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Dataset Title:  Home range and body size data compiled from the literature for marine and
terrestrial vertebrates
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_752795)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | 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 {
  System {
    String bcodmo_name "brief_desc";
    String description "System (Marine or Terrestrial)";
    String long_name "System";
    String units "unitless";
  }
  Group {
    String bcodmo_name "brief_desc";
    String description "Group (M = Mammals, B = Birds, R = Reptiles, F = Fishes)";
    String long_name "Group";
    String units "unitless";
  }
  Species {
    String bcodmo_name "taxon";
    String description "Species name from literature";
    String long_name "Species";
    String units "unitless";
  }
  BM {
    Int32 _FillValue 2147483647;
    Int32 actual_range 1, 79691179;
    String bcodmo_name "weight";
    String description "Body mass";
    String long_name "BM";
    String units "grams (g)";
  }
  HR {
    Float32 _FillValue NaN;
    Float32 actual_range 1.0e-6, 2605360.0;
    String bcodmo_name "range";
    String description "Home range";
    String long_name "HR";
    String units "square kilometers (km^2)";
  }
  Refs {
    String bcodmo_name "unknown";
    String description "Reference identification number for resources used for home range data. Any numbers that follow semi-colons were used for body mass data. References associated with these numbers can be found in the supplemental document \"McCauley_et_al_2015_references.pdf.\"";
    String long_name "Refs";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"We compiled the home range size of a representative selection of adult marine
and terrestrial vertebrates: seabirds (n = 19), marine reptiles (n = 6),
marine fishes (n = 20), marine mammals (n = 22), terrestrial birds (n = 95),
terrestrial reptiles (n = 65), and terrestrial mammals (n = 616). We only
accepted home range estimates that described > 75% of an adult individual's
total utilized area. Home range sizes in our compilation were estimated by
authors using a variety of analytical techniques, including kernel utilization
distributions, minimum convex polygon estimates, and geometric estimation
techniques. We primarily accepted studies that used satellite, radio, or
acoustic telemetry to obtain data for home range size estimation, though
estimates produced from visual observations were accepted if a species' home
range was small enough that the author could accurately describe it in its
entirety without issue (e.g., the 1.3x10-5 km2 home range of the 2 g lizard
Anolis distichus). If multiple home range estimates meeting these criteria
were available from different studies on the same species, we averaged these
values. Likewise, we averaged values for different groups of individuals
within a species (e.g., sexes) if these values were reported in a single
study. Data on the adult body mass of all species included in the home range
dataset were preferentially drawn from the primary literature source from
which home range data were taken. If body mass data were not available in
these sources, they were collected from alternate databases or from peer-
reviewed publications.
 
Scientific names in this dataset were obtained from literature and include
some misspelled names and unaccepted synonyms. These names were matched to
species in several authoritative name sources. Taxonomic identifiers and match
quality results can be found in the supplemental document \"Species Name Match
Results.\"";
    String awards_0_award_nid "559955";
    String awards_0_award_number "OCE-1426891";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1426891";
    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 "Michael E. Sieracki";
    String awards_0_program_manager_nid "50446";
    String cdm_data_type "Other";
    String comment 
"Vertebrate home range and body size 
  PI: Malin Pinsky 
  Data version 1: 2019-01-31";
    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 2.3  19 Dec 2019";
    String date_created "2019-01-16T14:10:50Z";
    String date_modified "2019-03-26T19:17:02Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.752795.1";
    String history 
"2022-08-16T05:02:40Z (local files)
2022-08-16T05:02:40Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_752795.das";
    String infoUrl "https://www.bco-dmo.org/dataset/752795";
    String institution "BCO-DMO";
    String keywords "bco, bco-dmo, biological, chemical, data, dataset, dmo, erddap, group, management, oceanography, office, preliminary, refs, species, system";
    String license "https://www.bco-dmo.org/dataset/752795/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/752795";
    String param_mapping "{'752795': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/752795/parameters";
    String people_0_affiliation "Rutgers University";
    String people_0_person_name "Malin Pinsky";
    String people_0_person_nid "554708";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of California-Santa Barbara";
    String people_1_affiliation_acronym "UCSB";
    String people_1_person_name "Doug McCauley";
    String people_1_person_nid "752800";
    String people_1_role "Contact";
    String people_1_role_type "related";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Amber York";
    String people_2_person_nid "643627";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "CC Fishery Adaptations";
    String projects_0_acronym "CC Fishery Adaptations";
    String projects_0_description 
"Description from NSF award abstract:
Climate change presents a profound challenge to the sustainability of coastal systems. Most research has overlooked the important coupling between human responses to climate effects and the cumulative impacts of these responses on ecosystems. Fisheries are a prime example of this feedback: climate changes cause shifts in species distributions and abundances, and fisheries adapt to these shifts. However, changes in the location and intensity of fishing also have major ecosystem impacts. This project's goal is to understand how climate and fishing interact to affect the long-term sustainability of marine populations and the ecosystem services they support. In addition, the project will explore how to design fisheries management and other institutions that are robust to climate-driven shifts in species distributions. The project focuses on fisheries for summer flounder and hake on the northeast U.S. continental shelf, which target some of the most rapidly shifting species in North America. By focusing on factors affecting the adaptation of fish, fisheries, fishing communities, and management institutions to the impacts of climate change, this project will have direct application to coastal sustainability. The project involves close collaboration with the National Oceanic and Atmospheric Administration, and researchers will conduct regular presentations for and maintain frequent dialogue with the Mid-Atlantic and New England Fisheries Management Councils in charge of the summer flounder and hake fisheries. To enhance undergraduate education, project participants will design a new online laboratory investigation to explore the impacts of climate change on fisheries, complete with visualization tools that allow students to explore inquiry-driven problems and that highlight the benefits of teaching with authentic data. This project is supported as part of the National Science Foundation's Coastal Science, Engineering, and Education for Sustainability program - Coastal SEES.
The project will address three questions:
1) How do the interacting impacts of fishing and climate change affect the persistence, abundance, and distribution of marine fishes?
2) How do fishers and fishing communities adapt to species range shifts and related changes in abundance? and
3) Which institutions create incentives that sustain or maximize the value of natural capital and comprehensive social wealth in the face of rapid climate change?
An interdisciplinary team of scientists will use dynamic range and statistical models with four decades of geo-referenced data on fisheries catch and fish biogeography to determine how fish populations are affected by the cumulative impacts of fishing, climate, and changing species interactions. The group will then use comprehensive information on changes in fisher behavior to understand how fishers respond to changes in species distribution and abundance. Interviews will explore the social, regulatory, and economic factors that shape these strategies. Finally, a bioeconomic model for summer flounder and hake fisheries will examine how spatial distribution of regulatory authority, social feedbacks within human communities, and uncertainty affect society's ability to maintain natural and social capital.";
    String projects_0_end_date "2018-08";
    String projects_0_geolocation "Northeast US Continental Shelf Large Marine Ecosystem";
    String projects_0_name "Adaptations of fish and fishing communities to rapid climate change";
    String projects_0_project_nid "559948";
    String projects_0_start_date "2014-09";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Home range and body size data compiled from the literature for marine and terrestrial vertebrates.";
    String title "Home range and body size data compiled from the literature for marine and terrestrial vertebrates";
    String version "1";
    String xml_source "osprey2erddap.update_xml() v1.3";
  }
}

 

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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