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 CECO – C eanothus shrub (13.4%) CC – Closed Canopy (67.7%) OC – Open Canopy (4.7%)

3. Changes in Forest Structure before disturbancesAfter 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. Teakettle Experimental Forest iriiri i = 1, 2, 3,…100 m Stem Map Microclimate Stations Hemispheric photos u PAR T a RH T sf T s15 M s G CR10 datalogger

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. iriiri 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. Tree density, dbh, and basal area may determine canopy cover in Zeniths. Open canopy Average Closed canopy

13. The relationship between canopy cover and forest structure CanopyCover = 72.545 - 0.004TD 1 + 0.011TD 3 - 0.053BA 25 - 0.440DBH 2 - 0.189DBH 7 - 0.098DBH 9 - 0.292DBH 12 + 0.915DBH 14 - 1.303DBH 15 using stepwise regression.

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 (T sf ) in May and August, and soil moisture (M s ) 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 ?