cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13021/orc2020/ebaihb/n7ukhp
title: IES-CODEBOOK-YEAR-1.pdf

description: Year 1 codebook
DOI: 10.13021/orc2020/ebaihb/iuwjji
title: IES-CODEBOOK-YEAR-1.doc

description: Year 1 codebook
DOI: 10.13021/orc2020/ebaihb/zels4k
title: IES-19-Data-sharing.doc

description: Data sharing document
DOI: 10.13021/orc2020/ebaihb/lcf6fh
title: IES-19-Data-sharing.pdf

description: Data sharing document
DOI: 10.13021/orc2020/ebaihb/u62stx
title: YEAR-2-anonymous.tab

description: Year 2 results
DOI: 10.13021/orc2020/ebaihb
title: Focusing on the Efficacy of Teaching Advanced Forms of Patterning on Kindergartners’ Improvements

description: File gives pretest and posttest scores of kindergartners who received four forms of instruction.
DOI: 10.13021/orc2020/ebaihb/svrzxc
title: YEAR-1-anonymous.tab

description: Year 1 results
DOI: 10.13021/orc2020/ughd5m/ymfujg
title: Occ_Data.tab
DOI: 10.13021/orc2020/ughd5m/8txka1
title: Wind_Speed.tab
DOI: 10.13021/orc2020/ughd5m/9reees
title: Occ_Covar.tab
DOI: 10.13021/orc2020/ughd5m/59w2m1
title: Precipitation.tab
DOI: 10.13021/orc2020/ughd5m
title: Replication Data for: Local habitat heterogeneity, productivity, and climate data for estimating avian species richness and species of concern

description: These files contain tabular data for occupancy, climate, habitat heterogeneity, and productivity measures. These data can be used to replicate models estimating avian species richness at a local scale. The resolution of the remote sensing data is calculated at 160m x 160m.
DOI: 10.13021/orc2020/ughd5m/suvirm
title: Temperature.tab
DOI: 10.13021/orc2020/tkofvk/khf5al
title: affective_forecasting_study1.tab
DOI: 10.13021/orc2020/tkofvk
title: Affective Forecasting and Performance 2016 - Study 1

description: Data is from a daily diary study in which participants made predictions about their emotions during upcoming work tasks, and then reported on their experienced emotions and performance over the course of a week.
DOI: 10.13021/orc2020/tkofvk/3zpvyd
title: affective_forecasting_study2.tab
DOI: 10.13021/orc2020/mvtefa/p6rcn1
title: Readme.pdf
DOI: 10.13021/orc2020/mvtefa/bqtl7t
title: Slab3_Accelerometer_Data.tab
DOI: 10.13021/orc2020/mvtefa/hrdiz6
title: Slab4_Accelerometer_Data.tab
DOI: 10.13021/orc2020/mvtefa/xs5ext
title: Slab7_Accelerometer_Data.tab
DOI: 10.13021/orc2020/mvtefa/i6inyu
title: Slab9_Displacement_Data.tab
DOI: 10.13021/orc2020/mvtefa/fkeleg
title: Slab4_Pressure_Data.tab
DOI: 10.13021/orc2020/mvtefa/hucffj
title: Slab5_Accelerometer_Data.tab
DOI: 10.13021/orc2020/mvtefa/rhkxwy
title: Slab10_Pressure_Data.tab
DOI: 10.13021/orc2020/mvtefa/vflmjq
title: Slab9_Accelerometer_Data.tab
DOI: 10.13021/orc2020/mvtefa/edllzr
title: Slab7_Pressure_Data.tab
DOI: 10.13021/orc2020/mvtefa/yne0bq
title: Slab6_Accelerometer_Data.tab
DOI: 10.13021/orc2020/mvtefa/jlono2
title: Slab3_Displacement_Data.tab
DOI: 10.13021/orc2020/mvtefa/wvb4g6
title: Slab2_Displacement_Data.tab
DOI: 10.13021/orc2020/mvtefa/hmwa15
title: Slab8_Pressure_Data.tab
DOI: 10.13021/orc2020/mvtefa/4sdss7
title: Slab1_Pressure_Data.tab
DOI: 10.6084/m9.figshare.27924837
title: A deep learning model based on the BERT pre-trained model to predict the antiproliferative activity of anti-cancer chemical compounds

