cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19672968
title: Diosmetin attenuates oxidative stress-induced damage to lens epithelial cells via the mitogen-activated protein kinase (MAPK) pathway

description: Cataract is a global ophthalmic disease that blinds the eye, and oxidative stress is one of its primary causes. Apoptosis of lens epithelial cells (LECs) is considered the major cytological basis of many cataracts except congenital cataracts. The purpose of this study was to investigate whether diosmetin could reduce oxidative stress-induced damage to LECs, and explore its regulatory pathway. Lens epithelial cell line SRA01/04 was used as the object of study. Using ultraviolet B (UVB) and hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>) as sources of oxidative stress, the protective effects of diosmetin at different concentrations on cells were investigated, including inhibition of proliferation, apoptosis, and oxidative stress. Molecular docking was then used to predict the target proteins and validation was performed at the cellular and protein levels. The oxidative stress of SRA01/04 was induced by UVB and H<sub>2</sub>O<sub>2</sub>, and inhibition of proliferation and apoptosis were observed. Here, diosmetin has a dose-dependent cell-protecting effect. This effect is achieved by targeting the MEK2 protein and inhibiting the MAPK signaling. In conclusion, diosmetin reduces H<sub>2</sub>O<sub>2</sub>- and UVB-induced inhibition of SRA01/04 proliferation and apoptosis by reducing oxidative stress-induced activation of the MAPK pathway.
DOI: 10.5281/zenodo.6500450
title: Electron Accepting Capacities of a wide variety of peat materials from around the Globe similarly explain CO2 and CH4 production

description: In peat soils the availability of terminal electron acceptors (TEAs), both inorganic and organic, largely determines the ratio of carbon dioxide to methane formation under waterlogged, anoxic conditions. The redox properties of peat organic matter and their relationship with anoxic carbon mineralization are yet only investigated for a limited amount of peat and reference materials, although electron accepting capacities of organic matter (EACOM) largely predominate over canonical inorganic TEAs in peatlands. To address this knowledge gap, we incubated 60 peat samples from four different depths of 15 sites located in five major peatland regions (including Germany, Sweden, Russia, France and Chile) distributed around the globe covering a variety of both bog and fen type samples and characterized their capacities to serve as electron acceptors for anaerobic carbon dioxide production.<br> The dataset consists of a wide variety of recorded and calculated variables for a 56-day incubation of those samples. These variables include the formation and rates of methane, carbon dioxide, electron acceptor capacities and electron donator capacities at two different times, data on stable isotopes in delta notation (such as nitrogen, carbon and sulfur), molar element ratios for carbon/nitrogen, carbon/sulfur and nitrogen/phosphorus and elemental contents like silicon, phosphorus, sulfur, calcium and iron as well as specific fourier transformed infrared spectroscopy ratios regarding the ratios of polysaccharides and aromatic structures. The dataset was created mostly in 2019, with some additional measurements carried out in 2020 and 2021.
description: This study was supported by the German Research Foundation (Deutsche Forschungsgemeinschaft DFG), grant no. KN 929/12-1 to K.-H. Knorr. Chuanyu Gao was also supported by the Chinese Scholarship Council (Nr. 201504910782).
DOI: 10.5281/zenodo.6500449
title: Electron Accepting Capacities of a wide variety of peat materials from around the Globe similarly explain CO2 and CH4 production

