Effect of information availability on assessment and designation of species at risk.
Information required to evaluate the extent to which species are at risk of extinction is usually limited and characterized as highly uncertain. In this context, we define information availability as the presence or absence of information used to determine the value of an ecological variable. We examined which of three hypothetical approaches best matched how levels of risk are assigned to species: (1) precautionary approach in which analysts designate levels of risk regardless of the amount of information available, (2) worst-case approach in which analysts assign the maximum level of risk possible from the criteria, and (3) insurance approach in which analysts assign poorly known species to a high-risk category when little information is available. We used the quantitative assessment criteria of the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) as a case study. We created a binary (0/1) matrix of all 2.4192 × 10(7) logical combinations of available information for the 14 ecological variables included in the quantitative criteria. We processed each combination of information availability represented in the matrix with a computer algorithm designed to emulate COSEWIC decision-making rules. Low information availability was associated with a relatively high frequency of not being able to assign a candidate taxon to a risk category, which does not follow the precautionary principle. Information availability and the level of risk assigned to species were directly related, which is associated with the worst-case approach, and counter to the insurance approach. Our results suggest that information availability can have a major effect on the level of risk assigned to a species. We recommend a conscious determination of whether such effects are desired, and we recommend the development of methods to explicitly characterize and incorporate information availability and other sources of uncertainty in decision-making processes.
Lukey
James R
JR
Department of Integrative Biology, University of Guelph, 50 Stone Road East, Guelph, ON N1G 2W1 Canada. jlukey@uoguelph.ca
Crawford
Stephen S
SS
Gillis
Daniel
D
D000465:Algorithms; D002170:Canada; D003247:Conservation of Natural Resources / Q000379:methods* / Q000706:statistics & numerical data; D003625:Data Collection / Q000706:statistics & numerical data; D017753:Ecosystem; D056727:Endangered Species; D012107:Research Design; D018570:Risk Assessment / Q000379:methods*; D013045:Species Specificity