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The application uses stochastic models to evaluate the future of populations. <jats:styled-content>Demography_Lab<\/jats:styled-content> may accommodate a wide range of life cycles and can construct models for populations with and without an age or stage structure. Difference equations are used for unstructured populations and matrix models for structured populations. Both types of models operate in discrete time. Models can be very simple, constructed with very limited demographic information or parameter\u2010rich, with a complex density\u2010dependence structure and detailed effects of the different sources of stochasticity. <jats:styled-content>Demography_Lab<\/jats:styled-content> allows for deterministic projections, asymptotic analysis, the extraction of confidence intervals for demographic parameters, and stochastic projections. Stochastic population growth is evaluated using up to three sources of stochasticity: environmental and demographic stochasticity and sampling error in obtaining the projection matrix. The user has full control on the effect of stochasticity on vital rates. The effect of the three sources of stochasticity may be evaluated independently for each vital rate. The user has also full control on density dependence. It may be included as a ceiling population size controlling the number of individuals in the population or it may be evaluated independently for each vital rate. Sensitivity analysis can be done for the asymptotic population growth rate or for the probability of extinction. Elasticity of the probability of extinction may be evaluated in response to changes in vital rates, and in response to changes in the intensity of density dependence and environmental stochasticity.<\/jats:p>","DOI":"10.1002\/ece3.7170","type":"journal-article","created":{"date-parts":[[2021,1,20]],"date-time":"2021-01-20T06:46:43Z","timestamp":1611125203000},"page":"1940-1956","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Demography_Lab, an educational application to evaluate population growth: Unstructured and matrix models"],"prefix":"10.1002","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3240-2373","authenticated-orcid":false,"given":"Julio","family":"Arrontes","sequence":"first","affiliation":[{"name":"Depto. 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