This dataset is based on the following manuscript/publication:
Page, N., S. Kasinathan, K. Bhat, G. Moorthi, T. Sundarraj, Divya Mudappa, and T. R. S. Raman (2022). A new population record of Critically Endangered Dipterocarpus bourdillonii Brandis from the Anamalai Tiger Reserve, Tamil Nadu. Journal of Threatened Taxa 14(8): 21651–21659. https://doi.org/10.11609/jott.7860.14.8.21651-21659

Please refer to the README.txt file included with the dataset for complete details and usage notes.

Geographic Coverage:
Location/Study Area: Valparai Plateau, Tamil Nadu, India; Anamalai Tiger Reserve, Tamil Nadu, India
GPS coordinates: Valparai Plateau (0°15'- 10°22'N, 76°52'-76°59'E); Anamalai Tiger Reserve (10°12'-10°35'N, 76°49'-77°24'E)

Temporal Coverage:
Begins: 2020-10-01 (Year, Month, Day)
Ends: 2022-05-31 (Year, Month, Day)

Funding:
Fondation Franklinia
AMM Murugappa Chettiar Research Centre
Rohini Nilekani Philanthropies

Dataset:

The dataset includes 7 files: 1 text file (README.txt), 5 data files in comma-delimited format (CSV), and 1 KML file of seven survey routes. Details of content of each CSV data file are provided below. The following files are included:
README.txt: Usage notes and metadata related to the dataset
1_Surveys_ver2.csv: Details of trails covered where Dipterocarpus bourdillonii was recorded during the survey
2_Focal_tree_data_ver2.csv: Details of focal trees of Dipterocarpus bourdillonii
3_Tree_centred_PCQ_ver2.csv: Data from point-centred quarter (PCQ) plots sampled with focal trees at the centre
4_Plant_checklist_ver2.csv: Checklist of plants (mainly trees) recorded on survey trails
5_Seed_fruit_ver2.csv: Measurements of fruits and seeds of Dipterocarpus bourdillonii
06_Dipterocarpus_bourdillonii_survey_trails.kml: This file includes the GPS tracks of the seven survey trails in KML format.

Details and data available in the columns in each of the above CSV files and the KML file are explained below.

1_Surveys_ver2.csv
Column: Description
Date: Date on which the survey was done
Place: Name of the place where the focal tree is located. e.g., Candura, Manamboli, Iyerpadi etc
Route_description:Description of place or route covered
Trail: Name of the tree survey trail
Trail_distance: Distance covered on the trail in kilometres (km)
Track_filename_kml: Name of the file with GPS track of survey trail/route, where available, in KML format
Observers: Names of observers who took measurements and filled datasheet during survey
Remarks: Notes and additional information

