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Effect of phosphorus fertilization on the microbial phosphorus pool in a spodosol under a slash pine plantation

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Effect of phosphorus fertilization on the microbial phosphorus pool in a spodosol under a slash pine plantation
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Bliss, Christine Marie
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Fertilization ( jstor )
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Microbial biomass ( jstor )
Oxalates ( jstor )
Phosphorus ( jstor )
Soil horizons ( jstor )
Soil science ( jstor )
Soil water ( jstor )
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Water tables ( jstor )
Dissertations, Academic -- Soil and Water Science -- UF ( lcsh )
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Thesis (Ph.D.)--University of Florida, 2003.
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Includes bibliographical references.
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Vita.
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by Christine Marie Bliss.

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THE EFFECT OF PHOSPHORUS FERTILIZATION ON THE MICROBIAL
PHOSPHORUS POOL IN A SPODOSOL UNDER A SLASH PINE PLANTATION















By

CHRISTINE MARIE BLISS


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA


2003















ACKNOWLEDGMENTS

I would first and foremost like to acknowledge and thank my major advisor, Dr.

Nick Comerford. His support, dedication, patience, and wisdom helped me to improve

both my professional and personal potential. He offered encouragement, advice, and

belief in my abilities that helped me to achieve my goals. I would also like to

acknowledge my committee members, Drs. E.J. Jokela, R.M. Muchovej, K.R. Reddy, and

R.D. Rhue. I greatly appreciate their help and suggestions for improving my research.

I will always be grateful for all the help I received from Mary Mcleod. Her

knowledge, support, and friendship motivated me through frustrating times in the

laboratory. Miranda Lucas was an invaluable asset to my research. I cannot thank her

enough for all of the help and support she provided me. I would also like to thank Nick

Comerford for his help in the laboratory. Adam Glassman and Marinela Capanu very

generously provided me with statistical help.

I would like to thank my family, especially my parents, for the endless

encouragement and support. Lastly, I would like to thank my friends. I cannot thank

them enough for their support, encouragement, and patience. I am most thankful to Dr.

Traci Ness and Jennifer Koski for listening and offering invaluable advice.















TABLE OF CONTENTS
Page

ACKNOW LEDGMENTS................... .............. ......... ..................

LIST OF TABLES ...................... .......................... ......- v

LIST OF FIGURES.............................. ................................... vii

ABSTRA CT .......................... .... .. .................... ......................ix

CHAPTER

1 INTRODUCTION ........................... ..... .... .. ........... 1

2 DETERMINATION OF MICROBIAL PHOSPHORUS Kp FACTORS:
INFLUENCE OF HORIZON AND WATER POTENTIAL................................ 9

Introduction .................................... ....................... 9
M methods ....... ......................... ....................... 12
Study Area and Field Sampling ....... ................ ....... .. ................... 12
Growth and Culture of Microbes .................... ... ................ ...... 12
K, Determination .............. ........... .........................14
Extractants .. ...................... ................... .................................... 15
Evaluation of Water Potential and Soil Characteristics on the Kp Method.... 16
Statistical A analysis ................... ........ ................... 16
R results ............................ ....... .. ...... ......... ............. 17
Soil Characterization................... ............. ................ ... 17
Recovery of P Spike .................................................... ...................... 17
Kp Factors by Extractant ................................................. 17
K, Factors by W ater Potential................................... ........................... 19
Kp Factors by Horizon................................ ................. ............ 20
Comparison of Inorganic P vs. Total P Kp Factors .................................... 20
Evaluation of Water Potential and Soil Characteristics on the Kp Method.... 20
Comparison of K, Factors with the Literature Kp Factor........................... 21
Regression Equations.............................. ..... ... .... .... ............ 21
D discussion ..................................... .. .............. ....................... 2 1
Objective 1: The Most Efficient Extractant............................ ........... 21
Objective 2: Effect of Water Potential on K, Factors................................ 23
Objective 3: Influence of Horizon on Kp Factors..................................... 26
Conclusion ................................. ...... ................... ....................... 28









3 SEQUESTERING OF PHOSPHORUS FERTILIZER IN MICROBIAL BIOMASS
OF A COASTAL PLAIN SPODOSOL ....................................... 45

Introduction ............................................................................ 45
M methods ................................................................................................ 46
Study Area and Field Sam pling ....................................... ....................... 46
Statistical A analysis ................................ ............... ................................ 48
Results and Discussion................................ ........ .................................. 49
Objective 1: Investigate the Influence of P Bioavailabilty on the Microbial
Biom ass ......................................... ...................... 49
Objective 2: Estimate the Immobilization and Retention of P Fertilizer by the
Soil M icrobial Biom ass ............................................ 51
Objective 3: Investigate How Soil Water Potential Affects Microbial Uptake
and P Fertilizer Retention....................... .............. 56
C conclusion ......................................... .................. ..................... 58

4 SUMMARY AND CONCLUSIONS.............................................................. 72

Objective 1: Determine the Superior Extractant for the Determination of Kp Factors
and Estimating Microbial Phosphorus on Acidic Spodosols of the
Coastal Plain.................................. .............................................. 73
Objective 2: Determine of K, Changes with Water Potential and Soil Horizon
Characteristics ........................................... ............................. 73
Objective 3: Determine of Microbial Biomass and Microbial Phosphorus Respond
to Phosphorus Fertilizer and How Those Responses Develop Over
Tim e........................................................ ............................ 74
Objective 4: Determine if Differing Water Potentials Affects Immobilization and
Retention of Phosphorus Fertilizer.................. ...... ............. 75
Research Conclusions......................................................... ............... ...... 75
Future R research ................................................ .... .......... ...................... 78

APENDIX A: K, FACTOR FIGURES............................................ ..................... 79

APPENDIX B: ANALYSIS OF VARIANCE TABLES........................ .............. 97

APPENDIX C: FERTILIZATION STUDY FIGURES....................... ...................... 124

LIST OF REFERENCES .............................................................. ............. 144

BIOGRAPHICAL SKETCH ............................................................. 154















LIST OF TABLES


Table page

2-1. Soil characterization for each horizon ..................... ........... ................... 29

2-2. Percent recovery of P, added as a spike................................... ......................29

2-3. Comparison of inorganic Kp factors by extractant within each water potential and by
water potential within each extractant in the A, E, and Bh horizons. ................... 30

2-4. Comparison of total Kp factors by extractant within each water potential and by
water potential within each extractant for the A and Bh horizons ......................... 32

2-5. Comparison of inorganic Kp factors by horizon within each water potential for each
extractant ....................................................... ..................................... 3 5

2-6. Comparison of total Kp factors by horizon within each water potential for each
extractant ................................................................................. ...................... 37

2-7. Significant differences (P<0.05) between the inorganic P and total P
Kp factors for the A and Bh horizons......................... ................... 38

2-8. Inorganic Kp factors measured in the "test" horizons.............................................. 39

2-9. Comparison of microbial P concentrations with determined inorganic Kp factors from
0.5 MNaHCO3 and aKp factor of 0.40 ..................... ............ ............ ... 40

2-10. Regression equations for inorganic Kp factors for each extractant and horizon...... 41

3-1. Comparison of microbial C by treatment within each day and by day within each
treatment for each water potential ................................................... 59

3-2. Comparison of microbial C between the control, 100 kg P ha-1, and DAP fertilizer
treatments within each day for each water potential......................................62

3-3. Comparison of microbial P by P fertilizer treatment within each day and by day
within each P fertilizer treatment for each water potential....................................... 63

3-4. Percent of P fertilizer immobilized and retained on day 77 by the microbial biomass...........66

3-5. Comparison of microbial P between the control, 100 kg P ha ', and DAP fertilizer
treatments within each day for each water potential .....................................67






vi





3-6. Comparison of microbial C:P ratios...................... ............................................ 68

3-7. Comparison of microbial P by water potential within each day for each treatment
............................................................................................. ....................... ......................... 6 9

3-8. Comparison of microbial C by water potential within each day for each treatment
...................................................... .... ................................... ................................ .............. 7 1

B-1. Analysis of variance table for inorganic Kp factors........................ .....................97

B-2. Analysis of variance table for microbial P from the P-only fertilizer treatments.....101

B-3. Analysis of variance table for microbial P from all fertilizer treatments, including
D A P ..................... ................................................................ ...... .......... 107

B-4. Analysis of variance for microbial C from all P-only fertilizer treatments............... 114

B-5. Analysis of variance table for microbial C from all fertilizer treatments, including
D A P ...................................................................................... ........................... ........... 119















LIST OF FIGURES


Figure page

1-1. Phosphorus cycle ........................................................ ........................................... 8

2-1. Inorganic K, factors by extractant within each water potential in the A horizon...... 31

2-2. Total Kp factors by extractant within each water potential in the A horizon............. 33

2-3. Inorganic Kp factors by water potential within each extractant for the A horizon .... 34

2-4. Inorganic Kp factors for the A, E, and Bh horizon within each water potential using 3
m M oxalate ........................................ ..................................... .................... 36

2-5. Inorganic Kp regression curves for the A, E, and Bh horizon.................................. 42

3-1. Solution inorganic P in the control at each water potential................................... 60

3-2. Microbial C for each day in the -3 kPa soil at each P fertilizer treatment ............... 61

3-3. Microbial P by P fertilizer treatments over time in the -0.1 kPa soil.................... 64

3-4. Microbial P over time for each water potential in the 30 kg P ha-' treatment........... 65

3-5. Microbial P by water potential in the control ......................... ............. .......... 70

A-1. Inorganic Kp factors by extractant within each water potential ............................. 79

A-2. Total K, factors by extractant within each water potential .................................. 81

A-3. Inorganic Kp factors by water potential within each extractant ............................ 82

A-4. Total K, factors by water potential within each extactant ..................................... 84

A-5. Inorganic Kp factors by horizon within each water potential................................ 85

A-6. Regression curves for inorganic K, factors in the A horizon.................................. 88

A-7. Regression curves for inorganic K, factors in the E horizon.............................. .... 91

A-8. Regression curves for inorganic Kp factors in the Bh horizon................................ 94









C-1. Microbial C by day at each P fertilizer treatment ....................................... 124

C-2. Microbial P by P fertilizer treatment for each day................... ................... 128

C-3. Microbial P by water potential for each day .............................. .................... 131

C-4. Microbial P by water potential in each P fertilizer treatment .............................. 133

C-5. Microbial C by water potential for each day......................................... 136

C-6. Microbial C by water potential for each treatment ...................... .................... 138

C-7. Microbial P by day for each P fertilizer treatment............................................ 141














Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

EFFECTS OF PHOSPHORUS FERTILIZATION ON THE MICROBIAL
PHOSPHORUS POOL IN A SPODOSOL UNDER A SLASH PINE PLANTATION

By

Christine Marie Bliss

August 2003

Chair: Dr. N.B. Comerford
Major Department: Soil and Water Science Department

The microbial biomass is significant in nutrient cycling and nutrient bioavailability.

The acidic, sandy soils in the southeastern U.S. are phosphorus (P) limited for forest

production and commonly fertilized with P. The surface horizon has no P retention

capacity, resulting in possible leaching of P fertilizer, so the microbial biomass may be a

significant sink and source of labile P for plant uptake in these soils. The ability of the

microbial biomass to immobilize and retain P fertilizer before it is leached below

seedling rooting depth would determine how important it might be as a source of

bioavailable P. Spodosols in the southeastern U.S. have a fluctuating water table that

influences the water potential of the surface horizon. Microbial communities are linked

to water potential and so may influence microbial immobilization of P fertilizer. An

accurate estimate of microbial P is dependent upon a correct Kp factor that may also be

affected by water potential.








The extractant, 0.5 MNaHCO3 (pH 8.5), used to measure microbial P was

questioned for use on these acidic soils. K, factors were measured using six extractants,

0.5 MNaHCO3, Mehlich 1, Bray and Kurtz, and 1 mM, 2 mM, and 3 mMoxalate, at five

water potentials ranging from -0.1 to -1000 kPa in the A, E, and Bh horizons. The

superior extractant for estimating microbial P in this soil was determined to be 3 mM

oxalate. Kp factors were determined to change with soil horizon and soil water potential.

Five treatments, control, 30, 60, and 100 kg P ha', and a DAP treatment, were

added to the A horizon at five water potentials. Microbial P and microbial biomass were

measured over time until 77 days after fertilizer addition. The microbial biomass in this

soil is not P limited but is N limited. After fertilization, up to three or more times the P

than the annual demand by pine plantations was sequestered and held for several weeks.

Water potential did not affect P immobilization. Microbial P would become slowly

available to plants over time, possibly after fertilizer is leached from the rooting zone.














CHAPTER 1
INTRODUCTION



Soil microbial biomass has been defined as the soil's living component (Sparling,

1985) and consists mainly of bacteria and fungi. It holds approximately 2-3 percent of

the total soil organic carbon. The microbial biomass has been shown to be a factor in

nutrient cycling and soil fertility (Cosgrove, 1977; Smith and Paul, 1991) by controlling

mineralization and immobilization. Soil microorganisms are both an important sink and

source of available essential nutrients (Jenkinson and Ladd, 1981; Tate and Salcedo,

1988). The size and turnover of the microbial biomass influence the supply of labile

nutrients to plants (Anderson and Domsch, 1980). Since the microbial biomass relies on

organic matter as an energy source, it has been proposed as an indicator of soil organic

matter change (Anderson and Domsch, 1989; Insam et al., 1989; Wolters and Joergensen,

1991; Sparling, 1992) and soil fertility status (Marumoto, 1984; Hassink et al., 1991).

The phosphorus (P) content of the microbial biomass can be a significant

component of bioavailable P. Microbial P reportedly varies from 6 to 106 jig P g- soil

(Brookes et al., 1984; Diaz-Ravifia et al., 1995; Joergensen et al., 1995). Microbial

biomass uptake ofP may be three to five times greater than plant uptake in semiarid

grasslands (Cole et al., 1977) and the flux of P through the microbial biomass may also

be three to five times greater than the quantity removed by annual harvesting of crops

(Chen and He, 2002).









The P cycle (Figure 1-1) is influenced by biological, chemical, and physical soil

properties. The original source of P in the soil is primary minerals, such as the various

forms of apatite. Through weathering, soluble P is released and made available to plant

or microbial uptake, leaching, or sorbed onto secondary minerals (Smeck, 1985).

Equilibrium is maintained between labile P and soluble P, with rapid exchange between

the pools (Olsen and Khasawneh, 1980). Removal of soluble P is buffered by the labile P

pool, but as both are depleted, these pools are replenished by both primary and secondary

P and mineralization of organic P (Po) (Smeck, 1985).

Secondary minerals, as sources of P, include minerals with P chemisorbed to the

surface, such as iron (Fe) and aluminum (Al) oxides and carbonates, and minerals derived

by crystallization at low temperatures with P as a structural component, such as variscite,

strengite, brushite, monetite, and Al, Fe, and calcium (Ca) phosphates (Smeck, 1985).

Secondary minerals may also physically occlude P when they form. Occluded P may

occur as Fe oxides, hematite, and goethite. Secondary minerals slowly release P into the

soil solution (Olsen and Khasawneh, 1980) and seldom achieve equilibrium with the

labile P pool (Murrmann and Peech, 1969; Olsen and Khasawneh, 1980) due to the

constant flux ofP in the soil (Olsen and Khasawneh, 1980). However, the long-term

tendency of P is to form secondary minerals (Smeck, 1985).

In soils with little or no ability to sorb P, the microbial biomass must be the

controlling factor in P cycling. The biota is decomposed into organic matter with various

forms of Po through microbial synthesis (Smeck, 1985). Microbial synthesis is believed

to be the origin of Po (Cosgrove, 1977; Anderson, 1980). Organic P in soil exists mainly

as ester linkages to inositols with small quantities of nucleic acids and phospholipids









(Stewart and McKercher, 1982). Some Po is transferred into a stable Po pool, which is

slow to hydrolyze. The small quantities of nucleic acids and phh...ph,-.ipid.. jr I,.

hydrolyzed into soluble and labile forms while the inositols tend to accumulate (Halstead

and McKercher, 1975). Transformation of Po occurs through plant uptake of soluble P,

some of which returns to the soil in plant litter with decomposition and accumulation of

Po, and microbial mineralization and return to soluble P pool.

Phosphorus mineralization is controlled by inorganic P (Pi) availability and P

demand by microorganisms and plants (Stewart and Tiessen, 1987; Walbridge, 1991).

When the labile P, pool is high, Po mineralization is repressed causing Po to accumulate

(Spiers and McGill, 1979; Smeck, 1985). Equilibrium occurs between Po and non-

occluded Pi (Williams and Walker, 1969). Unlike nitrogen (N) and carbon (C),

mineralization of Po may occur independently from C and is therefore labeled

biochemical mineralization (McGill and Cole, 1981). Phosphorus mineralization is

catalyzed by the enzyme, phosphohydrolase, which may be produced by plant roots,

mycorrhizae, or soil microbes (Gould et al., 1979; Smeck, 1985). Phosphohydrolase is

repressed when labile P, is high, causing the soil C:P ratio to decrease due to the

accumulation of Po (Smeck, 1985). This occurs when the C:P ratio is generally less than

100, but if the ratio exceeds 200, then phosphohydrolase is induced (Smeck, 1985).

The microbial community structure is affected by several factors, including soil

water potential (Sheilds et al., 1973; Diaz-Ravina et al., 1993). Seasonal community

structure changes have been linked to water potential (Smit et al, 2001) as have both

microbial C and microbial P contents (McLaughlin et al., 1988; Ross, 1987; Srivastava,

1992; Ghoshal and Singh, 1995). In addition of community structure, microbial activity









has historically been associated with soil water potential with changes in activity

decreasing with both excessive and deficient water conditions (Wilson and Griffin, 1975;

Orchard and Cook, 1983; Ross, 1987; Skopp et al., 1990).

Phosphorus fertilization, along with weed control, is a common management

practice in souther pine plantations due to P limiting forest production on Spodosols in

the Coastal Plain of the southeastern United States (Colbert et al., 1990). The sandy

surface horizons have a limited P retention capacity (Humphreys and Pritchett, 1971;

Ballard and Fiskell, 1974; Fox et al., 1990a; Harris et al., 1996; Zhou et al., 1997) which

allows for P mobility. Therefore, if sufficient rainfall events occur, P fertilizer not

absorbed by plants or microorganisms may be leached below the A horizon (Harris et al.,

1996; Nair et al., 1999). Since the surface horizon has a low P retention and the

associated understory vegetation is removed or reduced, the question is whether the

microbial population would be a significant sink for P fertilizer.

Earlier methods for determining microbial P employed C:P ratios to estimate

microbial P from microbial C (Anderson and Domsch, 1980; Chauhan et al., 1981).

Subsequently, microbial P was measured by a fumigation method developed by Hedley

and Stewart (1982) which was adapted from microbial C methodology and revised by

others (Brookes et al., 1982; McLaughlin et al., 1986; Walbridge and Vitousek, 1987;

Walbridge, 1991).

Hedley and Stewart (1982) measured microbial P by incubating air-dried soil at pH

7.4, removing Pi from the soil with an anion-exchange resin after which liquid

chloroform was added and the soil extracted with 0.5 MNaHCO3 (8.5 pH) following

chloroform evaporation. The authors calibrated their method by measuring a Kp factor









(the fraction of P recovered from the microbial biomass) using commonly found soil

bacteria and fungi and reported that the Kp factor was 0.37.

Brookes et al. (1982) tried to improve this method by using fresh soil, pH 5.6 to 7.3

and a correction for sorption of P. The authors used chloroform vapor and extracted the

samples with 0.5 M NaHCO3 (8.5 pH) along with fresh samples that had been incubated

for the same length of time as the samples under chloroform. Kp factors were measured

by spiking soils with several different common soil microorganisms and adding a spike

of P to another set of samples in order to determine the amount of P adsorbed by the soil.

Brookes et al. (1982) concluded the Kp factor to be 0.40, similar to that determined by

Hedley and Stewart (1982).

McLaughlin et al. (1986) used native microorganisms grown from their study soil,

pH 6.0 to 8.5, to derive Kp factors based on microbial assemblages more closely

associated with their study soils. The authors tested several lysing agents and extractants

and determined that using hexanol and 0.5 MNaHCO3 was best for their system. The Kp

factors ranged from 0.33 to 0.57, and like Hedley and Stewart (1982), Brookes et al.

(1982) and McLaughlin et al. (1986) concluded that Kp can differ according to soil type.

Walbridge and Vitousek (1987) developed yet another method for measuring

microbial P on a soil at pH 3.7. The authors used a different extractant, dilute acid-

fluoride (Bray and Kurtz extractant), which is widely used as an index ofP availability in

acid soils. Walbridge (1991) followed this same procedure on soils with a pH ranging

from 3.7 to 3.9. The author used labeled 32P043 to measure Kp factors and the recovery

of the inorganic spike by incubating the soil with the labeled P for 4 days to allow for









microbial immobilization and adsorption. Walbridge's research indicated that K, factors

ranged from 0.37 to 0.46.

Due to the limited P retention of the surface soils in the southeastern U.S. and the

potential for P fertilizer to leach quickly below the range of seedling root depth, the

microbial P pool may be a significant source of labile P in the surface horizon. If the

microbial biomass were able to immobilize P within hours, as was determined in

laboratory studies by Walbridge and Vitousek (1987), then the microbial biomass would

be able to immobilize a portion of the P fertilizer before it is leached. How long the

microbial biomass is able to retain immobilized P fertilizer and whether increasing the

level of P fertilizer also increases the level of microbial P and microbial C in these soils

was questioned. How different water potentials affect the uptake and retention of P

fertilizer is an additional concern due to the water table fluctuating significantly in

Flatwood soils. An accurate estimate of microbial P is dependent on measuring an

appropriate Kp factor. Microbial populations are sensitive to changes in water potential.

Therefore, one might suspect that Kp factors also are a function of water potential. The

use of the extractant, 0.5 MNaHCO3, also needs to be further questioned for acidic soils

as was done by Waldbridge and Vitousek (1987) and Waldbridge (1991).

Given the above discussion, the objectives of this study were to: 1) determine if

0.5 MNaHCO3 (pH 8.5) is a suitable extractant for microbial P on acidic Spodosols of

the Coastal Plain with the initial hypothesis that 0.5 MNaHCO3 is not a suitable

extractant for microbial P on acidic soils in Spodosols; 2) determine ifKp factors change

with water potential and soil horizon characteristics with the hypothesis that Kp factors do

not change with water potential and that Kp is a constant; 3) determine if microbial






7


biomass and microbial P increase with P fertilization, testing the hypothesis that

microbial C and microbial P increase with fertilizer addition; and 4) determine if water

potential affects immobilization and retention of P fertilizer, addressing the hypothesis

that water potential does not affect P fertilizer immobilization and retention.

Chapter 2 describes the testing of the basic standard microbial P extractant against

several acidic extractants. K,p factors were developed for the A, E, and Bh horizons at

five water potentials for each extractant (Objectives 1 and 2). Chapter 3 describes the

response of microbial biomass and microbial P response to P fertilizer over time at

differing water potentials (Objectives 3 and 4). Chapter 4 is a summary and discussion of

this dissertation and also includes relevant topics for future research.















Plants Plant
residues


\ \


Biological
Transformations



Pedologic
Transformations


Occluded P


Figure 1-1. Phosphorus cycle. Dashed arrows indicate microbial mediated processes.














CHAPTER 2
DETERMINATION OF MICROBIAL PHOSPHORUS Kp FACTORS: INFLUENCE
OF WATER POTENTIAL AND SOIL HORIZON

Introduction

Microbial biomass, which is composed of bacteria, fungi, and other microbiota, is

a major controlling component of nutrient transformations and cycling in soils.

Phosphorus (P) transformation and cycling through the microbial biomass have been

recently studied (Seeling and Zasoski, 1993; Gijsman et al., 1997; He et al., 1997b;

Grierson et al., 1998) under a variety of soil conditions. Brookes et al. (1984) estimated

that the P held in the microbial biomass ranges from 5 to 106 u.g P g' soil. Subsequent

studies fall within this estimated range of microbial P (Diaz-Ravifia et al., 1995;

Joergensen et al., 1995).

In the Coastal Plain of the southeastern U.S., P limits forest production on

Spodosols (Colbert et al., 1990). The sandy nature of the surface horizons limits P

retention capacity (Humphreys and Pritchett, 1971; Ballard and Fiskell, 1974; Fox et al.,

1990a; Harris et al., 1996; Zhou et al., 1997), resulting in P mobility. Therefore, P that is

not absorbed by plants or microorganisms may be leached below the A horizon (Harris et

al., 1996; Nair et al., 1999). Due to the low native bioavailability of P in these

Spodosols, P fertilization is commonly applied in combination with weed control during

a pine plantation's rotation. Since the surface horizon has a low P retention and the

associated understory vegetation is removed or reduced, the microbial population could

be a significant sink for P fertilizer.









Microbial P estimates, as defined by Brookes et al. (1982), Hedley and Stewart

( i" i and McLaughlin et al. (1986), are based on extracting soil with 0.5 MNaHCO3 at

pH 8.5. McLaughlin et al. (1986) investigated both basic and acidic soil extracting

solutions and concluded that 0.5 MNaHCO3 at pH 8.5 removed the most P from the

microbial biomass. It is important to note that the pH of the soils they tested was 6.0 and

higher. However, forested soils in the southeastern Coastal Plain are acidic, with the pH

often ranging between 3.8 to 4.5. Inorganic P (P,) chemistry is dominated by aluminum

oxides where present, such as in the spodic and argillic horizons. The appropriateness of

using a high pH extractant under these conditions is therefore questionable for this type

of soil. Other extractants, such as low molecular weight organic acids that promote

ligand exchange and aluminum oxide dissolution (Fox et al., 1990b; Lan et al., 1995), are

known to better remove P from acidic soils and may recover more P when measuring

microbial P.

The fumigation-extraction method underestimates microbial P due to the

incomplete release of P from the microbial cells during fumigation and due to subsequent

adsorption of the released Pi onto the mineral soil surface (Brookes et al., 1982; Hedley

and Stewart, 1982; McLaughlin et al., 1986). A correction factor, Kp, is used to

accurately estimate the total quantity of P held in the microbial biomass (Brookes et al.,

1982; Hedley and Stewart, 1982; McLaughlin et al., 1986). Kp factors may vary with soil

condition, due to either changes in microbial communities or sorption of P (Brookes et

al., 1982; Hedley and Stewart, 1982; McLaughlin et al., 1986). Brookes et al. (1982)

determined that inorganic Kp (Kp,) factors ranged from 0.32 to 0.38 and total Kp (K,,)

factors ranged from 0.44 to 0.49, while Hedley and Stewart (1982) reported a similar









range of 0.32 to 0.47 for Kp, factors. Brookes et al. (1982) and Hedley and Stewart

(1982) concluded that a Kof 0.40 provided a good estimate for soils with a basic pH, but

suggested that K, factors may vary with soil conditions.

Many studies have used 0.40 as the correction factor in microbial P estimation

(Perrott et al., 1990; Tate et al., 1991; Clarholm, 1993; Gijsman et al., 1997; Lukito et al.,

1998). McLaughlin et al. (1986) determined that Kp factors ranged from 0.33 to 0.57 for

a range of soils and suggested that Kp factors must be calibrated for each soil because of

different microbial populations present in each environment. Since microbial

communities also vary with soil water potential (Wilson and Griffin, 1975; Lund and

Goksoyr, 1980; Orchard and Cook, 1983; Skopp et al., 1990), it seems reasonable to

suggest that K, factors may also vary with this soil variable.

This study's overall purpose was to examine the fumigation-extraction method for

measuring microbial P in acidic, forested, sandy soils. There were three specific

objectives. The first objective was to determine which extractant was most efficient at

removing microbial P by comparing the standard basic extractant, 0.5 MNaHCO3 at pH

8.5, against several acidic and oxalate extractants with the hypothesis that 0.5 MNaHCO3

is not the most efficient extractant. Since soil water potential controls microbial

communities and population levels, the second objective was to evaluate whether the K,

factor was influenced by the soil water potential. The null hypothesis was that K, factors

are not affected by water potential. The third objective was to test whether the K, factor

differed by soil horizon within a profile of a representative Flatwoods Spodosol. The

hypothesis for the third objective was that Kp factors do not differ by soil horizon.









Methods

Study Area and Field Sampling

The study area was located 33 km northeast of Gainesville, FL. The site was a 16

ha managed slash pine plantation (Pinus elliottii var. Elliottii Engelm.) that was clearcut

in April 1994, bedded in September and November 1994, and planted with slash pine

seedlings in January 1995. In February 1995, 85 g ha-1 ofimazypyr was applied as

Arsenal in 1.5 m wide bands down the beds for weed control. The plantation is underlain

by a sandy, siliceous, thermic Ultic Alaquod, which is primarily Pomona fine sand and

sand. The average annual temperature is 21 C, and the long-term average annual rainfall

is approximately 1330 mm (Soil Conservation Service, 1995). Table 2-1 provides

chemical and physical characteristics of the A, E, and Bh soil horizons.

Soil was sampled in July 1996 from a subsection of the study area, approximately

2 ha. Approximately 10 kg of soil from each horizon was collected from 20 random

points with a 7.5 cm diameter soil auger. The samples were combined to form one

combined sample for each horizon. The soil was sieved to pass a 2 mm screen and air-

dried.

Growth and Culture of Microbes

Five water potentials were selected to represent a dry soil (-1000 kPa), near field

capacity (-15 kPa and -8 kPa), an unsaturated condition that represents a high water table

(-3 kPa), and near saturation (-0.1 kPa). These water potentials were based on results

from P mineralization studies that evaluated mineralization rate versus soil water

potential in a similar soil (Grierson et al., 1999).

In order to culture native microbial populations representative of the different water

potentials, soil samples from each horizon were incubated at each water potential for a









minimum of 10 days at 28 C. Water potential was kept constant throughout the

incubation period by weighing the samples and adding double deionized water when

required. The soil sample was then diluted with double deionized water to a soil to

solution ratio of 1:10 and 1:1000 for fungal and bacterial growth, respectively. The

native fungal populations were grown by adding 1 ml of the 1:10 dilution to a growth

medium containing 660 mg NaNO3, 330 mg KH2PO4, 265 mg KC1, 165 mg MgSO4

7H20, 6.6 mg FeSO4, 165 mg yeast extract, 10 g sucrose, 100 mg streptomycin sulphate,

and 5 mg tetracycline hydrochloride in one L of double deionized water (McLaughlin et

al., 1986). Native bacterial populations were grown by adding 1 ml of the 1:1000

solution to a 0.3 percent typic soy broth in double deionized water containing 100 mg

cycloheximide L-' (McLaughlin et al., 1986). The microbes were grown in the dark at 28

C for approximately 7 days. The fungal population was filtered from the nutrient

solution, rinsed in double deionized water, blotted dry, and subsampled before adding

back into soil samples for determination of Kp factors. Bacterial populations were grown

at the same temperature and time length as fungal populations. The bacterial suspension

was centrifuged, rinsed with double deionized water, and resuspended in double

deionized water before addition back into soil samples.

Total P (Pt) was measured in the fungal and bacterial populations following a

modified method of Smethurst and Comerford (1993). A known amount of sample

(approximately 300 mg of fungi and 5 mL of bacterial suspension) was dried in a muffle

furnace at 104 C overnight. The samples were then ashed at 500 C for 4 hours. When

cool, 7 mL of 40 percent HCI were added to samples and evaporated to dryness on a hot

plate. Five mL of concentrated HCI were added and again evaporated until dry. Ten mL









of 0.1 N HCI were added to samples and allowed to stand overnight. A known quantity

of the sample in 0.1 N HCI, depending upon the P concentration, was diluted to 25 mL

and analyzed for P using the Murphy and Riley (1962).

Kp Determination

Approximately 80 mg of the fungi and 1 ml of the bacterial suspension were

added to soil samples at the same water potential and horizon from which the

microorganisms were grown. The samples were then fumigated with 2 mL of liquid

chloroform for 24 hours. The chloroform was allowed to evaporate, and the soil was

extracted for P. The Kp factor, or percentage recovery of microbial P, was calculated by

using the equation:

Kp =(m-n)/(xy) (2-1)

from Brookes et al. (1982), where m is the amount of P, measured in the samples that

contained the added microbial biomass, n is the amount of Pi measured in fumigated

samples without additional microbes added, x is the percent recovery of Pi determined

from a P spike, and y is the amount of Pt in the microbial biomass added to the sample.

This equation is the same when measuring Kp factors for microbial Pt, except that m

becomes the amount of P, measured in the samples with added microbes and n becomes

the P, measured in sample without the added microbes. Total P was determined by

digestion of extractant as described above.

In order to determine the percent recovery of Pi for the variable x above, a range of

P, concentrations from 40 to 100 gg P g' soil were added to a set of soil samples in the

Bh horizon. This range was used because of the variable P contained in the added

microbes and to determine if P adsorption was linear. Although P adsorption was









assumed to be negligible in the A and E horizons (Harris et al., 1996; Zhou et al., 1997),

a spike of 40 ig P g' soil was added. This concentration of P was used because added P

in the microbes was generally 40 pg P g-' soil. Phosphorus recovery is presented in

Table 2-2. Inorganic P was used as the spike for both Kp, and K,, on account of most P

released from the microbial cells is P, (Brookes et al., 1982) and sorption of P, and Po was

assumed to be similar.

