Simulate_stochastic_stages11The names of the stages or categories of the input matrix. In the following example, the matrix has 5 stages or categories. The respective name stages must be filled one by one. First press add value (see arrow in Fig), fill a stage name (not longer than 8 characters) and press enter; then press add value and fill once again the next stage name, repeat the action until you have fill all the stages names.
In the following example, the matrix has 5 stages or categories:
The stages of this matrix are called:
1) Seedlings S
2) Juveniles J
3) Vegetative V
4) Reproductive individuals G
5) Dormant plants D
2014-07-11 13:17:44.858 UTC[S, J, V, G, D]2014-05-21 14:40:23.268 UTCgraph_title00Projection of stochastic growth for Gentiana using equal and unequal probabilities2014-05-21 14:40:55.852 UTCIs the main title to be display in the stochastic projection graph. Click in add value and then write the text in the right space. Please do not use a title longer than the suggest it.
2014-07-11 13:12:42.334 UTCintervals00This value is the number of time steps or projection intervals to predict future population size or in other words the time to predict future population size. Click in add value and write the number in the right space.2014-07-11 13:13:29.437 UTC252014-05-21 14:41:02.962 UTCiterations0010002014-07-11 13:21:02.274 UTCIt is the number of iterations or the number of realizations of population growth to simulate. Click in add value and write the number in the right space.2014-07-11 13:14:18.297 UTCprobabilities11[0.1, 0.1, 0.1, 0.1, 0.2, 0.4]2014-07-25 13:55:13.956 UTCIt is a vector of probability weights used by sample for selecting the projection matrices. In the following example, we use 6 matrices of 6 consecutive years, so if the user selects probabilities weights, the user must fill in 6 probabilities in total that sum up 1.
No probability weights:
If the user wants to use no probability weights, this is established by: First, click in add value, then in the left window a List is added with a "Some input data goes here" element in the right window. Delete that text. After, deletion the "List" have no elements. When running the workflow, Rshell script will assign NULL to the input. (this is when you are running the wf in Taverna workbench)
Probability weights:
The respective probabilities must be filled one by one, they must sum up 1. First, press add value (see arrow in Fig.), fill a probability number and press enter; then press add value and fill once again the next probability, repeat the action until you have filled the probabilities for all matrices. The order of the probabilities must follow the order of the years input. Each year represent a matrix.
e.g. 0.1, 0.1, 0.1, 0.1, 0.2, 0.4 (all the probabilities must sum up 1)
2014-07-25 13:55:07.547 UTCyears11[1987, 1988, 1989, 1990, 1991, 1992]2014-05-21 14:40:11.539 UTCYears in which the data of the matrices were collected. The years must be added one by one as list. First click in add value, fill the first year and press enter, then press add value and fill once again the next year, repeat the action until you have fill all the years.
The years can be display as follow:
e.g.
• 1987
or
• 1987-1988
2014-07-11 13:19:05.871 UTCsumweight11A vector of ones and zeroes used to omit stage classes when checking density. threshold.
The respective sumweights must be filled one by one, the values must be 1 if the stage is included or 0 if is absent. First, press add value (see arrow in Fig.), fill a sumweights number and press enter; then press add value and fill once again the next sumweight, repeat the action until you have filled the sumweights for all stages. The order of the sumweights must follow the order of the stage input.
e.g. 1, 1, 1, 1, 1 (all the stages are included)
e.g. 1, 1, 1, 0, 1 (stage G is omit)
2014-07-11 13:18:04.174 UTC[1, 1, 1, 1, 1]2014-07-11 13:19:50.432 UTCnmax11[]2014-07-28 14:01:46.564 UTCIt is a maximum number of individuals beyond which population projections cannot exceed.
No density dependence:
If the user wants to use no density dependence, this is established by: First, click in add value, then in the left window a List is added with a "Some input data goes here" element in the right window. Delete that text. After deletion the "List" have no elements in the right window. When running the workflow, Rshell script will assign NULL to the input. (this is when you are running the wf in Taverna workbench).
