Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
348
datasets available to search
ShareScore release 0.9.0
Dataset results
348 results for “Core data”
Data from: The role of environment and core-margin effects on range-wide phenotypic variation of a montane grasshopper
Open the record for dataset details and reuse information.
Data from: Brokering the core and the periphery: creative success and collaboration networks in the film industry
Open the record for dataset details and reuse information.
Data from: A 454 survey reveals the community composition and core microbiome of the common bed bug (Cimex lectularius) across an urban landscape
Open the record for dataset details and reuse information.
Data from: Deep-sea benthic ostracodes from multiple core and epibenthic sledge samples in Icelandic waters
Open the record for dataset details and reuse information.
Sedimentary and geochemical data from JRD-S core at Zhuoshui River Delta, Taiwan
Open the record for dataset details and reuse information.
Data from: Genome-wide assessment of population structure and genetic diversity and development of a core germplasm set for sweet potato based on specific length amplified fragment (SLAF) sequencing
Open the record for dataset details and reuse information.
Data from: Detection of tephra layers in Antarctic sediment cores with hyperspectral imaging
Open the record for dataset details and reuse information.
Mid to late-Holocene palynomorph, charcoal and sediment data from three middle and high-altitude sediment cores from the Kashmir Valley
Open the record for dataset details and reuse information.
BES LTER Base Cation Data for Core Monitoring Streams across Land Use Gradient
<p>The Baltimore Ecosystem Study LTER has established a network of long-term biogeochemical hydrologic study sites. Sites range from suburban to highly urban. More site information can be found on the BESLTER page at www.beslter.org </p> <p>Descriptions of land use and further site descriptions can be found in Kaushal et al 2017. Tabs represent a different sites, listing the base cation concentrations, as well as a tab summarizing site averages as used in Kaushal et al. 2017.</p>
Core SAFE project small mammal trapping data
<b>Description: </b><p>This is the combined dataset for the SAFE project's core small mammal trapping programme, which was run from 2011-2014 by O.R. Wearn, from 2015-2017 by P. M. Chapman, and from 2018-2019 by S. Heon. In total, trapping grids have been run at 30 sites across the SAFE landscape and control areas, covering blocks D, E, F, OG1, OG2, OG3 and OP2. However, since 2014 trapping has been limited to 12 standard permanent grids which are resampled annually: two in D (the 100ha fragment site), six in E (two each in the 1, 10 and 100ha sites), two in OG2 at the Maliau Basin Conservation area and two in OP2 at the Selangan Batu Oil Palm estate. In 2018, 2 new mammal grids were added : Dmatrix-1 and Ematrix-1 grid. The following grids were dropped E1-1, E10-1, E100-1 and D100-1, while D1-2 and D10-2 were sampled. In 2019, OG2-N, trap lines 1-8 were not accessible due to a massive landslide. In replacement, lines 47-56 were added to the trap grid for OG2-N. trapping grids Dmatrix-2 and Ematrix-2 were also added. All the new grids are reflected on the locations sheet. One standard annual sampling session comprises 96 traps run for seven nights, and the first sheet in the dataset ("Deployment") records this as 672 rows detailing the basic outcome of each trap night in the sampling session. There are several grids which form exceptions to this trapping pattern; details of these are recorded in the metadata. The subsequent two sheets (Corrected_Trapping_Data and Raw_Trapping_Data) form a more detailed record of captured animals. These sheets have the non-capture rows removed, along with most of the basic trap location and state data; however they can easily be linked back to the relevant rows in "Deployment" by the date and the unique trap identifier. At first capture, all possible details of captured animals are recorded, including age, sex, biometric measurements, crude estimates of parasite load, and the ID of any associated samples. All animals captured in good health were fitted with a Passive Integrated Transponder (PIT) Tag so the unique 10-digit alphanumeric number associated with each PIT tag is also recorded. Upon recapture, the animals are merely weighed and the PIT tag number and trap location recorded; this is partly to save time and partly to avoid unneccessary repeat anaesthesia. In 2018, Prevost's squirrel with the species code PVSQ was added into the species list. <br>The entire dataset from 2011-2017 was extensively error-checked by PMC in 2018, then from 2018-2019 by SH with many errors identified, recorded, and where possible, rectified. These errors are most frequently duplications or typos in the PIT tag string. Where these errors are unresolvable, the true unique ID of the individual is no longer certain, and its independence from other individuals cannot be guaranteed. These records will require omitting from most analyses. The detailed dataset with capture data is therefore presented in both its raw and corrected forms. ("Raw_Trapping_Data" and "Corrected_Trapping_Data", respectively). In the corrected datasheet, all the resolvable errors have been corrected, with a brief note made of what was done and why. Notes have also been added to irresolvable errors briefly explaining the problem, and recommending omission from analyses where appropriate. We strongly recommend that all users rely on the corrected version; however we also include the raw data for completeness. In 2018, an additional sheet - general site information details was added</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/140"><b>The impacts of tropical forest fragmentation on dispersal behaviour of mammal communities</b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3955050">here</a></p><p><b>Files: </b>This consists of 1 file: SAFE_Core_Small_Mammal_Data_V3_2019_ROB_SUI.xlsx</p><p><b>SAFE_Core_Small_Mammal_Data_V3_2019_ROB_SUI.xlsx</b></p><p>This file contains dataset metadata and 4 data tables:</p><ol><li><p><b>Basic trap outcome data</b> (described in worksheet Deployment)</p><p>Description: This is the basic trapping data covering the outcome of every trap night since the start of the study in 2011. It comprises merely the location and date information for the trap, the person who was responsible for baiting it, the state of the trap and bait on checking, any invertebrates captured, the number of small mammal captures (generally 0 or 1, but occasionally 2) and any notes pertaining to the trap itself.