Biodiversity and Conservation

, Volume 18, Issue 11, pp 2961–2978

Capacity of large-scale, long-term biodiversity monitoring programmes to detect trends in species prevalence

  • Scott E. Nielsen
  • Diane L. Haughland
  • Erin Bayne
  • Jim Schieck
Original Paper

DOI: 10.1007/s10531-009-9619-1

Cite this article as:
Nielsen, S.E., Haughland, D.L., Bayne, E. et al. Biodivers Conserv (2009) 18: 2961. doi:10.1007/s10531-009-9619-1

Abstract

There is a critical need for monitoring programmes to assess change or trends in species status to inform conservation. A key aspect in developing such programmes is evaluating their statistical power—the ability to detect a real change. Here we examine the capacity of a broad-scale biodiversity monitoring programme in Alberta, Canada to measure changes in species prevalence. Using observed variation in detectability and prevalence for 252 species monitored at 85 sites, we simulated 3% annual declines and evaluated sample size (6 different sizes) and length of monitoring (5 different durations) necessary to detect change with a 90% certainty (power) at an α of 0.1. Our results suggest that after four monitoring cycles (e.g., 20 years for a 5-year cycle) a power of 90% can be expected for 99% of species when monitoring 1,625 sites, 65% of species for 300 sites, 27% of species for 75 sites, and 8% of species for 25 sites. We found that 66% detectability and 50% prevalence were needed to ensure that 3% annual change is detected at 50 sites over a 20-year period. Our results demonstrate that broad-scale monitoring programmes cannot effectively detect trends in all species at all spatial scales. The time period and spatial scale necessary to detect a real change at a specified level needs to be provided to stakeholders to ensure the short-term success of biodiversity monitoring programmes and to ensure that the most robust indicators of biodiversity are selected.

Keywords

AlbertaBiodiversity monitoringDetectabilityPrevalenceStatistical power

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Scott E. Nielsen
    • 1
  • Diane L. Haughland
    • 2
  • Erin Bayne
    • 2
  • Jim Schieck
    • 2
    • 3
  1. 1.Department of Renewable ResourcesUniversity of AlbertaEdmontonCanada
  2. 2.Department of Biological SciencesUniversity of AlbertaEdmontonCanada
  3. 3.Alberta Biodiversity Monitoring InstituteAlberta Research CouncilVegrevilleCanada