2_Focal_tree_data_ver2.csv
Column: Description
FT_ID: Unique numeric linking ID of each focal tree (NA for 3 individuals found in plots around other focal trees)
Species: Focal tree species
Date: Date on which the survey was done
Place: Name of forest range (Manamboli)
Waypoint: Unique location waypoint number for the focal tree and GPS instrument used
Time: Time when the focal tree's data was collected
Location: Landmark where the focal tree is located (NA, if not available)
Latitude: Latitude of the focal tree (decimal degrees N)
Longitude: Longitude of the focal tree (decimal degrees E)
Elevation: Elevation of the focal tree from sea-level in metres
Slope: Slope at focal tree location assessed with Clinometer, categorised as Flat, Gentle, Moderate, or Steep (NA, if not available)
ID_Notes: Any obvious signs with which to identify focal tree (NA, if not available)
Phenophase: Phenophase of the focal tree viz. leaf flush, buds/flowers, fruits (NA, if not available)
GBH: Girth of the focal tree in cm, at 1.3m from ground; measured from the higher side if tree is on slope
Tree_ht: Focal tree's height in m (NA, if not available)
Canopy_ht: Height of canopy in m where the focal tree is located (NA, if not available)
Substrate: Substrate where focal tree is standing viz. Earth, Rock, Streamside, Other (NA, if not available)
Invasives: List of invasive plant species present within 5 m radius around the focal tree (NA, if not available)
Stature: Stature of the focal tree relative to its surroundings (NOT of the species in general) categorised as Understorey, Mid, Canopy, Emergent (NA, if not available)
Relatively: Relative height of focal tree in relation to other trees within 10 m radius categorised as Shorter than most, Taller than most, Same height as most (NA, if not available)
Deadwood: Estimated percentage of deadwood present on the tree in 4 classes of <25%, 26-50%, 51-75%, 76-100% (NA, if not available)
Damage: Observed damages such as Main trunk broken, Branches broken, Hollow at base, Gaping cavity, Infected, Dried leaves (as on a dead branch) (NA, if not available)
Shape: Canopy shape of the focal tree (not species in general) categorised as Spreading, Oval, Fan, Column, Cone (NA, if not available)
Closure: Canopy closure due to foliage visually estimated standing next to trunk of focal tree and looking up, categorised as 0% (only sky and leafless branches visible), 1-25%, 26-50%, 51-75%, 76-100% (NA, if not available)
Seedlings: Count of conspecific seedlings (stems of girth at breast height <10 cm) around the focal tree in a 5 m radius (NA, if not available)
Saplings: Count of conspecific saplings (stems of girth at breast height 10-30 cm) around the focal tree in a 5 m radius (NA, if not available)
Trees: Count of conspecific trees (stems of girth at breast height >30 cm) around the focal tree in a 5 m radius (NA, if not available)
Remarks: Notes and additional information (NA, if not available)

3_Tree_centred_PCQ_ver2.csv
Column: Description
FT_ID: Unique numeric linking ID of each focal tree in point-centred quarter (PCQ) plot
Focal_tree: Scientific name of focal tree species at the centre of the PCQ plot
Species: Scientific name of tree species recorded in PCQ plot around focal tree
GBH (cm): Girth of PCQ tree in cm, at 1.3 m from ground; measured from the higher side if tree is on a slope. Main stem only.
Distance: Distance from focal tree, in m; measured from the approximate centre of bole to centre of bole and not bark to bark
Multistem: NA if single-stemmed; if multi-stemmed, then GBH of additional stems given as notes.

4_Plant_checklist_ver2.csv
Column: Description
Date: Date on which the survey was done
Place: Name of the place where the focal tree is located. e.g., Candura, Manamboli, Iyerpadi etc
Route: Route of the tree survey trail
Checklist_species: Scientific name of tree species observed as present along trail and within 10 m on either side
Remarks: Notes and additional information

5_Seed_Fruit_ver2.csv
Column: Description
Sample: Serial number of sample of single winged fruit measured
Species: Scientific name of tree species
No_Seeds: Unit number of seed measured
Fresh_fruit_weight_g: Weight of each fruit measured on an Ohaus scale in grams
Nut_length_cm: Length of nut along the longitudinal axis in cm
Nut_width_1_cm: Width of nut in cm measured along axis perpendicular to nut length
Nut_width_2_cm: Width of nut in cm measured along axis perpendicular to nut length and nut width 1
Wing1_length_cm: Length of longer wing (sepal) in cm
Wing1_width_cm: Width of longer wing (sepal) in cm
Wing2_length_cm: Length of shorter wing (sepal) in cm
Wing2_width_cm: Width of shorter wing (sepal) in cm

06_Dipterocarpus_bourdillonii_survey_trails.kml
This file includes the GPS tracks of the following seven trails in KML format:
2021-01-30_Anali-Ayyankulam-Manamboli (Trail-2)
2021-03-26_Ayyankulam (Trail-4)
2021-04-10_Ayyankulam Parai (Trail-5)
2022-03-07_Ayyankulam Parai to Ayyankulam_leftbank (Trail-8)
2022-03-07_Ayyankulam Parai to Ayyankulam_rightbank (Trail-9)
2022-03-09_Manamboli PH_leftbank (Trail-10)
2022-03-09_Manamboli PH_rightbank (Trail-11)

Aggregated variant data obtained from tinnitus patients from Sweden.

