Skip to main content

Advertisement

SpringerLink
Log in

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

  • Original Paper
  • Published:
Biodiversity and Conservation Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Alberta Biodiversity Monitoring Institute (2007) Terrestrial field data collection protocols, Version 2.1. Alberta Biodiversity Monitoring Program, Alberta, Canada. Available via DIALOG http://www.abmi.ca. Cited 24 April 2007

  • Alberta Natural Heritage Information Centre (2006a) Bird tracking list. Available via DIALOG http://tprc.alberta.ca/parks/heritageinfocentre/default.aspx. Cited 1 December 2007

  • Alberta Natural Heritage Information Centre (2006b) Plant tracking and watch lists. Available via DIALOG http://tprc.alberta.ca/parks/heritageinfocentre/default.aspx. Cited 1 December 2007

  • Archaux F, Bergès L (2008) Optimising vegetation monitoring. A case study in a French lowland forest. Environ Monit Assess 141:19–25. doi:10.1007/s10661-007-9874-0

    Article  PubMed  Google Scholar 

  • Biggs BG (2000) What is significant—Wollemi pine or the southern rushes? Ann Mo Bot Gard 87(1):72–80. doi:10.2307/2666210

    Article  Google Scholar 

  • Buckland ST, Magurran AE, Green RE, Fewster RM (2005) Monitoring change in biodiversity through composite indices. Philos Trans R Soc B-Biol Sci 360(1454):243–254

    Article  CAS  Google Scholar 

  • Butchart SHM, Stattersfield AJ, Baillie J, Bennun LA, Stuart SN, Akcakaya HR, Hilton-Taylor C, Mace GM (2005) Using Red List Indices to measure progress towards the 2010 target and beyond. Philos Trans R Soc B-Biol Sci 360(1454):255–268

    Article  CAS  Google Scholar 

  • Ceballos G, Ehrlich PR (2002) Mammal population losses and the extinction crisis. Science 296(5569):904–907. doi:10.1126/science.1069349

    Article  PubMed  CAS  Google Scholar 

  • Clarke RT, Murphy JF (2006) Effects of locally rare taxa on the precision and sensitivity of RIVPACS bioassessment of freshwaters. Freshw Biol 51(10):1924–1940. doi:10.1111/j.1365-2427.2006.01611.x

    Article  Google Scholar 

  • Drapeau P, Leduc A, McNeil R (1999) Refining the use of point counts at the scale of individual points in studies of bird-habitat. J Avian Biol 30(4):367–382. doi:10.2307/3677009

    Article  Google Scholar 

  • Duro D, Coops NC, Wulder MA, Han T (2007) Development of a large area biodiversity monitoring system driven by remote sensing. Prog Phys Geogr 31(3):235–260. doi:10.1177/0309133307079054

    Article  Google Scholar 

  • Edwards TC, Cutler DR, Geiser L, Alegria J, McKenzie D (2004) Assessing rarity of species with low detectability: lichens in Pacific Northwest forests. Ecol Appl 14(2):414–424. doi:10.1890/02-5236

    Article  Google Scholar 

  • Fairweather PG (1991) Statistical power and design requirements for environmental monitoring. Aust J Mar Freshwater Res 42(5):555–567. doi:10.1071/MF9910555

    Article  Google Scholar 

  • Favreau JM, Drew CA, Hess GR, Rubino MJ, Koch FH, Eschelbach KA (2006) Recommendations for assessing the effectiveness of surrogate species approaches. Biodivers Conserv 15(12):3949–3969. doi:10.1007/s10531-005-2631-1

    Article  Google Scholar 

  • Field SA, Tyre AJ, Jonzen N, Rhodes JR, Possingham HP (2004) Minimizing the cost of environmental management decisions by optimizing statistical thresholds. Ecol Lett 7(8):669–675. doi:10.1111/j.1461-0248.2004.00625.x

    Article  Google Scholar 

  • Fox DR (2001) Environmental power analysis—a new perspective. Environmetrics 12(5):437–449. doi:10.1002/env.470

    Article  Google Scholar 

  • Gaston KJ (1994) Rarity. Chapman & Hall, London

    Google Scholar 

  • Gaston KJ, Fuller RA (2008) Commonness, population depletion and conservation biology. Trends Ecol Evol 23(1):14–19. doi:10.1016/j.tree.2007.11.001

    Article  PubMed  Google Scholar 

  • Haefner JW (2005) Modeling biological systems, 2nd edn. Springer, New York

    Google Scholar 

  • Henry PY, Lengyel S, Nowicki P, Julliard R, Clobert J, Čelik T, Gruber B, Schmeller DS, Babij V, Henle K (2008) Integrating ongoing biodiversity monitoring: potential benefits and methods. Biodivers Conserv 17(14):3357–3382. doi:10.1007/s10531-008-9417-1

