The importance of interspecific interactions for breeding‐site selection: peregrine falcons seek proximity to raven nests

• Published in: Ecography
• Main Authors: Sergio, Fabrizio, Rizzolli, Franco, Marchesi, Luigi, Pedrini, Paolo
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2004
• Subjects: Falco peregrinus; peregrine falcon; Aquila chrysaetos; golden eagle
• Online Access: http://dx.doi.org/10.1111/j.0906-7590.2004.04030.x; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.0906-7590.2004.04030.x; https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.0906-7590.2004.04030.x

The advent of GIS is initiating a rapid increase in the utilization of wildlife‐habitat models as tools for species and habitat management. However, such models rarely include estimates of interspecific interactions among explanatory variables. We tested the importance of such variables by using the peregrine falcon Falco peregrinus , a medium‐sized raptor frequently reported to be affected by heterospecifics, as a model species. In an Alpine population, compared to random locations, peregrines selected breeding sites farther from conspecifics, on taller cliffs, with higher availability of farmland and closer to raven Corvus corax nests. Within suitable habitat, peregrines selected sites near ravens and far from elevations associated with golden eagle Aquila chrysaetos nests. Productivity increased with cliff size, farmland availability (rich in the local main prey) and with proximity to ravens, suggesting that the observed choices were adaptive. Finally, at the regional level, peregrine density peaked at low elevation and was positively associated with raven density. The results suggested an active breeding association of peregrines with ravens, which may provide early‐warning cues against predators and safe alternative nest‐sites. They also confirmed the importance of including estimates of interspecific interactions among explanatory variables, which may: 1) make models more realistic; 2) increase their predictive power by lowering unexplained variance due to unmeasured factors; 3) provide unexpected results such as the cryptic, large‐scale breeding association of our study; and 4) stimulate further hypothesis formulation and testing, ultimately leading to deeper ecological knowledge of the study system.