description: Identifying new compounds with minimal side effects to enhance patients’ quality of life is the ultimate goal of drug discovery. Due to the expensive and time-consuming nature of experimental investigations and the scarcity of data in traditional QSAR studies, deep transfer learning models, such as the BERT model, have recently been suggested. This study evaluated the model’s performance in predicting the anti-proliferative activity of five cancer cell lines (HeLa, MCF7, MDA-MB231, PC3, and MDA-MB) using over 3,000 synthesized molecules from PubChem. The results indicated that the model could predict the class of designed small molecules with acceptable accuracy for most cell lines, except for PC3 and MDA-MB. The model’s performance was further tested on an in-house dataset of approximately 25 small molecules per cell line, based on IC50 values. The model accurately predicted the biological activity class for HeLa with an accuracy of 0.77±0.4 and demonstrated acceptable performance for MCF7 and MDA-MB231, with accuracy between 0.56 and 0.66. However, the results were less reliable for PC3 and HepG2. In conclusion, the ChemBERTa fine-tuned model shows potential for predicting outcomes on in-house datasets.
DOI: 10.6084/m9.figshare.27924837.v1
title: A deep learning model based on the BERT pre-trained model to predict the antiproliferative activity of anti-cancer chemical compounds

description: Identifying new compounds with minimal side effects to enhance patients’ quality of life is the ultimate goal of drug discovery. Due to the expensive and time-consuming nature of experimental investigations and the scarcity of data in traditional QSAR studies, deep transfer learning models, such as the BERT model, have recently been suggested. This study evaluated the model’s performance in predicting the anti-proliferative activity of five cancer cell lines (HeLa, MCF7, MDA-MB231, PC3, and MDA-MB) using over 3,000 synthesized molecules from PubChem. The results indicated that the model could predict the class of designed small molecules with acceptable accuracy for most cell lines, except for PC3 and MDA-MB. The model’s performance was further tested on an in-house dataset of approximately 25 small molecules per cell line, based on IC50 values. The model accurately predicted the biological activity class for HeLa with an accuracy of 0.77±0.4 and demonstrated acceptable performance for MCF7 and MDA-MB231, with accuracy between 0.56 and 0.66. However, the results were less reliable for PC3 and HepG2. In conclusion, the ChemBERTa fine-tuned model shows potential for predicting outcomes on in-house datasets.
DOI: 10.13021/orc2020/mvtefa/qfgut4
title: Slab7_Displacement_Data.tab
DOI: 10.13021/orc2020/mvtefa/vhe1v7
title: Slab1_Accelerometer_Data.tab
DOI: 10.13021/orc2020/mvtefa/hsqtlh
title: Slab4_Displacement_Data.tab
DOI: 10.13021/orc2020/mvtefa/9fcv9b
title: Slab8_Displacement_Data.tab
DOI: 10.13021/orc2020/mvtefa/xiaj4y
title: Slab10_Displacement_Data.tab
DOI: 10.13021/orc2020/mvtefa/gmbr3w
title: Slab5_Displacement_Data.tab
DOI: 10.13021/orc2020/mvtefa/e7nxw8
title: Slab6_Displacement_Data.tab
DOI: 10.13021/orc2020/mvtefa/ajnzsv
title: Slab3_Pressure_Data.tab
DOI: 10.13021/orc2020/mvtefa/oikb0j
title: Slab6_Pressure_Data.tab
DOI: 10.13021/orc2020/mvtefa/azq7qm
title: Slab2_Pressure_Data.tab
DOI: 10.13021/orc2020/mvtefa/sgiz62
title: Slab5_Pressure_Data.tab
DOI: 10.13021/orc2020/mvtefa/dme7rp
title: Slab9_Pressure_Data.tab
DOI: 10.13021/orc2020/mvtefa/4qljal
title: Urgessa_UNCDownloadMetrics_20210505.tab

description: Recorded data set download metrics from UNC Dataverse.
DOI: 10.13021/orc2020/mvtefa
title: Experimental Records from Blast Tests of Ten Reinforced Concrete Slabs

description: The data contains pressure, displacement, and acceleration measurements from ten reinforced concrete slabs subjected to blast. The tests were conducted at the Science and Technology Aerospace Department (DCTA) blast test site in São José dos Campos, São Paulo, Brazil. Note that Slab1_Displacement, Slab2_Accelerometer, Slab8_Accelerometer, and Slab10_Accelerometer are not provided because the sensors failed.
DOI: 10.13021/orc2020/mvtefa/rg1nze
title: Readme.pdf
DOI: 10.13021/orc2020/9qie8m
title: Mild Cognitive Impairment and Obstructive Sleep Apnea (2012-2014)

