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Dataset Title:  Catch data conducted on hook and line along Pt. Lobos shore in California from
2007 to 2012.
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_712899)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | Data Access Form | Files
 
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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Year {
    Int16 _FillValue 32767;
    Int16 actual_range 2007, 2012;
    String description "Year of sampling";
    String ioos_category "Time";
    String long_name "Year";
    String units "unitless";
  }
  Month {
    String description "Month of sampling";
    String ioos_category "Time";
    String long_name "Month";
    String units "unitless";
  }
  Area {
    String description "Area of data collection; Pt. Lobos (PL)";
    String ioos_category "Unknown";
    String long_name "Area";
    String units "unitless";
  }
  Site {
    String description "Site type; Marine Protected Area (MPA) or Reference (REF)";
    String ioos_category "Unknown";
    String long_name "Site";
    String units "unitless";
  }
  Common_Name {
    String description "Species common name";
    String ioos_category "Taxonomy";
    String long_name "Common Name";
    String units "unitless";
  }
  Length {
    Byte _FillValue 127;
    Byte actual_range 7, 40;
    String description "Length of fish";
    String ioos_category "Unknown";
    String long_name "Length";
    String units "centimeters";
  }
  Depth_Released {
    Int16 _FillValue 32767;
    Int16 actual_range 35, 164;
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Depth of fish release";
    String ioos_category "Location";
    String long_name "Depth";
    String standard_name "depth";
    String units "meters";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"This dataset contains fish hook-and-line census data that were collected by
hook-and-line fishing in a cooperative data collection effort on fishing boats
offshore of Pt. Lobos California.\\u00a0Full\\u00a0description of details is
provided in Starr et al. (2015).";
    String awards_0_award_nid "542383";
    String awards_0_award_number "OCE-1435473";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1435473";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "Dr David  L. Garrison";
    String awards_0_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"Hook and line survey data 
  Collected by Rick Starr 
  J. W. White, M. Carr, and R. Starr, PIs 
  Version 4 August 2017";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.2d  13 Jun 2019";
    String date_created "2017-08-16T20:57:53Z";
    String date_modified "2019-03-20T15:19:02Z";
    String defaultDataQuery "&time";
    String doi "10.1575/1912/bco-dmo.712899.1";
    String history 
"2019-06-25T09:40:19Z (local files)
2019-06-25T09:40:19Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_712899.das";
    String infoUrl "https://www.bco-dmo.org/dataset/712899";
    String institution "BCO-DMO";
    String instruments_0_acronym "Hook and line";
    String instruments_0_dataset_instrument_description "Used to collect fish census data";
    String instruments_0_dataset_instrument_nid "712910";
    String instruments_0_description "A type of fishing methodology sometimes used to collect fish census data. It is a hook at the end of a line.";
    String instruments_0_instrument_name "Hook and line";
    String instruments_0_instrument_nid "712909";
    String instruments_0_supplied_name "Hook and line";
    String keywords "area, bco, bco-dmo, biological, chemical, common, Common_Name, data, dataset, depth, Depth_Released, dmo, erddap, length, management, month, name, oceanography, office, preliminary, site, taxonomy, time, year";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    String metadata_source "https://www.bco-dmo.org/api/dataset/712899";
    String param_mapping "{'712899': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/712899/parameters";
    String people_0_affiliation "Oregon State University";
    String people_0_affiliation_acronym "OSU";
    String people_0_person_name "J Wilson White";
    String people_0_person_nid "516429";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of California-Santa Cruz";
    String people_1_affiliation_acronym "UC Santa Cruz";
    String people_1_person_name "Mark Carr";
    String people_1_person_nid "51504";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Moss Landing Marine Laboratories";
    String people_2_affiliation_acronym "MLML";
    String people_2_person_name "Dr Rick Starr";
    String people_2_person_nid "712778";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "Oregon State University";
    String people_3_affiliation_acronym "OSU";
    String people_3_person_name "J Wilson White";
    String people_3_person_nid "516429";
    String people_3_role "Contact";