</p><p>Number of fields: 15</p><p>Number of data rows: 71123</p><p>Fields: </p><ul><li><b>Grid-Session-Occasion</b>: An identifier for the individual trapping day ("occasion") within a sampling year ("session"). This nomenclature originates from applying Spatially Explicit Capture-Recapture models to this data, however experience suggests this is the most concise, intuitive way of referring to a particular day of trapping (rather than using the actual date). This is applied to all grids which were trapped in the standard pattern of 96 traps run for seven consecutive days. There are five exceptions: OG2-E in 2011, D100-2 in 2011, D100-1 in 2012, F100-1 in 2012, and F100-2 in 2012. These were all trapped in a non-standard pattern (either total trapping effort ≠ 96 traps and 7 days, or there were gaps etween days such that the total trapped duration > 7 days). These exceptions are given NA (Field type: id)</li><li><b>Date</b>: The calendar date of trapping (Field type: date)</li><li><b>Block</b>: The SAFE sampling block (Field type: categorical)</li><li><b>Fragment</b>: The fragment (SAFE landscape; 1, 10, or 100ha) or sub-block (control sites; e.g. OP2, OG1, etc) of the sampling session. (Field type: id)</li><li><b>Grid</b>: The grid of the sampling session. There are two grids (1 and 2, numered outwards from the centre of the lock) in each fragment in the SAFE design, and three in each su-block in the control sites (North, East and West). (Field type: id)</li><li><b>Point</b>: The camera trap/small mammal sampling point where the trap was located. (Field type: id)</li><li><b>Trap</b>: The trap identifier (two traps, A and B, are located within a 5m radius of each sampling point) (Field type: id)</li><li><b>Unique_Point_ID</b>: Unique identifier for the sampling point (corresponds to the Locations sheet, and the locations in the Gazeteer) (Field type: location)</li><li><b>Unique_Trap_ID</b>: Unique identifier for the individual trap. (Field type: id)</li><li><b>State</b>: The state of the trap when checked. (Field type: categorical)</li><li><b>Bait</b>: The state of the bait when checked. (Field type: categorical)</li><li><b>Invertebrates</b>: Comments on any invertebrates found; in particular the presence of ants is frequently recorded, as these can be a severe danger to small mammals. (Field type: comments)</li><li><b>Capture_N</b>: Number of small mammals caught. This is almost invarialy zero or one, however very occasionally two are caught together. Models such as Spatially Explicit Capture Recapture treat small mammal traps as "single-catch" traps, and the model is violated y these occasions - so they are worth flagging up. (Field type: numeric)</li><li><b>Who_baited</b>: Person who baited the trap (Field type: comments)</li><li><b>Other_Notes</b>: Original supplementary field notes on the trap outcome or the animal captured. On the "Deployment" sheet this column has Been trimmed to only include notes covering the placement and condition of the traps - with notes pertaining to captured animals removed. (Field type: comments)</li></ul></li><li><p><b>Corrected trapping data</b> (described in worksheet Corrected_Trapping_Data)</p><p>Description: This is the modified, corrected version of the detailed trapping data covering all the small mammal captures from 2011 (i.e. blank rows are removed). It is directly based on the raw trapping data, however it has been fully verified, with all rectifiable errors corrected. Extra columns are included to: 1.) display any corrections to species ID and PIT tag ID of an individual record, 2.) explain the reason for corrections applied, or any unresolvable errors, and 3.) recommend a record for omission from analyses, where appropriate.</p><p>Number of fields: 36</p><p>Number of data rows: 8101</p><p>Fields: </p><ul><li><b>Grid-Session-Occasion</b>: An identifier for the individual trapping day ("occasion") within a sampling year ("session"). This nomenclature originates from applying Spatially Explicit Capture-Recapture models to this data, however experience suggests this is the most concise, intuitive way of referring to a particular day of trapping (rather than using the actual date). This is applied to all grids which were trapped in the standard pattern of 96 traps run for seven consecutive days. There are five exceptions: OG2-E in 2011, D100-2 in 2011, D100-1 in 2012, F100-1 in 2012, and F100-2 in 2012. These were all trapped in a non-standard pattern (either total trapping effort ≠ 96 traps and 7 days, or there were gaps between days such that the total trapped duration > 7 days). These exceptions are given NA (Field type: id)</li><li><b>Date</b>: The calendar date of trapping (Field type: date)</li><li><b>Unique_Point_ID</b>: Unique identifier for the sampling point (corresponds to the Locations sheet, and the locations in the Gazeteer) (Field type: location)</li><li><b>Unique_Trap_ID</b>: Unique identifier for the individual trap. (Field type: id)</li><li><b>Species</b>: Raw species ID for the captured animal. All "target" small mammals receive an identifying code for brevity (see the Taxa sheet) while occasional caputures of "non-target" taxa (larger mammals, other vertebrates) are referred to in full. Fully unknown small mammal species are referred to as "Unknown". (Field type: taxa)</li><li><b>Species_Validated</b>: Corrected, verified species ID for the captured animal. This should be used in preference to "Species" as any misidentifications have been amended. Codes follow