description: See &lt;a href="https://clinicaltrials.gov/ct2/show/study/NCT01482351"&gt;https://clinicaltrials.gov/ct2/show/study/NCT01482351&lt;/a&gt;.
DOI: 10.13021/orc2020/ivbdod
title: Data for Long-term Changes in Plumage Between Urban and Rural Populations of White-crowned Sparrows

description: This file contains the plumage coloration values collected from white-crowned sparrow museum specimens. The specimen were collected between 1895-1990.
description: This data is a part of a peer-reviewed publication in the Journal of Urban Ecology. All methods are described in this manuscript. It has been accepted and will be published in early 2021.
DOI: 10.13021/orc2020/ivbdod/ocbpvy
title: Completed_data_for_WCSP_plumage_paper.tab

description: The original Excel spreadsheet contains two tabs. Tab 1 = plumage data breed only. Tab 2 = figs crown. This Tab file contains Tab 1.
DOI: 10.13021/orc2020/ivbdod/uhxvek
title: Completed_data_for_WCSP_plumage_paper_figs_crown.txt

description: This file contains Tab 2, figs crown.
DOI: 10.13021/orc2020/yiqttg
title: Data associated with temporal variations of de facto wastewater reuse and disinfection by-products in public drinking water systems in the Shenandoah River watershed, USA

description: This Excel file (comprising 5 tabs plus a ReadMe file) provides supplemental information for an article in Water Practice and Technology (https://iwaponline.com/wpt) titled "Temporal variations of de facto wastewater reuse and disinfection by-products in public drinking water systems in the Shenandoah River watershed, USA".
DOI: 10.13021/orc2020/yiqttg/k4jwnz
title: Weisman_TempVars_SI_2021_June.tab

description: Data associated with temporal variations of de facto wastewater reuse and disinfection by-products in public drinking water systems in the Shenandoah River watershed, USA
DOI: 10.13021/orc2020/1iwpsc/4lgsyw
title: Wave_Trans_1.py
DOI: 10.13021/orc2020/1iwpsc/5xmcbs
title: swan_HS_max.63.nc
DOI: 10.13021/orc2020/1iwpsc/zzrhtr
title: swan_DIR_max.63.nc
DOI: 10.13021/orc2020/1iwpsc/vsfqcv
title: fort15.15
DOI: 10.13021/orc2020/1iwpsc/9jcciu
title: timestep.py
DOI: 10.13021/orc2020/1iwpsc/chekxp
title: maxele.63.nc
DOI: 10.13021/orc2020/1iwpsc/sxssh1
title: swan_DIR.63.nc
DOI: 10.13021/orc2020/1iwpsc/l2vp4c
title: fort.15
DOI: 10.13021/orc2020/1iwpsc/0rfwxu
title: fort.14
DOI: 10.13021/orc2020/1iwpsc/sdhjg8
title: ArcWaT_Tutorial_v1.docx
DOI: 10.13021/orc2020/1iwpsc/vcygup
title: Arc_WaT.tbx
DOI: 10.13021/orc2020/1iwpsc/tbelfa
title: fort.22
DOI: 10.13021/orc2020/1iwpsc/czonvc
title: swan_HS.63.nc
DOI: 10.13021/orc2020/1iwpsc/f0ddsp
title: fort.63.nc
DOI: 10.13021/orc2020/1iwpsc/4gy0pf
title: fort.13
DOI: 10.13021/orc2020/1iwpsc/wyeebg
title: max.py
DOI: 10.13021/orc2020/1iwpsc/1u7txl
title: 424ac0a601136a7dcf8d8da3e898d260f72387
DOI: 10.13021/orc2020/1iwpsc/s2l5ra
title: HEAD
DOI: 10.13021/orc2020/1iwpsc/lzg1h4
title: pre-merge-commit.sample
DOI: 10.13021/orc2020/1iwpsc/xxc2oe
title: master
DOI: 10.13021/orc2020/1iwpsc/13s4aj
title: bbadfa7b9f0874f0c8f49e9ea6ddcb813f0586
DOI: 10.13021/orc2020/1iwpsc/dvgduq
title: e8d84c7f0c8c0099d7d8a80a824e9cf3e496ae
DOI: 10.13021/orc2020/1iwpsc/f7lkth
title: pre-commit.sample
DOI: 10.13021/orc2020/1iwpsc/myw3ly
title: update.sample
DOI: 10.13021/orc2020/1iwpsc/yvri5b
title: index
DOI: 10.13021/orc2020/1iwpsc/1pknrr
title: 3d7fa812ddf72fc3c0fde9a35de55b44d52ccd
DOI: 10.13021/orc2020/1iwpsc/axspkt
title: prepare-commit-msg.sample
DOI: 10.13021/orc2020/1iwpsc/tx6z46
title: exclude
DOI: 10.13021/orc2020/1iwpsc/ui8wzv
title: post-update.sample
DOI: 10.13021/orc2020/1iwpsc/nrwto8
title: commit-msg.sample
DOI: 10.13021/orc2020/1iwpsc/ouk6iw
title: e506c3670b93835add66a1464d1c758bda58ed
DOI: 10.13021/orc2020/1iwpsc/rqqjl8
title: pre-receive.sample
DOI: 10.13021/orc2020/1iwpsc/tljkh2
title: pre-push.sample
DOI: 10.13021/orc2020/1iwpsc/kwpw9p
title: applypatch-msg.sample
DOI: 10.15468/dl.swegb6
title: Occurrence Download

