Analysing Large-Scale Temporal Variability in Passerine Nest Survival Using Sparse Data: A Case Study on Red-Backed ShrikeLanius collurio

Abstract

Availability of nest survival estimates over large spatial and temporal scales is necessary for the complex modelling of population dynamics. However, there may be no standardized nest monitoring schemes, as a primary source of data, for many species, locations or years. Although other potential datasets often do exist, their applicability for analysing large-scale temporal patterns in nest survival is not well established. We used an alternative dataset of ringing records of 3 091 nests of the Red-backed Shrike Lanius collurio, representing five time series (6 to 42 years) from different sites within the Czech Republic, to analyse long-term variability in nest survival. We modelled trends in daily nest survival rates (DSR) over the years, either assuming a constant DSR, or accounting for unequal nest search efforts during the breeding season by assuming that DSR varies as a function of nest age and seasonal date. We found that even sparse nesting data may produce realistic estimates of nest survival. DSR varied greatly among sites, from 0.975 to 0.984, corresponding to a nest success from 48% to 62%. Both modelling approaches yielded almost identical estimates of DSR trends over the years. In this study, nest survival has either declined at all three agricultural sites or remained stable at one suburban site since the late 1980s. We conclude that sparse datasets with unequal searching effort during the nesting cycle and/or nesting season can be used to estimate long-term trends in nest survival, but this approach is warranted only if the analyses, based on different assumptions, yield consistent estimates.