Uploaded datasets are storage in annotated csv files. Annotation was performed using VEP (v106), including population frequencies for each variant from gnomAD, non-finnish Europeans from gnomAD, and swedish population from SweGen project. Pathogenicity scores from CADD are also annotated for each variant. Variants from genes found to be enriched in a gene burden analysis can be found in this aggregated dataset.

agg.tiger.csv - TIGER cohort is composed by 97 swedish whole-genome sequenced constant tinnitus patients.

agg.jaguar.csv - JAGUAR cohort is composed by 147 swedish whole-exome sequenced tinnitus patients .

agg.sevtin.csv - SEVTIN cohort is a subcohort from TIGER, with 34 WGS patients seggregating severe tinnitus phenotype.

agg.controls.csv - Controls is a swedish population cohort composed by 151 whole-exome sequenced swedish individuals.

Overview This dataset re-shares cartographic and demographic data from the U.S. Census Bureau to provide an obvious supplement to Open Environments Block Group publications.These results do not reflect any proprietary or predictive model. Rather, they extract from Census Bureau results with some proportions and aggregation rules applied. For additional support or more detail, please see the Census Bureau citations below. Cartographics refer to shapefiles shared in the Census TIGER/Line publications. Block Group areas are updated annually, with major revisions accompanying the Decennial Census at the turn of each decade. These shapes are useful for visualizing estimates as a map and relating geographies based upon geo-operations like overlapping. This data is kept in a geodatabase file format and requires the geopandas package and its supporting fiona and DAL software. Demographics are taken from popular variables in the American Community Survey (ACS) including age, race, income, education and family structure. This data simply requires csv reader software or pythons pandas package. While the demographic data has many columns, the cartographic data has a very, very large column called "geometry" storing the many-point boundaries of each shape. So, this process saves the data separately, with demographics columns in a csv file and geometry in a gpd file needed an installation of geopandas, fiona and DAL software. More details on the ACS variables selected and derivation rules applied can be found in the commentary docstrings in the source code found here: https://github.com/OpenEnvironments/blockgroupdemographics. ## Files While the demographic data has many columns, the cartographic data has a very, very large column called "geometry" storing the many-point boundaries of each shape. So, this process saves the data separately, with demographics columns in a csv file named YYYYblcokgroupdemographics.csv. The cartographic column, 'geometry', is shared as file named YYYYblockgroupdemographics-geometry.pkl. This file needs an installation of geopandas, fiona and DAL software.

Dataset of 3D landmark coordinate data (50 landmarks) placed on crania of 41 Australian tiger snakes (Notechis scutatus). Landmark data (Data.csv) were collected using Checkpoint (Stratovan) on microCT scans (scan data available from Morphosource https://www.morphosource.org/projects/00000C744). Script for R Statistical Environment (Palci et al script.R) is for all statistical analyses and visualisations performed in the paper, calling the Landmark data (Data.csv) and index for symmetry (Pairs.csv) from the working directory containing the R script. Preliminary data and analyses of measurement error are provided in the Error test.zip folder.

Geospatial data about Arkansas Civil Divisions (TIGER). Export to CAD, GIS, PDF, CSV and access via API.

