Biodiversity and Conservation

, Volume 17, Issue 14, pp 3417–3429 | Cite as

Process and measurement errors of population size: their mutual effects on precision and bias of estimates for demographic parameters

  • Thomas HovestadtEmail author
  • Piotr Nowicki
Original Paper


Knowing the parameters of population growth and regulation is fundamental for answering many ecological questions and the successful implementation of conservation strategies. Moreover, detecting a population trend is often a legal obligation. Yet, inherent process and measurement errors aggravate the ability to estimate these parameters from population time-series. We use numerical simulations to explore how the lengths of the time-series, process and measurement error influence estimates of demographic parameters. We first generate time-series of population sizes with given demographic parameters for density-dependent stochastic population growth, but assume that these population sizes are estimated with measurement errors. We then fit parameters for population growth, habitat capacity, total error and long-term trends to the ‘measured’ time-series data using non-linear regression. The length of the time-series and measurement error introduce a substantial bias in the estimates for population growth rate and to a lesser degree on estimates for habitat capacity, while process error has little effect on parameter bias. The total error term of the statistical model is dominated by process error as long as the latter is larger than the measurement error. A decline in population size is difficult to document as soon as either error becomes moderate, trends are not very pronounced, and time-series are short (<10–15 seasons). Detecting an annual decline of 1% within 6-year reporting periods, as required for the European Union for the species of Community Interest, appears unachievable.


Population parameters Time series Temporal trend Statistical testing Policy implications Conservation 



The study has been financially supported by the EU within its projects EVK2-CT-2001-00126 (MacMan, and STREP 006463 (EuMon, We thank Achim Poethke for helpful discussion while preparing this manuscript as well as Dirk Schmeller and an anonymous reviewer for valuable suggestions for improvement.


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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.Field Station FabrikschleichachUniversity of WürzburgRauhenebrachGermany
  2. 2.Institute of Environmental SciencesJagiellonian UniversityKrakowPoland

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