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Siyan Ma Co-authors: Malcolm North, Jiquan Chen, Stephen Mather ,

Within-stand Interactions of Forest Structure and Microclimate Variability in an Old-Growth, Mixed-Conifer Forest. Siyan Ma Co-authors: Malcolm North, Jiquan Chen, Stephen Mather , Martin Jurgensen, and Brian Oakley. A Heterogeneous, Old-Growth, Mixed-Conifer Forest. CC – Closed Canopy

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Siyan Ma Co-authors: Malcolm North, Jiquan Chen, Stephen Mather ,

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  1. Within-stand Interactions of Forest Structure and Microclimate Variability in an Old-Growth, Mixed-Conifer Forest Siyan Ma Co-authors: Malcolm North, Jiquan Chen, Stephen Mather, Martin Jurgensen, and Brian Oakley

  2. A Heterogeneous, Old-Growth, Mixed-Conifer Forest CC – Closed Canopy (67.7%) OC – Open Canopy (4.7%) CECO – Ceanothus shrub (13.4%)

  3. Changes in Forest Structure before disturbances After disturbances

  4. Canopy cover Canopy cover influences within-stand microclimate variability.

  5. Objectives • examine heterogeneous forest and canopy structure in multiple demonstrating scales • quantify spatial variability of microclimatic variables • explore spatial distributions of microclimatic variables using empirical models

  6. Hemispheric photos Microclimate Stations Ta RH PAR u ri CR10 datalogger Tsf Ts15 Ms G i = 1, 2, 3,…100 m Teakettle Experimental Forest Stem Map

  7. ? Microclimate Variables • Daily means of each microclimate station • Seasonal variability • Spatial variability

  8. Spatial variability in a whole year • Spatial variability - Coefficient of Variation (CV, %) • Spatial variability – seasonal patterns

  9. Histograms of CV • Different ranges of CV indicate spatial variability of each variable. • Most of variables have similar CV range. • G has the greatest CV range.

  10. ri i = 1, 2, 3,…100 m Forest Structure in different demonstrating scales

  11. Forest structure is “Heterogeneous” within the area < 25 m radius. N = 18

  12. Open canopy Average Closed canopy Tree density, dbh, and basal area maydetermine canopy cover in Zeniths.

  13. The relationship between canopy cover and forest structure using stepwise regression. CanopyCover = 72.545 - 0.004TD1 + 0.011TD3 - 0.053BA25 - 0.440DBH2 - 0.189DBH7 - 0.098DBH9 - 0.292DBH12 + 0.915DBH14 - 1.303DBH15

  14. From Stem Map to Canopy Map

  15. Table Linear regression models for predicting microclimatic variables from topographic and forest- structure factors (EL – elevation, AS – aspect, and CC -canopy cover), using photosynthetically active radiation (PAR) and soil surface temperature (Tsf) in May and August, and soil moisture (Ms) in June, 1999 and July, 2000 as examples.

  16. Within-stand Spatial Distribution

  17. Conclusions • Microclimate spatial variability can be measured using CV. • CVs have seasonal patterns. • Most of variables have similar spatial variability except soil heat flux (G). • Forest structure is “Heterogeneous” within the area < 25 m radius. • Spatial canopy distribution is related to forest structure. • Microclimate spatial distribution is predicable using the relationship between microclimatic variables and canopy distribution, topographic factors, and other microclimatic variables.

  18. Acknowledgements Nathan Williamson Rhonda Roberts Eric Huber Teakettle mapping Technicians (1999 ~ 2002) The University of Toledo USDA FS Pacific Southwest Research Station USDA FS Southern Research Station Michigan Technological University

  19. Thanks for coming.Questions ?

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