Package: poems 1.4.0

July Pilowsky

poems: Pattern-Oriented Ensemble Modeling System

A framework of interoperable R6 classes (Chang, 2020, <https://CRAN.R-project.org/package=R6>) for building ensembles of viable models via the pattern-oriented modeling (POM) approach (Grimm et al.,2005, <doi:10.1126/science.1116681>). The package includes classes for encapsulating and generating model parameters, and managing the POM workflow. The workflow includes: model setup; generating model parameters via Latin hyper-cube sampling (Iman & Conover, 1980, <doi:10.1080/03610928008827996>); running multiple sampled model simulations; collating summary results; and validating and selecting an ensemble of models that best match known patterns. By default, model validation and selection utilizes an approximate Bayesian computation (ABC) approach (Beaumont et al., 2002, <doi:10.1093/genetics/162.4.2025>), although alternative user-defined functionality could be employed. The package includes a spatially explicit demographic population model simulation engine, which incorporates default functionality for density dependence, correlated environmental stochasticity, stage-based transitions, and distance-based dispersal. The user may customize the simulator by defining functionality for translocations, harvesting, mortality, and other processes, as well as defining the sequence order for the simulator processes. The framework could also be adapted for use with other model simulators by utilizing its extendable (inheritable) base classes.

Authors:Sean Haythorne [aut], Damien Fordham [aut], Stuart Brown [aut], Jessie Buettel [aut], Barry Brook [aut], July Pilowsky [aut, cre]

poems_1.4.0.tar.gz
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poems_1.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
poems/json (API)

# Install 'poems' in R:
install.packages('poems', repos = c('https://globalecologylab.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/globalecologylab/poems/issues

Pkgdown/docs site:https://globalecologylab.github.io

Datasets:

On CRAN:

Conda:

biogeographypopulation-modelprocess-based

7.14 score 13 stars 1 packages 78 scripts 244 downloads 28 exports 46 dependencies

Last updated from:129b021c42. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK348
source / vignettesOK256
linux-release-x86_64OK270
macos-release-arm64OK227
macos-oldrel-arm64OK231
windows-develOK547
windows-releaseOK420
windows-oldrelOK466
wasm-releaseOK151

Exports:DispersalFrictionDispersalGeneratorDispersalTemplateGenerativeTemplateGeneratorGenericClassGenericManagerGenericModelLatinHypercubeSamplerModelSimulatorpopulation_densitypopulation_dispersalpopulation_env_stochpopulation_resultspopulation_simulatorpopulation_transformationpopulation_transitionsPopulationModelPopulationResultsRegionResultsManagerSimulationManagerSimulationModelSimulationResultsSimulatorReferenceSpatialCorrelationSpatialModelValidator

Dependencies:abcabc.dataclicodetoolscpp11DEoptimRdoParallelextraDistrforeachforeignfossilgdistanceglueigraphiteratorslatticelhslifecyclelocfitmagrittrmapsMASSMatrixMatrixModelsmetRologynnetnumDerivpkgconfigqs2quantregR6rasterRcppRcppArmadilloRcppParallelrlangrobustbaseshapefilesspSparseMstringfishsurvivalterratrendtruncnormvctrs

Workflow example for the Tasmanian thylacine
Setup | Workflow | Step 1: Build the population model for the study region | Tasmanian study region | IBRA bioregions | Density dependence function | Harvest function | Template model | Step 2: Build generators for dynamically generating model parameters | Initial habitat suitability | Habitat decline | Initial abundance and carrying capacity generator | Stage matrix generator | Dispersal generator | Example model run | Step 3: Sample model and generator parameters for each simulation | Step 4: Build a simulation manager to run each simulation | Step 5: Build a results manager to generate summary results (metrics) | Using the PopulationResults class | Generating summary metrics and matrices | Summary metric refinement | Step 6: Build a validator to select a model ensemble | Selected model ensemble | Model ensemble summary metrics | Model ensemble parameters | Model ensemble stochasticity | Model ensemble verification | Model ensemble usage | Summary | References

Last update: 2025-05-07
Started: 2020-12-09

Population introduction via translocation functions
Setup | Step 1: Build the population model for the study region | Study region | Land-use modifier | Environmental correlation | Spatially-varying growth rates | Step 2: Setup the translocation function | Introduction sites and times | Translocation function | Step 3: Build generators for dynamically generating model parameters | Growth rate generator | Dispersal generator | Capacity generator | Step 4: Build a template model | Step 5: Run multiple simulations | Define the latin-hypercube for sampling | Step 6: Extract results from simulations | Extract results

Last update: 2025-05-07
Started: 2023-08-04

Simple workflow example for a population model
Setup | Workflow | Step 1: Build the population model for the study region | Study region | Environmental correlation | Harvest function | Template model | Step 2: Build generators for dynamically generating model parameters | Habitat suitability | Initial abundance and carrying capacity generator | Dispersal generator | Step 3: Sample model and generator parameters for each simulation | Step 4: Build a simulation manager to run each simulation | Step 5: Build a results manager to generate summary results (metrics) | Step 6: Build a validator to select a model ensemble | Summary | References

Last update: 2024-04-03
Started: 2020-11-23

Readme and manuals

Help Manual

Help pageTopics
R6 class representing a dispersal friction.DispersalFriction
R6 class representing a dispersal generator.DispersalGenerator
R6 class representing a nested container for dispersal generator attributesDispersalTemplate
R6 class representing a nested container for generator attributesGenerativeTemplate
R6 class representing a dynamic attribute generatorGenerator
R6 class with generic reusable functionalityGenericClass
R6 class representing a generic manager.GenericManager
R6 class representing a generic model.GenericModel
R6 class to represent a Latin hypercube sampler.LatinHypercubeSampler
R6 class representing a model simulator.ModelSimulator
poems: Pattern-oriented ensemble modeling and simulationpoems
Nested functions for population density dependence.population_density
Nested functions for population dispersal.population_dispersal
Nested functions for population environmental stochasticity.population_env_stoch
Nested functions for initializing, calculating and collecting population simulator results.population_results
Runs a stage-based demographic population model simulation.population_simulator
Nested functions for a user-defined population abundance (and capacity) transformation.population_transformation
Nested functions for stage-based population transitions.population_transitions
R6 class representing a population modelPopulationModel
R6 class representing population simulator results.PopulationResults
R6 class representing a study region.Region
R6 class representing a results manager.ResultsManager
R6 class representing a simulation manager.SimulationManager
R6 class representing a simulation modelSimulationModel
R6 class representing simulation results.SimulationResults
R6 class for a simulator referenceSimulatorReference
R6 class representing a spatial correlation.SpatialCorrelation
R6 class representing a spatial modelSpatialModel
Thylacine vignette Tasmania IBRA datatasmania_ibra_data
Thylacine vignette Tasmania IBRA rastertasmania_ibra_raster
Tasmania land-use modifier rastertasmania_modifier
Thylacine vignette Tasmania rastertasmania_raster
Thylacine vignette bounty recordthylacine_bounty_record
Thylacine vignette demonstration example matricesthylacine_example_matrices
Thylacine vignette demonstration example (re-run) matricesthylacine_example_matrices_rerun
Thylacine vignette demonstration example metricsthylacine_example_metrics
Thylacine vignette demonstration example (re-run) metricsthylacine_example_metrics_rerun
Thylacine vignette habitat suitability rasterthylacine_hs_raster
R6 class representing a pattern-oriented validator.Validator