description: A dataset containing 293 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Belgium, Italy, France)",
 "HasCoordinate is false",
 "Month is one of (August, September, July, June)",
 "OccurrenceStatus is Present",
 "Year 2024-2025"
 ]
}

 The dataset includes 293 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072767-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13021/orc2020/1iwpsc/ps1o38
title: COMMIT_EDITMSG
DOI: 10.13021/orc2020/1iwpsc/0ihpo1
title: Wave_Trans_1.py
DOI: 10.13021/orc2020/1iwpsc/xezjkh
title: master
DOI: 10.13021/orc2020/1iwpsc/emg6oj
title: config
DOI: 10.13021/orc2020/1iwpsc/6n5dep
title: pre-applypatch.sample
DOI: 10.13021/orc2020/1iwpsc/5h9guk
title: 642851784194f8b50ae5437c21f6c5cd6dc2a5
DOI: 10.13021/orc2020/1iwpsc/eutrci
title: description
DOI: 10.13021/orc2020/1iwpsc/8l01tu
title: fsmonitor-watchman.sample
DOI: 10.13021/orc2020/1iwpsc/trnq4r
title: pre-rebase.sample
DOI: 10.13021/orc2020/1iwpsc
title: ArcGIS Wave Transformation toolbox - ArcWaT

description: The ArcWaT is a model-based GIS toolbox for estimating wave transformation from wave magnitude and direction model outputs.
DOI: 10.13021/orc2020/1iwpsc/vjulpg
title: HEAD
DOI: 10.13021/orc2020/c9ecfo/70oxff
title: z.cz00_eqv_v1.tab

description: Commuting zone file
DOI: 10.13021/orc2020/c9ecfo/31wkr2
title: z.county_adjacency.txt

description: County adjacency file
DOI: 10.13021/orc2020/c9ecfo/ggvzgj
title: tnd_covid_analysis_data-1.tab

description: Analysis data (CSV format)
DOI: 10.13021/orc2020/c9ecfo/byctmm
title: models_king_final.do

description: Stata do-file called by main analysis do-file
DOI: 10.13021/orc2020/c9ecfo/z3efva
title: tnd_covid_analysis_runall_final.do

description: Main Stata analysis do-file
DOI: 10.13021/orc2020/c9ecfo/9599ag
title: z.acs_prep.do

description: Stata do-file to construct variables using Social Explorer data
DOI: 10.13021/orc2020/c9ecfo/wokocl
title: tnd_covid_analysis_data.tab

description: Analysis data (Stata format)
DOI: 10.13021/orc2020/c9ecfo/c4cl3u
title: models_wi_final.do

description: Stata do-file called by main analysis do-file
DOI: 10.13021/orc2020/c9ecfo/zbpbt4
title: models_sf_final.do

description: Stata do-file called by main analysis do-file
DOI: 10.13021/orc2020/c9ecfo/nz0qyi
title: WI_COVID-19_Historical_Data_by_Census_Tract.tab

