Field | Definition |
Site name | Full site name as per the Antarctic Site compendium |
Site id | Four letter site code |
CCAMLR region | CCAMLR sub-region as per the CCAMLR homepage |
Longitude | Longitude (decimal degrees) in WSG 1984 / EPSG 4326 |
Latitude | Latitude (decimal degrees) in WSG 1984 / EPSG 4326 |
Common name | Common name of species |
Day | Day of count |
Month | Month of count |
Year | Year of count |
Season starting | Season of count. For example, a count made in January 2014 would have season = 2013. A count made in November 2013 would have season = 2013 |
Count | Number counted or estimated based on vantage. Count type field indicates what was counted |
Accuracy | Accuracy of count. |
Count type | The life phase of individuals counted (nests, chicks, adults) |
Vantage | The type of platform used to make the count |
Reference | Citation for the count wrapped with HTML code for formatting |
Notes | Important notes for the count |
Mean | Mean value of counts from Bayesian posteriors |
Lower CI | Lower bound of the 90th percentile Bayesian credible interval from the posterior distribution of the model |
Upper CI | Upper bound of the 90th percentile Bayesian credible interval from the posterior distribution of the model |
This field represents the full site name as represented in the Antarctic Site compendium
Four letter site codes defined by Lynch for identification purposes across the database. This is the primary key across the tables
E.G. Acuna Island = ACUN
This is the numeric value for the CCAMLR sub-region that the site falls within. For a map of the regions go to the CCAMLR website
The longitude of the centroid of the site in WGS 1984 (EPSG 4326) as calculated by way of a site polygon manually assigned by Lynch et al.
The latitude of the centroid of the site in WGS 1984 (EPSG 4326) as calculated by way of a site polygon manually assigned by Lynch et al.
English common name of the species counted. Either Adelie penguin, Chinstrap penguin, Emperor penguin or Gentoo penguin
Day of the month that the count was performed if known. Some days may not be known due to the information not being avaiable in the publication or report
Month of the year (numeric value: e.g. Jan = 01, Feb = 02) that the count was performed if known. Some months may not be known due to information being unavailable in the report or publication
Gregorian calender year that the count was performed
The season of the count. This does not always correspond to the year. Counts performed between Jan - June of year N are included in season = N - 1 (e.g., February 2010 is Season = 2009)
The actual count either derived or counted for the population. This is a whole number
This is a quality flag that is given to each count in the database. It is scaled from 1 to 5 with 1 being the highest quality and 5 being the lowest. Values of 1 are mostly associated with ground counts while values of 5 are associated with less accurate estimation techniques like satellite / VHR images.
This is the life stage counted and is either:
The type of platform used for counting or estimating populations. This can be one of:
This is the citation for the count wrapped with HTML code for formatting purposes. The formatting can be viewed when you click on "view source" in the count tables tab of your query
These are important notes for the particular count and may include information that will help determine how the accuracy or quality of the count was determined
The posterior samples from the Bayesian population model (n = 4500) are averaged across all sites in your query. E.g. Average(Sample1 Site1,...Sample1 SiteN), Average(Sample2 Site1,...Sample2 SiteN),...Average(Sample4500 Site1,... Sample4500 SiteN). This gives 4500 "possible" values for the total population. We take the mean of those 4500 samples as the estimated population size
This is the lower bound of the 90th percentile of the Bayesian credible interval calculated from the 4500 samples we use to calculate the mean value (see above). This is calculated using the highest posterior density interval (used for Bayesian techniques) as opposed to standard confidence intervals
This is the upper bound of the 90th percentile of the Bayesian credible interval calculated from the 4500 samples we use to calculate the mean value (see above). This is calculated using the highest posterior density interval (used for Bayesian techniques) as opposed to standard confidence intervals