Extractants

The following solutions were used to extract P from the soil samples: 0.5 M

NaHCO3 at pH 8.5 (Olsen et al., 1954), 0.03N NH4F and 0.25 NHCI (Bray and Kurtz,

1945), 0.05 N HCI and 0.025 N H2SO4, or Mehlich 1, (Nelson etal., 1953), and 1mM, 2

mM, and 3 mMoxalate at pH 3.2, 2.9, and 2.7, respectively. The Bray and Kurtz

extractant has been used in acidic soils as an index of P availability. It removes easily

acid-soluble forms of P from calcium phosphates and a portion of aluminum and iron

phosphates (Bray and Kurtz, 1945). Mehlich 1 was used as another measure of P

availability in acidic soils because of its ability to dissolve aluminum and iron phosphates

(Nelson et al., 1953). Oxalate is a naturally occurring, low molecular weight organic acid

whose presence in the soil solution is due to microbial activity and root exudation.

Oxalate increases P solubility through formation of stable complexes with aluminum

(Martell et al., 1988) in solution, ligand exchange (Stumm, 1986; Fox et al., 1990a), and

dissolution of metal-oxide surfaces (Stumm, 1986).

The NaHCO3 extract was used with a 1:10 soil to solution ratio and shaken for one

hour (Grierson et al., 1998). A 1:7 soil to solution ratio with a 1 minute shaking time and

a 1:4 soil to solution ratio with a 5 minute shaking time was used for the Bray and Kurtz









extract and Mehlich I, respectively (Olsen and Sommers, 1982). A 1:10 soil to solution

ratio and 10 minute shaking time was used with the oxalate solutions. Ten minute

shaking time was determined with initial studies to be the shaking time that extracted the

most P from the soil sample.

After extraction and filtration, Pi was measured using the Murphy and Riley (1962)

method. When required, filtered samples were treated with HCI to lower the pH for

analysis by this method. The NaHCO3 samples had to be refiltered after adding the acid

because acidification caused precipitation of organic compounds. Total P was also

measured for each sample as described previously.

Evaluation of Water Potential and Soil Characteristics on the Kp Method

Bacterial and fungal populations were grown from each horizon at -8 kPa using

the same methods described above. These microbial populations were then added into

soil samples maintained at each of the five different water potentials. Microbes were also

added into soil samples from the other horizons maintained at -8 kPa. For instance,

microbes grown from the A horizon at -8 kPa were added to soil samples from the A

horizon at each water potential and into the E horizon and Bh horizon at -8 kPa. Samples

were then extracted with 3 mM oxalate and analyzed for P,.

Statistical Analysis

Significant differences were determined using SAS, version 8.01 (SAS Institute,

Inc 2001) using a mixed ANOVA model. The least-squared means were analyzed for

significant differences, (P<0.05). Kp factors were analyzed within the main effects

(horizon, extractant, and water potential) and between main effects. Regression

equations for Kp, factors within each water potential, extract, and horizon were developed

using Statistica, 1999 edition (StatSoft Inc., 1999).









Results

Soil Characterization

Soil characteristics varied by horizon (Table 2-1). Organic carbon (C) was

significantly different by horizon, with the most organic C in the Bh and the least in the E

horizon. The greatest concentration of sand was in the E horizon, and the most silt and

clay was in the Bh horizon. Aluminum concentration was highest in the Bh horizon.

Recovery of P Spike

In the Bh horizon, more P was recovered with the 2 mM oxalate, 3 mM oxalate, and

Mehlich 1 extractants (Table 2-1). Between 80 to 89, 82 to 86, and 79 to 90 percent were

recovered in 2 mM oxalate, 3 mMoxalate, and Mehlich 1, respectively. Less P was

recovered with 1 mM oxalate and even less with NaHCO3. Only approximately 50

percent of the P spike were recovered when NaHCO3 was used. In the A and E horizons,

3 mM oxalate recovered all of the P spike while NaHCO3 recovered 94 and 90 percent in

the A and E horizon, respectively. The Bray and Kurtz extractant and Mehlich 1

recovered 96 and 95 and 96 and 94 percent in the A and E horizons, respectively.

K, Factors by Extractant

Inorganic Kp factors ranged from 0.14 to 0.72 in the A horizon, 0.19 to 0.99 in the

E horizon, and 0.11 to 0.45 in the Bh horizon (Table 2-3; Appendix A, Figure A-1). The

K,, factors for each extractant within each water potential were compared by horizon.

The A horizon provides an example of the differences in extraction efficiency (Figure 2-

1). The low concentrations of oxalate provided similar K,, factors to the standard

extractant, 0.5 MNaHCO3 (pH 8.5), in all three horizons. However, within the different

concentrations of oxalate, 3 mM oxalate had a tendency to be more efficient in removing

Pi that was attributable to the microbial biomass. The Bray and Kurtz extractant









removed less P, from the microbial biomass, but it was not always significantly lower

than the oxalate concentrations or 0.5 MNaHCO3. Mehlich 1 consistently extracted less

P than all other extractants. It extracted significantly less P, than both oxalate and 0.5 M

NaHCO3 but was not always significantly lower than Bray and Kurtz.

In the E horizon, the solutions extracted similarly to the A horizon. The oxalate

concentrations extracted similar quantities of P from the microbial biomass as 0.5 M

NaHCO3. Less P, was extracted when using Bray and Kurtz, but it was not always

significantly less than the oxalate concentrations or 0.5 MNaHCO3. Mehlich 1 again

consistently extracted the least quantity of P,. It was significantly lower than both oxalate

and 0.5 MNaHCO3 but not always significantly different from Bray and Kurtz.

Within the Bh horizon, the solutions did not extract P similarly as in the A and E

horizons. Sodium bicarbonate was similar to 2 mM and 3 mM oxalate, but the lowest

concentration of oxalate was clearly less able to extract P. The extraction efficiency of 3

mMoxalate was clearly shown in the Bh horizon, in which the different oxalate

concentrations displayed increasing P extraction with increasing concentration. The

Mehlich 1 solution extracted the least P, from the microbial biomass, but it was not

significantly lower than the other extractants in all cases.

Total Kp factors ranged from 0.22 to 0.97 in the A horizon and 0.10 to 0.89 in the

Bh horizon (Table 2-4; Appendix A, Figure A-2). There was not sufficient sample to

evaluate K,, for the E horizon. As with the Kp,, the K,, factors showed similar trends. In

the A horizon, the K,, factors for the three oxalate concentrations were mostly similar to

0.5 MNaHCO3, with Bray and Kurtz and Mehlich 1 extracting less Pt from the microbial









biomass (Figure 2-2). The Bh horizon provided similar trends. However, 2 mMoxalate

was able to remove more P, from the added microbes overall.

K, Factors by Water Potential

When comparing K,, factors by water potential within extractants (Table 2-3;

Appendix A, Figure A-3), the most Pi was extracted from the microbial biomass when the

soil was near saturation (-0.1 kPa). The A horizon provides an example of the

differences in P extracted from the microbial biomass between the different water

potentials within each extractant (Figure 2-3). Soil at saturation had the significantly

highest K,, factor or was similar to the highest K,, factor for the majority of comparisons.

In the A and E horizons, soil with the water potential closest to field capacity (-8 kPa)

yielded the least quantity of P from the microbial biomass. The K,, factors had a trend of

decreasing as the soil became drier but then increasing after -8 kPa with drier soil in both

the A and E horizons. In the Bh horizon, the lowest K,, occurred in soil at -3 kPa, after

which the K,, increased.

When comparing the amount of P, extracted (Table 2-4; Appendix A, Figure A-4),

the Kp,, factors followed the same trend as the K,, factors with more P extracted in soil at

saturated and dry conditions and least when the soil was at an optimum water potential,

near field capacity. Again, more P was extracted from the microorganisms in the

saturated soil with a decrease in extractability with decreasing water potential.

Extractable P increased again in the drier soils. In the A horizon, the least P was

extracted from the microbial biomass in soil at -8 kPa whereas in the Bh horizon, the

least P was extracted from microbes at -3 kPa.









K, Factors by Soil Horizon

When comparing the K,, factors by horizon, the highest K,, factors tended to be in

the E horizon (Table 2-5; Appendix A, Figure A-5). The A horizon also provided high

Kp, factors, while the Bh horizon usually had the lowest values. An example is provided

comparing the horizons using 3 mM oxalate (Figure 2-4). When comparing horizons

within each extractant, the E horizon provided the highest Kpi factor for all extractants

except for the Mehlich 1 extract; however the value was not always statistically higher.

The K,, factors were significantly higher for the A horizon (Table 2-6). This occurred for

all extractants except Mehlich 1, in which no significant differences were obtained.

Comparison of Inorganic P vs. Total P Kp factors

Significant differences were detected between the inorganic P and total P Kp

factors (Table 2-7). Approximately one half of the K,, factors were significantly different

from the K,, factors. Sodium bicarbonate and 2 mM and 3 mM oxalate concentrations

were significantly different the majority of the time. Bray and Kurtz and Mehlich 1 had

the least differences. When comparing the differences between water potentials, -15 kPa

in the A horizon, and -1000 kPa in the Bh horizon had the most significant differences,

but there did not seem to be a trend across the water potentials that was the same for each

horizon.

Evaluation of Water Potential and Soil Characteristics on the Kp Method

When comparing the Kp, factors measured within the original horizon, there was

no significant difference when microbes from one water potential were added to other

water potentials (Table 2-8). This result was consistent in all three horizons. But when

comparing the Kpi factors measured when the microbes were added to different horizons,

significant differences were determined. When testing microbes from the A horizon in









the E horizon and microbes from the E horizon into the A horizon, there were no

significant differences. Significant differences were detected when A and E microbes

were added into the Bh horizon and when Bh microbes were added into the E horizon.

Comparison of Kp Factors with the Literature Kp Factor

Since the K,, factors measured were determined to be significantly different by soil

water potential and horizon, the differences in microbial P were calculated using the

commonly used literature value of 0.40 (Brookes et al., 1982; Hedley and Stewart, 1982)

and the current study's values (Table 2-9). Assuming a Kp factor from the literature

resulted in estimates of microbial P that were 0 to 160% different from the estimates

using Kp values from this study.

Regression Equations

Regression equations were developed for the Kp, factors for each extractant and

horizon (Table 2-10; Appendix A, Figure 2-6). The R2 values ranged from 0.02 to 0.95.

One regression equation was applicable to 0.5 MNaHCO3, but with oxalate, there were

two distinct curves, one for the -0.1 to -8 kPa soils, or the "wet to moist" soil, and

another for the -8 to -1000 kPa soils, or the "moist to dry" soil (Figure 2-5). This

occurred in all horizons except the Bh horizon with 3 mM oxalate. The Bray and Kurtz

and Mehlich 1 extractants varied with horizon. Many of the equations in the wet to moist

soils had less variability than those for the moist to dry soil. Regression equations for the

Kp, factors were not developed due to the lack of data.

Discussion

Objective 1: The Most Efficient Extractant

There are two main factors that define an efficient extractant for removing P from

the microbial biomass. The extractant should consistently recover the highest percentage









of P from the microbial biomass and should not produce interference with colorimetric P

measurement. In Spodosols, sorption is not a factor in either the A or E horizons due to

the acidic, sandy nature of these soils. Therefore, in these surface soils, extraction should

only involve P released from the microbial biomass. The Bh horizon has the ability to

sorb released microbial P. Due to this sorption capacity, the extractant must have the

ability to re-extract this sorbed microbial P for measurement. Interference with

colorimetric procedures caused increased labor by increasing procedure steps and

diminishing accuracy and precision.

When comparing the ability and suitability of extracts for removing P, from the

microbial biomass, oxalate performed more consistently than the other extractants,

including NaHCO3. In Spodosols of the southeastern U.S., the Bh horizon is dominated

by amorphous Al-oxides (Ballard and Fiskell, 1974; Lee et al., 1988). Oxalate has an

effect on both P and Al release from the Bh horizon because of its ability to replace P

through ligand exchange and dissolution of Al-oxide surfaces (Fox and Comerford,

1992). The A horizon in this soil has little Al (Fox and Comerford, 1992) beyond what is

found on the meager cation exchange capacity, and the Pi in this horizon was nearly all

water soluble (Fox et al., 1990a). Under these conditions, oxalate and NaHCO3 would

extract similar amounts of P,. As shown in the recovery of the P spike in the A and E

horizon, a high percentage was recovered with all extractants, but 3 mM oxalate

recovered all of the spike. In acidic soils, HC03 ions replace P absorbed on the soil

surface (Olsen et al., 1954), but the high pH of NaHCO3 also dissolves some organic

compounds. The dissolution of organic matter results in precipitates when the sample is









acidified for the measurement of P, by the method of Murphy and Riley (1962).

Therefore extra filtration is required.

The Bray and Kurtz extractant was developed to remove acid-soluble forms of P,

mostly calcium phosphates, and some Al and Fe phosphates (Bray and Kurtz, 1945).

While it is a commonly used extractant for P on acidic soils, it did not perform well with

extraction of microbial P. Mehlich 1 uses the same concept of the Bray and Kurtz

extract, with the release of P from Fe phosphates due to the action of acids (Nelson et al.,

1953). Although Mehlich 1 recovered a high percentage of the P spike in the Bh

horizon, it did not perform well in extraction of P from the microbial cells.

For this type of soil, due to the better extraction of P from the microbial biomass

and the ease of analysis, oxalate is recommended. Of the oxalate concentrations tested, 3

mM oxalate was chosen due to its ability to recover more Pi and the ease of use when

compared with NaHCO3. As with Kp,, 2 mM oxalate and 3 mM oxalate were not

significantly different the majority of the time with respect to extraction of P, from the

microbial biomass. Two mM oxalate was determined to be the superior extractant, but

this may be due to missing values, especially in the Bh horizon, from 3 mM oxalate.

Objective 2: Effect of Water Potential on Kp Factors

The Kp equation, equation 2-1, cancels background P associated with the soil and

with the native microorganisms. Existing microbial P in the soil samples is subtracted

from the Kp equation through (m n). Both m and n are fumigated, which eliminates

existing microbial P and also native soil P, providing the quantity of P that is extracted

from the added microbial fungal and bacterial populations. Variable x, the percentage of

P recovery, corrects for any P that may be sorbed by the soil. Therefore, the Kp equation









calculates the fraction of P that is extracted from a microbial population with a known P

concentration.

Soil moisture content is a critical factor affecting microbial activity. Microbial

populations have been shown to increase activity with increasing water potential (Wilson

and Griffin, 1975; Orchard and Cook, 1983). Changes in fungal and bacterial ratios with

water content (Anderson and Domsch, 1975; Wilson and Griffin, 1975; Faegri et al.,

1977) suggest that dominant microbial assemblages change with water contents. Diaz-

Ravifa et al. (1995) determined that differences in nutrient concentrations in the

microbial biomass are significantly related to soil characteristics, including soil moisture.

Soil moisture content has also been shown to affect microbial community diversity

(Brockman et al., 1992). Furthermore, Sparling and West (1989) have already suggested

that the extractability of P from the microbial biomass is a function of soil water content.

When comparing our NaHCO3 study results with other studies (Brookes et al.,

1982; McLaughlin et al., 1986), Kp, factors for the A horizon were consistent with the

published range (0.36 to 0.42) when the soil was -3 kPa or drier. When the soil was near

saturation, Kp, increased to 0.61. This is in contrast to studies that determined the

microbial Kc factor (the fraction of microbial C that decomposes into C02-C in 10 days)

decreased with increasing water content (Ross, 1987; Wardle and Parkinson, 1990).

Wardle and Parkinson (1990) also suggested that water content significantly influenced

K, factors.

Since the methodology used cancels all background factors, there are only two

other factors affecting Kp. Those factors are microbial community changes and water

potential influence on P extraction from the microbial biomass. In order to test the effect









of water potential on the extraction of P, microbes grown at a specific water potential

were added to the same soil at different water potentials. The only factor changing was

water potential because the added microbial population was the same in each sample.

Therefore, the extraction procedure was not being affected by water potential. This

provides evidence that the extraction of P from the microbial biomass is not affected by

water potential as suggested by Sparling and West (1989). Therefore, the only other

factor changing was the microbial community.

Microbial communities have been documented to change with season (Smit et al.,

2001), temperature (Dalias et al., 2001), pH and substrate (Yan et al., 2000), and water

potential (Nazih et al., 2001; Marschner et al., 2002; Treves et al., 2003). Since water

potential has been shown to affect the diversity of microbial communities, it seems

reasonable to assume that this diversity may be influencing the Kp factors measured at

different water potentials.

Brookes et al. (1982) and Hedley and Stewart (1982) measured the Kp factor of

individual microbial species and determined that different species of microorganisms had

different Kp factors. Several studies have determined that Kc factors are also dependent

upon the diversity of organism assemblages (Jenkinson, 1976; Anderson and Domsch,

1978; Nicolardot et al., 1984). Thus, it seems reasonable to conclude that K, factors in

this study differed with water potential because of changes in microbial communities

caused by the change in water potential.

Although regression equations were created, use of these equations to predict Kp

factors should be restricted to soil very similar to this study. As discussed, differences in

soil properties such as organic C cause changes in microbial diversity, which in turn may









cause differences in K, factors. The percentage of variability in these equations indicated

the equations fit the data for many cases. However, with some equations, the predicted

values did not fit observed data, especially in the drier soils. For example, in the E

horizon, the predicted values provided Kp, factors well above 1, which is not possible.

This is most likely due to the design of the experiment that was set up for contrasting

different water potential, not for regressing Kp against water potential. The large gap

between -15 kPa and -1000 kPa does not provide a well-balanced regression curve.

Objective 3: Influence of Soil Horizon on Kp Factors

Microbial population diversity should also occur in different horizons within a soil

profile. Nutrient concentrations, water regime, quantity of and type of organic carbon as

a food source, soil texture, and possibly pH change with horizon. Both organic C and the

water regime in the three soil horizons are considerably different. Organic C, which was

discussed previously, is significantly different by horizon. Organic C is leached from the

A horizon, through the E horizon, and collects in the Bh horizon. Organic C provides

needed energy for microorganisms while also creating community diversity.

Permeability is rapid in the surface horizons (A and E horizons), but the subsurface

horizons have low permeability. In an average year, the shallow water table may be less

than 25 cm from the soil surface for one to three months, between 25 and 100 cm for six

months, and exceeding 100 cm during the dry season (Soil Conservation Service, 1985).

Soil water potential was found to be different between the A horizon and the lower

horizons with the lower horizons being similar when the water table was approximately

96 cm below the soil surface (Phillips, 1987). As mentioned previously, microbial

communities are affected by water potential (Diaz-Ravifia et al., 1995). Because the









horizons have different water regimes, it seems reasonable that microbial diversity may

also change with horizon due to the difference in water potential.

Microbial activity (Bauhus et al., 1998) and microbial community composition

(Sessitsch et al., 2001) also differ with soil texture. When comparing this study's A

horizon K,, factors using NaHCO3 with the K,, factors in similar textured soils by

Brookes et al. (1982) and McLaughlin et al. (1986), the K,, factors were similar; 0.39

(this study at -8 kPa), 0.32 (Brookes et al., 1982), and 0.33 (McLaughlin et al., 1986).

McLaughlin et al. (1986) measured Kp factors on three sites with different soil textures,

finding that K, differed by site. These data support the premise of McLaughlin et al.

(1986) by providing additional examples that soil texture does play a role in microbial

diversity.

Changes in the soil pH cause changes in the microbial community structure

(Frostegard et al., 1993; Degens et al., 2001; Yan et al., 2000) that affect microbial Kc

factors (Vance et al., 1987). Consequently, pH should also affect Kp factors since both

are determined by soil microorganisms. Another factor affecting microbial diversity

may be the diversity of plant roots. Differences in the compounds exuded by plant roots

result in microbial community diversity (Grayston and Campbell, 1996).

As discussed previously, microbial diversity has been linked to the value of

correction factors used in calculating microbial C. This study has shown that soil

physical and chemical properties influence the value of microbial Kp factors, which in

turn appear linked to changes in the microbial community. For example, the P removed

by from the microbial population by extractants was more easily removed from the E









horizon than the A and Bh horizons. Based on the above discussion, this suggests that

the microbial community in the E horizon more easily releases P following fumigation.

This study has clearly shown that K, factors are a function of soil water potential

and soil characteristics and should not be generalized for different soils. Since Kp is

clearly influenced by soil characteristics, using literature values for a K, factor will cause

a significant error, as much as 62, 145, and 48 percent in the A, E, and Bh horizons,

respectively, when using NaHCO3 as an extractant, in microbial P estimates.

Conclusion

A revised extraction method was more useful for measuring microbial P in acidic

sandy horizons with spodic horizons. For the soil used in these studies, oxalate was

determined to extract more or similar amounts of P from the microbial biomass as the

standard 0.5 MNaHCO3 Using 0.5 MNaHCO3 is still appropriate but difficult to apply

to spodic horizons due to the analytical interference. Therefore, it was concluded that

oxalate was a more efficient extractant for Spodosols. Kp factors were determined to be a

function of water potential and other soil characteristics due to the changes in microbial

diversity. It was concluded that a standard Kp for many soil conditions is not appropriate

and may cause significant errors of microbial P. A Kp factor should be assessed for each

soil condition to get the best estimate of microbial P.









Table 2-1. Soil characterization for each horizon
--. -----%- ...------ -------------------cmolc/kg--------------
Horizon pH Sand Silt Clay Organic C Al Fe Ca K Mg Na
A 4.1 94 5 1 0.69 (b)a 0.15 0.01 0.14 0.33 0.27 0.01
E 4.0 96 3 1 0.16(c) 0.00 0.01 0.04 0.12 0.16 0.01
Bh 4.3 90 8 2 1.23 (a) 2.24 0.02 0.04 0.17 0.28 0.03
aSignificant differences (P<0.05) between horizons within organic C




Table 2-2. Percent recovery of P, added as a spike to soil samples for each extractant
------------------% recovery of P added-------------
8.5 M 1 mM 2mM 3 mM Bray &
Horizon NaHCO3 Oxalate Oxalate Oxalate Kurtz Mehlich 1
Bh 40 pg g' soil 50 63 82 85 NDa 79
Bh 60 Lg g- soil 52 61 84 82 ND 83
Bh 80 .g g-' soil 52 72 89 82 ND 82
Bh 100 pg g-' soil 48 75 80 86 ND 90
Bh average 50 68 84 84 ND 83
A 40 plg g-' soil 94 95 97 100 96 96
E 40 pg g' soil 90 96 97 100 95 94
aND data not determined









Table 2-3. Comparison of inorganic Kp factors by extractant within each water potential
and by water potential within each extractant in the A, E, and Bh horizons
------------------------------Water Potential----------------------
-0.1 kPa -3 kPa -8 kPa -15 kPa -1000 kPa
Extractant A horizon
0.5 MNaHCO3 0.65 (Aaab) 0.42 (BCb) 0.35 (Ab) 0.45 (Ab) 0.38 (Bb)
1 mMoxalate 0.72 (Aa) 0.53 (ABb) 0.30 (ABc) 0.41 (Abc) 0.51 (ABb)
2 mM oxalate 0.71 (Aa) 0.47 (Bbc) 0.28 (ABc) 0.48 (Ab) 0.60 (Aab)
3 mMoxalate 0.67 (Aa) 0.65 (Aa) 0.31 (ABc) 0.49 (Ab) 0.56 (Aab)
Bray & Kurtz 0.39 (Bb) 0.29 (CDc) 0.34 (Abc) 0.51 (Aa) 0.28 (BCc)
Mehlich 1 0.22 (Ca) 0.21 (Da) 0.19 (Bab) 0.18 (Bb) 0.14 (Cb)

E horizon
0.5 MNaHCO3 0.99 (Aa) 0.75 (Bb) 0.60 (Ac) 0.73 (Abc) 0.73 (ABbc)
1 mMoxalate 0.66 (Bb) 0.95 (Aa) 0.53 (Ab) 0.70 (Aab) 0.71 (ABab)
2 mMoxalate 0.85 (ABab) 0.90 (Aa) 0.58 (Ac) 0.68 (Abc) 0.86 (Aab)
3 mMoxalate 0.74 (Bab) 0.91 (Aa) 0.48 (Ac) 0.64 (Abc) 0.83 (Aa)
Bray & Kurtz 0.79 (Ba) 0.55 (Cb) 0.30 (Bc) 0.42 (Bbc) 0.59 (Bb)
Mehlich 1 0.43 (Ca) 0.35 (Dab) 0.19 (Bc) 0.28 (Bbc) 0.28 (Cbc)

Bh Horizon
0.5 MNaHCO3 0.36 (ABb) 0.27 (Ab) 0.33 (Ab) NA' 0.72 (Aa)
1 mMoxalate 0.15 (Ca) 0.13 (Ba) 0.17 (Ba) NA 0.13 (Ca)
2 mMoxalate 0.25 (BCa) 0.17 (Bc) 0.23 (ABa) NA 0.18 (BCbc)
3 mMoxalate 0.45 (Aa) 0.28 (Ab) 0.30 (Aab) NA 0.22 (Bb)
Bray & Kurtz NDd ND ND ND ND
Mehlich 1 0.16 (Cab) 0.11 (Bb) 0.14 (Bb) NA 0.21 (BCa)
aSignificant differences (P<0.05) between extractants within each water potential and
horizon (upper case letters down columns)
bSignificant differences (P<0.05) between water potentials within each extractant and
horizon (lower case letters across rows)
'NA missing data
dND data not determined




















S0.5 MNaHCO3
1.0 [ 1 mMoxalate

S2 mMoxalate
0.8 3 mMoxalate

S0.6- Bray & Kurtz
S l i Mehlich I
0.4




0.0
-0.1 -3 -8 -15 -1000
Water potential (kPa)


Figure 2-1. Inorganic Kp factors by extractant within each water potential in the A
horizon









Table 2-4. Comparison of total K, factors by extractant within each water potential and
by water potential within each extractant for the A and Bh horizons. K,
factors were not determined for the E horizon.

--------- ---------Water Potential---- ---------
-0.1 kPa -3kPa -8 kPa -15 kPa -1000 kPa
Extractant A horizon
0.5MNaHCO3 0.91 (Aaab) 0.74 (Aab) 0.63 (Abc) 0.53 (Bc) NAc
1 mMoxalate NA 0.59 (Ba) 0.38 (Bbc) NA 0.51 (Bab)
2 mM oxalate 0.97 (Aa) 0.76 (Aab) 0.44 (Bb) 0.60 (Bb) 0.82 (Aab)
3 mMoxalate 0.74 (Ba) 0.77 (Aa) 0.43 (Bc) 0.59 (Bb) NA
Bray & Kurtz 0.41 (Cb) 0.34 (Cb) 0.38 (Bb) 0.86 (Aa) 0.44 (BCb)
Mehlich 1 0.22 (Da) 0.23 (Ca) 0.22 (Ca) 0.29 (Ca) 0.26 (Ca)

Bh horizon
0.5 MNaHCO3 0.43 (Ab) 0.55 (Ab) 0.40 (Ab) NA 0.78 (Ba)
1 mMoxalate 0.23 (Ba) 0.17 (Ca) 0.23 (Ba) NA 0.21 (Ca)
2 mMoxalate 0.55 (Ab) 0.33 (Bc) 0.43 (Abc) NA 0.89 (Aa)
3 mM oxalate 0.46 (Aa) NA NA NA 0.39 (Cab)
Mehlich I NA 0.16 (Cb) 0.17 (Bb) NA 0.33 (Ca)
aSignificant differences (P<0.05) between extractants within each water potential and
horizon (upper case letters down columns)
bSignificant differences (P<0.05) between water potentials within each extractant and
horizon (lower case letters across rows)
cNA missing data




















S0.5 MNaHCO3
1.2 H 1 mMoxalate
2 mMoxalate
1.0
13 mM oxalate
0.8 T Bray & Kurtz

I 0.6 Mehlich 1

0.4

0.2

0.0
-0.1 -3 -8 -15 -1000
Water Potential (kPa)


Figure 2-2. Total Kp factors by extractant within each water potential in the A horizon























-0.1 kPa

0.8 -3 kPa
-. -8 kPa

0.6 -15 kPa


0.4


0.2
0I -1000 kPa








NaHCO3 Oxl Ox2 Ox3 BK Mehlich I















Figure 2-3. Inorganic Kp factors by water potential within each extractant for the A
horizon. NaHCO3 = 0.5 MNaHCO3, Ox1 = 1 mMoxalate, 0x2 = 2 mM
oxalate, 0x3 = 3 mM oxalate, and BK = Bray and Kurtz










Table 2-5. Comparison of inorganic K, factors by horizon within each water potential for
each extractant

---------------Water potential -----------
-0.1 kPa -3kPa -8 kPa -15 kPa -1000 kPa
Horizon 0.5 MNaHCO3
A 0.65 (ba) 0.42 (b) 0.35 (b) 0.45 (b) 0.38 (b)
E 0.99 (a) 0.75 (a) 0.60 (a) 0.73 (a) 0.73 (a)
Bh 0.36 (c) 0.27 (c) 0.33 (b) NAb 0.72 (a)

1 mM oxalate
A 0.72 (a) 0.53 (b) 0.30(b) 0.41 (b) 0.51 (a)
E 0.66 (a) 0.95 (a) 0.53 (a) 0.70 (a) 0.71 (a)
Bh 0.15 (b) 0.13 (c) 0.17 (b) NA 0.13 (b)

2 mM oxalate
A 0.71 (a) 0.47 (b) 0.28 (b) 0.48 (b) 0.60 (b)
E 0.85 (a) 0.90 (a) 0.58 (a) 0.68 (a) 0.86 (a)
Bh 0.25 (b) 0.17 (c) 0.23 (b) NA 0.18 (c)

3 mM oxalate
A 0.67 (a) 0.65 (b) 0.31 (b) 0.49 (a) 0.56(b)
E 0.74 (a) 0.91 (a) 0.48 (a) 0.64 (a) 0.83 (a)
Bh 0.45 (b) 0.28 (c) 0.30 (b) NA 0.22 (c)

Bray and Kurtz
A 0.39 (b) 0.29 (b) 0.34 (a) 0.51 (a) 0.28 (b)
E 0.79 (a) 0.55 (a) 0.30 (b) 0.42 (b) 0.59 (a)
Bh NDC ND ND ND ND

Mehlich 1
A 0.22(b) 0.21 (b) 0.34(a) 0.18(b) 0.14(b)
E 0.43 (a) 0.35 (a) 0.30 (a) 0.28 (a) 0.28 (a)
Bh 0.16 (b) 0.11 (c) 0.14 (b) NA 0.21 (ab)
aSignificant differences (P<0.05) between horizons within each water potential and
extractant
bNA missing data
'ND data not determined


























0.8 -0 A horizon

[ M E horizon
S0.6 -
S6 Bhhorizon

0.4


0.2


0.0
-0.1 -3 -8 -15 -1000
Water potential (kPa)


Figure 2-4. Inorganic Kp factors for the A, E, and Bh horizons within each water potential
using 3 mM oxalate as an extractant











Table 2-6. Comparison of total Kp factors by horizon within each water potential for each
extractant


--------------Water potential---- -----
-0.1 kPa -3kPa -8 kPa -15 kPa -1000 kPa
Horizon 0.5 MNaHCO3
A 0.91 (aa) 0.74 (a) 0.63 (a) 0.53 (a) NAb
Bh 0.43 (b) 0.55 (b) 0.40 (b) NA 0.78

1 mM oxalate
A NA 0.59 (a) 0.38 (a) NA 0.51 (a)
Bh 0.23 0.17(b) 0.17(b) NA 0.21 (b)

2 mM oxalate
A 0.97 (a) 0.76 (a) 0.44 (a) 0.60 0.82 (a)
Bh 0.55 (b) 0.33 (b) 0.33 (a) NA 0.89 (a)

3 mM oxalate
A 0.74 (a) 0.77 (a) 0.43 (a) 0.59 NA
Bh 0.45 (b) 0.26 (b) 0.10(b) NA 0.39

Bray & Kurtz
A 0.41 0.34 0.38 0.86 0.44
Bh NDc ND ND ND ND

Mehlich I
A 0.22 0.23 (a) 0.22 (a) 0.29 0.26 (a)
Bh NA 0.16(a) 0.17(a) NA 0.33 (a)


aSignificant differences (P<0.05) between horizons within each water potential and
extractant
'NA missing data
'ND data not determined






38


Table 2-7. Significant differences (P<0.05) between the inorganic P and total P Kp factors
for the A and Bh horizons by extractant and water potential. Significant
differences indicated by an "*".
----------------- Water potential-------
-0.1 kPa -3 kPa -8 kPa -15 kPa -1000 kPa
Extract A horizon
0.5MNaHCO3 *
1 mM oxalate *
2 mM oxalate *
3 mM oxalate *
Bray & Kurtz *
Mehlich I *

Bh horizon
0.5 MNaHCO3 NDa
1 mM oxalate ND *
2 mM oxalate ND *
3 mM oxalate ND
Mehlich I ND *
aND not determined









Table 2-8. Inorganic Kp factors measured in the "test" horizons. Microbes were grown from the original horizon, added to the
test horizon, and the Kp factor was measured in the test horizon. For example, microbes were grown from the A horizon at -8
kPa and added to samples in each of the test horizons.