    String people_3_role_type "related";
    String people_4_affiliation "Woods Hole Oceanographic Institution";
    String people_4_affiliation_acronym "WHOI BCO-DMO";
    String people_4_person_name "Hannah Ake";
    String people_4_person_nid "650173";
    String people_4_role "BCO-DMO Data Manager";
    String people_4_role_type "related";
    String project "Impacts of size-selective mortality on sex-changing fishes";
    String projects_0_acronym "Goby size-selection";
    String projects_0_description 
"Description from NSF award abstract:
Many marine fish species change sex during their lifetimes, and many of them are targets of commercial and recreational fishing. The timing of sex change in these animals is often related to body size, so populations typically consist of many small fish of the initial sex (usually female) and few large fish of the other sex (usually male). In nature, smaller fish are at a greater risk of mortality due to predation, but fishermen tend to seek larger fish. Thus fishing that targets larger individuals may skew sex ratios, removing enough of the larger sex to hinder reproduction. However, the extent to which size-selective mortality affects sex-changing fishes is poorly understood. This research will explore the effects of size-selective mortality on the population dynamics of sex-changing species using an integrated set of field experiments and mathematical models. It will provide the first experimental exploration of the sensitivity of different sex-change patterns and reproductive strategies to selective mortality. The results will advance our knowledge of the susceptibility and resilience of sex-changing organisms to different types of size-selective mortality and will reveal how sex-changing species can recover after size-selection ceases, as in populations within marine reserves where fishing is suddenly prohibited. The findings will inform fisheries management policies, which do not currently consider the ability of a species to change sex in setting fisheries regulations.
This project will consist of a three-year study of the effects of size-specific mortality on sex-changing fishes. Field experiments will use three closely related rocky-reef fishes that differ in sex-change pattern and are amenable to field manipulation and direct measurement of reproductive output. The species include a protogynous hermaphrodite (a female-to-male sex-change pattern common among harvested species) and two simultaneous hermaphrodites that differ in their ability to switch between male and female. Two types of experiments will be conducted on populations established on replicate patch reefs at Santa Catalina Island, California: (1) sex ratios will be manipulated to determine when the scarcity of males limits population-level reproductive output; and (2) experiments cross-factoring the intensity of mortality with the form of size-selection (i.e., higher mortality of large or small individuals) will test the demographic consequences of size-selective mortality. In concert with the field experiments, size- and sex-structured population models (integral projection models) will be developed for use in three ways: (1) to evaluate how different types of selective mortality should affect population dynamics; (2) to predict outcomes of the field experiments, testing/validating the model and allowing direct prediction of the ecological significance of short-term selection; and (3) to fit to existing survey data for a fourth species, a widely fished, sex-changing fish, inside and outside of marine reserves. Part (3) will evaluate whether and how quickly the mating system and reproductive output of that species (not directly measurable in the field) is recovering inside reserves. This integrated set of field experiments and models will yield novel insight into the effects of size-selective mortality on the population dynamics of sex-changing marine species.";
    String projects_0_end_date "2018-02";
    String projects_0_geolocation "Southern California, Santa Catalina Island";
    String projects_0_name "Impacts of size-selective mortality on sex-changing fishes";
    String projects_0_project_nid "516431";
    String projects_0_start_date "2015-03";
    String publisher_name "Hannah Ake";
    String publisher_role "BCO-DMO Data Manager(s)";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v29";
    String subsetVariables "Area, Common_Name";
    String summary "Catch data conducted on hook and line along Pt. Lobos shore in California from 2007 to 2012.";
    String title "Catch data conducted on hook and line along Pt. Lobos shore in California from 2007 to 2012.";
    String version "1";
    String xml_source "osprey2erddap.update_xml() v1.5-beta";
  }
}

 

Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.


 
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