LOBLOLLY PINE (PINUS TAEDA L.) PLANTATION RESPONSE TO MECHANICAL SITE PREPARATION

IN THE SOUTH CAROLINA AND GEORGIA PIEDMONT

Michael Paul Cerchiaro

Thesis submitted to the Faculty of the

Virginia Polytechnic Institute and State University

In partial fulfillment of the requirements for the degree of

MASTER OF SCIENCE

in

Forestry

James A. Burger, Chair

W. Michael Aust

Shepard M. Zedaker

John L. Torbert

October 21, 2003 Key Words: loblolly pine plantations, mechanical site preparation, carbon sequestration,

site nitrogen, Piedmont

ii

LOBLOLLY PINE (PINUS TAEDA L.) PLANTATION RESPONSE TO MECHANICAL SITE PREPARATION

IN THE SOUTH CAROLINA AND GEORGIA PIEDMONT

Michael Paul Cerchiaro

(ABSTRACT)

Site preparation is fundamental for establishing loblolly pine (Pinus taeda L.)

plantations, but long-term sustainability of plantations established using mechanical

treatments is in question because of concerns regarding soil tillage and the removal of

harvest residue and soil organic matter. A study was installed in 1981 on 12 locations in

northeastern Georgia and west-central South Carolina to evaluate pine plantation

response to mechanical site preparation. Site preparation treatments induced gradients of

organic matter manipulation and soil tillage. The treatments included: Control,

Chop/Burn, Shear/Disc, Shear/V-Blade, Shear/Rake, and Shear/Rake/Pile. Research was

conducted to address the following objectives: (i) compare rotation-age forest response

to several intensive site preparation treatments used to establish pine plantations in the

Piedmont of the southeastern United States; (ii) correlate growth response with the

gradients of soil organic matter removal, soil tillage, and hardwood control; (iii)

determine the influence of intensive management on the amount of carbon contained in

pine plantations.

All site preparation treatments increased year-18 volume accumulation compared to

the control treatment. Chop/Burn and Shear/Disc treatments, with pine volumes of 214

m3 ha-1 and 232 m3 ha-1, respectively, conserved harvest residue and out-performed the

Shear/Rake treatment (191 m3 ha-1), which completely removed harvest residue.

Treatments that included tillage provided growth benefits that lasted throughout the

iii

rotation even when tillage was accompanied by complete organic matter removal.

Hardwood competition had the greatest influence on pine volume accumulation,

explaining over 54% of the variation in pine growth at age 18. Treatments that included

tillage most effectively controlled hardwood competition.

At year 18, site preparation treatments significantly affected soil organic matter

(SOM) content; however, soil nitrogen, foliar nitrogen, bulk density, and macroporosity

were not affected by site preparation. All treatments were equally deficient in foliar

nitrogen. The Shear/Disc and Shear/Rake/Disc treatments had a significantly positive

relationship between foliar nitrogen and pine volume. These treatments had lower

hardwood basal areas (below 15%), indicating that once hardwoods were controlled,

nitrogen became limiting to pine growth.

Using pre-harvest characterization data, carbon accumulation during old-field

succession increased fourfold compared to agricultural sites on the nearby Calhoun

Experimental Forest. Carbon accumulation on these old-field loblolly pine sites reached

quasi-equilibrium after 40 years as shown by uncut reference stands. Site preparation

significantly affected the amount of soil C in the upper 20 cm of the soil. Those site

preparation treatments that removed harvest residue and accelerated SOM decomposition

through tillage had the lowest soil carbon levels. The Shear/Rake/Disc treatment had

10% lower soil carbon content than the Control and Shear/V-Blade treatments.

iv

ACKNOWLEDGMENTS

I would first like to thank my predecessors for their work on this project.

Champion International’s role in the installation of this project was essential to be able to

evaluate these stands at year 18. Previous graduate students’ sweat paved the way for my

work and I am in their debt. I would like to specifically thank Doug Lantagne, Ted

Needham, and George O’Connor for their interpretation and documentation of stand

establishment data.

During the 1999 measurements, former Champion employees were extremely

helpful in accomplishing our goals. John Lyon, James Hodges, and Kirk McEachern all

played huge roles in the field crew’s success. Thanks to field crew members Terry

Lasher, Erika Peterson, and Jay Frost. The crew consistently demonstrated a superior

work ethic, resolve, and commitment to collecting and managing data and field samples.

I will always have fond memories of those four months. Thanks to David Mitchem,

Mike Spinney, Brian Long, and Terry Lasher for their assistance in the laboratory. Four

months of field work quickly turned into two years of lab work and I thank them all for

their contributions.

Thanks to the graduate student family I was a part of at Virginia Tech: Andy Scott,

Jason Rodrigue, Tonya Lister, Eric Bendfeldt, Cristina Siegel Issem, Yi-Jun Xu, and Dan

Kelting. Thanks for the countless discussions. I’d like to specifically recognize Dan for

his role in my development as an undergraduate while he was my TA in Forest Ecology

and Management.

I would also like to thank my committee chair Jim Burger. I can’t express the

amount of gratitude I have for Jim. I have never met a man with more patience, even-

v

temperament, and professionalism. When I was an undergrad, Jim encouraged my

interest in soils and silviculture. His teaching, dedication, and expertise in forest soils

research has resulted in my current skill set.

Finally, I would like to thank my family. Few people in a person’s life affect who

you are, where you’ve been, and where you’re going as much as your family. Thanks to

my parents Frank M. Cerchiaro and Mary Jane Watkins for being there in good times and

in bad. I’ve always had comfort knowing you both have been there for me as a safety

net. You’ve made me who I am today; thank you. Thanks to my brother Dave who has

taught me so much without even knowing it. Few people in my life can bring a smile to

my face like my bro. Thanks to my grandfather Frank L. Cerchiaro. I don’t need to

explain what Pap has taught me because it would be longer than this thesis.

vi

DEDICATION

This work is dedicated to the human intellect and the sustainable evolution of our planet.

"The significant problems we face cannot be solved at the same level of thinking we were at when we created them."

- Albert Einstein (1879-1955)

vii

TABLE OF CONTENTS Page ABSTRACT....................................................................................................................... ii

ACKNOWLEDGMENTS ............................................................................................... iv

DEDICATION.................................................................................................................. vi

LIST OF FIGURES ......................................................................................................... ix

LIST OF TABLES ........................................................................................................... xi

CHAPTER 1. INTRODUCTION .....................................................................................1

Objectives ...................................................................................................................2

Hypotheses..................................................................................................................2

CHAPTER 2. LITERATURE REVIEW .........................................................................4

Introduction.................................................................................................................4

Historical Context of Site Preparation ........................................................................5

Above-Ground Characteristics as Affected by Site Preparation.................................7

Crop Tree Response...........................................................................................7

Competition........................................................................................................9

Site Preparation Effects on Soil Nitrogen.................................................................10

Soil Physical Properties ............................................................................................12

Conceptual Framework....................................................................................12

Soil Tillage.......................................................................................................14

Carbon Sequestration as Affected by Site Preparation .............................................15

CHAPTER 3. MATERIALS AND METHODS............................................................17

Project Overview and History...................................................................................17

Study Area ................................................................................................................18

Soils ..........................................................................................................................19

Treatments.................................................................................................................19

Field Work ................................................................................................................21

Laboratory Procedures ..............................................................................................23

Soil ...................................................................................................................23

Litter.................................................................................................................24

Foliage..............................................................................................................24

Statistical Procedures ................................................................................................24

Calculations......................................................................................................24

viii

Carbon Inventory ....................................................................................25

Experimental Design........................................................................................26

Data Analysis ...................................................................................................26

CHAPTER 4. PINE PLANTATION RESPONSE TO SITE PREPARATION ........28

Results and Discussion .............................................................................................28

Tree and Stand Response to Site Preparation ..................................................28

Pine Density ............................................................................................28

Pine Height..............................................................................................29

Pine Diameter..........................................................................................30

Individual Tree Volume..........................................................................30

Pine Volume Response at Year 18..........................................................30

Pine Volume Response over Time..........................................................32

Tree Response to Site and Soil Factors............................................................34

Hardwood Competition...........................................................................34

Soil Organic Matter Effects on Forest Productivity ...............................37

Soil Nitrogen...........................................................................................39

Foliar Nitrogen........................................................................................42

Bulk Density and Porosity ......................................................................44

Conclusions...............................................................................................................45

CHAPTER 5. CARBON ACCUMULATION AS A FUNCTION OF LAND USE AND FOREST MANAGEMENT..........................................................................48

Results and Discussion .............................................................................................48

Carbon Accumulation with Time.....................................................................48

Site Preparation Treatment Effects on Carbon Storage ...................................51

Conclusions...............................................................................................................55

CHAPTER 6. SUMMARY AND CONCLUSIONS......................................................57

LITERATURE CITED ...................................................................................................59

APPENDICES .................................................................................................................67

Appendix A. Soil Physical Properties.......................................................................68

Appendix B. Pine Volume, Hardwood Basal Area, and Carbon Inventory .............71

Appendix C. Site Nitrogen........................................................................................79

VITA..................................................................................................................................86

ix

LIST OF FIGURES

Page Figure 1. Study locations and hypothetical layout for one of 12 replications of the

study.................................................................................................................19

Figure 2. Illustration of one of the 379 permanent 0.04-ha plots....................................22

Figure 3. Mean annual increment (MAI) by site preparation treatment of loblolly pine plantations in the southern Piedmont region....................................................32

Figure 4. Summary of volume response by site preparation treatment in loblolly pine plantations in the southern Piedmont region relative to the Chop/Burn treatment ..........................................................................................................33

Figure 5. Scatter plot of pine volume growth as a function of percent hardwood basal area in loblolly plantations located in the southern Piedmont region..............35

Figure 6. Scatter plots by treatment illustrating hardwood basal area effects on loblolly pine volume growth............................................................................36

Figure 7. Soil organic matter (SOM) of the upper 20 cm of the soil in loblolly pine plantations in the southern Piedmont region by site preparation treatment.....38

Figure 8. Loblolly pine volume as a function of soil organic matter (SOM) of the upper 20 cm of the soil for four site preparation treatments in the southern Piedmont region ...............................................................................................39

Figure 9. Total soil nitrogen content of the upper 20 cm of the soil in loblolly pine plantations in the southern Piedmont region....................................................40

Figure 10. Pine volume as a function of total soil nitrogen of the upper 20 cm of the soil in loblolly pine plantations in the southern Piedmont region ...................41

Figure 11. Pine volume as a function of total soil nitrogen concentration in loblolly pine plantations in the southern Piedmont region............................................41

Figure 12. Foliar nitrogen concentration in loblolly pine for four site preparation treatments in the southern Piedmont region.....................................................42

Figure 13. Pine volume as a function of foliar nitrogen concentration in loblolly pine for four site preparation treatments in the southern Piedmont region .............43

Figure 14. Loblolly pine volume as a function of bulk density and macroporosity of the A and B horizons for four site preparation treatments in the southern Piedmont region ...............................................................................................45

Figure 15. Carbon accumulation in forest litter and upper 20 cm of soil as affected by land use and time in loblolly pine stands in the southern Piedmont region.....49

Figure 16. Relative change in soil carbon (upper 20 cm) in 18-year-old loblolly pine plantations compared to pre-harvest carbon levels in the southern Piedmont region as a function of site preparation treatment............................................52

x

Figure 17. Site preparation treatment effect on soil carbon content in the upper 20 cm of soil in loblolly plantations of the southern Piedmont region.......................53

Figure 18. Carbon inventory of loblolly pine plantations in the southern Piedmont region as a function of site preparation............................................................54

xi

LIST OF TABLES Page

Table 1. The ANOVA for a randomized complete block design with subsampling ........26

Table 2. Pine density, height, diameter, individual tree volume, stand volume, and hardwood competition on site-prepared loblolly pine plantations in the southern Piedmont region ...................................................................................29

1

CHAPTER 1. INTRODUCTION

Site treatments as a component of pine plantation management are important for

meeting a growing international demand for wood products. Modifying sites to

concentrate biomass into genetically superior crop trees has proven to be economically

viable with appropriate management. Beginning around 1950, volume gains in pine

plantation management were achieved by planting seedlings instead of relying on natural

regeneration. Over time it became evident that increasing the quality of the planting

stock through the selection of genetically superior trees would increase growth rates even

more. While genetics were gradually improving, the benefits of cultural treatments such

as site preparation, fertilization, and weed control were being investigated. These

advances occurred slowly over a 40-year period and evolved into modern, intensive

plantation silviculture.

Matching sites with the appropriate seedling stock and cultural treatments has

become central to intensive pine plantation management in the southern pinery. To

accomplish this, forest managers must consider a whole host of factors in order to make

appropriate management decisions on their land base. These decisions must take into

account site-specific factors (e.g., soils, competition, drainage, aspect, slope, etc.) as well

as temporal considerations (e.g., net present value of investment, climate, stand

dynamics, etc.) in order to maintain economic and biological sustainability.

Pine plantation management in the Piedmont of the southeastern U.S. includes the

use of large-scale mechanical site preparation treatments to ready sites for planting and to

control hardwood competition. Traditional mechanical site preparation recommendations

used tillage and harvest residue removal to simulate favorable “old field” conditions.

2

While the early growth on these mechanically-prepared sites was rapid, early treatment

comparisons indicated that harvest slash and surface soil removal may not create the most

advantageous conditions for tree growth (Glass, 1976). A study was initiated in 1980 to

investigate the long-term effects of site preparation and organic matter removal on the

tree growth, soil quality, and sustainability of Piedmont loblolly pine plantations.

Objectives

The primary objectives of this study are to:

1. Compare rotation-age forest response to several intensive site preparation treatments

used to establish pine plantations in the Piedmont of the southern United States;

2. Correlate growth response with the gradients of soil organic matter removal, soil

tillage, and hardwood control;

3. Determine the influence of intensive management on the amount of carbon contained

in pine plantations.

Hypotheses

This project was created to address questions concerning the use of mechanical site

preparation in the Piedmont. These questions have been addressed by other studies over

varying time scales and for various regions. This set of questions directly pertains to

rotation-length response of loblolly pine in the Piedmont of the southeast. The following

alternate hypotheses were tested in this study:

HA: 1) Pine productivity will be lowest on the treatments that remove organic matter

and have the highest level of tillage.

HA: 2) The nitrogen status in the plantations will decrease proportionately with

removal of organic matter and increasing levels of tillage.

3

HA: 3) As the level of organic matter removal and tillage intensity increase, carbon

storage in the soil will decrease.

4

CHAPTER 2. LITERATURE REVIEW

Introduction

The role of plantation forestry in the production of wood products has dramatically

increased with a decreasing per-capita land base. Plantations occupy 17% of the

forestland in the southeast (Guldin and Wigley, 1998; Conner and Hartsell, 2002). The

desire to maximize the production of wood volume on a given acre of forest has

necessitated the development of intensive management strategies. Productivity on these

intensively-managed pine plantations in the southeast has increased productivity over

naturally-regenerated forests by 11 m3 ha-1 yr-1 to 18 m3 ha-1 yr-1 (Stanturf et al., 2003).

These intensive management regimes have increased yield, but the sustainability of these

systems has been questioned (Stone, 1975; Balmer, 1978). Most of the research in this

area addresses possible site quality loss resulting from harvesting and site preparation

activities that manipulate the forest site. The capacity of forest soils to sustain forest

productivity at current levels while possible site quality losses occur as a result of soil

disturbance, nutrient depletion, and a decrease in favorable rooting volume is in question

(Stone, 1987). Powers et al. (1990) reviewed examples of productivity decline in a

variety of forest types and regions and concluded that losses of site organic matter and

soil macroporosity are usually associated with productivity declines. Documented cases

of productivity decline in southeastern forests are rare, but Pritchett (1981) suggests that

intensive management causing nutrient losses through manipulation of the soil resource

could cause a decline in forest productivity.

Natural succession occurs through a series of gradual changes that result in a

species distribution shift (Coile, 1937). These changes include light dynamics, organic

5

matter decomposition, vegetative competition, soil temperature, soil chemistry, and

nutrient cycling. In essence, forest managers through site treatment are manipulating

natural succession to favor an early successional sere. It is possible that these

manipulations might adversely affect a forest’s natural progression, mineral cycling, and

long-term productivity.

Site preparation is used extensively in intensive management regimes and

contributes to site manipulation. This theme has driven an entire research area in forestry

to evaluate common forestry practices in order to assess their near-term productivity as

well as their long-term sustainability. Following is a review of the progression of site

preparation prescriptions and their influence on the forest’s above- and below-ground

characteristics within the context of forest sustainability.

Historical Context of Site Preparation

Natural regeneration was the predominant forest regeneration technique used in the

south until the 1950’s. It soon became evident that natural seeding did not produce the

adequately stocked stands necessary for timber production. This was due primarily to

poor seedling survival and lack of competition control (White, 1982). In the 1930’s and

’40’s, extensive acreages of abandoned agricultural fields were planted with pine

seedlings or left to natural succession. Those agricultural fields planted with pine

seedlings exhibited enhanced growth compared to forested cutover sites planted with the

same seedling stock (Ralston, 1978). This perceived “old-field” effect influenced the

first prescriptions of site preparation regimes in the southeastern Piedmont (Duzan, 1980;

Ralston, 1978) whereby competing vegetation and harvest residue were removed and

soils were tilled. However, early site preparation field trials did not show the same

6

accelerated growth that was evident on old fields (Fox, 1984), because the increased pine

growth on old fields was primarily due to residual fertility caused by nutrient additions to

agricultural crops (Haines et al., 1975).

Site preparation has evolved substantially since foresters attempted to create old

fields, and is still used extensively throughout the world to manipulate forest sites for

plantation establishment (Duzan, 1980). The primary objectives of site preparation are to

clear the site to facilitate planting, control competition, and improve the microsite for

seedling establishment (Crutchfield and Martin, 1982). Typical site preparation in the

southeastern United States includes fire, mechanical, and chemical treatments. These

practices are prescribed on a regional and forest type basis with soil type, competition

control, and management objective as important decision variables. By the mid-1970’s to

late 1980’s, mechanical site preparation remained the method of choice in the

southeastern Piedmont. The highly eroded soils, a propensity to machine plant, and

observed “old-field effect” on loblolly pine succession were the primary justifications for

the use of mechanical site preparation.

Modern site preparation and subsequent plantation management have been

influenced by university-industry research cooperatives (Stanturf et al., 2003). These

cooperatives concentrated on increasing forest productivity through investigation of the

biological response to tree improvement, vegetation management, and nutritional

management as a function of silvicultural treatment and genetic deployment. In addition,

nursery practices were refined, soil-site relationships were investigated, and growth and

yield models were developed. These combined research efforts have aided the

development of site-specific management prescriptions that utilize modern technology

7

while matching environmental and economic constraints with silvicultural objectives.

Still active today, university-industry cooperatives continue to affect plantation

management in the southeast.

Above-Ground Characteristics as Affected by Site Preparation

Crop Tree Response

Site preparation plays an important role in the intensive management of loblolly

pine plantations in the Piedmont of the southeast (Balmer et al., 1976; Dewit and Terry,

1983; Edwards, 1983; Morris and Lowery, 1988; Lowery and Gjerstad, 1991). While

intermediate treatments are becoming more common, the best opportunity for forest

managers to influence future stand characteristics is through site preparation. Most forms

of site preparation will increase survival and growth in young pine stands (Balmer et al.,

1976; Lantagne, 1984; Edwards, 1990; Fredericksen et al., 1991; Knowe et al., 1992;

Wheeler et al., 2003). Very few studies have followed volume response over the course

of the entire rotation, but early growth gains are thought to last throughout the rotation

(Burger and Crutchfield, 1986).

Tree survival is one of the main goals of site preparation because managing poorly

stocked stands is a poor investment (Smith, 1986). The stocking level of a plantation

after the first growing season is critical because filling in a site is cost-prohibitive and is

seldom effective. A stand will usually remain adequately stocked throughout the life of

the plantation if stocking is sufficient after the first year. There are conflicting reports

about mechanical site preparation effects on tree survival. While most site preparation

treatments will improve tree survival, increasing intensity of mechanical site preparation

does not necessarily increase tree survival proportionately (Campbell, 1973; Hu and

8

Ditthavong, 1981; Fox, 1984; Edwards, 1990, Wheeler et al., 2003). Site preparation

effects on mortality are highly site-specific (Wheeler et al. 2003). Tillage increases tree

survival due to the destruction of post-harvest hardwood root stocks and increased

rootability in compact, highly eroded Piedmont soils (Lantagne and Burger, 1983; Knowe

et al., 1992). While good survival is due to a combination of factors, any treatment that

increases soil tilth, decreases competition, and clears the planting area of debris usually

results in increased tree survival.