Original "Test" Kp Original "Test" Kp Original "Test" K,
horizon horizon factor horizon horizon factor horizon horizon factor
A (-0.1 kPa) 0.35 E (-0.1 kPa) 0.83 Bh (-0.1 kPa) 0.26
A (-3 kPa) 0.30* E (-3 kPa) 0.92 Bh (-3 kPa) 0.22*
A (-8 kPa) A (-8 kPa) 0.36 E (-8 kPa) E (-8 kPa) 0.94 Bh (-8 kPa) Bh (-8 kPa) 0.28
A (-15 kPa) 0.37 E (-15 kPa) 0.90 Bh (-15 kPa) 0.23
A (-1000 kPa) 0.37 E (-1000 kPa) 0.85 Bh (-1000 kPa) 0.25
E (-8 kPa) 0.42* A (-8 kPa) 0.85 A (-8 kPa) 0.34
Bh (-8 kPa) 0.46* Bh (-8 kPa) 0.65* E (-8 kPa) 0.35*
*inlilri.:nl,. different (P<0.05) from the original horizon value










Table 2-9. Comparison of microbial P concentrations with determined inorganic Kp
factors using 0.5 MNaHCO3 and a Kp factor of 0.40. For comparison purposes, 5 kg P
ha-' of microbial P is used.
-----------.------------------kg P ha ----- -----
A horizon
% Over % Under
Water potential with measured Kp, with K, = 0.40 estimation estimation
-0.1 kPa 8 13 63
-3 kPa 12 13 8
-8 kPa 14 13 -- 7
-15 kPa 11 13 18 --
-1000 kPa 13 13 0 0

E horizon
-0.1 kPa 5 13 160 --
-3 kPa 7 13 86
-8 kPa 8 13 63
-15 kPa 7 13 86
-1000 kPa 7 13 86

Bh horizon
-0.1 kPa 14 13 -- 7
-3 kPa 19 13 -- 32
-8 kPa 15 13 -- 7
-15 kPa NAa 13 --
-1000 kPa 7 13 86 --








Table 2-10. Regression equations for inorganic K, factors for each extractant and horizon
Extractant R2 Regression equation
A horizon
0.5 MNaHCO3 0.65 Kp= 0.489 -0.127*log() + 0.038*log(Y)2
1 mMoxalate (W <= -8 kPa) 0.92 K,p = 0.696 0.243*log(y) 0.219*log(W)2
1 mMoxalate ( >= -8 kPa) 0.63 K = 0.346*log(W)359
2 mMoxalate (W <= -8 kPa) 0.85 Kp = 0.681 0.052* (y)
2 mMoxalate ( >= -8 kPa) 0.70 K, =0.370*log(W)0461
3 mMoxalate ( <= -8 kPa) 0.92 Kp= 0.664 -0.008* (Y)2
3 mMoxalate (W >= -8 kPa) 0.64 K,= 0.389*log(Y)034'
Bray & Kurtz ( <= -15 kPa) 0.91 K,= 0.396 0.282*log(w) 0.008*log (W)2
+ 0.283* log(y)3
Bray & Kurtz (y >= -15 kPa) 0.95 K,= 0.667 0.130*log(y)
Mehlich 1 0.55 K,,= 0.198- 0.00005* (W)

E horizon
0.5 MNaHCO3 0.74 K,= 0.788 0.158*log(y) + 0.046*log(Y)2
1 mMoxalate (y <= -8 kPa) 0.85 K,= 1.158 0.131*log(y)- 0.629*log(Y)2
1 mM oxalate (W >= -8 kPa) 0.13 K = 0.520 + 0.60*log(y)
2 mM oxalate (W <= -8 kPa) 0.74 K,= 0.913 -0.037(y)
2 mMoxalate ( >= -8 kPa) 0.86 K = 0.500 + 0.121*log(y)
3 mM oxalate ( <= -8 kPa) 0.87 K, = 1.138 0.190*log(y) 0.592*log(w)2
3 mM oxalate (y >= -8 kPa) 0.78 Kp = -0.287 + 1.059*log(w) 0.228*log(y)2
Bray & Kurtz (W <= -8 kPa) 0.98 K,= 0.735 0.280*log() 0.228*log(Y)2
Bray & Kurtz (y >= -8 kPa) 0.67 K,= 0.224 + 0.125*log(y)
Mehlich 1 (W <= -8 kPa) 0.87 K, = 0.431 0.024(y) 0.228*log(Y)2
Mehlich 1 (W >= -8 kPa) 0.12 Kp = 0.202 + 0.026*log(y)

Bh horizon
0.5 MNaHCO3 0.92 K, = 0.285 0.016*log(w) + 0.053*log(Y)2
1 mMoxalate ( <= -8 kPa) 0.02 K,= 0.105 + 0.016*log(w) + 0.061*log(Y)2
1 mMoxalate (y >= -8 kPa) 0.45 Kp = 0.188 0.019*log(y)
2 mM oxalate ( <= -8 kPa) 0.67 K,= 0.147 + 0.001*log(y) + 0.106*log(y)2
2 mMoxalate ( >= -8 kPa) 0.54 K, = 0.253 -0.22*log(p)
3 mMoxalate 0.64 K, = 0.361 0.056*log(y)
Mehlich 1 0.73 K, = 0.127 -0.017*log(w) + 0.015*log(y)2














K,= 0.489 0.127*log(y) + 0.038*log(y)2
R2 = 0.65


S _

S* -
*
*
*


Log water potential (-kPa)


.-


-- S


K, = 0.664 0.008* (Y)2
R2 = 0.92 I


$


K, = 0.389*log(Y)0 341
R2 = 0.64


Log water potential (-kPa)


Figure 2-5. Inorganic Kp regression equations in the A horizon for a) 0.5 MNaHCO3 and
b) 3 mMoxalate, E horizon for c) 0.5 M NaHCO3 and d) 3 mM oxalate, and
Bh horizon for e) 0.5 MNaHCO3 and f) 3 mMoxalate


0.7

0.6

0.5

0.4

0.3


0.1


0.0














Kp = 0.788 0.158*log(y) + 0.046*log(y)2
R2= 0.74


S. ..
-. < .- 0
*


0.0 -----
0.1 1 10
Log water potential (-kPa)


100


0.0 -


0 \
*
,
0'


Kp =1.138-0.190*log(y) ,
-.592*log(Y)2
R2 = 0.87


*
A K= -0.287+1.059*log(y)
, 0 -0.228*log(Y)2
R2 = 0.78


10
Log water potential (-kPa)


Figure 2-5 continued


S0.6

0.4

0.2











0.9

0.8

0.7

0.6

0.5

0.4

0.3 -
0.2

0.1
0.0


K, = 0.285 0.016*log(y) + 0.053+log(Y)2
R2 = 0.92


1 10
Log water potential (-kPa)


0.9
0.8

0.7

0.6 K = 0.361 -0.056*log(
SR2 = 0.64
0.5

0.4 .

0.3 *- ..

0.2

0.1

0.0 --
0.1 1 10


Wv)


100


Log water potential (-kPa)


Figure 2-5 continued














CHAPTER 3
SEQUESTERING OF PHOSPHORUS FERTILIZER IN THE MICROBIAL BIOMASS
OF A COASTAL PLAIN SPODOSOL

Introduction

Forest productivity in much of the southeastern U.S. is phosphorus (P) limited

(Pritchett and Smith, 1975). The sandy, quartzic, surface horizons of Coastal Plain

Spodosols limit P retention (Zhou et al., 1997; Harris et al., 1996; Fox et al., 1990a),

resulting in P mobility. Therefore, P that is not absorbed by plants or microorganisms

may be leached below the A horizon (Harris et al., 1996; Nair et al., 1998; Nair et al.,

1999) and beyond newly planted seedling root depth. Since soil P bioavailability is

inherently low, P fertilization is a common practice due to the significant growth

response it elicits in southern pines (Pritchett and Smith, 1975; Prichett and Comerford,

1982). Likewise, the application of nitrogen (N) in addition to P has a significant effect

on southern pine growth (Jokela and Stears-Smith, 1993). While root density at time of

planting is low and early uptake rates do not become significant until about three months

after planting (Smethurst et al., 1993), the microbial biomass may have the potential to

sequester P, maintain it in the soil horizon, and eventually make it available over time.

Microbial cycling and associated P transformations have been well studied

(Seeling and Zasoski, 1993; Gijsman et al., 1997; He et al., 1997b; Grierson et al., 1998)

and have been shown to be dependent upon the concentration of P in the soil (Brookes et

al., 1984). It has also been shown that microbial P changes with water potential (Sparling

et al., 1986; Skopp et al., 1990; Grierson et al., 1999), nutrient bioavailability (Clarholm,









1993; He et al., 1997b; Dilly and Nannipieri, 2001) and microbial biomass (Walbridge,

1991).

The purpose of this study was to determine the interaction between P fertilization

and soil water potential in determining microbial biomass and the sequestering of P as

microbial P. More specifically, the first objective was to investigate the influence of P

bioavailability on microbial biomass and to determine whether microbial biomass growth

in a Spodosol of the southeastern U.S. is P limited. The hypothesis was that P is limiting

to soil microbial growth. The second objective was to estimate the immobilization and

retention of P fertilizer by the microbial biomass and test the hypothesis that microbial

biomass could immobilize and retain significant quantities of P fertilizer. The third

objective was to investigate how soil water potential affected microbial uptake and P

fertilizer retention. The hypothesis tested here is two fold. It first states that microbial

biomass at water potentials promoting poor aeration will immobilize less fertilizer P than

those near field capacity. Secondly, it states that microbial biomass at field capacity will

immobilize more fertilizer P than that at drier water potentials (i.e. -1000kPa).

Methods

Study Area and Field Sampling

The study area was located 33 km northeast of Gainesville, FL. The site was a 16

ha managed slash pine plantation (Pinus elliottii var. elliottii Engelm.) that was clearcut

April 1994, bedded in September and November 1994, and replanted to slash pine in

January 1995. In February 1995, 85 g ha' ofimazypyr was applied as Arsenal in 1.5 m

wide bands on the planted beds for weed control. The soil is a sandy, siliceous, thermic

Ultic Alaquod, mapped primarily as Pomona fine sand and sand. The average annual









temperature is 21 OC, and the long-term average annual rainfall is approximately 1330

mm (Soil Conservation Service, 1995).

Soil was randomly collected from the 15 cm thick A horizon across a subsection

(approximately 2 ha) of the study area in July 1996 with a 7.5 cm diameter soil auger.

Approximately 3 kg of soil were collected from randomly selected points from

approximately 20 auger holes. The soil was sieved to pass a 2 mm screen and air-dried.

Sub-samples containing 800 g of soil were incubated in triplicate bags at 28 OC at five

water potential treatments of-0.1, -3, -8, -15, and -1000 kPa for 10 days. Water potential

was kept constant throughout the incubation period by weighing the samples and adding

double deionized water when required. These water potentials were based on results

from P mineralization studies that evaluated mineralization rate versus soil water

potential for a similar soil (Grierson et al., 1999).

Phosphorus fertilizer treatments of 0 kg P ha-', 30 kg P ha', 60 kg P ha1', and 100

kg P ha-' (or 0, 80, 120, and 230 pg P g-' soil) as triple superphosphate granules were

added to each water potential treatment. An additional fertilizer treatment of

diammonium phosphate (DAP) was added to the study, equivalent to 640 tg P and 590

lg N g-' soil. This high fertilizer treatment was added to determine the quantity of P that

could be incorporated when N is not limiting microbial growth. Although carbon may

also be limiting in this system, it was not considered as a factor for this experiment. The

DAP treatment does not reflect a commercial application of fertilizer at this stage of stand

development which would be in the range of 40 to 50 kg P and N ha' (Kidder et al.,

1987).









Triplicate samples from each bag were taken at 0, 3, 7, 14, 28, 49, and 77 days after

fertilizer addition and analyzed for microbial P, microbial C, soil moisture content, and

pH. Moisture content was measured after drying the samples for 24 hours at 105 oC ,

and pH was measured in a 2:1 water:soil solution. Triplicate samples for microbial P

analysis and for microbial C analysis were removed from each treatment bag for

fumigation. Liquid chloroform was added to each sample, sealed for 24 hours, after

which the chloroform was allowed to evaporate. Microbial P was measured with 3 mM

oxalate extraction at a 1:10 soil:solution ratio with a shaking time of 10 minutes (Chapter

2). Microbial C was measured using the ninhydrin-reactive nitrogen method (Amato and

Ladd, 1988). Unfumigated triplicate samples were also taken at the same time as the

fumigated and immediately measured for both microbial P and microbial C. Microbial P,

the quantity of P in the microbial biomass, was defined as:

[P extracted from fumigated soil P extracted from unfumigated soil]/Kp (Eq. 3-1)

by Brookes et al. (1982). The Kp was determined in a previous study and is specific for

each water potential (Chapter 2). Microbial C, the quantity of carbon in the microbial

biomass, was determined by the method from Amato and Ladd (1988) and is defined as:

[ninhydrin-reactive N in fumigated soil ninhydrin-reactive N in unfumigated

soil]*21 (Eq. 3-2)

Statistical Analysis

Statistical differences were determined using SAS version 8.1 (The SAS Institute,

2001) using a three factor mixed ANOVA model. For each sample bag, the least-squared

means were analyzed for significant differences (P<0.05) by repeated measures analysis

of variance with a first order autoregressive covariance structure. Logarithmic

transformations were applied to microbial P and microbial C values in order to normalize









the variance. Microbial P, microbial C, and microbial C:P ratios were analyzed for

significant differences, (P<0.05), within the main effects (water potential, treatment, and

time) and among effects (Appendix B).

Results and Discussion

Objective 1: Investigate the Influence of P Bioavailabilty on the Microbial Biomass

Microbial C ranged from 18 to 302 [lg C g-' soil in the control (no P added) (Table

3-1). This range was similar to other studies reporting microbial C (Chauhan et al., 1981;

Saggar et al., 1998). Extracted labile inorganic P (P,) for the control ranged from 3.9 to

4.8 (-0.1 kPa), 4.5 to 5.5 (-3 kPa), 3.7 to 5.0 (-8 kPa), 0.7 to 2.8 (-15 kPa), and 2.2 to 3.6

(-1000 kPa) gg g-' soil (Figure 3-1). In a study using similar soil and water potentials,

Grierson et al. (1999) reported comparable solution Pi concentrations using KCI as the

extractant. Brookes et al. (1984) reported solution P, ranging from 3.1 to 84.8 .tg P g'

soil in a variety of soils. Some of the highest P, values were reported by Chauhan et al.

(1981) who measured 285 [tg P g-' in an Ap horizon from a sandy loam. Comparatively,

this soil was low in solution P,.

Microbial C was not affected by the P-only fertilizer treatments at any sampling

time when evaluated within a soil water potential, except in the driest soil at the end of

the experiment (Table 3-1; Appendix C, Figure C-1). Soil at -3 kPa provided an example

of the effect of P fertilization on microbial C (Figure 3-2). After a few days, the fertilizer

treatment had significantly affected microbial C, but there was no trend with time as

some days were significantly higher and some significantly lower than the control. The

overall trend of these data indicated that the microbial biomass was not P limited even









though the soil had low labile P, levels. Therefore, the first hypothesis, which stated that

P was limiting microbial growth, was negated.

The microbial population immobilizes phosphorus released through microbial

mineralization and turnover, and little may be available to plants (Tate et al., 1991).

Therefore, in soils with low Pi, like this Spodosol, the microbial biomass may be

immobilizing enough P to sustain its activity but not initially supply P to the pine

regenerating on the site.

Others have also confirmed that microbial C was not P limited on different sites

(Chauhan et al., 1981; Prescott et al., 1992; Bauhus and Khanna, 1994; Joergensen and

Scheu, 1999). Bauhus and Khanna (1984) added 100 kg P ha'- as superphosphate with

no change in microbial C on an acidic, sandy soil with low total P (P,), but the authors

determined that microbial carbon dioxide (C02) release (i.e. microbial activity) increased.

Parfitt et al. (1994) reported that microbial C in another sandy soil was not influenced by

P fertilizer even when it was added at rates up to 100 kg P ha'. Bolan et al. (1996) also

reported that microbial C was not affected by a range of single superphosphate

applications (15-60 kg P ha 1) in laboratory experiments.

However, microbial C increased in the Bolan et al. (1996) 8-year field study due to

increases in soil organic matter, which resulted from increased plant growth promoted by

fertilization. In contrast, Saggar et al. (1998) determined that microbial C decreased after

P-only fertilizer addition. The current study showed a similar response over the first 28

days when the water potential was maintained at -15 kPa. The large increase observed

towards the end of this study within the two driest soils indicated a delayed response to P

only fertilization. Why this occurred is not known; nevertheless the response is too large









to ignore. Because this response was observed in the two dry soil conditions, it would

not seem to be experimental error. A possible explanation is that the increase is due to

slow growing microorganisms.

In contrast to the P-only fertilizer treatments, the DAP treatment increased

microbial C (Table 3-2), presumably in response to the N addition. This increase

continued to be significantly higher than the 100 kg P ha' treatment and the control

throughout the experiment's duration and ranged between a low of a 291% increase (day

3, -1000 kPa) to a high of 36,887% increase (day 49, -8 kPa). Other studies reported that

additions of N increased microbial C when added along with P (Ghosal and Singh, 1995;

Hossain et al., 1995). The rate of DAP was extremely high and meant to give a glimpse

of how high microbial C could be increased. These soils support extremely high levels of

microbial biomass under high nutrient regimes. Microbial biomass, under the right

moisture regime exceeded 3 mg g-' soil (0.3%). While one would not expect to reach

these levels in sandy Spodosols under normal management regimes, they do provide a

sense of what this soil is capable of supporting if used under bio-solid management with

high rates of N and P.

Objective 2: Estimate the Immobilization and Retention of P Fertilizer by the Soil
Microbial Biomass

Microbial response to P fertilization may be different for growth and P uptake,

since P uptake does not require microbial biomass increase. In this study, microbial P

response to P-only fertilization was in fact unrelated to the microbial C response.

Microbial P did respond to treatment.

While microbial P in the control did not change significantly with time, microbial P

increased in response to rates of P addition (Table 3-3; Appendix C, Figure C-2).









Microbial P at -0.1 kPa water potential illustrates this response (Figure 3-3). Microbial P

peaked within one week of P-only fertilizer additions (Appendix C, Figure C-3).

The 30 kg P ha-' treatment peaked on day 3 for all levels of water potential (Figure

3-4). In the higher P-only treatments, microbial P peaked on day 3 in the three wetter

water potentials (-0.01 to -8 kPa) and on day 7 in the two drier water potentials (-15 and

-1000 kPa). After this initial peak, microbial P tended to decrease over time. In the two

wettest soils (-0.1 and -3 kPa), the unfertilized condition continued to be significantly

lower than the fertilizer treatments. In the other water potentials, the control was similar

to either the 30 or 60 kg P ha' treatments after the initial peak. The 100 kg P ha'

treatment, while significantly different from the control, was often similar to the other P

treatments, yet the tendency was for this treatment to have the highest quantity of

microbial P. This may have been due to the high variability, which may have been due to

the use of fertilizer granules instead of ground fertilizer. Many samples had to be

declared missing due to extremely high P concentrations, which was assumed to be due

to fertilizer granule remnants.

A diminishing returns pattern for microbial P was demonstrated as the P addition

rate increased (Table 3-4), suggesting that the microbial biomass in this soil can only

immobilize a limited concentration of P under these conditions. This level was estimated

to be between 27 and 52 mg P kg-' soil or 45 to 86 kg P ha-'. This may also indicate a

limiting factor, such as N or C, limits additional P immobilization. The decrease in

microbial P over time is consistent with the results of Clarholm (1993) and Grierson et al.

(1998) and may reflect the limited microbial P storage in this surface soil when P is non-

limiting.









Other studies have documented microbial P increases with P fertilizer addition

(Chauhan et al., 1981; Haynes and Swift, 1988; Parfitt et al., 1994; He et al., 1997a;

Quails and Richardson, 2000; Schneider et al., 2001). Haynes and Swift (1988) added

500 mg P g-i soil as Ca(H2P04)2 to an acidic silt loam and reported that microbial P

increased to twice the quantity determined in the control and continued at these levels

throughout the experiment. He et al. (1997a) measured microbial P increases of over

three times the magnitude in the control, from approximately 3 to 10 mg P kg" soil, after

adding nearly 400 mg P kg-' soil of carbonate-substituted phosphate rock to an acid loam.

Microbial P was still increasing at the end of their study (60 days). After adding 50 mg

kg-' soil of triple superphosphate (100 kg ha '), Schneider et al. (2001) determined that

microbial P doubled, from 49 to 104 mg P g-i soil, in soils with a 50 percent or higher

adsorption capacity. In this study, microbial P increased from six to 18 times after the

230 mg P kg-' soil (100 kg ha-' of triple superphosphate) was added and was still three to

six times higher than the control at the end of the study. Luxury uptake and retention of

P by microbes has been documented (Fuhs and Chen, 1975; Khoshmanesh et al., 2002).

The microbial biomass in this study also demonstrated the same capability.

In soils with very little or no P sorption capacity, such as this study's soil,

biological control of P leaching may be a factor in retaining P within the root zone

following fertilization and rainfall leaching events. The microbial biomass in the control

immobilized from 3 to 13 kg P ha'1, with the wetter soils containing the lowest quantity

of P. The annual aboveground uptake of a young slash pine plantation is approximately

1.5 kg P ha (Adegbidi et al., in review), and a semi-mature slash pine plantation's

annual aboveground uptake of P is approximately 4 kg P ha-' (Polglase et al., 1992). The









microbial biomass without fertilization holds enough P to supply the P nutrient demands

of a slash pine stand, especially in the drier soils. The quantity of P sequestered would be

sufficient to supply the needs of a pine plantation if it was slowly released over time due

to microbial turnover and if microbial turnover was timed with plant P demand.

One contribution of the microbial biomass may be controlling the loss of P

fertilizer due to leaching. Within a week, the microbial biomass immobilized from 17 to

52 mg P kg-', equivalent to 9 to 29 kg P ha', in soil for a range of water potentials. The

microbial biomass was able to retain more than enough P for a growing pine plantation,

even in the wettest conditions. Even after 77 days, the microbial biomass still held from

2 to 11 kg P ha'-. The percentage of P fertilizer still sequestered on day 77 was 4 to 17

%, 3 to 9 %, and 2 to 9 % of the 30, 60, and 100 kg P ha-' treatments, respectively (Table

3-5). Given these results, the second hypothesis, which stated that microbial biomass

could retain significant amounts of fertilizer P, was confirmed.

Phosphorus mineralization has been reported to increase with fertilization on

similar soils (Polglase et al., 1992; Grierson et al., 1998; Grierson et al., 1999). In these

studies, P mineralization was related to soil organic matter P, not microbial P (Grierson et

al., 1998). However, the P released from the microbial biomass via turnover, and the

increased mineralization due to fertilization, could combine to provide increased P

bioavailability. A significant quantity of this P may be preserved from leaching due to

biomass immobilization.

With the high DAP treatment, microbial P was significantly increased throughout

the study (Table 3-5). DAP elicited a continued increase in microbial P until days 14 to

28, after which it continued to be significantly higher throughout the experimental









duration. Microbial P increased up to 80 mg P kgl equivalent to 44 kg P ha-', at the

highest quantity and still retained 39 to 45 mg P kg ', equivalent to 21 to 25 kg P ha ', at

the end of the study.

The lack of response in microbial C, combined with the significant effect of P in

increasing microbial P, is further supported by the microbial C:P ratios (Table 3-6). As

soon as fertilizer was added, the microbial C:P ratio decreased in all fertilizer treatments

although they were only significantly different for the two wettest soils (-0.1 and -3 kPa).

Lack of significant differences may be due to the high variability of the ratios. The ratios

ranged from 19:1 to 202:1 before fertilizer addition. Immediately after fertilizer addition,

the microbial C:P ratios dropped dramatically, especially in the wetter soils, from 2:1 to

30:1 in the P-only fertilizer treatments and from 13:1 to 59:1 in the DAP treatments. The

ratios in the P-only fertilizer treatments continued to be much lower than the control, due

to the immobilization of P by the microbial biomass without the increase in microbial

population. The significant decrease in the microbial C:P ratios after fertilization

indicates that microbial P may be easily mineralized for increased P cycling (Parfitt et al.,

1994) due to microbial turnover (Cole et al., 1978). The DAP ratios were higher than the

P-only ratios, but that would likely be due to the increase in microbial biomass along with

the immobilization of P.

Although the microbial biomass in the surface horizon of this Spodosol was not P

limited, a significant quantity of P fertilizer was immobilized and sequestered under

laboratory conditions for more than 77 days. Particularly in the absence of understory

vegetation that is characteristically reduced in intensive forest management, microbial

biomass should be further investigated for its ability to sequester and eventually release









P. The pattern of release will determine how useful this is in increasing the efficiency of

P fertilization.

Objective 3: Investigate How Soil Water Potential Affects Microbial Uptake and P
Fertilizer Retention

In the control treatment, microbial P at the -15 kPa water potential was higher than

the other water potentials, while microbial P in the -0.1 kPa soil was usually lower than

the other water potentials (Table 3-7; Figure 3-5). The two drier soils (-15 and -1000

kPa) were significantly higher than the two wettest soils (-0.1 and -3 kPa) at nearly every

sampling date. With decreasing water potential, the microbial community changes from

an aerobic population to a population dominated by anaerobic and facultative

microorganisms. Microbial activity has been reported to be higher in aerobic soils

(Orchard and Cook, 1983; Lee et al., 1990), which may explain the higher microbial P in

the control at -15 kPa.

Prior to P fertilization, microbial P exhibited significant differences due to water

potential. After fertilization, few significant differences were observed. These

differences did not depict a consistent pattern (Appendix C, Figure C-4). It was

consistent that, after P fertilizer addition, microbial P in all water potentials increased

significantly. More P was taken up by the microbial biomass in the soil at -0.1 kPa,

increasing 20 to 32 times, while the drier condition promoted only a four to nine times

increase. Even with such a large increase, microbial P in the saturated water potential was

similar to microbial P in the other water potentials after day 3. These results confirm that

the last two hypotheses are incorrect when stating that microbial immobilization of P is

less in saturated soils and more in drier soils.









The surficial water table in Spodosols fluctuates widely during the year. In an

average year, the shallow water table may be less than 25 cm from the soil surface for

one to three months, between 25 and 100 cm for six months, and exceeding 100 cm

during the dry season (Soil Conservation Service, 1985). Microbial P is significantly

different between water potentials before fertilization; however, microbial P becomes

similar after fertilization due to the greater immobilization of P in the higher water

potentials. The differences in microbial P before and after fertilization may be due to

changes in microbial activity after addition of fertilizer. Therefore, on systems with

fluctuating water tables, the amount of P fertilizer immobilized is dependent upon the

water table depth. When the water table is high, the microbial biomass should

immobilize more P fertilizer. But when the water table is low, and P may be leached

more quickly from the rooting zone due to high permeability, less P fertilizer is

immobilized.

Why microorganisms in the wetter soil with P fertilizer treatments immobilized

more P is not known, but must be due to changes in the microbial community. Soil water

potential has been shown to affect microbial community diversity (Brockman et al.,

1992). As soil water potential changes, so do fungal and bacterial ratios (Faegri et al.,

1977; Anderson and Domsch, 1975; Wilson and Griffin, 1975). Nutrient concentrations

in the microbial biomass are related to soil characteristics, including soil water potential

(Diaz-Ravifia et al., 1995).

There were significant differences between the microbial biomass at different water

potentials, even after fertilization (Table 3-8; Appendix C, Figure C-5). But again, like

microbial P after fertilization, there were no consistent trends. Studies have reported that









the influence of water potential on microbial C is variable, both affecting (Sarathchandra

et al., 1988) and not affecting (Zaman et al., 1999) microbial C. This study used similar

water potentials to those of Grierson et al. (1999) on a similar soil, with similar results.

Conclusion

The microbial biomass was not P limited for growth, even though pine growth on

similar soils is naturally P limited. However, whereas increasing rates of triple

superphosphate did not increase microbial C, immobilization ofP was significant.

Microbial P increased between six and 18 times within three to seven days following

fertilizer additions. In the wetter soils, more P was taken up after fertilization, such that

microbial P was equivalent to the drier soils. Both microbial C and microbial P increased

dramatically when a large quantity of both N and P were added, demonstrating that this

system was N limited and the microbial biomass was capable of increasing significantly

and immobilizing a large quantity of P. Due to the inability of this soil to retain P in the

surface horizon, the microbial biomass would play a significant role in retention and

supply of P to plants through immobilization, along with the combination of

mineralization and microbial turnover. The question is how microbial turnover occurs

over time, and how is subsequent P mobilization timed with plant demand and the

development of an expanding southern pine root system.