those in the "Raw Taxon" column (Field type: taxa)</li><li><b>Species_Uncertainty</b>: Indicates uncertainty around the species identification (after correction). Species IDs are not alwaysCERtain, especially in the case of aberrant individuals, cryptic species or complexes such as Rattus, or heavily scavenged dead indivuduals. (Field type: categorical)</li><li><b>New/Recapture</b>: Indicates whether the individual is a new record or a recapture. NB: Biometric data (apart from weight) is not collected for recaptures for reasons of time and ethics (unnecessary anaesthesia). (Field type: categorical)</li><li><b>PIT_Tag/ID</b>: Raw individual ID for the captured animal. This is usually a 10-digit numeric or alphanumeric string, the number of the fitted Passive Integrated Transponder (PIT) tag. All zeros in PIT strings are replaced with capital Os due to persistent problems with Excel irreversibly modifying particular string formats (these errors are included in this raw data). Various other "generic" individual IDs have been applied to occasional animals which were untagged but somehow deemed to be otherwise identifiable. The format and use of these varies between fieldworkers and has not been standardised here in this raw verson. (Field type: id)</li><li><b>PIT_Tag/ID_Validated</b>: Corrected, validated individual ID for the captured small mammal. This should be used in preference to "PIT_Tag/ID" as resolvable errors have been amended. In some occasional cases this ID does not correspond to the (corrected) PIT tag string. In these cases a standardised generic ID was applied, generally under two possible conditions: 1.) The individual was released alive without tagging but there is effectively no chance of recapture (such as an animal on the last day of trapping in an isolated block which was not trapped subsequently). 2.) The animal was a new, untagged individual found dead in the trap. Case 1: individuals recieve an identifier comprised of the species code and a unique three-digit number e.g. "WH001". Case 2: Individuals recieve a unique two-digit number preceded by "NewDead". (Field type: id)</li><li><b>Age</b>: Age of the individual captured. Uncertain ages are given with question marks. Completely unknown or unrecorded age are given as NA. (Field type: categorical trait)</li><li><b>Sex</b>: Sex of the individual captured. Uncertain sexes are given with question marks. Completely unknown or unrecorded sexes are given as NA. (Field type: categorical trait)</li><li><b>Sexing_Notes</b>: Notes on criteria used for sexing. (Field type: comments)</li><li><b>HF</b>: (Left) Hind foot measurement (Field type: numeric trait)</li><li><b>E</b>: (Left) Ear length measurement (only rats) (Field type: numeric trait)</li><li><b>AGD</b>: Ano-genital distance measurement (only rats) (Field type: numeric trait)</li><li><b>HB</b>: Head-body length measurement (only treeshrews, squirrels and some rat species where ID is uncertain) (Field type: numeric trait)</li><li><b>T</b>: Tail length measurement (only treeshrews, squirrels and some rat species where ID is uncertain) (Field type: numeric trait)</li><li><b>T_%_of_HB</b>: Tail length as a percentage of body head-body length (Field type: numeric trait)</li><li><b>MZ</b>: Muzzle length measurement (only treeshrews) (Field type: numeric trait)</li><li><b>Bag_W</b>: Mass of the polythene weighing bag (Field type: numeric)</li><li><b>Gross_W</b>: Mass of the polythene weighing bag including animal (Field type: numeric)</li><li><b>Net_W</b>: Mass of the animal (Field type: numeric)</li><li><b>Parasite_Count</b>: Approximate ectoparasite load: rough visual count of the number of fur mites and other ectoparasites shed within the anaesthesia pot during anaesthesia (Field type: numeric trait)</li><li><b>Body_Fat</b>: Body fat score: a nine-level categorical score. Only applied from 2017 onwards. (Field type: categorical trait)</li><li><b>Injuries</b>: Description of any injuries or visible signs of diease to the captured small mammal. (Field type: comments)</li><li><b>Dead</b>: Was the individual found dead, or euthanised in the course of processing? (Field type: categorical trait)</li><li><b>Tissue_Sample_ID</b>: Identifier for any tissue samples taken (rats only, from the right ear) (Field type: id)</li><li><b>Parasite_Sample_ID</b>: Identifier for any parasite samples taken (Field type: id)</li><li><b>Fur_sample_ID</b>: Identifier for any fur samples taken (Field type: id)</li><li><b>Faecal_Sample_1_ID</b>: Identifier for any faecal samples taken (for first investigator) (Field type: id)</li><li><b>Faecal_Sample_2_ID</b>: Identifier for any faecal samples taken (for second investigator) (Field type: id)</li><li><b>Processor</b>: Person who processed the animal (Field type: comments)</li><li><b>Omit</b>: Identifies individuals which should be omitted from all analyses ("Y") or some analyses ("SA") due to data errors (Field type: categorical)</li><li><b>Correction_Notes</b>: Comments on any corrections made or reasoning for suggesting omissions in "Omit". Omissions are usually due to the individual ID or species ID of a capture being uncertain. Several common omission reasons are recorded with standard prhases in capitals for clarity: these include escapes, animals released untagged for various reasons (including non-target captures), and dead individuals where species identification was impossible or where it was uncertain if the individual was new or a recapture. More complex cases are discussed individually. (Field type: comments)</li><li><b>Other_Notes</b>: Original supplementary field notes on the trap outcome or the animal captured. This column includes supporting notes for ID, descriptions of the circumstances of a death, admissions of missing data, etc etc. These have not been error-checked or modified. (Field type: comments)</li></ul></li><li><p><b>Raw trapping data</b> (described in worksheet Raw_Trapping_Data)</p><p>Description: This is the unmodified, raw version of the detailed trapping data, covering all the small mammal sampling from 2011 (i.e. blank rows are removed). It is included for information only and we do not recommend that it is used.