• distance sampling;
  • double-observer method;
  • management policy;
  • monitoring protocol design;
  • population estimation;
  • simulation;
  • survey method


  • 1
    Methods papers play a crucial role in advancing applied ecology. Counting organisms, in particular, has a rich history of methods development with many key advances both in field sampling and the treatment of resulting data.
  • 2
    Most counts, however, have associated errors due to portions of the population of interest being unavailable for detection (e.g. target population not fully sampled; individuals present but not detectable), detection mistakes (e.g. detectable individuals missed; non-existent individuals recorded), or erroneous counts (e.g. large groups miscounted; individuals misidentified).
  • 3
    Developments in field methods focus on reducing biases in the actual counts. Simultaneously, statisticians have developed many methods for improving inference by quantifying and correcting for biases retrospectively. Prominent examples of methods used to account for detection errors include distance sampling and multiple-observer methods.
  • 4
    Simulations, in which population characteristics are set by the investigator, provide an efficient means of testing methods. With good estimates of sampling biases, computer simulations can be used to evaluate how much a given counting problem affects estimates of parameters such as population size and decline, thereby allowing applied ecologists to test the efficacy of sampling designs. Combined with cost estimates for each field method, such models would allow the cost-effectiveness of alternative protocols to be assessed.
  • 5
    Synthesis and applications. Major advances are likely to come from research that looks for systematic patterns, across studies, in the effects of different types of bias and assumption violation on the ecological conclusions drawn. Specifically, determining how often, and under what circumstances, errors contribute to poor management and policy would greatly enhance future application of ecological knowledge.