cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5063/f18s4n5g
title: Subsistence and personal use harvest of salmon in Alaska, 1960-2012

description: Subsistence fishing is important for the economies and cultures of many families and communities in Alaska. Subsistence uses of wild resources exist alongside other important uses of fish and game in Alaska and are especially important for many rural families who depend on subsistence use for nutrition and traditional cultural practices. Subsistence use is defined as the noncommercial, customary harvest and processing of wild resources for food, raw materials, and other traditional uses. These customs have been a central part of the traditions of many cultural and tribal groups in Alaska for centuries. Today, subsistence and personal use fisheries are open only to Alaska residents that have been living in the state for at least one year. The Board of Fisheries (BOF) has the authority to adopt regulations governing the use of fish resources in Alaska. In order to regulate subsistence fisheries and ensure sustainability, the BOF is directed by Alaskan state law to identify fish stocks that are customarily and traditionally used for subsistence in Alaska. After customary and traditional use has been determined for a stock, the amount reasonably necessary for subsistence is set. Subsistence and personal use fisheries are managed under different regulations and thus regulations vary by fishery and location across the state. For example, only some fisheries require a permit issued by ADFG and some waters are closed to subsistence fishing, other fisheries have season, gear, and/or bag limit restrictions. Finfish other than salmon, rainbow trout, and steelhead trout may be taken for subsistence purposes at any time in any area of the state by any method unless restricted by the subsistence fishing regulations in the Alaska Admin Code. Salmon are more strictly regulated and the fisheries require permits, only allow certain gear types, and are restricted to certain waters in the state. This dataset includes information on subsistence salmon harvest from 1960-2012 across the entire state of Alaska. The csv file "ASFDB_FullPermit.csv" has been reformatted from the original excel file ("ASFDB_Full_PermitTypeDetail.xlsx"). This processing was done using the R Markdown file, "subsistence_harvest_processing.Rmd". Each entry is a report from a specific fishery and community in Alaska including permit type, resource type, year, and harvest (both reported and estimated). For each species, harvest data include both the number of fish and the edible weight in lbs (dressed, head off). See methods for additional data considerations.
DOI: 10.5063/f1dj5cws
title: Statewide Sport Fish Harvest Survey for effort, catch, and harvest estimates, Alaska, 1996-2016

description: The Sport Fish Division of the Alaska Department of Fish and Game conducts an annual mail survey to estimate sport fish harvest and catch by fisheries, areas, regions in which the fish were caught, and species. Obtaining these data provides decision-makers with the information needed to maintain, protect, and improve recreational fisheries.The survey was first implemented in 1977, capturing harvest only metrics, but was expanded to include harvest plus fish caught and released in 1990. The current version of the survey was last revised in 2011 and is now designed to capture guided and non-guided fishing activity throughout the state of Alaska. The Alaska Sport Fishing Survey database made data from 1996 to 2016 available through a query application. Prior years data have not been included in this dataset, but can be found in historic publications (https://www.adfg.alaska.gov/sf/sportfishingsurvey/index.cfm?ADFG=main.historic). In accordance with guidelines established by Mills and Howe, other than to document that sport fishing occurred, estimates based on fewer than 12 responses should not be used. Estimates based on 12 to 29 responses can be useful in indicating relative orders of magnitude and for assessing long-term trends. Estimates based on 30 or more responses are generally useable. More information about the survey is available at the Alaska Sport Fishing Survey webpage (http://www.adfg.alaska.gov/sf/sportfishingsurvey/). In this dataset is the original excel file, an R script that reformats this file, and 3 csv files derived from the original file. Also included are two ADFG reports, in pdf format, which explain how these data are gathered and processed by ADFG.
DOI: 10.5063/f1h993fp
title: Violations and Enforcement of Salmon Fishing Regulations, Alaska, 2014-2017

