1 / 14

Richard Waring 1 Thomas Hilker 1 Nicholas Coops 2 Amanda Mathys 2 1 Oregon State University

I R S S. Mapping of stress on native tree species across western U.S.A. & Canada: interpretation of climatically-induced changes using a physiologically-based approach. Richard Waring 1 Thomas Hilker 1 Nicholas Coops 2 Amanda Mathys 2 1 Oregon State University

ocean
Télécharger la présentation

Richard Waring 1 Thomas Hilker 1 Nicholas Coops 2 Amanda Mathys 2 1 Oregon State University

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. I R S S Mapping of stress on native tree species across western U.S.A. & Canada: interpretation of climatically-induced changes using a physiologically-based approach Richard Waring1 Thomas Hilker1 Nicholas Coops2 Amanda Mathys2 1 Oregon State University 2 University of British Columbia

  2. Challenge: can we map where some tree species will die & others migrate in response to a changed climate? • In a previous NASA grant we predicted where a majority of 15 species in the Pacific N.W. might expect to be subject to fire, insect, or disease attack within broadly defined ecoregionswith 70 to 80% accuracy. • In this NASA grant, we seek to expand the areas to the entire West for 25 tree species and to improve spatial accuracy to 1km 2by: a) mapping variation in soil properties b) limiting predictions to areas where a tree species is known to be present on Forest Service survey plots c) field verification (or falsification) of model predictions

  3. Site productivity varies with climate and soil conditions: The maximum greenness (Leaf Area Index) of the vegetation during mid-summer directly mirrors variation in site productivity, even with disturbance 3-PG Modeled LAI MODIS LAI Coops, Waring, Hilker. 2012. Remote Sensing of Env. 126:160-173

  4. Modeling gross photosynthesis (GPP) • Assume Max GPP is the product of light absorbed by LAI each month and the photosynthetic efficiency of leaves, the latter dependent on soil fertility. • Actual GPP = • Max GPP * f(temp)*f(frost)*f(vpd)*f(avail H20) • Each of the functions vary from 0 (shutdown) to 1 (optimum)

  5. Decision tree analysis[Values in reference to optimum for Douglas-fir] (more frost) (cooler temp) (< humid) (soils saturated) (After Coops & Waring. 2011. Climatic Change 105:313-328)

  6. Presence & absence of 25 tree species on >43,400 survey plots predicted with an average accuracy of 80% Unpublished material :NASA Grant NNX11A029G

  7. Process-based decision-tree models predict where climatic conditions since 2000 are more or less favorable than they were previously (1950-75) Douglas-fir Ponderosa pine Unpublished material :NASA Grant NNX11A029G

  8. Modeled change in summer soil water stress since 2000 compared to 1950-75 period Range: --0.5 to +0.5

  9. Modeled change in spring frost since 2000 compared to 1950-75 period No change in 2000 Range:- 0.06 to 0.3

  10. Ponderosa pine: predicted area under stress in N. California,and vulnerable since 2000 compared to 1950-75 climatic conditions CALIFORNIA Unpublished material :NASA Grant NNX11A029G

  11. Whitebark pine: predicted areas under stress since 2000 in the vicinity of Bozeman, MT Unpublished material :NASA Grant NNX11A029G

  12. USFS species–level disturbance patterns COLORADO

  13. Summary • Inverting the process-based model to predict soil fertility & soil water holding capacity improves our ability to explain local patterns of tree death (Peterman et al. 2012). • Including soil properties did not improve broad scale accuracy in predicting presence or absence on field survey plots (80%), but we expect improved accuracy at local scales for specific species • We will restrict field inspections to areas where tree species have been recorded and are modeled to be in a changed state

  14. PUBLICATIONS • AUSTRALIA • Smettem, K.R.J., R.H. Waring, N. Callow, M. Wilson & Q. Mu (2013) Satellite-derived estimates of forest leaf area index in south west Western Australia are not tightly coupled to inter-annual variations in rainfall: implications for groundwater decline in a drying climate. Global Change Biology (in press). • SOUTHWEST USA • Peterman, W., R.H. Waring, T. Seager, and W.L. Pollock (2012) Soil properties affect pinyonpine-juniper response to drought.Ecohydrology (on line June 13th, 2012). • BRITISH COLUMBIA & ALBERTA, CANADA • Coops, N.C., M.A. Wulden, and R.H. Waring (2012) Modeling lodgepole and jack pine vulnerability to mountain pine beetle expansion into the Canadian boreal forest. Forest Ecology and Management 274:1601-171. • ALL WESTERN STATES AND CANADIAN PROVINCES • Coops, N.C., R.H. Waring & T. Hilker (2012) Prediction of soil properties using a process-based forest growth model to match satellite-derived estimates of leaf area index. Remote Sensing of Environment 126:160-173.

More Related