Soil characteristics and other abiotic factors play a crucial role in growth response

to site preparation. Low-quality sites may not be improved by some site preparation

treatments, particularly those treatments that create a rapid nutrient flush that cannot be

captured by the crop trees (Pritchett and Wells, 1978). In general, with increasing site

preparation treatment intensity, early pine growth increases. Tillage has been shown to

increase the diameter and height growth in young pine trees (Campbell, 1973; Haines and

Davey, 1979; Stransky, 1981; Pehl, 1983; Edwards, 1990; Fredericksen et al., 1991). As

mentioned above, most foresters believe early growth gains at the beginning of the

rotation will carry through to the end of the rotation. However, Burger and Kluender

(1982) hypothesized that those treatments that remove significant quantities of site

organic matter will create nutrient deficiencies at stand closure and cause subsequent

reductions in volume by rotation age. In conclusion, while intensive mechanical site

preparation has been shown to increase survival and early growth of young pines, few

studies have addressed the long-term influence of these treatments on volume growth.

9

Competition

A major factor influencing stand regeneration success and volume growth in pine

plantation silvicultural systems is vegetative competition (Glover, 1982; Lantagne and

Burger, 1987; Gjerstad and Barber, 1987). Growth of pines can be substantially

increased through the reduction of competing vegetation (Fredericksen et al., 1991).

Complete competition control can increase 10- to 12-year pine growth between 115 m3

ha-1 and 160 m3 ha-1(Borders and Bailey, 2001). Miller et al. (2003b) found a similar

response in woody competition control treatments on a variety of sites located in the

southeast. Stand regeneration studies have shown that both herbaceous and hardwood

competitors affect early seedling growth, but only hardwoods have the potential to

influence long-term stand dynamics (Clason, 1978; Bacon and Zedaker, 1987; Haywood,

1994). Glover and Zutter (1993) quantified hardwood competition effects on pine growth

and found a particularly strong, negative, linear relationship between hardwood basal

area at year 6 and pine basal area at year 27. These same authors also found a

relationship between year 3 hardwood basal area and rotation-length pine basal area

(Glover and Zutter, 1993). This relationship demonstrates the importance of hardwood

control at the time of stand establishment because, by stand closure, the amount of

hardwood basal area in the canopy is unlikely to change (Burkhart and Sprinz, 1984).

However, treatments that control competing hardwoods also decrease plant diversity

(Holland et al., 1994; Schabenberger and Zedaker, 1999).

In Piedmont pine plantation management, hardwoods must be controlled to ensure

adequate crop tree survival and growth (Gjerstad and Barber, 1987). In general, the

greater the intensity of mechanical site preparation, the greater the level of hardwood

10

control (Edwards,1990; Fredericksen et al., 1991). Those treatments that include the use

of tillage increase hardwood competition control (DeWit and Terry, 1983; Lantagne and

Burger, 1987). Variation in volume response decreases as hardwood basal area increases

and becomes the dominant factor influencing pine growth (Glover and Zutter, 1993;

Schabenberger and Zedaker, 1999). At lower levels of hardwood competition, other site

quality factors such as available water, available nitrogen, and soil tilth play a role on

volume response, which increases the variability in pine volume growth. Pine volume

growth can decrease by 10% for every 2.3 m3 ha-1 of hardwood basal area (Miller,

2003b).

While hardwood competition control is required for successful plantation

development, complete hardwood removal using mechanical site preparation is expensive

and unnecessary. The amount of site disturbance required for complete hardwood

removal would result in losses of site quality through compaction, soil displacement, and

loss of soil tilth (Miller, 1980; Slay et al., 1987; Lockaby et al., 1988) and would not

result in economic gains. In conclusion, site preparation treatments must control

hardwood competition on Piedmont sites in order to ensure adequate stocking and

plantation growth while minimizing site disturbance and the need for intermediate release

operations.

Site Preparation Effects on Soil Nitrogen

Site preparation affects the quantity and intensity of soil nitrogen in plantation

systems (Morris and Lowery, 1988). The diversity of site preparation techniques creates

a gradient of site disturbance and therefore gradients in total soil nitrogen and nitrogen

availability. Much of the variation across this gradient is due to the interaction of site and

11

treatment. Piedmont sites have more inorganic N, a larger potential to mineralize N, a

higher concentration of total N, and higher foliar N concentrations than Upper Coastal

Plain sites (Will et al., 2003), and therefore mechanical treatments differ in their impact

on nitrogen status.

Treatments that include the use of raking can displace surface soil along with litter

and coarse woody debris, which results in the depletion of nitrogen sources in the

windrowed areas (Pye and Vitousek, 1985). This may create nitrogen deficiencies in

raked areas due to the removal of large quantities of site nitrogen. On a coastal flatwoods

site, raking reduced soil nitrogen content by 372 kg N ha-1 in the windrowed areas

(Morris et al., 1983). Piedmont sites are even more susceptible to reductions in site

nitrogen from raking with as much as 650 kg N ha-1 being removed (Tew et al., 1986).

However, Piatek and Allen (1999) found that increased harvest residue removal through

site preparation may not decrease nitrogen availability. Harvest type (stem only vs.

whole tree), not site preparation type (Chop/Burn vs. Shear/Rake/Disc), decreased

nitrogen mineralization significantly after 15 years (Piatek and Allen, 1999).

Raking is not the only site preparation treatment that displaces site nitrogen.

Burning can volatilize large quantities of nitrogen depending on fuel variables such as

load, moisture content, and distribution. Some treatments indirectly affect nitrogen

storage through increased nitrogen mineralization and soil erosion (Morris and Pritchett,

1982). Harvesting and site preparation treatments have been shown to accelerate

nitrogen mineralization in the early years of plantation establishment primarily due to

increased soil temperature (Wiade et al., 1988; Vitousek et al., 1992). This increase can

occur for up to five years after harvest and site preparation (Vitousek et al., 1992).

12

Tillage can affect the amount of N stored and supplied; however, the relationship

can be confounded by the increased growth of the crop trees. With soil physical

limitations ameliorated, accelerated pine growth can increase the uptake of site nitrogen

which may distort soil nitrogen variables because of increased nitrogen content in the

trees (Will et al., 2003). Tillage has not been found to influence foliar nitrogen

concentration (Allen, 1990; Piatek and Allen, 1999; Will et al. 2003); however, nitrogen

content in the foliage may be increased (Will et al., 2003). In conclusion, it has been

shown that site preparation increases nitrogen mineralization in the early years of

plantation establishment. This increase, however, may not result in excessive nitrogen

limitations at rotation age.

Soil Physical Properties

Conceptual Framework

Soil physical properties play a large role in loblolly pine plantation growth in the

Piedmont of the southeast (Perry, 1964; Greacen and Sands, 1980; Morris and Lowery,

1988). Due to the truncated nature of Piedmont soils due to eroded surfaces and the high

probability of growing season drought, surface soil strength and water availability often

limit growth. Areas that have had heavy machine traffic can also limit growth at rotation

age (Perry, 1964). Some site preparation treatments, primarily discing, modify the

surface soil to reduce soil strength and increase macroporosity, thereby increasing

available water (Morris and Lowery, 1988). Other mechanical site preparation treatments

such as bedding and subsoiling also change the soil physical condition; however, only

discing was included as a tillage treatment in this study.

13

“Plants can not grow without water” (Letey, 1985). This in a nutshell captures the

essence of the effect of soil physical properties on plant growth. Physical properties

determine how much water is stored in the soil and at what energy potential it will be

available. The soil physical condition dictates where and with what intensity roots grow

and thereby are able to uptake essential nutrients and water. The soil physical

environment relating to plant growth can be separated into four fundamental factors:

aeration, mechanical resistance, water, and temperature (Letey, 1985). These factors are

not independent of each other. One factor cannot be changed without one or more of the

other factors also changing. In addition, one or more of these factors might limit growth

while another factor is at its optimum. For example, if a soil is inundated with water,

plants have an excess supply of water; however, aeration will limit root growth because

of inadequate gas exchange required for root respiration.

Agricultural as well as forest harvesting and site preparation research has sought to

characterize the effect of intensive management scenarios on the soil physical

environment. Bulk density has been used extensively to assess disturbance effects on the

soil physical condition (da Silva et al., 1994). This variable has its interpretive problems;

the relationship between plant growth and bulk density depends on the in situ moisture

content, texture, and organic matter content (Greacen and Sands, 1980). Workers have

labored to create a variable that accounts for the four fundamental factors that influence

the soil physical environment (Letey, 1985) with hopes of increasing the explanatory

power in relation to plant growth (da Silva et al., 1994). Childs et al. (1989) first

introduced the “root growth window,” which was defined as the window of root growth

opportunity that was limited by aeration at high moisture contents and high mechanical

14

impedance at low soil water contents. Bulk density greatly influences the size of the root

growth window; as bulk density increases the root growth window decreases.

Soil Tillage

The use of soil tillage in the management of pine plantations originated with

observations that old-field site characteristics promoted excellent growth of pine trees

(Haines et al., 1975). This perceived old-field effect coupled with the highly eroded

characteristics of Piedmont soils made tillage a commonly used site treatment once the

machinery became available. Tillage treatments increase the exploitable soil volume to

young pine seedlings, increase macropore space, and increase air and water movement

(Morris and Lowery, 1988), though these increases are not likely to remain throughout

the rotation (Schultz, 1973). This increased rootability in young pine stands can partially

explain the increased tree survival commonly found on tilled sites (Edwards, 1990;

Fredericksen et al., 1991; Knowe et al., 1992; Zhou et al., 1998). Increased tree survival

on tilled sites can also be explained by a reduction in hardwood competition through the

destruction of hardwood root stocks, inhibiting sprouting and suckering (Balmer et al.,

1976).

Tillage improves survival and early growth but also changes soil structure,

increases organic matter decomposition (McKee and Shoulders, 1974), and increases

nitrogen mineralization (Burger and Kluender, 1982; Burger and Pritchett, 1984;

Vitousek and Matson, 1985; Waide et al., 1988; Vitousek et al., 1992). While tillage

might provide an increase in stocking levels coupled with reduced hardwood competition,

its financial costs may not justify its use.

15

Carbon Sequestration as Affected by Site Preparation

Carbon dynamics in forest systems has become a huge research issue in recent

years. With a growing research base that shows increasing atmospheric CO2 levels with

time, a need has developed for investigating how carbon is cycled, captured, and released

in forest soils, litter, and biomass. This need has been facilitated both politically and

ecologically. There are conflicting conclusions regarding how forest management fits

into the overall carbon dynamics of terrestrial systems. A forest can be a source or sink

of carbon depending on whether it is intensively managed or not (Johnson, 1992). Most

of our understanding of carbon storage and cycling in soils has been from long term

agricultural studies (Richter et al., 1999; Grigal and Vance, 2000). Agricultural studies

are valuable within the overall conceptual framework of land use effects on carbon

dynamics; however, they do not account for conditions associated with common forestry

practices (Richter et al., 1999).

It has been shown by numerous studies that intensive agricultural practices that

include traditional tillage significantly remove large amounts of organic matter

(Hajabbasi, 1997). When conservation tillage is used in an agricultural setting, an

increase in soil carbon in sandy soils can occur (Hunt et al., 1996). This shows that even

in an annually cultivated land management scenario, soil carbon can be conserved if site

organic matter is conserved. However, forest management differs greatly from

agricultural practices, and comparisons are difficult to make (Grigal and Vance, 2000).

The majority of research conducted in temperate regions has shown that forest

harvesting has little effect on mineral soil carbon (< 10% decrease) (Huntington and

Ryan, 1990), while site preparation has been shown to decrease soil carbon levels

16

(Johnson, 1992). This decrease is larger when treatments include intensive scarification

or tillage (Orlander, 1996). The type of site preparation dictates how much soil C is lost.

As Johnson (1992) points out, it is difficult to account for treatments that displace surface

soil (such as rootraking) in global carbon budgets, because the soil carbon may not

evolve to CO2 since the surface soil is simply displaced.

Given the time frame of carbon dynamics in forest systems, a chronosequence

approach has been used by some researchers to investigate the carbon status before,

during, and after forest establishment. Black and Harden (1995) found that C/N ratios

should be used to account for site differences. This variable includes inherent site

nitrogen, which plays a critical role in soil carbon sequestration (Johnson, 1992; Black

and Harden, 1995). In a rare study that did not use a chronosequence, Richter et al.

(1999) found that an aggrading forest accumulated approximately 39,250 kg ha-1 of

carbon in the forest floor and mineral soil. The majority of this carbon was found in the

litter layer, while only the surface 7.5 cm of the mineral soil layer had a statistically

significant increase in carbon. It is apparent in the literature that aggrading forests

increase carbon capture on a given site, but forest management-induced changes in

carbon capture are unclear.

17

CHAPTER 3. MATERIALS AND METHODS

Project Overview and History

This study began in 1981 with funding and logistical support provided by

Champion International Corporation. Forest soils researchers from Virginia Polytechnic

Institute and State University installed 12 replications of an operational-scale research

project. The initial objectives were to determine how to best prepare different types of

cut-over forest sites in order to optimize stocking and early growth. Mechanical

treatments were needed that reduced harvesting debris and residual vegetation, improved

soil tilth and fertility, and controlled unwanted vegetation. In the process of achieving

these aims, there was concern that unwanted side effects such as organic matter removal,

soil erosion, soil compaction, and nutrient mobilization could reduce long-term

productivity.

A total of 12 20-ha pine-mixed hardwood stands were selected based on previous

land use, above-ground stand conditions, topographic features, and soils. Eight of these

sites were located in Chester, Fairfield, and Newberry Counties in west-central South

Carolina, while the remaining four sites were installed in Wilkes and Oglethorpe

Counties in northeastern Georgia. All stands were naturally-regenerated old-field mature

pine-mixed hardwood stands, ranging in age from 30 to 50 years at the time the study

was installed. All sites were old fields that were in agriculture production for 100 years

or more before being abandoned. They were all upland Piedmont sites on residual soils

formed from metamorphic and igneous parent materials. After a pre-harvest

characterization was conducted, the study areas were harvested and then site-prepared.

18

For a detailed account and description of the harvesting and site preparation, see

Lantagne (1984).

All permanent plots were measured at plantation ages 1, 2, 3, 6, 9, and 18. Above-

ground stand conditions, soil variables, and litter variables were all characterized in each

of the measurement cycles. Over the years, plantation response was measured with

varying degrees of intensity, but this year-18 measurement protocol was similar to the

one used during year 1 to ensure that a clear comparison could be made across the age of

the plantation. In addition to an identical field measurement protocol, all laboratory

methods used in year 1 were used at age 18.

Study Area

The study areas are located in northeastern Georgia and west central South Carolina on

the Piedmont physiographic providence of the southeastern United States (Figure 1). The

southern Piedmont region of the southeastern United Stated extends from central Virginia

into Georgia and Alabama and ranges in width from 80 km in the northern portion to

about 200 km in North Carolina. The elevation ranges from 91 m on the eastern edge of

the fall line to about 366 m as it approaches the Blue Ridge to the West. The climate of

the study areas is classified as humid subtropical and is characterized as having relatively

mild winters and hot summers (Greene, 1953). Rainfall is normally abundant and

averages 121 cm annually. However, droughts are a frequent occurrence during the

growing season, which extends from early April to the first of November (Green, 1953).

19

Figure 1. Study locations and hypothetical layout for one of 12 replications of the study. Checkered area is the Piedmont physiographic province. Each star represents the approximate location of a replicate (block) of the study.

Soils

All sites were established on similar soils primarily consisting of Appling, Pacolet,

Cecil, and Hiwassee soil series. These soils are deep, well drained Ultisols with medium

fertility and moderate permeability. All are clayey, kaolinitic, thermic, Typic

Kanhapludults except for the Hiwassee series, which is a Typic Rhodudult. Minor

differences in color and texture of the subsoil occurs among these soils.

Treatments

The study contained five mechanical site preparation treatments and a control, for a

total of six treatments. Treatments were replicated in 12 blocks located on forest sites in

the Georgia and South Carolina Piedmont. Treatments were installed operationally in

2-ha treatment areas or plots. In each of the treatment plots, 5 permanent 0.04-ha

Study Location and LayoutStudy Location Study Layout

Shear-Rake

Shear-Rake-Disc

Shear-Disc Shear-Vblade-Disc

Control

Chop-Burn

Twelve 15 ha blocks

Six 2.5 ha mechanicalsite preparation treatmentswithin each block

Five 0.04 ha measurementsubplots within eachtreatment

20

subplots were established. All subplots were remeasured at years 1, 2, 3, 6, 9, and 18.

Treatment descriptions are as follows:

1) No site preparation (Control) – This treatment was harvested and hand planted with

no site preparation.

2) Chop/Burn – The site was chopped using an empty 3-m-wide Marden double drum

offset chopper pulled by a Caterpillar D-7 crawler tractor. The area was broadcast

burned two to six weeks later. Due to the light fuel load, fires were light and spotty.

3) Shear/Disc (one-pass) – Shearing and discing were accomplished in one pass using a

Caterpillar D-7 crawler tractor. The shear was attached to the front of the tractor and

was maintained approximately 10 to 15 cm above the forest floor. A 16-disc, double-

gang offset harrow was used for the tillage operation. Due to some debris remaining

on site, the tillage depth varied from 0 to 30 cm.**

4) Shear/V- blade (two-pass) – In the first pass residuals were sheared. In the second

pass a D-7, equipped with a V blade on the front and the same disc-harrow as

mentioned above, aligned debris into “mini-windrows” and disced the soil. The

discing depth was more consistent then in the Shear/Disc treatment since

displacement of debris facilitated better discing. The tillage depth was 20 to 30 cm.

Small windrows of harvest debris were left in rows approximately 3 m apart.

5) Shear/Rake (two-pass) – This treatment was another two-pass system where in the

first pass the residuals were again sheared. Raking occurred on the second pass,

where all debris was piled into large windrows 30 to 100 m apart and then burned.

Care was taken to avoid surface soil penetration by the tines of the rake.

21

6) Shear/Rake/Disc (three-pass) – Shearing and raking were completed as described

above using two passes. In the third pass, the same disc described above was used for

discing. This treatment produced the most intensive discing with the most consistent

tillage depth.

**NOTE: Tillage depth not only varied with debris levels but with the amount of surface

soil. A greater tillage depth resulted in those soils that had deeper surface soils than

those with shallow surface soils or exposed subsoils.

These six mechanical site preparation treatments were designed to induce gradients

of organic matter removal, soil tillage, and hardwood competition.

Field Work

Field work was completed in the winter of 1999. The measurement protocol was

the same used during the first year so a clear comparison could be made across the

rotation. A total of 17 soil samples were taken from the upper 20 cm of the mineral soil

using a standard soil probe with a 2-cm diameter tube at each of the 379 permanent

sampling plots. These 17 samples were taken from two concentric circles, 5 and 10

meters from the southeast corner of each plot. The push tube samples were taken at the

intersection of the cardinal and intercardinal directions and the two concentric circles,

with the 17th sample taken at the southeast corner (Figure 2).

22

Soil Probe (20 cm)

Soil Probe and Litter Sample

LAI Ocular Estimate

N

Figure 2. Illustration of one of the 379 permanent 0.04-ha

plots. Shows the relative position of the soil sampling, litter sampling, and the LAI ocular estimates. Map is not to scale.

In each of the 0.04-ha plots, all planted loblolly pines were measured for diameter

at breast height (DBH) and total height. Hardwood competition was tallied by diameter

class for those stems less than 10 cm in diameter. A 0.008-ha subplot was established in

the center of the plot for hardwood sampling in the control plots due to the large number

of hardwood stems found in this treatment. For hardwood stems greater than 10 cm,

DBH and total height were measured. In addition to a stand inventory, an ocular estimate

of Leaf Area Index (LAI) was estimated using the North Carolina State Forest Nutrition

Cooperative template. These estimates were taken 10 m toward plot center from each of

the plot corners (Figure 2).

23

Foliage samples were taken from five trees per plot. Each sample consisted of 20

fascicles taken from the previous year’s first full flush. Samples were removed from the

upper third of the canopy using a 12-gauge shotgun.

Forest litter samples, Oi, Oe, and Oa layers, were collected from the 379 permanent

sampling plots using 23-cm plastic plates and pruning shears. A total of four samples

were collected and composited for each plot. The four samples were collected at the

intersection of the 5-m circle and the cardinal directions (Figure 2). Samples were taken

by placing the plastic plate on the ground and cutting around the perimeter using the

pruning shears. The litter layer was defined as all material extending downward until the

mineral soil was reached.

