1. ESTIMATING WOODY BROWSE ABUNDANCE IN REGENERATING CLEARCUTS USING AERIAL IMAGERY Shawn M. Crimmins, Alison R. Mynsberge, Timothy A. Warner

2. INTRODUCTION Timber harvest Timber harvest Common in eastern hardwood forests Common in eastern hardwood forests Can create wildlife habitat Can create wildlife habitat Abundance of available forage Abundance of available forage Assessment of forage abundance Assessment of forage abundance Time consuming, labor intensive field work Time consuming, labor intensive field work Method to quantify browse remotely? Method to quantify browse remotely?

3. INTRODUCTION Remote sensing in forestry Remote sensing in forestry Forest species classification Forest species classification Forest health Forest health Forest regeneration Forest regeneration Remote sensing in wildlife Remote sensing in wildlife Habitat classification Habitat classification Habitat quality? Habitat quality?

4. OBJECTIVE Use readily available aerial imagery to estimate the abundance of woody browse in regenerating clearcuts Use readily available aerial imagery to estimate the abundance of woody browse in regenerating clearcuts

5. STUDY AREA Penn-Virginia (formerly MeadWestvaco) Wildlife and Ecosystem Research Forest Penn-Virginia (formerly MeadWestvaco) Wildlife and Ecosystem Research Forest 3413 hectares 3413 hectares Randolph County, WV Randolph County, WV Northern hardwood forest community Northern hardwood forest community Actively harvested Actively harvested Dominated by clearcutting Dominated by clearcutting

8. METHODS 12 regenerating clearcuts 12 regenerating clearcuts Surveyed as part of large-scale deer research Surveyed as part of large-scale deer research 6 age classes (0 – 5 years post harvest) 6 age classes (0 – 5 years post harvest) 2 cuts in each class 2 cuts in each class 30 plots in each cut (15 edge, 15 interior), 0.5m 2 30 plots in each cut (15 edge, 15 interior), 0.5m 2 Identified and counted all woody stems < 1.5 m Identified and counted all woody stems < 1.5 m Maximum browse height of deer Maximum browse height of deer Variable of interest Variable of interest

9. METHODS

10. METHODS Aerial imagery Aerial imagery National Agriculture Imagery Program (USDA) National Agriculture Imagery Program (USDA) 2 meter resolution 2 meter resolution Visible spectrum only Visible spectrum only Taken on September 24 (37 days after last field survey) Taken on September 24 (37 days after last field survey) Chosen due to availability Chosen due to availability Publicly available Publicly available Representative of data available to forest/wildlife managers Representative of data available to forest/wildlife managers

11. METHODS Generated 12 image metrics Generated 12 image metrics Mean and variance Mean and variance Red, Green, Blue Red, Green, Blue Ratios calculated, but abandoned later Ratios calculated, but abandoned later Hand digitized clearcuts in ArcGIS 9.1 Hand digitized clearcuts in ArcGIS 9.1 Multiple Linear Regression (PROC REG) Multiple Linear Regression (PROC REG) Forward variable selection Forward variable selection α = 0.10 for entry into model α = 0.10 for entry into model

12. RESULTS Censored one cut from analysis due to excessive shadows covering edge plots Censored one cut from analysis due to excessive shadows covering edge plots Ratio terms removed Ratio terms removed Insufficient degrees of freedom Insufficient degrees of freedom 12 predictor variables 12 predictor variables 11 observations 11 observations

13. RESULTS VariableEstimatep Intercept261.423760.0052 Red-mean-1.824090.0134 Forward selection-first step (r 2 = 0.5109) Forward selection-first step (r 2 = 0.5109) Forward selection-second step (r 2 = 0.7684) Forward selection-second step (r 2 = 0.7684) VariableEstimatep Intercept424.793320.0005 Red-mean-2.380200.0010 Green-variance-0.120220.0175

14. RESULTS VariableEstimatep Intercept345.499280.0007 Red-mean-1.935860.0013 Blue-variance0.131380.0226 Green-variance-0.197430.0015 Forward selection-third step (r 2 = 0.8953) Forward selection-third step (r 2 = 0.8953)

15. RESULTS VariableEstimatep Intercept240.057310.0166 Red-mean-2.232530.0006 Blue-variance0.163280.0072 Green-mean0.818050.0910 Green-variance-0.185250.0014 Forward selection-final step (r 2 = 0.9375) Forward selection-final step (r 2 = 0.9375) Variable r 2 Partial r 2 F value Red-mean0.51099.40 Blue-variance0.25758.90 Green-mean0.12698.48 Green-variance0.04224.04 Variable selection summary Variable selection summary

16. RESULTS Final model (p = 0.0009) Final model (p = 0.0009) Global model (p = 0.0062, r 2 = 0.9671) Global model (p = 0.0062, r 2 = 0.9671)

17. RESULTS Accurate across abundances Accurate across abundances

18. DISCUSSION High (r 2 > 0.9) predictive accuracy High (r 2 > 0.9) predictive accuracy Minimal complexity Minimal complexity 4 predictor variables 4 predictor variables Visible spectrum Visible spectrum Normally distributed error term Normally distributed error term Slight deviance in tails Slight deviance in tails Low abundance sites (logging slash) Low abundance sites (logging slash) High abundance sites (canopy growth) High abundance sites (canopy growth)

19. DISCUSSION Visible spectrum only Visible spectrum only Available in almost all imagery Available in almost all imagery Still allowed high predictive accuracy Still allowed high predictive accuracy Lack of IR bands (required for NDVI) Lack of IR bands (required for NDVI) Growth > 1.5 meters Growth > 1.5 meters Technique available to most managers Technique available to most managers No knowledge of remote sensing/GIS required No knowledge of remote sensing/GIS required

20. FUTURE DIRECTIONS Temporal replication Temporal replication Only 1 year Only 1 year Track individual cuts across growing seasons Track individual cuts across growing seasons Spatial replication Spatial replication Local weather/climate affecting growth? Local weather/climate affecting growth? Different forest types? Different forest types?

21. ACKNOWLEDGMENTS Matt Shumar, Chris Runner Matt Shumar, Chris Runner MeadWestvaco Corporation MeadWestvaco Corporation West Virginia Division of Natural Resources West Virginia Division of Natural Resources WVU WVU Division of Forestry and Natural Resources Division of Forestry and Natural Resources Cooperative Fisheries & Wildlife Research Unit Cooperative Fisheries & Wildlife Research Unit Department of Geology and Geography Department of Geology and Geography WV View WV View

22. QUESTIONS?