These files contain data from the article "SHAP zero Explains All-order Feature Interactions in Black-box Genomic Models with Near-zero Query Cost" by Darin Tsui, Aryan Musharaf, and Amirali Aghazadeh. Files presented here contains all SHAP values and Shapley interactions found by SHAP zero, KernelSHAP, and SHAP-IQ from inDelphi and TIGER, using code from https://github.com/amirgroup-codes/shapzero/.Description of filesTIGER_shapzero_values.csv: All SHAP values found by SHAP zero from TIGER.Columns:Sequence: sequence inputted to TIGER.Position 1 to 26: SHAP value of each nucleotide at each position.TIGER_kernelshap_values.csv: All SHAP values found by KernelSHAP from TIGER.Columns:Sequence: sequence inputted to TIGER.Position 1 to 26: SHAP value of each nucleotide at each position.TIGER_deepshap_values.csv: All SHAP values found by DeepSHAP from TIGER.Columns:Sequence: sequence inputted to TIGER.Position 1 to 26: SHAP value of each nucleotide at each position.TIGER_fastshap_values.csv: All SHAP values found by FastSHAP from TIGER.Columns:Sequence: sequence inputted to TIGER.Position 1 to 26: SHAP value of each nucleotide at each position.TIGER_shapzero_fsi.csv: All Faith-Shap interactions found by SHAP zero from TIGER.Columns:Sequence: sequence inputted to TIGER.Order 1 to 5: Dictionary of all interactions of orders 1-5. The keys represent the nucleotide position (0-indexed) affected, and the values represent the Faith-Shap interaction at those nucleotides. For example, the key:value pairing {(0,1,2):0.1} and the sequence TCA, means that the first (T), second (C), and third (A) nucleotides are interacting with a Faith-Shap interaction value of 0.1.TIGER_shapiq_fsi.csv: All Faith-Shap interactions found by SHAP-IQ from TIGER.Columns:Sequence: sequence inputted to TIGER.Order 1 to 2: Dictionary of all interactions of orders 1-2. The keys represent the nucleotide position (0-indexed) affected, and the values represent the Faith-Shap interaction at those nucleotides.Order 3 part 1 to 6: Since SHAP-IQ produced too many 3rd-order interactions for Excel to handle in a single column, the 3rd orders are split across 6 columns.inDelphi_shapzero_values.csv: All SHAP values found by SHAP zero from inDelphi.Columns:Sequence: sequence inputted to inDelphi.Position 1 to 40: SHAP value of each nucleotide at each position.inDelphi_kernelshap_values.csv: All SHAP values found by KernelSHAP from inDelphi.Columns:Sequence: sequence inputted to inDelphi.Position 1 to 40: SHAP value of each nucleotide at each position.inDelphi_fastshap_values.csv: All SHAP values found by FastSHAP from inDelphi.Columns:Sequence: sequence inputted to inDelphi.Position 1 to 40: SHAP value of each nucleotide at each position.inDelphi_shapzero_fsi.csv: All Faith-Shap interactions found by SHAP zero from inDelphi.Columns:Sequence: sequence inputted to inDelphi.Order 1 to 5: Dictionary of all interactions of orders 1-5. The keys represent the nucleotide position (0-indexed) affected, and the values represent the Faith-Shap interaction at those nucleotides. For example, the key:value pairing {(0,1,2):0.1} and the sequence TCA, means that the first (T), second (C), and third (A) nucleotides are interacting with a Faith-Shap interaction value of 0.1.inDelphi_shapiq_fsi.csv: All Faith-Shap interactions found by SHAP-IQ from inDelphi.Columns:Sequence: sequence inputted to inDelphi.Order 1 to 2: Dictionary of all interactions of orders 1-2. The keys represent the nucleotide position (0-indexed) affected, and the values represent the Faith-Shap interaction at those nucleotides.Order 3 part 1 to 20: Since SHAP-IQ produced too many 3rd-order interactions for Excel to handle in a single column, the 3rd orders are split across 20 columns.