Laboratory Procedures

Soil

Loose soil samples were ground and passed through a 2-mm sieve. Samples were

split to create samples for storage and immediate laboratory analysis. Total nitrogen was

determined from a 5.000 gram sample using the Kjeldahl Al block digestion technique

(K2SO4 + HgO + CuSO4 catalyst) (Bremner, 1965b). Nitrogen mineralization was

indexed using an anaerobic incubation. This index was calculated by determining the

amount of NH4 evolved over a 7-day incubation period at 40oC (Bremner, 1965a). Initial

NH4 concentrations were established using a 2M KCl extract. The difference between

the initial NH4 concentrations and the post incubation NH4 levels was used as the index

of mineralizable nitrogen. Concentrations for all of the above procedures were

determined using a colorimetric analysis (Bran and Luebbe TRAACS). Soil organic

24

matter (SOM) was determined using a Walkley-Black wet digestion method (Allison,

1965).

Litter

Litter biomass was estimated by weighing after the sample reached a constant

weight in a 65oC oven. The entire sample was then ground using a Wiley Mill and then

passed through a 2-mm sieve. The sample was ashed in a muffle furnace at 550oC for 24

hours to correct for any mineral soil contamination. The carbon content was determined

using a LECO Total Carbon Analyzer, (LECO Corp., Saint Joseph, MI).

Foliage

All foliage samples were dried in a 65oC oven to a constant weight. After the

samples were weighed, the fascicles were recounted to ensure a correct needle count so

an accurate unit needle weight could be determined. The samples were then ground in a

Wiley Mill and passed though a 2-mm sieve. The samples were then analyzed for

nitrogen using a thermal conductivity detector (Elementar varioMAX CNS).

Statistical Procedures

Calculations

All tree measurement data were expressed on a per-hectare basis. Basal area was

calculated with the following equation:

BA (m2) = DBH2*0.00007854

Individual tree basal area was calculated and then summed per plot. The total summed

plot data were then blown up based on plot size. Individual tree volume was calculated,

converted to metric, and then summed for each plot using the equation from Amateis and

Burkhart (1987).

25

Total Volume (ft3) =0.21949+0.00238*(DBH2)*HT

Carbon Inventory

A carbon inventory was conducted for the upper 20 cm of the mineral soil, forest

litter, loblolly pine biomass, and hardwood biomass. SOM values as determined by the

Walkley-Black wet oxidation procedure were converted to soil C concentrations by

dividing SOM concentrations by 1.7 (Allison, 1965). The mass of carbon per unit area

was determined by multiplying the carbon concentration by soil depth and year 9 bulk

density. When appropriate, weighted averages were used if the depth of 20 cm included

more than one soil horizon. Forest litter samples were weighed and a subsample was

used for C determination using a LECO Total Carbon Analyzer (LECO Corp., Saint

Joseph, MI). A subsample was ashed in the muffle furnace at 550oC for 24 hours for an

ash free estimate of C.

Loblolly pine above- and below- ground biomass were estimated using Baldwin’s

(1987) biomass equations. Carbon in the biomass was calculated using a standard

conversion factor of 0.5 kg C kg-1 biomass (Reichle et al., 1973). Above-ground

hardwood biomass was calculated using the all-species regression equation published for

hardwood species in the Piedmont using DBH and total height as the independent

variables (Clark et al., 1986). Below-ground biomass was calculated by multiplying

above-ground biomass by 0.197 (Birdsey, 1992). Once the above- and below-ground

hardwood biomass were summed, biomass carbon was determined by multiplying the

total biomass by 0.497 (Birdsey, 1992).

26

Experimental Design

The experimental design was a randomized complete block design with

subsampling. The experimental units were the 2-ha treatment plots, and the observational

units were the 0.04-ha permanent sampling plots (Table 1).

Table 1. The ANOVA for a randomized complete block design with subsampling. This table was used for testing treatment effects.

Source Degrees of Freedom Mean Square Error F-Test Blocks b – 1 = 11 SS(B) / 11 Treatments t – 1 = 5 SS(T) / 5 MS(T) / MSE Exp. Error (b – 1)(t – 1) = 55 SS(EE) / 55 Total (bt – 1) = 71

Data Analysis

Plot means for tree, hardwood competition, soil, litter, and foliage measurements

were calculated for a total of 379 observations across all sites in the study. Mean

separations were done using Duncan’s range test at an alpha of 0.1. All data analysis was

performed with SAS in PROC GLM and PROC REG.

For most analyses, all treatments were included. When specific cause and effect

comparisons were made across the gradient of harvest residue removal, tillage, and

hardwood competition control, the Control and Shear/V-Blade treatments were removed.

This was done to minimize the influence of a disproportionate amount of hardwood

competition found in these treatments.

When comparisons were made across time periods, such as with the carbon

chronosequence, a one-sided t-test was used on pooled treatment level data. The site

preparation data were subtracted from pre-harvest levels by treatment (i.e., soil carbon

27

and litter carbon) and the difference was tested to see if it was significantly different from

zero.

Regression analysis was used to determine the relationship between tree response

and site and soil factors. All analyses were done with SAS v. 8.0 in PROC REG. Before

final variable selections were made, the full model was tested for multicollinearity. This

was done using two methods, variance inflation factors (VIFs) and a correlation matrix.

A benchmark of 10 was used with the VIFs. The correlation matrix identified potential

candidates for removal when a correlation of >0.9 was present. After final variable

selection using a combination of R2, mean square error, and Mallow’s Cp statistic, highly

influential observation (HIO) diagnostics were conducted to remove such observations.

This was accomplished using residual plots, DFFITS and DFBETAS. The removal of

HIOs decreases MSE, increased R2, and increased the overall power of the model.

28

CHAPTER 4. PINE PLANTATION RESPONSE TO SITE PREPARATION

Results and Discussion

Tree and Stand Response to Site Preparation

Pine Density

Pine density followed the gradient in tillage intensity with Shear/Rake/Disc >

Shear/Disc > Shear/V-Blade > Chop/Burn > Shear/Rake (Table 2). Pine density ranged

from 555 trees ha-1 to 963 trees ha-1 on the Control and Shear/Rake/Disc treatments,

respectively. Treatments that included the highest level of tillage, Shear/Rake/Disc and

Shear/Disc, resulted in the highest pine densities at year 18 with 963 trees ha-1 and 970

trees ha-1, respectively (Table 2). Stocking levels are affected by the type and intensity of

site preparation prescribed on pine plantation sites (Campbell, 1973; Hu and Ditthavong,

1981; Fox, 1984; Edwards, 1990). Tillage increased survival due to the destruction of

hardwood root stocks and increased rootability (Lantagne and Burger, 1983; Knowe et

al., 1992). Frederickson et al. (1991) also noted that hardwood stems ha-1 decreased with

tillage compared to chopped sites. During stand establishment on these Piedmont sites,

tree survival followed the relative intensity of site preparation (Lantagne, 1984). The

Control treatment had the poorest survival throughout the rotation and by year 18 was

understocked, with only 555 trees ha-1 (Table 2). By stand closure, all treatments except

for the Control resulted in an adequately stocked stand (unpublished data) using Smith et

al.’s (1965) 740 trees ha-1 as a benchmark. This relationship held true through year 18

(Table 2).

29

Table 2. Pine density, height, diameter, individual tree volume, stand volume, and

hardwood competition on site-prepared loblolly pine plantations in the southern Piedmont region. Control was not included in the means separation due to its unequal variance and statistical bias. Different letters within columns show that values are significantly different (ά = 0.1).

Hardwood Comp.

Treatment

Pine Density

(trees ha-1) Height

(m) DBH (cm)

Individual Tree Vol.

(m3)

Stand Volume (m3 ha-1)

HWBA (m2 ha-1)

%HWBA (%)

Control 555 14.8 19.3 0.23 129 13.2 43.8 Chop/Burn 879 ab 15.4 a 20.8 ab 0.25 a 214 a 5.7 ab 15.8 ab Shear/Disc 970 a 15.5 a 20.3 abc 0.24 ab 232 a 5.2 ab 13.7 b Shear/V-Blade 849 b 15.5 a 20.8 ab 0.25 a 207 ab 6.3 a 17.6 a Shear/Rake 842 b 15.0 a 20.1 bc 0.23 b 191 b 6.1 a 18.1 a Shear/Rake/Disc 963 a 15.4 a 19.6 c 0.22 b 212 ab 4.6 b 13.4 b

The Shear/V-Blade treatment included a tillage operation in the second pass;

however, the tillage was not as uniform as in the Shear/Rake/Disc and Shear/Disc

treatments because the harvest slash was concentrated between planting rows. While not

quantified, the majority of hardwood competition was found in these inter-row areas,

which resulted in higher hardwood competition levels and fewer pines. The Shear/Rake

treatment had the lowest pine densities for all site preparation treatments, primarily due to

the lack of tillage and hardwood competition control.

Pine Height

Pine height ranged from 14.8 m in the Control to 15.5 m in the Shear/Disc and

Shear/Rake treatments. Year 18 height was not significantly affected by site preparation

treatment and was within a relatively small range (Table 2). Lantagne (1984) found a

significant positive height response at year 2; the trees in Shear/Rake/Disc, Chop/Burn,

and Shear/Rake treatments were 16 cm, 10 cm, and 15 cm taller than the control trees,

respectively. This early height response was not sustained through year 18 (Table 2). As

in our study, Edwards (1990) found no significant increase in pine height due to tillage

30

when Shear-Chop and Shear-Rake-Disk treatments were compared at year 5. Early

height response to site preparation in this study was probably a function of increased

nitrogen availability, increased rootability, and decreased competition.

Pine Diameter

Pine diameter at breast height (DBH) ranged from 19.3 cm in the Control treatment

to 20.8 cm in the Chop/Burn and Shear/V-Blade treatments. The Chop/Burn and

Shear/V-Blade treatments had a significantly larger mean DBH than the Shear/Rake/Disc

treatment at year 18 (Table 2). Differences in tree diameter were largely a function of

density; the greater the density, the smaller the diameter.

Individual Tree Volume

Individual tree volume ranged from 0.22 m3 in the Shear/Rake/Disc treatment to

0.25 m3 in the Chop/Burn and Shear/Rake treatments (Table 2). The Chop/Burn and

Shear/Rake treatments had significantly higher individual tree volumes than the

Shear/Rake and Shear/Rake/Disc treatments. Individual tree volume also followed the

trend in DBH and pine density. Pine density affected DBH, which in turn affected the

individual tree volume; the higher the pine density, the lower the DBH, and subsequently,

the lower the DBH, the lower the individual tree volume (Table 2).

Pine Volume Response at Year 18

Pine volume at year 18 ranged from 129 m3 ha-1 to 232 m3 ha-1 in the Control and

Shear/Disc treatments, respectively (Table 2). Any mechanical site preparation treatment

increased pine volume accumulation compared to the control treatment (p<0.0001) at

year 18. When a means separation test was performed without the Control treatment, the

Shear/Disc and Chop/Burn treatments with 232 m3 ha-1 and 214 m3 ha-1 had higher stand

31

volumes than the Shear/Rake treatment at 191 m3 ha-1 (ά = 0.1) (Table 2). Tree volumes

in the Shear/V-Blade and Shear/Rake/Disc treatments with 207 m3 ha-1 and 212 m3 ha-1

were not significantly greater than the tree volumes resulting from Shear/Rake only.

Mean annual increment (MAI) ranged from 7.2 m3 ha-1 yr-1 in the Control to 12.9

m3 ha-1 yr-1 in the Shear/Disc (Figure 3). Numerous researchers have shown that site

preparation increases volume growth across a variety of site types when compared to

non-site prepared plantations (Balmer et al., 1976; Edwards, 1983; Morris and Lowery,

1988). Much of the volume increase can be attributed to early rotation soil physical

properties (Morris and Lowery, 1988); however, competition control resulting from site

preparation seemed to exert a larger effect on volume growth after canopy closure

(Harrington and Edwards, 1996).

This study confirmed that any mechanical site preparation, even without

intermediate treatments, increased the MAI by at least 3.4 m3 ha-1 yr-1 (Figure 3). Those

treatments that included chopping or tillage (i.e., Chop/Burn, Shear/Disc, Shear/V-Blade,

and Shear/Rake/Disc) had the largest gains in volume, possibly due to better competition

control. The Shear/Rake treatment removed harvest residue but did not include tillage.

The lack of tillage and poor hardwood competition control were the likely causes of the

poor volume response (Table 2). In addition, the Shear/Rake treatment had an early

rotation compacted rooting environment, causing poor survival (Lantagne, 1984). These

results suggest that soil physical properties and competition play a significant role in the

productivity of pine plantations in the Piedmont.

32

0.02.04.06.08.0

10.012.014.016.0

Control

Chop/Burn

Shear/

Disc

Shear/

V-Blad

e

Shear/

Rake

Shear/

Rake/D

isc

MA

I (m

3 ha-1

yr-1

)

Figure 3. Mean annual increment (MAI) by site preparation treatment of

loblolly pine plantations in the southern Piedmont region. The Control treatment was not included in the means separation due to its unequal variance and statistical bias. Different letters within columns show that values are significantly different (ά = 0.1).

The trend in pine volume response suggests that treatments that included tillage

changed site conditions in a beneficial way. The Shear/Disc, Shear/Rake/Disc, and

Shear/V-Blade treatments all outperformed the Shear/Rake treatment by 18%, 10%, and

8%, respectively. Chopping and tillage provided benefits that lasted throughout the

length of the rotation through competition control and increased rootability.

Pine Volume Response over Time

Using the historical data set in conjunction with age 18 measurements, we plotted

volume response over time for the Shear/Rake/Disc, Shear/Disc and the Shear/Rake

treatments compared to the Chop/Burn treatment (Figure 4). Compared to the Chop/Burn

treatment (zero base line in Figure 4), a traditional inexpensive practice used for decades

in the southeast, these treatments represented tillage only (Shear/Disc), residue removal

only (Shear/Rake), and a combination of tillage and residue removal (Shear/Rake/Disc).

a a ab b ab

33

Early mean pine volume response across the 12 blocks generally followed treatment

intensity until age 6. Residue removal plus tillage resulted in the highest volume

response followed by tillage only with residue intact. Residue removal without tillage

resulted in the slowest early growth. Treatments that included discing improved the

seedling rooting environment, provided better hardwood competition control, and

increased availability of nitrogen during stand establishment (Lantagne, 1984).

Figure 4. Summary of volume response by site preparation treatment in loblolly pine plantations in the southern Piedmont region relative to the Chop/ Burn treatment. Measurements were taken at years 1, 2, 3, 6, 9, and 18.

Research on both the Piedmont and Coastal Plain has clearly shown that discing

reduces hardwood competition (Morris and Lowery, 1988). On these Piedmont sites,

hardwood competition control played an important role in survival and early volume

growth (Lantagne, 1984). Discing can also increase the rate and amount of nitrogen

mineralization (Burger and Prichett, 1984; Morris and Lowery, 1988; Piatek and Allen,

1999), thereby increasing the early supply of nitrogen in young stands (Vitousek and

Matson, 1985; Vitousek et al., 1992). It was hypothesized that this early acceleration of

-30

-20

-10

0

10

20

30

40

50

60

0 2 4 6 8 10 12 14 16 18 20

Plantation Age (Years)

Ral

ativ

e St

and

Volu

me

Diff

eren

ce

(%)

Shear/Rake/Disc

Shear/Disc

Chop/Burn

Shear/Rake

34

nitrogen mineralization could create nitrogen limitations by canopy closure (Burger and

Kluender, 1982; Neary et al., 1984; Munson et al., 1993). These authors speculated that

an early flush of nitrogen due to increased nitrogen mineralization, and the inability of

young seedlings to capture that nitrogen, could cause a decrease in relative growth by

stand closure around age 10.

They suggest that those treatments that conserved harvest residue should

outperform those that removed it because of increased long-term nutrient availability that

would accompany the slow decomposition of harvest residue. Our data show that after

stand closure those treatments that conserved harvest residue, Chop/Burn and Shear/Disc,

outperformed those treatments that did not. This response supported the hypothesis that

harvest residue conservation increases soil and site quality and plantation yield.

Tree Response to Site and Soil Factors

Hardwood Competition

The Control treatment areas had the highest mean hardwood basal area, with 13.2

m3 ha-1, and can account for the poor stocking levels and stand volume growth on these

untreated areas (Table 2). Of the site preparation treatments, the Shear/V-Blade and

Shear/Rake treatments had the highest hardwood basal areas, with 6.3 m3 ha-1 and 6.1 m3

ha-1, respectively. These treatments were statistically higher than the Shear/Rake/Disc

treatment, which had the lowest hardwood basal area of 4.6 m3 ha-1. On these sites, over

54% of the variation in pine volume was explained by hardwood basal area (HWBA) and

percent hardwood basal area (%HWBA) using regression analysis. The type and

intensity of mechanical site preparation determines the extent of hardwood competition

control. In this study, this relationship was evident at stand establishment (Lantagne,

35

1984) as well as at near rotation end. Burkhart and Sprinz (1984) showed that the percent

hardwood competition in the canopy does not change after canopy closure. Treatments

that included tillage had the fewest hardwoods after stand closure, which in turn

minimized the presence of hardwoods by age 18.

At low levels of hardwood competition, other growth factors often limited volume

accumulation (Figure 5), as shown by plots with low pine volume and low hardwood

basal area. To examine this relationship, we plotted all 379 plot volumes as a function of

%HWBA. At higher levels of %HWBA, hardwood competition had an overriding effect

on pine volume accumulation evidenced by reduced variation in pine volume as

%HWBA increased. Several reports support this model by showing that, as hardwood

competition increases, its influence on volume accumulation increases exponentially

(Glover and Zutter, 1993; Schabenberger and Zedaker, 1999).

y = 281.51e-0.0223x

R2 = 0.4946

050

100150200250300350400

0 15 30 45 60 75 90

Hardwood BA (%)

Pine

Vol

ume

(m3 ha

-1)

Figure 5. Scatter plot of pine volume growth as a function of percent

hardwood basal area in loblolly plantations located in the southern Piedmont region.

36

There was no evidence of a hardwood competition threshold relationship between

hardwood competition and volume; however, the data show a decrease in pine growth

between 15% and 30 % HWBA (Figure 5).

Figure 6. Scatter plots by treatment illustrating hardwood basal area effects on loblolly pine volume growth. When significant, regression lines are shown with the coefficient of determination (R2).

We further partitioned the influence of HWBA on pine volume by treatment (Figure

6). A linear relationship best described the relationship between pine volume and

%HWBA when separated by treatment. This relationship is supported by other work

(Miller et al., 2003b). As shown previously in Table 2, the Chop/Burn, Shear/V-blade,

and Shear/Rake had the highest %HWBA of the treated plots. %HWBA significantly

influenced pine growth on plots treated by Chop/Burn and Shear/V-blade (Figure 6), but

No Site Preparation

R2 = 0.4436

0

100200

300

400

0 10 20 30 40 50 60 70 80 90 100

Percent HWBA

Volu

me

(m3 h

a-1)

Chop/Burn

R2 = 0.0394

0

100200

300

400

0 10 20 30 40 50 60 70 80 90 100

Percent HWBA

Volu

me

(m3 h

a-1)

Shear/Disc

0

100200

300

400

0 10 20 30 40 50 60 70 80 90 100

Percent HWBA

Volu

me

(m3 h

a-1)

Shear/V-Blade

R2 = 0.4045

0

100200

300

400

0 10 20 30 40 50 60 70 80 90 100

Percent HWBA

Volu

me

(m3

ha-1

)

Shear/Rake

0100

200300

400

0 10 20 30 40 50 60 70 80 90 100

Percent HWBA

Volu

me

(m3 h

a-1)

Shear/Rake/Disc

0

100200

300

400

0 10 20 30 40 50 60 70 80 90 100

Percent HWBA

Volu

me

(m3

ha-1

)

37

the relationship was not evident on plots treated by Shear/Rake. Soil physical factors

were most likely limiting pine volume in plots with low % HWBA.

Soil Organic Matter Effects on Forest Productivity

Soil organic matter (SOM) in the surface 20 cm of mineral soil in the Chop/Burn,

Shear/Disc, Shear/Rake, and Shear/Rake/Disc treatments are presented and discussed

relative to treatment effects on forest productivity. The Control and Shear/V-Blade

treatments were not included because of the disproportionate influence of hardwood

competition on pine volume in these treatments.

SOM ranged from 35.1 Mg ha-1 to 40.0 Mg ha-1 for the Shear/Rake/Disc and

Chop/Burn, respectively, and followed the treatment-induced gradients of harvest residue

removal (Figure 7). Piatek and Allen (1999) also found that in a 15-year-old stand, site

preparation significantly affected soil C. Approximately 5.0 Mg ha-1 of SOM was

removed in the treatments that were raked. Morris et al. (1983) found that over 179 t ha-1

of soil, coarse wood and fine wood were displaced into the windrows, of which 154 t ha-1

was soil. Pine volume response generally followed the treatment-induced gradient of

harvest residue removal; those treatments that conserved harvest residue generally had

the highest volumes (Table 2). This pine response is hypothesized to be due to

removal/displacement of nutrients into the windrows causing nutrient deficiencies.