Density dependence:
If the user wants to introduce a density dependence: Click in add value and write the number in the right space.
e.g. 5002014-07-11 14:29:27.987 UTCstochastic_projection0equal_selection0unequal_selection0RequestStageMatricesvalues_L1multiple0field0title0matrices_LL22net.sf.taverna.t2.activitiesdataflow-activity1.5-SNAPSHOTnet.sf.taverna.t2.activities.dataflow.DataflowActivitynet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Parallelize1net.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.ErrorBouncenet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Failovernet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Retry1.0100050000net.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.InvokeReadStageMatrixmatrix_file0labels_L1matrix_Rn211net.sf.taverna.t2.activitiesdataflow-activity1.5-SNAPSHOTnet.sf.taverna.t2.activities.dataflow.DataflowActivitynet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Parallelize1net.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.ErrorBouncenet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Loopnet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Failovernet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Retry1.0100050000net.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.InvokeFlatten_Listinputlist2outputlist11net.sf.taverna.t2.activitieslocalworker-activity1.5-SNAPSHOTnet.sf.taverna.t2.activities.localworker.LocalworkerActivityinputlist2l(l(''))[Btrueoutputlist1l('')1workfloworg.embl.ebi.escience.scuflworkers.java.FlattenListnet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Parallelize1net.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.ErrorBouncenet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Failovernet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Retry1.0100050000net.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.InvokeConvert_LRn2_to_RLn2list_of_r_expressions2r_list_of_expressions11net.sf.taverna.t2.activitiesdataflow-activity1.5-SNAPSHOTnet.sf.taverna.t2.activities.dataflow.DataflowActivitynet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Parallelize1net.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.ErrorBouncenet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Failovernet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Retry1.0100050000net.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Invokegraphprobabilities1iterations0intervals0graph_title0stages1abundances1matrices1weight1n_max1stochastic_growth_plot00eq11uneq11net.sf.taverna.t2.activitiesrshell-activity1.5-SNAPSHOTnet.sf.taverna.t2.activities.rshell.RshellActivitystages1falseabundances1falsematrices1falsegraph_title0falseintervals0falseiterations0falseprobabilities1falseweight1falsen_max1falsestochastic_growth_plot00eq11uneq11falselocalhost6311falsefalsestagesSTRING_LISTabundancesR_EXPmatricesR_EXPgraph_titleSTRINGintervalsINTEGERiterationsINTEGERprobabilitiesDOUBLE_LISTweightINTEGER_LISTn_maxINTEGER_LISTstochastic_growth_plotPNG_FILEeqR_EXPuneqR_EXPnet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Parallelize1net.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.ErrorBouncenet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Failovernet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Retry1.01002000net.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.InvokeAbundance_Interactionstages1title0message0abundances11Abundance iteraction:
Initial abundance: In this dialogue authomatically appears the fields to fill out the initial abundance per stage observed in the field (see data below). After fill out the abundances, the user confirms the numbers.
As a example Gentiana pneumonanthe has 5 stages with its respective abundance:
stage abundance
1) S (seedlings) 69
2) J (Juveniles) 100
3) V (vegetative) 111
4) G (reproductive individuals) 21
5) D (dormant plants) 43
