ESTIMATING THE EFFECTIVENESS OF FURTHER SAMPLING IN SPECIES INVENTORIES

Estimators of the number of additional species expected in the next al l samples offer a potentially important tool for improving cost-effect iveness of species inventories but are largely untested. We used Monte Carlo methods to compare ii such estimators, across a range of commun ity structures and sampling regimes, and validated our results, where possible, using empirical data from vascular plant and beetle inventor ies from Glacier National Park, Montana, USA. We found that B. Efron a nd R. Thisted's 1976 negative binomial estimator was most robust to di fferences in community structure and that it was among the most accura te estimators when sampling was from model communities with structures resembling the large, heterogeneous communities that are the likely t argets of major inventory efforts. Other estimators may be preferred u nder specific conditions, however. For example, when sampling was from model communities with highly even species-abundance distributions, e stimates based on the Michaelis-Menten model were most accurate; when sampling was from moderately even model communities with S = 10 specie s or communities with highly uneven species-abundance distributions, e stimates based on Gleason's (1922) species-area model were most accura te. We suggest that use of such methods in species inventories can hel p improve cost-effectiveness by providing an objective basis for redir ecting sampling to more-productive sites, methods, or time periods as the expectation of detecting additional species becomes unacceptably l ow.