Repeatability of Community Data: Species Richness versus Gradient Scores in Large-Scale Lichen Studies

Abstract

Repeated ecological assessments based on permanent plot data require sufficient data quality to detect a signal of change against a background of noise (sampling error of various kinds). We analyzed several components of error in the time-constrained method for sampling lichen communities used by the Forest Health Monitoring program: between-crew (Technicians), crew-to-expert, between-expert, and seasonal variation. Data were from the southeastern United States and Oregon. Two types of dependent variables were used: species richness and scores on lichen community gradients (responses to climatic and air quality gradients). Gradient scores were repeatable to within 2-10% for experts and technicians alike and did not differ between those groups. Species richness is much more difficult to estimate reliably. Despite relatively low species capture by technicians, the high repeatability in gradient scores demonstrates the statis- tical redundancy in information provided by various lichen species. These results imply that re- peated assessments of species richness will contain considerable observer error, but that shifts in community composition may nevertheless be detected reliably.