2012-11-01 11:56:16.812 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initial population vectornet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Parallelize1net.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.ErrorBouncenet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Failovernet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Retry1.0100050000net.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.InvokeSelect_matrix_filesvalue00net.sf.taverna.t2.activitiesstringconstant-activity1.5-SNAPSHOTnet.sf.taverna.t2.activities.stringconstant.StringConstantActivitySelect matrix 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Paula Balcazar-Vargas, Mikolaj Krzyzanowski, Jonathan Giddy, Francisco Quevedo and Gerard Oostermijer .2014-07-30 12:22:31.930 UTC69cdff57-e566-4b9b-98a9-45b0b98819b72014-03-05 15:49:04.215 UTC37c2bda2-fd8e-4c9a-94f4-2e17dd3f81182014-07-28 16:54:27.695 UTC033579c5-1a8a-4b9f-8c74-63a87aee03ba2014-07-10 12:33:14.480 UTC352a165e-e1b7-4081-a39d-098cc18760d12014-01-30 12:25:41.905 UTCc7fc79f1-1545-48da-a748-a2104f1714642014-01-30 12:41:13.191 UTCf2ef7c08-49ac-436b-a4ae-9a2b19f85c242014-07-10 14:42:24.666 UTC4b09c6e5-5def-4c9a-8a1b-7dbff06e99652014-01-30 12:29:36.252 UTCe22c8fc0-897d-4851-821a-b52c19f082282014-01-30 13:04:03.827 UTCce2001d5-a3e7-41b1-af9a-8f3c528a2deb2014-02-05 13:22:11.360 UTC752811f1-6468-4f64-9f11-49d0cda7a85f2014-07-10 12:57:06.319 UTCe72bc4ea-d7aa-4b82-86bf-b31c783c83242014-01-30 12:19:46.292 UTCf7a6e74d-dc66-491b-b0d2-f9abbeae76832014-07-10 12:42:48.656 UTC3660a11a-23e6-4ae8-86c2-45652e978e502014-01-22 15:34:57.108 UTCdfc14de5-0609-498c-b6b9-0231d9c5445c2014-07-25 13:31:46.932 UTCaf1ed12c-fb04-490c-9cd8-c9d37050acf32014-01-22 15:30:51.591 UTCdf50d7f7-8e37-4649-bbfe-2f179541ea7d2014-01-30 12:26:33.170 UTC8d809279-8d16-421e-b03b-17b65fc2a7452014-03-05 14:35:39.929 UTC72cac1e2-9029-4603-8f97-67aca3e76b992014-07-11 14:29:29.258 UTC975cd586-3894-44b0-86b3-fbeecd2719622014-01-30 12:28:04.777 UTCb925170a-0f46-4fc0-9dfd-b2abd93c28c92014-01-30 12:23:36.905 UTCf1edc485-4c4b-44ba-971d-8fe7606fa0672014-03-05 13:13:52.949 UTC217d4dcf-1d99-4b1a-8d24-9c16ae5f69382014-01-30 13:26:10.134 UTC138a43e6-a2a4-43d6-a834-ba27c0b5b1682014-05-21 14:41:29.549 UTC5f54285a-3376-4822-8d53-ed98f87f6dbb2014-03-05 12:12:20.893 UTCfbc4d358-ab9f-4863-9cbd-25a25434ab392014-01-30 12:20:41.104 UTC074d93e2-58ed-46f4-b6da-84c9bbff07f72014-03-05 15:59:49.623 UTC9b80b070-a717-4de8-ad28-f6aecba0ed4a2014-01-22 15:36:19.385 UTC59b59c5c-1f95-47d8-89a9-47dc2a92dfa62014-01-30 13:06:46.694 UTCSimulate stochastic growth from a sequence of matrices2014-07-10 12:28:35.864 UTCc3f6066d-838f-49e2-bc95-be6888a887752014-07-28 13:53:36.852 UTC6f78ab7c-498a-47df-b4d4-734203b129de2014-01-30 12:44:46.92 UTC17189ca3-7ecb-4f6e-af1a-37864bde05262014-03-05 13:14:59.234 UTC4c1611b0-f95c-49cc-a56f-d7b6e14fff542014-07-11 13:19:56.104 UTC38e4998b-9253-4469-b9ff-b3b8dce7d2832014-03-05 15:55:07.4 UTC5c4367a4-766b-41ad-8e11-09e270bc7c0e2014-03-05 15:50:48.886 UTCc57c0a13-3ab8-4c3f-884f-c7f761ca8d182014-03-05 16:02:29.984 UTC10f8bebd-8324-4144-a1f8-5ccf55927c9b2014-07-30 12:22:33.562 UTC19920aef-bdc0-4c4c-916a-3ae020cc77f92014-01-22 15:37:40.706 UTC3de0f13c-49e9-47a8-a8e5-30ad02cf9c412014-07-10 12:46:39.601 UTCc75a5a9e-2bc1-475a-b91b-7dcb4330e4462014-07-10 13:19:23.326 UTC037d672c-8377-4684-bf3f-e9fef2a6ed5e2014-05-21 14:34:58.347 UTC6435d6da-e85e-4c82-b050-032bd48fcdc62014-07-28 14:02:00.358 UTCf3a7d64a-1db0-45c1-9c11-016743aaf83d2014-03-05 15:51:41.811 UTC90ff69d6-f86e-4209-a0a7-663b17c3c1282014-05-21 14:37:48.906 UTC348f209f-f7de-42f1-9a56-9dcb19dc4ec22014-01-30 12:52:09.874 UTCcf79b137-b2e4-4a8b-8030-25ac8be5b0402014-03-05 13:22:14.121 UTC16628918-ef09-43ec-92ef-7f0ff47c03f22014-03-05 13:12:23.822 UTCThe Simulate stochastic growth from a sequence of matrices Workflow provides an environment to simulate stochastic growth by projection using whole matrix selection techniques in an independently and identically distributed (iid) environment from a set of 2 or more projection matrices.
