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SRKW demographic data
The data (a .csv-file) has the format of a table containing the Orcinus orca demographic data with the columns named: Year, Age, Count, Offspring and Cat1. Each year, the number of individuals per age and the number of offspring per age reproductive female category are counted (females ≥ 10 years old). IF A Female category does not have offspring equals to 0. For the called column, Cat1; Ages 1 to 9 belongs to Juv (Juveniles) and 10 to 88 (this tutorial) belongs to Female or Male. Juv and Male categories must have a NA offspring.
Download SRKW_R.csv.
| Year | Age | Count | Offspring | Cat1 |
|---|---|---|---|---|
| 2007 | 23 | 0.00 | NA | Male |
| 2007 | 24 | 0.00 | NA | Male |
| 2007 | 24 | 0.00 | 0.00 | Female |
| 2007 | 25 | 0.00 | NA | Male |
| 2007 | 25 | 0.00 | 0.00 | Female |
| 2007 | 26 | 0.00 | 0.00 | Female |
| 2007 | 26 | 0.00 | NA | Male |
| 2007 | 27 | 0.00 | 0.00 | Female |
| 2007 | 27 | 0.00 | NA | Male |
| 2007 | 28 | 0.00 | 0.00 | Female |
| 2007 | 28 | 0.00 | NA | Male |
| 2007 | 29 | 0.00 | NA | Male |
| 2007 | 29 | 1.00 | 0.00 | Female |
| 2007 | 30 | 1.00 | NA | Male |
| 2007 | 30 | 0.00 | 0.00 | Female |
| 2007 | 31 | 5.00 | 1.00 | Female |
| 2007 | 31 | 1.00 | NA | Male |
| 2007 | 32 | 0.00 | 0.00 | Female |
| 2007 | 32 | 0.00 | NA | Male |
| 2007 | 33 | 0.00 | 0.00 | Female |
| 2007 | 33 | 0.00 | NA | Male |
| 2007 | 34 | 0.00 | NA | Male |
| 2007 | 34 | 2.00 | 0.00 | Female |
| 2007 | 35 | 0.00 | NA | Male |
| 2007 | 35 | 1.00 | 0.50 | Female |
| 2007 | 36 | 2.50 | 0.50 | Female |
| 2007 | 36 | 0.00 | NA | Male |
| 2007 | 37 | 1.50 | 0.00 | Female |
| 2007 | 37 | 0.00 | NA | Male |
| 2007 | 38 | 0.00 | 0.00 | Female |
| 2007 | 38 | 0.00 | NA | Male |
| 2007 | 39 | 0.00 | 0.00 | Female |
| 2007 | 39 | 0.00 | NA | Male |
| 2007 | 40 | 0.00 | NA | Male |
| 2007 | 40 | 0.00 | 0.00 | Female |
| 2007 | 41 | 0.00 | NA | Male |
| 2007 | 41 | 0.00 | 0.00 | Female |
| 2007 | 42 | 0.00 | 0.00 | Female |
| 2007 | 42 | 0.00 | NA | Male |
| 2007 | 43 | 0.00 | 0.00 | Female |
| 2007 | 43 | 0.00 | NA | Male |
| 2007 | 44 | 0.00 | 0.00 | Female |
| 2007 | 44 | 0.00 | NA | Male |
| 2007 | 45 | 0.00 | NA | Male |
| 2007 | 45 | 1.00 | 0.00 | Female |
| 2007 | 46 | 0.00 | NA | Male |
| 2007 | 46 | 2.00 | 0.00 | Female |
| 2007 | 47 | 0.00 | 0.00 | Female |
| 2007 | 47 | 0.00 | NA | Male |
| 2007 | 48 | 0.00 | 0.00 | Female |
| 2007 | 48 | 0.00 | NA | Male |
| 2007 | 49 | 1.00 | 0.00 | Female |
| 2007 | 49 | 0.00 | NA | Male |
| 2007 | 50 | 0.00 | NA | Male |
| 2007 | 50 | 0.00 | 0.00 | Female |
| 2007 | 51 | 0.00 | NA | Male |
| 2007 | 51 | 0.00 | 0.00 | Female |
| 2007 | 52 | 1.00 | 0.00 | Female |
| 2007 | 52 | 0.00 | NA | Male |
| 2007 | 53 | 0.00 | 0.00 | Female |
| 2007 | 53 | 0.00 | NA | Male |
| 2007 | 54 | 2.00 | 0.00 | Female |
| 2007 | 54 | 0.00 | NA | Male |
| 2007 | 55 | 0.00 | 0.00 | Female |
| 2007 | 55 | 0.50 | NA | Male |
| 2007 | 56 | 0.50 | NA | Male |
| 2007 | 56 | 0.00 | 0.00 | Female |
| 2007 | 57 | 0.00 | 0.00 | Female |
| 2007 | 58 | 0.00 | 0.00 | Female |
| 2007 | 59 | 0.00 | 0.00 | Female |
| 2007 | 60 | 0.00 | 0.00 | Female |
| 2007 | 61 | 0.00 | 0.00 | Female |
| 2007 | 62 | 0.00 | 0.00 | Female |
| 2007 | 63 | 0.00 | 0.00 | Female |
| 2007 | 64 | 1.00 | 0.00 | Female |
| 2007 | 65 | 0.00 | 0.00 | Female |
| 2007 | 66 | 0.00 | 0.00 | Female |
| 2007 | 67 | 0.00 | 0.00 | Female |
| 2007 | 68 | 0.00 | 0.00 | Female |
| 2007 | 69 | 0.00 | 0.00 | Female |
| 2007 | 70 | 0.50 | 0.00 | Female |
| 2007 | 71 | 0.50 | 0.00 | Female |
| 2007 | 72 | 3.00 | 0.00 | Female |
| 2007 | 73 | 0.50 | 0.00 | Female |
| 2007 | 74 | 0.50 | 0.00 | Female |
| 2007 | 75 | 0.00 | 0.00 | Female |
| 2007 | 76 | 0.00 | 0.00 | Female |
| 2007 | 77 | 0.00 | 0.00 | Female |
| 2007 | 78 | 0.00 | 0.00 | Female |
| 2007 | 79 | 0.00 | 0.00 | Female |
| 2007 | 80 | 0.00 | 0.00 | Female |
| 2007 | 81 | 0.00 | 0.00 | Female |
| 2007 | 82 | 0.00 | 0.00 | Female |
| 2007 | 83 | 0.00 | 0.00 | Female |
| 2007 | 84 | 0.00 | 0.00 | Female |
| 2008 | 1 | 3.00 | NA | Juv |
| 2008 | 2 | 3.00 | NA | Juv |
| 2008 | 3 | 1.00 | NA | Juv |
| 2008 | 4 | 5.00 | NA | Juv |
| 2008 | 5 | 2.00 | NA | Juv |
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Disclaimer
This website is a demonstrator for the integration of several informatics technologies useful in "in-silico" biodiversity science: Scratchpads, Taverna Player and BioVeL infrastructure for executing workflows. This particular example makes use of population census data for Killer Whales and abundance data for Chinook Salmon in the north-east Pacific Ocean, which has kindly been provided by Antonio Velez-Espino of Fisheries and Oceans Canada. Please do not rely on the data or results information provided for any actual scientific, conservation or policy use. Mistakes herein (of which there are several) are solely the responsibility of the technical parties working on the technology integration. These include: Cardiff University, University of Manchester and the Natural History Museum, London.