In This Article Expand or collapse the "in this article" section Methods in Population Dynamics

  • Introduction
  • General Overviews
  • Demographic Rates
  • Unstructured Populations
  • Species Interactions
  • Spatial Models
  • Software Packages

Ecology Methods in Population Dynamics
Cory Merow
  • LAST REVIEWED: 27 July 2016
  • LAST MODIFIED: 27 July 2016
  • DOI: 10.1093/obo/9780199830060-0158


Methods in population dynamics aim to describe and understand the abundance or (st)age structure of individuals in a population. St(age) structure is critical for describing how different individuals’ fate (e.g., survival, reproductive output) depends on their state (e.g., size, age). Processes of birth, growth, and death define the demographic aspects of change in abundance or structure over time. Dispersal connects populations and introduces spatial patterns. Methods in population dynamics aim to disentangle generalities in these processes, and how they vary in time and space, amidst imperfect detection of the individuals under study (e.g., some birds are not caught each year) or the inability to directly observe the processes (e.g., dispersal). Approaches may aim to simply describe the temporal or spatial patterns of the population, characterize the processes underlying population dynamics, or synthesize these processes to describe or predict population dynamics. Advances in personal computing resources and familiarity with software platforms such as R, Matlab, and BUGS in the 21st century has shifted the focus from predominantly analytical methods to statistical approaches. Hence, much of modern population ecology is concerned with data analysis, extracting trends in vital rates, abundance, or population structure and inferring their drivers. Due to the practical limitations of studying entire populations over large spatial areas, many studies focus on a handful of populations and a subset of individuals from them. Similarly, studies focus on time scales that may be short (often one to five years) relative to the lifespan of the study species. Consequently, methods focus on ways to extract patterns from potentially noisy subsamples from populations, while accounting for their natural variability (e.g., differences driven by variable weather across years). Rather than focus on the most influential papers in population dynamics, this article focuses on the resources that describe how to use the quantitative methods on which these papers are built, in an attempt to guide researchers toward the appropriate tools for their data and questions. Topics below are organized according to the types of information that one might have for their study species, as the methods are typically more specific to data type than to the subfield of ecology on which the study focuses.

General Overviews

There are many widely used introductions to population dynamics that offer different strengths depending on reader’s quantitative background and intended applications. Introductory textbooks such as Silvertown and Charlesworth 2009 and Vandermeer and Goldberg 2013 focus on models with qualitative or analytical results and primarily form the basis for more theoretical studies. Much of modern population ecology is concerned with data analysis, extracting trends in abundance or structure and inferring their drivers. Turchin 2003 provides an accessible theoretical introduction to studying population dynamics aimed at researchers, while Gurney and Nisbet 1998 works through the mathematics of these models. Caswell 2001 is widely viewed as the authoritative text on stage-structured models (e.g., individuals’ growth, survival or reproduction depends on their age or size). Tuljapurkar and Caswell 1997 covers a similar range, but via more technical case studies. Morris and Doak 2002 contains some overlap with Caswell 2001 but is less technical and focuses on conservation applications, particularly population viability analysis (to assess extinction risk). Royle and Dorazio 2008 is a core resource for wildlife researchers, with a focus on models that use repeated observations of abundance or individuals that have been marked and recaptured.

  • Caswell, H. 2001. Matrix population models: Construction, analysis, and interpretation. Sunderland, MA: Sinauer.

    An authoritative book for methods in population projection modeling. It describes the technical aspects of modeling with a focus on examples and practical aspects. It is heavy on linear algebra but takes a readable tone. Examples use the Matlab programming language. Suitable for graduate courses.

  • Gurney, W. S. C., and R. M. Nisbet. 1998. Ecological dynamics. Oxford: Oxford Univ. Press.

    An accessible comprehensive overview of mathematical models of population dynamics that works through problems in detail. Suitable for graduate courses.

  • Morris, W., and D. Doak. 2002. Quantitative conservation biology: The theory and practice of population viability analysis. Sunderland, MA: Sinauer.

    A core textbook in conservation biology, suitable for undergraduate and graduate courses. The comprehensiveness is similar to Caswell 2001 but with a more applied focus, particularly toward population viability analysis (determining extinction risk).

  • Royle, J., and R. M. Dorazio. 2008. Hierarchical modelling and inference in ecology. San Diego, CA: Academic Press.

    A core textbook for technical aspects of modeling animal populations, especially using repeated observations of abundance or individuals that have been marked and recaptured. Uses the BUGS programming language to make Bayesian models more accessible.

  • Silvertown, J., and D. Charlesworth. 2009. Introduction to plant population biology. Hoboken, NJ: John Wiley.

    A general introduction to population biology suitable for undergraduates; modeling focuses on graphical approaches and algebra.

  • Tuljapurkar, S., and H. Caswell. 1997. Structured-population models in marine, terrestrial, and freshwater systems. New York: Chapman and Hall.

    DOI: 10.1007/978-1-4615-5973-3

    An overview of methods by a wide range of specialists, including stochastic models, density dependence, trophic interactions, and a variety of nonlinear models.

  • Turchin, P. 2003. Complex population dynamics: A theoretical/empirical synthesis. Princeton, NJ: Princeton Univ. Press.

    Describes theory and mathematical models, with a conceptual emphasis on population regulation (density-dependence) and a statistical emphasis on time series analysis. Suitable for a graduate course.

  • Vandermeer, J. H., and D. E. Goldberg. 2013. Population ecology: First principles. 2d ed. Princeton, NJ: Princeton Univ. Press.

    A general introduction to models for population dynamics suitable for undergraduates.

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