</p><p>Number of fields: 32</p><p>Number of data rows: 8101</p><p>Fields: </p><ul><li><b>Grid-Session-Occasion</b>: An identifier for the individual trapping day ("occasion") within a sampling year ("session"). This nomenclature originates from applying Spatially Explicit Capture-Recapture models to this data, however experience suggests this is the most concise, intuitive way of referring to a particular day of trapping (rather than using the actual date). This is applied to all grids which were trapped in the standard pattern of 96 traps run for seven consecutive days. There are five exceptions: OG2-E in 2011, D100-2 in 2011, D100-1 in 2012, F100-1 in 2012, and F100-2 in 2012. These were all trapped in a non-standard pattern (either total trapping effort ≠ 96 traps and 7 days, or there were gaps between days such that the total trapped duration > 7 days). These exceptions are given NA (Field type: id)</li><li><b>Date</b>: The calendar date of trapping (Field type: date)</li><li><b>Unique_Point_ID</b>: Unique identifier for the sampling point (corresponds to the Locations sheet, and the locations in the Gazeteer) (Field type: location)</li><li><b>Unique Trap ID</b>: Unique identifier for the individual trap. (Field type: id)</li><li><b>Species</b>: Raw species ID for the captured animal. All "target" small mammals receive an identifying code for brevity (see the Taxa sheet) while occasional captures of "non-target" taxa (larger mammals, other vertebrates) are referred to in full. Fully unknown small mammal species are referred to as "Unknown". (Field type: taxa)</li><li><b>Species Uncertainty</b>: Indicates uncertainty around the species identification. Species IDs are not always certain, especially in the case of aberrant individuals, cryptic species or complexes such as Rattus, or heavily scavenged dead indivuduals. (Field type: categorical)</li><li><b>New/Recapture</b>: Indicates whether the individual is a new record or a recapture. NB: Biometric data (apart from weight) is not collected for recaptures for reasons of time and ethics (unnecessary anaesthesia). (Field type: categorical)</li><li><b>PIT_Tag/ID</b>: Raw individual ID for the captured animal. This is usually a 10-digit numeric or alphanumeric string, the number of the fitted Passive Integrated Transponder (PIT) tag. All zeros in PIT strings are replaced with capital Os due to persistent problems with Excel irreversibly modifying particular string formats (these errors are included in this raw data). Various other "generic" individual IDs have been applied to occasional animals which were untagged but somehow deemed to be otherwise identifiable. The format and use of these varies between fieldworkers and has not been standardised here in this raw dataset. (Field type: id)</li><li><b>Age</b>: Age of the individual captured. Uncertain ages are given with question marks. Completely unknown or unrecorded age are given as NA. (Field type: categorical trait)</li><li><b>Sex</b>: Sex of the individual captured. Uncertain sexes are given with question marks. Completely unknown or unrecorded sexes are given as NA. (Field type: categorical trait)</li><li><b>Sexing Notes</b>: Notes on criteria used for sexing. (Field type: comments)</li><li><b>HF</b>: (Left) Hind foot measurement (Field type: numeric trait)</li><li><b>E</b>: (Left) Ear length measurement (only rats) (Field type: numeric trait)</li><li><b>AGD</b>: Ano-genital distance measurement (only rats) (Field type: numeric trait)</li><li><b>HB</b>: Head-body length measurement (only treeshrews, squirrels and some rat species where ID is uncertain) (Field type: numeric trait)</li><li><b>T</b>: Tail length measurement (only treeshrews, squirrels and some rat species where ID is uncertain) (Field type: numeric trait)</li><li><b>T % of HB</b>: Tail length as a percentage of body head-body length (Field type: numeric trait)</li><li><b>MZ</b>: Muzzle length measurement (only treeshrews) (Field type: numeric trait)</li><li><b>Bag W</b>: Mass of the polythene weighing bag (Field type: numeric)</li><li><b>Gross W</b>: Mass of the polythene weighing bag including animal (Field type: numeric)</li><li><b>Net W</b>: Mass of the animal (Field type: numeric)</li><li><b>Parasite Count</b>: Approximate ectoparasite load: rough visual count of the number of fur mites and other ectoparasites shed within the anaesthesia pot during anaesthesia (Field type: numeric trait)</li><li><b>Body Fat</b>: Body fat score: a nine-level categorical score. Only applied from 2017 onwards. (Field type: categorical trait)</li><li><b>Injuries</b>: Description of any injuries or visible signs of diease to the captured small mammal. (Field type: comments)</li><li><b>Dead</b>: Was the individual found dead, or euthanised in the course of processing? (Field type: categorical trait)</li><li><b>Tissue Sample ID</b>: Identifier for any tissue samples taken (rats only, from the right ear) (Field type: id)</li><li><b>Parasite Sample ID</b>: Identifier for any parasite samples taken (Field type: id)</li><li><b>Fur sample ID</b>: Identifier for any fur samples taken (Field type: id)</li><li><b>Faecal Sample 1 ID</b>: Identifier for any faecal samples taken (for first investigator) (Field type: id)</li><li><b>Faecal Sample 2 ID</b>: Identifier for any faecal samples taken (for second investigator) (Field type: id)</li><li><b>Processor</b>: Person who processed the animal (Field type: comments)</li><li><b>Other Notes</b>: Original supplementary field notes on the trap outcome or the animal captured. This column includes supporting notes for ID, descriptions of the circumstances of a death, admissions of missing data, etc etc. These have not been error-checked or modified. (Field type: comments)</li></ul></li><li><p><b>Site deployment information</b> (described in worksheet Site_Deployment_Info)</p><p>Description: This sheet contains information about the weather condition, animal occurrences or human disturbances which may influence the live mammal trapping outcome during the