Grigal and Vance (2000) reviewed the influence of SOM additions. Organic

amendments generally increase SOM; however, interpreting forest productivity as a

function of SOM can be confounded by nutrient additions and other beneficial changes in

the soil resulting from these organic additions (Grigal and Vance 2000). In general, the

increase in SOM resulting from organic amendments is considered beneficial from a

38

nutritional and soil physical standpoint. An agricultural example reviewed by Hunt et al.

(1996) in which conventional tillage was compared with conservation tillage demonstrates

that SOM can increase on sandy sites when site organic residue is left on site.

0

5

10

15

20

25

30

35

40

45

Chop/Burn Shear/Disc Shear/Rake Shear/Rake/Disc

SOM

(Mg

ha-1)

Figure 7. Soil organic matter (SOM) of the upper 20 cm of the soil in

loblolly pine plantations in the southern Piedmont region by site preparation treatment. Different letters within columns show that values are significantly different (ά = 0.1).

Despite a significant difference of 5 Mg ha-1 among treatments, a regression

analysis of stand volume as a function of SOM showed that treatment-induced

differences in SOM content had no effect on stand volume (Figure 8). The benefits of

SOM in forest ecosystems are well documented; however, the explanatory power of

SOM in models predicting growth response has been weak (Grigal and Vance, 2000).

Typically, SOM influences other soil properties such as increased soil tilth, water holding

capacity, and nutrient availability, which in turn are better correlated with volume

response.

a ab ab b

39

050

100150200250300350400450

0 20,000 40,000 60,000 80,000

SOM (kg ha-1)

Stan

d Vo

lum

e (m

3 ha

-1) Chop and

Burn

Shear, Disc

Shear, Rake,Disc

Shear, Rake

Figure 8. Loblolly pine volume as a function of soil organic matter (SOM) of the

upper 20 cm of the soil for four site preparation treatments in the southern Piedmont region. Each point represents an average for each treatment across each block. No significant relationship was evident.

Soil Nitrogen

Total soil N in the upper 20 cm of the mineral soil layers ranged from 1045 kg ha-1

to 1135 kg ha-1 in the Chop/Burn and Shear/Rake treatments, respectively (Figure 9). As

with early rotation observations of total nitrogen (Lantagne, 1984), there was no

significant difference in total N between site preparation treatments (ά = 0.1). While

other workers have found a reduction in soil nitrogen content with harvest residue

removal and displacement through raking (Morris et al., 1983; Tew et al., 1986), there

was no evidence of decreased nitrogen content in the mineral soil surface in our study at

year 18. Documented decreases in nitrogen usually occurred in relatively young stands

where N-mineralization increased along with N removals due to displacement. In

another study in the Piedmont of North Carolina, Piatek and Allen (1999) reported

increased N-mineralization early in the rotation; however, after 15 years, there was no

site preparation effect on N mineralization or total N content. In our study, Lantagne

40

(1984) found increases in total N in years 1 and 2, indicating a trend in increasing total N.

This trend appeared to continue over time, with litter inputs, N mineralization, and

atmospheric deposition being the main sources of N. In conclusion, while there were

higher levels of SOM (Figure 7) with conservation of harvest residue, there was no

corresponding detectable increase in soil nitrogen. This relationship may have been

weakened by the variability in both SOM and total nitrogen (Figures 8 and 10).

When the relationship of total soil nitrogen and pine volume were partitioned based

on preharvest site quality, two different clusters of data were apparent (Figure 11). The

higher quality sites (SI50 = 85 to 90 ft) had higher volumes and higher soil nitrogen, while

the lower quality sites (SI50 = 65 to 70 ft) had lower volumes and lower soil nitrogen,

showing that soil nitrogen is clearly a site quality determinant. However, when a

regression analysis was performed on pine volume as a function of total soil nitrogen, no

significant relationship was evident due to large variation among the data. Therefore, it is

unlikely that small, treatment-induced changes in soil nitrogen would have a significant

effect on pine volume at rotation age.

0

200

400

600

800

1000

1200

1400

Chop/Burn Shear/Disc Shear/Rake Shear/Rake/Disc

Nitr

ogen

(kg

ha-1)

Figure 9. Total soil nitrogen content of the upper 20 cm of the soil in loblolly pine plantations in the southern Piedmont region. There were no significant differences among treatments (ά = 0.1).

41

0

50

100

150

200

250

300

350

400

450

0 500 1000 1500 2000

Total Nitrogen (kg ha-1)

Volu

me

(m3 h

a-1)

Chop/Burn

Shear/Disc

Shear/Rake/DiscShear/Rake

Figure 10. Pine volume as a function of total soil nitrogen of the upper 20 cm of the soil in loblolly pine plantations in the southern Piedmont region. Each point represents an average for each treatment across each block. No significant relationship was evident.

0

50

100

150

200

250

300

350

0 200 400 600 800 1000

Total Soil Nitrogen (ug g-1 in soil)

Volu

me

(m3

ha-1

) HighQuality

LowQuality

Figure 11. Pine volume as a function of total soil nitrogen concentration in loblolly pine plantations in the southern Piedmont region. Data were partitioned based on pre-harvest site quality and represent all treatments. When regression analysis was performed, no significant relationship existed.

42

Foliar Nitrogen

A comparison of foliar nitrogen levels in the Chop/Burn, Shear/Disc, Shear/Rake,

and Shear/Rake/Disc treatments are presented. The Control and Shear/V-Blade

treatments were not included because of the influence of hardwood competition. Foliar

nitrogen ranged from 1.07% to 1.04% on the Chop/Burn and Shear/Rake treatments

respectively (Figure 12). There were no significant differences among treatments. Piatek

and Allen (2000) also found no site preparation effects on foliar nitrogen 15 years after

site preparation on a Piedmont study site near Henderson, NC. By year 18 in our study,

no treatment effect on nitrogen status was evident. One commonality across all

treatments, including those not shown, was that the majority of the plots were deficient in

nitrogen. By age 18, foliar nitrogen was a function of the inherent fertility of these

Piedmont sites and unaffected by treatment.

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Chop/Burn Shear/Disc Shear/Rake Shear/Rake/Disc

Folia

r Nitr

ogen

(%)

Figure 12. Foliar nitrogen concentration in loblolly pine for four site preparation treatments in the southern Piedmont region. The horizontal line at 1.2% foliar nitrogen depicts a critical level according to Fowells and Krauss (1959). There were no significant differences among treatments (ά = 0.1).

Critical level (Fowells and Krauss, 1959)

43

Figure 13. Pine volume as a function of foliar nitrogen concentration in loblolly pine for

four site preparation treatments in the southern Piedmont region. The critical foliar concentration of 1.2% is depicted with a vertical line. For significant relationships, regression lines are shown with the coefficient of determination (R2).

Foliar nitrogen scattergrams were created for the site preparation treatments (Figure

13). The majority of the plots across the four treatments were nitrogen deficient (<1.2%

nitrogen). However, only the Shear/Disc and Shear/Rake/Disc treatments had a

significant relationship between pine volume and foliar nitrogen (Figure 10). Both of

these treatments had %HWBA below 15% (Table 1). As a result, other site factors, e.g.

site nitrogen, limited growth and produced a significant relationship between foliar

nitrogen and volume growth.

Residue retention and soil tillage did not affect foliar nitrogen at year 18 (Figure

12). In a study at Henderson, North Carolina Piatek and Allen (1999) also found that

increased harvest residue removal as a result of site preparation did not increase nitrogen

availability. This suggests that the N removed with harvest residue may not be

Chop/Burn

0

200

400

600

0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4

Foliar N (%)

Volu

me

(m3 h

a-1)

Shear/Disc

y = 228.42x - 10.365R2 = 0.131p = 0.0057

0100200300400

0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4

Foliar N (%)

Volu

me

(m3 h

a-1)

Shear/Rake/Disc

y = 281.68x - 82.562R2 = 0.2509p < 0.0001

0100200300400

0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4

Foliar N (%)

Volu

me

(m3 h

a-1)

Shear/Rake

0100200300400

0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4

Foliar N (%)

Volu

me

(m3 h

a-1)

44

significant over the long run, despite the findings of Fox et al., (1986), Burger and

Pritchett, (1984) and Morris et al., (1983) who show that N removal at stand

establishment can exceed 500 kg ha -1.

Bulk Density and Porosity

Bulk density values ranged from 0.64 g cm-1 to 1.94 g cm-1 in the A and B horizons

(Figure 14). There were no significant differences in soil bulk density at age 18.

Variation in stand volume was not related to bulk density. When separated, neither the A

horizon nor B horizon bulk density were of value in explaining the variation in pine

volume growth. As mentioned above, hardwood competition was responsible for a large

portion of the variation in pine growth and probably overshadowed any other site factor

influences that may have existed.

Macroporosity ranged from 9.8% to 48.2% in the A horizon and 7.9 % to 27.1% in

the B horizon in the A and B horizons (Figure 14). While many of the treatments

modified the soil physical environment at stand establishment (Lantagne, 1984), by year

18, there were no treatment effects on macroporosity. In addition, the range in

macroporosity was similar among all treatments regardless if they received tillage or not.

There was no relationship between macroporosity and pine volume (Figure 14).

45

Figure 14. Loblolly pine volume as a function of bulk density and macroporosity of the A

and B horizons for four site preparation treatments in the southern Piedmont region. Each point represents a sample from each treatment across each block. No significant relationships were evident.

Conclusions

Most forms of site preparation will increase survival and create a favorable

environment for stand establishment compared with no site preparation. Treatments that

included chopping or tillage provided the greatest benefit in the short and long term. The

Shear/V-Blade treatment included tillage; however, the volume growth was not at the

level of the Shear/Disc and Shear/Rake/Disc treatments. This response can be attributed

to the lack of tillage between the planting rows where slash was oriented into mini-

windrows. These areas had the highest concentrations of hardwood competition, which

hindered pine volume growth. Hardwood competition explained the most variation in

0

50100

150

200

250300

350

400

0.00 0.50 1.00 1.50 2.00

Bulk Density (g cm -3)

Volu

me

(m3 h

a-1) Chop/Burn

Shear/Disc

Shear/Rake

Shear/Rake/Disc 0

50

100

150

200

250

300

350

0 10 20 30 40 50

Macroporosity (%)Vo

lum

e (m

3 ha-1

) Chop/Burn

Shear/Disc

Shear/Rake

Shear/Rake/Disc

0

50100

150

200

250300

350

400

0.00 0.50 1.00 1.50 2.00

Bulk Density (g cm-3)

Volu

me

(m3 h

a-1) Chop/Burn

Shear/Disc

Shear/Rake

Shear/Rake/Disc 0

50100

150

200

250300

350

400

0 10 20 30 40 50

Macroporosity (%)

Volu

me

(m3 h

a-1) Chop/Burn

Shear/Disc

Shear/Rake

Shear/Rake/Disc

A Horizon A Horizon

B Horizon B Horizon

46

pine volume growth. The most intensive treatments did not reduce pine productivity as

hypothesized.

Relative pine volume response early in the rotation did not represent rotation-length

response. Early treatment response followed the gradient of site preparation intensity,

possibly due to a combination of both availability of nitrogen and a more favorable soil

physical environment. By canopy closure, volume response changed; those treatments

that conserved harvest residue, Chop/Burn and Shear/Disc, outperformed those site

preparation treatments that did not. Year 18 volume response also followed a gradient in

organic matter removal, except for the Shear/Rake/Disc treatment, which had the highest

level of hardwood competition control and subsequently higher volumes.

Hardwood competition on these sites explained a large portion of the variation in

age 18 pine growth. Over 54% of the variation in volume response was explained by

total hardwood basal area and the percentage of the total basal area in hardwoods.

Hardwood competition played an important role in these Piedmont pine plantations.

In addition to hardwood competition, it was hypothesized that the gradients of

harvest residue removal and tillage would affect the nitrogen status and soil physical

environment and therefore pine volume growth. At year 18, site preparation significantly

affected SOM; however, soil nitrogen, foliar nitrogen, bulk density, and macroporosity

were not affected. Other researchers have found similar accumulations of SOM without

increases in available nitrogen. All treatments were equally deficient in foliar nitrogen.

The soil physical environment at year 18 was not affected by treatments based on the soil

analyses performed.

47

While pine volume generally followed the qualitative gradient of harvest residue

removal and tillage, nitrogen status appeared to be unaffected by either tillage or site

organic matter conservation. A significant treatment effect on SOM did not result in

increased nitrogen availability. Pine productivity was lowest on those treatments that did

not control hardwood competition, indicating that the hardwood control, not tillage and

residue removal, was the dominant influence on pine productivity.

48

CHAPTER 5. CARBON ACCUMULATION AS A FUNCTION OF

LAND USE AND FOREST MANAGEMENT

Results and Discussion

Carbon Accumulation With Time

A chronosequence approach was used to estimate carbon accumulation after

abandoned agricultural sites were left to naturally regenerate into loblolly pine stands

(Figure 15). Agricultural sites, similar to those represented in our study, were

characterized in the early 1950’s in the Calhoun Experimental Forest (Richter et al.,

1999). The Calhoun old-field sites are in the same vicinity and had the same soil series

(fine, kaolinitic, thermic, Typic Kanhapludults) as most of the sites in our study. We

believe that these historical data from abandoned cotton fields, reported by Richter et al.

(1999) for the nearby Calhoun forest, serve as a good reference point for our sites before

the natural regeneration of loblolly pine occurred in these abandoned fields.

Data from Richter et al. (1999) show that over a century of agricultural land use

reduced soil C to about 12 Mg ha-1. This observation was supported by Huntington’s

(1995) work on Piedmont sites near Atlanta, Georgia. He found that the upper 20 cm of

the soil in a nearby “undisturbed” forest contained 70.1 Mg C ha-1, whereas the cultivated

site contained 30 Mg C ha-1. These reports further support Johnson’s (1992) review of

management effects on SOM, which showed that the vast majority of research

investigating the impact of soil cultivation shows significant deceases in soil C.

49

Figure 15. Carbon accumulation in forest litter and upper 20 cm of soil as affected by land use and time in loblolly pine stands in the southern Piedmont region. Agricultural field carbon value is for the Calhoun Experimental Forest reported by Richter et al., 1999. Old-field loblolly pine stand (age 30-50) represents the average of 12 natural old-field-succession pine stands. Old-field loblolly pine stand (age 48-68) represents parts of the same stands 18 years later. Eighteen-year-old loblolly pine plantation represents parts of the same sites harvested and converted to loblolly pine plantations. There were significant decreases in soil carbon, litter carbon, and the sum of two following harvest, site preparation and 18-years of forest development (fourth bar compared with second bar).

Our data showed that carbon can increase fourfold under forest vegetation

following prolonged agriculture use (Figure 15, second data bar). Compared to the soil C

content of the old fields reported by Richter (1999), soil carbon in the upper 20 cm of the

soil of the first-rotation old-field succession forests measured in 1981 increased 15 Mg

ha-1 over a 30-50 year span. Forest litter contained another 15 Mg ha –1 of carbon over

that same time period (second bar of Figure 15). This resulted in an almost fourfold

increase in carbon stored in the upper 20 cm of mineral soil and in the forest floor

combined.

05

1015202530354045

AgriculturalField **

Old FieldLoblolly PineStand (age

30-50)

Old FieldLoblolly PineStand (age

48-68)

18 Year OldLoblolly Pine

Plantation

Carb

on (M

g/ha

) Forest FloorCarbon

Soil Carbon(upper 20cm)

**Richter et al., 1999

*

*

*

50

Other studies in various regions have shown similar accumulation rates in soil

carbon under forest vegetation; however, the magnitude of the carbon captured varied by

site type, region, and vegetation. Huntington (1995) found accumulations between 23.8

Mg ha-1 and 55.3 Mg ha-1 in the surface 1.0 m of an aggrading forest at the Panola

Mountain Research Watershed near Atlanta, Georgia. In Wisconsin, Wilde (1964) found

an almost 400% increase in soil carbon in 30- to 50-year-old red pine (Pinus resinosa)

plantations after many decades of agricultural land use. Van Lear et al. (1995) found an

increase of 26 Mg ha-1of soil carbon in the upper 1 m of the soil. Billings (1938) found

an increase in surface soil C of 25-100 Mg ha-1 in an aggrading old-field shortleaf pine

stand (Pinus echinata) in North Carolina over a 50-year period. None of these studies

included pre-cultivation soil C, so it is not possible to compare how these rebuilt carbon

stocks compared to the original pre-cultivation levels.

It is difficult to determine if a complete recovery in soil C is possible on these

Piedmont study sites due to widespread erosion that occurred during the century or more

that they were exposed to abusive agriculture (Trimble, 1974). With each passing year in

agricultural use, erosion caused a substantial loss in surface soil, which contained the

highest concentrations of SOM in the soil profile. In the upper 20 cm of an undisturbed

forest site that showed no signs of cultivation, Huntington (1995) found almost 50% more

SOM compared to that in an aggrading old-field forest. He suggested that the aggrading

forest had a greater potential to capture carbon, but did not suggest that these levels

would return to pre-disturbance levels.

In our study, we were able to use the pre-harvest characterization data along with

uncut reference stands 18 years later to determine if carbon continued to accumulate in

51

the forest floor and surface soil of these old-field Piedmont forests. The uncut reference

stands were re-measured in 1999 using the same methods as those used in 1981. Over

the 18-year span between pre-harvest characterization and this final measurement cycle,

there was no additional carbon sequestered in the upper 20 cm of soil or the forest floor

on these old-field forest sites (compare second and third bars of Figure 15).

In the study areas that were harvested and site-prepared, forest floor carbon was

reduced 5.0 Mg ha-1 and soil carbon in the upper 20 cm was reduced by 1.6 Mg ha-1

compared to pre-harvest levels (compare second and fourth bars of Figure 15). This

amounts to an overall reduction of 6.6 Mg ha-1 due to the conversion of natural old-field

stands to plantations. This reduction in carbon is presumably due to harvest and site

preparation biomass removals and greater decomposition levels of soil organic matter in

plantation systems. In a study of forest conversion on the Atlantic Coastal Plain in

Florida, Burger and Pritchett (1984) showed that site preparation removes and displaces

the forest floor and soil organic matter. They found that soil temperature and moisture

increased for a period of years following harvest and site preparation, which increased the

rate of decomposition of the remaining residue and soil organic matter.

Site Preparation Treatment Effects on Carbon Storage

Compared to the pre-harvest baseline, treatments that included harvest residue

removal followed by tillage removed or displaced the largest quantity of carbon. The

Shear/Rake/Disc treatment removed the most, followed by the Shear/V-Blade and the

Shear/Rake treatments (Figure 16). The three-pass Shear/Rake/Disc treatment, the most

intensive site preparation treatment, caused the largest decrease in soil carbon in the

52

upper 20 cm. Those treatments that removed or displaced harvest residue followed by

tillage had the largest potential to remove carbon from the soil

-25

-20

-15

-10

-5

0

5

chan

ge in

car

bon

(%)

Figure 16. Relative change in soil carbon (upper 20 cm) in 18-year-old loblolly pine plantations compared to pre-harvest carbon levels in the southern Piedmont region as a function of site preparation treatment. There was a significant decrease in soil carbon in the Shear/Rake/Disc treatment (ά = 0.1).

Soil carbon in the upper 20 cm ranged from 24.0 Mg ha-1 in the Control treatment to

20.6 Mg ha-1 in the Shear/Rake/Disc treatment (Figure 17). The Control, Shear/V-Blade,

and Chop/Burn treatments had significantly more carbon in the upper 20 cm than the

Shear/Rake/Disc treatment. Treatments that conserved harvest residue had the highest

soil C content (Figure 17). Research on agricultural soils shows that conservation tillage

treatments can increase soil C in sandy soils (Hunt et al., 1996). In our study, treatments

that conserved harvest residue are analogous to conservation tillage treatments in

agriculture. Conservation of residue may account for the higher amounts of soil C in the

upper 20 cm of the mineral soil of the non-raked treatments.

*

Pre-harvest carbon level

Control Shear/V-Blade-Disc Chop/Burn Shear/Disc Shear/Rake Shear/Rake/Disc

53

0

5

10

15

20

25

30

Control

Shear/

V-Blad

e

Chop/Burn

Shear/

Disc

Shear/

Rake

Shear/

Rake/D

isc

Soi

l Car

bon

(Mg

ha-1

)

Figure 17. Site preparation treatment effect on soil carbon content in the upper 20 cm of soil in loblolly plantations of the southern Piedmont region. Different letters within columns show that values are significantly different (ά level = 0.1).

