Integral projection models perform better for small demographic data sets than matrix population models: a case study of two perennial herbs
Article first published online: 1 OCT 2009
© 2009 The Authors. Journal compilation © 2009 British Ecological Society
Journal of Applied Ecology
Volume 46, Issue 5, pages 1048–1053, October 2009
How to Cite
Ramula, S., Rees, M. and Buckley, Y. M. (2009), Integral projection models perform better for small demographic data sets than matrix population models: a case study of two perennial herbs. Journal of Applied Ecology, 46: 1048–1053. doi: 10.1111/j.1365-2664.2009.01706.x
- Issue published online: 1 OCT 2009
- Article first published online: 1 OCT 2009
- Received 18 May 2009; accepted 3 August 2009 Handling Editor: Marc Cadotte
- integral projection model;
- matrix population model;
- plant population dynamics;
- population growth rate;
- population viability analysis
1. Matrix population models are widely used to describe population dynamics, conduct population viability analyses and derive management recommendations for plant populations. For endangered or invasive species, management decisions are often based on small demographic data sets. Hence, there is a need for population models which accurately assess population performance from such small data sets.
2. We used demographic data on two perennial herbs with different life histories to compare the accuracy and precision of the traditional matrix population model and the recently developed integral projection model (IPM) in relation to the amount of data.
3. For large data sets both matrix models and IPMs produced identical estimates of population growth rate (λ). However, for small data sets containing fewer than 300 individuals, IPMs often produced smaller bias and variance for λ than matrix models despite different matrix structures and sampling techniques used to construct the matrix population models.
4.Synthesis and applications. Our results suggest that the smaller bias and variance of λ estimates make IPMs preferable to matrix population models for small demographic data sets with a few hundred individuals. These results are likely to be applicable to a wide range of herbaceous, perennial plant species where demographic fate can be modelled as a function of a continuous state variable such as size. We recommend the use of IPMs to assess population performance and management strategies particularly for endangered or invasive perennial herbs where little demographic data are available.