| Registro completo |
| Provedor de dados: |
AgEcon
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| País: |
United States
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| Título: |
Optimal Detection Strategies for an Established Invasive Forest Pest
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| Autores: |
Horie, Tetsuya
Homans, Frances R.
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| Data: |
2007-06-27
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| Ano: |
2007
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| Palavras-chave: |
Resource /Energy Economics and Policy
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| Resumo: |
When it comes to invasive species management, economists have focused on the trade-off between prevention of potential invasions and management of established populations. The intermediate step-detection of established populations on the landscape so that management can commence-has only recently received attention in the economics literature. A recent paper (Mehta et al., 2007) explores how biological and economic parameters affect optimal detection spending, recognizing that greater expenditures on detection can lead to smaller and more manageable population sizes upon detection because populations are discovered early. We build upon this framework by considering the optimal spatial allocation of detection effort when it is impossible to stop the advance of the main front of an invasive species, yet it is beneficial to detect and control sub-populations of the species that erupt ahead of the front. Our approach recognizes that the duration of management of sub-populations is constrained by the amount of time remaining before the main front arrives. Locations close to the front have less time remaining than locations that are more distant. These differences imply different levels of potential benefit from early detection; in particular, shorter management horizons translate into lower benefits from intervention. The optimal intensity of detection effort varies over space along with this variation in the benefits from management.
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| Tipo: |
Conference Paper or Presentation
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| Idioma: |
Inglês
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| Identificador: |
26512
http://purl.umn.edu/9695
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| Editor: |
AgEcon Search
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| Relação: |
American Agricultural Economics Association>2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon
Selected Paper 174828
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| Formato: |
10
application/pdf
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