Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/25119
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: The effects of invasive pests and pathogens on strategies for forest diversification
Author(s): Macpherson, Morag
Kleczkowski, Adam
Healey, John
Quine, Christopher P
Hanley, Nick
Keywords: Bioeconomic modelling
Forest management
Natural resource management
Tree pests and pathogens
Tree species diversification
Issue Date: 24-Apr-2017
Date Deposited: 6-Mar-2017
Citation: Macpherson M, Kleczkowski A, Healey J, Quine CP & Hanley N (2017) The effects of invasive pests and pathogens on strategies for forest diversification. Ecological Modelling, 350, pp. 87-99. https://doi.org/10.1016/j.ecolmodel.2017.02.003
Abstract: Diversification of the tree species composition of production forests is a frequently advocated strategy to increase resilience to pests and pathogens; however, there is a lack of a general framework to analyse the impact of economic and biological conditions on the optimal planting strategy in the presence of tree disease. To meet this need we use a novel bioeconomic model to quantitatively assess the effect oftree disease on the optimal planting proportion of two tree species. We find that diversifying the species composition can reduce the economic loss from disease even when the benefit from the resistant speciesis small. However, this key result is sensitive to a pathogen’s characteristics (probability of arrival, timeof arrival, rate of spread of infection) and the losses (damage of the disease to the susceptible species and reduced benefit of planting the resistant species). This study provides an exemplar framework which can be used to help understand the effect of a pathogen on forest management strategies.
DOI Link: 10.1016/j.ecolmodel.2017.02.003
Rights: This article is available under the terms of the Creative Commons Attribution License (CC BY). You may copy and distribute the article, create extracts, abstracts and new works from the article, alter and revise the article, text or data mine the article and otherwise reuse the article commercially (including reuse and/or resale of the article) without permission from Elsevier. You must give appropriate credit to the original work, together with a link to the formal publication through the relevant DOI and a link to the Creative Commons user license above. You must indicate if any changes are made but not in any way that suggests the licensor endorses you or your use of the work. Permission is not required for this type of reuse.
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

Files in This Item:
File Description SizeFormat 
Macpherson_et_al-EcologicalModelling_2017.pdfFulltext - Published Version1.32 MBAdobe PDFView/Open



This item is protected by original copyright



A file in this item is licensed under a Creative Commons License Creative Commons

Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved https://creativecommons.org/publicdomain/zero/1.0/

If you believe that any material held in STORRE infringes copyright, please contact library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.