Table 3-1. Comparison of microbial C by treatment within each day and by day within each treatment for each water potential
Day 0 Day 3 Day 7 Day 14 Day 28 Day 49 Day 77
-------------------------- -----g C g' soil--------------------------------
Treatment -0.1 kPa
Control 105 (A'b') 184 (Aab) 427 (Aa) 105 (Bb) 213 (Ab) 180 (Aab) 171 (Aab)
30 kg P ha- 161 (Aa) 173 (Aa) 62 (Cb) 180 (Aa) 261 (Aa) 164 (Aa) 175 (ABa)
60 kg P ha" 209 (Aa) 174 (Aa) 172 (ABa) 170 (ABa) 209 (Aa) 179 (Aa) 126 (ABa)
100 kg P ha' 46 (Bc) 162 (Aa) 142 (Ba) 102 (Ba) 426 (Aa) 108 (Ab) 92 (Bbc)

-3 kPa
Control 200 (Aa) 128 (ABab) 302 (Aa) 209 (Aa) 61 (Bbc) 46 (Be) 83 (Abc)
30 kg P ha- 109 (Ab) 90 (Bb) 137 (Aa) 217 (Aa) 67 (Bb) 76 (Bb) 54 (Ab)
60 kg P ha' 129 (Ab) 98 (ABb) 181 (Aab) 258 (Aa) Ill (ABb) 243 (Aab) 62 (Ab)
100 kg P ha-' 198 (Aa) 199 (Aa) 138 (Aa) 183 (Aa) 137 (Aa) 139 (ABa) 64 (Aa)

-8 kPa
Control 122 (Aab) 53 (ABb) 136 (Aa) 32 (Ac) 140 (Aa) 18 (Bc) 75 (Aab)
30 kg P ha-' 87 (ABa) 150 (Aa) 82 (Aa) 18 (Ab) 59 (Ba) 69 (Aa) 71 (Aa)
60 kg P ha' 88 (Aa) 33 (Bbc) 83 (Aa) 80 (Aab) 76 (ABab) 27 (Bc) 29 (Bc)
100 kg P ha' 72 (Bb) 67 (ABb) 116 (Aa) NAC 98 (ABa) 157 (Aa) NA

-15 kPa
Control 245 (Aa) 208 (Aa) NA NA 96 (Ab) NA 250 (ABa)
30 kg P ha-' 231 (Aa) 148 (Aab) 61 (Ab) NA 55 (Ab) NA 156 (Bab)
60 kg P ha' 237 (Aa) 155 (Aa) 112(Bb) NA 113(Ab) NA 217 (Ba)
100 kg P ha' 223 (Aa) 212 (Aa) 100 (ABb) NA 17 (Ab) NA 285 (Aa)

-1000 kPa
Control 112 (Aab) 284 (Aa) 56 (Bb) 171 (Aa) NA NA 77 (Bb)
30 kg P ha' 63 (Bc) 267 (Ab) 183 (Ab) 144 (Ab) 76 (Bbc) NA 682 (Aa)
60 kg P ha-' 113 (Ab) 266 (Aa) 93 (Bb) 109 (Ab) 107 (Ab) NA 475 (Aa)
100 kg P ha-' 66 (ABb) 332 (Aa) 70 (Bb) 95 (Ab) 88 (Bb) NA 533 (Aa)
aSignificant differences (P<0.05) between treatments within each day and water potential (upper case letters down columns)
bSignificant differences (P<0.05) between days within each treatment and water potential (lower case letters across rows)
cNA missing data





















*-0.1 kPa
0 -3 kPa
1-8kPa
0-15 kPa
6 -1000 kPa



S4

B 3

2

n 1

0
0 3 7 14 28 49 77
Days from beginning of study


Figure 3-1. Solution inorganic P in the control at each water potential






















400



0 300
3- day0

0 -a -- -day3
O 200 -- -- --day7
S-- o _.-- --day 14
S--- day 28
S100 ---day 77


0 -
0 20 40 60 80 100

P fertilizer added (kg ha-')


Figure 3-2. Microbial C for each day in the -3 kPa soil at each P fertilizer treatment







Table 3-2. Comparison of microbial C between the control, 100 kg P ha-1, and DAP fertilizer treatments within each day for
each water potential
Day 0 Day 3 Day 7 Day 14 Day 28 Day 49 Day 77
------- ------------------------ g soil------------- ---------------
Treatment -0.1 kPa


Control 105 (B") 184 (B) 427 (B) 105(B) 213 (B) 180(B) 171 (B)
100 kg P ha' 46 (C) 162 (B) 142 (C) 102 (B) 426 (B) 108(B) 92 (C)
DAPb 348 (Acc) 1338 (Aab) 1759 (Aab) 1255 (Ab) 1555 (Aab) 2908 (Aa) 891 (Ab)

-3 kPa
Control 200 (A) 128 (B) 302 (B) 209 (B) 61 (C) 46 (C) 83 (A)
100 kg P ha- 198 (A) 199 (B) 138 (B) 183 (B) 137 (B) 139 (B) 64 (A)
DAP 161 (Ac) 1716 (Ab) 1031 (Ab) 3433 (Aa) 766 (Ab) 942 (Ab) 316 (Abc)

-8 kPa
Control 122 (A) 53 (B) 136 (B) 32 140 (B) 18 (C) 75 (A)
100 kg P ha-' 72 (B) 67 (B) 116(B) NA" 98 (B) 157(B) NA
DAP 104 (Ac) 2122(Aab) 1106(Aab) NA 919(Ab) 5918 (Aa) 786 (Ab)

-15 Kpa
Control 245 (A) 208 (B) ND NA 96 (B) NA 250 (B)
100 kg P ha' 223 (A) 212 (B) 100 (B) NA 17 (C) NA 285 (B)
DAP 207 (Ac) 9470 (Aa) 783 (Ab) NA 549 (Abc) NA 1720 (Ab)

-1000 kPa
Control 112 (A) 284 (B) 56 (B) 171 (B) NA NA 77 (C)
100 kg P ha 66 (B) 332 (B)) 70 (B) 95 (B) 88 (B) NA 533 (B)
DAP 157 (Ac) 1120 (Aab) 942 (Aab) 1206 (Aab) 768 (Ab) NA 2953 (Aa)
aSignificant differences (P<0.05) between treatments within each day and water potential (upper case letters down colums)
bDAP = 350 kg P and 352 kgN ha'
'Significant differences (P<0.05) between days within the DAP treatment for each water potential (lower case letters across rows)
dNA missing data






Table 3-3. Comparison of microbial P by P fertilizer treatment within each day and by day within each P fertilizer treatment
fnr oeilrh nwatPr nntential


Day 0 Day 3 Day 7 Day 14 Day 28 Day 49 Day 77
------- ----------------- -------- g soil------------------------------------


Treatment -0.1 kPa
Control 1.0 (Ab) 1.2 (Cab) 1.2 (Bab) 2.5 (Ca) 1.7 (Ba) 1.8 (Ba) 2.4 (Ca)
30 kg P ha'' 0.9 (Ab) 17.7 (Ba) 8.9 (Aa) 8.2 (Ba) 15.6 (Aa) 9.0 (Aa) 11.5 (ABa)
60 kg P ha-' 1.0 (Ac) 32.5 (Aa) 9.7 (Aab) 19.7 (ABab) 27.4 (Aa) 28.4 (Aa) 6.6 (BCb)
100 kg P ha' 1.3 (Ab) 24.0 (ABa) 40.4 (Aa) 23.6 (Aa) 37.7 (Aa) 22.4 (Aa) 14.3 (ABa)


-3 kPa
Control 1.8 (Aaab) 1.5 (Ba) 1.4 (Ca) 1.6 (Ba) 1.7 (Ba) 1.7 (Ba) 1.2 (Ba)
30 kg P ha" 3.2 (Ab) 24.4 (Aa) 8.1 (ABab) 5.1 (Bb) 13.3 (Aa) 8.3 (Aa) 7.4 (Ab)
60 kg P ha' 1.5 (Ac) 16.7 (Aa) 7.5 (BCbc) 11.6 (Aa) 25.9 (Aa) 13.6 (Aa) 9.1 (Ab)
100 kg P ha- 1.4 (Ac) 27.1 (Aa) 25.2 (Aa) 20.3 (Aa) 17.7 (Aa) NAC 4.1 (Ab)

-8 kPa
Control 3.6 (Aa) 4.9 (Ca) 5.2 (Ba) 5.3 (Ba) 3.5 (Ba) 4.3 (Aa) 2.9 (Ba)
30 kg P ha' 1.5 (Ac) 21.3 (Ba) 16.7 (Ab) 14.8 (Ab) 11.6 (Ab) 5.2 (Ac) 5.0 (Bc)
60 kg P ha-' 2.9 (Ab) 21.7 (ABa) 11.3 (ABa) 12.1 (ABa) 6.0 (Bb) 12.6 (Aa) 8.6 (ABab)
100 kg P ha' 2.7 (Ac) 33.6 (Aa) 30.1 (Aa) 16.7 (Ab) 14.4 (Ab) 16.2 (Ab) 19.8 (Aa)

-15 kPa
Control 8.1 (Aa) 5.9 (Ca) 7.2 (Da) 5.9 (Ba) 4.7 (Aa) NA 4.7 (Ba)
30 kg P ha' 7.9 (Ab) 30.7 (Ba) 22.5 (Ca) 8.9 (Bab) 9.3 (Aab) NA 13.0 (ABab)
60 kg P ha' 9.6 (Abc) 16.6 (Cab) 37.1 (Ba) 26.0 (Aab) 7.5 (Ac) NA 14.5 (Abc)
100 kg P ha' 7.8 (Ac) 37.1 (Aab) 52.2 (Aa) 21.3 (Ab) 16.8 (Ab) NA 14.4 (Ab)

-1000 kPa
Control 4.0 (Aa) 3.5 (Ba) 5.0 (Ca) 4.5 (Ba) 4.2 (Aa) NA 3.3 (Ca)
30 kg P ha' 3.7 (Ab) 19.2 (Aa) 13.9 (Ba) 14.6 (ABa) 19.1 (Aa) NA 11.1 (ABa)
60 kg P ha' 3.3 (Ad) 11.2 (ABbc) 30.9 (Aa) 18.0 (Aab) 10.0 (Abc) NA 6.2 (BCc)
100 kg P ha' 3.7 (Ac) 23.4 (Ab) 20.0 (ABab) 30.1 (Aa) 9.6 (Ab) NA 13.8 (ABab)
"Significant differences (P<0.05) between treatments within each day and water potential (upper case letters down columns)
bSignificant differences (P<0.05) between days within each treatment and water potential (lower case letters across rows)
'NA data missing


~





















70

60

50
S40 Control
40
SI 30 kg P ha
30 0 60 kg P ha
. 0 100 kg P ha

10

0
0 3 7 14 28 49 77
Days from beginning of study


Figure 3-3. Microbial P by P fertilizer treatments over time in the -0.1 kPa soil
























---0.1 kPa
-- -3 kPa
-- -8 kPa
-- 15 kPa
- 1--1000 kPa


20 40 60 80

Days from beginning of study


Figure 3-4. Microbial P over time for each water potential in the 30 kg P ha' treatment


60

- 50

S40

. 30

. 20

10

0






66



Table 3-4. Percent of P fertilizer immobilized and retained on day 77 by the microbial
biomass
-0.1 kPa -3 kPa -8 kPa -15 kPa -1000 kPa
--------------------% P immobilized-----------
P fertilizer Peak day
30 kg P ha"' 30 42 30 45 29
60 kg P ha-' 29 14 15 27 24
100 kg P ha'1 13 14 16 25 14

Day 77
30 kg P ha 17 11 4 15 14
60 kg P ha' 4 7 5 9 3
100 kg P ha-' 7 2 9 5 6






Table 3-5. Comparison of microbial P between the control, 100 kg P ha ', and DAP fertilizer treatments within each day for
ePn-h wtepr nnotentil


Day 0 Day 3 Day 7 Day 14 Day 28 Day 49 Day 77
--------------------------------------------- (g P g- soil)--------------------------------
Treatment -0.1 kPa
Control 1.0 (Aa) 1.2 (C) 1.2 (C) 2.5 (C) 1.7 (C) 1.8 (C) 2.4 (C)
100 kg P ha-' 1.3 (A) 24.0 (B) 40.4 (B) 23.6 (B) 37.7 (B) 22.4 (B) 14.3 (B)
DAPb 0.5 (AdC) 64.2 (Abc) 56.7 (Abc) 33.4 (Ac) 203.2 (Aa) 111.2 (Ab) 94.2 (Ab)

-3 kPa
Control 1.8 (A) 1.5 (C) 1.4 (C) 1.6 (C) 1.7 (B) 1.7 1.2 (C)
100 kg P ha' 1.4 (A) 27.1 (B) 25.2 (B) 20.3 (B) 17.7 (A) NAd 4.1 (B)
DAP 1.9 (Ac) 49.5 (Ab) 37.1 (Ab) 122.5 (Aa) 16.1 (Ab) NA 32.2 (Ab)

-8 kPa
Control 3.6 (A) 4.9 (C) 5.2 (C) 5.3 (B) 3.5 (C) 4.3 (B) 2.9 (C)
100 kg P ha-1 2.7 (A) 33.6 (B) 30.1 (B) 16.7 (B) 14.4 (B) 16.2 (B) 19.8 (B)
DAP 2.0 (Ac) 190.3 (Aa) 245.5 (Aa) 314.9 (Aa) 49.8 (Ab) 64.8 (Aab) 62.7 (Ab)

-15 kPa
Control 8.1 (A) 5.9 (C) 7.2 (C) 5.9 (C) 4.7 (B) NA 4.7 (C)
100 kg P ha' 7.8 (A) 37.1 (B) 52.2 (B) 21.3 (B) 16.8 (B) NA 14.4 (B)
DAP 7.8 (Ab) 193.7 (Aa) 266.2 (Aa) 273.1 (Aa) 82.2 (Aa) NA 186.4 (Aa)

-1000 kPa
Control 4.0 (A) 3.5 (C) 5.0 (C) 4.5 (C) 4.2 (B) NA 3.3 (C)
100 kg P ha' 3.7 (A) 23.4 (B) 20.0 (B) 30.1 (B) 9.6 (B) NA 13.8 (B)
DAP 2.2 (Ac) 107.9 (Aab) 102.0 (Aab) 207.8 (Aa) 77.0 (Ab) NA 130.9 (Aab)


aSignificant differences (P<0.05) between treatments within days and water potentials (upper case letters down columns)
bDAP = 350 kg P and 352 kg N ha
'Significant differences (P<0.05) between days within the DAP treatment within each water potential (lower case letters across
rows)
dNA missing data






Table 3-6. Comparison of microbial C:P ratios by treatment within each day for each water potential
Day Day 3 Day 7 Day 14 Day 28 Day 49 Day 77
Treatment -0.1 kPa
Control 193:1 (AVb) 266:1 (Ac) 375:1 (Aa) 50:1 (Ae) 163:1 (Ad) 80:1 (Ae) 84:1 (Ae)
30 kg P ha' 199:1 (Aa) 30:1 (Ba) 14:1 (Ba) 23:1 (Aa) 17:1 (Ba) 11:1 (Ba) 18:1 (ABa)
60 kg P ha-' 202:1 (Aa) 7:1 (Bc) 16:1 (Bc) 13:1 (Ac) 12:1 (Bc) 8:1 (Bc) 20:1 (ABb)
100 kg P ha-' 86:1 (Ba) 7:1 (Bb) 20:1 (Bb) 13:1 (Ab) 10:1 (Bb) 2:1 (Bb) 14:1 (Bb)
DAP 152:1 (Ab) 26:1 (Ba) 31:1 (ABa) 38:1 (Aa) 8:1 (Ba) 38:1 (ABa) 28:1 (ABa)

-3 kPa
Control 112:1 (Ba) 100:1 (Aa) 46:1 (Aa) 140:1 (Aa) 31:1 (Aa) 34:1 (Aa) 76:1 (Aa)
30 kgP ha' 19:1 (Bb) 6:1 (Bb) 13:1 (Ab) 93:1 (ABa) 5:1 (Ab) 11:1 (Ab) 11:1 (Bb)
60 kg P ha-' 63:1 (Ba) 26:1 (Ba) 13:1 (Aa) 33:1 (BCa) 5:1 (Aa) 101:1 (Aa) 12:1 (Ba)
100 kg P ha1 173:1 (Aa) 10:1 (Bb) 7:1 (Ab) 16:1 (Cb) 9:1 (Ab) NAC 17:1 (ABab)
DAP 61:1 (Ba) 18:1 (Ba) 32:1 (Aa) 30:1 (BCa) 15:1 (Aa) NA 10:1 (ABa)

-8 kPa
Control 33:1 (Aa) 12:1 (Aa) 27:1 (Aa) 9:1 (Aa) 44:1 (Aa) 4:1 (Aa) 30:1 (Aa)
30kg Pha-' 44:1 (Aa) 5:1 (Aa) 7:1 (Aa) 3:1 (Aa) 8:1 (Aa) 27:1 (Aa) 25:1 (Aa)
60 kg P ha-' 31:1 (Aa) 9:1 (Aa) 7:1 (Aa) 7:1 (Aa) 31:1 (Aa) 2:1 (Aa) 3:1 (Aa)
100 kg P ha-' 25:1 (Aa) 2:1 (Aa) 7:1 (Aa) NA 12:1 (Aa) 5:1 (Aa) NA
DAP 48:1 (Aa) 21:1 (Aa) 18:1 (Aa) NA 45:1 (Aa) 27:1 (Aa) 13:1 (Aa)

-15 kPa
Control 30:1 (Aa) 34:1 (Aa) NA NA 23:1 (Aa) NA 53:1 (Aa)
30 kg P ha' 31:1 (Aa) 18:1 (Aa) 6:1 (Aa) NA 7:1 (Aa) NA 15:1 (Aa)
60 kg P ha' 25:1 (Aa) 12:1 (Aa) 3:1 (Aa) NA 14:1 (Aa) NA 15:1 (Aa)
100 kg P ha"' 28:1 (Aa) 5:1 (Aa) 3:1 (Aa) NA NA NA 27:1 (Aa)
DAP 32:1 (Aa) 59:1 (Aa) 5:1 (Aa) NA 7:1 (Aa) NA 3:1 (Aa)

-1000 kPa
Control 32:1 (Aa) 105:1 (Aa) 11:1 (Ab) 40:1 (Aa) NA NA 21:1 (Ba)
30 kg P ha 26:1 (Aab) 15:1 (Bab) 16:1 (Aab) 14:1 (Ab) 4:1 (Ab) NA 63:1 (ABa)
60 kg P ha 34:1 (Ab) 24:1 (Bb) 4:1 (Ab) 12:1 (Ab) 43:1 (Ab) NA 100:1 (Aa)
100 kg P ha' 19:1 (Aa) 15:1 (Ba) 8:1 (Aa) 3:1 (Aa) 8:1 (Aa) NA 38:1 (ABa)
DAP 51:1 (Aa) 13:1 (Ba) 6:1 (Aa) 12:1 (Aa) 27:1 (Aa) NA 14:1 (Ba)
'Significant differences (P<0.05) between treatments within each day and water potential (upper case letters down columns)
bSignificant differences (P<0.05) between days within each treatment and water potential (lower case letters across rows)
CNA- data missing










Table 3-7. Comparison of microbial P by water potential within each day for each
treatment
Day 0 Day 3 Day 7 Day 14 Day 28 Day 49 Day 77
Water --------------------------------------------pg g'- soil --------------------
Potential Control
-0.1 kPa 1.0 (Da) 1.2 (C) 1.2 (B) 2.5 (B) 1.7 (B) 1.8 (B) 2.4 (A)
-3 kPa 1.8 (CD) 1.5(BC) 1.4 (B) 1.6(B) 1.7(B) 1.7(B) 1.2 (B)
-8 kPa 3.6 (BC) 4.9 (A) 5.2 (A) 5.3 (A) 3.5 (AB) 4.3 (A) 2.9 (A)
-15kPa 8.1 (A) 5.9 (A) 7.2 (A) 5.9 (A) 4.7 (A) NAb 4.7 (A)
-1000 kPa 4.0 (AB) 3.5 (AB) 5.0 (A) 4.5 (A) 4.2 (A) NA 3.3 (A)

30 kg P ha-'
-0.1 kPa 0.9 (D) 17.7 (A) 8.9 (A) 8.2 (AB) 15.6 (A) 9.0 (A) 11.5 (A)
-3 kPa 3.2(B) 24.4 (A) 8.1 (A) 5.1 (B) 13.3 (A) 8.3 (A) 7.4(A)
-8 kPa 1.5 (C) 21.3(A) 16.7 (A) 14.8 (A) 11.6 (A) 5.2 (A) 5.0 (B)
-15 kPa 7.9 (A) 30.7 (A) 22.5 (A) 8.9 (AB) 9.3 (A) NA 13.0 (A)
-1000 kPa 3.7 (AB) 19.2 (A) 13.9 (A) 14.6 (A) 19.1 (A) NA 11.1 (A)

60 kg P ha-'
-0.1 kPa 1.0 (C) 32.5 (A) 9.7 (B) 19.7 (A) 27.4 (A) 28.4 (A) 6.6 (AB)
-3 kPa 1.5 (C) 16.7 (B) 7.5 (B) 11.6(A) 25.9 (AB) 13.6(A) 9.1 (AB)
-8 kPa 2.9 (B) 21.7 (AB) 11.3(B) 12.1 (AB) 6.0 (B) 12.6 (A) 8.6 (AB)
-15 kPa 9.6 (A) 16.6 (AB) 37.1 (A) 26.05 (A) 7.5 (B) NA 14.5 (A)
-1000kPa 3.3 (B) 11.2(AB) 30.9(A) 18.0 (A) 10.0 (AB) NA 6.2 (B)

100 kg P ha"'
-0.1 kPa 13 (D) 24.0 (A) 40.4 (AB) 23.6(AB) 37.7 (A) 22.4 (A) 14.3 (AB)
-3 kPa 1.4 (C) 27.1 (A) 25.2 (B) 20.3 (AB) 17.7 (AB) NA 4.1 (B)
-8 kPa 2.7 (BC) 33.6 (A) 30.1 (B) 16.7 (B) 14.4 (AB) 16.2 (A) 19.8 (A)
-15 kPa 7.8 (A) 37.1 (A) 52.2 (A) 21.3 (AB) 16.8 (AB) NA 14.4 (AB)
-1000 kPa 3.7 (AB) 23.4 (A) 20.0 (B) 30.1 (A) 9.6 (B) NA 13.8 (AB)

DAP


-0.01 kPa 0.5 (C) 64.2 (B) 56.7 (B) 33.4 (B) 203.2 (A) 111.2 (A) 94.2 (AB)
-3 kPa 1.9(B) 49.5 (B) 37.1 (C) 122.5 (A) 16.1 (C) NA 32.2 (B)
-8 kPa 2.0 (B) 190.3 (A) 245.5 (A) 314.9 (A) 49.8 (B) 64.8 (A) 62.7 (AB)
-15 kPa 7.8 (A) 193.7 (A) 266.2 (A) 273.1 (A) 82.2 (AB) NA 186.7 (A)
-1000 kPa 2.2 (AB) 107.9 (A) 102.0 (AB) 207.8 (A) 77.0 (B) NA 130.9 (AB)
'Significant differences (P<0.05) between water potentials within each day and treatment
bNA data missing























9
S8 *-0.1 kPa
0 E -3 kPa
7 7
S-8 kPa
6 l -15 kPa
o 52 -a y I I 4 *-1000O kPa
b4






0 3 7 14 28 49 77
Days from beginning of study


Figure 3-5. Microbial P by water potential in the control









Table 3-8. Comparison of microbial C by water potential within each day for each
treatment
Day 0 Day 3 Day 7 Day 14 Day 28 Day 49 Day 77
Water -------------------------------------g--- g soil------------------ -------
Potential Control
-0.1 kPa 105(Ba) 184(AB) 427(A) 105 (A) 213(A) 180(A) 171 (AB)
-3kPa 200 (AB) 128(BC) 302 (A) 209 (A) 61 (B) 46 (B) 83 (B)
-8 kPa 122 (B) 53 (C) 136 (B) 32 (B) 140 (AB) 18(B) 75 (B)
-15 kPa 245 (A) 208 (AB) NAb NA 96 (B) NA 250 (A)
-1000kPa 112(B) 284 (A) 56 (B) 171 (A) NA NA 77 (B)

30 kg P ha-'
-0.1 kPa 161 (AB) 173 (AB) 62(B) 180 (A) 261 (A) 164 (A) 175(B)
-3kPa 109 (B) 90 (B) 137 (AB) 217 (A) 67 (B) 76 (A) 54 (B)
-8 kPa 87 (B) 150 (B) 82 (AB) 18 (B) 59 (B) 69 (A) 71 (B)
-15kPa 231 (A) 148 (B) 61 (B) NA 55 (B) NA 156 (B)
-1000 kPa 63 (B) 267 (A) 183 (A) 144 (AB) 76 (AB) NA 682 (A)

60 kg P ha'
-0.1 kPa 209 (A) 174 (A) 172 (A) 170(AB) 209 (A) 179 (A) 126 (BC)
-3 kPa 129 (AB) 98 (BC) 181 (A) 258 (A) 111 (AB) 243 (A) 62 (C)
-8 kPa 88 (B) 33 (C) 83 (A) 80 (B) 76 (B) 27 (B) 29 (C)
-15 kPa 237 (A) 155 (B) 112 (A) NA 113(AB) NA 217 (B)
-1000kPa 113(AB) 266 (A) 93 (A) 109 (B) 107 (AB) NA 475 (A)

100 kg P ha-l
-0.1 kPa 46 (B) 162 (B) 142 (A) 102 (A) 426 (A) 108 (A) 92 (C)
-3kPa 198 (A) 199(B) 138 (A) 183 (A) 137(B) 139 (A) 64 (C)
-8 kPa 72 (B) 67 (B) 116 (A) NA 98 (B) 157 (A) NA
-15 kPa 223 (A) 212 (B) 100 (A) NA 17 (B) NA 285 (B)
-1000 kPa 66 (B) 332 (A) 70 (A) 95 (A) 88 (B) NA 533 (A)

DAP
-0.1 kPa 348 (A) 1338 (B) 1759 (A) 1255 (B) 1555 (A) 2908 (B) 891 (B)
-3kPa 161 (AB) 1716(B) 1031(A) 3433 (A) 766 (B) 942 (B) 316(B)
-8kPa 104 (B) 2122 (B) 1106(A) NA 919(AB) 5918(A) 786 (B)
-15kPa 207 (A) 9470 (A) 783 (A) NA 549 (B) NA 1720 (AB)
-1000 kPa 157 (AB) 1120(B) 942 (A) 1206 (B) 768 (B) NA 2953 (A)
aSignificant differences (P<0.05) between water potentials within each treatment and day
bNA data missing














CHAPTER 4
SUMMARY AND CONCLUSIONS

The microbial biomass represents an important component influencing nutrient

cycling and nutrient bioavailability. The acidic, sandy soils in the southeastern U.S. are

phosphorus (P) limited for forest production and hence are commonly fertilized with P.

The surface horizon of these soils have very little or no P retention capacity, resulting in

the unique condition where P fertilizer may be leached from the A horizon. The

microbial biomass may represent a significant sink and, later, a source of labile P for

plant uptake, particularly for soils with little or no P retention capacity. The ability of the

microbial biomass to immobilize and retain P fertilizer before it is leached below

seedling rooting depth would determine how important it might be as a source of

bioavailable P. Spodosols in the southeastern U.S. are defined by a fluctuating water

table that influences, along with rainfall, the water potential of the surface horizon. Since

microbial communities are linked to water potential, it is reasonable to assume that water

potential may also influence microbial immobilization of P fertilizer. To determine a

more accurate estimate of microbial P, a Kp factor, or correction value, is used. Kp factors

are dependent upon microbial communities, so the factors may also be affected by water

potential.

Realizing the interactions between microbial communities, biomass, and water

potential, the six objectives of Chapters 2 and 3 can be discussed under the four more

broadly stated objectives: 1) to determine the most appropriate extractant for the

determination of microbial K, factors and for estimating microbial P on acidic Spodosols









of the Coastal Plain; 2) to determine if Kp changes with water potential and soil horizon

characteristics; 3) to determine if microbial biomass and microbial P respond to P

fertilizer and how those responses progress over time, and 4) to determine if water

potential affects immobilization and retention of P fertilizer.

Objective 1: Determine the Most Appropriate Extractant for the Determination of
K, Factors and Estimating Microbial P on Acidic Spodosols of the Coastal Plain.

The hypothsis that 0.5 MNaHCO3 (pH 8.5) would not be suitable for extracting

microbial P on acidic soils in Spodosols was accepted. Oxalate was found to be more

consistent in removing inorganic P (P,) from the microbial biomass than the other

extractants, including NaHCO3. As the Bh horizon is dominated by amorphous Al-

oxides, oxalate extracted more microbial P and is better suited for extracting P, due to it's

ability to replace P through ligand exchange and dissolution of Al-oxide surfaces. In the

A and E horizon, oxalate performed similarly to NaHCO3 as most of the P, in these

horizons was water-soluble. However, the high pH (8.5) of NaHCO3 dissolves organic

compounds that creates interference problems for colorimetric analysis. Therefore, due

to the improved P extraction and the ease of analysis, oxalate is recommended. Of the

oxalate concentrations tested, 3 mM oxalate was recommended due to its greater ability

to recover P,, especially in the Bh horizon.

Objective 2. Determine if K Changes with Water Potential and Soil Horizon
Characteristics.

K, factors were affected by water potential and other soil horizon characteristics,

nullifying the hypothesis that soil water potential would not cause changes in Kp factors.

The highest K, factor was generally detected under the wettest soil condition, indicating

more P, was extractable from those microbial populations. The lower K, factors occurred

in the A and E horizons near field capacity (-8 kPa), while in the Bh horizon, the lowest









K, factor occurred in the -3 kPa soil. Significant differences in K, factors were evident

between horizons at similar water potentials, with the E horizon providing the highest Kp

factors and the Bh horizon the lowest. Changes in dominant microbial species within the

population, along with changing bacterial to fungal ratios due to differences in water

potential and soil characteristics, are suggested as the cause for the changes in Kp factors.

This study recommends that a Kp factor must be measured for each soil condition to get

the most accurate estimate of microbial P.

Objective 3. Determine if Microbial Biomass and Microbial P Respond to P
Fertilizer and How Those Responses Develop Over Time.

No clear trend of P-only fertilization could be seen on microbial C, suggesting

that microbial biomass was not P limited. In contrast to microbial C, microbial P

responded quickly to the addition of P-only fertilizer. Microbial P increased significantly

three days following fertilization and then decreased over time after the initial

immobilization peak. Microbial P increased from six to 18 times after fertilization and

was three to six times higher than the control at the end of the study, indicating microbial

P would continue to be higher than the control over a longer period of time.

Microbial P increased with increasing P rates, but the lower P rates did not differ

from the control after day 3. The highest P rate was different than the control, but not

from the other P-only treatments. The non-linear increase in microbial P suggested an

upper limit of P that the microbial biomass could immobilize under these conditions,

approximately 45 to 85 kg P ha ', depending on the water potential. When large

quantities of both nitrogen (N) and P were added, microbial C and microbial P responded

dramatically. This not only indicated that microbial biomass was N limited, but also that

the microbial biomass was able to immobilize a large quantity of P when made available









once the limiting factor, N, was removed. The microbial biomass was able to sequester

between 15 and 29 kg P ha in the P-only fertilization and up to 44 kg P ha-' when a

large quantity of both N and P was added.

The quantity of P immobilized by the microbial biomass was considerably more

than the annual demand of pine plantations. These data indicate that the microbial

biomass would be able to take up a significant quantity ofP and retain it over time. This

labile P source would become slowly available to plants over time as microbial turnover

occurred.

Objective 4. Determine if Differing Water Potential Affects Immobilization and
Retention of P Fertilizer

Before fertilization, microbial P was lowest in the wettest soil and highest in the

soil maintained at -15 kPa. After fertilization, microbial P increased dramatically and

was similar among all water potentials. More P was immobilized by the microorganisms

in the wettest soil, with microbial P increasing 11 to 29 times more than the drier soils.

Factors that may account for this occurrence include differences in microbial

populations' metabolic demand for P and sensitivity to limiting factors. Retention of P

in the microbial biomass did not seem to be affected by water potential.

Research Conclusions

This dissertation combined method evaluation and revision with investigations on

the role that microbial biomass has on sequestering P when plant biomass is not sufficient

to capture fertilization. The focus was on P fertilization of newly planted and herbicided

pine plantations developing on a typical flatwoods Spodosol of northern Florida. This

cover type and soil type represent a significant component of northern Florida and









southeastern Georgia where forest industry has a concentrated land base and pulp mills at

their highest density.

Phosphorus deficiencies are common on these soils so P fertilization is also

common. The Forest Soils program at the University of Florida has investigated a variety

of aspects P cycling in forested soils including work on fertilization practices, P uptake

by mature and young pine, organic P mineralization, inorganic P chemistry, and

microbial biomass changes due to long-term changes in forest productivity. This study

compliments those previous efforts and adds to the knowledge of: (1) how to measure

microbial P and (2) what is the potential of microbial P influencing the efficiency of P

fertilization practices.

The most adequate extractant for estimating microbial P in a sandy, acidic

Spodosol was 3 mM oxalate. The Kp factor for the most accurate estimate of microbial P

changed with soil horizon and soil water potential. It is recommended that Kp factors be

specific for changing soil conditions. Using an inaccurate Kp factor may cause significant

under or over estimations of microbial P. For example, if the Kp factor of 0.40 by

Brookes et al. (1982) was used for the A horizon at -0.01 kPa, microbial P would be

overestimated by 4 kg ha' in this soil. The microbial biomass in this soil at this stage of

stand development is not P limited but appears to be N limited. After fertilization, up to

three or more times the P than the annual demand by pine plantations will be sequestered

and held for several weeks. Although the microbial population may change due to

differences in water potential, P immobilization will not be affected. The sequestered P

would become slowly available to plants over time, but the timing of release with respect

to plant demand was not investigated and is an unknown.









Surprisingly, little information on K, factors is available in the literature. While K,

factors have been researched previously in the A horizon of soils having different

textures, prior to this study no information existed on how water potential affects K,

factors or if K, factors were influenced by soil horizons within the same soil profile. K,

factors determined in previous studies were from neutral or alkaline soils. Prior to this

study, no information was available for acidic soils of the southeastern U.S.

This research strengthened and expanded the limited information pertaining to K,

factors by demonstrating how significant differences resulted from varying water

potential and soil horizons in an acidic, sandy Spodosol. A standard method was revised

in order to make it more accurate for measuring microbial P in acidic soils. The method is

now simpler and more efficient in extracting P from the Bh horizon than the standard

extractant, 0.5 MNaHCO3.

Few studies have researched the relationship between P-only fertilization and

microbial P, and even fewer have done so on forest soils; and there is little information

on microbial biomass or microbial P in Flatwoods soils. Prior to this study there was no

information on the influence that water potential has on microbial P sequestration of P-

only fertilization. Prior to this study, it was not known that microbial P was not limited

by P bioavailability in this soil type; and prior to this study it was not clear that microbial

biomass could sequester enough P from P fertilization to supply the demands of a young,

developing pine stand. This study has significantly increased our knowledge of microbial

P in forested soils of the southeastern coastal plain and provided a guide as to what would

be productive avenues to continue this type of research. These are itemized below.









Future Research

The above results do not answer all the potential questions regarding the role that

microbial biomass plays in fertilizer P sequestration and subsequent bioavailability to a

developing pine stand. Future avenues of research that are logical extensions of this

dissertation are suggested below:

1. Extending the results of this study, it seems reasonable to think that K, factors
change with nutrient availability. Some microbial species may become more
dominant when they grow in a nutrient non-limiting environment. Since Kp is
related to microbial communities, this may cause changes in the Kp factor.
Measuring the Kp factors from soil with different rates of P fertilizer plus N and P
fertilizer should provide this information.

2. These data showed that microbial sequestration of fertilizer P was rapid, but the
time frame of these studies was too gross to adequately describe the kinetics of this
P absorption. A more refined time scale that defines these kinetics would better
describe the ability and rapidity of microbial P uptake. These kinetics are crucial if
one is to know if microbial uptake is in a competitive time frame with P leaching
following fertilization. A comparative study of these kinetics with and without
leaching events would further define how important P sequestering by the
microbial biomass can be.

3. Once the comparative kinetics are addressed, field tests of fertilizer events,
microbial sequestering, and the time subsequent release of microbial P to plants is
appropriate. Does microbial P release fertilizer P at a rate and in the appropriate
time frame to make the P available to developing pine. The mechanism of release
over time needs to be elucidated and tested under field conditions.

4. It was clear P did not limit microbial biomass. It was also clear that high rates of
DAP did overcome limitations to microbial biomass development. A factorial
approach to define what nutrient conditions limit microbial biomass development
and how the biomass responds to increasing nutrients would be useful. It could also
be done in conjunction with # 1 above.

5. Information on microbial biomass and microbial P in the spodic horizon is lacking
and should be addressed in both a laboratory and field study.












APPENDIX A
Kp FACTOR FIGURES


0.8

0.6

0.4

0.2

0.0


S-

A 'b
_ll l*h


0 NaHCO3
0 1 mM Oxalate
0 2mMOxalate
* 3 mM Oxalate
O Bray & Kurtz
0 Mehlich 1


-0.1 -3 -8 -15 -1000
Water potential (kPa)










Figure A-1. Inorganic Kp factors by extractant within each water potential for the a) A
horizon, b) E horizon, and c) Bh horizon


0
I
3















0.8


S0.6


0.4


0.2


0.0


-0.1 -3 -8 -15 -1000
Water potential (kPa)


1.0


0.8


S0.6


0.4


0.2 -


0.0
-0.1 -3 -8 -15 -1000
Water potential (kPa)


0 NaHCO3
0 1 mM Oxalate
0 2 mMOxalate
* 3mMOxalate
O Bray & Kurtz
O Mehlich 1


Figure A-1 continued













1.0


0.8


0.6


0.4


0.2


0.0 --
-0.1 -3 -8


Water potential (kPa)


-15


1.0


0.8


S0.6


0.4


0.2


0.0


-1000


0 NaHCO3
I 1 mMOxalate
0 2 mMOxalate
* 3 mMOxalate
O Bray & Kurtz
G Mehlich 1


-0.1 -3 -8 -15
Water potential (kPa)


-1000


Figure A-2. Total Kp factors by extractant within each water potential for the a) A horizon
and b) Bh horizon


a
0.






