description: Archive of dependent variable download
DOI: 10.13021/orc2020/c9ecfo/uqoiav
title: z.R_create_mobdis.R

description: R script to construct neighborhood networks and mobility-based disadvantage
DOI: 10.13021/orc2020/c9ecfo
title: Replication Data for: Neighborhood Mobility Inequality Predicts COVID-19

description: This dataset provides replication data and code for the publication listed below.
DOI: 10.13021/orc2020/c9ecfo/l2wncl
title: readme.docx

description: How to use this replication package
DOI: 10.13021/orc2020/z2wmau/kvqhet
title: N_protein_177.pdb

description: Initial structure for NAMD
DOI: 10.13021/orc2020/z2wmau/jcbdjl
title: N-protein phi-psi.tab

description: data matrix containing phi and psi angles
DOI: 10.13021/orc2020/z2wmau/ydchpn
title: NP177_Sol_ion.psf

description: PSF file generated from simulation
DOI: 10.13021/orc2020/z2wmau/oxljvj
title: NP177_Sol_ion.pdb

description: Initial structure for NAMD
DOI: 10.13021/orc2020/z2wmau/onpy4x
title: NP198_Sol_ion.psf

description: PSF file generated from simulation
DOI: 10.13021/orc2020/z2wmau/1k6dvn
title: NPS177A_Sol_ion.psf

description: PSF file from NAMD simulation
DOI: 10.13021/orc2020/z2wmau/baa8mv
title: Classification Tree.ows

description: Orange3 module for Classification Trees
DOI: 10.13021/orc2020/z2wmau/fwv1nl
title: NAMD_R_analysis_2020.R

description: R scripts to perform machine learning
DOI: 10.13021/orc2020/z2wmau/ptah4w
title: NPS177A_Sol_ion.pdb

description: Initial structure for NAMD
DOI: 10.13021/orc2020/z2wmau/ulv9po
title: NP_wb_ion.psf

description: PSF file from NAMD simulation
DOI: 10.13021/orc2020/z2wmau/odrxnb
title: Cross-Validation.ows

description: Orange3 module for Cross Validation
DOI: 10.13021/orc2020/z2wmau/mihkpw
title: NP_wb_ion .namd

description: NAMD script
DOI: 10.13021/orc2020/z2wmau
title: Replication Data for: Active Site Prediction of Phosphorylated SARS-CoV-2 N-Protein Using Molecular Simulation

description: Scripts and configuration files needed to reproduce data in the manuscript.&lt;BR&gt;
DOI: 10.13021/orc2020/z2wmau/vpnepb
title: getphi.tcl

description: TCL code to extract phi and psi angles
DOI: 10.13021/orc2020/ow4t3k/eaegds
title: getphi.tcl

description: TCL code to extract phi and psi angles
DOI: 10.13021/orc2020/ow4t3k/kqxwsc
title: NSP10.Rnw
DOI: 10.13021/orc2020/ow4t3k/tldt67
title: 6ZPE.pdb

description: PDB structure file with initial structure
DOI: 10.13021/orc2020/ow4t3k/j0lsop
title: README.txt

description: File List
DOI: 10.13021/orc2020/ow4t3k/rh9urw
title: NSP10_param.namd

description: NAMD parameter file
DOI: 10.5281/zenodo.14673679
title: S-NPP OMPS LP PSC Data

description: Daily files of polar stratospheric cloud presence observed by the Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) instrument on the Suomi National Polar-orbiting Partnership (S-NPP) satellite.
DOI: 10.13021/orc2020/ow4t3k
title: Replication Data for: Optimizing Peptide Inhibitors of SARS-Cov-2 nsp10/nsp16 Methyltransferase Predicted through Molecular Simulation and Machine Learning

description: Scripts and files needed to reproduce manuscript results.
DOI: 10.13021/orc2020/ow4t3k/ueocsm
title: NSP10.conf

description: NAMD configuration file
DOI: 10.13021/orc2020/vczoqg/mlrhgj
title: restart.init

description: Initial conditions for model
DOI: 10.13021/orc2020/vczoqg/kwg28s
title: main.f

description: Main program

Makefile used is below,

#makefile for generating program to solve 1-D spatial model
#
#Gnu Compiler
FFLAGS=-O4 -ffixed-line-length-132
#F77=g77
F77=gfortran
#HP Compiler
#FFLAGS=-O3 +U77 +extend_source
#F77=f90

