Secondary forest succession quantification using LIDAR analysis in the southern AppalachiansTucker J. Souther1, Robbie G. Kreza1, Marcus C. Mentzer1, Brian D. Kloeppel1, and Ryan E. Emanuel2

1Department of Geosciences and Natural Resources, Western Carolina University, Cullowhee, NC 28723, tjsouther1@catamount.wcu.edu2Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695

Introduction

Objectives

Methods

Results

Conclusions

funding provided by

Figure 2. Forest cutting history at Balsam Mountain Preserve by the former land owner, Champion International. Years indicate the most recent cut for each stand and stands used in this study are highlighted in yellow.

Figure 1. In an effort to provide a statewide perspective of LIDAR accuracy, four other institutions were involved with the project, including UNC-Pembroke, Johnson C. Smith University, Livingstone College, and North Carolina State University. Counties are highlighted in red and study sites are indicated by green dots with Balsam Mountain Preserve near Western Carolina University indicated with an arrow.

Secondary forest succession is an important ecosystem process that occurs as forested ecosystems regenerate naturally after disturbance. As forests undergo succession, the mass of carbon stored within the ecosystem changes. The primary goal of the project was to determine if airplane-based LIDAR (Light Detection And Ranging) data could be used to accurately predict tree height, providing insight into forest structure across a suite of successional age classes. We used both indirect and direct forest structure measurements to determine the structure of the forest during these successional changes. These measurements included tree height, forest density, plant area index, forest basal area, and species distribution (all collected in the field). To assess the accuracy of the LIDAR data, four forest stands of similar species composition (deciduous montane mixed oak-hickory forest), in different successional stages (30, 50, 70, and 90+ years since disturbance) were utilized for our measurements. This project was a collaborative effort between Western Carolina University (WCU)and four other institutions across the state of North Carolina.

The objectives of this research were to:1)Determine if the LIDAR imagery available in Jackson County, North Carolina could accurately predict tree height as measured in the field2)Determine what impact stand age and the concomitant change in forest structure has on our ability to accurately predict tree height using LIDAR imagery3)Measure plant area index of these stands from field-based measurements using the LAI 2000 instrument4)Compare species composition using forest biometrics across several successional stand ages

This research was conducted at Balsam Mountain Preserve (BMP) in Jackson County in western North Carolina. BMP is an 1800 hectare mountain site (4400 acres) that was originally owned by Champion International Paper Company and was purchased in the late 1990’s for an upscale housing development containing 354 home lots. At that time, half of the remaining land that was not being developed was placed into a conservation easement forming the non-profit BMP trust. The past land use history (see Figure 2 below) provided us with a range of stand ages in the montane oak-hickory forest type with dominant species including chestnut oak (Quercus montana), northern red oak (Quercus rubra), scarlet oak (Quercus coccinea), hickory (Carya spp.), sourwood (Oxydendrum arboreum), red maple (Acer rubrum), and black locust (Robinia pseudoacacia).

Figure 3. Each plot in the 30, 50, 70, and 90 year-old stands was arranged similarly with marked and repeatable locations for the measurement of each LIDAR pixel. Forest density and basal area (entire plot), tree height (of three tallest plot trees), plant area index (on each of 9 subplots), and GPS readings (on each plot corner and plot center) were collected.

AcknowledgementsWe thank the National Science Foundation for financial support (Award DEB-1110742). We thank Balsam Mountain Preserve for permission to sample on their property, especially Michael Skinner, Ron Lance, and Blair Ogburn. We thank Cody Amakali at Appalachian State University for LIDAR data processing.

Within the Balsam Mountain Preserve study site, four montane oak-hickory forest stands were identified across a chronosequence representing differing successional stages (30, 50, 70 and 90+ years since disturbance). Ground-based data collection for each plot included tree species and diameter (measured with a DBH tape). In addition, the three tallest trees in each plot were identified and height was measured using a Vertex Laser Hypsometer. Plant area index was measured using the LAI 2000 leaf area index meter. The remotely sensed LIDAR data used to predict tree height were accessed through the State of North Carolina and developed using ArcGIS.

Figure 10. Co-authors TJ Souther, Robbie Kreza, and Marcus Mentzer at Balsam Mountain Preserve.

Figure 4. The vegetation height layer was calculated by subtracting the difference in height of the bare earth data layer from the first return data layer.

Figure 8. LIDAR derived tree height vs. field measured tree height in four montane oak-hickory stands from 30 to 90 years old.

Figure 5. Plant area index versus stand age as measured with a LAI 2000 in October 2010 and in May 2011 in four montane oak-hickory stands from 30 to 90 years old.

Figure 6. (a) Relative importance value of tree species in four montane oak-hickory sites from 30 to 90 years old. (b) Stand density and stand basal area vs. stand age across the 30 to 90 year-old sites.

1) Our age chronosequence in montane oak-hickory forests resulted in decreasing density and increasing basal area from 30 to 90 year-old stands and plant area index reached a maximum in 50 year-old stands.

2) LIDAR derived tree height accurately (linear regression slope of 1.01 and R2= 0.92) predicted tree height when compared to ground based laser hypsometer measurements.

3) For all stands, except the 30-year old, the plot level LIDAR derived tree height was representative of the entire stand (see Figure 7).

4) Plant area index varied from 3.26 to 4.16 m2/m2 with a peak in the 50 year-old stand. May 2011 plant area index values were lower because measurements were collected before leaf expansion reached a maximum.

rho = -1.00, P = 0.08

rho = 1.00, P = 0.08

Figure 9. Measuring tree stand density and basal area in the 70-year old stand at Balsam Mountain Preserve near Western Carolina University.Figure 7. LIDAR derived plot tree height and stand tree height

distributions in four montane oak-hickory stands from 30 to 90 years old. * = median plot and stand heights significantly different

*

30 Year Plot

50 Year Plot70 Year Plot

90 Year Plot

Tree Locations

Low : -1.39

High : 44.53

Vegetation Height (m)

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