Bootstrap of observed census transitions.

Created: 2012-11-05 15:05:37 Last updated: 2014-07-24 13:09:04

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This workflow calculates bootstrap distributions of population growth rates (Î»), stage vectors, and projection matrix elements by randomly sampling with replacement from a stage-fate data frame of observed transitions. The goal of a demographic analysis is very often to estimate lambda, because lambda is estimated from imperfect data, such estimation are uncertain. Therefore, when the results have policy implications it is important to quantify that uncertainty. Confidence interval is one of the traditional tools to doing so (see outputs: Bootstrap analysis).

A detailed description of resampling methods to estimate confidence intervals for demographic estimates is described Caswell (2001, Chapter 12)

============================================================ Literature

Caswell, H. 2001. Matrix population models: Construction, analysis and interpretation, 2nd Edition. Sinauer Associates, Sunderland, Massachusetts.

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This workflow has been created by the Biodiversity Virtual e-Laboratory (BioVeL http://www.biovel.eu/) project. BioVeL is funded by the EUâ€™s Seventh Framework Program, grant no. 283359.

This workflow was created based on Package â€˜popbioâ€™ in R.

Stubben, C & B. Milligan. 2007. Estimating and Analysing Demographic Models Using the popbio Package in R. Journal of Statistical Software 22 (11): 1-23

Stubben, C., B. Milligan, P. Nantel. 2011. Package â€˜popbioâ€™. Construction and analysis of matrix population models. Version 2.3.1

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Inputs (3)

Name	Description
TableFile	Table containing demographic data of individuals in two year The input data (a .txt-file) has to have the format of a table containing the demographic data on a series of individuals in two years. Each individual has a table row for each year and is identified by a number (plant column in example). For the year specified in the column 'year', each individual has a certain life stage ('stage'). The stage codes can be chosen by the user, not longer than 5 characters. For all individuals, the number of offspring is specified in a chosen way (in the example, 'repstr' gives the number of flowers/fruits for each plant. In the example, it can be seen that only generative adults (stage=G) had flowers. Individuals without offspring have to be indicated by filling in '0' in this column, which cannot have empty cells. The column 'recruitment' specifies those individuals that are new to the population by means of a code. In the example, 'RS' is a new seedling, and 'RJ' a new juvenile plant. As can be seen in the example, no code is needed in this column for individuals that were already present.
SpeciesName	In this input port SpeciesName comes the title of the bar plot that will be generated with the analysis. As an example, it can be the name of the species or the name of the place where the research has been conducted, between others.
Bootstrap_Iterations	Number of iterations for calculation of bootstrap distributions

Processors (7)

Name	Type	Description
DisplayConfidenceInterval	rshell	Script sink(output) print(input) R Server springer.grid.cf.ac.uk:6311
Bootstrap_of__observ	workflow
CensusData_ReadFromFile	rshell	Script census_data <- read.table(census_data_file, header=TRUE, fill=TRUE) R Server springer.grid.cf.ac.uk:6311
SelectYear	workflow
year	stringconstant	Value year
SortAndCategoriseSta	workflow
stage	stringconstant	Value stage

Beanshells (0)

Outputs (2)

Name	Description
Confidence_Interval_CI	95% Confidence interval of Lambda In statistics, a confidence interval (CI) is a type of interval estimate of a population parameter and is used to indicate the reliability of an estimate. It is an observed interval (i.e. it is calculated from the observations), in principle different from sample to sample, that frequently includes the parameter of interest if the experiment is repeated. How frequently the observed interval contains the parameter is determined by the confidence level or confidence coefficient.
histogram	Histogram plotting the frecuencies of the lambda values and the 95% confidence intervals resulting from the bootstrap analysis

Datalinks (14)

Source	Sink
Bootstrap_of__observ:confidence_interval	DisplayConfidenceInterval:input
CensusData_ReadFromFile:census_data	Bootstrap_of__observ:census_data
SelectYear:initialYear	Bootstrap_of__observ:startYear
SortAndCategoriseSta:matrixStages	Bootstrap_of__observ:stages
SortAndCategoriseSta:recruitedStages	Bootstrap_of__observ:recruitedStages
SpeciesName	Bootstrap_of__observ:plotTitle
Bootstrap_Iterations	Bootstrap_of__observ:bootstrapIterations
TableFile	CensusData_ReadFromFile:census_data_file
CensusData_ReadFromFile:census_data	SelectYear:census_data
year:value	SelectYear:yearColumnName
CensusData_ReadFromFile:census_data	SortAndCategoriseSta:census_data
stage:value	SortAndCategoriseSta:stageColumnHeader
DisplayConfidenceInterval:output	Confidence_Interval_CI
Bootstrap_of__observ:histogram	histogram

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Maria Paula Balcazar-Vargas

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Version History

In chronological order:

Bootstrap of observed census transitions.

Created by Maria Paula Balcazar-Vargas on Monday 05 November 2012 15:05:36 (UTC)
Bootstrap of observed census transitions.

Created by Maria Paula Balcazar-Vargas on Thursday 24 July 2014 12:58:55 (UTC)

Revision comment:

Chages:
* Print values with 16 digits
*Liberate sink memory
* The previous was a spriger version, this uses local R.
*Forcing the execution order of the interactions.
Bootstrap of observed census transitions.

Created by Maria Paula Balcazar-Vargas on Thursday 24 July 2014 13:09:04 (UTC)

Revision comment:

Chages:
* Print values with 16 digits
*Liberate sink memory
* The previous was a spriger version, this uses local R.
*Forcing the execution order of the interactions. Fist stages and the years.