description: In peat soils the availability of terminal electron acceptors (TEAs), both inorganic and organic, largely determines the ratio of carbon dioxide to methane formation under waterlogged, anoxic conditions. The redox properties of peat organic matter and their relationship with anoxic carbon mineralization are yet only investigated for a limited amount of peat and reference materials, although electron accepting capacities of organic matter (EACOM) largely predominate over canonical inorganic TEAs in peatlands. To address this knowledge gap, we incubated 60 peat samples from four different depths of 15 sites located in five major peatland regions (including Germany, Sweden, Russia, France and Chile) distributed around the globe covering a variety of both bog and fen type samples and characterized their capacities to serve as electron acceptors for anaerobic carbon dioxide production.<br> The dataset consists of a wide variety of recorded and calculated variables for a 56-day incubation of those samples. These variables include the formation and rates of methane, carbon dioxide, electron acceptor capacities and electron donator capacities at two different times, data on stable isotopes in delta notation (such as nitrogen, carbon and sulfur), molar element ratios for carbon/nitrogen, carbon/sulfur and nitrogen/phosphorus and elemental contents like silicon, phosphorus, sulfur, calcium and iron as well as specific fourier transformed infrared spectroscopy ratios regarding the ratios of polysaccharides and aromatic structures. The dataset was created mostly in 2019, with some additional measurements carried out in 2020 and 2021.
description: This study was supported by the German Research Foundation (Deutsche Forschungsgemeinschaft DFG), grant no. KN 929/12-1 to K.-H. Knorr. Chuanyu Gao was also supported by the Chinese Scholarship Council (Nr. 201504910782).
DOI: 10.5517/ccdc.csd.cc296y0h
title: CCDC 2121826: Experimental Crystal Structure Determination

description: Related Article: O.A. Kizas, S.K. Moiseev, I.S. Chaschin, I.A. Godovikov, F.M. Dolgushin, A.R. Khokhlov|2022|J.Organomet.Chem.|968-969|122358|doi:10.1016/j.jorganchem.2022.122358
DOI: 10.5517/ccdc.csd.cc29cl1b
title: CCDC 2126291: Experimental Crystal Structure Determination

description: Related Article: Chun-Mei Xu, Shuang-Long Wang, Wen-Li Yuan, Lei Zhang, Hangyu Liu, Guo-Hong Tao, Ling He|2022|J.Mol.Struct.|1262|133099|doi:10.1016/j.molstruc.2022.133099
DOI: 10.6084/m9.figshare.19661115
title: Artificial intelligence for Ionospheric DEtections (AIDE): dataset and trained detection models

description: Dataset and trained detection models used in paper: "Near-real-time automatic detection of co-seismic ionospheric disturbances using machine learning" in Geophysical Jounral International, 2022 (https://doi.org/10.1093/gji/ggac167)
DOI: 10.5281/zenodo.6501494
title: Mock Ceramics Dataset

description: This is an adaptation of the 'portal_data_joined.csv' and 'portal_mammals.sqlite' datasets as cited below. The data has been modified with mock values to represent data about ceramics, for use in a Data Carpentry course to teach R to Archaeologists. The data is not real and may not make sense! <strong>portal_mammals.sqlite</strong> Ernest, Morgan; Brown, James; Valone, Thomas; White, Ethan P. (2018): Portal Project Teaching Database. figshare. Dataset. https://doi.org/10.6084/m9.figshare.1314459.v10 <strong>portal_data_joined.csv</strong> Chiapello, Marco (2020): Datasets. figshare. Dataset. https://doi.org/10.6084/m9.figshare.8336996.v1
description: {"references": ["Chiapello, Marco (2020): Datasets. figshare. Dataset. https://doi.org/10.6084/m9.figshare.8336996.v1", "Ernest, Morgan; Brown, James; Valone, Thomas; White, Ethan P. (2018): Portal Project Teaching Database. figshare. Dataset. https://doi.org/10.6084/m9.figshare.1314459.v10"]}
DOI: 10.24341/tethys.182
title: Geodaten - Blatt 114 Holzgau (1:50.000)
title: Geodata - sheet 114 Holzgau (1:50,000)

