Population modelling & methods

Demography is rooted within actuarial science. As such, demographic research is rather quantitative. Thus, tracking statistical progress in demographic modelling has become challenging for a range of ecologists and conservation managers. The lack of connection between demographic modelling techniques and biologists has hindered the further combination of ecological/evolutionary questions and robust demographic models in the field.

The SalGo team leads the development of open-access R routine and packages (e.g. IPMpack, ipmRR-Age, R-COMPADRE) that allow users to relatively easily and reliably apply demographic techniques to the analyses of laboratory and field collected data of animals, plants, and microbes. These approaches help researchers answer a wide range of questions, from conservation biology and management, to ecology, evolution and economics.

life cycle of cryptantha flava a and carrichtera annua b used to study effects of climate change in desert plants salguero gomez et al ptrsb


The SalGo team also runs frequent workshops on the development, analyses and interpretation of demographic modelling techniques (e.g. integral projection models, life tables, matrix population models, integrated population models) both nationally and internationally. If you would like to host one of such events, please contact us with details on the number of potential participants, venue, and economic support - we charge flight, accommodation, meals and a teaching fee (the latter is waived for developing countries). We are particularly interested in running these activities in areas of the globe where less demographic knowledge is available.

Journal of Ecology 2010

SalGo team members:

  • Heitor Campos de Sousa
  • Fiona Chong
  • Aldo Compagnoni
  • John Jackson
  • Maja Kajin
  • Sam Levin
  • Courtenay Ray
  • Rob Salguero-Gomez
  • Gabriel Santos


Selected collaborators:

Selected Publications

Salguero-Gómez R & Gamelon M. In press. Demographic Methods across the Tree of Life. Oxford University Press

Levin SCompagnoni A, Childs D, Evers S, Knight T* & Salguero-Gómez R*. ipmr: Flexibly implement Integral Projection Models in R. Methods in Ecology and Evolution

Logofet D* & Salguero-Gómez R*. 2021. Novel challenges and opportunities in the theory and practice of matrix population modelling. Ecological Modelling 443, 109457 DOI 10.1016/j.ecolmodel.2021.109457

Takada T, Kawai Y & Salguero-Gómez R. A cautionary note on elasticity analyses in a ternary plot using randomly generated population matrices. Population Ecology 1-11. DOI 10.1007/s10144-018-0619-4

Paniw M, Quintana-Ascencio P, Ojeda F & Salguero-Gómez R. 2017. Accounting for uncertainty in dormant life stages in stochastic demographic models. Oikos 6, 900-909. DOI 10.1111/oik.03696

Metcalf CJE, Ellner SP, Childs DZ, Salguero-Gómez R, Merow C, McMahon SM, Jongejans E & Rees M. Statistical modelling of annual variation for stochastic population dynamics using integral projection models. Methods in Ecology and Evolution 6, 1007-1017. DOI 10.1111/2041-210X.12405

Merow C, Dahlgren J, Metcalf CJE, Childs D, Evans MEK, Jongejans E, Metcalf CJE, Record S, Rees M, Salguero-Gómez R & McMahon S. 2014. Advancing population ecology with integral projection models: a practical guide. Methods in Ecology & Evolution 2, 99-110. Editor’s monthly publication choice. DOI 10.1111/2041-210X.12146

Metcalf CJE, McMahon S, Salguero-Gómez R, & Jongejans E. 2013. IPMpack: an R package for integral projection models. Methods in Ecology & Evolution 4, 195-200. Editor’s monthly publication choice DOI 10.1111/2041-210x.12001

Caswell H, Salguero-Gómez R. 2013. Age, stage, and senescence in plants. Journal of Ecology 3, 585-595. DOI 10.1111/1365-2745.12088


*Shared senior author