (C57 strain mouse absent) or 3 (C57 strain mouse present).
DOI: 10.6084/m9.figshare.14167394
title: Latency to enter playpens

description: Latency of mice to voluntarily enter playpens from a standard cage. Day 1 is baseline. Max latency was 300 seconds.
DOI: 10.6084/m9.figshare.14167394.v1
title: Latency to enter playpens

description: Latency of mice to voluntarily enter playpens from a standard cage. Day 1 is baseline. Max latency was 300 seconds.
DOI: 10.6084/m9.figshare.14167397.v1
title: Scan sampled behaviour during playpen sessions

description: Scan sampled observations for mice in standard cages (control) or playpens (treatment). Mice were each observed a total of 25 times, spaced 2-5 minutes apart. Full behaviour names are included on the second spreadsheet.
DOI: 10.6073/pasta/a577eb0f9c7e5721f40b41612b62ab8f
title: Jornada Basin LTER: Wireless meteorological station at NPP C-GRAV site: 5-minute summary wind and air temperature data: 2013 - ongoing

description: 5-minute summary data at NPP C-GRAV met station. Average air temperature, wind speed and wind direction are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP C-GRAV site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature at approximate 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.