Evaluating the Small Population Paradigm for Rare Large-Bodied Woodpeckers, with Implications for the Ivory-billed Woodpecker

Six large-bodied, ≥ 120 g, woodpecker species are listed as near-threatened to critically endangered by the International Union for Conservation of Nature (IUCN). The small population paradigm assumes that these populations are likely to become extinct without an increase in numbers, but the combined influences of initial population size and demographic rates, i.e., annual adult survival and fecundity, may drive population persistence for these species. We applied a stochastic, stage-based single-population model to available demographic rates for Dryocopus and Campephilus woodpeckers. In particular, we determined the change in predicted extinction rate, i.e., proportion of simulated populations that went extinct within 100 yr, to concomitant changes in six input parameters. To our knowledge, this is the first study to evaluate the combined importance of initial population size and demographic rates for the persistence of large-bodied woodpeckers. Under a worse-case scenario, the median time to extinction was 7 yr (range: 1–32). Across the combinations of other input values, increasing initial population size by one female induced, on average, 0.4%–3.2% (range: 0%–28%) reduction in extinction rate. Increasing initial population size from 5–30 resulted in extinction rates < 0.05 under limited conditions: (1) all input values were intermediate, or (2) Allee effect present and annual adult survival ≥ 0.8. Based on our model, these species can persist as rare, as few as five females, and thus difficult-to-detect, populations provided they maintain ≥ 1.1 recruited females annually per adult female and an annual adult survival rate ≥ 0.8. Athough a demographic-based population viability analysis (PVA) is useful to predict how extinction rate changes across scenarios for life-history attributes, the next step for modeling these populations should incorporate more easily acquired data on changes in patch occupancy to make predictions about patch colonization and extinction rates.