Identifying interactions among reforestation success drivers: A case study from the Philippines

Le, Hai Dinh, Smith, Carl and Herbohn, John (2015) Identifying interactions among reforestation success drivers: A case study from the Philippines. Ecological Modelling, 316 62-77. doi:10.1016/j.ecolmodel.2015.08.005

Author Le, Hai Dinh
Smith, Carl
Herbohn, John
Title Identifying interactions among reforestation success drivers: A case study from the Philippines
Journal name Ecological Modelling   Check publisher's open access policy
ISSN 0304-3800
Publication date 2015-11-24
Year available 2015
Sub-type Article (original research)
DOI 10.1016/j.ecolmodel.2015.08.005
Open Access Status Not Open Access
Volume 316
Start page 62
End page 77
Total pages 16
Place of publication Amsterdam, Netherlands
Publisher Elsevier
Language eng
Formatted abstract
Reforestation is an expensive undertaking. It is a long-term, complex, and trans-disciplinary process and it involves uncertainties and changing conditions. There is also a complex array of drivers (including biophysical, technical, socio-economic, institutional, and management drivers) that affect reforestation success. Previous research has documented the independent effects of biophysical and technical, environmental and socio-economic drivers on reforestation success. However, research over the last decade has revealed that the outcome of multiple factor interactions is commonly non-additive (i.e. synergies and antagonisms). Therefore, in order to provide better decision support for reforestation planning and policy setting it is necessary to understand the interactive effects that drivers have on reforestation success. To understand these interactive effects, we developed a Bayesian network model based on data collected from 43 reforestation projects on Leyte Island, the Philippines. Non-additive interactions among reforestation success drivers (i.e. synergies and antagonisms) were found to account for up to 90% of interactions tested. This result suggests an urgent need to account for these non-additive interactions in reforestation policy and planning in order to avoid unanticipated outcomes, wasted effort and missed opportunities.
Keyword Bayesian networks
Synergistic interactions
Antagonistic interactions
Non-additive interactions
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Agriculture and Food Sciences
Official 2016 Collection
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 3 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 3 times in Scopus Article | Citations
Google Scholar Search Google Scholar
Created: Sun, 30 Aug 2015, 01:17:35 EST by Dr Carl Smith on behalf of School of Agriculture and Food Sciences