This dataset contains Mammal occurrence records (January 2020 - June 2023) in the Valparai Plateau and Anamalai Tiger Reserve, Western Ghats, India. It includes a few occurrence records of reptiles. Occurrence records were gathered in the field by researchers of the Nature Conservation Foundation, India, using a mobile data collection application. Suggested citation is:Nature Conservation Foundation (2024). Mammal occurrence records (2020-23) in the Valparai Plateau and Anamalai Tiger Reserve, Western Ghats, India. Nature Conservation Foundation, India. Dataset, Zenodo. DOI: 10.5281/zenodo.11903722 CONTACT #11. Name: T. R. Shankar Raman 2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India3. Work Phone: +91 821 25156014. Email address: trsr@ncf-india.org 5. ORCID: https://orcid.org/0000-0002-1347-3953

CONTACT #21. Name: Divya Mudappa 2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India3. Work Phone: +91 821 25156014. Email address: divya@ncf-india.org 5. ORCID: https://orcid.org/0000-0001-9708-4826

Keywords: tropical rainforest, plantations, Anamalai Hills, Western Ghats, animal distribution, mammals

Geographic Coverage:1. Location/Study Area: Valparai Plateau, Tamil Nadu, India; Anamalai Tiger Reserve, Tamil Nadu, India2. GPS coordinates: Valparai Plateau (10°15'- 10°22'N, 76°52' - 76°59'E); Anamalai Tiger Reserve (10°12' - 10°35'N, 76°49' - 77°24'E)

Temporal Coverage:1. Begins: 2020-01-11 (Year, Month, Day)2. Ends: 2023-06-02 (Year, Month, Day)

Besides the 000_readMe.txt file containing this information, the dataset includes 60 images (photographs), three comma-delimited text (csv) files, and one R markdown text file with R code as explained below:1) 001_mammalData.csv -- This file has the main mammal occurrence data with relevant and renamed columns derived from the original downloaded Excel worksheet file

2) 002_placeLocs.csv -- This file lists names places for which the GPS location was unavailable from the mobile phone application, and was manually assigned to coordinates with 500 m accuracy

3) 003_nameMatch.csv -- This file matches the name as originally recorded with the correct common name and scientific name

4) 004_mammup.Rmd -- R code for processing the files to create a file for upload as an occurrence dataset on the Global Biodiversity Information Facility (GBIF.org)

+60 image files (with ".jpg" file extension)

FILES INCLUDED IN DATASET

001_mammdata.csvThis file has the main mammal occurrence data with relevant and renamed columns derived from the original downloaded Excel worksheet file recordedBy: Observer who recorded/made the observationusername: Username of person on whose mobile phone the data were notedtimestamp: Automatic time stamp of date and time when app was useddate: Date of observationtime: Time of observationdecimalLatitude: Latitude in decimal degrees NdecimalLongitude: Longitude in decimal degrees EGPSaltitude: Altitude in metresGPSaccuracy: Horizontal accuracy of GPS location in metresplace: Name of localityhabitat: Habitat typespecies: Species common namecount: Number of individuals observedcountType: Total (solitary or fully counted groups) or Partial (incompletely counted groups)obsType: Type of observation: sighting, sign (droppings or vocalisation), death, roadkill, electrocution, othernotes: Notes or remarks on observationimageID: Image filename if available (NA, if not available)instanceID: Automatically generated unique identifier of observation

002_placeLocs.csvThis file lists names places for which the GPS location was unavailable from the mobile phone application, and was manually assigned to coordinates with 500 m accuracyplace: Name of locality as recordedlat: Assigned latitude in decimal degrees Nlong: Assigned longitude in decimal degrees EGPSaccuracy: Assigned as 500 m – Horizontal accuracy of GPS location in metres

003_nameMatch.csvThis file matches the name as originally recorded with the correct common name and scientific name.verbatimIdentification: Identification as originally recorded in the ‘species’ column of the mammdata.csv filevernacularName: Common or engish namescientificName: Scientific name

004_mammup.RmdR code for processing the files to create a file for upload as an occurrence dataset on the Global Biodiversity Information Facility (GBIF.org)