course of the live trapping. It contains the grid information, trapping day, data, observers and the weather condition and if any general observations made about the grid on the trapping days. </p><p>Number of fields: 6</p><p>Number of data rows: 154</p><p>Fields: </p><ul><li><b>Location</b>: Grid-Session-Occasion (Field type: id)</li><li><b>Day</b>: Trapping day number (Field type: id)</li><li><b>Date</b>: Date of trap collection (Field type: date)</li><li><b>Observer</b>: Observer (Field type: comments)</li><li><b>Weather condition</b>: Weather notes (Field type: comments)</li><li><b>General Notes</b>: Other notes (Field type: comments)</li></ul></li></ol><p><b>Date range: </b>2011-05-12 to 2019-11-22</p><p><b>Latitudinal extent: </b>4.6429 to 4.7539</p><p><b>Longitudinal extent: </b>116.9471 to 117.5938</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> -  -  Chordata <br> -  -  -  Aves <br> -  -  -  -  Cuculiformes <br> -  -  -  -  -  Cuculidae <br> -  -  -  -  -  -  <i>Centropus</i> <br> -  -  -  -  Passeriformes <br> -  -  -  -  -  Timaliidae <br> -  -  -  -  -  -  <i>Macronus</i> <br> -  -  -  -  -  -  -  <i>Macronus bornensis</i> <br> -  -  -  -  -  Pellorneidae <br> -  -  -  -  -  -  <i>Malacocincla</i> <br> -  -  -  -  -  -  -  <i>Malacocincla malaccensis</i> <br> -  -  -  -  -  Pittidae <br> -  -  -  -  -  -  <i>Pitta</i> <br> -  -  -  -  -  -  -  <i>Pitta arquata</i> <br> -  -  -  Mammalia <br> -  -  -  -  Rodentia <br> -  -  -  -  -  Sciuridae <br> -  -  -  -  -  -  <i>Callosciurus</i> <br> -  -  -  -  -  -  -  <i>Callosciurus adamsi</i> <br> -  -  -  -  -  -  -  <i>Callosciurus notatus</i> <br> -  -  -  -  -  -  -  <i>Callosciurus prevostii</i> <br> -  -  -  -  -  -  <i>Lariscus</i> <br> -  -  -  -  -  -  -  <i>Lariscus hosei</i> <br> -  -  -  -  -  -  <i>Sundasciurus</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus brookei</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus hippurus</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus lowii</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus tenuis</i> <br> -  -  -  -  -  Muridae <br> -  -  -  -  -  -  <i>Maxomys</i> <br> -  -  -  -  -  -  -  <i>Maxomys rajah</i> <br> -  -  -  -  -  -  -  <i>Maxomys ochraceiventer</i> <br> -  -  -  -  -  -  -  <i>Maxomys surifer</i> <br> -  -  -  -  -  -  -  <i>Maxomys baeodon</i> <br> -  -  -  -  -  -  <i>Rattus</i> <br> -  -  -  -  -  -  -  <i>Rattus tiomanicus</i> <br> -  -  -  -  -  -  -  <i>Rattus exulans</i> <br> -  -  -  -  -  -  -  <i>Rattus rattus</i> <br> -  -  -  -  -  -  <i>Sundamys</i> <br> -  -  -  -  -  -  -  <i>Sundamys muelleri</i> <br> -  -  -  -  -  -  <i>Niviventer</i> <br> -  -  -  -  -  -  -  <i>Niviventer cremoriventer</i> <br> -  -  -  -  -  -  <i>Chrotomys</i> <br> -  -  -  -  -  -  -  <i>Chrotomys whiteheadi</i> (as homotypic_synonym: <i>Maxomys whiteheadi</i>)<br> -  -  -  -  -  -  <i>Leopoldamys</i> <br> -  -  -  -  -  -  -  <i>Leopoldamys sabanus</i> <br> -  -  -  -  Carnivora <br> -  -  -  -  -  Viverridae <br> -  -  -  -  -  -  <i>Viverra</i> <br> -  -  -  -  -  -  -  <i>Viverra tangalunga</i> <br> -  -  -  -  -  Mustelidae <br> -  -  -  -  -  -  <i>Martes</i> <br> -  -  -  -  -  -  -  <i>Martes flavigula</i> <br> -  -  -  -  Erinaceomorpha <br> -  -  -  -  -  Erinaceidae <br> -  -  -  -  -  -  <i>Echinosorex</i> <br> -  -  -  -  -  -  -  <i>Echinosorex gymnura</i> <br> -  -  -  -  Scandentia <br> -  -  -  -  -  Tupaiidae <br> -  -  -  -  -  -  <i>Tupaia</i> <br> -  -  -  -  -  -  -  <i>Tupaia longipes</i> <br> -  -  -  -  -  -  -  <i>Tupaia minor</i> <br> -  -  -  -  -  -  -  <i>Tupaia tana</i> <br> -  -  -  -  -  -  -  <i>Tupaia gracilis</i> <br> -  -  -  -  -  -  -  <i>Tupaia dorsalis</i> <br> -  -  -  Reptilia <br> -  -  -  -  Squamata <br> -  -  -  -  -  Gekkonidae <br> -  -  -  -  -  Scincidae <br> -  -  -  -  -  Varanidae <br> -  -  -  -  -  -  <i>Varanus</i> <br></div><p></p>
Data from: eDNA metabarcoding reveals a core and secondary diets of the greater horseshoe bat with strong spatio-temporal plasticity
<p><strong>ABSTRACT</strong></p> <p>Dietary plasticity is an important issue for conservation biology as it may be essential for species to cope with environmental changes. However, it still remains scarcely addressed in the literature, potentially because diet studies have long been constrained by methodological limits. The advent of molecular approaches now makes it possible to get a precise picture of diet and its plasticity, even for endangered and elusive species. Here we focused on the greater horseshoe bat (<em>Rhinolophus ferrumequinum</em>) in Western France, where this insectivorous species has been classified as ‘Vulnerable’ on the Regional Red List (2016). We applied an eDNA metabarcoding approach on 1986 fecal samples collected in six maternity colonies at three sampling dates. We described its diet and investigated whether the landscape surrounding colonies and the different phases of the maternity cycle influenced the diversity and the composition of this diet. We showed that <em>R. ferrumequinum</em> feed on a highly more diverse spectrum of prey than expected from previous studies, therefore highlighting how eDNA metabarcoding can help improving diet knowledge of a flying elusive endangered species. Our approach also revealed that <em>R. ferrumequinum</em> diet is composed of two distinct features: the core diet consisting in a few preferred taxa shared by all the colonies (25% of the occurrences) and the secondary diet consisting in numerous rare prey that were highly different between colonies and sampling dates (75% of the occurrences). Energetic needs and constraints associated with the greater horseshoe bat life-cycle, as well as insect phenology and landscape features, strongly influenced the diversity and composition of both the whole and core diets. Further research should now explore the relationships between <em>R. ferrumequinum</em> dietary plasticity and fitness, to better assess the impact of core prey decline on <em>R. ferrumequinum</em> populations viability.