description: The Alaska Department of Public Safety, Division of Alaska Wildlife Troopers is tasked with patrolling a number of domains related to wildlife in Alaska. They provide statewide patrol of commercial big game services, commercial fisheries, sport fish and sport fish guiding, game hunting and trapping, boating safety, and habitat protection including permit compliance. The regulations which are enforced by the Alaska Wildlife Troopers (AWT) are outlined in the Alaska Administrative Code (AAC). As part of the State of Alaska Salmon and People Project, data on violations and enforcement of salmon-related regulations were gathered. These data provide useful insight into the governance and regulation of salmon fisheries in the state, including where violations occur and what the nature of those violations are. Patterns in violation numbers through time and space are not necessarily indicative of changing behavior of fishers through time or in different locations. There are many contributing factors that could lead to a change in the number of violations, the most important of which is the amount of time the AWT is able to patrol. A number of factors influence where and when the AWT conducts enforcement activities, including the number of personnel available, the annual budget, and guidance from other state departments such as the Alaska Department of Fish and Game. For this reason, included in this dataset is not only a list of salmon-related violations, but also contextual information on the staffing of the division. Important to note is although a certain number of positions are authorized each year in the division by the state legislature, for a variety of reasons not all of these positions are filled. When considering temporal trends in the number of violations, this is an important factor to consider, thus the AWT_troopers_positions_filled.csv includes information on the number of filled positions from 2013-2017 in the month of July for each of these years.
DOI: 10.5063/f1j964nz
title: State of Alaska's Salmon and People Regional Boundaries

description: This dataset depicts the boundaries of the State of Alaska's Salmon and People (SASAP) regions. The SASAP region boundaries were updated in 2017 to better reflect HUC 8 watershed boundaries and to repair gaps, overlaps, and other topological errors.
DOI: 10.5063/f1n29v6g
title: Summary of Pacific Salmon Escapement Goals in Alaska with a Review of Escapements from 2007 to 2015

description: This dataset is compiled from Tables 1-4 from the report "Summary of Pacific salmon escapement goals in Alaska with a review of escapements from 2007 to 2017." Escapement is defined as the number of mature salmon migrating from the marine environment to freshwater streams. Escapement data are the enumeration of these migrating fish as they pass upstream, and are a widely used index of spawning salmon abundance. These data are important for fisheries management, since most salmon harvest occurs in freshwater rivers during this migration. As a part of management of these salmon stocks, some Alaskan river systems are assigned escapement goals, which generally represent the number of salmon that need to be given the opportunity to spawn to ensure survival of the stock. Generally there are three common types of escapement goals. Biological Escapement Goals (BEGs) are defined in Alaska fishery regulations 5 AAC 39.222(f) as "the escapement that provides the greatest potential for maximum sustained yield." Sustainable Escapement Goals (SEGs) are defined in the same section as "a level of escapement, indicated by an index or an escapement estimate, that is known to provide for sustained yield over a 5 to 10 year period, used in situations where a BEG cannot be estimated or managed for." Optimal Escapement Goals (OEGs) are defined as "a specific management objective for salmon escapement that considers biological and allocative factors and may differ from the SEG or BEG."
DOI: 10.5063/f1p26wdr
title: Sockeye salmon brood tables, Washington, 1967-2011

description: Brood tables, also called run reconstructions, utilize annual estimates of the total run (commercial catch plus escapement), and samples of ages, to estimate the number of recruits per age class. These data are useful for salmon biologists to understand salmon productivity and salmon life histories. These data can come in a number of different formats, but generally follow the pattern of: rows for each brood year, and columns for the estimated number of fish in each age class. This dataset consists of reformatted sockeye salmon brood tables from Lake Washington. Age classes are given in European Notation, where the first number is the number of winters spent in freshwater before going to sea (1 winter in freshwater = age-1.X), and the second number is the number of winters spent at sea (3 winters at sea = age-X.3).
DOI: 10.5063/f1rv0kzg
title: Summary of Pacific Salmon Escapement Goals in Alaska with a Review of Escapements from 2001 to 2009