description: Die Geodaten wurden aus dem Kartenwerk GK50 „Geologische Karte der Republik Österreich 1:50.000“ abgeleitet. Die Datengrundlage basiert auf einer umfassenden Datenerhebung im Rahmen der gesetzlich verankerten geologischen Landesaufnahme von Österreich, welche eine umfangreiche Literaturrecherche, die Geländekartierung, sowie die Probenahme mit wissenschaftlichen Analysen und Messungen beinhaltet. Die im BMN-Blattschnitt veröffentlichten Geodaten entsprechen dem aktuellen Wissensstand zum Zeitpunkt des Kartendruckes und können geringfügig von den Originalen abweichen.
description: The geodata were derived from the corresponding printed map sheet series “Geological Map of Austria 1:50.000”. The dataset is based on a comprehensive collection of geological data in the Division of Geological Mapping at the Geological Survey of Austria including extensive literature research, geological mapping and scientific research on rock samples. The geodata are published in the BMN-map sheet layout and correspond to the current state of knowledge at the time of the map printing. The published data may slightly deviate of the originals due to e.g. error correction (typos).
description: Die vorliegende Datenpublikation ist ein Bestandteil der Kartenserie „Geologische Karte der Republik Österreich 1:50.000“ (GK50). Eine ausführliche Datenbeschreibung wird mit den Kartendaten bereitgestellt und kann direkt zu jeder Publikation heruntergeladen werden.
description: This data publication is part of the map series "Geological Map of the Republic of Austria 1:50.000" (GK50). A detailed data description is provided with the map data and can be downloaded together with the data publication.
DOI: 10.5258/soton/d2103
title: Dataset for: Short single-frequency self-pulsing Brillouin-Raman distributed feedback fiber laser

description: Dataset for the paper: 'Short single-frequency self-pulsing Brillouin-Raman distributed feedback fiber laser' accepted in Optics Express. Dataset contains raw data for all the optical/eletronic spectra and oscioscope graphs presented in the paper.
DOI: 10.34934/dvn/lsxxzv
title: Sub-state Autonomy Scale (SAS)

description: This dataset comprises the data collected for the Sub-state Autonomy Scale (SAS). The SAS is an indicator measuring the autonomy demands and statutes of sub-state communities in kind (whether competences are administrative or legislative), in degree (how much each dimension is present) and by competences (as a function of the extent of comprised policy domains). Definitions: -By 'sub-state community', I refer to sub-state entities within countries for which autonomous institutions have been demanded by a significant regionalist or traditional (centrist, liberal or socialist main-stream) political party (&gt;5%) or to which autonomous institutions have been conferred. -By 'autonomy statutes', I refer to the legal autonomy prerogatives obtained by sub-state communities. -For 'autonomy demands', I distinguish between the legal autonomy prerogatives demanded by the regionalist party with the highest vote share and those demanded by the traditional party with the largest autonomy demand. Detailed conceptual presentation: see the Regional Studies article cited below (the open access author version can be found in the files section). Specifications: -Unit of analysis: sub-state communities by yearly intervals. -Country coverage: Belgium, Spain, United Kingdom (31 sub-state communities). -Time coverage: 1707-2020 (starting dates vary across sub-state communities). *For the full list of sub-state communities and their respective time coverage, see the codebook. Citation and acknowledgement: when using the data, please cite the Regional Studies article listed below. Latest version: 1.0 [01.02.2022].
DOI: 10.5258/soton/d2169
title: Additional Computational Data to support the University of Southampton Doctoral thesis, "Computational Screening of Small-Molecule Organic Semiconductors"

description: The dataset contains csv. and excel files zipped into a tar.gz file which underpin the Predicted crystal structures and calculated properties.
DOI: 10.6084/m9.figshare.17261480
title: SEOSS-Queries

description: Stakeholders of software development projects have various information needs for making rational decisions during their daily work. Satisfying these needs requires substantial knowledge of where and how the relevant information is stored and consumes valuable time that is often not available. Easing the need for this knowledge is an ideal text-to-SQL benchmark problem, a field where public datasets are scarce and needed. We propose the SEOSS-Queries dataset consisting of natural language utterances and accompanying SQL queries extracted from previous studies, software projects, issue tracking tools, and through expert surveys to cover a large variety of information need perspectives. Our dataset consists of 1,162 English utterances translating into 166 SQL queries; each query has four precise utterances and three more general ones. Furthermore, the dataset contains 393,086 classified utterances extracted from issue tracker comments. We provide pre-trained SQLNet and RatSQL baseline models for benchmark comparisons, a replication package facilitating a seamless application, and discuss various other tasks that may be solved and evaluated using the dataset
DOI: 10.34740/kaggle/dsv/3543724
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.6499687
title: 5.0 EVALUATING CHANGES IN TRANSIT ACCESSIBILITY FOR TRANSPORTATION-DISADVANTAGED POPULATIONS IN THE CITY OF GAINESVILLE

