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Potential sex-dependent effects of weather on apparent survival of a high-elevation specialist

Cite this dataset

Strinella, Eliseo et al. (2020). Potential sex-dependent effects of weather on apparent survival of a high-elevation specialist [Dataset]. Dryad.


Mountain ecosystems are inhabited by highly specialised and endemic species which are particularly susceptible to climatic changes. However, the mechanisms by which climate change affects species population dynamics are still largely unknown, particularly for mountain birds. We investigated how weather variables correlate with apparent survival of the White-winged Snowfinch Montifringilla nivalis, a specialist of high-elevation habitat. We analysed a 15-year (2003-2017) mark-recapture data set of 671 individuals from the Apennines (Italy), using mark-recapture models. We estimated annual apparent survival to be around 0.44-0.54 for males and around 0.51-0.64 for females. Variance among years was high (range: 0.2-0.8), particularly so for females. Apparent survival was lower in winter compared to summer. Female annual apparent survival was negatively correlated with warm and dry summers, whereas in males these weather variables only weakly correlate with apparent survival. Remarkably, the average apparent survival measured in this study was lower than expected. We suggest that the low apparent survival may be due to recent changes in the environment caused by global warming. Possible, non-exclusive mechanisms that potentially also could explain sexual differential apparent survival act via differential breeding dispersal, physiological tolerance of high temperature, weather-dependent food availability, and weather-dependent trade-off between reproduction and self-maintenance. These results improve our current understanding of the mechanisms driving population dynamics in high-elevation specialists, which are particularly at risk due to climate change.


marking and recapturing by metal rings (see manuscript)


Usage notes

The four rda files can be loaded into R using the function "load". Each vile contains an R-object called "datax".

"datax" is a list that contains:

- the capture history: a matrix with one row for each individual and one column for each capture occasion (4-month period or year). 0 = the indivdiual was not captured during that capture occasion, 1 = individual was captured

- the vector first: gives the capture occasion number during which the individual was marked (full data set) or at which the sex was first identified (reduced data set)

- number of individuals "nind": in the full data set nindi = number of individuals with identified sex, nindni = number of individuals with non-identified sex.

- number of capture occasion

- age matrix: 1 = first year, 2 = after first year

- transients matrix: indicator of the occasion when the individual was first captured

- sex: 1 = males, 2 = females

- tempsu: z-transformed average summer temperature (see manuscript)

- tempwi: z-transformed average winter temperature (see manuscript)

The data is formatted so that the models of which the Stan code is given in the supplementary material of the manuscript can be fitted.