Litter layer carbon was affected by site preparation (Figure 18). Values ranged

from 10.5 Mg ha-1 to 12.2 Mg ha-1 on the Control and Shear/Disc treatments respectively.

The Shear/Disk treatment had more litter layer carbon than the Shear/V-Blade,

Shear/Rake/Disc, Shear/Rake, and the Control. Richter et al. (1995) found 32.8 Mg ha-1

of litter layer carbon in a 35-year-old loblolly pine stand in the Piedmont of South

Carolina. This amount of carbon was similar to the amount in our stands prior to harvest.

The pine stand studied by Richter et al. (1995) was nearly twice the age but contained

three times more carbon in the litter layer. This suggests that our treated stands, if left

unharvested, would rapidly accrue additional litter over the next 15 years. The overall

treatment effect on carbon accumulation in the litter generally follows the treatment

effect on overall above ground productivity; that is, the greater the tree biomass, the more

carbon sequestered in the litter layer.

a a a ab ab b

54

0

20

40

60

80

100

120

Shear/

Disc

Chop/B

urn

Shear/

V-Blad

e

Shear/

Rake

Shear/

Rake/D

isc

Contro

l

Car

bon

(Mg

ha-1

) Crop TreeCarbon

HardwoodCarbon

LitterCarbon

SoilCarbon

Figure 18. Carbon inventory of loblolly pine plantations in the southern Piedmont region as

a function of site preparation. Inventory includes the upper 20 cm soil carbon, litter layer carbon, above- and below-ground hardwood carbon, and above- and below-ground pine carbon. Different letters within each carbon component show that values are significantly different among treatments (ά level = 0.1). The letters above the bars refer to total inventoried carbon.

Although it has been reported that the short-term net flux of carbon can be negative

due to harvest and site preparation (Johnson, 1992), our study, along with other long-term

studies (Huntington and Ryan, 1990; Huntington, 1995; Richter et al., 1999), show that

old-field forest sites of the southeast are carbon sinks. This is especially true given

increased sequestration of carbon in tree biomass, and less intensive mechanical site

preparation techniques that are now prevalent on non-industrial private and industry

lands.

Above- and below-ground tree biomass carbon accounted for a significant portion

of the carbon stored on these Piedmont loblolly pine plantation sites (Figure 18).

a a ab b a

a ab b b b b b b b b b

a

a ab ab b ab c

a ab ab bc bc c

ab

55

Treatments that conserved harvest residue increased above- and below-ground tree

biomass carbon in addition to carbon in the upper 20 cm. Increased crop and non-crop

biomass can create a net increase in carbon stored on a site even if there is a near-term

decrease in surface soil carbon (Laiho et al., 2003). This increase in biomass carbon

could translate into increases in both litter layer carbon and soil carbon through litter

inputs and root turnover.

Conclusions

Land use and management practices affect the amount of carbon stored in the plant

and soil system. We estimated carbon accumulation in the upper 20 cm of the soil and

forest litter. We found that carbon accumulation in the soil and forest floor increased

fourfold during old field succession compared to sites that remained in agricultural use on

the nearby Calhoun Experimental Forest located in Union County, South Carolina. In

these old-field loblolly pine stands, carbon accumulation reached quasi-equilibrium after

40 years, as shown by the uncut reference stands and the pre-harvest site characterization.

Mechanical site preparation treatments significantly affected carbon accumulation

in the upper 20 cm of the soil. Those treatments that manipulated harvest residue

combined with tillage (Shear/V-Blade and Shear/Rake/Disc) resulted in lower soil carbon

content than those treatments that conserved harvest residue (Chop/Burn and Shear/Disc).

Site preparation treatments that did not remove harvest residue increased SOM content in

the upper horizons due to incorporation of that residue into the mineral soil. Forest

managers have the opportunity to manipulate and manage not only the crop trees in

plantation systems, but also the amount of carbon stored on a site. Above- and below-

ground tree carbon accounts for a large portion of the carbon stored on a forest site. Site

56

preparation treatments that increase productivity and promote volume growth will also

promote additional carbon accumulation through biomass carbon. Forest carbon can be

managed through an understanding of how a manager’s silvicultural decisions affect

productivity and harvest residue manipulation.

57

CHAPTER 6. SUMMARY AND CONCLUSIONS

Mechanical site preparation in the Piedmont is critical for successful management

of loblolly pine plantations. In this study, early volume response did not represent stand

volume at age 18. Tillage and chopping treatments provided lasting benefits in volume

accumulation across the rotation. The Shear/Disc and Chop/Burn treatments had larger

stand volume than the untilled Shear/Rake treatment. Hardwood competition control was

the primary factor controlling this response. The gradient of tillage was closely linked to

hardwood competition control. Those treatments that included total area tillage provided

the best control of hardwoods. The Shear/Disc and Shear/Rake/Disc treatments had

percent hardwood basal area below 15% and had a significant positive relationship

between foliar N and stand volume. This indicated that nitrogen was a growth-limiting

factor when hardwoods were controlled.

There was a significant treatment effect on soil organic matter (SOM)

accumulation. The Chop/Burn treatment, which conserved harvest residue and had

minimal tillage, had significantly higher SOM than the Shear/Rake/Disc. Increased SOM

accumulation did not result in higher site nitrogen. All sites were deficient in foliar

nitrogen irrespective of treatment, indicating that conservation of harvest residue did not

increase nitrogen availability in these stands at age 18. When scatter plots of total

nitrogen and stand volume were partitioned based on pre-harvest site index, there were

two distinct clusters of data for the high and low quality sites. The higher-quality sites

had higher total nitrogen in the upper 20 cm of the soil and larger stand volumes.

Carbon increased fourfold under forest vegetation following agricultural use. There

was a significant site treatment effect on soil C in the upper 20 cm. Those treatments that

58

conserved harvest residue had the highest accumulations of soil C. Forest managers have

the opportunity to capture carbon by conserving harvest residue as well as increasing

growth rates of the crop trees.

In conclusion, results of this research support the use of site preparation treatments

such as the Chop/Burn and the one-pass Shear/Disc treatments to establish loblolly pine

stands in the Piedmont. These treatments were beneficial in a number of ways: (1)

hardwood competition was adequately controlled; (2) volume growth was best for both of

these treatments; (3) these treatments were the least expensive to implement; and (4)

these treatments conserved the greatest amount of harvest residue, which increased soil

carbon storage in the upper 20 cm of soil and the forest litter layer. Across the gradient

of harvest residue removal, the availability of site nitrogen was the same as measured by

foliar nitrogen. However, conservation of harvest debris resulted in increased SOM,

which could enhance the long-term sustainability of these systems by maintaining or

increasing macropore space, nutrient release, and water holding capacity.

59

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APPENDICES

68

APPENDIX A. SOIL PHYSICAL PROPERTIES

BLK TRT PTL Sample B.D.

g cm-3

Total Porosity

(%)

Cap Porosity

(%)

Noncap Porosity

(%) 1 CH 1 A1 1.52 49.5 28.0 21.5 1 CH 1 A2 1.58 47.5 24.0 23.5 1 CH 1 B 1.52 49.8 32.6 17.1 1 CO 1 A1 1.27 57.9 17.9 40.0 1 CO 1 B 1.71 43.2 30.2 13.0 1 KD 1 B 1.73 42.5 27.4 15.1 1 KK 1 A1 1.46 51.7 20.0 31.7 1 KK 1 A2 1.49 50.6 21.7 28.9 1 KK 1 B 1.67 44.6 30.6 14.0 1 KR 1 B 1.87 38.0 21.0 16.9 1 VB 1 A1 1.54 48.9 22.4 26.5 1 VB 1 B 1.56 48.2 34.1 14.1 2 CH 1 A1 1.13 62.7 20.4 42.3 2 CO 1 A1 1.51 49.9 31.6 18.3 2 CO 1 A2 1.70 43.6 20.2 23.4 2 KD 1 A1 1.43 52.6 24.5 28.2 2 KD 1 A2 1.55 48.6 20.1 28.5 2 KD 1 B 1.73 42.5 28.3 14.2 2 KK 1 A1 1.48 51.0 29.0 22.0 2 KK 1 A2 1.68 44.4 22.9 21.5 2 KK 1 B 1.68 44.3 29.6 14.7 2 KR 1 A1 1.62 46.2 17.6 28.6 2 KR 1 A2 1.50 50.4 22.2 28.2 2 KR 1 B 1.35 55.2 42.8 12.4 2 VB 1 A1 1.44 52.2 23.5 28.7 2 VB 1 A2 1.65 45.2 19.3 25.9 2 VB 1 B 1.74 42.3 23.4 18.9 3 CH 1 A1 1.39 54.1 23.9 30.2 3 CH 1 A2 1.42 52.8 35.5 17.3 3 CO 1 A1 1.67 44.5 20.3 24.2 3 KD 1 A1 1.49 50.6 19.4 31.2 3 KD 1 A2 1.56 48.2 20.8 27.3 3 KK 1 A2 1.50 50.2 25.5 24.7 3 KR 1 A1 1.61 46.6 19.4 27.2 3 VB 1 A1 1.29 57.3 16.3 40.9 3 VB 1 A2 1.41 53.2 16.3 36.9 5 CH 1 A1 1.38 54.4 21.0 33.4 5 CH 1 A2 1.38 54.3 23.2 31.1 5 CH 1 B 1.67 44.7 27.7 17.0 5 CO 1 A1 1.44 52.2 27.3 24.9 5 CO 1 A2 1.12 62.8 26.6 36.2 5 CO 1 B 1.46 51.6 39.3 12.3 5 KD 1 A1 1.26 58.2 28.5 29.7 5 KD 1 A2 1.32 56.3 28.8 27.5 5 KD 1 B 1.50 50.4 36.4 14.0 5 KK 1 A1 1.50 50.4 28.7 21.7 5 KK 1 A2 1.62 46.3 27.0 19.3 5 KK 1 B 1.67 44.6 28.2 16.4 5 KR 1 A1 1.58 47.5 25.8 21.7 5 KR 1 A2 1.33 55.8 26.1 29.7 5 KR 1 B 1.63 46.1 31.6 14.5

69

BLK TRT PTL Sample B.D.

g cm-3

Total Porosity

(%)

Cap Porosity

(%)

Noncap Porosity

(%) 5 VB 1 A 1.30 57.0 24.1 32.9 5 VB 1 A2 1.10 63.5 29.1 34.4 5 VB 1 B 1.52 49.5 37.3 12.2 6 CH 1 A1 1.55 48.7 31.4 17.3 6 CH 1 A2 1.41 53.3 30.5 22.8 6 CH 1 B 1.86 38.3 18.6 19.7 6 CO 1 A1 1.33 55.8 27.6 28.2 6 CO 1 A2 1.27 58.0 26.6 31.3 6 CO 1 B 1.26 58.2 43.7 14.5 6 KK 1 A1 1.34 55.5 21.8 33.7 6 KK 1 A2 1.32 56.4 13.8 42.6 6 KK 1 B 1.64 45.7 28.8 17.0 6 KR 1 A1 1.28 57.4 39.4 18.0 6 KR 1 A2 1.60 47.0 28.5 18.5 6 KR 1 B 1.73 42.7 28.3 14.4 6 VB 1 A1 1.44 52.1 32.8 19.3 6 VB 1 A2 1.34 55.6 27.2 28.4 6 VB 1 B 1.49 50.8 34.1 16.7 8 CH 1 A1 1.58 47.5 24.2 23.3 8 CH 1 A2 1.43 52.7 19.5 33.2 8 CH 1 B 1.48 50.8 34.3 16.6 8 CO 1 A1 1.16 61.6 13.4 48.2 8 CO 1 A2 1.39 53.9 12.6 41.3 8 CO 1 B 1.45 51.9 24.8 27.1 8 KD 1 A1 1.43 52.5 17.1 35.4 8 KD 1 A2 1.45 51.9 16.7 35.2 8 KD 1 B 1.78 41.0 21.6 19.4 8 KK 1 A1 1.40 53.5 28.2 25.2 8 KK 1 A2 1.51 50.0 23.4 26.7 8 KK 1 B 1.48 50.8 32.8 18.0 8 KR 1 A1 1.08 64.3 21.5 42.8 8 KR 1 A2 1.47 51.3 18.9 32.3 8 KR 1 B 1.70 43.6 17.1 26.5 8 VB 1 A1 1.34 55.5 11.9 43.6 8 VB 1 A2 1.66 44.9 20.0 24.9 8 VB 1 B 1.53 49.3 28.6 20.7 9 CH 1 A1 1.34 55.4 37.4 18.1 9 CH 1 A2 1.51 50.1 37.8 12.2 9 CH 1 B 1.64 45.5 38.2 7.4 9 CO 1 A 1.32 56.3 39.7 16.6 9 CO 1 A1 1.41 53.2 38.8 14.4 9 CO 1 B 1.44 52.4 40.7 11.8 9 KD 1 A1 1.54 48.8 37.0 11.8 9 KD 1 A2 1.37 54.7 39.1 15.7 9 KD 1 B 1.55 48.5 39.6 8.9 9 KK 1 A1 1.34 55.5 36.6 18.9 9 KK 1 A2 1.51 49.9 39.3 10.6 9 KK 1 B 1.46 51.5 40.2 11.2 9 KR 1 A1 1.45 51.8 37.3 14.5 9 KR 1 A2 1.54 49.0 37.8 11.2 9 KR 1 B 1.51 49.9 37.1 12.8 9 VB 1 A1 1.42 53.1 37.8 15.3 9 VB 1 A2 1.44 52.2 37.0 15.2

70

BLK TRT PTL Sample B.D.

g cm-3

Total Porosity

(%)

Cap Porosity

(%)

Noncap Porosity

(%) 9 VB 1 B 1.53 49.3 42.1 7.2

10 CH 1 A1 1.52 49.6 27.8 21.8 10 CH 1 A2 1.56 48.4 25.1 23.3 10 CH 1 B 1.75 42.1 28.3 13.7 10 CO 1 A1 1.47 51.3 30.1 21.2 10 CO 1 A2 1.34 55.6 33.9 21.6 10 CO 1 B 1.26 58.3 46.5 11.8 10 KD 1 A1 1.59 51.3 39.5 11.8 10 KD 1 A2 1.52 47.2 26.5 20.8 10 KD 1 B 1.44 49.5 29.8 19.7 10 KK 1 A1 0.64 52.2 42.4 9.8 10 KK 1 A2 1.47 78.6 57.0 21.6 10 KK 1 B 1.35 55.3 45.5 9.7 10 KR 1 A1 1.43 52.6 29.2 23.4 10 KR 1 A2 1.49 50.6 32.2 18.4 10 KR 1 B 1.50 50.4 39.5 10.8 10 VB 1 A1 1.38 54.1 39.6 14.6 10 VB 1 A2 1.32 56.1 35.8 20.3 10 VB 1 B 1.44 52.2 42.9 9.3 11 CH 1 A1 1.55 48.5 24.0 24.5 11 CH 1 A2 1.60 47.1 16.9 30.1 11 CH 1 B2 1.35 55.2 36.7 18.5 11 CO 1 A1 1.58 47.5 27.5 20.1 11 CO 1 A2 1.46 51.5 26.1 25.4 11 CO 1 B 1.93 35.9 22.1 13.8 11 KD 1 A1 1.37 54.7 34.2 20.5 11 KD 1 A2 0.84 72.1 45.2 26.9 11 KD 1 B 1.64 45.6 32.3 13.2 11 KK 1 A1 1.42 52.9 21.7 31.1 11 KK 1 A2 1.43 52.5 20.9 31.6 11 KK 1 B 1.70 43.6 29.8 13.8 11 KR 1 A1 1.55 48.4 27.5 20.9 11 KR 1 A2 1.37 54.5 25.9 28.6 11 KR 1 B 1.81 39.8 19.6 20.2 11 VB 1 A1 1.59 47.2 20.7 26.6 11 VB 1 A2 1.68 44.2 19.4 24.7 11 VB 1 B 1.77 41.4 24.0 17.4 12 CH 1 A2 1.54 48.9 22.6 26.3 12 CH 1 B 1.27 57.9 44.3 13.5 12 CH 1 B 1.59 47.3 33.9 13.4 12 CO 1 A1 1.33 55.8 33.3 22.5 12 CO 1 A1 1.31 56.4 22.6 33.8 12 CO 1 A2 1.39 53.8 30.2 23.6 12 CO 1 B 1.51 50.0 35.5 14.5 12 KD 1 A1 1.49 50.6 28.4 22.2 12 KD 1 A2 1.37 54.7 38.8 15.9 12 KK 1 A1 1.50 50.3 19.4 30.8 12 KK 1 A2 1.60 46.9 16.4 30.5 12 KR 1 A1 1.39 54.0 32.3 21.6 12 KR 1 A2 0.97 68.0 28.9 39.1 12 VB 1 B 1.71 43.4 26.5 16.9

71

APPENDIX B. PINE VOLUME, HARDWOOD BASAL AREA, AND CARBON INVENTORY

BLK TRT PLT

Stand Volume (m3ha-1)

HWBA (m2ha-1) OM%

Soil C upper 20 cm

(%)

Soil C upper 20 cm

(kg ha-1)

Litter Wt.

(kg ha-1)

Litter C

(%)

Litter C

(kg ha-1) 1 CH 1 179.7 3.1 1.31 0.77 19,732 19,698 48.9 9,624 1 CH 2 260.3 3.5 1.74 1.02 26,225 30,660 59.6 18,288 1 CH 3 124.4 2.3 1.59 0.93 23,872 26,282 58.5 15,378 1 CH 4 235.1 5.0 1.27 0.75 19,078 33,140 46.5 15,423 1 CH 5 224.6 8.4 1.21 0.71 18,239 26,049 47.1 12,275 1 CH 6 194.6 0.3 2.17 1.28 32,648 17,755 49.1 8,710 1 CO 1 92.5 . 1.77 1.04 27,703 23,396 59.5 13,914 1 CO 2 85.2 20.1 1.62 0.96 23,307 30,156 64.8 19,547 1 CO 3 98.6 19.7 2.22 1.30 28,929 17,791 43.8 7,794 1 CO 4 84.9 1.4 1.48 0.87 21,893 13,359 65.8 8,785 1 CO 5 132.5 11.4 1.64 0.96 23,131 27,903 45.7 12,741 1 CO 6 73.9 . 1.61 0.95 22,799 17,473 55.1 9,628 1 KD 1 273.9 6.8 1.43 0.84 27,327 18,116 52.6 9,534 1 KD 2 242.6 4.9 1.27 0.74 21,743 27,507 46.5 12,785 1 KD 3 253.1 4.1 1.39 0.82 20,165 22,438 47.2 10,588 1 KD 4 184.2 6.4 1.39 0.82 19,808 25,797 47.7 12,296 1 KD 5 226.4 . 1.47 0.87 23,733 11,224 37.6 4,215 1 KK 1 313.6 4.4 1.59 0.93 25,784 16,811 53.5 8,996 1 KK 2 321.0 4.0 1.50 0.88 20,998 18,333 46.5 8,527 1 KK 3 256.6 4.1 1.31 0.77 17,994 18,995 48.0 9,125 1 KK 4 293.9 8.9 1.56 0.92 22,608 23,444 53.1 12,451 1 KK 5 247.6 3.3 0.86 0.51 14,682 11,751 50.7 5,960 1 KR 1 237.9 2.0 1.39 0.82 18,823 18,590 54.9 10,209 1 KR 2 217.8 10.3 0.88 0.52 14,476 15,186 63.6 9,656 1 KR 3 274.1 7.2 1.01 0.59 15,049 24,896 45.0 11,199 1 KR 4 261.3 7.5 1.14 0.67 17,636 21,182 53.5 11,332 1 KR 5 310.4 4.9 1.99 1.17 29,466 27,165 43.9 11,931 1 VB 1 299.0 5.3 1.21 0.71 19,764 12,158 51.9 6,312 1 VB 2 309.1 5.8 0.83 0.49 12,551 31,808 39.8 12,658 1 VB 3 332.1 6.6 1.39 0.82 22,355 38,195 53.4 20,392 1 VB 4 315.8 8.8 1.50 0.88 19,100 31,185 53.0 16,514 1 VB 5 254.7 7.4 2.07 1.22 25,849 22,221 45.2 10,043 2 CH 1 243.5 9.4 2.07 1.22 33,536 25,003 57.1 14,270 2 CH 2 191.7 12.4 1.28 0.75 20,756 16,598 57.3 9,513 2 CH 3 84.0 9.4 1.44 0.84 23,307 13,814 51.0 7,043 2 CH 4 112.1 10.1 1.12 0.66 18,257 14,954 33.6 5,020 2 CH 5 226.8 9.9 1.30 0.76 21,044 17,332 53.0 9,179 2 CH 6 150.5 7.3 1.60 0.94 25,951 16,368 32.6 5,343 2 CO 1 110.1 9.5 1.52 0.89 25,722 20,743 54.8 11,362 2 CO 2 110.5 11.0 1.79 1.06 31,030 18,694 49.9 9,323 2 CO 3 111.7 7.1 1.64 0.96 28,856 24,055 45.3 10,888 2 CO 4 112.9 10.5 1.46 0.86 25,483 15,424 57.2 8,826 2 CO 5 111.1 . 1.69 1.00 27,110 20,778 54.7 11,359 2 CO 6 198.0 12.2 1.48 0.87 24,449 17,715 52.8 9,360 2 KD 1 167.9 7.6 1.38 0.81 21,466 14,651 55.2 8,090 2 KD 2 179.7 0.4 1.93 1.14 20,678 16,694 50.4 8,411 2 KD 3 121.2 5.2 0.95 0.56 15,910 20,482 53.0 10,846 2 KD 4 181.0 9.2 1.01 0.59 14,013 18,853 50.9 9,594 2 KD 5 192.5 4.9 0.83 0.49 14,502 22,728 51.1 11,621

72

BLK TRT PLT

Stand Volume (m3ha-1)

HWBA (m2ha-1) OM%

Soil C upper 20 cm

(%)

Soil C upper 20 cm

(kg ha-1)

Litter Wt.