description: This dataset is compiled from Tables 1-4 from the report "Summary of Pacific salmon escapement goals in Alaska with a review of escapements from 2001 to 2009.” Escapement is defined as the number of mature salmon migrating from the marine environment to freshwater streams. Escapement data are the enumeration of these migrating fish as they pass upstream, and are a widely used index of spawning salmon abundance. These data are important for fisheries management, since most salmon harvest occurs in freshwater rivers during this migration. As a part of management of these salmon stocks, some Alaskan river systems are assigned escapement goals, which generally represent the number of salmon that need to be given the opportunity to spawn to ensure survival of the stock. Generally there are three common types of escapement goals. Biological Escapement Goals (BEGs) are defined in Alaska fishery regulations 5 AAC 39.222(f) as "the escapement that provides the greatest potential for maximum sustained yield." Sustainable Escapement Goals (SEGs) are defined in the same section as "a level of escapement, indicated by an index or an escapement estimate, that is known to provide for sustained yield over a 5 to 10 year period, used in situations where a BEG cannot be estimated or managed for." Optimal Escapement Goals (OEGs) are defined as "a specific management objective for salmon escapement that considers biological and allocative factors and may differ from the SEG or BEG."
DOI: 10.5063/f1st7n3q
title: Sockeye salmon brood tables, Upper Cook Inlet, Alaska, 1968-2016

description: Brood tables, also called run reconstructions, utilize annual estimates of the total run (commercial catch plus escapement), and samples of ages, to estimate the number of recruits per age class. These data are useful for salmon biologists to understand salmon productivity and salmon life histories. This dataset consists of original brood tables for sockeye salmon from the Kenai and Kasilof Rivers of the Upper Cook Inlet in excel format, R scripts that slightly reformat the dataset into a format consistent with other brood tables collected as part of the State of Alaskan Salmon and People project (https://alaskasalmonandpeople.org/), and the reformatted tables as a .csv file. Age classes are given in European Notation, where the first number is the number of winters spent in freshwater before going to sea (1 winter in freshwater = age-1.X), and the second number is the number of winters spent at sea (3 winters at sea = age-X.3).
DOI: 10.5063/f1wm1bp6
title: Summary data of subsistence salmon catch from in-season fish camp surveys, Lower Kuskokwim River, Alaska, 2009-2016

description: The Kuskokwim inseason subsistence catch monitoring project, a partnership between the Orutsararmiut Traditional Native Council (OTNC) and the Alaska Department of Fish and Game (ADF&G), seeks to provide local input from subsistence fisherman on salmon management during the fishing season (Fishery Management Report No. 16-06). Salmon are a highly important resource to residents of the Kuskokwim river drainage, and account for the majority of all wild resources consumed for subsistence in this watershed. The subsistence harvest monitoring program began in 2001, and as of 2004 has specifically centered on the Bethel area subsistence fishery. The OTNC surveys fish camps in the Bethel area every year in June and July for information about fishing activity, whether the camps are reaching their subsistence goals, what kind of fishing gear they are using, and relative run timing and fishing success compared to previous years. Certain data from these forms was redacted to ensure the exact location of the fish camps and families fishing there are kept confidential. Forms were transcribed in to tabular format for each weekly visit to a fish camp. These forms were then reformatted into the summary table, Fish_Camp_Summary_Table.csv. Additional information on project objectives, methods, and results can be found in the archived files ending in "...InseasonHarvestMonitoring.pdf". The files ending in "...infopacket.pdf" are weekly reports from the OTNC and Kuskokwim River Salmon Management Working Group, which contain data summaries, analyses, and comments from meetings that were held about each of the weekly surveys. The date listed in the file name is the date of the meeting for that weekly survey.
DOI: 10.5063/f1xk8csk
title: Sockeye salmon brood tables, PWS and Southeast, Alaska, 1958-2016

description: Brood tables, also called run reconstructions, utilize annual estimates of the total run (commercial catch plus escapement), and samples of ages, to estimate the number of recruits per age class. These data are useful for salmon biologists to understand salmon productivity and salmon life histories. This dataset consists of: original brood tables in excel format for sockeye salmon from Copper River, Coghill and Eshamy Lakes of Prince William Sound (PWS), and Chilkoot, Redoubt, and Speel Lakes of Southeast Alaska; R scripts that slightly reformat the dataset into a format consistent with other brood tables collected as part of the State of Alaskan Salmon and People project (https://alaskasalmonandpeople.org/); and the reformatted tables as .csv files. Age classes are given in European Notation, where the first number is the number of winters spent in freshwater before going to sea (1 winter in freshwater = age-1.X), and the second number is the number of winters spent at sea (3 winters at sea = age-X.3).
DOI: 10.5281/zenodo.2530899
title: Improve your Galaxy text life: The Query Tabular Tool

