potentially changed with population density (both positively and negatively;
author’s unpublished data). Retrospective simulations without the positive effects of
SFS on young survival but no effects of poison on adult survival rates yielded a
lower number of territories than observed in the study population (71 vs. 80 territories, Fig. 15.5). However, population trends were quite similar in all cases
(scenario 1: k = 0.961, scenario 5: k = 1.000, observed: k = 1.048) suggesting that
population consequences of the progressive reduction in adult survival rates could
have been buffered by increments in young survival rates associated with the use of
SFS.
15.6.3 Availability of SFS
We envisaged that the illegal use of poison continues affecting survival rates of
vultures using the survival rates of pre-adult and adult birds estimated by the
best-selected model (see Oro et al. 2008), which were lower than expected likely
due to the effect of illegal poison. Thus, we performed a second set of simulations
considering that the temporal dynamics of poisoning are dominated by fluctuations,
both short and long term, with positive temporal autocorrelation (coloured environmental noise, Inchausti and Halley 2003). Finally, we simulated the behaviour
of our population under effective management actions reducing the impact of
poisoning, using actual adult survival estimates obtained in our study area but
without poison effects.
Fig. 15.5 Retrospective analysis of the dynamics of the Spanish population of bearded vultures in
the Pyrenees during 1985–2007. Simulations were carried out using estimated values of a actual
survival rates, i.e. with the effects of poison and SFS; and b survival with poison effects but
without SFS. Dashed lines show the mean value of stochastic trajectories using Monte Carlo
simulations, while open dots are the maximum and minimum values of that run. For comparison,
we show the observed number of breeding territories through time (solid lines) from Oro et al.
(2008)
362
A. Margalida
author’s unpublished data). Retrospective simulations without the positive effects of
SFS on young survival but no effects of poison on adult survival rates yielded a
lower number of territories than observed in the study population (71 vs. 80 territories, Fig. 15.5). However, population trends were quite similar in all cases
(scenario 1: k = 0.961, scenario 5: k = 1.000, observed: k = 1.048) suggesting that
population consequences of the progressive reduction in adult survival rates could
have been buffered by increments in young survival rates associated with the use of
SFS.
15.6.3 Availability of SFS
We envisaged that the illegal use of poison continues affecting survival rates of
vultures using the survival rates of pre-adult and adult birds estimated by the
best-selected model (see Oro et al. 2008), which were lower than expected likely
due to the effect of illegal poison. Thus, we performed a second set of simulations
considering that the temporal dynamics of poisoning are dominated by fluctuations,
both short and long term, with positive temporal autocorrelation (coloured environmental noise, Inchausti and Halley 2003). Finally, we simulated the behaviour
of our population under effective management actions reducing the impact of
poisoning, using actual adult survival estimates obtained in our study area but
without poison effects.
Fig. 15.5 Retrospective analysis of the dynamics of the Spanish population of bearded vultures in
the Pyrenees during 1985–2007. Simulations were carried out using estimated values of a actual
survival rates, i.e. with the effects of poison and SFS; and b survival with poison effects but
without SFS. Dashed lines show the mean value of stochastic trajectories using Monte Carlo
simulations, while open dots are the maximum and minimum values of that run. For comparison,
we show the observed number of breeding territories through time (solid lines) from Oro et al.
(2008)
362
A. Margalida