title: Determination of the influence of dispersion pattern of pesticide-resistant individuals on the reliability of resistance estimates using different sampling plans.
abstract: Pesticide resistance monitoring includes resistance detection and subsequent documentation/ measurement. Resistance detection would require at least one (≥1) resistant individual(s) to be present in a sample to initiate management strategies. Resistance documentation, on the other hand, would attempt to get an estimate of the entire population (≥90%) of the resistant individuals. A computer simulation model was used to compare the efficiency of simple random and systematic sampling plans to detect resistant individuals and to document their frequencies when the resistant individuals were randomly or patchily distributed. A patchy dispersion pattern of resistant individuals influenced the sampling efficiency of systematic sampling plans while the efficiency of random sampling was independent of such patchiness. When resistant individuals were randomly distributed, sample sizes required to detect at least one resistant individual (resistance detection) with a probability of 0.95 were 300 (1%) and 50 (10% and 20%); whereas, when resistant individuals were patchily distributed, using systematic sampling, sample sizes required for such detection were 6000 (1%), 600 (10%) and 300 (20%). Sample sizes of 900 and 400 would be required to detect ≥90% of resistant individuals (resistance documentation) with a probability of 0.95 when resistant individuals were randomly dispersed and present at a frequency of 10% and 20%, respectively; whereas, when resistant individuals were patchily distributed, using systematic sampling, a sample size of 3000 and 1500, respectively, was necessary. Small sample sizes either underestimated or overestimated the resistance frequency. A simple random sampling plan is, therefore, recommended for insecticide resistance detection and subsequent documentation.
authors.affiliation: Department of Biology, University of Windsor, Ontario, Canada.
authors.forename: R
authors.initials: R
authors.lastname: Shah
authors.affiliation: Bio-Protection Research Centre, PO Box 84, Lincoln University 764, Christchurch, New Zealand.
authors.forename: S P
authors.initials: SP
authors.lastname: Worner
authors.affiliation: Bio-Protection Research Centre, PO Box 84, Lincoln University 764, Christchurch, New Zealand.
authors.forename: R B
authors.initials: RB
authors.lastname: Chapman
mesh_terms: D063147:Animal Distribution; D000818:Animals; D003198:Computer Simulation; D007300:Insect Control / Q000379:methods*; D007313:Insecta / Q000187:drug effects* / Q000502:physiology*; D007305:Insecticide Resistance; D007306:Insecticides / Q000494:pharmacology*; D011156:Population Density; D015203:Reproducibility of Results; D018401:Sample Size
chemical_list: D007306:Insecticides