description: This dataset contains four parts: 1. A geodatabase of street network in Alachua County ; 2. Shapefiles of places (hospitals, parks, schools, etc.) in Florida that were defined as "trip destinations" in our research; 3. GTFS (General Transit Feed Specification) data used to developed different transit service scenarios; 4. Data of the transit service scenarios that we developed.
DOI: 10.5281/zenodo.6499686
title: 5.0 EVALUATING CHANGES IN TRANSIT ACCESSIBILITY FOR TRANSPORTATION-DISADVANTAGED POPULATIONS IN THE CITY OF GAINESVILLE

description: This dataset contains four parts: 1. A geodatabase of street network in Alachua County ; 2. Shapefiles of places (hospitals, parks, schools, etc.) in Florida that were defined as "trip destinations" in our research; 3. GTFS (General Transit Feed Specification) data used to developed different transit service scenarios; 4. Data of the transit service scenarios that we developed.
DOI: 10.14272/ztjnwvohdvhtnz-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (N-[2-[2-[2-(2-azidoethoxy)ethoxy]ethoxy]ethyl]-4-nitro-2,1,3-benzoxadiazol-7-amine)
title: InChI=1S/C14H19N7O6/c15-20-17-4-6-25-8-10-26-9-7-24-5-3-16-11-1-2-12(21(22)23)14-13(11)18-27-19-14/h1-2,16H,3-10H2

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (500 MHz, CDCl3, ppm) δ = 8.52 (d, J = 8.6 Hz, 1H), 7.03 (br, 1H), 6.21 (d, J = 8.6 Hz, 1H), 3.93–3.88 (t, J = 4.8 Hz, 2H), 3.74 (s, 12H), 3.44–3.39 (t, J = 4.8 Hz, 2H).
DOI: 10.14272/ztjnwvohdvhtnz-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (N-[2-[2-[2-(2-azidoethoxy)ethoxy]ethoxy]ethyl]-4-nitro-2,1,3-benzoxadiazol-7-amine)
title: InChI=1S/C14H19N7O6/c15-20-17-4-6-25-8-10-26-9-7-24-5-3-16-11-1-2-12(21(22)23)14-13(11)18-27-19-14/h1-2,16H,3-10H2

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (126 MHz, CDCl3, ppm) δ = 144.5, 144.3, 144.1, 136.6, 124.2, 98.8, 70.9, 70.9, 70.8, 70.7, 70.2, 68.3, 50.8, 43.9.
DOI: 10.14272/ztjnwvohdvhtnz-uhfffaoysa-n.1
title: N-[2-[2-[2-(2-azidoethoxy)ethoxy]ethoxy]ethyl]-4-nitro-2,1,3-benzoxadiazol-7-amine
title: InChI=1S/C14H19N7O6/c15-20-17-4-6-25-8-10-26-9-7-24-5-3-16-11-1-2-12(21(22)23)14-13(11)18-27-19-14/h1-2,16H,3-10H2

description: This dataset contains experimental data from a sample (N-[2-[2-[2-(2-azidoethoxy)ethoxy]ethoxy]ethyl]-4-nitro-2,1,3-benzoxadiazol-7-amine, InChI=1S/C14H19N7O6/c15-20-17-4-6-25-8-10-26-9-7-24-5-3-16-11-1-2-12(21(22)23)14-13(11)18-27-19-14/h1-2,16H,3-10H2). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR) mass spectrometry (MS)
DOI: 10.14272/ztjnwvohdvhtnz-uhfffaoysa-n/chmo0000470
title: mass spectrometry (MS) (N-[2-[2-[2-(2-azidoethoxy)ethoxy]ethoxy]ethyl]-4-nitro-2,1,3-benzoxadiazol-7-amine)
title: InChI=1S/C14H19N7O6/c15-20-17-4-6-25-8-10-26-9-7-24-5-3-16-11-1-2-12(21(22)23)14-13(11)18-27-19-14/h1-2,16H,3-10H2

description: dataset for mass spectrometry (MS) ESI-MS: Calcd. For [M+Na]+: 404.1289; found: 404.1337.
DOI: 10.5517/ccdc.csd.cc29jpl4
title: CCDC 2131206: Experimental Crystal Structure Determination

