Journal
FOREST ECOLOGY AND MANAGEMENT
Volume 261, Issue 11, Pages 1792-1798Publisher
ELSEVIER
DOI: 10.1016/j.foreco.2011.01.043
Keywords
Biosecurity; Disease risk assessment; Disease severity; Dothistroma needle blight; Invasive species; Red band needle blight
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Funding
- Ministry of Agriculture and Forestry [C04X0901]
- New Zealand Forest Service
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Despite being a damaging foliar disease of Pinus species little research has characterised spatial variation in disease severity of Dothistroma needle blight at a macroscale. Using an extensive dataset describing Dothistroma needle blight severity (S-sev) on plantation grown Pinus radiata stands distributed widely across New Zealand the objectives of this research were to (i) develop a regression model describing S-sev, (ii) use this model to identify key drivers of S-sev, their functional form and relative importance, and (iii) develop spatial predictions of S-sev, for New Zealand P. radiata under current climate. Using an independent validation dataset, the final model accounted for 72% of the variance in S-sev using four significant (P < 0.001) explanatory variables and an isotrophic exponential model to account for the spatial covariance in the data. S-sev was most sensitive to mean air temperature from November to April (TNov-Apr), followed by mean relative humidity from October to April (RHOct_Apr), mean total November rainfall (P-Nov), and then stand age (A). There was a quadratic correlation between A and S-sev with S-sev increasing to a maxima at 12 years before declining. S-sev exponentially increased to a threshold with increases in both P-Nov and RHOct_Apr. The relationship between S-sev and TNov-Apr was quadratic with S-sev increasing to a maximum at TNov-Apr of 15.5 degrees C before declining at higher values of T-Nov_Apr. Spatial predictions of S-sev varied widely throughout New Zealand. Values of S, were highest in moderately warm wet environments in the North Island, and on the west coast of the South Island. In contrast, relatively low values of S-sev were predicted in drier eastern and southern regions of New Zealand. (C) 2011 Elsevier B.V. All rights reserved.
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