(kg ha-1)

Litter C

(%)

Litter C

(kg ha-1) 2 KK 1 126.4 5.2 1.27 0.75 20,143 16,454 50.1 8,238 2 KK 2 205.4 3.8 1.09 0.64 14,931 14,487 51.9 7,522 2 KK 3 264.3 8.2 2.57 1.51 30,514 36,634 53.1 19,436 2 KK 4 236.1 3.8 1.35 0.80 18,625 11,888 50.2 5,964 2 KK 5 210.9 4.4 0.80 0.47 12,769 15,676 50.5 7,914 2 KR 1 163.4 5.1 1.13 . . . . . 2 KR 2 190.1 6.1 1.31 0.77 22,817 28,417 49.0 13,934 2 KR 3 208.1 11.0 0.84 0.50 13,490 16,052 63.5 10,193 2 KR 4 235.4 6.9 1.67 0.98 25,143 15,918 66.4 10,577 2 KR 5 145.6 10.8 0.75 0.44 12,816 14,519 46.8 6,788 2 VB 1 194.5 8.0 1.18 0.70 19,082 9,951 56.5 5,624 2 VB 2 98.4 8.0 1.54 0.91 24,438 19,551 54.6 10,671 2 VB 3 233.3 7.2 1.51 0.89 29,006 14,995 46.3 6,940 2 VB 4 233.8 6.4 1.29 0.76 20,714 24,834 48.0 11,923 2 VB 5 145.6 10.3 1.10 0.64 16,769 14,123 57.4 8,113 3 CH 1 173.1 4.8 1.89 1.11 31,372 15,693 54.9 8,613 3 CH 2 238.0 0.6 1.34 0.79 22,301 29,493 51.8 15,266 3 CH 3 248.2 0.5 1.22 0.72 20,209 21,061 50.3 10,595 3 CH 4 166.5 3.3 1.47 0.87 24,406 17,045 48.8 8,316 3 CH 5 226.2 1.0 1.19 0.70 19,778 27,849 54.6 15,205 3 CH 6 228.5 2.9 1.29 0.76 21,455 20,293 48.8 9,908 3 CO 1 116.4 . 1.15 0.68 16,123 17,989 55.7 10,020 3 CO 2 148.2 16.5 1.50 0.88 21,320 19,280 53.6 10,328 3 CO 3 187.3 9.8 1.30 0.77 21,730 16,746 58.8 9,851 3 CO 4 105.3 26.6 1.96 1.15 30,456 34,732 48.6 16,865 3 CO 5 111.3 4.1 1.93 1.13 32,616 27,344 45.9 12,538 3 CO 6 110.2 8.8 1.15 0.68 17,835 27,850 41.9 11,672 3 KD 1 337.8 0.2 1.78 1.04 30,701 22,512 58.4 13,145 3 KD 2 260.3 0.2 2.02 1.19 34,945 37,624 54.7 20,584 3 KD 3 262.7 1.3 2.08 1.23 32,124 27,782 54.1 15,041 3 KD 4 369.7 0.6 1.15 0.67 15,793 35,578 45.6 16,225 3 KD 5 261.4 0.6 1.31 0.77 13,709 35,759 46.4 16,592 3 KK 1 146.3 4.5 1.46 0.86 22,355 17,001 50.8 8,643 3 KK 2 120.9 3.3 1.40 0.82 22,524 19,908 50.7 10,093 3 KK 3 90.8 5.7 1.49 0.88 23,910 29,435 52.0 15,316 3 KK 4 184.1 5.6 0.65 0.38 9,742 29,574 55.0 16,277 3 KK 5 172.1 2.2 1.49 0.87 19,571 12,177 64.4 7,837 3 KR 1 155.2 5.3 0.75 0.44 9,936 19,727 53.7 10,595 3 KR 2 142.3 3.6 1.20 0.71 21,476 20,896 43.9 9,165 3 KR 3 162.9 1.3 1.10 0.65 17,633 21,331 45.2 9,636 3 KR 4 182.0 5.4 1.38 0.81 25,538 32,886 46.6 15,332 3 KR 5 186.6 1.7 1.21 0.71 20,797 12,426 42.3 5,257 3 VB 1 166.4 3.3 1.20 0.71 21,766 27,807 58.7 16,335 3 VB 2 146.5 6.2 1.81 1.07 30,918 20,125 54.1 10,885 3 VB 3 263.3 3.2 1.69 0.99 24,655 14,482 46.3 6,704 3 VB 4 175.8 9.1 1.83 1.08 18,964 22,827 52.3 11,928 3 VB 5 213.4 0.7 1.09 0.64 19,146 27,886 53.0 14,793 4 CH 1 264.3 5.6 0.65 0.38 9,401 30,928 57.9 17,919 4 CH 2 361.1 1.7 1.31 0.77 18,946 17,237 47.4 8,166 4 CH 3 192.7 3.3 1.17 0.69 16,903 19,442 62.5 12,155 4 CH 4 238.6 8.2 1.39 0.82 20,096 27,783 60.5 16,798 4 CH 5 302.2 10.0 1.06 0.62 15,349 29,338 52.6 15,417 4 CO 1 6.4 46.6 1.46 0.86 26,620 29,979 64.1 19,213

73

BLK TRT PLT

Stand Volume (m3ha-1)

HWBA (m2ha-1) OM%

Soil C upper 20 cm

(%)

Soil C upper 20 cm

(kg ha-1)

Litter Wt.

(kg ha-1)

Litter C

(%)

Litter C

(kg ha-1) 4 CO 2 53.7 16.7 1.21 0.71 19,179 19,002 52.9 10,060 4 CO 3 70.6 18.5 1.85 1.09 26,067 16,012 67.4 10,791 4 CO 4 65.8 14.8 1.46 0.86 19,808 23,923 62.0 14,822 4 CO 5 70.1 1.7 1.90 1.12 29,659 16,976 58.5 9,929 4 CO 6 18.1 14.1 1.62 0.96 23,318 20,203 58.0 11,722 4 KD 1 290.2 1.3 1.38 0.81 21,895 26,340 59.3 15,618 4 KD 2 279.5 9.7 1.38 0.81 19,936 24,868 48.3 12,006 4 KD 3 245.0 5.5 1.34 0.79 19,812 22,316 56.0 12,491 4 KD 4 306.9 5.8 0.81 0.48 12,525 27,001 45.3 12,223 4 KD 5 358.2 4.3 0.93 0.55 10,833 32,993 68.4 22,556 4 KK 1 259.3 4.7 1.47 0.87 16,269 15,601 58.2 9,079 4 KK 2 292.8 2.7 1.34 0.79 23,208 18,110 55.0 9,962 4 KK 3 288.0 5.1 2.10 1.24 30,928 32,254 59.7 19,267 4 KK 4 222.8 5.4 1.24 0.73 19,927 31,762 61.7 19,586 4 KK 5 333.1 3.6 1.09 0.64 10,944 24,607 55.8 13,739 4 KR 1 180.0 8.6 1.27 0.75 20,037 21,462 57.1 12,252 4 KR 2 150.0 11.4 1.28 0.75 18,512 22,235 68.5 15,242 4 KR 3 207.4 11.0 1.23 0.73 17,995 27,669 54.1 14,956 4 KR 4 169.3 1.3 1.25 0.74 16,788 13,121 51.7 6,787 4 KR 5 190.7 11.4 1.28 0.75 17,711 32,766 59.1 19,350 4 VB 1 152.7 7.0 1.38 0.81 23,781 16,914 63.7 10,768 4 VB 2 122.1 15.7 1.26 0.74 23,188 20,778 57.5 11,940 4 VB 3 129.4 8.9 1.53 0.90 17,993 18,450 58.5 10,789 4 VB 4 137.8 10.5 1.96 1.15 32,071 11,203 54.4 6,097 4 VB 5 156.6 6.9 1.56 0.92 23,425 20,573 58.0 11,934 5 CH 1 322.3 6.4 1.51 0.89 23,733 16,634 55.3 9,196 5 CH 2 235.2 8.0 1.95 1.15 30,704 18,416 51.4 9,458 5 CH 3 240.2 6.7 2.44 1.44 38,479 27,272 57.1 15,572 5 CH 4 270.3 2.6 1.58 0.93 24,985 29,283 51.9 15,189 5 CH 5 240.7 2.5 1.64 0.97 25,918 21,563 51.9 11,198 5 CH 6 289.7 5.4 1.44 0.85 22,750 18,517 55.3 10,243 5 CO 1 253.5 14.0 2.69 1.58 44,366 22,880 48.7 11,142 5 CO 2 216.8 8.7 2.35 1.38 37,831 17,749 53.8 9,553 5 CO 3 191.4 7.2 2.21 1.30 32,728 23,176 52.1 12,073 5 CO 4 211.1 8.2 1.83 1.07 24,279 22,441 54.8 12,306 5 CO 5 208.5 12.5 1.40 0.82 20,679 20,341 52.1 10,589 5 CO 6 206.1 12.8 2.24 1.32 33,696 27,654 55.9 15,454 5 KD 1 248.1 15.8 2.19 1.29 33,170 18,700 53.3 9,967 5 KD 2 329.0 8.8 2.26 1.33 33,297 18,133 50.2 9,094 5 KD 3 307.2 14.3 2.61 1.53 39,861 16,855 88.6 14,936 5 KD 4 285.5 9.1 2.05 1.20 31,792 20,512 36.9 7,570 5 KD 5 290.3 9.6 2.42 1.42 37,897 25,442 54.2 13,791 5 KK 1 323.9 1.8 1.19 0.70 17,968 27,602 52.8 14,569 5 KK 2 163.6 1.0 1.51 0.89 20,200 23,449 47.1 11,048 5 KK 3 260.2 9.2 1.74 1.02 26,343 15,450 47.8 7,387 5 KK 4 271.1 9.1 1.95 1.15 32,819 16,890 51.4 8,675 5 KK 5 251.6 4.8 1.95 1.15 29,362 20,911 55.9 11,695 5 KR 1 214.1 8.9 1.36 0.80 22,966 18,967 58.9 11,174 5 KR 2 176.8 6.7 1.50 0.89 23,541 17,067 40.9 6,979 5 KR 3 161.1 2.5 1.53 0.90 22,725 20,669 56.0 11,578 5 KR 4 233.1 5.6 1.58 0.93 24,215 15,256 49.9 7,617 5 KR 5 227.4 4.2 1.46 0.86 23,248 21,461 50.3 10,800 5 VB 1 236.9 10.3 1.80 1.06 30,879 23,688 51.7 12,255

74

BLK TRT PLT

Stand Volume (m3ha-1)

HWBA (m2ha-1) OM%

Soil C upper 20 cm

(%)

Soil C upper 20 cm

(kg ha-1)

Litter Wt.

(kg ha-1)

Litter C

(%)

Litter C

(kg ha-1) 5 VB 2 294.0 5.9 1.65 0.97 25,980 21,194 49.2 10,423 5 VB 3 248.7 5.1 1.52 0.89 21,267 22,675 53.7 12,184 5 VB 4 272.5 2.7 1.13 0.66 16,758 25,361 52.1 13,225 5 VB 5 308.1 2.5 1.83 1.08 27,543 28,466 50.8 14,450 6 CH 1 160.5 1.7 1.31 0.77 20,957 10,692 56.2 6,004 6 CH 2 148.6 2.1 1.54 0.90 24,566 16,259 53.2 8,643 6 CH 3 181.0 0.3 1.25 0.73 19,960 22,219 52.4 11,636 6 CH 4 118.6 1.0 1.99 1.17 31,868 19,637 60.1 11,798 6 CH 5 . 6.9 1.41 0.83 22,629 17,719 60.1 10,648 6 CH 6 238.8 5.1 1.42 0.84 22,766 20,284 43.5 8,814 6 CO 1 32.7 9.3 2.12 1.25 33,207 20,864 52.2 10,898 6 CO 2 94.0 6.9 1.18 0.70 19,075 17,309 56.9 9,843 6 CO 3 96.6 10.5 1.42 0.83 22,480 16,461 25.5 4,204 6 CO 4 104.7 17.6 1.82 1.07 27,847 15,091 56.7 8,558 6 CO 5 72.3 14.0 1.41 0.83 21,715 13,200 43.6 5,756 6 CO 6 7.6 22.1 1.58 0.93 24,467 13,343 56.6 7,556 6 KD 1 135.6 1.0 2.14 1.26 37,447 22,499 61.3 13,782 6 KD 2 205.5 2.5 1.58 0.93 25,025 25,093 60.3 15,140 6 KD 3 131.1 5.9 1.70 1.00 28,039 12,513 62.6 7,838 6 KD 5 . . 1.32 0.78 16,151 15,816 56.3 8,907 6 KK 1 156.7 0.6 1.42 0.83 16,988 25,109 56.8 14,262 6 KK 2 198.0 2.4 1.26 0.74 17,154 26,067 59.6 15,529 6 KK 3 150.0 2.0 1.54 0.91 22,822 17,716 59.3 10,501 6 KK 4 120.3 0.6 1.54 0.90 25,130 21,662 60.5 13,101 6 KK 5 150.1 2.7 0.99 0.59 14,627 25,708 60.3 15,494 6 KR 1 85.7 2.4 2.47 1.45 38,373 8,649 51.9 4,493 6 KR 2 99.4 2.1 1.24 0.73 20,355 17,991 50.0 8,992 6 KR 3 125.4 0.9 1.29 0.76 18,527 11,693 55.8 6,528 6 KR 4 206.0 2.0 1.42 0.83 22,691 19,404 56.7 11,001 6 KR 5 173.0 5.5 1.25 0.74 21,949 12,045 66.0 7,949 6 VB 1 124.2 1.9 1.39 0.82 20,318 15,461 55.2 8,530 6 VB 2 203.0 4.9 1.58 0.93 25,392 19,442 64.3 12,493 6 VB 3 193.1 2.8 1.62 0.95 31,647 24,674 57.7 14,246 6 VB 4 142.5 5.3 1.76 1.03 26,884 17,283 52.9 9,149 6 VB 5 . . 1.47 0.86 19,684 20,173 58.4 11,773 7 CH 1 195.4 1.4 1.65 0.97 26,057 16,944 58.5 9,912 7 CH 2 256.0 4.0 2.60 1.53 40,996 17,769 57.1 10,149 7 CH 3 157.1 2.1 2.77 1.63 43,727 18,432 58.8 10,843 7 CH 4 102.2 3.3 1.52 0.89 23,981 29,990 52.7 15,812 7 CH 5 116.1 1.8 2.41 1.42 38,022 10,850 49.5 5,371 7 CH 6 165.5 1.3 2.47 1.45 38,929 6,419 53.0 3,403 7 CO 1 125.4 13.2 1.83 1.08 23,262 16,082 54.9 8,836 7 CO 2 192.7 11.4 1.13 0.67 17,462 25,051 54.8 13,729 7 CO 3 114.0 2.2 1.13 0.67 19,758 26,553 48.1 12,777 7 CO 4 146.2 10.4 0.87 0.51 12,754 35,500 51.7 18,337 7 CO 5 130.4 11.9 1.54 0.91 22,997 13,539 55.0 7,444 7 CO 6 219.8 5.7 1.39 0.82 20,170 18,483 59.0 10,900 7 KD 1 124.8 1.5 1.56 0.92 23,648 16,879 53.8 9,080 7 KD 2 209.2 0.8 1.14 0.67 17,388 22,498 46.8 10,532 7 KD 3 178.2 3.9 1.43 0.84 19,620 22,817 53.1 12,111 7 KD 4 186.8 1.8 1.02 0.60 13,180 26,587 59.1 15,718 7 KD 5 206.3 4.1 1.04 0.61 17,027 26,501 55.5 14,716 7 KK 1 238.4 8.6 1.59 0.93 22,416 14,966 50.6 7,573 7 KK 2 204.2 6.8 1.19 0.70 15,942 15,633 55.7 8,700

75

BLK TRT PLT

Stand Volume (m3ha-1)

HWBA (m2ha-1) OM%

Soil C upper 20 cm

(%)

Soil C upper 20 cm

(kg ha-1)

Litter Wt.

(kg ha-1)

Litter C

(%)

Litter C

(kg ha-1) 7 KK 3 135.7 1.1 1.30 0.77 22,803 21,324 52.3 11,160 7 KK 4 186.1 2.7 1.28 0.75 16,210 19,926 47.5 9,472 7 KK 5 296.7 4.5 1.07 0.63 10,917 17,521 52.9 9,268 7 KR 1 195.6 3.9 1.55 0.91 24,442 26,175 53.7 14,053 7 KR 2 269.2 4.5 2.10 1.24 32,882 21,371 57.5 12,278 7 KR 3 198.5 6.3 1.68 0.99 27,660 20,902 60.1 12,559 7 KR 4 219.3 6.5 1.16 0.68 15,743 25,459 52.2 13,287 7 KR 5 204.0 5.6 1.32 0.78 22,973 20,204 50.3 10,166 7 VB 1 176.3 8.0 1.78 1.04 30,078 19,252 54.9 10,572 7 VB 2 189.1 4.9 1.16 0.68 18,742 18,833 51.9 9,773 7 VB 3 175.5 1.6 1.40 0.82 23,208 20,650 56.0 11,571 7 VB 5 274.3 7.4 1.41 0.83 25,456 13,488 43.0 5,807 8 CH 1 203.3 9.1 2.69 1.58 41,521 25,157 59.2 14,902 8 CH 2 190.8 3.7 1.09 0.64 16,857 26,026 81.5 21,219 8 CH 3 241.7 8.6 0.80 0.47 12,400 22,288 66.2 14,760 8 CH 4 239.9 5.5 1.10 0.65 16,960 11,287 53.0 5,980 8 CH 5 257.8 5.5 0.96 0.56 14,770 17,272 61.1 10,546 8 CH 6 249.1 5.4 1.09 0.64 16,752 31,247 61.5 19,218 8 CO 1 164.9 7.0 1.26 0.74 18,882 16,578 46.9 7,778 8 CO 2 65.5 23.8 1.29 0.76 18,683 27,870 50.0 13,933 8 CO 3 72.5 6.5 1.43 0.84 21,825 26,586 40.8 10,835 8 CO 4 78.5 12.6 1.28 0.75 13,224 16,627 67.1 11,159 8 CO 5 79.1 8.9 1.01 0.60 17,180 21,250 53.9 11,453 8 CO 6 149.9 22.6 1.54 0.91 22,082 14,683 57.0 8,372 8 KD 1 240.1 5.8 1.64 0.97 23,795 20,012 50.4 10,095 8 KD 2 182.7 8.6 1.37 0.81 21,604 22,134 49.9 11,050 8 KD 3 218.4 5.8 1.50 0.88 22,966 31,262 53.7 16,776 8 KD 4 223.2 2.8 1.80 1.06 27,575 19,209 54.4 10,448 8 KD 5 246.6 3.7 1.25 0.73 19,052 23,925 52.1 12,456 8 KK 1 125.3 3.5 1.36 0.80 20,341 14,639 55.0 8,054 8 KK 2 114.5 3.4 1.07 0.63 17,244 20,446 52.1 10,661 8 KK 3 232.7 6.0 1.32 0.77 20,147 20,829 55.9 11,635 8 KK 4 283.0 5.5 1.06 0.62 16,104 22,868 60.0 13,725 8 KK 5 . 0.9 1.35 0.79 18,055 21,786 62.8 13,682 8 KR 1 119.6 7.5 1.35 0.79 23,203 16,940 52.6 8,906 8 KR 2 213.4 10.7 1.08 0.63 16,847 25,946 52.1 13,506 8 KR 3 246.2 9.0 1.08 0.64 16,040 19,454 58.8 11,435 8 KR 4 184.9 7.3 1.17 0.69 15,895 22,288 61.5 13,716 8 KR 5 230.3 4.4 1.84 1.09 29,085 18,193 58.3 10,601 8 VB 1 271.0 0.2 1.70 1.00 27,260 26,184 57.5 15,044 8 VB 2 273.7 3.2 1.71 1.00 27,325 22,284 55.5 12,365 8 VB 3 264.5 11.0 1.42 0.83 23,711 23,613 55.5 13,099 8 VB 4 263.2 4.5 1.05 0.62 16,574 27,120 62.3 16,906 8 VB 5 156.7 6.3 1.31 0.77 20,818 15,492 56.5 8,757 9 CH 1 209.1 8.5 2.53 1.49 33,076 23,977 52.5 12,579 9 CH 2 190.0 6.4 2.01 1.18 26,230 19,360 55.4 10,723 9 CH 3 265.8 6.2 1.71 1.00 22,295 17,154 50.3 8,620 9 CH 4 234.3 14.8 1.42 0.84 18,550 16,923 50.2 8,502 9 CH 5 480.3 13.7 1.73 1.02 22,573 15,853 55.6 8,807 9 CH 6 230.0 11.4 1.53 0.90 20,005 27,819 49.9 13,889 9 CO 1 48.9 6.9 1.51 0.89 24,273 12,250 52.9 6,480 9 CO 2 152.4 10.8 1.76 1.03 27,704 20,306 51.5 10,462 9 CO 3 116.2 16.6 2.04 1.20 30,042 15,671 52.4 8,215 9 CO 4 134.8 . 1.80 1.06 25,623 22,508 51.6 11,608

76

BLK TRT PLT

Stand Volume (m3ha-1)

HWBA (m2ha-1) OM%

Soil C upper 20 cm

(%)

Soil C upper 20 cm

(kg ha-1)

Litter Wt.