description: Related Article: O.A. Kizas, S.K. Moiseev, I.S. Chaschin, I.A. Godovikov, F.M. Dolgushin, A.R. Khokhlov|2022|J.Organomet.Chem.|968-969|122358|doi:10.1016/j.jorganchem.2022.122358
DOI: 10.5517/ccdc.csd.cc29jpm5
title: CCDC 2131207: Experimental Crystal Structure Determination

description: Related Article: O.A. Kizas, S.K. Moiseev, I.S. Chaschin, I.A. Godovikov, F.M. Dolgushin, A.R. Khokhlov|2022|J.Organomet.Chem.|968-969|122358|doi:10.1016/j.jorganchem.2022.122358
DOI: 10.5517/ccdc.csd.cc29jpn6
title: CCDC 2131208: Experimental Crystal Structure Determination

description: Related Article: O.A. Kizas, S.K. Moiseev, I.S. Chaschin, I.A. Godovikov, F.M. Dolgushin, A.R. Khokhlov|2022|J.Organomet.Chem.|968-969|122358|doi:10.1016/j.jorganchem.2022.122358
DOI: 10.5517/ccdc.csd.cc29cl09
title: CCDC 2126290: Experimental Crystal Structure Determination

description: Related Article: Chun-Mei Xu, Shuang-Long Wang, Wen-Li Yuan, Lei Zhang, Hangyu Liu, Guo-Hong Tao, Ling He|2022|J.Mol.Struct.|1262|133099|doi:10.1016/j.molstruc.2022.133099
DOI: 10.5517/ccdc.csd.cc2bkfgt
title: CCDC 2161706: Experimental Crystal Structure Determination

description: Related Article: T. Kornilova, V. Glebov, R. Castañeda, T.V. Timofeeva|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|468|doi:10.1107/S2056989022003309
DOI: 10.5517/ccdc.csd.cc2bkmk3
title: CCDC 2161895: Experimental Crystal Structure Determination

description: Related Article: K. Kubono, K. Tani, Y. Kashiwagi, F. Tani, T. Matsumoto|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|477|doi:10.1107/S2056989022003383
DOI: 10.5517/ccdc.csd.cc2bl2mn
title: CCDC 2162331: Experimental Crystal Structure Determination

description: Related Article: C. Kachi-Terajima, S. Hagiwara|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|473|doi:10.1107/S2056989022003437
DOI: 10.5517/ccdc.csd.cc2bly41
title: CCDC 2163153: Experimental Crystal Structure Determination

description: Related Article: M. Varisco, A. Crochet, O. Mamula Steiner|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|464|doi:10.1107/S2056989022003589
DOI: 10.5517/ccdc.csd.cc2bn78j
title: CCDC 2164397: Experimental Crystal Structure Determination

description: Related Article: M. Bookwala, S. Patel, P.T. Flaherty, P.L.D. Wildfong|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|485|doi:10.1107/S2056989022003723
DOI: 10.5517/ccdc.csd.cc2bnfs7
title: CCDC 2164599: Experimental Crystal Structure Determination

description: Related Article: C. Näther, F. Danker, W. Bensch|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|490|doi:10.1107/S2056989022003759
DOI: 10.5517/ccdc.csd.cc2bnn4t
title: CCDC 2164796: Experimental Crystal Structure Determination

description: Related Article: V.V. Rudiuk, A.M. Shaposhnik, V.M. Baumer, I.A. Levandovskiy, S.V. Shishkina|2022|Acta Crystallogr.,Sect.E:Cryst.Commun.|78|496|doi:10.1107/S2056989022003784
DOI: 10.5519/qd.juhsv5sr
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (3242 records)
DOI: 10.5281/zenodo.6501580
title: Alpine and subalpine vegetation of Mt. Midzhur, Stara Planina, Bulgaria