NaHCO3 Oxl Ox2


Ox3 BK Mehlich 1


NaHCO3 Oxl Ox2 Ox3 BK Mehlich I


Figure A-3. Inorganic Kp factors by water potential within each extractant in the a) A
horizon, b) E horizon, and c) Bh horizon NaHCO3 = 0.5 MNaHCO3, Oxl = 1
mM oxalate, 0x2 = 2 mM oxalate, 0x3 = 3 mM oxalate, and BK = Bray and
Kurtz


0.2


0.0






b
1.0


0.8


0.6


0.4


0.2


0.0


* -0.1 kPa
0 -3 kPa
S-8 kPa
i-15 kPa
-1000 kPa
























C
1.0


0.8

*-0.1 kPa
0.6 0-3 kPa
[ -8 kPa

S0.4 O0-15 kPa
S-1000 kPa

0.2


0.0o
NaHCO3 Oxl 0x2 0x3 Mehlich 1


Figure A-3 continued














0.8

S0.6

0.4

0.2

0.0


NaHCO3 Oxl





Iit


0x2 0x3 BK Mehlich I


I9-0.1 kPa
0-3 kPa
M-8 kPa
0-15 kPa
S-1000 kPa


1.0

0.8

S0.6

0.4

0.2

0.0


NaHCO3 Oxi 0x2 0x3 Mehlich I



Figure A-4. Total Kp factors by water potential within each extactant for the a) A horizon
and b) Bh horizon NaHCO3 = 0.5 MNaHCO3, Oxl = 1 mMoxalate, 0x2 = 2
mM oxalate, 0x3 = 3 mMoxalate, and BK = Bray and Kurtz











1.0


0.8


c 0.6


0.4


0.2


0.0


-0.1 -3 -8 -15 -1000
Water potential (kPa)


O A Horizon
0 E Horizon
* Bh Horizon


1.0


0.8


i 0.6


0.4


0.2


0.0


-0.1 -3 -8 -15 -1000
Water potential (kPa)


Figure A-5. Inorganic Kp factors by horizon within each water potential in a) 0.5 M
NaHCO3, b) 1 mM oxalate. c) 2 mM oxalate, d) 3 mM oxalate, e) Bray and
Kurtz, and f) Mehlich 1










c
1.0


0.8


I 0.6


0.4


0.2


0.0


-0.1 -3 -8 -15 -1000

Water potential (kPa)


0 A Horizon
I E Horizon
* Bh Horizon


d
1.0


0.8


S0.6
S-s

0.4


0.2


0.0


Figure A-5 continued


-0.1 -3 -8 -15 -1000

Water potential (kPa)










1.0


0.8


0.6


0.4


0.2


0.0--
-0.1 -3 -8 -15 -1000
Water potential (kPa)


O A Horizon
I E Horizon
Bh Horizon
1.0


0.8


0.6


0.4


0.2


0.0 -. r
-0.1 -3 -8 -15 -1000
Water potential (kPa)


Figure A-5 continued












0.7 I

0.6 *.,

S 0.5 J

0.4

0.3

0.2

0.1

0.0
0.1


K, =0.489-
R2 = 0.65


0.127*log(y) + 0.038*log(Y)2


S-=-


Log water potential (-kPa)


I--- ----


'0*


K,= 0.696- 0.243*log(y)
0.219*log(Y)2 *
R2 = 0.92


K, = 0.346*log(y)0359
R2 = 0.63


Log water potential (-kPa)


Figure A-6. Regression curves for inorganic Kp factors in the A horizon for a) 0.5 M
NaHCO3, b) 1 mM oxalate, c) 2 mM oxalate, d) 3 mM oxalate, e) Bray and
Kurtz, and f) Mehlich I


w











0.8

0.7

0.6 "

0.5

0.4 -
Kp,=0.681 -0.052* (y)
S0.3 R2 = 0.85

0.2


0.0 -


K, =0.370*log(q)0 46'
R2 = 0.70


10
Log water potential (-kPa)


Kp= 0.664 0.008* (Y)2
R2 = 0.92


2
* .


100 1000


- 3 *


K, =0.389*log()( )341
R2 = 0.64


10
Log water potential (-kPa)


Figure A-6 continued










0.8

0.7
K,= 0.396 0.282*log(y) 0.008*log (Y)2
0.6 + 0.283* log(Y)3

0.5 R2 = 0.91 ,.
0.4 5 -


0 .3 -' "- "
SK, = 0.667

0.2 R2 = 0.95

0.1

0.0
0.1 1 10


100


Log water potential (-kPa)


J.8

0.7

0.6

0.5

Q 0.4

~0.3

0.2

0.1

0.0
0.1


K,= 0.198 0.00005* (y)
R2 = 0.55


-- --.----- .-.....
*


10
Log water potential (-kPa)


Figure A-6 continued


- 0.130*log(y)




Full Text
THE EFFECT OF PHOSPHORUS FERTILIZATION ON THE MICROBIAL
PHOSPHORUS POOL IN A SPODOSOL UNDER A SLASH PINE PLANTATION
By
CHRISTINE MARIE BLISS
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
2003

ACKNOWLEDGMENTS
I would first and foremost like to acknowledge and thank my major advisor, Dr.
Nick Comerford. His support, dedication, patience, and wisdom helped me to improve
both my professional and personal potential. He offered encouragement, advice, and
belief in my abilities that helped me to achieve my goals. I would also like to
acknowledge my committee members, Drs. E.J. Jokela, R.M. Muchovej, K.R. Reddy, and
R.D. Rhue. I greatly appreciate their help and suggestions for improving my research.
I will always be grateful for all the help I received from Mary Mcleod. Her
knowledge, support, and friendship motivated me through frustrating times in the
laboratory. Miranda Lucas was an invaluable asset to my research. I cannot thank her
enough for all of the help and support she provided me. 1 would also like to thank Nick
Comerford for his help in the laboratory. Adam Glassman and Marínela Capanu very
generously provided me with statistical help.
I would like to thank my family, especially my parents, for the endless
encouragement and support. Lastly, I would like to thank my friends. I cannot thank
them enough for their support, encouragement, and patience. 1 am most thankful to Dr.
Traci Ness and Jennifer Koski for listening and offering invaluable advice.

TABLE OF CONTENTS
Page
ACKNOWLEDGMENTS ii
LIST OF TABLES v
LIST OF FIGURES vii
ABSTRACT ix
CHAPTER
1 INTRODUCTION 1
2 DETERMINATION OF MICROBIAL PHOSPHORUS K„ FACTORS:
INFLUENCE OF HORIZON AND WATER POTENTIAL 9
Introduction 9
Methods 12
Study Area and Field Sampling 12
Growth and Culture of Microbes 12
A,, Determination 14
Extractants 15
Evaluation of Water Potential and Soil Characteristics on the Kp Method.... 16
Statistical Analysis 16
Results 17
Soil Characterization 17
Recovery of P Spike 17
Kp Factors by Extractant 17
Kp Factors by Water Potential 19
Kp Factors by Horizon 20
Comparison of Inorganic P vs. Total P Kp Factors 20
Evaluation of Water Potential and Soil Characteristics on the Kp Method.... 20
Comparison of Kp Factors with the Literature Kp Factor 21
Regression Equations 21
Discussion 21
Objective 1: The Most Efficient Extractant 21
Objective 2: Effect of Water Potential on Kp Factors 23
Objective 3: Influence of Horizon on Kp Factors 26
Conclusion 28
iii

3 SEQUESTERING OF PHOSPHORUS FERTILIZER IN MICROBIAL BIOMASS
OF A COASTAL PLAIN SPODOSOL 45
Introduction 45
Methods 46
Study Area and Field Sampling 46
Statistical Analysis 48
Results and Discussion 49
Objective 1: Investigate the Influence of P Bioavailabilty on the Microbial
Biomass 49
Objective 2: Estimate the Immobilization and Retention of P Fertilizer by the
Soil Microbial Biomass 51
Objective 3: Investigate How Soil Water Potential Affects Microbial Uptake
and P Fertilizer Retention 56
Conclusion 58
SUMMARY AND CONCLUSIONS 72
Objective 1: Determine the Superior Extractant for the Determination of Kp Factors
and Estimating Microbial Phosphorus on Acidic Spodosols of the
Coastal Plain 73
Objective 2: Determine of Kp Changes with Water Potential and Soil Horizon
Characteristics 73
Objective 3: Determine of Microbial Biomass and Microbial Phosphorus Respond
to Phosphorus Fertilizer and How Those Responses Develop Over
Time 74
Objective 4: Determine if Differing Water Potentials Affects Immobilization and
Retention of Phosphorus Fertilizer 75
Research Conclusions 75
Future Research 78
APENDIX A: Kp FACTOR FIGURES 79
APPENDIX B: ANALYSIS OF VARIANCE TABLES 97
APPENDIX C: FERTILIZATION STUDY FIGURES 124
LIST OF REFERENCES 144
BIOGRAPHICAL SKETCH 154
IV

LIST OF TABLES
Table Edge
2-1. Soil characterization for each horizon 29
2-2. Percent recovery of P¡ added as a spike 29
2-3. Comparison of inorganic Kp factors by extractant within each water potential and by
water potential within each extractant in the A, E, and Bh horizons 30
2-4. Comparison of total Kp factors by extractant within each water potential and by
water potential within each extractant for the A and Bh horizons 32
2-5. Comparison of inorganic Kp factors by horizon within each water potential for each
extractant 35
2-6. Comparison of total Kp factors by horizon within each water potential for each
extractant 37
2-7. Significant differences (P<0.05) between the inorganic P and total P
Kp factors for the A and Bh horizons 38
2-8. Inorganic Kp factors measured in the “test” horizons 39
2-9. Comparison of microbial P concentrations with determined inorganic Kp factors from
0.5 MNaHCCh and a Kp factor of 0.40 40
2-10. Regression equations for inorganic Kp factors for each extractant and horizon 41
3-1. Comparison of microbial C by treatment within each day and by day within each
treatment for each water potential 59
3-2. Comparison of microbial C between the control, 100 kg P ha-1, and DAP fertilizer
treatments within each day for each water potential 62
3-3. Comparison of microbial P by P fertilizer treatment within each day and by day
within each P fertilizer treatment for each water potential 63
3-4. Percent of P fertilizer immobilized and retained on day 77 by the microbial biomass 66
3-5. Comparison of microbial P between the control, 100 kg P ha1, and DAP fertilizer
treatments within each day for each water potential 67
v

vi
3-6. Comparison of microbial C:P ratios 68
3-7. Comparison of microbial P by water potential within each day for each treatment
69
3-8. Comparison of microbial C by water potential within each day for each treatment
71
B-l. Analysis of variance table for inorganic Kp factors 97
B-2. Analysis of variance table for microbial P from the P-only fertilizer treatments 101
B-3. Analysis of variance table for microbial P from all fertilizer treatments, including
DAP 107
B-4. Analysis of variance for microbial C from all P-only fertilizer treatments 114
B-5. Analysis of variance table for microbial C from all fertilizer treatments, including
DAP 119

LIST OF FIGURES
Figure gage
1-1. Phosphorus cycle 8
2-1. Inorganic Kp factors by extractant within each water potential in the A horizon 31
2-2. Total Kp factors by extractant within each water potential in the A horizon 33
2-3. Inorganic Kp factors by water potential within each extractant for the A horizon.... 34
2-4. Inorganic Kp factors for the A, E, and Bh horizon within each water potential using 3
mM oxalate 36
2-5. Inorganic Kp regression curves for the A, E, and Bh horizon 42
3-1. Solution inorganic P in the control at each water potential 60
3-2. Microbial C for each day in the -3 kPa soil at each P fertilizer treatment 61
3-3. Microbial P by P fertilizer treatments over time in the -0.1 kPa soil 64
3-4. Microbial P over time for each water potential in the 30 kg P ha’1 treatment 65
3-5. Microbial P by water potential in the control 70
A-l. Inorganic Kp factors by extractant within each water potential 79
A-2. Total Kp factors by extractant within each water potential 81
A-3. Inorganic Kp factors by water potential within each extractant 82
A-4. Total Kp factors by water potential within each extactant 84
A-5. Inorganic Kp factors by horizon within each water potential 85
A-6. Regression curves for inorganic Kp factors in the A horizon 88
A-7. Regression curves for inorganic Kp factors in the E horizon 91
A-8. Regression curves for inorganic Kp factors in the Bh horizon 94
vii

viii
C-l. Microbial C by day at each P fertilizer treatment 124
C-2. Microbial P by P fertilizer treatment for each day 128
C-3. Microbial P by water potential for each day 131
C-4. Microbial P by water potential in each P fertilizer treatment 133
C-5. Microbial C by water potential for each day 136
C-6. Microbial C by water potential for each treatment 138
C-l. Microbial P by day for each P fertilizer treatment 141
viii

Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy
EFFECTS OF PHOSPHORUS FERTILIZATION ON THE MICROBIAL
PHOSPHORUS POOL IN A SPODOSOL UNDER A SLASH PINE PLANTATION
By
Christine Marie Bliss
August 2003
Chair: Dr. N.B. Comerford
Major Department: Soil and Water Science Department
The microbial biomass is significant in nutrient cycling and nutrient bioavailability.
The acidic, sandy soils in the southeastern U.S. are phosphorus (P) limited for forest
production and commonly fertilized with P. The surface horizon has no P retention
capacity, resulting in possible leaching of P fertilizer, so the microbial biomass may be a
significant sink and source of labile P for plant uptake in these soils. The ability of the
microbial biomass to immobilize and retain P fertilizer before it is leached below
seedling rooting depth would determine how important it might be as a source of
bioavailable P. Spodosols in the southeastern U.S. have a fluctuating water table that
influences the water potential of the surface horizon. Microbial communities are linked
to water potential and so may influence microbial immobilization of P fertilizer. An
accurate estimate of microbial P is dependent upon a correct Kp factor that may also be
affected by water potential.
IX

X
The extractant, 0.5 A/NaHCXh (pH 8.5), used to measure microbial P was
questioned for use on these acidic soils. Kp factors were measured using six extractants,
0.5 A/NaHCXT, Mehlich 1, Bray and Kurtz, and 1 mM, 2 mM, and 3 mMoxalate, at five
water potentials ranging from -0.1 to -1000 kPa in the A, E, and Bh horizons. The
superior extractant for estimating microbial P in this soil was determined to be 3 mM
oxalate. Kp factors were determined to change with soil horizon and soil water potential.
Five treatments, control, 30, 60, and 100 kg P ha'1, and a DAP treatment, were
added to the A horizon at five water potentials. Microbial P and microbial biomass were
measured over time until 77 days after fertilizer addition. The microbial biomass in this
soil is not P limited but is N limited. After fertilization, up to three or more times the P
than the annual demand by pine plantations was sequestered and held for several weeks.
Water potential did not affect P immobilization. Microbial P would become slowly
available to plants over time, possibly after fertilizer is leached from the rooting zone.

CHAPTER 1
INTRODUCTION
Soil microbial biomass has been defined as the soil’s living component (Sparling,
1985) and consists mainly of bacteria and fungi. It holds approximately 2-3 percent of
the total soil organic carbon. The microbial biomass has been shown to be a factor in
nutrient cycling and soil fertility (Cosgrove, 1977; Smith and Paul, 1991) by controlling
mineralization and immobilization. Soil microorganisms are both an important sink and
source of available essential nutrients (Jenkinson and Ladd, 1981; Tate and Salcedo,
1988). The size and turnover of the microbial biomass influence the supply of labile
nutrients to plants (Anderson and Domsch, 1980). Since the microbial biomass relies on
organic matter as an energy source, it has been proposed as an indicator of soil organic
matter change (Anderson and Domsch, 1989; Insam et al., 1989; Wolters and Joergensen,
1991; Sparling, 1992) and soil fertility status (Marumoto, 1984; Hassink et al., 1991).
The phosphorus (P) content of the microbial biomass can be a significant
component of bioavailable P. Microbial P reportedly varies from 6 to 106 pg P g'1 soil
(Brookes et al., 1984; Diaz-Ravifla et al., 1995; Joergensen et al., 1995). Microbial
biomass uptake of P may be three to five times greater than plant uptake in semiarid
grasslands (Cole et al., 1977) and the flux of P through the microbial biomass may also
be three to five times greater than the quantity removed by annual harvesting of crops
(Chen and He, 2002).
1

The P cycle (Figure 1-1) is influenced by biological, chemical, and physical soil
properties. The original source of P in the soil is primary minerals, such as the various
forms of apatite. Through weathering, soluble P is released and made available to plant
or microbial uptake, leaching, or sorbed onto secondary minerals (Smeck, 1985).
Equilibrium is maintained between labile P and soluble P, with rapid exchange between
the pools (Olsen and Khasawneh, 1980). Removal of soluble P is buffered by the labile P
pool, but as both are depleted, these pools are replenished by both primary and secondary
P and mineralization of organic P (P0) (Smeck, 1985).
Secondary minerals, as sources of P, include minerals with P chemisorbed to the
surface, such as iron (Fe) and aluminum (Al) oxides and carbonates, and minerals derived
by crystallization at low temperatures with P as a structural component, such as variscite,
strengite, brushite, monetite, and Al, Fe, and calcium (Ca) phosphates (Smeck, 1985).
Secondary minerals may also physically occlude P when they form. Occluded P may
occur as Fe oxides, hematite, and goethite. Secondary minerals slowly release P into the
soil solution (Olsen and Khasawneh, 1980) and seldom achieve equilibrium with the
labile P pool (Murrmann and Peech, 1969; Olsen and Khasawneh, 1980) due to the
constant flux of P in the soil (Olsen and Khasawneh, 1980). However, the long-term
tendency of P is to form secondary minerals (Smeck, 1985).
In soils with little or no ability to sorb P, the microbial biomass must be the
controlling factor in P cycling. The biota is decomposed into organic matter with various
forms of P0 through microbial synthesis (Smeck, 1985). Microbial synthesis is believed
to be the origin of P0 (Cosgrove, 1977; Anderson, 1980). Organic P in soil exists mainly
as ester linkages to inositols with small quantities of nucleic acids and phospholipids

3
(Stewart and McKercher, 1982). Some P„ is transferred into a stable P0 pool, which is
slow to hydrolyze. The small quantities of nucleic acids and phospholipids are easily
hydrolyzed into soluble and labile forms while the inositols tend to accumulate (Halstead
and McKercher, 1975). Transformation of P0 occurs through plant uptake of soluble P,
some of which returns to the soil in plant litter with decomposition and accumulation of
P0, and microbial mineralization and return to soluble P pool.
Phosphorus mineralization is controlled by inorganic P (P¡) availability and P
demand by microorganisms and plants (Stewart and Tiessen, 1987; Walbridge, 1991).
When the labile Pj pool is high, P0 mineralization is repressed causing P0 to accumulate
(Spiers and McGill, 1979; Smeck, 1985). Equilibrium occurs between P0 and non-
occluded P¡ (Williams and Walker, 1969). Unlike nitrogen (N) and carbon (C),
mineralization of P0 may occur independently from C and is therefore labeled
biochemical mineralization (McGill and Cole, 1981). Phosphorus mineralization is
catalyzed by the enzyme, phosphohydrolase, which may be produced by plant roots,
mycorrhizae, or soil microbes (Gould et al„ 1979; Smeck, 1985). Phosphohydrolase is
repressed when labile Pj is high, causing the soil C:P ratio to decrease due to the
accumulation of P0 (Smeck, 1985). This occurs when the C:P ratio is generally less than
100, but if the ratio exceeds 200, then phosphohydrolase is induced (Smeck, 1985).
The microbial community structure is affected by several factors, including soil
water potential (Sheilds et ah, 1973; Diaz-Ravina et al., 1993). Seasonal community
structure changes have been linked to water potential (Smit et al, 2001) as have both
microbial C and microbial P contents (McLaughlin et ah, 1988; Ross, 1987; Srivastava,
1992; Ghoshal and Singh, 1995). In addition of community structure, microbial activity

4
has historically been associated with soil water potential with changes in activity
decreasing with both excessive and deficient water conditions (Wilson and Griffin, 1975;
Orchard and Cook, 1983; Ross, 1987; Skopp et al., 1990).
Phosphorus fertilization, along with weed control, is a common management
practice in souther pine plantations due to P limiting forest production on Spodosols in
the Coastal Plain of the southeastern United States (Colbert et al., 1990). The sandy
surface horizons have a limited P retention capacity (Humphreys and Pritchett, 1971;
Ballard and Fiskell, 1974; Fox et al., 1990a; Harris et al., 1996; Zhou et al., 1997) which
allows for P mobility. Therefore, if sufficient rainfall events occur, P fertilizer not
absorbed by plants or microorganisms may be leached below the A horizon (Harris et al.,
1996; Nair et al., 1999). Since the surface horizon has a low P retention and the
associated understory vegetation is removed or reduced, the question is whether the
microbial population would be a significant sink for P fertilizer.
Earlier methods for determining microbial P employed C:P ratios to estimate
microbial P from microbial C (Anderson and Domsch, 1980; Chauhan et al., 1981).
Subsequently, microbial P was measured by a fumigation method developed by Hedley
and Stewart (1982) which was adapted from microbial C methodology and revised by
others (Brookes et al., 1982; McLaughlin et al., 1986; Walbridge and Vitousek, 1987;
Walbridge, 1991).
Hedley and Stewart (1982) measured microbial P by incubating air-dried soil at pH
7.4, removing P, from the soil with an anion-exchange resin after which liquid
chloroform was added and the soil extracted with 0.5 MNaHCC>3 (8.5 pH) following
chloroform evaporation. The authors calibrated their method by measuring a Kp factor

(the fraction of P recovered from the microbial biomass) using commonly found soil
bacteria and fungi and reported that the Kp factor was 0.37.
Brookes et al. (1982) tried to improve this method by using fresh soil, pH 5.6 to 7.3
and a correction for sorption of P. The authors used chloroform vapor and extracted the
samples with 0.5 MNaHCCh (8.5 pH) along with fresh samples that had been incubated
for the same length of time as the samples under chloroform. Kp factors were measured
by spiking soils with several different common soil microorganisms and adding a spike
of P to another set of samples in order to determine the amount of P adsorbed by the soil.
Brookes et al. (1982) concluded the Kp factor to be 0.40, similar to that determined by
Hedley and Stewart (1982).
McLaughlin et al. (1986) used native microorganisms grown from their study soil,
pH 6.0 to 8.5, to derive Kp factors based on microbial assemblages more closely
associated with their study soils. The authors tested several lysing agents and extractants
and determined that using hexanol and 0.5 A/NaHCCh was best for their system. The Kp
factors ranged from 0.33 to 0.57, and like Hedley and Stewart (1982), Brookes et al.
(1982) and McLaughlin et al. (1986) concluded that Kp can differ according to soil type.
Walbridge and Vitousek (1987) developed yet another method for measuring
microbial P on a soil at pH 3.7. The authors used a different extractant, dilute acid-
fluoride (Bray and Kurtz extractant), which is widely used as an index of P availability in
acid soils. Walbridge (1991) followed this same procedure on soils with a pH ranging
from 3.7 to 3.9. The author used labeled 32PO of the inorganic spike by incubating the soil with the labeled P for 4 days to allow for

6
microbial immobilization and adsorption. Walbridge’s research indicated that Kp factors
ranged from 0.37 to 0.46.
Due to the limited P retention of the surface soils in the southeastern U.S. and the
potential for P fertilizer to leach quickly below the range of seedling root depth, the
microbial P pool may be a significant source of labile P in the surface horizon. If the
microbial biomass were able to immobilize P within hours, as was determined in
laboratory studies by Walbridge and Vitousek (1987), then the microbial biomass would
be able to immobilize a portion of the P fertilizer before it is leached. How long the
microbial biomass is able to retain immobilized P fertilizer and whether increasing the
level of P fertilizer also increases the level of microbial P and microbial C in these soils
was questioned. How different water potentials affect the uptake and retention of P
fertilizer is an additional concern due to the water table fluctuating significantly in
Flatwood soils. An accurate estimate of microbial P is dependent on measuring an
appropriate Kp factor. Microbial populations are sensitive to changes in water potential.
Therefore, one might suspect that Kp factors also are a function of water potential. The
use of the extractant, 0.5 MNaHCC>3, also needs to be further questioned for acidic soils
as was done by Waldbridge and Vitousek (1987) and Waldbridge (1991).
Given the above discussion, the objectives of this study were to: 1) determine if
0.5 MNaHCC>3 (pH 8.5) is a suitable extractant for microbial P on acidic Spodosols of
the Coastal Plain with the initial hypothesis that 0.5 MNaHCC>3 is not a suitable
extractant for microbial P on acidic soils in Spodosols; 2) determine if Kp factors change
with water potential and soil horizon characteristics with the hypothesis that Kp factors do
not change with water potential and that Kp is a constant; 3) determine if microbial

7
biomass and microbial P increase with P fertilization, testing the hypothesis that
microbial C and microbial P increase with fertilizer addition; and 4) determine if water
potential affects immobilization and retention of P fertilizer, addressing the hypothesis
that water potential does not affect P fertilizer immobilization and retention.
Chapter 2 describes the testing of the basic standard microbial P extractant against
several acidic extractants. Kp factors were developed for the A, E, and Bh horizons at
five water potentials for each extractant (Objectives 1 and 2). Chapter 3 describes the
response of microbial biomass and microbial P response to P fertilizer over time at
differing water potentials (Objectives 3 and 4). Chapter 4 is a summary and discussion of
this dissertation and also includes relevant topics for future research.

Figure 1-1. Phosphorus cycle. Dashed arrows indicate microbial mediated processes.

CHAPTER 2
DETERMINATION OF MICROBIAL PHOSPHORUS KP FACTORS: INFLUENCE
OF WATER POTENTIAL AND SOIL HORIZON
Introduction
Microbial biomass, which is composed of bacteria, fungi, and other microbiota, is
a major controlling component of nutrient transformations and cycling in soils.
Phosphorus (P) transformation and cycling through the microbial biomass have been
recently studied (Seeling and Zasoski, 1993; Gijsman et al., 1997; He et ah, 1997b;
Grierson et al., 1998) under a variety of soil conditions. Brookes et ah (1984) estimated
that the P held in the microbial biomass ranges from 5 to 106 pg P g"1 soil. Subsequent
studies fall within this estimated range of microbial P (Díaz-Raviña et ah, 1995;
Joergensen et ah, 1995).
In the Coastal Plain of the southeastern U.S., P limits forest production on
Spodosols (Colbert et ah, 1990). The sandy nature of the surface horizons limits P
retention capacity (Humphreys and Pritchett, 1971; Ballard and Fiskell, 1974; Fox et ah,
1990a; Harris et ah, 1996; Zhou et ah, 1997), resulting in P mobility. Therefore, P that is
not absorbed by plants or microorganisms may be leached below the A horizon (Harris et
ah, 1996; Nair et ah, 1999). Due to the low native bioavailability of P in these
Spodosols, P fertilization is commonly applied in combination with weed control during
a pine plantation’s rotation. Since the surface horizon has a low P retention and the
associated understory vegetation is removed or reduced, the microbial population could
be a significant sink for P fertilizer.
9

10
Microbial P estimates, as defined by Brookes et al. (1982), Hedley and Stewart
(1982), and McLaughlin et al. (1986), are based on extracting soil with 0.5 MNaHCCb at
pH 8.5. McLaughlin et al. (1986) investigated both basic and acidic soil extracting
solutions and concluded that 0.5 MNaHC03 at pH 8.5 removed the most P from the
microbial biomass. It is important to note that the pH of the soils they tested was 6.0 and
higher. However, forested soils in the southeastern Coastal Plain are acidic, with the pH
often ranging between 3.8 to 4.5. Inorganic P (P,) chemistry is dominated by aluminum
oxides where present, such as in the spodic and argillic horizons. The appropriateness of
using a high pH extractant under these conditions is therefore questionable for this type
of soil. Other extractants, such as low molecular weight organic acids that promote
ligand exchange and aluminum oxide dissolution (Fox et al., 1990b; Lan et al., 1995), are
known to better remove P from acidic soils and may recover more P when measuring
microbial P.
The fumigation-extraction method underestimates microbial P due to the
incomplete release of P from the microbial cells during fumigation and due to subsequent
adsorption of the released P¡ onto the mineral soil surface (Brookes et al., 1982; Hedley
and Stewart, 1982; McLaughlin et al., 1986). A correction factor, Kp, is used to
accurately estimate the total quantity of P held in the microbial biomass (Brookes et al.,
1982; Hedley and Stewart, 1982; McLaughlin et al., 1986). Kp factors may vary with soil
condition, due to either changes in microbial communities or sorption of P (Brookes et
al., 1982; Hedley and Stewart, 1982; McLaughlin et al., 1986). Brookes et al. (1982)
determined that inorganic Kp (Kp,) factors ranged from 0.32 to 0.38 and total Kp (Kp,)
factors ranged from 0.44 to 0.49, while Hedley and Stewart (1982) reported a similar

11
range of 0.32 to 0.47 for Kp, factors. Brookes et al. (1982) and Hedley and Stewart
(1982) concluded that a Kp of 0.40 provided a good estimate for soils with a basic pH, but
suggested that Kp factors may vary with soil conditions.
Many studies have used 0.40 as the correction factor in microbial P estimation
(Perrott et al., 1990; Tate et al., 1991; Clarholm, 1993; Gijsman et al., 1997; Lukito et al.,
1998). McLaughlin et al. (1986) determined that Kp factors ranged from 0.33 to 0.57 for
a range of soils and suggested that Kp factors must be calibrated for each soil because of
different microbial populations present in each environment. Since microbial
communities also vary with soil water potential (Wilson and Griffin, 1975; Lund and
Goksoyr, 1980; Orchard and Cook, 1983; Skopp et al., 1990), it seems reasonable to
suggest that Kp factors may also vary with this soil variable.
This study’s overall purpose was to examine the fumigation-extraction method for
measuring microbial P in acidic, forested, sandy soils. There were three specific
objectives. The first objective was to determine which extractant was most efficient at
removing microbial P by comparing the standard basic extractant, 0.5 MNaHCCL at pH
8.5, against several acidic and oxalate extractants with the hypothesis that 0.5 ALNaHCCh
is not the most efficient extractant. Since soil water potential controls microbial
communities and population levels, the second objective was to evaluate whether the Kp
factor was influenced by the soil water potential. The null hypothesis was that Kp factors
are not affected by water potential. The third objective was to test whether the Kp factor
differed by soil horizon within a profile of a representative Flatwoods Spodosol. The
hypothesis for the third objective was that Kp factors do not differ by soil horizon.

