The Peregrine population study in the French Jura mountains 1964–2016: use of occupancy modeling to estimate population size and analyze site persistence and colonization rates

Abstract

We summarize key results of the first 53 years of one of the longest-running avian population studies in the world, on the Peregrine Falcon (Falco peregrinus), in the French Jura mountains (12,714 km 2 ), launched in 1964. A total of 449 cliff sites in 338 potential Peregrine territories were surveyed: 287 (85%) of these territories were occupied by an adult pair at least once, while in 51 (15%) we never detected an adult pair. Most sites were visited several times during a breeding season to survey occupancy and later fecundity, but the proportion of sites visited was highly variable over the years. We highlight the power of the Bayesian implementation of site-occupancy models (MacKenzie et al. 2002, 2003) to analyze data from raptor population studies: to correct population size estimates for sites not visited in a given year and for the biasing effects of preferential sampling (when better sites are more likely to be checked). In addition, these models allow estimation and modeling of the site-level persistence and colonization rates, which can provide important clues about drivers of population dynamics, even without individually marking any birds. Changes in the dynamics rates may serve as early-warning signals for subsequent population declines. Since 1964, the observed number of adult pairs varied between 17 in 1972 and 196 in 2008, but the proportion of sites visited increased from 43% in 1964 to 80–90% after 2002. Hence, this raw population total must be an underestimate. We found strong evidence for preferential sampling in our study. Correcting for this, we estimated 56 pairs in 1964, after which the population dropped to a minimum of 18 in 1972, but then recovered rapidly, leveling off somewhat around 1995 and reaching a maximum of 200–210 adult pairs during 2000–2012. This was then followed by a decline to 170–190 pairs. In any one year, the raw counts underestimated the true population size by 5–39% (mean 11%), due to sites not being visited (this correction ignores imperfect detection though). Site persistence rates declined from 78% to less than 60% during 1967–1972, and then increased rapidly to over 90% during 1980–1990, suggesting that once pesticide effects vanished, individual survival probability increased rapidly and as a consequence also site persistence. Since the 1990s, persistence has declined slowly, which may indicate decreasing adult survival. In contrast, colonization rates increased steadily from about 3% in the early years to maxima of 46–49% during 1994–2001, but declined thereafter and currently reach about 33%. Taller cliffs had greater persistence and colonization rates than medium or small cliffs. Both the decline in colonization and in persistence rates during the last 15 years may reflect density-dependence, predation by the expanding European Eagle Owl (Bubo bubo) population, human persecution or any as yet unknown factors. Importantly, we note that both persistence and colonization rates began to decline many years before the recent population decline became apparent. Thus, analysis of population studies using dynamic occupancy models can provide early-warning signals for future population declines. Our study demonstrates the benefits of modern analytical methods that can correct for several key deficiencies in probably all raptor population studies: incomplete coverage of sites and imperfect detection (though we only dealt with the former here). Occupancy models, possibly accounting for preferential sampling, appear to represent the logical analytical framework for abundance in raptor population studies.