    Article  Google Scholar 

  • Huggard DJ, Dunsworth GB, Herbers JR, Klenner W, Kremsater LL, Serrouya R (2006) Monitoring ecological representation in currently non-harvestable areas: four British Columbia case studies. For Chron 82(3):383–394

    Google Scholar 

  • Karr JR, Chu EW (1999) Restoring life in running waters: better biological monitoring. Island Press, Washington, DC

    Google Scholar 

  • Lamb EG, Bayne E, Holloway G, Schieck J, Boutin S, Herbers J, Haughland DL (2009) Indices for monitoring biodiversity change: are some more effective than others? Ecol Indicators 9(3):432–444. doi:10.1016/j.ecolind.2008.06.001

    Article  Google Scholar 

  • Legg CJ, Nagy L (2006) Why most conservation monitoring is, but need not be, a waste of time. J Environ Manag 78(2):194–199. doi:10.1016/j.jenvman.2005.04.016

    Article  Google Scholar 

  • Lengyel S, Deri E, Varga Z, Horvath R, Tothmeresz B, Henry PY, Kobler A, Kutnar L, Babij V, Seliskar A, Christia C, Papastergiadou E, Gruber B, Henle K (2008a) Habitat monitoring in Europe: a description of current practices. Biodivers Conserv 17(14):3327–3339. doi:10.1007/s10531-008-9395-3

    Article  Google Scholar 

  • Lengyel S, Kobler A, Kutnar L, Framstad E, Henry PY, Babij V, Gruber B, Schmeller D, Henle K (2008b) A review and framework for the integration of biodiversity monitoring at the habitat level. Biodivers Conserv 17(14):3341–3356. doi:10.1007/s10531-008-9359-7

    Article  Google Scholar 

  • Liang KY, Zeger SL (1986) Longitudinal data analysis using generalized linear models. Biometrika 73(1):13–22. doi:10.1093/biomet/73.1.13

    Article  Google Scholar 

  • Lindenmayer DB, Manning A, Smith PL, Possingham HP, Fischer J, Oliver I, McCarthy MA (2002) The focal species approach and landscape restoration: a critique. Conserv Biol 16(2):338–345. doi:10.1046/j.1523-1739.2002.00450.x

    Article  Google Scholar 

  • Lotz A, Allen CR (2007) Observer bias in anuran call surveys. J Wildl Manag 71(2):675–679. doi:10.2193/2005-759

    Article  Google Scholar 

  • MacKenzie DI, Nichols JD, Sutton N, Kawanishi K, Bailey LL (2005a) Improving inferences in population studies of rare species that are detected imperfectly. Ecology 86(5):1101–1113. doi:10.1890/04-1060

    Article  Google Scholar 

  • MacKenzie DI, Nichols JD, Pollock KH, Royle JA, Bailey LL, Hines JE (2005b) Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Academic Press, Amsterdam

    Google Scholar 

  • Manley PN, Zielinski WJ, Schlesinger MD, Mori S (2004) Evaluation of a multiple-species approach to monitoring species at the ecoregional scale. Ecol Appl 14(1):296–310. doi:10.1890/02-5249

    Article  Google Scholar 

  • Manley PN, Schlesinger MD, Roth JK, Van Horne B (2005) A field-based evaluation of a presence-absence protocol for monitoring ecoregional-scale biodiversity. J Wildl Manag 69(3):950–966. doi:10.2193/0022-541X(2005)069[0950:AFEOAP]2.0.CO;2

    Article  Google Scholar 

  • Mapstone BD (1995) Scalable decision rules for environmental-impact studies—effect size, Type-I, and Type-II errors. Ecol Appl 5(2):401–410. doi:10.2307/1942031

    Article  Google Scholar 

  • Marsh DM, Trenham PC (2008) Current trends in plant and animal population monitoring. Conserv Biol 22(3):647–655. doi:10.1111/j.1523-1739.2008.00927.x

    Article  PubMed  Google Scholar 

  • McCune B, Dey JP, Peck JE, Cassell D, Heiman K, Will-Wolf S, Neitlich PN (1997) Repeatability of community data: species richness versus gradient scores in large-scale lichen studies. Bryologist 100(1):40–46

    Google Scholar 

  • Menard S (2000) Coefficients of determination for multiple logistic regression. Am Stat 54(1):17–24. doi:10.2307/2685605

    Article  Google Scholar 

  • Moss EH (1994) Flora of Alberta. In: Packer JG (ed), 2nd edn. University of Toronto Press, Toronto