description: Sample PSM input file for metaproteomics galaxy workflow to describe Query Tabular tool
DOI: 10.6073/pasta/f80007221fd839a2ca057b8297450e56
title: Black Sand pilot experiment for speeding snowmelt on Niwot Ridge for summer 2015

description: We piloted using black sand as a method for speeding snowmelt on Niwot
  Ridge in the summer of 2015. At each of two sites (Trough and Tvan),
  two 2x2 m plots were set up and two 3x3m plots were set up, with one
  of each size plot receiving 600 g/m2 black sand and one receiving 800
  g/m2 of black sand. The sand treatments sped snowmelt by 6-9 days.
  Initially, soil moisture appeared to be slightly lower in the sand
  plots and soil temperature appeared to be slightly higher, but these
  effects disappeared by July.
DOI: 10.17632/7n5f3txs76.1
title: Data for: The geologic record of the exhumed root of the Central African Orogenic Belt in the Central Cameroon Domain (Mbé - Sassa-Mbersi region)

description: Geochemical and geochronological data
DOI: 10.5517/ccdc.csd.cc10j8ld
title: CCDC 939163: Experimental Crystal Structure Determination

description: Related Article: Monika Asztemborska, Magdalena Ceborska, Mariusz Pietrzak|2019|Carbohydrate Polymers|209|74|doi:10.1016/j.carbpol.2019.01.011
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2015s1
title: CCDC 1848182: Experimental Crystal Structure Determination

description: Related Article: Yachun Ma, Junjun Sun, Chen Li, Nan Li, Pengtao Ma, Dongdi Zhang, Guan Wang, Jingyang Niu|2019|Inorg.Chem.Commun.|101|6|doi:10.1016/j.inoche.2019.01.004
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2015t2
title: CCDC 1848183: Experimental Crystal Structure Determination

description: Related Article: Yachun Ma, Junjun Sun, Chen Li, Nan Li, Pengtao Ma, Dongdi Zhang, Guan Wang, Jingyang Niu|2019|Inorg.Chem.Commun.|101|6|doi:10.1016/j.inoche.2019.01.004
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc205bp7
title: CCDC 1852178: Experimental Crystal Structure Determination

description: Related Article: Anthony R. Leverett, Marcus L. Cole, Alasdair I. McKay|2019|Dalton Trans.|48|1591|doi:10.1039/C8DT04956D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc205bq8
title: CCDC 1852179: Experimental Crystal Structure Determination

description: Related Article: Anthony R. Leverett, Marcus L. Cole, Alasdair I. McKay|2019|Dalton Trans.|48|1591|doi:10.1039/C8DT04956D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc205br9
title: CCDC 1852180: Experimental Crystal Structure Determination

description: Related Article: Anthony R. Leverett, Marcus L. Cole, Alasdair I. McKay|2019|Dalton Trans.|48|1591|doi:10.1039/C8DT04956D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc20c03j
title: CCDC 1857616: Experimental Crystal Structure Determination

description: Related Article: Manisha Das, Zeenat Afsan, Dipmalya Basak, Farukh Arjmand, Debashis Ray|2019|Dalton Trans.|48|1292|doi:10.1039/C8DT04183K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc20fk12
title: CCDC 1860063: Experimental Crystal Structure Determination

description: Related Article: Kun-Quan Chen, Zhong-Hua Gao, Song Ye|2019|Org.Chem.Front.|6|405|doi:10.1039/C8QO01302K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc20gxcs
title: CCDC 1861375: Experimental Crystal Structure Determination

description: Related Article: Danijela Cvijanović, Jana Pisk, Gordana Pavlović, Dubravka Šišak-Jung, Dubravka Matković-Čalogović, Marina Cindrić, Dominique Agustin, Višnja Vrdoljak|2019|New J.Chem.|43|1791|doi:10.1039/C8NJ04074E
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.