12
Methods
Study Area and Field Sampling
The study area was located 33 km northeast of Gainesville, FL. The site was a 16
ha managed slash pine plantation (Pinus elliottii var. Elliottii Engelm.) that was clearcut
in April 1994, bedded in September and November 1994, and planted with slash pine
seedlings in January 1995. In February 1995, 85 g ha'1 of imazypyr was applied as
Arsenal in 1.5 m wide bands down the beds for weed control. The plantation is underlain
by a sandy, siliceous, thermic Ultic Alaquod, which is primarily Pomona fine sand and
sand. The average annual temperature is 21 °C, and the long-term average annual rainfall
is approximately 1330 mm (Soil Conservation Service, 1995). Table 2-1 provides
chemical and physical characteristics of the A, E, and Bh soil horizons.
Soil was sampled in July 1996 from a subsection of the study area, approximately
2 ha. Approximately 10 kg of soil from each horizon was collected from 20 random
points with a 7.5 cm diameter soil auger. The samples were combined to form one
combined sample for each horizon. The soil was sieved to pass a 2 mm screen and air-
dried.
Growth and Culture of Microbes
Five water potentials were selected to represent a dry soil (-1000 kPa), near field
capacity (-15 kPa and -8 kPa), an unsaturated condition that represents a high water table
(-3 kPa), and near saturation (-0.1 kPa). These water potentials were based on results
from P mineralization studies that evaluated mineralization rate versus soil water
potential in a similar soil (Grierson et al., 1999).
In order to culture native microbial populations representative of the different water
potentials, soil samples from each horizon were incubated at each water potential for a

13
minimum of 10 days at 28 °C. Water potential was kept constant throughout the
incubation period by weighing the samples and adding double deionized water when
required. The soil sample was then diluted with double deionized water to a soil to
solution ratio of 1:10 and 1:1000 for fungal and bacterial growth, respectively. The
native fungal populations were grown by adding 1 ml of the 1:10 dilution to a growth
medium containing 660 mg NaNCb, 330 mg KH2PO4, 265 mg KC1, 165 mg MgSC>4
7H2O, 6.6 mg FeSC>4, 165 mg yeast extract, 10 g sucrose, 100 mg streptomycin sulphate,
and 5 mg tetracycline hydrochloride in one L of double deionized water (McLaughlin et
al., 1986). Native bacterial populations were grown by adding 1 ml of the 1:1000
solution to a 0.3 percent typic soy broth in double deionized water containing 100 mg
cycloheximide L*1 (McLaughlin et al., 1986). The microbes were grown in the dark at 28
°C for approximately 7 days. The fungal population was filtered from the nutrient
solution, rinsed in double deionized water, blotted dry, and subsampled before adding
back into soil samples for determination of Kp factors. Bacterial populations were grown
at the same temperature and time length as fungal populations. The bacterial suspension
was centrifuged, rinsed with double deionized water, and resuspended in double
deionized water before addition back into soil samples.
Total P (Pt) was measured in the fungal and bacterial populations following a
modified method of Smethurst and Comerford (1993). A known amount of sample
(approximately 300 mg of fungi and 5 mL of bacterial suspension) was dried in a muffle
furnace at 104 °C overnight. The samples were then ashed at 500 °C for 4 hours. When
cool, 7 mL of 40 percent HC1 were added to samples and evaporated to dryness on a hot
plate. Five mL of concentrated HC1 were added and again evaporated until dry. Ten mL

14
of 0.1 N HC1 were added to samples and allowed to stand overnight. A known quantity
of the sample in 0.1 AHC1, depending upon the P concentration, was diluted to 25 mL
and analyzed for P using the Murphy and Riley (1962).
Kp Determination
Approximately 80 mg of the fungi and 1 ml of the bacterial suspension were
added to soil samples at the same water potential and horizon from which the
microorganisms were grown. The samples were then fumigated with 2 mL of liquid
chloroform for 24 hours. The chloroform was allowed to evaporate, and the soil was
extracted for P. The Kp factor, or percentage recovery of microbial P, was calculated by
using the equation:
Kp = (m-n)/(xy) (2-1)
from Brookes et al. (1982), where m is the amount of P¡ measured in the samples that
contained the added microbial biomass, n is the amount of P¡ measured in fumigated
samples without additional microbes added, x is the percent recovery of P¡ determined
from a P spike, and y is the amount of Pt in the microbial biomass added to the sample.
This equation is the same when measuring Kp factors for microbial Pt, except that m
becomes the amount of Pt measured in the samples with added microbes and n becomes
the P, measured in sample without the added microbes. Total P was determined by
digestion of extractant as described above.
In order to determine the percent recovery of P| for the variable x above, a range of
P¡ concentrations from 40 to 100 pg P g’1 soil were added to a set of soil samples in the
Bh horizon. This range was used because of the variable P contained in the added
microbes and to determine if P adsorption was linear. Although P adsorption was

15
assumed to be negligible in the A and E horizons (Harris et al., 1996; Zhou et ah, 1997),
a spike of 40 pg P g'1 soil was added. This concentration of P was used because added P
in the microbes was generally 40 pg P g'1 soil. Phosphorus recovery is presented in
Table 2-2. Inorganic P was used as the spike for both Kpi and Kp, on account of most P
released from the microbial cells is P, (Brookes et ah, 1982) and sorption of P, and P0 was
assumed to be similar.
Extractants
The following solutions were used to extract P from the soil samples: 0.5 M
NaHC03 at pH 8.5 (Olsen et ah, 1954), 0.03.VNH4F and 0.25 N HC1 (Bray and Kurtz,
1945), 0.05 IVHC1 and 0.025 AH2SO4, or Mehlich 1, (Nelson et al., 1953), and ImM, 2
mM, and 3 mMoxalate at pH 3.2, 2.9, and 2.7, respectively. The Bray and Kurtz
extractant has been used in acidic soils as an index of P availability. It removes easily
acid-soluble forms of P from calcium phosphates and a portion of aluminum and iron
phosphates (Bray and Kurtz, 1945). Mehlich 1 was used as another measure of P
availability in acidic soils because of its ability to dissolve aluminum and iron phosphates
(Nelson et al., 1953). Oxalate is a naturally occurring, low molecular weight organic acid
whose presence in the soil solution is due to microbial activity and root exudation.
Oxalate increases P solubility through formation of stable complexes with aluminum
(Martell et ah, 1988) in solution, ligand exchange (Stumm, 1986; Fox et al., 1990a), and
dissolution of metal-oxide surfaces (Stumm, 1986).
The NaHCOa extract was used with a 1:10 soil to solution ratio and shaken for one
hour (Grierson et ah, 1998). A 1:7 soil to solution ratio with a 1 minute shaking time and
a 1:4 soil to solution ratio with a 5 minute shaking time was used for the Bray and Kurtz

16
extract and Mehlich I, respectively (Olsen and Sommers, 1982). A 1:10 soil to solution
ratio and 10 minute shaking time was used with the oxalate solutions. Ten minute
shaking time was determined with initial studies to be the shaking time that extracted the
most P from the soil sample.
After extraction and filtration, P, was measured using the Murphy and Riley (1962)
method. When required, filtered samples were treated with HC1 to lower the pH for
analysis by this method. The NaHC03 samples had to be refiltered after adding the acid
because acidification caused precipitation of organic compounds. Total P was also
measured for each sample as described previously.
Evaluation of Water Potential and Soil Characteristics on the Kp Method
Bacterial and fungal populations were grown from each horizon at -8 kPa using
the same methods described above. These microbial populations were then added into
soil samples maintained at each of the five different water potentials. Microbes were also
added into soil samples from the other horizons maintained at -8 kPa. For instance,
microbes grown from the A horizon at -8 kPa were added to soil samples from the A
horizon at each water potential and into the E horizon and Bh horizon at -8 kPa. Samples
were then extracted with 3 mM oxalate and analyzed for P¡.
Statistical Analysis
Significant differences were determined using SAS, version 8.01 (SAS Institute,
Inc 2001) using a mixed ANOVA model. The least-squared means were analyzed for
significant differences, (PO.05). Kp factors were analyzed within the main effects
(horizon, extractant, and water potential) and between main effects. Regression
equations for Kp¡ factors within each water potential, extract, and horizon were developed
using Statistica, 1999 edition (StatSoft Inc., 1999).

17
Results
Soil Characterization
Soil characteristics varied by horizon (Table 2-1). Organic carbon (C) was
significantly different by horizon, with the most organic C in the Bh and the least in the E
horizon. The greatest concentration of sand was in the E horizon, and the most silt and
clay was in the Bh horizon. Aluminum concentration was highest in the Bh horizon.
Recovery of P Spike
In the Bh horizon, more P was recovered with the 2 mM oxalate, 3 mM oxalate, and
Mehlich 1 extractants (Table 2-1). Between 80 to 89, 82 to 86, and 79 to 90 percent were
recovered in 2 mM oxalate, 3 mM oxalate, and Mehlich 1, respectively. Less P was
recovered with 1 mM oxalate and even less with NaHC03. Only approximately 50
percent of the P spike were recovered when NaHCOs was used. In the A and E horizons,
3 mM oxalate recovered all of the P spike while NaHCCb recovered 94 and 90 percent in
the A and E horizon, respectively. The Bray and Kurtz extractant and Mehlich 1
recovered 96 and 95 and 96 and 94 percent in the A and E horizons, respectively.
Kp Factors by Extractant
Inorganic Kp factors ranged from 0.14 to 0.72 in the A horizon, 0.19 to 0.99 in the
E horizon, and 0.11 to 0.45 in the Bh horizon (Table 2-3; Appendix A, Figure A-l). The
KPi factors for each extractant within each water potential were compared by horizon.
The A horizon provides an example of the differences in extraction efficiency (Figure 2-
1). The low concentrations of oxalate provided similar Kp, factors to the standard
extractant, 0.5 MNaHCCb (pFl 8.5), in all three horizons. However, within the different
concentrations of oxalate, 3 mli oxalate had a tendency to be more efficient in removing
Pi that was attributable to the microbial biomass. The Bray and Kurtz extractant

18
removed less P¡ from the microbial biomass, but it was not always significantly lower
than the oxalate concentrations or 0.5 M NaHCC>3. Mehlich 1 consistently extracted less
P than all other extractants. It extracted significantly less P¡ than both oxalate and 0.5 M
NaHCCb but was not always significantly lower than Bray and Kurtz.
In the E horizon, the solutions extracted similarly to the A horizon. The oxalate
concentrations extracted similar quantities of P from the microbial biomass as 0.5 M
NaHCC>3. Less P¡ was extracted when using Bray and Kurtz, but it was not always
significantly less than the oxalate concentrations or 0.5 MNaHCC>3. Mehlich 1 again
consistently extracted the least quantity of P¡. It was significantly lower than both oxalate
and 0.5 MNaHCCb but not always significantly different from Bray and Kurtz.
Within the Bh horizon, the solutions did not extract P similarly as in the A and E
horizons. Sodium bicarbonate was similar to 2 mM and 3 mM oxalate, but the lowest
concentration of oxalate was clearly less able to extract P. The extraction efficiency of 3
mM oxalate was clearly shown in the Bh horizon, in which the different oxalate
concentrations displayed increasing P extraction with increasing concentration. The
Mehlich 1 solution extracted the least P¡ from the microbial biomass, but it was not
significantly lower than the other extractants in all cases.
Total Kp factors ranged from 0.22 to 0.97 in the A horizon and 0.10 to 0.89 in the
Bh horizon (Table 2-4; Appendix A, Figure A-2). There was not sufficient sample to
evaluate Kp, for the E horizon. As with the Kpi, the Kp, factors showed similar trends. In
the A horizon, the Kpl factors for the three oxalate concentrations were mostly similar to
0.5 MNaHC03, with Bray and Kurtz and Mehlich 1 extracting less P, from the microbial

19
biomass (Figure 2-2). The Bh horizon provided similar trends. However, 2 mM oxalate
was able to remove more Pt from the added microbes overall.
Kp Factors by Water Potential
When comparing Kpi factors by water potential within extractants (Table 2-3;
Appendix A, Figure A-3), the most P¡ was extracted from the microbial biomass when the
soil was near saturation (-0.1 kPa). The A horizon provides an example of the
differences in P extracted from the microbial biomass between the different water
potentials within each extractant (Figure 2-3). Soil at saturation had the significantly
highest Kp, factor or was similar to the highest Kpl factor for the majority of comparisons.
In the A and E horizons, soil with the water potential closest to field capacity (-8 kPa)
yielded the least quantity of P from the microbial biomass. The Kp, factors had a trend of
decreasing as the soil became drier but then increasing after -8 kPa with drier soil in both
the A and E horizons. In the Bh horizon, the lowest Kp, occurred in soil at -3 kPa, after
which the Kpi increased.
When comparing the amount of P, extracted (Table 2-4; Appendix A, Figure A-4),
the Kp, factors followed the same trend as the Kpi factors with more P extracted in soil at
saturated and dry conditions and least when the soil was at an optimum water potential,
near field capacity. Again, more P was extracted from the microorganisms in the
saturated soil with a decrease in extractability with decreasing water potential.
Extractable P increased again in the drier soils. In the A horizon, the least P was
extracted from the microbial biomass in soil at -8 kPa whereas in the Bh horizon, the
least P was extracted from microbes at -3 kPa.

20
Kp Factors by Soil Horizon
When comparing the Kp, factors by horizon, the highest Kp¡ factors tended to be in
the E horizon (Table 2-5; Appendix A, Figure A-5). The A horizon also provided high
Kpi factors, while the Bh horizon usually had the lowest values. An example is provided
comparing the horizons using 3 mM oxalate (Figure 2-4). When comparing horizons
within each extractant, the E horizon provided the highest Kpi factor for all extractants
except for the Mehlich 1 extract; however the value was not always statistically higher.
The Kp, factors were significantly higher for the A horizon (Table 2-6). This occurred for
all extractants except Mehlich 1, in which no significant differences were obtained.
Comparison of Inorganic P vs. Total P Kp factors
Significant differences were detected between the inorganic P and total P Kp
factors (Table 2-7). Approximately one half of the Kp, factors were significantly different
from the Kpl factors. Sodium bicarbonate and 2 mM and 3 m.M oxalate concentrations
were significantly different the majority of the time. Bray and Kurtz and Mehlich 1 had
the least differences. When comparing the differences between water potentials, -15 kPa
in the A horizon, and -1000 kPa in the Bh horizon had the most significant differences,
but there did not seem to be a trend across the water potentials that was the same for each
horizon.
Evaluation of Water Potential and Soil Characteristics on the Kp Method
When comparing the Kp, factors measured within the original horizon, there was
no significant difference when microbes from one water potential were added to other
water potentials (Table 2-8). This result was consistent in all three horizons. But when
comparing the Kp, factors measured when the microbes were added to different horizons,
significant differences were determined. When testing microbes from the A horizon in

21
the E horizon and microbes from the E horizon into the A horizon, there were no
significant differences. Significant differences were detected when A and E microbes
were added into the Bh horizon and when Bh microbes were added into the E horizon.
Comparison of Kp Factors with the Literature Kp Factor
Since the Kpi factors measured were determined to be significantly different by soil
water potential and horizon, the differences in microbial P were calculated using the
commonly used literature value of 0.40 (Brookes et al., 1982; Hedley and Stewart, 1982)
and the current study’s values (Table 2-9). Assuming a Kp factor from the literature
resulted in estimates of microbial P that were 0 to 160% different from the estimates
using Kp values from this study.
Regression Equations
Regression equations were developed for the Kp< factors for each extractant and
horizon (Table 2-10; Appendix A, Figure 2-6). The R2 values ranged from 0.02 to 0.95.
One regression equation was applicable to 0.5 MNaHCX>3, but with oxalate, there were
two distinct curves, one for the -0.1 to -8 kPa soils, or the “wet to moist” soil, and
another for the -8 to -1000 kPa soils, or the “moist to dry” soil (Figure 2-5). This
occurred in all horizons except the Bh horizon with 3 mM oxalate. The Bray and Kurtz
and Mehlich 1 extractants varied with horizon. Many of the equations in the wet to moist
soils had less variability than those for the moist to dry soil. Regression equations for the
Kp, factors were not developed due to the lack of data.
Discussion
Objective 1: The Most Efficient Extractant
There are two main factors that define an efficient extractant for removing P from
the microbial biomass. The extractant should consistently recover the highest percentage

22
of P from the microbial biomass and should not produce interferences with colorimetric P
measurement. In Spodosols, sorption is not a factor in either the A or E horizons due to
the acidic, sandy nature of these soils. Therefore, in these surface soils, extraction should
only involve P released from the microbial biomass. The Bh horizon has the ability to
sorb released microbial P. Due to this sorption capacity, the extractant must have the
ability to re-extract this sorbed microbial P for measurement. Interference with
colorimetric procedures caused increased labor by increasing procedure steps and
diminishing accuracy and precision.
When comparing the ability and suitability of extracts for removing P¡ from the
microbial biomass, oxalate performed more consistently than the other extractants,
including NaHCCh. In Spodosols of the southeastern U.S., the Bh horizon is dominated
by amorphous Al-oxides (Ballard and Fiskell, 1974; Lee et al., 1988). Oxalate has an
effect on both P and Al release from the Bh horizon because of its ability to replace P
through ligand exchange and dissolution of Al-oxide surfaces (Fox and Comerford,
1992). The A horizon in this soil has little Al (Fox and Comerford, 1992) beyond what is
found on the meager cation exchange capacity, and the P¡ in this horizon was nearly all
water soluble (Fox et al., 1990a). Under these conditions, oxalate and NaHC03 would
extract similar amounts of P¡. As shown in the recovery of the P spike in the A and E
horizon, a high percentage was recovered with all extractants, but 3 mM oxalate
recovered all of the spike. In acidic soils, HCO3' ions replace P absorbed on the soil
surface (Olsen et al., 1954), but the high pH of NaHCOj also dissolves some organic
compounds. The dissolution of organic matter results in precipitates when the sample is

23
acidified for the measurement of P¡ by the method of Murphy and Riley (1962).
Therefore extra filtration is required.
The Bray and Kurtz extractant was developed to remove acid-soluble forms of P,
mostly calcium phosphates, and some A1 and Fe phosphates (Bray and Kurtz, 1945).
While it is a commonly used extractant for P on acidic soils, it did not perform well with
extraction of microbial P. Mehlich 1 uses the same concept of the Bray and Kurtz
extract, with the release of P from Fe phosphates due to the action of acids (Nelson et al.,
1953). Although Mehlich 1 recovered a high percentage of the P spike in the Bh
horizon, it did not perform well in extraction of P from the microbial cells.
For this type of soil, due to the better extraction of P from the microbial biomass
and the ease of analysis, oxalate is recommended. Of the oxalate concentrations tested, 3
mM oxalate was chosen due to its ability to recover more P¡ and the ease of use when
compared with NaHC03. As with Kph 2 mM oxalate and 3 mM oxalate were not
significantly different the majority of the time with respect to extraction of Pt from the
microbial biomass. Two mM oxalate was determined to be the superior extractant, but
this may be due to missing values, especially in the Bh horizon, from 3 mM oxalate.
Objective 2: Effect of Water Potential on Kp Factors
The Kp equation, equation 2-1, cancels background P associated with the soil and
with the native microorganisms. Existing microbial P in the soil samples is subtracted
from the Kp equation through (m - n). Both m and n are fumigated, which eliminates
existing microbial P and also native soil P, providing the quantity of P that is extracted
from the added microbial fungal and bacterial populations. Variable x, the percentage of
P recovery, corrects for any P that may be sorbed by the soil. Therefore, the Kp equation

24
calculates the fraction of P that is extracted from a microbial population with a known P
concentration.
Soil moisture content is a critical factor affecting microbial activity. Microbial
populations have been shown to increase activity with increasing water potential (Wilson
and Griffin, 1975; Orchard and Cook, 1983). Changes in fungal and bacterial ratios with
water content (Anderson and Domsch, 1975; Wilson and Griffin, 1975; Faegri et ah,
1977) suggest that dominant microbial assemblages change with water contents. Diaz-
Raviña et al. (1995) determined that differences in nutrient concentrations in the
microbial biomass are significantly related to soil characteristics, including soil moisture.
Soil moisture content has also been shown to affect microbial community diversity
(Brockman et ah, 1992). Furthermore, Sparling and West (1989) have already suggested
that the extractability of P from the microbial biomass is a function of soil water content.
When comparing our NaHCC>3 study results with other studies (Brookes et ah,
1982; McLaughlin et ah, 1986), Kpi factors for the A horizon were consistent with the
published range (0.36 to 0.42) when the soil was -3 kPa or drier. When the soil was near
saturation, Kp¡ increased to 0.61. This is in contrast to studies that determined the
microbial Kc factor (the fraction of microbial C that decomposes into CO2-C in 10 days)
decreased with increasing water content (Ross, 1987; Wardle and Parkinson, 1990).
Wardle and Parkinson (1990) also suggested that water content significantly influenced
Kc factors.
Since the methodology used cancels all background factors, there are only two
other factors affecting Kp. Those factors are microbial community changes and water
potential influence on P extraction from the microbial biomass. In order to test the effect

25
of water potential on the extraction of P, microbes grown at a specific water potential
were added to the same soil at different water potentials. The only factor changing was
water potential because the added microbial population was the same in each sample.
Therefore, the extraction procedure was not being affected by water potential. This
provides evidence that the extraction of P from the microbial biomass is not affected by
water potential as suggested by Sparling and West (1989). Therefore, the only other
factor changing was the microbial community.
Microbial communities have been documented to change with season (Smit et al.,
2001), temperature (Dalias et al., 2001), pH and substrate (Yan et al., 2000), and water
potential (Nazih et al., 2001; Marschner et al., 2002; Treves et al., 2003). Since water
potential has been shown to affect the diversity of microbial communities, it seems
reasonable to assume that this diversity may be influencing the Kp factors measured at
different water potentials.
Brookes et al. (1982) and Hedley and Stewart (1982) measured the Kp factor of
individual microbial species and determined that different species of microorganisms had
different Kp factors. Several studies have determined that Kc factors are also dependent
upon the diversity of organism assemblages (Jenkinson, 1976; Anderson and Domsch,
1978; Nicolardot et al., 1984). Thus, it seems reasonable to conclude that Kp factors in
this study differed with water potential because of changes in microbial communities
caused by the change in water potential.
Although regression equations were created, use of these equations to predict Kp
factors should be restricted to soil very similar to this study. As discussed, differences in
soil properties such as organic C cause changes in microbial diversity, which in turn may

26
cause differences in Kp factors. The percentage of variability in these equations indicated
the equations fit the data for many cases. However, with some equations, the predicted
values did not fit observed data, especially in the drier soils. For example, in the E
horizon, the predicted values provided Kpi factors well above 1, which is not possible.
This is most likely due to the design of the experiment that was set up for contrasting
different water potential, not for regressing Kp against water potential. The large gap
between -15 kPa and -1000 kPa does not provide a well-balanced regression curve.
Objective 3: Influence of Soil Horizon on Kp Factors
Microbial population diversity should also occur in different horizons within a soil
profile. Nutrient concentrations, water regime, quantity of and type of organic carbon as
a food source, soil texture, and possibly pH change with horizon. Both organic C and the
water regime in the three soil horizons are considerably different. Organic C, which was
discussed previously, is significantly different by horizon. Organic C is leached from the
A horizon, through the E horizon, and collects in the Bh horizon. Organic C provides
needed energy for microorganisms while also creating community diversity.
Permeability is rapid in the surface horizons (A and E horizons), but the subsurface
horizons have low permeability. In an average year, the shallow water table may be less
than 25 cm from the soil surface for one to three months, between 25 and 100 cm for six
months, and exceeding 100 cm during the dry season (Soil Conservation Service, 1985).
Soil water potential was found to be different between the A horizon and the lower
horizons with the lower horizons being similar when the water table was approximately
96 cm below the soil surface (Phillips, 1987). As mentioned previously, microbial
communities are affected by water potential (Diaz-Raviña et al., 1995). Because the

27
horizons have different water regimes, it seems reasonable that microbial diversity may
also change with horizon due to the difference in water potential.
Microbial activity (Bauhus et al., 1998) and microbial community composition
(Sessitsch et al., 2001) also differ with soil texture. When comparing this study’s A
horizon Kpi factors using NaHC03 with the Kpi factors in similar textured soils by
Brookes et al. (1982) and McLaughlin et al. (1986), the Kpi factors were similar; 0.39
(this study at -8 kPa), 0.32 (Brookes et al., 1982), and 0.33 (McLaughlin et al., 1986).
McLaughlin et al. (1986) measured Kp factors on three sites with different soil textures,
finding that Kp differed by site. These data support the premise of McLaughlin et al.
(1986) by providing additional examples that soil texture does play a role in microbial
diversity.
Changes in the soil pH cause changes in the microbial community structure
(Frostegard et al., 1993; Degens et al., 2001; Yan et al., 2000) that affect microbial Kc
factors (Vance et al., 1987). Consequently, pH should also affect Kp factors since both
are determined by soil microorganisms. Another factor affecting microbial diversity
may be the diversity of plant roots. Differences in the compounds exuded by plant roots
result in microbial community diversity (Grayston and Campbell, 1996).
As discussed previously, microbial diversity has been linked to the value of
correction factors used in calculating microbial C. This study has shown that soil
physical and chemical properties influence the value of microbial Kp factors, which in
turn appear linked to changes in the microbial community. For example, the P removed
by from the microbial population by extractants was more easily removed from the E

28
horizon than the A and Bh horizons. Based on the above discussion, this suggests that
the microbial community in the E horizon more easily releases P following fumigation.
This study has clearly shown that Kp factors are a function of soil water potential
and soil characteristics and should not be generalized for different soils. Since Kp is
clearly influenced by soil characteristics, using literature values for a Kp factor will cause
a significant error, as much as 62, 145, and 48 percent in the A, E, and Bh horizons,
respectively, when using NaHCC>3 as an extractant, in microbial P estimates.
Conclusion
A revised extraction method was more useful for measuring microbial P in acidic
sandy horizons with spodic horizons. For the soil used in these studies, oxalate was
determined to extract more or similar amounts of P from the microbial biomass as the
standard 0.5 MNaHCCb Using 0.5 MNaHCC>3 is still appropriate but difficult to apply
to spodic horizons due to the analytical interference. Therefore, it was concluded that
oxalate was a more efficient extractant for Spodosols. Kp factors were determined to be a
function of water potential and other soil characteristics due to the changes in microbial
diversity. It was concluded that a standard Kp for many soil conditions is not appropriate
and may cause significant errors of microbial P. A Kp factor should be assessed for each
soil condition to get the best estimate of microbial P.

29
Table 2-1. Soil characterization for each horizon
Horizon
pH
Sand
Silt
Clay
Organic C
A1
Fe
Ca K
Mg
Na
A
4.1
94
5
1
0.69 (b)a
0.15
0.01
0.14
0.33
0.27
0.01
E
4.0
96
3
1
0.16(c)
0.00
0.01
0.04
0.12
0.16
0.01
Bh
4.3
90
8
2
1.23 (a)
2.24
0.02
0.04
0.17
0.28
0.03
aSignificant differences (P<0.05) between horizons within organic C
Table 2-2. Percent recovery of P¡ added as a spike to soil samples for each extractant
Horizon
% recovery of P added—
8.5 M
NaHCOs
1 mM
Oxalate
2 mM
Oxalate
3 mM
Oxalate
Bray &
Kurtz
Mehlich 1
Bh 40 |tg g ' soil
50
63
82
85
NDa
79
Bh 60 pg g’1 soil
52
61
84
82
ND
83
Bh 80 pg g'1 soil
52
72
89
82
ND
82
Bh 100 pg g'1 soil
48
75
80
86
ND
90
Bh average
50
68
84
84
ND
83
A 40 pg g’1 soil
94
95
97
100
96
96
E 40 pg g'1 soil
90
96
97
100
95
94
“ND - data not determined

30
Table 2-3. Comparison of inorganic Kp factors by extractant within each water potential
and by water potential within each extractant in the A, E, and Bh horizons
-0.1 kPa
Water Potential-
-3 kPa -8 kPa
-15 kPa
-1000 kPa
Extractant
A horizon
0.5 MNaHC03
0.65 (Aaab)
0.42 (BCb)
0.35 (Ab)
0.45 (Ab)
0.38 (Bb)
1 ntM oxalate
0.72 (Aa)
0.53 (ABb)
0.30 (ABc)
0.41 (Abe)
0.51 (ABb)
2 mM oxalate
0.71 (Aa)
0.47 (Bbc)
0.28 (ABc)
0.48 (Ab)
0.60 (Aab)
3 mM oxalate
0.67 (Aa)
0.65 (Aa)
0.31 (ABc)
0.49 (Ab)
0.56 (Aab)
Bray & Kurtz
0.39 (Bb)
0.29 (CDc)
0.34 (Abe)
0.51 (Aa)
0.28 (BCc)
Mehlich 1
0.22 (Ca)
0.21 (Da)
0.19 (Bab)
E horizon
0.18 (Bb)
0.14 (Cb)
0.5 A/NaHC03
0.99 (Aa)
0.75 (Bb)
0.60 (Ac)
0.73 (Abe)
0.73 (ABbc)
1 mM oxalate
0.66 (Bb)
0.95 (Aa)
0.53 (Ab)
0.70 (Aab)
0.71 (ABab)
2 mM oxalate
0.85 (ABab)
0.90 (Aa)
0.58 (Ac)
0.68 (Abe)
0.86 (Aab)
3 mM oxalate
0.74 (Bab)
0.91 (Aa)
0.48 (Ac)
0.64 (Abe)
0.83 (Aa)
Bray & Kurtz
0.79 (Ba)
0.55 (Cb)
0.30 (Be)
0.42 (Bbc)
0.59 (Bb)
Mehlich 1
0.43 (Ca)
0.35 (Dab)
0.19 (Be)
Bh Horizon
0.28 (Bbc)
0.28 (Cbc)
0.5 A/NaHC03
0.36 (ABb)
0.27 (Ab)
0.33 (Ab)
NAC
0.72 (Aa)
1 mM oxalate
0.15 (Ca)
0.13 (Ba)
0.17 (Ba)
NA
0.13 (Ca)
2 mM oxalate
0.25 (BCa)
0.17 (Be)
0.23 (ABa)
NA
0.18 (BCbc)
3 mM oxalate
0.45 (Aa)
0.28 (Ab)
0.30 (Aab)
NA
0.22 (Bb)
Bray & Kurtz
NDd
ND
ND
ND
ND
Mehlich 1
0.16 (Cab)
0.11 (Bb)
0.14 (Bb)
NA
0.21 (BCa)
“Significant differences (P<0.05) between extractants within each water potential and
horizon (upper case letters down columns)
bSignificant differences (P<0.05) between water potentials within each extractant and
horizon (lower case letters across rows)
“NA - missing data
- data not determined

Kp factor
31
-0.1 -3 -8 -15
Water potential (kPa)
-1000
S 0.5 A/NaHCC>3
0 1 mili oxalate
0 2 mM oxalate
I 3 mM oxalate
D Bray & Kurtz
0 Mehlich 1
Figure 2-1. Inorganic Kp factors by extractant within each water potential in the A
horizon

32
Table 2-4. Comparison of total Kp factors by extractant within each water potential and
by water potential within each extractant for the A and Bh horizons. Kp
factors were not determined for the E horizon.
-0.1 kPa â– 
Water Potential-
-3 kPa -8 kPa -:
15 kPa
1000 kPa
Extractant
A horizon
0.5MNaHCO3
0.91 (A“ab)
0.74 (Aab)
0.63 (Abe)
0.53 (Be)
NAC
1 mM oxalate
NA
0.59 (Ba)
0.38 (Bbc)
NA
0.51 (Bab)
2 mM oxalate
0.97 (Aa)
0.76 (Aab)
0.44 (Bb)
0.60 (Bb)
0.82 (Aab)
3 mM oxalate
0.74 (Ba)
0.77 (Aa)
0.43 (Be)
0.59 (Bb)
NA
Bray & Kurtz
0.41 (Cb)
0.34 (Cb)
0.38 (Bb)
0.86 (Aa)
0.44 (BCb)
Mehlich 1
0.22 (Da)
0.23 (Ca)
0.22 (Ca)
Bh horizon
0.29 (Ca)
0.26 (Ca)
0.5 WNaHC03
0.43 (Ab)
0.55 (Ab)
0.40 (Ab)
NA
0.78 (Ba)
1 mM oxalate
0.23 (Ba)
0.17 (Ca)
0.23 (Ba)
NA
0.21 (Ca)
2 mM oxalate
0.55 (Ab)
0.33 (Be)
0.43 (Abe)
NA
0.89 (Aa)
3 mM oxalate
0.46 (Aa)
NA
NA
NA
0.39 (Cab)
Mehlich 1
NA
0.16 (Cb)
0.17 (Bb)
NA
0.33 (Ca)
“Significant differences (P<0.05) between extractants within each water potential and
horizon (upper case letters down columns)
bSignificant differences (P<0.05) between water potentials within each extractant and
horizon (lower case letters across rows)
CNA - missing data

Kp factor
33
1.2
-0.1 -3 -8 -15 -1000
Water Potential (kPa)
0.5 MNaHCOs
B
0
I
â–¡
a
1 mM oxalate
2 mM oxalate
3 mM oxalate
Bray & Kurtz
Mehlich 1
Figure 2-2. Total Kp factors by extractant within each water potential in the A horizon

K„ factor
34
Figure 2-3. Inorganic Kp factors by water potential within each extractant for the A
horizon. NaHC03 = 0.5 MNaHCC>3, Oxl = 1 mMoxalate, 0x2 = 2 mM
oxalate, 0x3 = 3 mM oxalate, and BK = Bray and Kurtz

35
Table 2-5. Comparison of inorganic Kp factors by horizon within each water potential for
each extractant
Horizon
-0.1 kPa
-3 kPa -8 kPa -15kPa
-1000 kPa
0.5 MNaHCCh
A
0.65 (ba)
0.42 (b)
0.35(b) 0.45(b)
0.38 (b)
E
0.99 (a)
0.75 (a)
0.60 (a) 0.73 (a)
0.73 (a)
Bh
0.36 (c)
0.27 (c)
0.33(b) NAb
0.72 (a)
1 mM oxalate
A
0.72 (a)
0.53 (b)
0.30(b) 0.41 (b)
0.51 (a)
E
0.66 (a)
0.95 (a)
0.53 (a) 0.70 (a)
0.71 (a)
Bh
0.15(b)
0.13(c)
0.17(b) NA
0.13(b)
2 mM oxalate
A
0.71 (a)
0.47 (b)
0.28(b) 0.48(b)
0.60 (b)
E
0.85 (a)
0.90 (a)
0.58 (a) 0.68 (a)
0.86 (a)
Bh
0.25 (b)
0.17(c)
0.23 (b) NA
0.18(c)
3 mM oxalate
A
0.67 (a)
0.65 (b)
0.31(b) 0.49(a)
0.56 (b)
E
0.74 (a)
0.91 (a)
0.48 (a) 0.64 (a)
0.83 (a)
Bh
0.45 (b)
0.28 (c)
0.30(b) NA
0.22 (c)
Bray and Kurtz
A
0.39 (b)
0.29 (b)
0.34(a) 0.51(a)
0.28 (b)
E
0.79 (a)
0.55 (a)
0.30 (b) 0.42 (b)
0.59 (a)
Bh
NDC
ND
ND ND
ND
Mehlich 1
A
0.22 (b)
0.21 (b)
0.34(a) 0.18(b)
0.14(b)
E
0.43 (a)
0.35 (a)
0.30 (a) 0.28 (a)
0.28 (a)
Bh
0.16(b)
0.11 (c)
0.14(b) NA
0.21 (ab)
aSignificant differences (P<0.05) between horizons within each water potential and
extractant
"NA - missing data
CND - data not determined

K„ factor
36
Figure 2-4. Inorganic Kp factors for the A, E, and Bh horizons within each water potential
using 3 mM oxalate as an extractant

