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Demographic consequences of management actions for the successful reintroduction of the White Stork Ciconia ciconia to the UK

Published online by Cambridge University Press:  20 February 2023

Elouise Mayall*
Affiliation:
University of East Anglia, School of Environmental Sciences, Norwich, NR4 7TJ, UK
Lucy Groves
Affiliation:
Durrell Wildlife Conservation Trust UK, St Helier, Jersey, Channel Islands
Rosalind Kennerley
Affiliation:
Durrell Wildlife Conservation Trust UK, St Helier, Jersey, Channel Islands
Michael Hudson
Affiliation:
Durrell Wildlife Conservation Trust UK, St Helier, Jersey, Channel Islands
Aldina Franco
Affiliation:
University of East Anglia, School of Environmental Sciences, Norwich, NR4 7TJ, UK
*
*Author for correspondence: Elouise Mayall, Email: e.mayall@uea.ac.uk
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Summary

Species reintroductions can be used in conservation management to increase biodiversity and aid in restoring ecosystem function. For reintroductions to be successful, it is important to identify the conditions required to establish a viable population. We developed a demographic model using Vortex10, an individual-based simulation software, to assess the long-term consequences of different management interventions on the success of the recent reintroduction of the white stork, Ciconia ciconia, to the UK. Demographic data obtained from this reintroduced population were supplemented with information from western European populations to build the models. The impact of incorporating different management actions (e.g. supplementing with captive-bred juveniles, provision of nesting platforms, and habitat improvement/supplementary feeding) on the stochastic population growth rate was assessed. Survival rates also differ depending on an individual’s migratory strategy, hence we tested the impact of having different proportions of the population as residents or migrants. Our models showed that if the British stork population adopts a fully migratory strategy, with its associated higher mortality rates, i.e. all individuals migrating to southern Europe or northern Africa, increasing the supplementation rate would not lead to a positive population growth rate. However, management actions which increased the number of fledglings per nest generated a slight positive growth rate that led to a 54.3% increase in population size after 50 years and, when combining all three management options, the population grew by 378.3%. Alternatively, if a minimum of 9% of individuals overwintered in Britain, which is likely based on field observations and tracking data, a positive growth rate can be achieved without additional management due to this behaviour’s lower mortality rates. We conclude that the British white stork population will likely be viable in the long term, but these models and projections should be updated as more demographic data on this novel population become available.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of BirdLife International
Figure 0

Table 1. Vortex10 parameter inputs for the baseline British white stork population model. EV = environmental variation; N/A = not available; SD = standard deviation; WSP = White Stork Project.

Figure 1

Table 2. Different management strategies applied in Vortex10.

Figure 2

Table 3. The British white stork initial population size and mortality rates for migratory and non-migratory birds entered into Vortex10. EV = environmental variation; SD = standard deviation.

Figure 3

Table 4. Population viability model results from Vortex10 comparing different management strategies on the British white stork population. Det. r = deterministic growth rate; Stoch. r = stochastic growth rate; SE = standard error; Exc. supp. years = excluding years where population supplementation occurred; N = population size; PE = probability of extinction in 50 years.

Figure 4

Figure 1. Predicted trends in population size of white storks (Ciconia ciconia) in Great Britain over 50 years using Vortex10 under different management strategies (1a–1g). The initial population size in all scenarios was 155 and a carrying capacity of 12,600. The grey shading represents 95 CI based on the distribution of iterations.

Figure 5

Table 5. Population viability model results from Vortex10 modelling different proportions of non-migratory individuals in the British white stork population. Det. r = deterministic growth rate; Stoch. r = stochastic growth rate; SE = standard error; Exc. supp. years = excluding years where population supplementation occurred; N = population size; PE = probability of extinction of the population in 50 years.

Figure 6

Figure 2. A: Predicted trends in population size of white storks (Ciconia ciconia) in Great Britain over 50 years using Vortex10 where different percentages of non-migratory individuals within the population were modelled. The initial population size in all scenarios was 155 and the carrying capacity was set to 12,600. The grey shading represents 95% CI from the distribution of values from all iterations. B: The relationship between the percentage of non-migratory/resident white stork (Ciconia ciconia)overwintering in Great Britain and the mean stochastic growth rate of the population across all years. Models were produced using Vortex10 and were run for 50 years and 1000 iterations. The initial population size in all scenarios was 155 and a carrying capacity of 12,600. The grey shading represents 95% CI from the distribution of values from all iterations.

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