The three scenarios considered within this group of simulations showed different
patterns associated with the effects of poison on survival. When the survival of
adults decreases because of the illegal use of poison and survival of young increases
due to their use of SFS (scenarios 1 and 2, Fig. 15.6), population trajectories
decreased over the years (scenario 1: k = 0.961; scenario 2: k = 0.932). However,
extinction probabilities were not equal in the first and the second scenarios. When
the impact of poison was stochastic with no clear trend over time (scenario 1
Table 15.2), probabilities of extinction were nil, although some trajectories attained
the quasi-extinction threshold (scenario 1 Table 15.2, Fig. 15.6). Conversely,
ARIMA analysis indicated that the way in which illegal poisoning impacted our
bearded vulture population (i.e. the colour of the environmental noise) depended on
the age class considered. For instance, the decrease of survival among birds older
than 4 years during 1986–2007 (a = 0.264, b = 0.241) showed a long-term temporal autocorrelation (i.e. red noise), whereas for birds up to 4 years old
(a = −0.018, b = 0.250) survival exhibited a short-term temporal autocorrelation
Fig. 15.6 Stochastic population projections estimated through Monte Carlo simulations (50 years
of temporal window, 500 runs) for some of the scenarios considered: (1) actual values of adult
survival without temporal autocorrelation in the use of poison, (2) and (4) actual values of adult
survival with temporal autocorrelation in the use of poison, (3) no impact of poison, assuming that
young and adult survival were equal, and (5) no impact of poison, assuming that survival of young,
and adults were the same t (see Oro et al. 2008 for details). Lines are mean values of the stochastic
runs for each time step, while dots show the maximum and minimum values of those runs.
Projections were carried out on the density of females of any age, which have different scales in
each graph
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363
patterns associated with the effects of poison on survival. When the survival of
adults decreases because of the illegal use of poison and survival of young increases
due to their use of SFS (scenarios 1 and 2, Fig. 15.6), population trajectories
decreased over the years (scenario 1: k = 0.961; scenario 2: k = 0.932). However,
extinction probabilities were not equal in the first and the second scenarios. When
the impact of poison was stochastic with no clear trend over time (scenario 1
Table 15.2), probabilities of extinction were nil, although some trajectories attained
the quasi-extinction threshold (scenario 1 Table 15.2, Fig. 15.6). Conversely,
ARIMA analysis indicated that the way in which illegal poisoning impacted our
bearded vulture population (i.e. the colour of the environmental noise) depended on
the age class considered. For instance, the decrease of survival among birds older
than 4 years during 1986–2007 (a = 0.264, b = 0.241) showed a long-term temporal autocorrelation (i.e. red noise), whereas for birds up to 4 years old
(a = −0.018, b = 0.250) survival exhibited a short-term temporal autocorrelation
Fig. 15.6 Stochastic population projections estimated through Monte Carlo simulations (50 years
of temporal window, 500 runs) for some of the scenarios considered: (1) actual values of adult
survival without temporal autocorrelation in the use of poison, (2) and (4) actual values of adult
survival with temporal autocorrelation in the use of poison, (3) no impact of poison, assuming that
young and adult survival were equal, and (5) no impact of poison, assuming that survival of young,
and adults were the same t (see Oro et al. 2008 for details). Lines are mean values of the stochastic
runs for each time step, while dots show the maximum and minimum values of those runs.
Projections were carried out on the density of females of any age, which have different scales in
each graph
15 Importance of Long-Term Studies to Conservation …
363