</p> <p> </p> <p><strong>FILE DESCRIPTION</strong></p> <p><strong>Information concerning the samples and the positive and negative controls multiplexed in the MiSeq Runs 5 to 9</strong></p> <p>This XLSX file contains the sample IDs, the sample types, the PCR IDs, the PCR replicate numbers, the locality names, the predator species and the fastq file names for each PCR products multiplexed in the five different Illumina MiSeq runs.</p> <p>File name: Sample_informations.xlsx</p> <p> </p> <p><strong>MiSeq raw sequences of the COI minibarcode from the faecal pellets of bats (Run5)</strong></p> <p>This ZIP file contains the Run5 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each faecal pellet in triplicate using the MiSeq platform. The 1271 multiplexed PCR products were indexed using both forward and reverse indices. The list of the 475 multiplexed samples and the 8 positive and 94 negative controls are provided in the following XLSX file titled: Sample_Information.xlsx.</p> <p>Note: the 186 PCR3 replicates from the localities BEA and SGE are available in the ZIP file MiSeq_Reads_COI_Bat_faecal_pellets_Run9.zip</p> <p>File name: MiSeq_Reads_COI_Bat_faecal_pellets_Run5.zip</p> <p> </p> <p><strong>MiSeq raw sequences of the COI minibarcode from the faecal pellets of bats (Run6)</strong></p> <p>This ZIP file contains the Run6 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each faecal pellet in triplicate using the MiSeq platform. The 1440 multiplexed PCR products were indexed using both forward and reverse indices. The list of the 466 multiplexed samples and the 8 positive and 130 negative controls are provided in the following XLSX file titled: Sample_Information.xlsx.</p> <p>File name: MiSeq_Reads_COI_Bat_faecal_pellets_Run6.zip</p> <p> </p> <p><strong>MiSeq raw sequences of the COI minibarcode from the faecal pellets of bats (Run7)</strong></p> <p>This ZIP file contains the Run7 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each faecal pellet in triplicate using the MiSeq platform. The 1464 multiplexed PCR products were indexed using both forward and reverse indices. The list of the 475 multiplexed samples and the 8 positive and 103 negative controls are provided in the following XLSX file titled: Sample_Information.xlsx.</p> <p>File name: MiSeq_Reads_COI_Bat_faecal_pellets_Run7.zip</p> <p> </p> <p><strong>MiSeq raw sequences of the COI minibarcode from the faecal pellets of bats (Run8)</strong></p> <p>This ZIP file contains the Run8 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each faecal pellet in triplicate using the MiSeq platform. The 1464 multiplexed PCR products were indexed using both forward and reverse indices. The list of the 475 multiplexed samples and the 8 positive and 103 negative controls are provided in the following XLSX file titled: Sample_Information.xlsx.</p> <p>File name: MiSeq_Reads_COI_Bat_faecal_pellets_Run8.zip</p> <p> </p> <p><strong>MiSeq raw sequences of the COI minibarcode from the faecal pellets of bats (Run9)</strong></p> <p>This ZIP file contains the Run9 FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each faecal pellet in triplicate using the MiSeq platform. The 499 multiplexed PCR products were indexed using both forward and reverse indices. The list of the 281 multiplexed samples (including 29 samples from another project) and the 11 positive and 172 negative controls are provided in the following XLSX file titled: Sample_Information.xlsx.</p> <p>Note: the 372 PCR1 & PCR2 replicates from the localities BEA and SGE are available in the ZIP file MiSeq_Reads_COI_Bat_faecal_pellets_Run5.zip</p> <p>File name: MiSeq_Reads_COI_Bat_faecal_pellets_Run9.zip</p> <p> </p> <p><strong>Raw abundance tables of the COI minibarcode from the faecal pellets of bats before data filtering (Run5 to 9)</strong></p> <p>This ZIP file contains five TXT files showing the number of reads for each of the 17,998 distinct variants (OTUs) and each of the 6138 PCR products of the samples (<em>n</em>=2015) and controls sequenced in the MiSeq Runs 5 to 9 before the data filtering.</p> <p>File name: Raw_COI_Bat_Faecal_Pellets_abundance_Runs5to9_before_filtering.zip</p> <p> </p> <p><strong>Abundance table of the COI minibarcode from the faecal pellets of bats after data filtering (Run5 to 9)</strong></p> <p>This XLSX file contains the number of reads for each of the 7206 distinct variants (OTUs) and each of sample (<em>n</em>=2014) after the data filtering using (1) the thresholds based on the negative and positive controls (Tcc & Tfa) and (2) the validation using the three technical replicates.</p> <p>File name: COI_Bat_Faecal_Pellets_abundance_Runs5to9_after_filtering.xlsx</p> <p> </p> <p><strong>Final abundance table of the COI minibarcode for the prey of <em>Rhinolophus ferrumequinum</em> only (Run5 to 9)</strong></p> <p>This XLSX file contains the number of reads for each <em>Rhinolophus ferrumequinum</em> samples (<em>n</em>=1034) and each of the 679 validated prey taxa (OTUs) after taxonomic affiliations check and redundancy removals.</p> <p>File name: Final_COI_Rhino_Prey_abundance_Run5to9.xlsx</p> <p> </p> <p><strong>Landscape data table used to build the PCA</strong></p> <p>File name: Landscape_variables.xlsx</p>
Data from: Preparation of core–shell structured CaCO 3 microspheres as rapid and recyclable adsorbent for anionic dyes
Core–shell structured CaCO3 microspheres (MSs) were prepared by a facile, one-pot method at room temperature. The adsorbent dosage and adsorption time of the obtained CaCO3 MSs were investigated. The results suggest that these CaCO3 MSs can rapidly and efficiently remove 99–100% of anionic dyes within the first 2 min. The obtained CaCO3 MSs have a high Brunauer–Emmett–Teller surface area (211.77 m2 g−1). In addition, the maximum adsorption capacity of the obtained CaCO3 MSs towards Congo red was 99.6 mg g−1. We also found that the core–shell structured CaCO3 MSs have a high recycling capability for removing dyes from water. Our results demonstrate that the prepared core–shell structured CaCO3 MSs can be used as an ideal, rapid, efficient and recyclable adsorbent to remove dyes from aqueous solution.
