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Dataset Title:  Fish observations corresponding to one fish or a group of conspecific fish
taken in Point Lobos, California between 1997 and 2007.
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_712771)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | Files | Make a graph
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
   or a List of Values ?
   Maximum ?
 
 year (unitless) ?          1999    2014
 month (unitless) ?          7    11
 day (unitless) ?          3    30
 site (unitless) ?              
 campus (unitless) ?      
   - +  ?
 method (unitless) ?      
   - +  ?
 side (unitless) ?              
 zone (unitless) ?              
 level (unitless) ?              
 transect (unitless) ?          1    3
 classcode (unitless) ?              
 count (count) ?          1    229
 fish_tl (millimeters) ?          2.0    70.0
 min_tl (millimeters) ?          3    36
 max_tl (millimeters) ?          4    40
 observer (unitless) ?              
 depth_ (meters) ?          0.2    24.1
 vis (meters) ?          2.0    30.0
 temp (Temperature, degrees Celsius) ?          7.2    17.4
 surge (unitless) ?              
 windwave (unitless) ?              
 ptccnpy (percent) ?          0    3
 
Server-side Functions ?
 distinct() ?
? (" ")

File type: (more info)

(Documentation / Bypass this form ? )
 
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 1999, 2014;
    String description "Year of collection";
    String ioos_category "Time";
    String long_name "Year";
    String units "unitless";
  }
  month {
    Byte _FillValue 127;
    Byte actual_range 7, 11;
    String description "Month of collection";
    String ioos_category "Time";
    String long_name "Month";
    String units "unitless";
  }
  day {
    Byte _FillValue 127;
    Byte actual_range 3, 30;
    String description "Day of collection";
    String ioos_category "Time";
    String long_name "Day";
    String units "unitless";
  }
  site {
    String description "Site name";
    String ioos_category "Unknown";
    String long_name "Site";
    String units "unitless";
  }
  campus {
    String description "Group collecting the data; UCSC or UCSB";
    String ioos_category "Unknown";
    String long_name "Campus";
    String units "unitless";
  }
  method {
    String description "Survey method; SBTL_fish = subtidal visual surveys";
    String ioos_category "Unknown";
    String long_name "Method";
    String units "unitless";
  }
  side {
    String description "Side of site; East or West";
    String ioos_category "Unknown";
    String long_name "Side";
    String units "unitless";
  }
  zone {
    String description "Zone within side; inner outer etc.";
    String ioos_category "Unknown";
    String long_name "Zone";
    String units "unitless";
  }
  level {
    String description "Depth of survey; CAN = canopy; BOT = bottom; MID = midwater";
    String ioos_category "Unknown";
    String long_name "Level";
    String units "unitless";
  }
  transect {
    Byte _FillValue 127;
    Byte actual_range 1, 3;
    String description "Transect number";
    String ioos_category "Unknown";
    String long_name "Transect";
    String units "unitless";
  }
  classcode {
    String description "4-letter species code; NO_ORG = no organisms observed";
    String ioos_category "Unknown";
    String long_name "Classcode";
    String units "unitless";
  }
  count {
    Int16 _FillValue 32767;
    Int16 actual_range 1, 229;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "Number of fish observed";
    String ioos_category "Statistics";
    String long_name "Count";
    String units "count";
  }
  fish_tl {
    Float32 _FillValue NaN;
    Float32 actual_range 2.0, 70.0;
    String description "Total length of fish observed";
    String ioos_category "Unknown";
    String long_name "Fish Tl";
    String units "millimeters";
  }
  min_tl {
    Byte _FillValue 127;
    Byte actual_range 3, 36;
    String description "Minimum total length (if in a group)";
    String ioos_category "Unknown";
    String long_name "Min Tl";
    String units "millimeters";
  }
  max_tl {
    Byte _FillValue 127;
    Byte actual_range 4, 40;
    String description "Maximum total length (if in a group)";
    String ioos_category "Unknown";
    String long_name "Max Tl";
    String units "millimeters";
  }
  observer {
    String description "Name of observer";
    String ioos_category "Unknown";
    String long_name "Observer";
    String units "unitless";
  }
  depth_ {
    Float32 _FillValue NaN;
    Float32 actual_range 0.2, 24.1;
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Depth of transect";
    String ioos_category "Location";
    String long_name "Depth";
    String standard_name "depth";
    String units "meters";
  }
  vis {
    Float32 _FillValue NaN;
    Float32 actual_range 2.0, 30.0;
    String description "Visability on transect";
    String ioos_category "Unknown";
    String long_name "Vis";
    String units "meters";
  }
  temp {
    Float32 _FillValue NaN;
    Float32 actual_range 7.2, 17.4;
    String description "Temperature at transect";
    String ioos_category "Temperature";
    String long_name "Temperature";
    String units "degrees Celsius";
  }
  surge {
    String description "Qualitative description of surge";
    String ioos_category "Unknown";
    String long_name "Surge";
    String units "unitless";
  }
  windwave {
    String description "Qualitative description of wind and wave conditions";
    String ioos_category "Surface Waves";
    String long_name "Windwave";
    String units "unitless";
  }
  ptccnpy {
    Byte _FillValue 127;
    Byte actual_range 0, 3;
    String description "Relative kelp canopy cover; 0-3";
    String ioos_category "Unknown";
    String long_name "PTCCNPY";
    String units "percent";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Fish survey data were collected by\\u00a0underwater\\u00a0visual survey on
transects in kelp forests surrounding Pt. Lobos California from
1999-2007.\\u00a0Full\\u00a0description of details is provided in Appendix S1 of
White et al. (2016).";
    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 
"Observations of a fish or a group of conspecific fish 
  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 "2017-08-11T20:41:49Z";
    String date_modified "2019-03-20T15:38:24Z";
    String defaultDataQuery "&time";
    String doi "10.1575/1912/bco-dmo.712771.1";
    String history 
"2019-06-27T01:01:35Z (local files)
2019-06-27T01:01:35Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_712771.html";
    String infoUrl "https://www.bco-dmo.org/dataset/712771";
    String institution "BCO-DMO";
    String keywords "bco, bco-dmo, biological, campus, chemical, classcode, count, data, dataset, day, depth, dmo, erddap, fish, fish_tl, level, management, max, max_tl, method, min, min_tl, month, observer, oceanography, office, preliminary, ptccnpy, side, site, statistics, surface, surface waves, surge, temperature, time, transect, vis, waves, windwave, year, zone";
    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/712771";
    String param_mapping "{'712771': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/712771/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 "campus, method";
    String summary "Fish observations corresponding to one fish or a group of conspecific fish taken in Point Lobos, California between 1997 and 2007.";
    String title "Fish observations corresponding to one fish or a group of conspecific fish taken in Point Lobos, California between 1997 and 2007.";
    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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