(kg ha-1)

Litter C

(%)

Litter C

(kg ha-1) 9 CO 5 . . 2.41 1.42 43,333 19,836 52.5 10,407 9 CO 6 144.0 6.4 1.70 1.00 26,779 14,359 51.5 7,390 9 KD 1 184.4 6.0 0.97 0.57 15,356 13,457 54.2 7,293 9 KD 2 185.7 4.4 2.27 1.34 37,723 19,166 50.3 9,640 9 KD 3 274.9 9.7 2.00 1.18 26,144 33,475 53.7 17,972 9 KD 4 184.3 . 2.35 1.38 35,333 19,540 53.8 10,522 9 KD 5 122.9 2.7 2.00 1.18 26,605 19,793 57.5 11,379 9 KK 1 186.8 4.1 1.90 1.12 29,298 21,631 55.3 11,969 9 KK 2 190.5 6.2 2.48 1.46 34,445 18,592 52.7 9,806 9 KK 3 164.5 4.5 2.06 1.21 29,991 22,111 51.9 11,479 9 KK 4 149.7 4.3 2.06 1.21 25,440 18,660 50.9 9,505 9 KK 5 210.4 1.6 2.07 1.22 28,774 17,917 55.0 9,847 9 KR 1 139.1 3.1 1.54 0.90 19,869 17,024 52.6 8,961 9 KR 2 203.1 8.8 2.04 1.20 28,552 16,910 48.7 8,233 9 KR 3 158.3 7.4 2.33 1.37 27,170 18,441 53.1 9,784 9 KR 4 167.5 9.7 2.20 1.29 28,978 16,244 51.7 8,405 9 KR 5 148.8 7.6 2.66 1.57 36,028 19,368 58.5 11,324 9 VB 1 113.8 7.2 1.79 1.05 27,112 20,817 56.7 11,801 9 VB 2 174.1 10.8 2.14 1.26 27,435 15,571 51.4 7,998 9 VB 3 137.1 7.3 2.48 1.46 36,992 11,002 52.5 5,777 9 VB 4 200.3 12.1 3.10 1.82 44,456 21,078 50.6 10,656 9 VB 5 136.9 7.4 2.05 1.21 28,508 18,905 50.6 9,573

10 CH 1 194.4 4.3 1.24 0.73 17,008 13,680 58.3 7,973 10 CH 2 302.4 3.4 2.56 1.51 35,286 17,311 52.9 9,157 10 CH 3 290.4 . 1.68 0.99 23,151 19,152 51.5 9,868 10 CH 4 226.7 8.8 1.10 0.65 15,190 20,262 49.5 10,029 10 CH 5 229.5 15.5 1.76 1.04 25,913 16,149 52.1 8,418 10 CO 1 102.7 16.1 1.10 0.65 18,248 20,685 50.3 10,413 10 CO 2 151.3 12.0 1.11 0.65 16,927 17,972 39.0 7,015 10 CO 3 110.4 10.5 1.40 0.82 19,545 12,489 46.5 5,810 10 CO 4 115.9 16.3 1.41 0.83 21,373 17,487 49.5 8,654 10 CO 5 68.6 9.5 1.52 0.89 21,441 16,631 49.1 8,167 10 CO 6 84.7 . 1.69 0.99 25,399 33,295 40.3 13,425 10 KD 1 255.1 2.5 0.68 0.40 10,353 23,793 53.3 12,684 10 KD 2 255.8 5.2 1.51 0.89 25,965 18,164 56.7 10,296 10 KD 3 228.8 4.9 1.40 0.83 19,482 20,582 47.0 9,680 10 KD 4 182.0 4.4 1.37 0.81 19,964 13,356 56.6 7,557 10 KD 5 175.8 6.8 1.51 0.89 19,064 12,957 81.7 10,580 10 KK 1 176.0 5.2 1.32 0.78 23,462 16,146 51.0 8,228 10 KK 2 261.6 8.0 1.62 0.95 25,119 19,113 54.4 10,397 10 KK 3 322.1 4.9 1.35 0.79 21,139 30,274 43.3 13,116 10 KK 4 298.6 5.4 1.60 0.94 24,113 19,636 42.8 8,407 10 KK 5 271.7 7.6 1.23 0.73 15,243 16,111 46.6 7,505 10 KR 1 184.7 11.8 1.45 0.85 19,759 14,587 54.9 8,001 10 KR 2 217.9 0.8 1.44 0.84 14,020 14,761 44.7 6,604 10 KR 3 188.4 6.9 1.42 0.84 22,106 18,536 41.3 7,657 10 KR 4 172.1 6.3 1.46 0.86 22,351 19,153 56.1 10,751 10 KR 5 176.6 8.8 2.07 1.22 29,925 20,515 49.2 10,087 10 VB 1 244.1 13.2 1.75 1.03 29,994 25,458 43.5 11,084 10 VB 2 282.6 5.9 1.51 0.89 24,040 28,258 43.4 12,264 10 VB 3 366.0 6.7 1.93 1.14 32,758 20,715 52.8 10,940 10 VB 4 229.8 3.0 1.72 1.01 21,847 21,692 46.9 10,163 10 VB 5 212.7 8.8 1.58 0.93 24,040 13,939 51.9 7,231 11 CH 1 327.4 4.4 1.13 0.66 18,337 28,290 49.6 14,020

77

BLK TRT PLT

Stand Volume (m3ha-1)

HWBA (m2ha-1) OM%

Soil C upper 20 cm

(%)

Soil C upper 20 cm

(kg ha-1)

Litter Wt.

(kg ha-1)

Litter C

(%)

Litter C

(kg ha-1) 11 CH 2 301.2 5.0 0.91 0.53 14,696 22,039 72.7 16,016 11 CH 3 215.9 4.5 0.77 0.46 12,570 22,650 57.7 13,066 11 CH 4 226.1 5.5 1.26 0.74 20,502 19,773 56.2 11,104 11 CH 5 257.4 10.1 1.02 0.60 16,624 25,929 51.7 13,394 11 CH 6 273.4 4.6 0.90 0.53 14,678 20,666 56.8 11,747 11 CO 1 169.7 1.6 1.86 1.10 28,924 25,747 47.7 12,292 11 CO 2 167.9 12.0 1.03 0.60 16,562 16,805 53.9 9,064 11 CO 3 123.4 11.2 0.79 0.47 12,183 19,786 48.7 9,639 11 CO 4 69.0 16.5 2.18 1.28 31,592 11,732 66.2 7,761 11 CO 5 104.2 4.6 1.19 0.70 18,851 16,977 43.5 7,387 11 CO 6 66.5 11.9 1.04 0.61 16,131 19,559 51.3 10,028 11 KD 1 332.3 5.7 2.12 1.25 38,892 43,585 50.3 21,934 11 KD 2 247.9 5.8 0.89 0.53 15,152 33,911 56.5 19,161 11 KD 3 374.5 8.8 1.30 0.77 22,721 28,910 52.5 15,179 11 KD 4 322.1 7.8 0.92 0.54 15,215 28,091 53.0 14,890 11 KD 5 347.5 10.0 1.03 0.61 15,007 22,580 52.6 11,885 11 KK 1 232.0 . 0.92 0.54 14,130 23,974 46.9 11,232 11 KK 2 202.1 5.1 1.05 0.62 18,722 14,959 59.9 8,965 11 KK 3 245.8 3.1 1.05 0.62 14,386 14,145 53.5 7,572 11 KK 4 174.2 8.8 0.92 0.54 14,483 10,700 56.9 6,089 11 KK 5 290.1 . 0.94 0.55 15,336 17,166 52.9 9,077 11 KR 1 241.8 3.7 0.79 0.46 13,037 20,446 55.9 11,429 11 KR 2 255.4 5.1 0.81 0.48 12,192 19,624 52.3 10,273 11 KR 3 315.5 8.9 1.07 0.63 19,123 14,386 51.0 7,343 11 KR 4 240.2 6.9 1.08 0.64 17,401 20,307 50.3 10,222 11 KR 5 263.1 6.2 1.34 0.79 20,721 23,194 51.2 11,884 11 VB 1 260.6 3.0 0.67 0.39 10,542 24,486 54.3 13,302 11 VB 2 317.6 4.0 1.21 0.71 20,367 18,158 53.7 9,745 11 VB 3 163.7 2.2 1.05 0.62 16,553 26,427 52.2 13,804 11 VB 4 306.4 1.2 0.92 0.54 15,988 17,172 51.6 8,857 11 VB 5 231.8 4.3 1.08 0.64 18,693 18,272 53.5 9,781 12 CH 1 178.2 4.4 2.73 1.60 41,384 23,037 56.0 12,910 12 CH 2 113.1 5.3 1.02 0.60 15,490 22,445 54.8 12,307 12 CH 3 138.4 10.6 1.34 0.79 20,267 21,159 53.9 11,402 12 CH 4 154.0 7.0 1.73 1.02 26,267 15,592 52.1 8,128 12 CH 5 162.9 9.2 1.49 0.88 22,596 22,740 52.9 12,041 12 CO 1 98.3 22.3 1.66 0.97 28,642 16,137 45.3 7,307 12 CO 2 86.2 29.9 1.32 0.78 19,312 20,110 50.7 10,188 12 CO 3 62.5 16.3 2.07 1.22 32,216 17,161 41.1 7,051 12 CO 4 219.0 12.8 1.29 0.76 21,167 16,791 40.8 6,844 12 CO 5 107.8 30.5 1.46 0.86 22,044 20,089 51.5 10,340 12 CO 6 169.7 23.3 0.88 0.52 13,919 23,421 56.4 13,203 12 KD 1 233.0 4.1 1.46 0.86 20,441 15,509 49.9 7,733 12 KD 2 184.8 3.8 1.30 0.76 17,864 24,400 51.0 12,446 12 KD 3 207.9 3.6 1.45 0.85 20,963 18,443 55.1 10,162 12 KD 4 134.0 4.9 0.81 0.48 11,629 28,214 52.9 14,919 12 KD 5 165.5 5.0 2.13 1.25 29,509 16,512 49.3 8,137 12 KK 1 144.4 4.6 1.29 0.76 20,471 19,201 62.1 11,923 12 KK 2 158.7 3.0 1.25 0.73 19,047 22,378 62.8 14,055 12 KK 3 120.0 3.9 1.05 0.62 16,731 21,730 55.1 11,964 12 KK 4 114.5 4.6 1.73 1.02 24,891 30,312 50.0 15,168 12 KK 5 214.4 3.3 . . . . . . 12 KR 1 135.7 4.7 3.41 2.01 53,397 22,488 56.4 12,673 12 KR 2 119.3 4.5 1.70 1.00 24,762 16,094 59.1 9,504

78

BLK TRT PLT

Stand Volume (m3ha-1)

HWBA (m2ha-1) OM%

Soil C upper 20 cm

(%)

Soil C upper 20 cm

(kg ha-1)

Litter Wt.

(kg ha-1)

Litter C

(%)

Litter C

(kg ha-1) 12 KR 3 190.6 6.2 0.92 0.54 12,073 37,415 53.6 20,063 12 KR 4 117.4 8.4 1.37 0.81 22,272 13,293 50.1 6,656 12 KR 5 98.4 0.2 2.08 1.23 33,815 31,693 68.5 21,696 12 VB 1 96.9 10.3 1.69 1.00 23,426 16,510 49.5 8,173 12 VB 2 152.0 2.9 2.02 1.19 26,042 13,969 56.4 7,878 12 VB 3 109.2 6.8 2.21 1.30 28,708 36,837 56.9 20,954 12 VB 4 58.8 5.6 1.56 0.92 21,526 9,668 50.3 4,860 12 VB 5 126.4 7.7 1.95 1.15 26,084 19,676 55.8 10,973

79

APPENDIX C. SITE NITROGEN

BLK TRT PLT

Total Nitrogen

(ppm)

Total Nitrogen (kg ha-1)

Mineralized Nitrogen (pmm)

Potentially Mineralizable N

(kg ha-1) Inorganic N

(kg ha-1)

Foliar Nitrogen

(%) 1 CH 1 381 976 17.10 43.77 9.13 1.15 1 CH 2 356 912 17.74 45.41 9.10 1.24 1 CH 3 336 860 23.00 58.87 12.13 1.25 1 CH 4 323 827 26.05 66.69 9.63 1.21 1 CH 5 425 1089 24.46 62.61 14.52 1.20 1 CH 6 380 972 19.19 49.13 10.61 1.13 1 CO 1 350 931 39.81 105.89 18.18 1.19 1 CO 2 353 861 44.48 108.53 24.29 1.21 1 CO 3 347 770 32.13 71.32 24.39 1.37 1 CO 4 343 865 46.76 117.84 15.75 1.20 1 CO 5 319 767 44.29 106.29 19.49 1.27 1 CO 6 333 799 26.54 63.70 15.28 1.30 1 KD 1 537 1751 42.24 137.71 14.94 1.21 1 KD 2 520 1517 27.43 80.10 8.86 1.14 1 KD 3 540 1328 26.07 64.13 29.38 1.22 1 KD 4 504 1221 33.30 80.59 14.35 1.13 1 KD 5 494 1353 27.65 75.76 12.30 1.28 1 KK 1 458 1263 46.10 127.23 14.64 1.43 1 KK 2 622 1480 36.02 85.74 12.33 1.24 1 KK 3 622 1454 36.65 85.77 18.50 1.27 1 KK 4 521 1281 31.76 78.13 12.87 1.33 1 KK 5 517 1500 39.80 115.42 10.92 1.21 1 KR 1 426 979 16.43 37.78 9.92 1.30 1 KR 2 432 1211 37.74 105.67 28.95 1.10 1 KR 3 458 1164 28.50 72.38 12.57 1.08 1 KR 4 462 1219 24.82 65.53 13.90 1.10 1 KR 5 370 933 22.40 56.45 17.82 1.26 1 VB 1 435 1210 35.44 98.53 15.81 1.26 1 VB 2 435 1113 47.42 121.39 15.41 1.41 1 VB 3 436 1195 25.53 69.95 11.19 1.24 1 VB 4 421 910 29.66 64.05 8.88 1.25 1 VB 5 460 975 46.05 97.63 11.50 1.25 2 CH 1 221 609 67.26 185.63 42.27 0.96 2 CH 2 394 1088 22.91 63.23 33.83 0.96 2 CH 3 282 778 30.21 83.38 40.91 1.08 2 CH 4 321 887 20.54 56.69 32.80 1.15 2 CH 5 300 829 13.85 38.22 47.69 1.01 2 CH 6 538 1485 12.96 35.76 32.76 1.10 2 CO 1 535 1541 17.70 50.99 25.42 0.87 2 CO 2 435 1278 10.16 29.88 42.80 0.96 2 CO 3 506 1519 16.34 49.01 34.76 1.00 2 CO 4 490 1451 19.96 59.09 14.59 1.09 2 CO 5 325 884 5.72 15.56 37.48 1.03 2 CO 6 389 1088 22.57 63.21 41.48 1.07 2 KD 1 374 989 6.02 15.89 49.26 0.98 2 KD 2 727 1322 14.48 26.35 40.34 1.00 2 KD 3 321 911 5.87 16.66 44.05 0.94 2 KD 4 512 1209 9.15 21.59 44.96 0.89 2 KD 5 335 997 3.40 10.12 39.26 1.05 2 KK 1 334 901 18.57 50.14 53.80 0.93 2 KK 2 239 554 24.31 56.39 21.15 0.97 2 KK 3 303 611 50.15 101.29 65.87 1.02

80

BLK TRT PLT

Total Nitrogen

(ppm)

Total Nitrogen (kg ha-1)

Mineralized Nitrogen (pmm)

Potentially Mineralizable N

(kg ha-1) Inorganic N

(kg ha-1)

Foliar Nitrogen

(%) 2 KR 2 372 1102 11.11 32.88 47.54 0.99 2 KR 3 387 1054 1.40 3.80 42.94 1.03 2 KR 4 315 807 13.08 33.48 54.69 1.00 2 KR 5 516 1496 11.06 32.07 16.98 0.95 2 VB 1 266 729 27.30 74.80 42.80 1.13 2 VB 2 323 871 13.17 35.55 48.71 0.91 2 VB 3 235 765 10.20 33.25 49.04 1.01 2 VB 4 437 1197 18.89 51.76 0.00 1.02 2 VB 5 331 862 9.95 25.86 32.92 0.96 3 CH 1 858 2421 . . . 1.00 3 CH 2 362 1021 12.03 33.92 22.95 0.87 3 CH 3 257 726 . . . 1.10 3 CH 4 242 683 6.09 17.18 56.59 1.09 3 CH 5 368 1038 . . . 1.00 3 CH 6 274 773 22.12 62.38 24.24 1.06 3 CO 1 453 1079 24.55 58.43 27.62 0.98 3 CO 2 197 476 16.36 39.58 35.67 1.00 3 CO 3 407 1156 33.23 94.37 23.63 1.03 3 CO 4 428 1129 15.09 39.84 40.10 1.06 3 CO 5 348 1003 14.77 42.55 27.45 1.02 3 CO 6 280 738 11.86 31.30 8.62 0.95 3 KD 1 329 967 22.37 65.76 68.77 1.09 3 KD 2 560 1647 23.39 68.78 68.11 1.22 3 KD 3 318 833 . . . 1.20 3 KD 4 329 771 9.80 22.94 7.92 1.21 3 KD 5 552 982 19.93 35.47 10.78 1.24 3 KK 1 392 1019 23.94 62.24 25.94 1.08 3 KK 2 384 1053 11.82 32.39 33.32 1.03 3 KK 3 361 981 14.83 40.33 42.41 0.94 3 KK 4 400 1024 5.19 13.28 31.80 1.12 3 KK 5 417 934 27.11 60.72 37.10 1.02 3 KR 1 438 991 29.39 66.42 8.29 1.14 3 KR 2 484 1472 . . . 1.00 3 KR 3 268 730 20.74 56.41 39.53 . 3 KR 4 537 1686 7.88 24.74 59.35 1.15 3 KR 5 578 1689 23.34 68.15 32.46 1.12 3 VB 1 802 2470 37.65 115.95 28.45 1.31 3 VB 2 365 1058 27.23 78.98 56.98 1.39 3 VB 3 456 1131 37.33 92.57 23.42 1.27 3 VB 4 408 719 24.46 43.06 36.87 1.14 3 VB 5 383 1141 20.43 60.89 38.73 1.19 4 CH 1 439 1079 13.52 33.26 6.50 1.13 4 CH 2 295 726 17.26 42.45 9.36 1.17 4 CH 3 447 1099 25.95 63.84 6.00 1.11 4 CH 4 375 923 8.57 21.09 6.57 1.07 4 CH 5 377 927 9.16 22.52 6.91 1.14 4 CO 1 417 1291 20.73 64.25 24.20 1.02 4 CO 2 387 1044 20.27 54.74 12.97 1.04 4 CO 3 417 1000 18.17 43.61 5.85 0.92 4 CO 4 429 987 25.20 57.96 13.10 0.98 4 CO 5 732 1948 24.86 66.13 20.01 0.96 4 CO 6 561 1369 21.60 52.71 28.41 1.04 4 KD 1 664 1792 21.93 59.20 6.27 . 4 KD 2 363 893 20.66 50.82 8.50 1.12