This workflow is based on the popbio package (script: stoch.projection - Simulate stochastic growth from a sequence of matrices, Stubben, Milligan and Nantel, 2013) based on the The MATLAB code in Box 7.3 (Morris and Doak 2002). For more details of the analysis see: Exploring population growth in a variable environment with computer simulations (Morris and Doak 2002, pag: 229-233 and Caswell 2001, Chapter 14).
Outputs:
• Equal selection data
• Stochastic projection
• Unequal selection data
We use Gentiana pneumonanthe only as example how to run this workflow.
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 using and based on Package ‘popbio’ in R. (Stubben & Milligan 2007; Stubben, Milligan & Nantel 2011).
==================================================================================
Literature
Caswell, H. 2001. Matrix population models: Construction, analysis and interpretation, 2nd
Edition. Sinauer Associates, Sunderland, Massachusetts.
Oostermeijer J.G.B., M.L. Brugman; E.R. de Boer; H.C.M. Den Nijs. 1996. Temporal and Spatial Variation in the Demography of Gentiana pneumonanthe, a Rare Perennial Herb. The Journal of Ecology, Vol. 84(2): 153-166.
Morris, W. F., and D. F. Doak. 2002. Quantitative conservation biology: Theory and practice of population viability analysis. Sinauer, Sunderland, Massachusetts, USA. 480 pages
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. 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UTCReadStageMatrixlabels_L11matrix_file00matrix_Rn21Matrix_ReadFromFilematrix_file0labels1read_matrix11net.sf.taverna.t2.activitiesrshell-activity1.5-SNAPSHOTnet.sf.taverna.t2.activities.rshell.RshellActivitymatrix_file0falselabels1falseread_matrix11falselocalhost6311falsefalsematrix_fileTEXT_FILElabelsSTRING_LISTread_matrixR_EXPnet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Parallelize1net.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.ErrorBouncenet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Failovernet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Retry1.0100050000net.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.InvokeMatrix_ReadFromFilematrix_filematrix_fileMatrix_ReadFromFilelabelslabels_Lmatrix_Rn2Matrix_ReadFromFileread_matrix6b5b9009-65c6-45a2-941f-188268b27c592013-10-14 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UTCConvert_Taverna_listlist_of_r_expressions22r_list_of_expressions1FlattenListOfStringsToStringstringlist1concatenated00net.sf.taverna.t2.activitieslocalworker-activity1.5-SNAPSHOTnet.sf.taverna.t2.activities.localworker.LocalworkerActivitystringlist1l('text/plain')java.lang.Stringtrueconcatenated00workfloworg.embl.ebi.escience.scuflworkers.java.StringListMergeUserNameHere2013-10-14 14:22:51.151 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UTCnet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Parallelize1net.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.ErrorBouncenet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Failovernet.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.Retry1.0100050000net.sf.taverna.t2.coreworkflowmodel-impl1.5-SNAPSHOTnet.sf.taverna.t2.workflowmodel.processor.dispatch.layers.InvokeFlattenListOfStringsToStringstringlistlist_of_r_expressionsCombineListOfStringsIntoRListstringlistFlattenListOfStringsToStringconcatenatedr_list_of_expressionsCombineListOfStringsIntoRListoutput13112099-3efd-42a7-bf18-a93c89de52dd2013-09-04 15:30:31.850 UTCJonathan Giddy2013-09-04 15:12:34.436 UTC1ff54110-840d-474e-95a4-877c8f2c5b5e2013-09-04 15:26:02.821 UTC472c6bef-15bc-4782-ab72-9e041b46e9d02013-10-14 14:28:56.870 UTCThis workflow accepts a Taverna list of arbitrary R expressions and returns a single R expression representing an R list containing the original expressions.
This workflow relies on the current Taverna behaviour of an R expression being represented by a list of strings containing the deparsed expression. If this changes, this workflow will likely break.
The first BeanShell converts each R expression (actually a list of strings) to a single string. This uses implicit iteration to do this for each R expression, so input port depth is 2 but the BeanShell input depth is 1.
The second Beanshell creates a comma-separated list of the deparsed R expressions and wraps the string with the R list() function. So now we have a single string s that can be turned into an R list using eval(parse(text=s)).
But RShell already does that parsing for us, so we just need to ensure the string looks like an R expression by turning it into a list of strings. So we actually output a 1-element list containing the string.
2013-10-14 14:28:55.280 UTCConvert Taverna list of RExpr to R list2013-09-04 15:13:12.850 UTC