Optimal control of Atlantic population Canada geese
Management of Canada geese (Branta canadensis) can be a balance between providing sustained harvest opportunity while not allowing populations to become overabundant and cause damage. In this paper, we focus on the Atlantic population of Canada geese and use stochastic dynamic programming to determi...
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ftunivqespace:oai:espace.library.uq.edu.au:UQ:134458 2023-05-15T15:46:17+02:00 Optimal control of Atlantic population Canada geese Hauser, C. E. Runge, M. C. Cooch, E. G. Johnson, F. A. Harvey IV, W. F. S. E. Jorgensen 2007-01-01 https://espace.library.uq.edu.au/view/UQ:134458 eng eng Elsevier doi:10.1016/j.ecolmodel.2006.07.019 issn:0304-3800 Ecology stochastic dynamic programming harvest control Canada geese Branta canadensis uncertainty age structure Adaptive Management Fluctuating Populations Waterfowl Harvests Mallard Harvests Optimization Recruitment Strategies Resources Dynamics 239901 Biological Mathematics C1 770403 Living resources (flora and fauna) Conference Paper 2007 ftunivqespace https://doi.org/10.1016/j.ecolmodel.2006.07.019 2020-08-17T23:05:01Z Management of Canada geese (Branta canadensis) can be a balance between providing sustained harvest opportunity while not allowing populations to become overabundant and cause damage. In this paper, we focus on the Atlantic population of Canada geese and use stochastic dynamic programming to determine the optimal harvest strategy over a range of plausible models for population dynamics. There is evidence to suggest that the population exhibits significant age structure, and it is possible to reconstruct age structure from surveys. Consequently the harvest strategy is a function of the age composition, as well as the abundance, of the population. The objective is to maximize harvest while maintaining the number of breeding adults in the population between specified upper and lower limits. In addition, the total harvest capacity is limited and there is uncertainty about the strength of density-dependence. We find that under a density-independent model, harvest is maximized by maintaining the breeding population at the highest acceptable abundance. However if harvest capacity is limited, then the optimal long-term breeding population size is lower than the highest acceptable level, to reduce the risk of the population growing to an unacceptably large size. Under the proposed density-dependent model, harvest is maximized by maintaining the breeding population at an intermediate level between the bounds on acceptable population size; limits to harvest capacity have little effect on the optimal long-term population size. It is clear that the strength of density-dependence and constraints on harvest significantly affect the optimal harvest strategy for this population. Model discrimination might be achieved in the long term, while continuing to meet management goals, by adopting an adaptive management strategy. Conference Object Branta canadensis The University of Queensland: UQ eSpace Canada Ecological Modelling 201 1 27 36 |
institution |
Open Polar |
collection |
The University of Queensland: UQ eSpace |
op_collection_id |
ftunivqespace |
language |
English |
topic |
Ecology stochastic dynamic programming harvest control Canada geese Branta canadensis uncertainty age structure Adaptive Management Fluctuating Populations Waterfowl Harvests Mallard Harvests Optimization Recruitment Strategies Resources Dynamics 239901 Biological Mathematics C1 770403 Living resources (flora and fauna) |
spellingShingle |
Ecology stochastic dynamic programming harvest control Canada geese Branta canadensis uncertainty age structure Adaptive Management Fluctuating Populations Waterfowl Harvests Mallard Harvests Optimization Recruitment Strategies Resources Dynamics 239901 Biological Mathematics C1 770403 Living resources (flora and fauna) Hauser, C. E. Runge, M. C. Cooch, E. G. Johnson, F. A. Harvey IV, W. F. Optimal control of Atlantic population Canada geese |
topic_facet |
Ecology stochastic dynamic programming harvest control Canada geese Branta canadensis uncertainty age structure Adaptive Management Fluctuating Populations Waterfowl Harvests Mallard Harvests Optimization Recruitment Strategies Resources Dynamics 239901 Biological Mathematics C1 770403 Living resources (flora and fauna) |
description |
Management of Canada geese (Branta canadensis) can be a balance between providing sustained harvest opportunity while not allowing populations to become overabundant and cause damage. In this paper, we focus on the Atlantic population of Canada geese and use stochastic dynamic programming to determine the optimal harvest strategy over a range of plausible models for population dynamics. There is evidence to suggest that the population exhibits significant age structure, and it is possible to reconstruct age structure from surveys. Consequently the harvest strategy is a function of the age composition, as well as the abundance, of the population. The objective is to maximize harvest while maintaining the number of breeding adults in the population between specified upper and lower limits. In addition, the total harvest capacity is limited and there is uncertainty about the strength of density-dependence. We find that under a density-independent model, harvest is maximized by maintaining the breeding population at the highest acceptable abundance. However if harvest capacity is limited, then the optimal long-term breeding population size is lower than the highest acceptable level, to reduce the risk of the population growing to an unacceptably large size. Under the proposed density-dependent model, harvest is maximized by maintaining the breeding population at an intermediate level between the bounds on acceptable population size; limits to harvest capacity have little effect on the optimal long-term population size. It is clear that the strength of density-dependence and constraints on harvest significantly affect the optimal harvest strategy for this population. Model discrimination might be achieved in the long term, while continuing to meet management goals, by adopting an adaptive management strategy. |
author2 |
S. E. Jorgensen |
format |
Conference Object |
author |
Hauser, C. E. Runge, M. C. Cooch, E. G. Johnson, F. A. Harvey IV, W. F. |
author_facet |
Hauser, C. E. Runge, M. C. Cooch, E. G. Johnson, F. A. Harvey IV, W. F. |
author_sort |
Hauser, C. E. |
title |
Optimal control of Atlantic population Canada geese |
title_short |
Optimal control of Atlantic population Canada geese |
title_full |
Optimal control of Atlantic population Canada geese |
title_fullStr |
Optimal control of Atlantic population Canada geese |
title_full_unstemmed |
Optimal control of Atlantic population Canada geese |
title_sort |
optimal control of atlantic population canada geese |
publisher |
Elsevier |
publishDate |
2007 |
url |
https://espace.library.uq.edu.au/view/UQ:134458 |
geographic |
Canada |
geographic_facet |
Canada |
genre |
Branta canadensis |
genre_facet |
Branta canadensis |
op_relation |
doi:10.1016/j.ecolmodel.2006.07.019 issn:0304-3800 |
op_doi |
https://doi.org/10.1016/j.ecolmodel.2006.07.019 |
container_title |
Ecological Modelling |
container_volume |
201 |
container_issue |
1 |
container_start_page |
27 |
op_container_end_page |
36 |
_version_ |
1766380981949825024 |