81

BLK TRT PLT

Total Nitrogen

(ppm)

Total Nitrogen (kg ha-1)

Mineralized Nitrogen (pmm)

Potentially Mineralizable N

(kg ha-1) Inorganic N

(kg ha-1)

Foliar Nitrogen

(%) 4 KD 3 285 719 18.34 46.21 6.10 0.96 4 KD 4 366 960 8.82 23.10 13.47 1.02 4 KD 5 337 668 16.10 31.88 6.27 1.10 4 KK 1 238 448 34.62 65.09 9.65 1.24 4 KK 2 303 889 20.53 60.36 13.40 1.08 4 KK 3 420 1049 62.12 155.30 35.28 1.23 4 KK 4 366 1004 18.73 51.33 20.93 0.99 4 KK 5 344 585 25.52 43.38 9.16 0.92 4 KR 1 274 733 7.37 19.75 9.61 0.90 4 KR 2 436 1073 16.46 40.50 5.97 0.93 4 KR 3 327 812 10.20 25.30 5.12 0.96 4 KR 4 275 626 14.30 32.60 6.47 0.97 4 KR 5 320 754 11.98 28.27 5.54 0.94 4 VB 1 633 1849 11.47 33.50 9.95 0.99 4 VB 2 346 1085 9.76 30.65 7.10 1.12 4 VB 3 366 732 29.65 59.30 6.86 1.03 4 VB 4 224 622 14.48 40.27 8.72 1.06 4 VB 5 216 554 18.59 47.58 6.07 1.04 5 CH 1 216 580 54.30 145.53 24.15 1.07 5 CH 2 254 680 16.60 44.49 35.54 0.96 5 CH 3 189 507 25.09 67.24 76.97 1.00 5 CH 4 337 903 64.71 173.43 53.87 1.03 5 CH 5 406 1087 . . . 0.99 5 CH 6 344 921 23.89 64.04 48.61 0.99 5 CO 1 534 1494 39.24 105.16 36.21 1.05 5 CO 2 410 1122 38.69 108.32 94.24 1.02 5 CO 3 376 948 35.57 97.45 61.44 0.95 5 CO 4 297 671 59.81 150.72 41.89 1.01 5 CO 5 385 970 44.82 112.95 73.06 1.06 5 CO 6 387 989 45.66 116.89 66.09 1.02 5 KD 1 394 1017 54.67 141.04 71.79 1.05 5 KD 2 490 1224 41.08 102.70 68.75 1.01 5 KD 3 532 1383 47.61 123.79 61.44 0.98 5 KD 4 750 1979 52.55 138.72 54.77 1.02 5 KD 5 672 1788 42.95 114.24 27.10 0.97 5 KK 1 567 1451 29.78 76.24 37.32 1.02 5 KK 2 456 1040 25.72 58.64 42.26 0.96 5 KK 3 756 1950 38.33 98.88 43.84 1.02 5 KK 4 833 2382 24.85 71.08 64.72 0.97 5 KK 5 651 1668 51.00 130.57 47.14 0.96 5 KR 1 539 1554 25.72 74.07 27.66 0.99 5 KR 2 930 2474 30.68 81.61 9.04 0.95 5 KR 3 632 1593 26.88 67.74 28.63 0.96 5 KR 4 738 1919 36.20 94.11 47.51 1.01 5 KR 5 700 1889 24.83 67.05 18.88 0.97 5 VB 1 538 1572 37.74 110.19 32.16 1.06 5 VB 2 458 1227 25.45 68.21 23.22 1.03 5 VB 3 578 1375 25.33 60.29 45.40 0.90 5 VB 4 460 1159 15.22 38.35 13.13 0.99 5 VB 5 423 1082 36.26 92.82 25.10 1.06 6 CH 1 480 1305 8.98 24.41 13.56 1.03 6 CH 2 579 1576 10.26 27.91 12.91 1.07 6 CH 3 424 1153 18.30 49.77 15.46 1.19 6 CH 4 968 2633 19.33 52.58 11.72 1.20

82

BLK TRT PLT

Total Nitrogen

(ppm)

Total Nitrogen (kg ha-1)

Mineralized Nitrogen (pmm)

Potentially Mineralizable N

(kg ha-1) Inorganic N

(kg ha-1)

Foliar Nitrogen

(%) 6 CH 5 643 1750 11.53 31.35 11.72 1.14 6 CH 6 573 1559 25.85 70.31 13.19 1.23 6 CO 1 687 1827 14.96 39.80 18.74 0.99 6 CO 2 404 1107 9.23 25.29 12.39 0.86 6 CO 3 578 1561 20.12 54.32 10.72 0.94 6 CO 4 526 1369 14.54 37.79 14.51 0.94 6 CO 5 570 1492 16.41 42.99 11.36 0.93 6 CO 6 333 880 17.34 45.79 11.26 0.93 6 KD 1 456 1358 18.26 54.42 18.93 0.95 6 KD 2 408 1103 16.73 45.18 14.15 1.01 6 KD 3 347 972 13.06 36.56 17.30 1.05 6 KD 5 396 825 19.12 39.76 11.18 1.03 6 KK 1 525 1072 11.01 22.46 9.90 0.91 6 KK 2 415 963 13.43 31.16 10.73 1.01 6 KK 3 344 866 21.59 54.40 14.75 0.94 6 KK 4 623 1731 16.44 45.71 11.12 0.93 6 KK 5 329 822 13.70 34.26 10.81 0.99 6 KR 1 301 794 11.86 31.32 12.45 1.02 6 KR 2 564 1567 19.17 53.29 13.08 1.03 6 KR 3 482 1177 13.58 33.14 8.48 1.02 6 KR 4 459 1249 13.89 37.78 10.60 1.02 6 KR 5 568 1692 18.62 55.50 14.91 0.98 6 VB 1 375 930 22.26 55.19 8.97 1.05 6 VB 2 424 1160 19.94 54.63 16.55 1.01 6 VB 3 457 1518 30.81 102.28 18.32 1.00 6 VB 4 426 1107 20.04 52.11 10.98 1.03 6 VB 5 344 784 21.69 49.46 10.69 0.98 7 CH 1 409 1097 46.94 125.81 39.89 0.93 7 CH 2 457 1225 16.03 42.97 27.63 0.99 7 CH 3 405 1084 21.78 58.37 15.10 1.03 7 CH 4 419 1124 17.29 46.35 30.74 0.91 7 CH 5 393 1053 67.74 181.54 58.58 1.09 7 CH 6 533 1428 61.80 165.63 32.32 1.10 7 CO 1 546 1179 7.95 17.18 10.75 0.97 7 CO 2 345 903 6.35 16.65 14.45 1.00 7 CO 3 442 1308 5.28 15.64 9.85 0.89 7 CO 4 430 1075 12.83 32.09 13.23 0.86 7 CO 5 437 1111 12.81 32.53 12.28 0.88 7 CO 6 549 1352 8.30 20.42 11.84 0.94 7 KD 1 481 1242 27.64 71.32 14.33 1.08 7 KD 2 751 1953 10.19 26.49 9.93 1.02 7 KD 3 384 899 19.65 45.98 10.60 1.03 7 KD 4 357 786 10.83 23.82 8.81 0.95 7 KD 5 380 1057 13.70 38.10 9.82 1.06 7 KK 1 1262 3028 30.59 73.41 10.65 0.96 7 KK 2 829 1891 14.84 33.83 6.08 0.92 7 KK 3 433 1291 11.17 33.29 8.68 0.95 7 KK 4 293 634 9.05 19.54 8.15 0.89 7 KK 5 275 479 13.08 22.76 6.21 . 7 KR 1 262 703 17.29 46.33 8.28 0.98 7 KR 2 363 966 28.31 75.32 11.46 1.05 7 KR 3 360 1007 27.48 76.95 10.46 0.97 7 KR 4 569 1308 20.84 47.92 7.22 0.89 7 KR 5 316 934 19.88 58.83 9.31 0.82

83

BLK TRT PLT

Total Nitrogen

(ppm)

Total Nitrogen (kg ha-1)

Mineralized Nitrogen (pmm)

Potentially Mineralizable N

(kg ha-1) Inorganic N

(kg ha-1)

Foliar Nitrogen

(%) 7 VB 1 488 1406 10.10 29.08 11.21 1.04 7 VB 2 262 718 21.45 58.78 15.53 0.97 7 VB 3 320 903 14.40 40.61 9.01 0.88 7 VB 5 428 1318 22.31 68.72 12.42 0.99 8 CH 1 360 942 13.32 34.89 11.13 0.93 8 CH 2 308 806 14.34 37.56 8.28 0.98 8 CH 3 285 747 12.00 31.44 6.38 0.93 8 CH 4 397 1041 13.55 35.50 11.04 1.12 8 CH 5 575 1506 15.92 41.72 9.98 0.95 8 CH 6 501 1312 11.29 29.59 7.77 0.95 8 CO 1 300 762 15.19 38.59 11.06 1.00 8 CO 2 318 783 17.94 44.14 12.95 1.01 8 CO 3 408 1062 23.44 60.96 9.24 1.12 8 CO 4 331 582 17.91 31.51 4.47 1.14 8 CO 5 342 984 10.86 31.27 12.43 0.99 8 CO 6 496 1210 20.88 50.95 13.32 1.20 8 KD 1 400 984 29.99 73.78 10.60 1.17 8 KD 2 319 855 16.80 45.03 17.97 1.28 8 KD 3 307 798 7.19 18.70 7.02 1.09 8 KD 4 270 702 33.93 88.21 12.15 1.21 8 KD 5 306 795 14.57 37.89 8.89 0.95 8 KK 1 280 712 11.75 29.83 9.20 1.10 8 KK 2 313 856 16.93 46.39 11.47 1.20 8 KK 3 387 1006 24.72 64.28 10.09 1.06 8 KK 4 408 1053 21.22 54.75 9.56 1.12 8 KK 5 448 1022 15.23 34.73 6.57 1.70 8 KR 1 286 835 19.50 56.95 12.00 1.13 8 KR 2 340 904 19.61 52.15 10.64 1.20 8 KR 3 319 805 15.37 38.72 9.08 1.18 8 KR 4 416 958 18.94 43.57 8.87 1.18 8 KR 5 414 1108 21.62 57.93 11.72 1.25 8 VB 1 344 935 19.99 54.38 13.02 1.12 8 VB 2 333 905 15.86 43.14 10.83 1.18 8 VB 3 329 935 34.58 98.20 17.53 1.18 8 VB 4 373 1000 17.29 46.33 11.81 1.28 8 VB 5 343 925 15.98 43.14 10.55 1.20 9 CH 1 321 713 55.06 122.24 50.59 1.13 9 CH 2 375 832 40.49 89.88 19.13 1.01 9 CH 3 353 783 30.47 67.63 26.41 1.01 9 CH 4 329 730 20.94 46.48 20.53 1.03 9 CH 5 288 639 27.37 60.77 38.98 1.06 9 CH 6 301 668 46.40 103.00 45.50 1.05 9 CO 1 295 809 32.54 89.15 56.13 1.08 9 CO 2 371 994 51.09 136.92 62.48 1.04 9 CO 3 309 773 10.31 25.76 65.04 1.11 9 CO 4 301 729 94.79 229.39 90.70 1.06 9 CO 5 470 1438 57.05 174.58 115.20 1.35 9 CO 6 360 965 35.23 94.41 36.79 1.03 9 KD 1 325 879 24.06 64.97 36.50 0.72 9 KD 2 823 2321 40.60 114.49 55.93 1.00 9 KD 3 520 1153 26.65 59.16 11.13 1.06 9 KD 4 521 1333 17.16 43.93 27.33 1.00 9 KD 5 536 1210 28.33 64.02 12.77 0.91 9 KK 1 557 1458 15.45 40.48 15.02 1.00

84

BLK TRT PLT

Total Nitrogen

(ppm)

Total Nitrogen (kg ha-1)

Mineralized Nitrogen (pmm)

Potentially Mineralizable N

(kg ha-1) Inorganic N

(kg ha-1)

Foliar Nitrogen

(%) 9 KK 2 767 1810 30.76 72.60 20.65 0.99 9 KK 3 611 1516 21.01 52.11 24.35 1.05 9 KK 4 710 1491 16.00 33.59 15.51 0.93 9 KK 5 693 1635 16.01 37.79 11.39 1.01 9 KR 1 810 1782 15.64 34.42 22.48 1.03 9 KR 2 972 2314 26.26 62.50 23.48 0.91 9 KR 3 648 1282 36.23 71.74 11.66 0.95 9 KR 4 575 1287 33.60 75.26 13.97 1.00 9 KR 5 856 1969 41.05 94.41 11.91 0.92 9 VB 1 502 1294 15.61 40.28 23.94 0.84 9 VB 2 567 1236 16.85 36.72 21.57 1.01 9 VB 3 524 1332 8.42 21.38 13.67 0.87 9 VB 4 576 1406 50.31 122.76 10.86 0.99 9 VB 5 822 1940 20.01 47.22 10.97 0.89

10 CH 1 722 1689 17.48 40.91 25.19 1.10 10 CH 2 612 1432 52.05 121.79 56.72 1.13 10 CH 3 596 1395 28.49 66.66 33.42 1.01 10 CH 4 511 1195 4.62 10.81 23.30 1.05 10 CH 5 672 1679 26.70 66.75 10.53 1.07 10 CO 1 610 1720 31.06 87.58 47.64 1.03 10 CO 2 681 1770 11.17 29.05 40.75 1.07 10 CO 3 701 1668 22.21 52.87 43.06 1.13 10 CO 4 455 1175 30.47 78.62 45.86 1.02 10 CO 5 526 1261 35.11 84.26 27.21 1.08 10 CO 6 486 1244 17.91 45.84 48.02 1.11 10 KD 1 850 2193 12.02 31.01 22.39 1.03 10 KD 2 500 1460 18.02 52.61 17.41 1.10 10 KD 3 278 656 11.32 26.72 23.38 1.04 10 KD 4 720 1786 17.62 43.71 29.74 1.07 10 KD 5 389 832 21.83 46.72 12.90 1.05 10 KK 1 302 911 16.43 49.63 35.55 0.95 10 KK 2 420 1107 34.67 91.52 70.65 1.15 10 KK 3 349 927 30.30 80.59 32.48 1.13 10 KK 4 291 745 32.38 82.89 42.12 1.17 10 KK 5 376 790 33.29 69.91 28.90 1.01 10 KR 1 435 1009 33.07 76.72 32.27 1.04 10 KR 2 424 703 28.65 47.55 31.04 1.10 10 KR 3 403 1065 17.54 46.31 14.50 1.08 10 KR 4 269 699 18.32 47.64 39.06 1.04 10 KR 5 344 847 31.96 78.62 51.69 1.05 10 VB 1 354 1034 33.37 97.45 59.15 1.09 10 VB 2 336 907 24.33 65.69 51.73 1.07 10 VB 3 400 1152 30.50 87.84 61.67 1.05 10 VB 4 337 727 20.11 43.44 41.74 . 10 VB 5 580 1495 26.20 67.59 39.39 1.09 11 CH 1 352 972 4.08 11.25 11.05 0.99 11 CH 2 430 1188 4.03 11.11 13.07 0.99 11 CH 3 351 968 4.68 12.91 11.85 1.11 11 CH 4 466 1285 2.91 8.02 15.72 1.07 11 CH 5 393 1085 3.16 8.74 11.91 1.12 11 CH 6 383 1057 . . . 1.14 11 CO 1 399 1053 . . . 1.07 11 CO 2 522 1429 10.65 29.19 12.88 1.01 11 CO 3 522 1369 2.98 7.80 10.94 1.06

85

BLK TRT PLT

Total Nitrogen

(ppm)

Total Nitrogen (kg ha-1)

Mineralized Nitrogen (pmm)

Potentially Mineralizable N

(kg ha-1) Inorganic N

(kg ha-1)

Foliar Nitrogen

(%) 11 CO 4 396 974 4.56 11.22 8.86 1.01 11 CO 5 430 1161 9.41 25.39 11.62 1.16 11 CO 6 481 1269 1.95 5.15 9.41 1.13 11 KD 1 428 1334 15.78 49.25 18.88 1.13 11 KD 2 274 788 9.63 27.72 9.77 1.06 11 KD 3 227 672 16.61 49.17 16.07 1.08 11 KD 4 259 730 7.56 21.32 10.83 1.12 11 KD 5 300 743 1.67 4.14 11.84 1.20 11 KK 1 263 688 7.43 19.46 14.73 1.02 11 KK 2 235 710 6.26 18.91 13.78 1.11 11 KK 3 185 429 6.03 14.00 9.38 1.05 11 KK 4 307 823 13.71 36.75 13.73 1.09 11 KK 5 230 640 . . . 1.13 11 KR 1 255 719 . . . 1.02 11 KR 2 263 674 1.76 4.49 9.32 1.10 11 KR 3 226 687 10.29 31.29 15.45 1.04 11 KR 4 485 1329 5.19 14.22 14.90 1.06 11 KR 5 290 759 4.13 10.81 12.55 1.05 11 VB 1 267 717 4.57 12.25 10.37 1.00 11 VB 2 253 725 13.99 40.00 16.37 1.13 11 VB 3 203 544 1.51 4.05 14.92 1.09 11 VB 4 158 468 3.89 11.52 11.44 1.16 11 VB 5 223 656 . . . 1.13 12 CH 1 314 810 18.64 48.09 7.64 1.06 12 CH 2 226 582 4.95 12.78 3.33 1.10 12 CH 3 276 712 8.72 22.51 3.30 1.03 12 CH 4 213 551 13.87 35.79 8.73 1.21 12 CH 5 172 445 15.46 39.88 10.77 1.17 12 CO 1 253 743 42.07 123.67 11.27 1.16 12 CO 2 228 565 15.76 39.08 7.79 1.20 12 CO 3 476 1255 23.83 62.91 5.35 1.08 12 CO 4 194 544 11.70 32.76 6.88 1.11 12 CO 5 332 850 4.57 11.70 5.29 1.09 12 CO 6 211 566 7.98 21.38 4.69 1.34 12 KD 1 192 457 26.64 63.41 32.36 0.97 12 KD 2 203 475 12.85 30.08 35.99 1.03 12 KD 3 395 973 12.65 31.13 36.90 1.08 12 KD 4 185 451 17.56 42.85 33.90 1.04 12 KD 5 325 767 21.25 50.14 45.77 1.03 12 KK 1 399 1077 5.60 15.12 16.50 1.09 12 KK 2 417 1085 35.27 91.69 10.13 1.08 12 KK 3 506 1376 7.42 20.19 35.02 1.05 12 KK 4 349 852 14.35 35.02 26.22 1.05 12 KK 5 497 1291 . . . 1.14 12 KR 1 286 760 35.24 93.75 72.58 1.37 12 KR 2 313 777 14.22 35.27 38.64 1.03 12 KR 3 271 601 16.97 37.67 35.32 1.04 12 KR 4 442 1220 41.88 115.60 57.86 1.08 12 KR 5 294 811 12.63 34.85 17.87 0.98 12 VB 1 347 816 26.70 62.75 19.83 1.35 12 VB 2 387 847 46.65 102.16 11.53 1.18 12 VB 3 372 822 19.29 42.64 18.38 . 12 VB 4 940 2210 32.99 77.53 9.47 1.04 12 VB 5 501 1137 30.12 68.37 16.69 1.17

86

VITA

Michael Paul Cerchiaro was born to Frank M. Cerchiaro and Mary Jane Watkins on

March 16, 1975, in Pittsburgh, Pennsylvania. He lived in Pittsburgh from 1975 to 1984;

Bradenton, Florida, from 1984 to 1989; Charleston, West Virginia, from 1989 to 1993;

and Blacksburg, Virginia, from 1993 to 2001. He attended and graduated from

Charleston Catholic High School in 1993. From there he moved to Blacksburg, Virginia,

where he attended Virginia Polytechnic Institute and State University. He graduated in

1998 with a Bachelor of Science degree in Forest Management. Following his

undergraduate work, he then completed a Master of Science Degree in Forest Soils and

Silviculture at Virginia Tech.