mito: main.o fcn.o rk4am.o 
 $(F77) $(FFLAGS) *.o -o mito

.f.o:
 $(F77) $(FFLAGS) -c $&lt;
DOI: 10.13021/orc2020/vczoqg/px3kzk
title: rk4am.f

description: Runge-Kutta ODE solver
DOI: 10.13021/orc2020/vczoqg
title: Replication Data for: Computational Modelling of Mitochondria to Understand the Dynamics of Oxidative Stress

description: Fortran code for mitochondrial model
DOI: 10.13021/orc2020/vczoqg/uvba80
title: fcn.f

description: ODE equations for the model
DOI: 10.13021/orc2020/byz4wb
title: Replication Data for: Cardiac alternans occurs through the synergy of voltage- and calcium-dependent mechanisms.

description: Fortran/CUDA Fortran Code for the rat ventricular myocyte model
DOI: 10.13021/orc2020/byz4wb/9ti3qe
title: ratmodelcode.tar

description: Fortran Model Code
DOI: 10.13021/orc2020/pcvrh4/ccpzsb
title: Flock_foraging_heights.tab
DOI: 10.13021/orc2020/pcvrh4/d9rhgx
title: KarlFlocksGIS.tab
DOI: 10.13021/orc2020/pcvrh4/cehpmb
title: Space Use Publication R Script.R
DOI: 10.13021/orc2020/pcvrh4/hlwu1w
title: LAD_table-Flocks_2.tab
DOI: 10.13021/orc2020/pcvrh4/pyzvio
title: FlockData.tab
DOI: 10.13021/orc2020/pcvrh4/klh3zy
title: FlockDataCorr.tab
DOI: 10.13021/orc2020/pcvrh4/rtdirv
title: FlockDataUse.tab
DOI: 10.13021/orc2020/pcvrh4/i5ubcs
title: Space Use Publication R Script.R
DOI: 10.13021/orc2020/pcvrh4/xicshd
title: ReadMe.txt
DOI: 10.13021/orc2020/pcvrh4/jopdcs
title: Flock Composition.tab
DOI: 10.13021/orc2020/pcvrh4
title: Amazonian mixed-species flocks demonstrate flexible preferences for vertical forest structure

description: These data were used for the study "Amazonian mixed-species flocks demonstrate flexible preferences for vertical forest structure". All necessary .csv files used to reproduce our statistical analyses and figures are included, as well as the R-script we used to generate them.
description: Our study is currently in review at Ecosphere.
DOI: 10.13021/orc2020/pcvrh4/oj282m
title: Coddington et al. Space Use R Script.R
DOI: 10.13021/orc2020/ewfejv/aom2rf
title: BandingDataPub.tab
DOI: 10.13021/orc2020/ewfejv/lrupxy
title: ReadMe.txt
DOI: 10.13021/orc2020/ewfejv/dwmmpr
title: Coddington et al. Breeding Declines.R
DOI: 10.13021/orc2020/ewfejv/9smsbo
title: BandingDataPub.tab
DOI: 10.13021/orc2020/ewfejv/gwxeus
title: Coddington et al. Breeding Declines Publication.R
DOI: 10.13021/orc2020/ewfejv/hdf9uw
title: README.txt
DOI: 10.13021/orc2020/ewfejv/ulixqm
title: nest ttest.tab
DOI: 10.13021/orc2020/0jl4of/dm2fzu
title: NEON-Structure_climate_productivity-master.tab
DOI: 10.13021/orc2020/ewfejv
title: Avian breeding activity declines after forest fragment isolation

