(i.e. blue noise). This temporal autocorrelation in the impact of poison, the most
realistic situation (scenario 2 Table 15.2), increased the extinction probabilities of
the whole population, with a maximum value over a time horizon of 50 years
(p e (t = 50) = 1, mean extinction time: 10.2 years, see scenario 2 Table 15.2,
Fig. 15.6). Note that for these two poison-impacted scenarios the mean trajectories
were quite similar, except for the largest variability expected in population trajectories when the impact of poison was temporally correlated (scenario 2 Table 15.2,
Fig. 15.6). Interestingly, both mean trajectories were relatively stable in early years,
probably due to the buffer capacity of recruits resulting from very high young
survival.
Increments in the survival rate of adult birds up to that expected when the illegal
use of poison was near nil combined with a high survival rate of young (maintained
through SFS) predicted a marked increment in the number of breeding territories
(k = 1.014; Fig. 15.6).
15.6.4 No Availability of SFS
This group of simulations allowed us to disentangle the actual usefulness of SFS to
mitigate the effects of illegal poison on population persistence.
Populations suffering from negative effects of illegal poisoning on survival rates
but not managed with SFS showed a lower population growth rate and a slightly
higher probability of extinction in the time horizon of 50 years than its most
conservative counterpart (scenario 1: k = 0.961; scenario 4: k = 0.932; Fig. 15.6).
However, in a scenario of no use of illegal poisoning and no SFS, population
numbers are somewhat lower although still rather stable (scenario 5: k = 1.000;
scenario 3: k = 1.016).
Population projections under scenarios of illegal poisoning did not forecast a
positive outcome for the most important European core of this species. When the
impact of poison on adult survival was stochastic, probabilities of extinction for the
population were nil, although some trajectories achieved the quasi-extinction
threshold. Of even greater concern, extinction probabilities for the population
increased when the effect of illegal poisoning on adult survival followed a temporal
autocorrelation, the most probable scenario. Conversely, population projections run
with the survival of adults not affected by illegal poisoning predicted better situations, with larger population increments in scenarios of maintenance of SFS, when
survival rates of young birds are also improved. The counter-scenario, no use of
illegal poisoning and no availability of SFS, predicts slightly lower population sizes
but with near stable trajectories. Consequently, an important management action
intuitively used to reduce the negative effects of illegal poisoning such as the
opening of SFS as appear to be not as effective as expected in saving threatened
populations from future negative trends. As in many other long-lived species,
survival of adults is the key demographic parameter contributing most to the projected population growth rate (e.g. Saether and Bakke 2000), and management
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A. Margalida
realistic situation (scenario 2 Table 15.2), increased the extinction probabilities of
the whole population, with a maximum value over a time horizon of 50 years
(p e (t = 50) = 1, mean extinction time: 10.2 years, see scenario 2 Table 15.2,
Fig. 15.6). Note that for these two poison-impacted scenarios the mean trajectories
were quite similar, except for the largest variability expected in population trajectories when the impact of poison was temporally correlated (scenario 2 Table 15.2,
Fig. 15.6). Interestingly, both mean trajectories were relatively stable in early years,
probably due to the buffer capacity of recruits resulting from very high young
survival.
Increments in the survival rate of adult birds up to that expected when the illegal
use of poison was near nil combined with a high survival rate of young (maintained
through SFS) predicted a marked increment in the number of breeding territories
(k = 1.014; Fig. 15.6).
15.6.4 No Availability of SFS
This group of simulations allowed us to disentangle the actual usefulness of SFS to
mitigate the effects of illegal poison on population persistence.
Populations suffering from negative effects of illegal poisoning on survival rates
but not managed with SFS showed a lower population growth rate and a slightly
higher probability of extinction in the time horizon of 50 years than its most
conservative counterpart (scenario 1: k = 0.961; scenario 4: k = 0.932; Fig. 15.6).
However, in a scenario of no use of illegal poisoning and no SFS, population
numbers are somewhat lower although still rather stable (scenario 5: k = 1.000;
scenario 3: k = 1.016).
Population projections under scenarios of illegal poisoning did not forecast a
positive outcome for the most important European core of this species. When the
impact of poison on adult survival was stochastic, probabilities of extinction for the
population were nil, although some trajectories achieved the quasi-extinction
threshold. Of even greater concern, extinction probabilities for the population
increased when the effect of illegal poisoning on adult survival followed a temporal
autocorrelation, the most probable scenario. Conversely, population projections run
with the survival of adults not affected by illegal poisoning predicted better situations, with larger population increments in scenarios of maintenance of SFS, when
survival rates of young birds are also improved. The counter-scenario, no use of
illegal poisoning and no availability of SFS, predicts slightly lower population sizes
but with near stable trajectories. Consequently, an important management action
intuitively used to reduce the negative effects of illegal poisoning such as the
opening of SFS as appear to be not as effective as expected in saving threatened
populations from future negative trends. As in many other long-lived species,
survival of adults is the key demographic parameter contributing most to the projected population growth rate (e.g. Saether and Bakke 2000), and management
364
A. Margalida