  • Nichols JD, Williams BK (2006) Monitoring for conservation. Trends Ecol Evol 21(12):668–673. doi:10.1016/j.tree.2006.08.007

    Article  PubMed  Google Scholar 

  • Nielsen SE, Bayne EM, Schieck J, Herbers J, Boutin S (2007) A new method to estimate species and biodiversity intactness using empirically derived reference conditions. Biol Conserv 137(3):403–414. doi:10.1016/j.biocon.2007.02.024

    Article  Google Scholar 

  • Plattner M, Birrer S, Weber D (2004) Data quality in monitoring plant species richness in Switzerland. Community Ecol 5(1):135–143. doi:10.1556/ComEc.5.2004.1.13

    Article  Google Scholar 

  • Prendergast JR, Quinn RM, Lawton JH, Eversham BC, Gibbons DW (1993) Rare species, the coincidence of diversity hotspots and conservation strategies. Nature 365(6444):335–337. doi:10.1038/365335a0

    Article  Google Scholar 

  • Purvis A, Hector A (2000) Getting the measure of biodiversity. Nature 405(6783):212–219. doi:10.1038/35012221

    Article  PubMed  CAS  Google Scholar 

  • Roy DB, Rothery P, Brereton T (2007) Reduced-effort schemes for monitoring butterfly populations. J Appl Ecol 44(5):993–1000. doi:10.1111/j.1365-2664.2007.01340.x

    Article  Google Scholar 

  • Secretariat of the Convention on Biological Diversity (2005) Handbook of the convention on biological diversity including its cartagena protocol on biosafety, 3rd edn. UNEP, Montreal

    Google Scholar 

  • Simberloff DA (1998) Flagships, umbrellas, and keystones: is single-species management passé in the landscape era? Biol Conserv 83(3):247–257. doi:10.1016/S0006-3207(97)00081-5

    Article  Google Scholar 

  • Stadt JJ, Schieck J, Stelfox HA (2006) Alberta biodiversity monitoring program—monitoring effectiveness of sustainable forest management planning. Environ Monit Assess 121(1):33–46. doi:10.1007/s10661-005-9075-7

    Article  PubMed  Google Scholar 

  • StataCorp (2005) Stata statistical software: release 9. StataCorp, College Station

    Google Scholar 

  • Strand GH (1996) Detection of observer bias in ongoing forest health monitoring programmes. Can J Res 26(9):1692–1696. doi:10.1139/x26-191

    Article  Google Scholar 

  • Taylor BL, Gerrodette T (1993) The uses of statistical power in conservation biology: the Vaquita and Northern Spotted Owl. Conserv Biol 7(3):489–500. doi:10.1046/j.1523-1739.1993.07030489.x

    Article  Google Scholar 

  • Thompson AA, Mapstone BD (1997) Observer effects and training in underwater visual surveys of reef fishes. Mar Ecol Prog Ser 154:53–63. doi:10.3354/meps154053

    Article  Google Scholar 

  • Urquhart NS, Kincaid TM (1999) Designs for detecting trend from repeated surveys of ecological resources. J Agric Biol Environ Stat 4(4):404–414

    Article  Google Scholar 

  • Van Strien AJ, Vande Pavert R, Moss D, Yates TJ, Van Swaay CAM, Vos P (1997) The statistical power of two butterfly monitoring schemes to detect trends. J Appl Ecol 34(3):817–828. doi:10.2307/2404926

    Article  Google Scholar 

  • Yoccoz NG, Nichols JD, Boulinier T (2001) Monitoring of biological diversity in space and time. Trends Ecol Evol 16(8):446–453. doi:10.1016/S0169-5347(01)02205-4

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Renewable Resources, University of Alberta, 751 General Services Building, Edmonton, AB, T6G 2H1, Canada

    Scott E. Nielsen

  2. Department of Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E9, Canada

    Diane L. Haughland, Erin Bayne & Jim Schieck

  3. Alberta Biodiversity Monitoring Institute, Alberta Research Council, P.O. Bag 4000, Vegreville, AB, T9C 1T4, Canada

    Jim Schieck

Authors
  1. Scott E. Nielsen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Diane L. Haughland
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Erin Bayne
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jim Schieck
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Scott E. Nielsen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nielsen, S.E., Haughland, D.L., Bayne, E. et al. Capacity of large-scale, long-term biodiversity monitoring programmes to detect trends in species prevalence. Biodivers Conserv 18, 2961–2978 (2009). https://doi.org/10.1007/s10531-009-9619-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10531-009-9619-1

Keywords

Search

Navigation