description: These data were used for the study "Avian breeding activity declines after forest fragment isolation". All necessary .csv files used to reproduce our statistical analyses and figures are included, as well as the R-script we used to generate them.
DOI: 10.13021/orc2020/ewfejv/cryzll
title: diet ttest.tab
DOI: 10.13021/orc2020/0jl4of/qkoukq
title: NEON-Functional-Redundancy-b2.tab
DOI: 10.13021/orc2020/0jl4of/d3fe34
title: 2-StructureDataFromLidar.R
DOI: 10.13021/orc2020/0jl4of/iqbwa4
title: 5-mBoostModels.R
DOI: 10.13021/orc2020/0jl4of/qpvuox
title: 4-DiagnosticPlots.R
DOI: 10.13021/orc2020/0jl4of/sswhad
title: 3-FunctionaDiversityEstimates.R
DOI: 10.13021/orc2020/0jl4of/zqkewt
title: 1-DataDownload.R
DOI: 10.13021/orc2020/0jl4of/2rpo5g
title: brd_perpoint.tab
DOI: 10.13021/orc2020/0jl4of/hwle5f
title: 6-PredictivePlots.R
DOI: 10.13021/orc2020/0jl4of/iazgiq
title: cutlidrMetrics_fromDisks-NEON.R
DOI: 10.13021/orc2020/0jl4of/in4nvi
title: NEON-domainID-RegionName.tab
DOI: 10.13021/orc2020/0jl4of/suwlwi
title: NEON_Field_Site_Metadata_20201102.tab
DOI: 10.13021/orc2020/0jl4of/f5cq2m
title: NEON-siteForestType.tab
DOI: 10.13021/orc2020/0jl4of/lebuzd
title: NEON_pointData.tab
DOI: 10.13021/orc2020/0jl4of/sn6dop
title: NEONgamboost-b2_models.Rdata
DOI: 10.13021/orc2020/0jl4of/5xc2jt
title: 7-WhittakerPlots.R
DOI: 10.13021/orc2020/0jl4of/nibloh
title: NEON-FD-Bird_data-B2.tab
DOI: 10.13021/orc2020/0jl4of/g0l41o
title: Structure_metrics_table_over50.tab
DOI: 10.13021/orc2020/0jl4of/srtm8p
title: NEON-FDmodels-MasterTable.tab
DOI: 10.13021/orc2020/0jl4of/yeyj9u
title: NEON-FD-Trait_Data-B2.tab
DOI: 10.13021/orc2020/0jl4of/dpxbfp
title: NEON-Functional-Distinctiveness_b2.tab
DOI: 10.13021/orc2020/0jl4of/j5bi2k
title: ReadMe.rtf
DOI: 10.13021/orc2020/0jl4of/95dhoi
title: NEON-Structure_climate_productivity-master.tab
DOI: 10.13021/orc2020/0jl4of/qe5zqy
title: NEON-FD-Trait_Data-B2.tab
DOI: 10.13021/orc2020/0jl4of/2p63zh
title: NEON-FDmodels-MasterTable.tab
DOI: 10.13021/orc2020/0jl4of/duxnew
title: NEON-Functional-Redundancy-b2.tab
DOI: 10.13021/orc2020/0jl4of/ns4jpk
title: Structure_metrics_table_over50.tab
DOI: 10.13021/orc2020/0jl4of/09jdry
title: NEON-Functional-Distinctiveness_b2.tab
DOI: 10.13021/orc2020/0jl4of/do8liv
title: NEON-FD-Bird_data-B2.tab
DOI: 10.13021/orc2020/0jl4of/wvw0bt
title: 5.5-mboostModels-wFigs.R
DOI: 10.13021/orc2020/0jl4of/zji2hm
title: FunctionalDiversity_NEON_SelectionFreq.tab
DOI: 10.13021/orc2020/0jl4of/bghjqx
title: ReadMe.rtf
DOI: 10.13021/orc2020/0jl4of
title: Replication Data for: "Harmonizing spatial scales and ecological theories to predict avian richness and functional diversity within forest ecosystems"

description: This folder provides all necessary scripts and data files to replicate results in "Harmonizing spatial scales and ecological theories to predict avian richness and functional diversity within forest ecosystems." Please see the folder structure below for details on each folder and file. For ease of use, you may run any script file independently without regard to the order presented because all necessary data files are included in the 'Files' folder. The 'Files' folder contains tabular data for occurrence, climate, habitat heterogeneity, and productivity measures across the United States. These data were derived from data available from the National Ecological Observation Network. R scripts are included to download these data from https://www.neonscience.org/data. These data and the available scripts presented in 'NEON-R/R-Scripts' can be used to replicate models and figures estimating avian species richness and functional diversity and their relationship with forest structure along climatic gradients.
description: These data were updated in response to reviewer comments. Updates include subsetting NEON sites into independent models to better evaluate results at a finer scale than our North American scale model.
DOI: 10.13021/orc2020/0jl4of/jbs1dj
title: 2023_NEONgamboost-b2_models_wPartition_allFunct.tab