Data from: Breeding system evolution influenced the geographic expansion and diversification of the core Corvoidea (Aves: Passeriformes)
Birds vary greatly in their life-history strategies, including their breeding systems, which range from brood parasitism to a system with multiple non-breeding helpers at the nest. By far the most common arrangement, however, is where both parents participate in raising the young. The traits associated with parental care have been suggested to affect dispersal propensity and lineage diversification, but to date tests of this potential relationship at broad temporal and spatial scales have been limited. Here, using data from a globally distributed group of corvoid birds in concordance with state-dependent speciation and extinction models, we suggest that pair breeding is associated with elevated speciation rates. Estimates of transition between breeding systems imply that cooperative lineages frequently evolve biparental care, whereas pair breeders rarely become cooperative. We further highlight that these groups have differences in their spatial distributions, with pair breeders over-represented on islands, and cooperative breeders mainly found on continents. Finally, we find that speciation rates appear to be significantly higher on islands compared to continents. These results imply that the transition from cooperative breeding to pair breeding was likely a significant contributing factor facilitating dispersal across tropical archipelagos, and subsequent world-wide phylogenetic expansion among the core Corvoidea.
Data from: The core planar cell polarity gene, Vangl2, directs adult corneal epithelial cell alignment and migration
This study shows that the core planar cell polarity (PCP) genes direct the aligned cell migration in the adult corneal epithelium, a stratified squamous epithelium on the outer surface of the vertebrate eye. Expression of multiple core PCP genes was demonstrated in the adult corneal epithelium. PCP components were manipulated genetically and pharmacologically in human and mouse corneal epithelial cells in vivo and in vitro. Knockdown of VANGL2 reduced the directional component of migration of human corneal epithelial (HCE) cells without affecting speed. It was shown that signalling through PCP mediators, dishevelled, dishevelled-associated activator of morphogenesis and Rho-associated protein kinase directs the alignment of HCE cells by affecting cytoskeletal reorganization. Cells in which VANGL2 was disrupted tended to misalign on grooved surfaces and migrate across, rather than parallel to the grooves. Adult corneal epithelial cells in which Vangl2 had been conditionally deleted showed a reduced rate of wound-healing migration. Conditional deletion of Vangl2 in the mouse corneal epithelium ablated the normal highly stereotyped patterns of centripetal cell migration in vivo from the periphery (limbus) to the centre of the cornea. Corneal opacity owing to chronic wounding is a major cause of degenerative blindness across the world, and this study shows that Vangl2 activity is required for directional corneal epithelial migration.
Data from: Burying beetles regulate the microbiome of carcasses and use it to transmit a core microbiota to their offspring
Necrophagous beetles utilize carrion, a highly nutritious resource that is susceptible to intense microbial competition, by treating it with antimicrobial anal and oral secretions. However, how this regulates the carcass microbiota remains unclear. Here, we show that carcasses prepared by the burying beetle Nicrophorus vespilloides undergo significant changes in their microbial communities subsequent to their burial and 'preparation'. Prepared carcasses hosted a microbial community that was more similar to that of beetles' anal and oral secretions than to the native carcass community or the surrounding soil, indicating that the beetles regulated the carcass microbiota. A core microbial community (Xanthomonadaceae, Enterococcaceae, Enterobacteriaceae, and Yarrowia yeasts) was transmitted by the beetles to the larvae via the anal and oral secretions and the carcass surface. These core taxa proliferated on the carcass, indicating a growth conducive environment for these microbes when associated with beetles. However, total bacterial loads were higher on decomposing carcasses without beetles than on beetle-prepared carcasses, indicating that the beetles and/or their associated symbionts suppress the growth of competing microbes. Thus, apart from being a nutritional resource, the carcass provides a medium for vertical transmission of a tightly regulated symbiotic microbiota, whose activity on the carcass and in the larval gut may involve carcass preservation as well as digestion.
Data from: Worldwide core collections of tea (Camellia sinensis) based on SSR markers
Tea (Camellia sinensis (L.) O. Kuntze) is the world's most popular beverage crop. However, to date, no core collection has been selected from worldwide germplasm resources on the basis of genotype data. In this study, we analyzed 788 tea germplasm accessions using 23 simple sequence repeat (SSR) markers. Our population structure analysis divided the germplasms into a Japanese group and an exotic group. The latter could be divided into var. sinensis and var. assamica. The genetic diversity was higher in germplasms from China, Taiwan, India, and Sri Lanka than in those from other countries, and low in germplasms from Japan. Using the number of SSR alleles as a measure of genetic diversity, we developed a core collection consisting of 192 accessions and three subcore collections with 96, 48, and 24 accessions. Although the results might be affected by marker-selection bias, the core 192 collection adequately covered the range of variation of the 788 accessions in floral morphology, and the chemical composition of first-flush leaves. These collections will be powerful tools for breeding and genetic research in tea.
Data from: Plasticity of promoter-core sequences allows bacteria to compensate for the loss of a key global regulatory gene
Transcription regulatory networks (TRNs) are of central importance for both short-term phenotypic adaptation in response to environmental fluctuations and long-term evolutionary adaptation, with global regulatory genes often being targets of natural selection in laboratory experiments. Here, we combined evolution experiments, whole-genome resequencing, and molecular genetics to investigate the driving forces, genetic constraints, and molecular mechanisms that dictate how bacteria can cope with a drastic perturbation of their TRNs. The crp gene, encoding a major global regulator in Escherichia coli, was deleted in four different genetic backgrounds, all derived from the Long-Term Evolution Experiment (LTEE) but with different TRN architectures. We confirmed that crp deletion had a more deleterious effect on growth rate in the LTEE-adapted genotypes; and we showed that the ptsG gene, which encodes the major glucose-PTS transporter, gained CRP dependence over time in the LTEE. We then further evolved the four crp-deleted genotypes in glucose minimal medium, and we found that they all quickly recovered from their growth defects by increasing glucose uptake. We showed that this recovery was specific to the selective environment and consistently relied on mutations in the cis regulatory region of ptsG, regardless of the initial genotype. These mutations affected the interplay of transcription factors acting at the promoters, changed the intrinsic properties of the existing promoters, or produced new transcription initiation sites. Therefore, the plasticity of even a single promoter region can compensate by three different mechanisms for the loss of a key regulatory hub in the E. coli TRN.
