Journal of Ornithology

, Volume 152, Supplement 2, pp 409–418 | Cite as

Quantifying changes in abundance without counting animals: extensions to a method of fitting integrated population models

  • Stephen N. FreemanEmail author
  • Panagiotis Besbeas
Original Article


Integrated population modelling techniques combine information from population surveys and independent demographic studies to estimate population size, survival and productivity rates simultaneously. We review the development of the approach, and investigate further the potential to incorporate sources of population survey data other than those currently employed. Generally, the simpler the field protocol, the more data can be gathered; in the simplest case, only a list of species encountered when a site is surveyed might be recorded. We extend the integrated approach to the case of presence/absence survey data from species lists. We consider specifically the extent to which high-quality demographic data, used in conjunction with an ecologically sound model, may result in credible estimates of change and the drivers of it in the context of either counts or presence/absence survey data. We propose an approach to practical model fitting, applicable in either context, using standard software, and we illustrate its performance in practice. Examples are based on simulated data and records of species with very different trends and ecology, and they are used to compare approaches.


Demographic rates Generalized linear modelling Presence/absence data Profile likelihood Species lists 



The work of P.B. was supported by a BRFP-AUEB grant. The UKBMS is a joint partnership between Butterfly Conservation and the Centre for Ecology and Hydrology and is funded by a multi-agency consortium led by DEFRA. We are grateful to these organisations and to the volunteer recorders who contribute data to the UKBMS, and to Marc Kéry, Byron Morgan and the referees for comments leading to an improved manuscript.


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Copyright information

© Dt. Ornithologen-Gesellschaft e.V. 2011

Authors and Affiliations

  1. 1.Centre for Ecology and HydrologyCrowmarsh Gifford, WallingfordUK
  2. 2.School of Mathematics, Statistics and Actuarial ScienceThe UniversityCanterburyUK
  3. 3.Department of StatisticsAthens University of Economics and BusinessAthensGreece

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