matlab+人口增长代码-msPVA:用于基于计数的种群生存力分析的R软件包

# msPVA : An R implementation of count-based multi-site population viability analysis [](https://zenodo.org/badge/latestdoi/19481/cmartin/msPVA) [](https://travis-ci.org/cmartin/msPVA) This package implements a stochastic simulation for a count-based multi-site population viability analysis as described in chapter 11 of Quantitative Conservation Ecology (Morris & Doak, 2002). Code is highly inspired from the MatLab implementation described in the book. ## Installation You have two options here. ### Install package from github.com This allows you to easily install updates, have access to the function help files etc. ```r library(devtools) devtools::install_github("cmartin/msPVA") library(msPVA) ``` ### Or you download the source file and run it directly In this case, you need download [the raw R file](https://raw.githubusercontent.com/cmartin/msPVA/master/R/MultisitePVA.R) and then execute : ```r source("MultisitePVA.R") ``` This is a quicker, but dirtier way! ## Try some examples With the same Clapper rail data as in Morris & Doak ### Definining parameters manually : ```r res <- simulate_ms_pva( leaving_prob = 0.2, reaching_prob = 0.5, growth_rate_means = c(0.043, -0.002, 0), growth_rate_vars = c(0.051, 0.041, 0.051), initial_pops = c(70, 26, 33), growth_rate_corrs = {matrix( c( 1.000, 0.995, 0.896, 0.995, 1.000, 0.938, 0.896, 0.938, 1.000), nrow = 3, ncol = 3, byrow = TRUE )}, K = c(286, 60, 58), quasi_extinction_thresholds = c(20, 20, 20), n_years = 50, n_runs = 100, with_progress_bar = FALSE ) print(res) ``` ``` This is the deterministic lambda value : 1.0319573564599 And this is the mean stochastic lambda : 0.99642732192589 Below is mean and standard deviation of log lambda : -0.00367530129674074 0.013982886113063 ``` ```r hist(res) ```  ```r plot(res) ```  ### Or ask the package to calculate most of them automatically from a time-series : With a two-populations polar bear time series from [Stirling et al. 2004](http://arctic.journalhosting.ucalgary.ca/arctic/index.php/arctic/article/view/479/509) ```r params <- calculate_params_from_file( system.file("extdata", "PolarBear_Stirling2004.csv", package = "msPVA") ) ``` ``` Warning in calculate_params_from_file(system.file("extdata", "PolarBear_Stirling2004.csv", : There were gaps in the time series. Mean and variance were computed by linear regression. Correlation matrix was calculated assuming regular intervals. ``` ```r res <- do.call( "simulate_ms_pva", c( params, list( K = c(300,200), leaving_prob = 0.1, reaching_prob = 0.7, quasi_extinction_thresholds = c(20, 20), n_years = 50, n_runs = 100, with_progress_bar = FALSE ) ) ) print(res) ``` ``` This is the deterministic lambda value : 1.05786392886293 And this is the mean stochastic lambda : 0.990314335670581 Below is mean and standard deviation of log lambda : -0.00978931640713308 0.0107011693034957 ``` ## Run it for a single population ```r # From a precalculated mean log-lambdas res <- simulate_ss_pva( growth_rate_means = 0.043, growth_rate_vars = 0.051, initial_pops = 70, K = 286, quasi_extinction_thresholds = 20, n_years = 50, n_runs = 100 ) print(res) ``` ``` Over a 50 years span, the extinction risk of this population is 0.1 And the risk of decline is 0.16 ``` ```r hist(res) ```  ```r # From a vector of log-lambdas res <- simulate_ss_pva( log_lambdas = c(-0.0503626618483076, -0.0316522478682412, -0.205890697055539, -0.0407897021414208, 0.151024474883104, -0.141017433696716, 0.105149579850484, 0.104087724782143, 0.18297223483855), initial_pops = 70, K = 286, quasi_extinction_thresholds = 20, n_years = 50, n_runs = 100 ) ``` ## Read the book If you are to use this package, I highly recommend that you first read chapter 11 from [Quantitative Conservation Ecology (Morris & Doak, 2002)](http://www.sinauer.com/quantitative-conservation-biology-theory-and-practice-of-population-viability-analysis.html), so you understand limitations and assumptions from the underlying model. Managing animal populations should not be taken lightly. ## Problems Please report any bugs to the [GitHub issue tracker](https://github.com/cmartin/msPVA/issues) and write any questions to <charles.martin1@uqtr.ca> ## Citation If this code is useful to you, please cite as : ``` Charles A. Martin (2016). msPVA: An R implementation of count-based multi-site population viability analysis. R package version 0.0.0.9005. https://github.com/cmartin/msPVA. DOI:10.5281/zenodo.34692 ```