37
Table 2-6. Comparison of total Kp factors by horizon within each water potential for each
extractant
Horizon
TIT , . . • 1
-0.1 kPa
-3 kPa -BkPa -15kPa
-1000 kPa
0.5 MNaHCCb
A
0.91 (aa)
0.74 (a)
0.63 (a)
0.53 (a)
NAb
Bh
0.43 (b)
0.55 (b)
0.40 (b)
NA
0.78
1 mM oxalate
A
NA
0.59 (a)
0.38 (a)
NA
0.51 (a)
Bh
0.23
0.17(b)
0.17(b)
NA
0.21 (b)
2 mM oxalate
A
0.97 (a)
0.76 (a)
0.44 (a)
0.60
0.82 (a)
Bh
0.55 (b)
0.33 (b)
0.33 (a)
NA
0.89 (a)
3 mM oxalate
A
0.74 (a)
0.77 (a)
0.43 (a)
0.59
NA
Bh
0.45 (b)
0.26 (b)
0.10(b)
NA
0.39
Bray & Kurtz
A
0.41
0.34
0.38
0.86
0.44
Bh
NDC
ND
ND
ND
ND
Mehlich 1
A
0.22
0.23 (a)
0.22 (a)
0.29
0.26 (a)
Bh
NA
0.16(a)
0.17(a)
NA
0.33 (a)
“Significant differences (P<0.05) between horizons within each water potential and
extractant
'’NA - missing data
CND - data not determined

38
Table 2-7. Significant differences (P<0.05) between the inorganic P and total P Kp factors
for the A and Bh horizons by extractant and water potential. Significant
differences indicated by an
Water potential
-0.1 kPa
-3 kPa -8 kPa -15 kPa
-1000 kPa
Extract
A horizon
0.5 MNaHC03
*
* *
1 mM oxalate
*
2 mM oxalate
*
*
*
3 mM oxalate
* * *
Bray & Kurtz
*
*
Mehlich 1
*
*
Bh horizon
0.5 MNaHC03
* NDa
1 mM oxalate
*
ND
*
2 mM oxalate
*
* * ND
*
3 mM oxalate
* ND
Mehlich 1
ND
*
“ND - not determined

Table 2-8. Inorganic Kp factors measured in the “test” horizons. Microbes were grown from the original horizon, added to the
test horizon, and the Kp factor was measured in the test horizon. For example, microbes were grown from the A horizon at —8
kPa and added to samples in each of the test horizons.
Original
horizon
“Test”
horizon
Kp
factor
Original
horizon
“Test”
horizon
Kp
factor
Original
horizon
“Test”
horizon
Kp
factor
A (-0.1 kPa)
0.35
E (-0.1 kPa)
0.83
Bh (-0.1 kPa)
0.26
A (-3 kPa)
0.30*
E (-3 kPa)
0.92
Bh (-3 kPa)
0.22*
A (-8 kPa)
A (-8 kPa)
0.36
E (-8 kPa)
E (-8 kPa)
0.94
Bh (-8 kPa)
Bh (-8 kPa)
0.28
A (-15 kPa)
0.37
E (-15 kPa)
0.90
Bh (-15 kPa)
0.23
A (-1000 kPa)
0.37
E(-1000kPa)
0.85
Bh(-1000kPa)
0.25
E (-8 kPa)
0.42*
A (-8 kPa)
0.85
A (-8 kPa)
0.34
Bh (-8 kPa)
0.46*
Bh (-8 kPa)
0.65*
E (-8 kPa)
0.35*
* Significantly different (PO.05) from the original horizon value
SO

40
Table 2-9. Comparison of microbial P concentrations with determined inorganic Kp
factors using 0.5 MNaHCC>3 and a Kp factor of 0.40. For comparison purposes, 5 kg P
ha'1 of microbial P is used.
A horizon
% Over
% Under
Water potential
with measured Kp,
with K0 - 0.40
estimation
estimation
-0.1 kPa
8
13
63
-
-3 kPa
12
13
8
-
-8 kPa
14
13
-
7
-15 kPa
11
13
18
-
-1000 kPa
13
13
0
0
E horizon
-0.1 kPa
5
13
160
-
-3 kPa
7
13
86
-
-8 kPa
8
13
63
-
-15 kPa
7
13
86
-
-1000 kPa
7
13
86
-
Bh horizon
-0.1 kPa
14
13
-
7
-3 kPa
19
13
-
32
-8 kPa
15
13
-
7
-15 kPa
NAa
13
-
-
-1000 kPa
7
13
86
-

41
Table 2-10. Regression equations for inorganic K„ factors for each extractant and horizon
Extractant
R2
Regression equation
A horizon
0.5 MNaHC03
0.65
K„= 0.489 - 0.127*log(r)<) + 0.038*log(t(/)2
1 mM oxalate (t|/ <= -8 kPa)
0.92
Kp = 0.696 - 0.243*log(t|/) - 0.219*log(V)2
1 mM oxalate (tg >= -8 kPa)
0.63
Kp = 0.346*log(vj/)°359
2 mM oxalate (t(/ <= -8 kPa)
0.85
Kp = 0.681 - 0.052* (vjt)
2 mM oxalate (vg >= -8 kPa)
0.70
Kp =0.370*log(v|/)°461
3 mM oxalate (t|t <= -8 kPa)
0.92
Kp = 0.664 - 0.008* (y)2
3 mM oxalate (t|/ >= -8 kPa)
0.64
Kp = 0.389*log(rt/)0 341
Bray & Kurtz (t|/ <= -15 kPa)
0.91
Kp = 0.396 - 0.282*log(v|/) - 0.008*log (tg)2
+ 0.283* log(v(r)3
Bray & Kurtz (\|/ >= -15 kPa)
0.95
Kp = 0.667 - 0.130*log(i|/)
Mehlich 1
0.55
Kp = 0.198 -0.00005* (r|/)
E horizon
0.5 MNaHC03
0.74
Kp = 0.788 - 0.158*log(t|/) + 0.046*log(v|/)2
1 mM oxalate (tg <= -8 kPa)
0.85
Kp = 1.158 - 0.131 *log(vj/) - 0.629*log(i)/)2
1 mM oxalate (t|r >= -8 kPa)
0.13
Kp = 0.520 + 0.60*log(v|/)
2 mM oxalate (t|t <= -8 kPa)
0.74
Kp = 0.913 -0.037(v|/)
2 mM oxalate (\|/ >= -8 kPa)
0.86
Kp = 0.500 + 0.121 *log(t|/)
3 mM oxalate (\|/ <= -8 kPa)
0.87
Kp = 1.138 - 0.190*log(y) - 0.592*log(»)/)2
3 mM oxalate (t|/ >= -8 kPa)
0.78
Kp = -0.287 + 1.059*log(t|/) - 0.228*log(t)/)2
Bray & Kurtz (i|/ <= -8 kPa)
0.98
Kp = 0.735 - 0.280*log(M/) - 0.228*log(v|/)2
Bray & Kurtz (vg >= -8 kPa)
0.67
Kp = 0.224 + 0.125*log(i)/)
Mehlich 1 (y <= -8 kPa)
0.87
Kp = 0.431 - 0.024(v)t) - 0.228*log(t(/)2
Mehlich 1 (vj/ >= -8 kPa)
0.12
Kp = 0.202 + 0.026* log(v|r)
Bh horizon
0.5 MNaHC03
0.92
Kp = 0.285 - 0.016*log(vj/) + 0.053*log(vg)2
1 mM oxalate (t|t <= -8 kPa)
0.02
Kp = 0.105 + 0.016*log(\j/) + 0.061 *log(t|t)2
1 mM oxalate (vj/ >= -8 kPa)
0.45
Kp = 0.188 - 0.019*log(vj/)
2 mM oxalate (v|/ <= -8 kPa)
0.67
Kp = 0.147 + 0.001 *log(»j/) + 0.106*log(t|/)2
2 mM oxalate (14/ >= -8 kPa)
0.54
Kp = 0.253 - 0.22*log(r)/)
3 mM oxalate
0.64
Kp = 0.361 - 0.056*log(vg)
Mehlich 1
0.73
Kp = 0.127 —0.017*log(\}/) + 0.015*log(r|/)2

K„ factors ^ K„ factor
42
0.8
0.7 *
0.6 i(
0.5
0.4 -
0.3 -
0.2 -
0.1 -
0.0 —
0.1
Kp= 0.489 - 0.127*log(t|t) + 0.038»log(V)2
R2 = 0.65
' * „ •
1 10 100 1000
Log water potential (-kPa)
0.8
0.7 •
0.6
0.5
0.4
0.3
= 0.664 - 0.008* (\)/)2
R2 = 0.92
V -
s
0.2 -
0.1 -
0.0
0.1 1 10
I
Kp = 0.389*log(tg)0341
R2 = 0.64
100 1000
Log water potential (-kPa)
Figure 2-5. Inorganic Kp regression equations in the A horizon for a) 0.5 MNaHCC>3 and
b) 3 mMoxalate, E horizon for c) 0.5 MNaHCC>3 and d) 3 mM oxalate, and
Bh horizon for e) 0.5 MNaHC03 and f) 3 mM oxalate

43
1.2 i
1.0 » ^
0.8 -
o
I 0.6 -
0.4 -
0.2 -
0.0
0.1
Kp = 0.788 - 0.158*log(\|/) + 0.046*log(t|/)2
R2 = 0.74
1 10 100 1000
Log water potential (-kPa)
1.2
1.0 -
0.8
o
| 0.6 ^
0.4
* »
X
Kp= 1.138 - 0.190*log(y)
A
â– ,592*log(v)/)
R = 0.87
Kp = -0.287+1.059*log(tg)
-0.228*log(t)t)2
R2 = 0.78
0.2 -
0.0 -I 1 1 1 1
0.1 1 10 100 1000
Log water potential (-kPa)
Figure 2-5 continued
• •

K„ factor ^ K„ factor
44
0.9 -
0.8
0.7 -
0.6 -
0.5 -
0.4
0.3
0.2 -
0.1 -
0.0 —
0.1
Kp= 0.285 -0.016*log(t|/) + 0.053*log(t|/)2 |
R2 = 0.92 _ *
1 10 100 1000
Log water potential (-kPa)
0.9
0.8
0.7
0.6
)
0.5
I
0.4
>
0.3 -
0.2 -
0.1 -
0.0 -
0.1
Kp = 0.361 - 0.056*log(\|/)
R2 = 0.64
10 100 1000
Log water potential (-kPa)
Figure 2-5 continued

CHAPTER 3
SEQUESTERING OF PHOSPHORUS FERTILIZER IN THE MICROBIAL BIOMASS
OF A COASTAL PLAIN SPODOSOL
Introduction
Forest productivity in much of the southeastern U.S. is phosphorus (P) limited
(Pritchett and Smith, 1975). The sandy, quartzic, surface horizons of Coastal Plain
Spodosols limit P retention (Zhou et al., 1997; Harris et al., 1996; Fox et ah, 1990a),
resulting in P mobility. Therefore, P that is not absorbed by plants or microorganisms
may be leached below the A horizon (Harris et al., 1996; Nair et al., 1998; Nair et al.,
1999) and beyond newly planted seedling root depth. Since soil P bioavailability is
inherently low, P fertilization is a common practice due to the significant growth
response it elicits in southern pines (Pritchett and Smith, 1975; Prichett and Comerford,
1982). Likewise, the application of nitrogen (N) in addition to P has a significant effect
on southern pine growth (Jokela and Steams-Smith, 1993). While root density at time of
planting is low and early uptake rates do not become significant until about three months
after planting (Smethurst et al., 1993), the microbial biomass may have the potential to
sequester P, maintain it in the soil horizon, and eventually make it available over time.
Microbial cycling and associated P transformations have been well studied
(Seeling and Zasoski, 1993; Gijsman et al., 1997; He et al., 1997b; Grierson et al., 1998)
and have been shown to be dependent upon the concentration of P in the soil (Brookes et
al., 1984). It has also been shown that microbial P changes with water potential (Sparling
et al., 1986; Skopp et al., 1990; Grierson et al., 1999), nutrient bioavailability (Clarholm,
45

46
1993; He et al., 1997b; Dilly and Nannipieri, 2001) and microbial biomass (Walbridge,
1991).
The purpose of this study was to determine the interaction between P fertilization
and soil water potential in determining microbial biomass and the sequestering of P as
microbial P. More specifically, the first objective was to investigate the influence of P
bioavailability on microbial biomass and to determine whether microbial biomass growth
in a Spodosol of the southeastern U.S. is P limited. The hypothesis was that P is limiting
to soil microbial growth. The second objective was to estimate the immobilization and
retention of P fertilizer by the microbial biomass and test the hypothesis that microbial
biomass could immobilize and retain significant quantities of P fertilizer. The third
objective was to investigate how soil water potential affected microbial uptake and P
fertilizer retention. The hypothesis tested here is two fold. It first states that microbial
biomass at water potentials promoting poor aeration will immobilize less fertilizer P than
those near field capacity. Secondly, it states that microbial biomass at field capacity will
immobilize more fertilizer P than that at drier water potentials (i.e. -1 OOOkPa).
Methods
Study Area and Field Sampling
The study area was located 33 km northeast of Gainesville, FL. The site was a 16
ha managed slash pine plantation (Pinus elliottii var. elliottii Engelm.) that was clearcut
April 1994, bedded in September and November 1994, and replanted to slash pine in
January 1995. In February 1995, 85 g ha"1 of imazypyr was applied as Arsenal in 1.5 m
wide bands on the planted beds for weed control. The soil is a sandy, siliceous, thermic
Ultic Alaquod, mapped primarily as Pomona fine sand and sand. The average annual

47
temperature is 21 °C, and the long-term average annual rainfall is approximately 1330
mm (Soil Conservation Service, 1995).
Soil was randomly collected from the 15 cm thick A horizon across a subsection
(approximately 2 ha) of the study area in July 1996 with a 7.5 cm diameter soil auger.
Approximately 3 kg of soil were collected from randomly selected points from
approximately 20 auger holes. The soil was sieved to pass a 2 mm screen and air-dried.
Sub-samples containing 800 g of soil were incubated in triplicate bags at 28 °C at five
water potential treatments of -0.1, -3, -8, -15, and -1000 kPa for 10 days. Water potential
was kept constant throughout the incubation period by weighing the samples and adding
double deionized water when required. These water potentials were based on results
from P mineralization studies that evaluated mineralization rate versus soil water
potential for a similar soil (Grierson et al., 1999).
Phosphorus fertilizer treatments of 0 kg P ha'1, 30 kg P ha'1, 60 kg P ha"1, and 100
kg P ha~' (or 0, 80, 120, and 230 pg P g'1 soil) as triple superphosphate granules were
added to each water potential treatment. An additional fertilizer treatment of
diammonium phosphate (DAP) was added to the study, equivalent to 640 pg P and 590
pg N g'1 soil. This high fertilizer treatment was added to determine the quantity of P that
could be incorporated when N is not limiting microbial growth. Although carbon may
also be limiting in this system, it was not considered as a factor for this experiment. The
DAP treatment does not reflect a commercial application of fertilizer at this stage of stand
development which would be in the range of 40 to 50 kg P and N ha"1 (Kidder et al.,
1987).

48
Triplicate samples from each bag were taken at 0, 3, 7, 14, 28, 49, and 77 days after
fertilizer addition and analyzed for microbial P, microbial C, soil moisture content, and
pH. Moisture content was measured after drying the samples for 24 hours at 105 °C ,
and pH was measured in a 2:1 watensoil solution. Triplicate samples for microbial P
analysis and for microbial C analysis were removed from each treatment bag for
fumigation. Liquid chloroform was added to each sample, sealed for 24 hours, after
which the chloroform was allowed to evaporate. Microbial P was measured with 3 mM
oxalate extraction at a 1:10 soihsolution ratio with a shaking time of 10 minutes (Chapter
2). Microbial C was measured using the ninhydrin-reactive nitrogen method (Amato and
Ladd, 1988). Unfumigated triplicate samples were also taken at the same time as the
fumigated and immediately measured for both microbial P and microbial C. Microbial P,
the quantity of P in the microbial biomass, was defined as:
[P extracted from fumigated soil - P extracted from unfumigated soil]/Ap (Eq. 3-1)
by Brookes et al. (1982). The Kp was determined in a previous study and is specific for
each water potential (Chapter 2). Microbial C, the quantity of carbon in the microbial
biomass, was determined by the method from Amato and Ladd (1988) and is defined as:
[ninhydrin-reactive N in fumigated soil - ninhydrin-reactive N in unfumigated
soil]*21 (Eq. 3-2)
Statistical Analysis
Statistical differences were determined using SAS version 8.1 (The SAS Institute,
2001) using a three factor mixed ANOVA model. For each sample bag, the least-squared
means were analyzed for significant differences (PO.05) by repeated measures analysis
of variance with a first order autoregressive covariance structure. Logarithmic
transformations were applied to microbial P and microbial C values in order to normalize

49
the variance. Microbial P, microbial C, and microbial C:P ratios were analyzed for
significant differences, (P<0.05), within the main effects (water potential, treatment, and
time) and among effects (Appendix B).
Results and Discussion
Objective 1: Investigate the Influence of P Bioavailabilty on the Microbial Biomass
Microbial C ranged from IB to 302 pg C g'1 soil in the control (no P added) (Table
3-1). This range was similar to other studies reporting microbial C (Chauhan et al., 1981;
Saggar et al., 1998). Extracted labile inorganic P (P¡) for the control ranged from 3.9 to
4.8 (-0.1 kPa), 4.5 to 5.5 (-3 kPa), 3.7 to 5.0 (-8 kPa), 0.7 to 2.8 (-15 kPa), and 2.2 to 3.6
(-1000 kPa) pg g'1 soil (Figure 3-1). In a study using similar soil and water potentials,
Grierson et al. (1999) reported comparable solution P¡ concentrations using KC1 as the
extractant. Brookes et al. (1984) reported solution P¡ ranging from 3.1 to 84.8 pg P g'1
soil in a variety of soils. Some of the highest P¡ values were reported by Chauhan et al.
(1981) who measured 285 pg P g'1 in an Ap horizon from a sandy loam. Comparatively,
this soil was low in solution P¡.
Microbial C was not affected by the P-only fertilizer treatments at any sampling
time when evaluated within a soil water potential, except in the driest soil at the end of
the experiment (Table 3-1; Appendix C, Figure C-l). Soil at -3 kPa provided an example
of the effect of P fertilization on microbial C (Figure 3-2). After a few days, the fertilizer
treatment had significantly affected microbial C, but there was no trend with time as
some days were significantly higher and some significantly lower than the control. The
overall trend of these data indicated that the microbial biomass was not P limited even

50
though the soil had low labile P¡ levels. Therefore, the first hypothesis, which stated that
P was limiting microbial growth, was negated.
The microbial population immobilizes phosphorus released through microbial
mineralization and turnover, and little may be available to plants (Tate et al., 1991).
Therefore, in soils with low P¡_ like this Spodosol, the microbial biomass may be
immobilizing enough P to sustain its activity but not initially supply P to the pine
regenerating on the site.
Others have also confirmed that microbial C was not P limited on different sites
(Chauhan et al., 1981; Prescott et al., 1992; Bauhus and Khanna, 1994; Joergensen and
Scheu, 1999). Bauhus and Khanna (1984) added 100 kg P ha'1 as superphosphate with
no change in microbial C on an acidic, sandy soil with low total P (P,), but the authors
determined that microbial carbon dioxide (C02) release (i.e. microbial activity) increased.
Parfitt et al. (1994) reported that microbial C in another sandy soil was not influenced by
P fertilizer even when it was added at rates up to 100 kg P ha'1. Bolán et al. (1996) also
reported that microbial C was not affected by a range of single superphosphate
applications (15-60 kg P ha'1) in laboratory experiments.
However, microbial C increased in the Bolán et al. (1996) 8-year field study due to
increases in soil organic matter, which resulted from increased plant growth promoted by
fertilization. In contrast, Saggar et al. (1998) determined that microbial C decreased after
P-only fertilizer addition. The current study showed a similar response over the first 28
days when the water potential was maintained at -15 kPa. The large increase observed
towards the end of this study within the two driest soils indicated a delayed response to P
only fertilization. Why this occurred is not known; nevertheless the response is too large

51
to ignore. Because this response was observed in the two dry soil conditions, it would
not seem to be experimental error. A possible explanation is that the increase is due to
slow growing microorganisms.
In contrast to the P-only fertilizer treatments, the DAP treatment increased
microbial C (Table 3-2), presumably in response to the N addition. This increase
continued to be significantly higher than the 100 kg P ha'1 treatment and the control
throughout the experiment’s duration and ranged between a low of a 291% increase (day
3, -1000 kPa) to a high of 36,887% increase (day 49, -8 kPa). Other studies reported that
additions of N increased microbial C when added along with P (Ghosal and Singh, 1995;
Hossain et al., 1995). The rate of DAP was extremely high and meant to give a glimpse
of how high microbial C could be increased. These soils support extremely high levels of
microbial biomass under high nutrient regimes. Microbial biomass, under the right
moisture regime exceeded 3 mg g’1 soil (0.3%). While one would not expect to reach
these levels in sandy Spodosols under normal management regimes, they do provide a
sense of what this soil is capable of supporting if used under bio-solid management with
high rates of N and P.
Objective 2: Estimate the Immobilization and Retention of P Fertilizer by the Soil
Microbial Biomass
Microbial response to P fertilization may be different for growth and P uptake,
since P uptake does not require microbial biomass increase. In this study, microbial P
response to P-only fertilization was in fact unrelated to the microbial C response.
Microbial P did respond to treatment.
While microbial P in the control did not change significantly with time, microbial P
increased in response to rates of P addition (Table 3-3; Appendix C, Figure C-2).

52
Microbial P at -0.1 kPa water potential illustrates this response (Figure 3-3). Microbial P
peaked within one week of P-only fertilizer additions (Appendix C, Figure C-3).
The 30 kg P ha'1 treatment peaked on day 3 for all levels of water potential (Figure
3-4). In the higher P-only treatments, microbial P peaked on day 3 in the three wetter
water potentials (-0.01 to -8 kPa) and on day 7 in the two drier water potentials (-15 and
-1000 kPa). After this initial peak, microbial P tended to decrease over time. In the two
wettest soils (-0.1 and -3 kPa), the unfertilized condition continued to be significantly
lower than the fertilizer treatments. In the other water potentials, the control was similar
to either the 30 or 60 kg P ha'1 treatments after the initial peak. The 100 kg P ha'1
treatment, while significantly different from the control, was often similar to the other P
treatments, yet the tendency was for this treatment to have the highest quantity of
microbial P. This may have been due to the high variability, which may have been due to
the use of fertilizer granules instead of ground fertilizer. Many samples had to be
declared missing due to extremely high P concentrations, which was assumed to be due
to fertilizer granule remnants.
A diminishing returns pattern for microbial P was demonstrated as the P addition
rate increased (Table 3-4), suggesting that the microbial biomass in this soil can only
immobilize a limited concentration of P under these conditions. This level was estimated
to be between 27 and 52 mg P kg'1 soil or 45 to 86 kg P ha'1. This may also indicate a
limiting factor, such as N or C, limits additional P immobilization. The decrease in
microbial P over time is consistent with the results of Clarholm (1993) and Grierson et al.
(1998) and may reflect the limited microbial P storage in this surface soil when P is non¬
limiting.

53
Other studies have documented microbial P increases with P fertilizer addition
(Chauhan et al., 1981; Haynes and Swift, 1988; Parfitt et al., 1994; He et al., 1997a;
Qualls and Richardson, 2000; Schneider et al., 2001). Haynes and Swift (1988) added
500 mg P g'1 soil as Ca(H2P04)2 to an acidic silt loam and reported that microbial P
increased to twice the quantity determined in the control and continued at these levels
throughout the experiment. He et al. (1997a) measured microbial P increases of over
three times the magnitude in the control, from approximately 3 to 10 mg P kg"1 soil, after
adding nearly 400 mg P kg'1 soil of carbonate-substituted phosphate rock to an acid loam.
Microbial P was still increasing at the end of their study (60 days). After adding 50 mg
kg’1 soil of triple superphosphate (100 kg ha’1), Schneider et al. (2001) determined that
microbial P doubled, from 49 to 104 mg P g’1 soil, in soils with a 50 percent or higher
adsorption capacity. In this study, microbial P increased from six to 18 times after the
230 mg P kg’1 soil (100 kg ha'1 of triple superphosphate) was added and was still three to
six times higher than the control at the end of the study. Luxury uptake and retention of
P by microbes has been documented (Fuhs and Chen, 1975; Khoshmanesh et al., 2002).
The microbial biomass in this study also demonstrated the same capability.
In soils with very little or no P sorption capacity, such as this study’s soil,
biological control of P leaching may be a factor in retaining P within the root zone
following fertilization and rainfall leaching events. The microbial biomass in the control
immobilized from 3 to 13 kg P ha'1, with the wetter soils containing the lowest quantity
of P. The annual aboveground uptake of a young slash pine plantation is approximately
1.5 kg P ha’1 (Adegbidi et al., in review), and a semi-mature slash pine plantation’s
annual aboveground uptake of P is approximately 4 kg P ha'1 (Polglase et al., 1992). The

54
microbial biomass without fertilization holds enough P to supply the P nutrient demands
of a slash pine stand, especially in the drier soils. The quantity of P sequestered would be
sufficient to supply the needs of a pine plantation if it was slowly released over time due
to microbial turnover and if microbial turnover was timed with plant P demand.
One contribution of the microbial biomass may be controlling the loss of P
fertilizer due to leaching. Within a week, the microbial biomass immobilized from 17 to
52 mg P kg’1, equivalent to 9 to 29 kg P ha'1, in soil for a range of water potentials. The
microbial biomass was able to retain more than enough P for a growing pine plantation,
even in the wettest conditions. Even after 77 days, the microbial biomass still held from
2 to 11 kg P ha"1. The percentage of P fertilizer still sequestered on day 77 was 4 to 17
%, 3 to 9 %, and 2 to 9 % of the 30, 60, and 100 kg P ha'1 treatments, respectively (Table
3-5). Given these results, the second hypothesis, which stated that microbial biomass
could retain significant amounts of fertilizer P, was confirmed.
Phosphorus mineralization has been reported to increase with fertilization on
similar soils (Polglase et al., 1992; Grierson et ah, 1998; Grierson et ah, 1999). In these
studies, P mineralization was related to soil organic matter P, not microbial P (Grierson et
ah, 1998). However, the P released from the microbial biomass via turnover, and the
increased mineralization due to fertilization, could combine to provide increased P
bioavailability. A significant quantity of this P may be preserved from leaching due to
biomass immobilization.
With the high DAP treatment, microbial P was significantly increased throughout
the study (Table 3-5). DAP elicited a continued increase in microbial P until days 14 to
28, after which it continued to be significantly higher throughout the experimental

55
duration. Microbial P increased up to 80 mg P kg"1, equivalent to 44 kg P ha"', at the
highest quantity and still retained 39 to 45 mg P kg'1, equivalent to 21 to 25 kg P ha"1, at
the end of the study.
The lack of response in microbial C, combined with the significant effect of P in
increasing microbial P, is further supported by the microbial C:P ratios (Table 3-6). As
soon as fertilizer was added, the microbial C:P ratio decreased in all fertilizer treatments
although they were only significantly different for the two wettest soils (-0.1 and -3 kPa).
Lack of significant differences may be due to the high variability of the ratios. The ratios
ranged from 19:1 to 202:1 before fertilizer addition. Immediately after fertilizer addition,
the microbial C:P ratios dropped dramatically, especially in the wetter soils, from 2:1 to
30:1 in the P-only fertilizer treatments and from 13:1 to 59:1 in the DAP treatments. The
ratios in the P-only fertilizer treatments continued to be much lower than the control, due
to the immobilization of P by the microbial biomass without the increase in microbial
population. The significant decrease in the microbial C:P ratios after fertilization
indicates that microbial P may be easily mineralized for increased P cycling (Parfitt et al.,
1994) due to microbial turnover (Cole et al., 1978). The DAP ratios were higher than the
P-only ratios, but that would likely be due to the increase in microbial biomass along with
the immobilization of P.
Although the microbial biomass in the surface horizon of this Spodosol was not P
limited, a significant quantity of P fertilizer was immobilized and sequestered under
laboratory conditions for more than 77 days. Particularly in the absence of understory
vegetation that is characteristically reduced in intensive forest management, microbial
biomass should be further investigated for its ability to sequester and eventually release

56
P. The pattern of release will determine how useful this is in increasing the efficiency of
P fertilization.
Objective 3: Investigate How Soil Water Potential Affects Microbial Uptake and P
Fertilizer Retention
In the control treatment, microbial P at the -15 kPa water potential was higher than
the other water potentials, while microbial P in the -0.1 kPa soil was usually lower than
the other water potentials (Table 3-7; Figure 3-5). The two drier soils (-15 and -1000
kPa) were significantly higher than the two wettest soils (-0.1 and -3 kPa) at nearly every
sampling date. With decreasing water potential, the microbial community changes from
an aerobic population to a population dominated by anaerobic and facultative
microorganisms. Microbial activity has been reported to be higher in aerobic soils
(Orchard and Cook, 1983; Lee et ah, 1990), which may explain the higher microbial P in
the control at -15 kPa.
Prior to P fertilization, microbial P exhibited significant differences due to water
potential. After fertilization, few significant differences were observed. These
differences did not depict a consistent pattern (Appendix C, Figure C-4). It was
consistent that, after P fertilizer addition, microbial P in all water potentials increased
significantly. More P was taken up by the microbial biomass in the soil at -0.1 kPa,
increasing 20 to 32 times, while the drier condition promoted only a four to nine times
increase. Even with such a large increase, microbial P in the saturated water potential was
similar to microbial P in the other water potentials after day 3. These results confirm that
the last two hypotheses are incorrect when stating that microbial immobilization of P is
less in saturated soils and more in drier soils.

57
The surficial water table in Spodosols fluctuates widely during the year. In an
average year, the shallow water table may be less than 25 cm from the soil surface for
one to three months, between 25 and 100 cm for six months, and exceeding 100 cm
during the dry season (Soil Conservation Service, 1985). Microbial P is significantly
different between water potentials before fertilization; however, microbial P becomes
similar after fertilization due to the greater immobilization of P in the higher water
potentials. The differences in microbial P before and after fertilization may be due to
changes in microbial activity after addition of fertilizer. Therefore, on systems with
fluctuating water tables, the amount of P fertilizer immobilized is dependent upon the
water table depth. When the water table is high, the microbial biomass should
immobilize more P fertilizer. But when the water table is low, and P may be leached
more quickly from the rooting zone due to high permeability, less P fertilizer is
immobilized.
Why microorganisms in the wetter soil with P fertilizer treatments immobilized
more P is not known, but must be due to changes in the microbial community. Soil water
potential has been shown to affect microbial community diversity (Brockman et al.,
1992). As soil water potential changes, so do fungal and bacterial ratios (Faegri et ah,
1977; Anderson and Domsch, 1975; Wilson and Griffin, 1975). Nutrient concentrations
in the microbial biomass are related to soil characteristics, including soil water potential
(Diaz-Raviña et ah, 1995).
There were significant differences between the microbial biomass at different water
potentials, even after fertilization (Table 3-8; Appendix C, Figure C-5). But again, like
microbial P after fertilization, there were no consistent trends. Studies have reported that

58
the influence of water potential on microbial C is variable, both affecting (Sarathchandra
et al., 1988) and not affecting (Zaman et al., 1999) microbial C. This study used similar
water potentials to those of Grierson et al. (1999) on a similar soil, with similar results.
Conclusion
The microbial biomass was not P limited for growth, even though pine growth on
similar soils is naturally P limited. However, whereas increasing rates of triple
superphosphate did not increase microbial C, immobilization of P was significant.
Microbial P increased between six and 18 times within three to seven days following
fertilizer additions. In the wetter soils, more P was taken up after fertilization, such that
microbial P was equivalent to the drier soils. Both microbial C and microbial P increased
dramatically when a large quantity of both N and P were added, demonstrating that this
system was N limited and the microbial biomass was capable of increasing significantly
and immobilizing a large quantity of P. Due to the inability of this soil to retain P in the
surface horizon, the microbial biomass would play a significant role in retention and
supply of P to plants through immobilization, along with the combination of
mineralization and microbial turnover. The question is how microbial turnover occurs
over time, and how is subsequent P mobilization timed with plant demand and the
development of an expanding southern pine root system.

