Arctic peregrine falcons (Falco peregrinus tundrius; hereafter Arctic peregrine) have a limited and northern breeding distribution, including the Colville River Special Area (CRSA) in the National Petroleum Reserve-Alaska, USA. We quantified influences of climate, topography, nest productivity, prey habitat, density dependence, and interspecific competition affecting Arctic peregrines in the CRSA by applying the Dail-Madsen model to estimate abundance and vital rates of adults on nesting cliffs from 1981 through 2002. Arctic peregrine abundance increased throughout the 1980s, which spanned the population's recovery from DDT-induced reproductive failure, until exhibiting a stationary trend in the 1990s. Apparent survival rate (i.e., emigration; death) was negatively correlated with number of adult Arctic peregrines on the cliff the previous year, suggesting effects of density-dependent population regulation. Apparent survival rate and arrival rate (i.e., immigration; recruitment) were higher during years with earlier snowmelt and milder winters, and apparent survival was positively correlated with nesting season maximum daily temperature. Arrival rate was positively correlated with average Arctic peregrine productivity along a cliff segment from the previous year and initial abundance was positively correlated with cliff height. Higher cliffs with documented higher productivity, and presumably indicative of higher quality habitat, are a priority for continued protection from potential nearby development and disturbance to minimize population-level impacts. Our work provides insight into factors affecting a population during and after recovery, and demonstrates how the Dail-Madsen model can be used for any unmarked population with multiple years of abundance data collected through repeated surveys.
This data set consists of fourteen data files. Rcode_arctic_peregrine_abundance.R contains R code that was used to analyze Arctic peregrine falcon data collected between 1981 and 2002. The code primarily uses the R package "UNMARKED" and is based on the Dail-Madsen model for estimating population abundance. To run this code in an R environment, download the file and open it in an R interpreter (such as RStudio). The remaining files are all covariate matrices that act as inputs to the R code. To use these, download and unzip the ZIP file and place them into R's working directory. For more information about the different covariate files or further directions on running the code, see the README file.
|Release Date|| |
|Spatial / Geographical Coverage Location|| |
Colville River, Alaska
University of Minnesota
|Temporal Coverage|| |
June 1, 1981 to August 15, 2002
|Contact Name|| |
Bruggeman, Jason E.
|Public Access Level|| |