description: This dataset contains data used in my diploma thesis. The fieldwork was carried out in the Western Stara Planina Mountains, mainly in the area of Mt. Midzhur. I recorded 78 vegetation plots using the Braun-Blanquet approach. The dataset was classified using modified Twinspan algorithm. A DCA ordination graph was created to present the dissimilarity of the vegetation types. The vegetation was divided into 12 classes. Seven alliances not previously known from Bulgaria and one newly described alliance of subalpine tall-herb vegetation on screes were reported. Numerous associations were newly reported for Bulgaria or were newly described. The role of altitude and soil pH on the vegetation was analyzed using the general linear model; the floristic composition was analyzed on the level of floristic elements.
DOI: 10.5281/zenodo.6459294
title: Alpine and subalpine vegetation of Mt. Midzhur, Stara Planina, Bulgaria

description: This dataset contains data used in my diploma thesis. The fieldwork was carried out in the Western Stara Planina Mountains, mainly in the area of Mt. Midzhur. I recorded 78 vegetation plots using the Braun-Blanquet approach. The dataset was classified using modified Twinspan algorithm. A DCA ordination graph was created to present the dissimilarity of the vegetation types. The vegetation was divided into 12 classes. Seven alliances not previously known from Bulgaria and one newly described alliance of subalpine tall-herb vegetation on screes were reported. Numerous associations were newly reported for Bulgaria or were newly described. The role of altitude and soil pH on the vegetation was analyzed using the general linear model; the floristic composition was analyzed on the level of floristic elements.
DOI: 10.34740/kaggle/dsv/3543786
title: 2021 World Population (updated daily)
DOI: 10.5281/zenodo.6501593
title: Mock Ceramics Dataset

description: This is an adaptation of SQLite and CSV files from the Portal Project Teaching Database, and of 'portal_data_joined.csv' created by Marco Chiapello. The data has been modified with mock values to represent data about ceramics, for use in a Data Carpentry course to teach R to Archaeologists. The data is not real and may not make sense! <strong>Portal Project Teaching Database</strong> Ernest, Morgan; Brown, James; Valone, Thomas; White, Ethan P. (2018): Portal Project Teaching Database. figshare. Dataset. https://doi.org/10.6084/m9.figshare.1314459.v10 <strong>portal_data_joined.csv</strong> Chiapello, Marco (2020): Datasets. figshare. Dataset. https://doi.org/10.6084/m9.figshare.8336996.v1
description: {"references": ["Chiapello, Marco (2020): Datasets. figshare. Dataset. https://doi.org/10.6084/m9.figshare.8336996.v1", "Ernest, Morgan; Brown, James; Valone, Thomas; White, Ethan P. (2018): Portal Project Teaching Database. figshare. Dataset. https://doi.org/10.6084/m9.figshare.1314459.v10"]}
DOI: 10.5281/zenodo.6478180
title: Mock Ceramics Dataset

description: This is an adaptation of SQLite and CSV files from the Portal Project Teaching Database, and of 'portal_data_joined.csv' created by Marco Chiapello. The data has been modified with mock values to represent data about ceramics, for use in a Data Carpentry course to teach R to Archaeologists. The data is not real and may not make sense! <strong>Portal Project Teaching Database</strong> Ernest, Morgan; Brown, James; Valone, Thomas; White, Ethan P. (2018): Portal Project Teaching Database. figshare. Dataset. https://doi.org/10.6084/m9.figshare.1314459.v10 <strong>portal_data_joined.csv</strong> Chiapello, Marco (2020): Datasets. figshare. Dataset. https://doi.org/10.6084/m9.figshare.8336996.v1
description: {"references": ["Chiapello, Marco (2020): Datasets. figshare. Dataset. https://doi.org/10.6084/m9.figshare.8336996.v1", "Ernest, Morgan; Brown, James; Valone, Thomas; White, Ethan P. (2018): Portal Project Teaching Database. figshare. Dataset. https://doi.org/10.6084/m9.figshare.1314459.v10"]}
DOI: 10.7298/vg3t-8d62
title: Social Safety Net Index
DOI: 10.5066/p93y0ms0
title: Hawaii Island Kohala Mountain complex forest bird survey, 2017

description: This data release contains the point-transect distance sampling records of forest bird survey collected in the Kohala Mountain complex in 2017, including survey point IDs, distance to detected birds, sampling conditions, ohia phenology, habitat classifications and background noise levels. This data release consists of one tabular dataset.