WWETAC Projects
Project Title: Adapting and improving Swiss needle cast management tools to incorporate climate change projections
STDP ID: R6-2009-03
Principal Investigator: Jeffrey K. Stone, Leonard B. Coop, Dept of Botany and Plant Pathology, Oregon State University, Corvallis, OR
Collaborators: Greg Filip, USDA Forest Service, Portland, OR; Alan Kanaskie, Oregon Dept. of Forestry, Salem, OR; Dan Omdahl, Washington Dept of Natural Resources, Olympia, WA; David Shaw, Dept. of Forest Resources, Engineering and Management, Oregon State University; Ian Hood, Scion (NZ Forest Research Institute Ltd), Rotorua, NZ; and Michael Watt, Scion (NZ Forest Research Institute Ltd), Christchurch, NZ
Status: Ongoing
E-mail Contact: stonej[at]science.oregonstate.edu
Key Issue/Problem Addressed: Disease spatial modeling/forecasting in relation to climate change models.
Study Objectives and Goals: Our objective is to develop a high resolution (200 to 800 m) disease visualization tool that will incorporate weather, climate, and topographic effects to spatially display Swiss needle cast disease distribution and severity for all of western Oregon and Washington to serve several management needs. Improvements will be made to existing SNC spatial models to improve model accuracy and resolution, and to more accurately reflect coastal and inland meteorological effects. The model will incorporate IPCC climate change projections to predict effects of climate change on SNC severity.
General Description: Although it has long been considered a minor problem in native western forests, Swiss needle cast (SNC) of Douglas-fir has been emerging as a significant forest health problem in the Pacific Northwest over the past two decades. Research on SNC in western North America and New Zealand has demonstrated a strong relationship between variation in disease severity and long term climate patterns. Because distribution of the disease is stronly correlated with climatic factors, mainly winter termperatures, it is likely that current disease distributions will be influenced by climate change.
SNC is an ideal model system for illustrating effects of climate change on forest health because it is strongly influenced by climate, has been modeled at high resolution, and affects a major forest tree species. A particular advantage for modeling SNC is the availability of high resolution, high quality climate model data through the PRISM group of Oregon State University.
A regional Swiss needle cast risk model would have several potential applications for forest managers and regional planners preparing for climate change impacts in the PNW. The spatial risk model can be used to predict changes in disease severity and distribution under different climate change scenarios and so would be directly applicable as a management decision support tool. The disease model under development will incorporate high resolution PRISM climate data, disease severity and foliage retention estimates for all of western Oregon and Washington, and will include two IPPC general circulation models for predictions of SNC distribution under ‘moderate’ and ‘pessimistic’ GHC emissions scenarios.
Status:
Progress Update for 2009: Funding for FY2009 was not available until May 15, 2009, delaying year 1 progress:
a) The CLIMEX model (Sutherst et al. 1999, 2004) v.3.0.2 is being parameterized to model distributions of Douglas fir and SNC, both by standard iterative fitting based on biological understanding and published climate limits (e. g. Coops et al. 2009), and using new CLIMEX genetic algorithm features to fit initial parameters for comparison.
b) GIS approaches for development of gridded RH-am and RH-pm data (needed for CLIMEX modeling) have been developed from PRISM Tmax, Tmin, and T-dew point data. These routines are nearly ready to convert PRISM 30-year and real-time monthly data and up to 9 different PRISM-downscaled multiple climate change GCM models/scenarios (CSIRO-MK3, Hadley-CM3, MIROC-MEDRES x B1, A1B, A2), 2000±100 year climate data, obtained from collaborator Ron Neilson's working group.
c) Programs for conversion of PRISM and downscaled GCM grids into CLIMEX-formatted data are under development, which will allow 800m and higher gridded CLIMEX analyses.
d) Detailed disease severity data were collected for 18 sites extending from the western Coast Range to the western Cascades of western Oregon for model development.
e) Met with Ron Neilson’s group to discuss incorporation of SNC distribution in an MC1 module. Downscaled nine GCM climate change scenarios to PRISM 800 m resolution were provided by Ray Drapek (Neilson group) for incorporation in an SNC predictive model for climate-mediated disease impacts.
These developments will allow multi-scale climate change effects on Douglas-fir/SNC interactions to be investigated using the well-known CLIMEX system. A similar GRASS-R.MAPCALC model will also be improved from earlier SNC distribution models for comparison with the CLIMEX distribution models.
Background Citations:
Coops, N.C, Waring, R.H., Schroeder, T. (2009) A generic process-based growth model that predicts the presence and absence of tree species on U.S. Forest Service survey plots in the Pacific Northwest, U.S.A. Ecological Modelling. 220: 1776-1796.
Manter, D. K., P. W. Reeser and J. K. Stone. 2005. A climate based model for predicting geographic variation in Swiss needle cast severity in the Oregon Coast Range. Phytopathology 95:1256-1265.
Stone J. K., L. B. Coop, and D. K. Manter. 2008. Predicting effects of climate change on Swiss needle cast disease severity in Pacific Northwest forests. Canadian Journal of Plant Pathology 30:169-176.
Stone, J. K., I. A. Hood, M. S. Watt,, J. L. Kerrigan. 2007. Distribution of Swiss needle cast in New Zealand in relation to winter temperature. Australasian Plant Pathology: 36: 445-454.
Stone, J. K., L. B. Coop, and D. K. Manter, 2007. A spatial model for predicting Swiss needle cast severity in the Pacific Northwest. Encyclopedia of Forest Environmental Threats Forest Encyclopedia Network, www.forestencyclopedia.net.
Sutherst R.W., Maywald G.F., Yonow T., Stevens P.M. (1999) CLIMEX: predicting the effects of climate on plants and animals. CLIMEX: predicting the effects of climate on plants and animals. Collingwood, Australia CSIRO Publishing iv + 88 pp.
Sutherst R.W., Maywald G.F., Bottomley W., Bourne A. (2004) Climex V2 Users Guide. Hearne, Melbourne, Australia.
Project ID: FY09TS67