Data from: Combination of shear-wave elastography and color Doppler: feasible method to avoid unnecessary breast excision of fibroepithelial lesions diagnosed by core needle biopsy
Background: We evaluated shear-wave elastography (SWE) and color Doppler ultrasonography (US) features for fibroepithelial lesions (FELs), and to evaluate their utility to differentiate fibroadenomas (FAs) and phyllodes tumors (PTs). Methods: This retrospective study included 67 FELs pathologically confirmed (49 FAs, 18 PTs). B-mode US, SWE and color Doppler US were performed for each lesion. Mean elasticity (Emean), maximum elasticity (Emax), and vascularity were determined by SWE and Doppler US. Diagnostic performances were calculated to differentiate FAs and PTs. Equivocal FELs diagnosed by core needle biopsy (CNB) were further analyzed. Results: Median Emean and Emax were significantly lower for FAs than PTs (Emean, 15.7 vs. 66.7 kPa; Emax, 21.0 vs. 76.7 kPa, P<0.01). Low vascularity (0-1 vessel flow) on color Doppler US were more frequent in FAs than in PTs (P<0.01). SWE showed significantly higher specificities (Emean >43.9 kPa, 89.8%; Emax >46.1 kPa, 79.6%) than B-mode US (42.9%) (P<0.01) for differentiating PTs from FAs. Other diagnostic values of SWE and overall diagnostic values of Doppler US were not significantly different from B-mode US (P>0.05). The combination of SWE and Doppler US with 'Emean>43.9 kPa or high vascularity (≥2 vessel flows)' showed a higher area under the curve (0.786 vs. 0.687) and higher diagnostic values than B-mode US (sensitivity, 100 vs. 94.4 %; specificity, 57.1 vs. 42.9 %; positive predictive value, 46.2 vs. 37.8 %; negative predictive value, 100 vs. 95.5 %), without statistical significance (P>0.05). Of the 30 equivocal FELs, all lesions with 'Emean≤43.9 kPa and low vascularity (0-1 vessel flow)' (23.3%, 7/30) were finally confirmed as FAs by excision. Conclusion: FAs have a tendency to have less stiffness and lower vascularity than PTs. Combined SWE and color Doppler US may help patients with equivocal FELs diagnosed by CNB avoid unnecessary excision.
Data from: Synthesis and photoluminescence properties of silica-modified SiO2@ANA-Si-Tb@SiO2, SiO2@ANA-Si-Tb-L@SiO2 core-shell-shell nanostructured composites
Three novel core-shell nanostructured composites SiO2@ANA-Si-Tb, SiO2@ANA-Si-Tb-L (L = second ligand) with SiO2 as the core and terbium organic complex as the shell were successfully synthesized. The core and shell were connected together by covalent bonds. The terbium ion was coordinated with organic ligand forming terbium organic complex in the shell layer. The organosilane (HOOCC5H4NN(CONH(CH2)3Si(OCH2CH3)3)2 (abbreviated as ANA-Si) was used as the first ligand and 1, 10-phenanthroline (phen) or 2-thenoyltrifluoroacetone (TTA) was used as the second ligand. Furthermore, silica-modified SiO2@ANA-Si-Tb@SiO2, SiO2@ANA-Si-Tb-L@SiO2 core-shell-shell nanostructured composites were also synthesized by sol-gel chemical route, which involved the hydrolysis and polycondensation processes of tetraethoxysilane (TEOS) using cetyltrimethyl ammonium bromide (CTAB) as a surface-active agent. An amorphous silica shell was coated around the SiO2@ANA-Si-Tb, SiO2@ANA-Si-Tb-L core-shell nanostructured composites. The core-shell and core-shell-shell nanostructured composites exhibited excellent luminescence in solid state. Meanwhile, an improved luminescent stability property of the core-shell-shell nanostructured composites was observed for the aqueous solution. This type of core-shell-shell nanostructured composites exhibited bright luminescence, high stability and good solubility, which may present potential applications in the fields of optoelectronic devices, bio-imaging, medical diagnosis, and study on the structure of function composite materials.
Data from: Morphology of the core fibrous layer of the cetacean tail fluke
The cetacean tail fluke blades are not supported by any vertebral elements. Instead, the majority of the blades are composed of a densely packed collagenous fiber matrix known as the core layer. Fluke blades from six species of odontocete cetaceans were examined to compare the morphology and orientation of fibers at different locations along the spanwise and chordwise fluke blade axes. The general fiber morphology was consistent with a three‐dimensional structure comprised of two‐dimensional sheets of fibers aligned tightly in a laminated configuration along the spanwise axis. The laminated configuration of the fluke blades helps to maintain spanwise rigidity while allowing partial flexibility during swimming. When viewing the chordwise sectional face at the leading edge and mid‐chord regions, fibers displayed a crossing pattern. This configuration relates to bending and structural support of the fluke blade. The trailing edge core was found to have parallel fibers arranged more dorso‐ventrally. The fiber morphology of the fluke blades was dorso‐ventrally symmetrical and similar in all species except the pygmy sperm whale (Kogia breviceps), which was found to have additional core layer fiber bundles running along the span of the fluke blade. These additional fibers may increase stiffness of the structure by resisting tension along their long spanwise axis.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.