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This workflow calculates bootstrap distributions of population growth rates (λ), 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)
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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 EU’s Seventh Framework Program, grant no. 283359.
This workflow was created based on Package ‘popbio’ 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 ‘popbio’. Construction and analysis of matrix population models. Version 2.3.1
Inputs (3)
Data Inputs (1)
TableFile (text/plain)
Description:
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.
Example value:
plant year stage reprstr recruitment
2 1987 D 0
4 1987 J 0
5 1987 D 0
31 1987 V 0
36 1987 G 5
37 1987 J 0
41 1987 J 0
43 1987 S 0
46 1987 V 0
2 1988 V 0
4 1988 D 0
5 1988 V 0
9 1988 J 0 RJ
14 1988 J 0 RJ
Parameter Inputs (2)
Bootstrap_Iterations
Description:
Number of iterations for calculation of bootstrap distributions
Example value:
10000
SpeciesName
Description:
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.
Example value:
Gentiana pneumonanthe
Outputs (2)
Result Outputs (2)
Confidence_Interval_CI (text/csv)
Description:
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.
Example value:
2.5% 97.5%
0.954955 1.468701
histogram (image/png)
Description:
Histogram plotting the frecuencies of the lambda values and the 95% confidence intervals resulting from the bootstrap analysis
Error/Log Outputs (0)
None
Interactions (2)
CategoriseStagesInteraction
Description:
Inputs: unsortedStages
Outputs: sortedStages, recruitedStages, reproductiveStages
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SelectYear_Interaction
Description:
Inputs: years
Outputs: year
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R Scripts (9)
DisplayConfidenceInterval
Description:
Inputs: input
Outputs: output
Script:
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CensusData_ReadFromFile
Description:
Inputs: census_data_file
Outputs: census_data
Script:
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ParseStages
Description:
Inputs: census_data, stage_column_header
Outputs: all_stages
Script:
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ParseYears
Description:
Inputs: census_data, year_column_name
Outputs: census_years
Script:
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Prepare
Description:
Inputs: census_data, stages, recruited_stages, start_year
Outputs: trans1, trans, log
Script:
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Analysis
Description:
Inputs: trans1, stages
Outputs: projection_matrix
Script:
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PlotHistogram
Description:
Inputs: a, ci, plot_title
Outputs: ci, histogram
Script:
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ConfidenceInterval
Description:
Inputs: trans1, bootstrap_iterations
Outputs: a, ci
Script:
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DisplayTrans1
Description:
Inputs: input
Outputs: output
Script:
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Details
Filename:
Bootstrap_of_observed_census_transitions._V3-2014-07-23.t2flow
Category:
Population Modelling
Author:
Maria Paula Balcázar-Vargas, Jonathan Giddy and G. Oostermeijer
Uploader:
Maria Balcazar-Vargas
Uploaded at:
21 Aug 2014 15:11:10 UTC
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Bootstrap of observed census transitions. (v1) run 20 May 2015 13:12:26 UTC