Optimizing inventories of diverse sites: insights from Barro Colorado Island birds

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Summary 1. Diverse sites have long‐attracted ecologists, yet the overwhelming variety of species can confound attempts to enumerate species richness. Various predictive methods estimate species richness by comparing the rate at which species are first detected with the rate at which they are detected again, yielding richness estimates of known precision without exhaustive sampling. 2. While frequently used for arthropods, predictive methods are rarely applied to vertebrate surveys where species identity is often a priority. Expressing observed richness as a function of estimated richness, an estimate of survey completeness can be derived, offering the potential for inventories of standardized precision for comparison and further analysis. 3. To realize this potential, I conducted 402 h of bird surveys on Barro Colorado Island (Panama) and performed a series of retrospective analyses to address three questions: (i) How much effort is required to achieve complete inventories (maximum completeness)? (ii) What is the least amount of effort required to yield robust richness estimates (maximum efficiency)? and (iii) How much effort is required to optimize sampling, balancing completeness and efficiency? 4. Whereas the richness estimate for all species required thirty 6‐h samples to attain maximum completeness, once migrants, waterbirds and non‐forest‐dependent species were excluded, the richness of forest‐dependent residents could be estimated to the same precision with fifteen samples and to 80% completeness with four samples. 5. Of the 186 bird species detected, 70 represented unique or duplicate records, seen in only one or two sampling periods. These low detectability species were dominated by migrants (28) and raptors (14) and also included seven waterbirds, five nocturnal species and four aerial foragers, justifying the widespread practice of excluding these groups from surveys of forest assemblages. 6. In addition to demonstrating the reliability of predictive approaches, this study demonstrates the practicality of results‐based stopping rules for sampling diverse sites, especially for targeted groups of species. Combining predictive methods with targeted sampling represents an efficient and rigorous design, increasing the number of sites that can be sampled and enhancing the overall power and value of the study.