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Demography_Lab an educational application to evaluate population growth: Unstructured and matrix models

机译:Demopach_Lab一种评估人口增长的教育申请:非结构化和矩阵模型

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摘要

Training in Population Ecology asks for scalable applications capable of embarking students on a trip from basic concepts to the projection of populations under the various effects of density dependence and stochasticity. Demography_Lab is an educational tool for teaching Population Ecology aspiring to cover such a wide range of objectives. The application uses stochastic models to evaluate the future of populations. Demography_Lab 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‐rich, with a complex density‐dependence structure and detailed effects of the different sources of stochasticity. Demography_Lab 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.
机译:人口生态培训要求可扩展的应用程序,能够在密度依赖性和随机性的各种影响下从基本概念开始到群体的投影。 Demopach_Lab是一种教育人口生态学的教育工具,以涵盖这种广泛的目标。该应用程序使用随机模型来评估人口的未来。 Demopach_Lab可以适应各种生命周期,可以构建具有和没有年龄或阶段结构的人群模型。差分方程用于结构化群体的非结构化群体和矩阵模型。两种类型的模型在离散时间内运行。模型可以非常简单,构建了非常有限的人口统计信息或富有的参数,具有复杂的密度依赖性结构和不同的随机源的详细效果。 Demograph_Lab允许确定性投影,渐近分析,对人口统计参数的置信区间的提取,以及随机投影。随机群体增长使用多达三个随机来源评估:在获得投影矩阵时,环境和人口统计学同意性和采样误差。用户可以完全控制随机性对生命速率的效果。可以为每个生命速率独立地评估三种速度源的效果。用户还对密度依赖性完全控制。它可以作为控制群体中的个体数量的天花板种群尺寸包括在内,或者可以针对每个生命速度进行独立评估。可以为渐近人口增长率或灭绝概率进行敏感性分析。响应于生命速率的变化,以及响应于密度依赖性和环境随机性强度的变化,可以评估消光概率的弹性。

著录项

  • 期刊名称 Ecology and Evolution
  • 作者

    Julio Arrontes;

  • 作者单位
  • 年(卷),期 2021(11),5
  • 年度 2021
  • 页码 1940–1956
  • 总页数 17
  • 原文格式 PDF
  • 正文语种
  • 中图分类
  • 关键词

    机译:人口剧性;环境随机性;矩阵模型;人口模型;采样误差;敏感性分析;随机模型;
  • 入库时间 2022-08-21 12:18:36

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