Table 3-1. Comparison of microbial C by treatment within each day and by day within each treatment for each water potential
Day 0
Day 3
Day 7 Day 14 Day 28 Day 49 Day 77
Treatment
-0.1 kPa
Control
105 (AV)
184 (Aab)
427 (Aa)
105 (Bb)
213 (Ab)
180 (Aab)
171 (Aab)
30 kg P ha 1
161 (Aa)
173 (Aa)
62 (Cb)
180 (Aa)
261 (Aa)
164 (Aa)
175 (ABa)
60 kg P ha 1
209 (Aa)
174 (Aa)
172 (ABa)
170 (ABa)
209 (Aa)
179 (Aa)
126 (ABa)
100 kg P ha'1
46 (Be)
162 (Aa)
142 (Ba)
102 (Ba)
426 (Aa)
108 (Ab)
92 (Bbc)
-3 kPa
Control
200 (Aa)
128 (ABab)
302 (Aa)
209 (Aa)
61 (Bbc)
46 (Be)
83 (Abe)
30 kg P ha 1
109 (Ab)
90 (Bb)
137 (Aa)
217 (Aa)
67 (Bb)
76 (Bb)
54 (Ab)
60 kg P ha'1
129 (Ab)
98 (ABb)
181 (Aab)
258 (Aa)
111 (ABb)
243 (Aab)
62 (Ab)
100 kg P ha'1
198 (Aa)
199 (Aa)
138 (Aa)
183 (Aa)
137 (Aa)
139 (ABa)
64 (Aa)
-8 kPa
Control
122 (Aab)
53 (ABb)
136 (Aa)
32 (Ac)
140 (Aa)
18 (Be)
75 (Aab)
30 kg P ha 1
87 (ABa)
150 (Aa)
82 (Aa)
18 (Ab)
59 (Ba)
69 (Aa)
71 (Aa)
60 kg P ha'1
88 (Aa)
33 (Bbc)
83 (Aa)
80 (Aab)
76 (ABab)
27 (Be)
29 (Be)
100 kg P ha'1
72 (Bb)
67 (ABb)
116 (Aa)
NAC
98 (ABa)
157 (Aa)
NA
-15 kPa
Control
245 (Aa)
208 (Aa)
NA
NA
96 (Ab)
NA
250 (ABa)
30 kg P ha'1
231 (Aa)
148 (Aab)
61 (Ab)
NA
55 (Ab)
NA
156 (Bab)
60 kg P ha'1
237 (Aa)
155 (Aa)
112 (Bb)
NA
113 (Ab)
NA
217 (Ba)
100 kg P ha'1
223 (Aa)
212 (Aa)
100 (ABb)
i NA
17 (Ab)
NA
285 (Aa)
-1000 kPa
Control
112 (Aab)
284 (Aa)
56 (Bb)
171 (Aa)
NA
NA
77 (Bb)
30 kg P ha'1
63 (Be)
267 (Ab)
183 (Ab)
144 (Ab)
76 (Bbc)
NA
682 (Aa)
60 kg P ha'1
113 (Ab)
266 (Aa)
93 (Bb)
109 (Ab)
107 (Ab)
NA
475 (Aa)
100 kg P ha'1
66 (ABb)
332 (Aa)
70 (Bb)
95 (Ab)
88 (Bb)
NA
533 (Aa)
“Significant differences (P<0.05) between treatments within each day and water potential (upper case letters down columns)
bSignificant differences (PO.05) between days within each treatment and water potential (lower case letters across rows)
CNA - missing data
L/t
VO

60
â–  -0.1 kPa
â–¡ -3 kPa
â–¡ -8 kPa
â–¡ -15 kPa
Figure 3-1. Solution inorganic P in the control at each water potential

61
— ♦— day O
— * — day 3
— -a- - day 7
—m—day 14
— *— day 28
—•— day 77
Figure 3-2. Microbial C for each day in the -3 kPa soil at each P fertilizer treatment

Table 3-2. Comparison of microbial C between the control, 100 kg P ha-1, and DAP fertilizer treatments within each day for
each water potential
Day 0
Day 3
Day 7
Day 14
Day 28
Day 49
Day 77
-1 *i
Treatment
-0.1 kPa
Control
105 (B")
184 (B)
427 (B)
105 (B)
213 (B)
180 (B)
171 (B)
100 kg P ha 1
46 (C)
162(B)
142 (C)
102 (B)
426 (B)
108(B)
92(C)
DAPb
348 (Ac")
1338 (Aab)
1759 (Aab)
1255 (Ab)
-3 kPa
1555(Aab)
2908 (Aa)
891 (Ab)
Control
200 (A)
128(B)
302(B)
209 (B)
61 (C)
46 (C)
83 (A)
100 kg P ha'1
198 (A)
199 (B)
138(B)
183 (B)
137(B)
139(B)
64(A)
DAP
161 (Ac)
1716 (Ab)
1031 (Ab)
3433 (Aa)
-8 kPa
766 (Ab)
942 (Ab)
316 (Abe)
Control
122 (A)
53 (B)
136(B)
32
140 (B)
18(C)
75(A)
100 kg P ha'1
72 (B)
67(B)
116(B)
NAd
98 (B)
157(B)
NA
DAP
104 (Ac)
2122 (Aab)
1106 (Aab)
NA
-15 Kpa
919 (Ab)
5918 (Aa)
786 (Ab)
Control
245 (A)
208 (B)
ND
NA
96 (B)
NA
250 (B)
100 kg P ha'1
223 (A)
212 (B)
100 (B)
NA
17(C)
NA
285 (B)
DAP
207 (Ac)
9470 (Aa)
783 (Ab)
NA
-1000 kPa
549 (Abe)
NA
1720 (Ab)
Control
112 (A)
284 (B)
56(B)
171 (B)
NA
NA
77 (C)
100 kg P ha'1
66(B)
332 (B)
70 (B)
95 (B)
88 (B)
NA
533 (B)
DAP
157 (Ac)
1120 (Aab)
942 (Aab)
1206 (Aab)
768 (Ab)
NA
2953 (Aa)
"Significant differences (P<0.05) between treatments within each day and water potential (upper case letters down colums)
bDAP = 350 kg P and 352 kgN ha1
"Significant differences (P<0.05) between days within the DAP treatment for each water potential (lower case letters across rows)
NA - missing data

Table 3-3. Comparison of microbial P by P fertilizer treatment within each day and by day within each P fertilizer treatment
Day 0
Day 3
Day 7
Day 14
Day 28
Day 49
Day 77
T reatment
-0.1 kPa
Control
1.0 (Ab)
1.2 (Cab)
1.2 (Bab)
2.5 (Ca)
1.7 (Ba)
1.8 (Ba)
2.4 (Ca)
30 kg P ha 1
0.9 (Ab)
17.7 (Ba)
8.9 (Aa)
8.2 (Ba)
15.6 (Aa)
9.0 (Aa)
11.5 (ABa)
60 kg P ha 1
1.0 (Ac)
32.5 (Aa)
9.7 (Aab)
19.7 (ABab)
27.4 (Aa)
28.4 (Aa)
6.6 (BCb)
100 kg P ha1
1.3 (Ab)
24.0 (ABa)
40.4 (Aa)
23.6 (Aa)
37.7 (Aa)
22.4 (Aa)
14.3 (ABa)
-3 kPa
Control
1.8 (A"ab)
1.5 (Ba)
1.4 (Ca)
1.6 (Ba)
1.7 (Ba)
1.7 (Ba)
1.2 (Ba)
30 kg P ha 1
3.2 (Ab)
24.4 (Aa)
8.1 (ABab)
5.1 (Bb)
13.3 (Aa)
8.3 (Aa)
7.4 (Ab)
60 kg P ha 1
1.5 (Ac)
16.7 (Aa)
7.5 (BCbc)
11.6 (Aa)
25.9 (Aa)
13.6 (Aa)
9.1 (Ab)
100 kg P ha'1
1.4 (Ac)
27.1 (Aa)
25.2 (Aa)
20.3 (Aa)
17.7 (Aa)
NAC
4.1 (Ab)
-8 kPa
Control
3.6 (Aa)
4.9 (Ca)
5.2 (Ba)
5.3 (Ba)
3.5 (Ba)
4.3 (Aa)
2.9 (Ba)
30 kg P ha 1
1.5 (Ac)
21.3 (Ba)
16.7 (Ab)
14.8 (Ab)
11.6 (Ab)
5.2 (Ac)
5.0 (Be)
60 kg P ha'1
2.9 (Ab)
21.7 (ABa)
11.3 (ABa)
12.1 (ABa)
6.0 (Bb)
12.6 (Aa)
8.6 (ABab)
100 kg P ha'1
2.7 (Ac)
33.6 (Aa)
30.1 (Aa)
16.7 (Ab)
14.4 (Ab)
16.2 (Ab)
19.8 (Aa)
-15 kPa
Control
8.1 (Aa)
5.9 (Ca)
7.2 (Da)
5.9 (Ba)
4.7 (Aa)
NA
4.7 (Ba)
30 kg P ha’1
7.9 (Ab)
30.7 (Ba)
22.5 (Ca)
8.9 (Bab)
9.3 (Aab)
NA
13.0 (ABab)
60 kg P ha '
9.6 (Abe)
16.6 (Cab)
37.1 (Ba)
26.0 (Aab)
7.5 (Ac)
NA
14.5 (Abe)
100 kgPha1
7.8 (Ac)
37.1 (Aab)
52.2 (Aa)
21.3 (Ab)
16.8 (Ab)
NA
14.4 (Ab)
-1000 kPa
Control
4.0 (Aa)
3.5 (Ba)
5.0 (Ca)
4.5 (Ba)
4.2 (Aa)
NA
3.3 (Ca)
30 kg P ha'
3.7 (Ab)
19.2 (Aa)
13.9 (Ba)
14.6 (ABa)
19.1 (Aa)
NA
11.1 (ABa)
60 kg P ha'1
3.3 (Ad)
11.2 (ABbc)
30.9 (Aa)
18.0 (Aab)
10.0 (Abe)
NA
6.2 (BCc)
100 kgPha-'
3.7 (Ac)
23.4 (Ab)
20.0 (ABab)
30.1 (Aa)
9.6 (Ab)
NA
13.8 (ABab)
aSignificant differences (P<0.05) between treatments within each day and water potential (upper case letters down colums)
bSignificant differences (PO.05) between days within each treatment and water potential (lower case letters across rows)
‘T'JA - data missing
Os

64
â–  Control [
^30 kg P ha
â–¡ 60 kg P ha
â–¡ 100 kgPha
Figure 3-3. Microbial P by P fertilizer treatments over time in the -0.1 kPa soil

65
—• 0.1 kPa
—■— -3 kPa
—• --8 kPa
* -15 kPa
—* 1000 kPa
Days from beginning of study
Figure 3-4. Microbial P over time for each water potential in the 30 kg P ha'1 treatment

66
Table 3-4. Percent of P fertilizer immobilized and retained on day 77 by the microbial
biomass
P fertilizer
-0.1 kPa
-3 kPa
-8 kPa
-15 kPa
-1000 kPa
-% P immobilized
Peak day
30 kg P ha'1
30
42
30
45
29
60 kg P ha'1
29
14
15
27
24
100 kg P ha’1
13
14
16
25
14
Day 77
30 kg P ha'1
17
11
4
15
14
60 kg P ha'1
4
7
5
9
3
100 kg P ha'1
7
2
9
5
6

Table 3-5. Comparison of microbial P between the control, 100 kg P ha'1, and DAP fertilizer treatments within each day for
Day 0
Day 3
Day 7
Day 14
Day 28
Day 49
Day 77
v^g r g son;-
Treatment
-0.1 kPa
Control
1.0 (Aa)
1.2 (C)
1.2 (C)
2.5 (C)
1.7(C)
1.8(C)
2.4 (C)
100 kg P ha'1
1.3 (A)
24.0 (B)
40.4 (B)
23.6 (B)
37.7 (B)
22.4 (B)
14.3 (B)
DAPb
0.5 (Adc)
64.2 (Abe)
56.7 (Abe)
33.4 (Ac)
203.2 (Aa)
111.2 (Ab)
94.2 (Ab)
-3 kPa
Control
1.8(A)
1.5 (C)
1.4 (C)
1.6(C)
1.7 (B)
1.7
1.2 (C)
100 kg P ha'1
1.4(A)
27.1 (B)
25.2 (B)
20.3 (B)
17.7 (A)
NAd
4.1 (B)
DAP
1.9 (Ac)
49.5 (Ab)
37.1 (Ab)
122.5 (Aa)
16.1 (Ab)
NA
32.2 (Ab)
-8 kPa
Control
3.6(A)
4.9 (C)
5.2 (C)
5.3 (B)
3.5 (C)
4.3 (B)
2.9 (C)
100 kgPha'1
2.7 (A)
33.6(B)
30.1 (B)
16.7(B)
14.4 (B)
16.2 (B)
19.8 (B)
DAP
2.0 (Ac)
190.3 (Aa)
245.5 (Aa)
314.9 (Aa)
49.8 (Ab)
64.8 (Aab)
62.7 (Ab)
-15 kPa
Control
8.1 (A)
5.9(C)
7.2 (C)
5.9 (C)
4.7 (B)
NA
4.7 (C)
100 kg P ha'1
7.8 (A)
37.1 (B)
52.2 (B)
21.3 (B)
16.8(B)
NA
14.4 (B)
DAP
7.8 (Ab)
193.7 (Aa)
266.2 (Aa)
273.1 (Aa)
82.2 (Aa)
NA
186.4 (Aa)
-1000 kPa
Control
4.0 (A)
3.5 (C)
5.0(C)
4.5 (C)
4.2(B)
NA
3.3 (C)
100 kg P ha'1
3.7(A)
23.4 (B)
20.0 (B)
30.1 (B)
9.6(B)
NA
13.8(B)
DAP
2.2 (Ac)
107.9 (Aab)
102.0 (Aab)
207.8 (Aa)
77.0 (Ab)
NA
130.9 (Aab)
“Significant differences (P<0.05) between treatments within days and water potentials (upper case letters down columns)
bDAP = 350 kg P and 352 kg N ha'1
“Significant differences (P<0.05) between days within the DAP treatment within each water potential (lower case letters across
rows)
dNA - missing data
On

Table 3-6. Comparison of microbial C:P ratios by treatment within each day for each water potential
Day 0
Day 3
Day 7
Day 14
Day 28
Day 49
Day 77
Treatment
-0.1 kPa
Control
193:1 (AV)
266:1 (Ac)
375:1 (Aa)
50:1 (Ae)
163:1 (Ad)
80:1 (Ae)
84:1 (Ae)
30 kg P ha'
199:1 (Aa)
30:1 (Ba)
14:1 (Ba)
23:1 (Aa)
17:1 (Ba)
11:1 (Ba)
18:1 (ABa)
60 kg P ha'
202:1 (Aa)
7:1 (Be)
16:1 (Be)
13:1 (Ac)
12:1 (Be)
8:1 (Be)
20:1 (ABb)
100 kg P ha"1
86:1 (Ba)
7:1 (Bb)
20:1 (Bb)
13:1 (Ab)
10:1 (Bb)
2:1 (Bb)
14:1 (Bb)
DAP
152:1 (Ab)
26:1 (Ba)
31:1 (ABa)
38:1 (Aa)
8:1 (Ba)
38:1 (ABa)
28:1 (ABa)
-3 kPa
Control
112:1 (Ba)
100:1 (Aa)
46:1 (Aa)
140:1 (Aa)
31:1 (Aa)
34:1 (Aa)
76:1 (Aa)
30 kg P ha1
19:1 (Bb)
6:1 (Bb)
13:1 (Ab)
93:1 (ABa)
5:1 (Ab)
11:1 (Ab)
11:1 (Bb)
60 kg P ha'
63:1 (Ba)
26:1 (Ba)
13:1 (Aa)
33:1 (BCa)
5:1 (Aa)
101:1 (Aa)
12:1 (Ba)
100 kg P ha1
173:1 (Aa)
10:1 (Bb)
7:1 (Ab)
16:1 (Cb)
9:1 (Ab)
NAC
17:1 (ABab)
DAP
61:1 (Ba)
18:1 (Ba)
32:1 (Aa)
30:1 (BCa)
15:1 (Aa)
NA
10:1 (ABa)
-8 kPa
Control
33:1 (Aa)
12:1 (Aa)
27:1 (Aa)
9:1 (Aa)
44:1 (Aa)
4:1 (Aa)
30:1 (Aa)
30 kg P ha 1
44:1 (Aa)
5:1 (Aa)
7:1 (Aa)
3:1 (Aa)
8:1 (Aa)
27:1 (Aa)
25:1 (Aa)
60 kg P ha'1
31:1 (Aa)
9:1 (Aa)
7:1 (Aa)
7:1 (Aa)
31:1 (Aa)
2:1 (Aa)
3:1 (Aa)
100 kgPha'
25:1 (Aa)
2:1 (Aa)
7:1 (Aa)
NA
12:1 (Aa)
5:1 (Aa)
NA
DAP
48:1 (Aa)
21:1 (Aa)
18:1 (Aa)
NA
45:1 (Aa)
27:1 (Aa)
13:1 (Aa)
-15 kPa
Control
30:1 (Aa)
34:1 (Aa)
NA
NA
23:1 (Aa)
NA
53:1 (Aa)
30 kg P ha1
31:1 (Aa)
18:1 (Aa)
6:1 (Aa)
NA
7:1 (Aa)
NA
15:1 (Aa)
60 kg Pha'
25:1 (Aa)
12:1 (Aa)
3:1 (Aa)
NA
14:1 (Aa)
NA
15:1 (Aa)
100 kgPha*'
28:1 (Aa)
5:1 (Aa)
3:1 (Aa)
NA
NA
NA
27:1 (Aa)
DAP
32:1 (Aa)
59:1 (Aa)
5:1 (Aa)
NA
7:1 (Aa)
NA
3:1 (Aa)
-1000 kPa
Control
32:1 (Aa)
105:1 (Aa)
11:1 (Ab)
40:1 (Aa)
NA
NA
21:1 (Ba)
30 kg P ha'1
26:1 (Aab)
15:1 (Bab)
16:1 (Aab)
14:1 (Ab)
4:1 (Ab)
NA
63:1 (ABa)
60 kg P ha"
34:1 (Ab)
24:1 (Bb)
4:1 (Ab)
12:1 (Ab)
43:1 (Ab)
NA
100:1 (Aa)
100 kgPha'1
19:1 (Aa)
15:1 (Ba)
8:1 (Aa)
3:1 (Aa)
8:1 (Aa)
NA
38:1 (ABa)
DAP
51:1 (Aa)
13:1 (Ba)
6:1 (Aa)
12:1 (Aa)
27:1 (Aa)
NA
14:1 (Ba)
aSignificant differences (PO.05) between treatments within each day and water potential (upper case letters down columns)
bSignificant differences (P<0.05) between days within each treatment and water potential (lower case letters across rows)
CNA - data missing

69
Table 3-7. Comparison of microbial P by water potential within each day for each
treatment
Day 0
Day 3
Day 7
Day 14
Day 28
Day 49
Day 77
Potential
Control
-0.1 kPa
1.0 (D*)
1.2 (C)
1.2 (B)
2.5 (B)
1.7 (B)
1.8(B)
2.4 (A)
-3 kPa
1.8 (CD)
1.5 (BC)
1.4 (B)
1.6(B)
1.7(B)
1.7(B)
1.2 (B)
-8 kPa
3.6 (BC)
4.9 (A)
5.2 (A)
5.3 (A)
3.5 (AB)
4.3 (A)
2.9 (A)
-15 kPa
8.1 (A)
5.9 (A)
7.2 (A)
5.9(A)
4.7(A)
NAb
4.7 (A)
-1000 kPa
4.0 (AB)
3.5 (AB)
5.0 (A)
4.5 (A)
4.2 (A)
NA
3.3 (A)
30 kg P ha1
-0.1 kPa
0.9 (D)
17.7(A)
8.9 (A)
8.2 (AB)
15.6 (A)
9.0 (A)
11.5 (A)
-3 kPa
3.2 (B)
24.4 (A)
8.1(A)
5.1(B)
13.3 (A)
8.3 (A)
7.4 (A)
-8 kPa
1.5 (C)
21.3 (A)
16.7(A)
14.8 (A)
11.6 (A)
5.2 (A)
5.0 (B)
-15 kPa
7.9 (A)
30.7 (A)
22.5 (A)
8.9 (AB)
9.3 (A)
NA
13.0 (A)
-1000 kPa
3.7 (AB)
19.2 (A)
13.9 (A)
14.6(A)
19.1 (A)
NA
H I (A)
60 kg P ha"1
-0.1 kPa
1.0(C)
32.5 (A)
9.7 (B)
19.7(A)
27.4 (A)
28.4 (A)
6.6 (AB)
-3 kPa
1.5 (C)
16.7(B)
7.5 (B)
11.6(A)
25.9 (AB)
13.6 (A)
9.1 (AB)
-8 kPa
2.9 (B)
21.7 (AB)
11.3 (B)
12.1 (AB)
6.0 (B)
12.6 (A)
8.6 (AB)
-15 kPa
9.6 (A)
16.6 (AB)
37.1 (A)
26.05 (A)
7.5 (B)
NA
14.5 (A)
-1000 kPa
3.3 (B)
11.2 (AB)
30.9 (A)
18.0 (A)
10.0 (AB)
NA
6.2 (B)
100 kg P ha'1
-0.1 kPa
1.3 (D)
24.0 (A)
40.4 (AB)
23.6 (AB)
37.7 (A)
22.4 (A)
14.3 (AB)
-3 kPa
1.4 (C)
27.1 (A)
25.2 (B)
20.3 (AB)
17.7 (AB)
NA
4.1(B)
-8 kPa
2.7 (BC)
33.6 (A)
30.1 (B)
16.7(B)
14.4 (AB)
16.2 (A)
19.8(A)
-15 kPa
7.8 (A)
37.1 (A)
52.2 (A)
21.3 (AB)
16.8 (AB)
NA
14.4 (AB)
-1000 kPa
3.7 (AB)
23.4 (A)
20.0 (B)
30.1 (A)
9.6 (B)
NA
13.8 (AB)
DAP
-0.01 kPa
0.5 (C)
64.2 (B)
56.7 (B)
33.4 (B)
203.2 (A)
111.2 (A)
94.2 (AB)
-3 kPa
1.9(B)
49.5 (B)
37.1 (C)
122.5(A)
16.1 (C)
NA
32.2 (B)
-8 kPa
2.0 (B)
190.3 (A)
245.5 (A)
314.9 (A)
49.8 (B)
64.8 (A)
62.7 (AB)
-15 kPa
7.8 (A)
193.7(A)
266.2 (A)
273.1 (A)
82.2 (AB)
NA
186.7(A)
-1000 kPa
2.2 (AB)
107.9 (A)
102.0 (AB)
207.8 (A)
77.0 (B)
NA
130.9 (AB)
aSignificant differences (P<0.05) between water potentials within each day and treatment
hNA - data missing

70
â–  -0.1 kPa
â–¡ -3 kPa
â–  -8 kPa
â–¡ -15 kPa
â–  -lOOOkPa
Days from beginning of study
Figure 3-5. Microbial P by water potential in the control

71
Table 3-8. Comparison of microbial C by water potential within each day for each
treatment
Water
Potential
Day 0
Day 3
Day 7
Day 14 Day 28
Day 49
Day 77
Control
-0.1 kPa
105 (B*)
184 (AB)
427 (A)
105(A)
213(A)
180(A)
171 (AB)
-3 kPa
200 (AB)
128 (BC)
302 (A)
209 (A)
61(B)
46 (B)
83 (B)
-8 kPa
122 (B)
53 (C)
136 (B)
32(B)
140 (AB)
18(B)
75 (B)
-15 kPa
245 (A)
208 (AB)
NAb
NA
96(B)
NA
250 (A)
-1000 kPa
112(B)
284 (A)
56 (B)
171 (A)
30 kg P ha'1
NA
NA
77 (B)
-0.1 kPa
161 (AB)
173 (AB)
62(B)
180 (A)
261 (A)
164 (A)
175 (B)
-3 kPa
109 (B)
90 (B)
137 (AB)
217(A)
67(B)
76(A)
54 (B)
-8 kPa
87 (B)
150(B)
82 (AB)
18(B)
59 (B)
69 (A)
71 (B)
-15 kPa
231 (A)
148 (B)
61 (B)
NA
55 (B)
NA
156 (B)
-1000 kPa
63(B)
267 (A)
183 (A)
144 (AB)
60 kg P ha'1
76 (AB)
NA
682 (A)
-0.1 kPa
209 (A)
174 (A)
172 (A)
170 (AB)
209 (A)
179(A)
126 (BC)
-3 kPa
129 (AB)
98 (BC)
181 (A)
258 (A)
111 (AB)
243 (A)
62(C)
-8 kPa
88 (B)
33(C)
83 (A)
80 (B)
76(B)
27 (B)
29 (C)
-15 kPa
237 (A)
155 (B)
112(A)
NA
113 (AB)
NA
217(B)
-1000 kPa
113 (AB)
266 (A)
93 (A)
109 (B)
100 kg P ha'1
107 (AB)
NA
475 (A)
-0.1 kPa
46 (B)
162 (B)
142 (A)
102 (A)
426 (A)
108(A)
92(C)
-3 kPa
198 (A)
199 (B)
138(A)
183 (A)
137(B)
139(A)
64(C)
-8 kPa
72(B)
67(B)
116(A)
NA
98(B)
157(A)
NA
-15 kPa
223 (A)
212(B)
100 (A)
NA
17(B)
NA
285 (B)
-1000 kPa
66 (B)
332 (A)
70(A)
95 (A)
DAP
88 (B)
NA
533 (A)
-0.1 kPa
348 (A)
1338 (B)
1759(A)
1255 (B)
1555 (A)
2908 (B)
891 (B)
-3 kPa
161 (AB)
1716(B)
1031 (A)
3433 (A)
766 (B)
942 (B)
316(B)
-8 kPa
104 (B)
2122 (B)
1106 (A)
NA
919 (AB)
5918(A)
786 (B)
-15 kPa
207 (A)
9470 (A)
783 (A)
NA
549 (B)
NA
1720 (AB)
-1000 kPa
157 (AB)
1120 (B)
942 (A)
1206 (B)
768 (B)
NA
2953 (A)
"Significant differences (P<0.05) between water potentials within each treatment and day
bNA - data missing

CHAPTER 4
SUMMARY AND CONCLUSIONS
The microbial biomass represents an important component influencing nutrient
cycling and nutrient bioavailability. The acidic, sandy soils in the southeastern U.S. are
phosphorus (P) limited for forest production and hence are commonly fertilized with P.
The surface horizon of these soils have very little or no P retention capacity, resulting in
the unique condition where P fertilizer may be leached from the A horizon. The
microbial biomass may represent a significant sink and, later, a source of labile P for
plant uptake, particularly for soils with little or no P retention capacity. The ability of the
microbial biomass to immobilize and retain P fertilizer before it is leached below
seedling rooting depth would determine how important it might be as a source of
bioavailable P. Spodosols in the southeastern U.S. are defined by a fluctuating water
table that influences, along with rainfall, the water potential of the surface horizon. Since
microbial communities are linked to water potential, it is reasonable to assume that water
potential may also influence microbial immobilization of P fertilizer. To determine a
more accurate estimate of microbial P, a Kp factor, or correction value, is used. Kp factors
are dependent upon microbial communities, so the factors may also be affected by water
potential.
Realizing the interactions between microbial communities, biomass, and water
potential, the six objectives of Chapters 2 and 3 can be discussed under the four more
broadly stated objectives: 1) to determine the most appropriate extractant for the
determination of microbial Kp factors and for estimating microbial P on acidic Spodosols
72

73
of the Coastal Plain; 2) to determine if Kp changes with water potential and soil horizon
characteristics; 3) to determine if microbial biomass and microbial P respond to P
fertilizer and how those responses progress over time, and 4) to determine if water
potential affects immobilization and retention of P fertilizer.
Objective 1: Determine the Most Appropriate Extractant for the Determination of
Kp Factors and Estimating Microbial P on Acidic Spodosols of the Coastal Plain.
The hypothsis that 0.5 MNaHC03 (pH 8.5) would not be suitable for extracting
microbial P on acidic soils in Spodosols was accepted. Oxalate was found to be more
consistent in removing inorganic P (P¡) from the microbial biomass than the other
extractants, including NaHCCfy As the Bh horizon is dominated by amorphous Al-
oxides, oxalate extracted more microbial P and is better suited for extracting P; due to it’s
ability to replace P through ligand exchange and dissolution of Al-oxide surfaces. In the
A and E horizon, oxalate performed similarly to NaHC03 as most of the P¡ in these
horizons was water-soluble. However, the high pH (8.5) of NaHC03 dissolves organic
compounds that creates interference problems for colorimetric analysis. Therefore, due
to the improved P extraction and the ease of analysis, oxalate is recommended. Of the
oxalate concentrations tested, 3 mM oxalate was recommended due to its greater ability
to recover P¡, especially in the Bh horizon.
Objective 2. Determine if Kp Changes with Water Potential and Soil Horizon
Characteristics.
Kp factors were affected by water potential and other soil horizon characteristics,
nullifying the hypothesis that soil water potential would not cause changes in Kp factors.
The highest Kp factor was generally detected under the wettest soil condition, indicating
more P¡ was extractable from those microbial populations. The lower Kp factors occurred
in the A and E horizons near field capacity (-8 kPa), while in the Bh horizon, the lowest

74
Kp factor occurred in the -3 kPa soil. Significant differences in Kp factors were evident
between horizons at similar water potentials, with the E horizon providing the highest Kp
factors and the Bh horizon the lowest. Changes in dominant microbial species within the
population, along with changing bacterial to fungal ratios due to differences in water
potential and soil characteristics, are suggested as the cause for the changes in Kp factors.
This study recommends that a Kp factor must be measured for each soil condition to get
the most accurate estimate of microbial P.
Objective 3. Determine if Microbial Biomass and Microbial P Respond to P
Fertilizer and How Those Responses Develop Over Time.
No clear trend of P-only fertilization could be seen on microbial C, suggesting
that microbial biomass was not P limited. In contrast to microbial C, microbial P
responded quickly to the addition of P-only fertilizer. Microbial P increased significantly
three days following fertilization and then decreased over time after the initial
immobilization peak. Microbial P increased from six to 18 times after fertilization and
was three to six times higher than the control at the end of the study, indicating microbial
P would continue to be higher than the control over a longer period of time.
Microbial P increased with increasing P rates, but the lower P rates did not differ
from the control after day 3. The highest P rate was different than the control, but not
from the other P-only treatments. The non-linear increase in microbial P suggested an
upper limit of P that the microbial biomass could immobilize under these conditions,
approximately 45 to 85 kg P ha'1, depending on the water potential. When large
quantities of both nitrogen (N) and P were added, microbial C and microbial P responded
dramatically. This not only indicated that microbial biomass was N limited, but also that
the microbial biomass was able to immobilize a large quantity of P when made available

75
once the limiting factor, N, was removed. The microbial biomass was able to sequester
between 15 and 29 kg P ha'1 in the P-only fertilization and up to 44 kg P ha"1 when a
large quantity of both N and P was added.
The quantity of P immobilized by the microbial biomass was considerably more
than the annual demand of pine plantations. These data indicate that the microbial
biomass would be able to take up a significant quantity of P and retain it over time. This
labile P source would become slowly available to plants over time as microbial turnover
occurred.
Objective 4. Determine if Differing Water Potential Affects Immobilization and
Retention of P Fertilizer
Before fertilization, microbial P was lowest in the wettest soil and highest in the
soil maintained at -15 kPa. After fertilization, microbial P increased dramatically and
was similar among all water potentials. More P was immobilized by the microorganisms
in the wettest soil, with microbial P increasing 11 to 29 times more than the drier soils.
Factors that may account for this occurrence include differences in microbial
populations’ metabolic demand for P and sensitivity to limiting factors. Retention of P
in the microbial biomass did not seem to be affected by water potential.
Research Conclusions
This dissertation combined method evaluation and revision with investigations on
the role that microbial biomass has on sequestering P when plant biomass is not sufficient
to capture fertilization. The focus was on P fertilization of newly planted and herbicided
pine plantations developing on a typical flatwoods Spodosol of northern Florida. This
cover type and soil type represent a significant component of northern Florida and

76
southeastern Georgia where forest industry has a concentrated land base and pulp mills at
their highest density.
Phosphorus deficiencies are common on these soils so P fertilization is also
common. The Forest Soils program at the University of Florida has investigated a variety
of aspects P cycling in forested soils including work on fertilization practices, P uptake
by mature and young pine, organic P mineralization, inorganic P chemistry, and
microbial biomass changes due to long-term changes in forest productivity. This study
compliments those previous efforts and adds to the knowledge of: (1) how to measure
microbial P and (2) what is the potential of microbial P influencing the efficiency of P
fertilization practices.
The most adequate extractant for estimating microbial P in a sandy, acidic
Spodosol was 3 mM oxalate. The Kp factor for the most accurate estimate of microbial P
changed with soil horizon and soil water potential. It is recommended that Kp factors be
specific for changing soil conditions. Using an inaccurate Kp factor may cause significant
under or over estimations of microbial P. For example, if the Kp factor of 0.40 by
Brookes et al. (1982) was used for the A horizon at -0.01 kPa, microbial P would be
overestimated by 4 kg ha'1 in this soil. The microbial biomass in this soil at this stage of
stand development is not P limited but appears to be N limited. After fertilization, up to
three or more times the P than the annual demand by pine plantations will be sequestered
and held for several weeks. Although the microbial population may change due to
differences in water potential, P immobilization will not be affected. The sequestered P
would become slowly available to plants over time, but the timing of release with respect
to plant demand was not investigated and is an unknown.

77
Surprisingly, little information on Kp factors is available in the literature. While Kp
factors have been researched previously in the A horizon of soils having different
textures, prior to this study no information existed on how water potential affects Kp
factors or if Kp factors were influenced by soil horizons within the same soil profile. Kp
factors determined in previous studies were from neutral or alkaline soils. Prior to this
study, no information was available for acidic soils of the southeastern U.S.
This research strengthened and expanded the limited information pertaining to Kp
factors by demonstrating how significant differences resulted from varying water
potential and soil horizons in an acidic, sandy Spodosol. A standard method was revised
in order to make it more accurate for measuring microbial P in acidic soils. The method is
now simpler and more efficient in extracting P from the Bh horizon than the standard
extractant, 0.5 MNaHCC>3.
Few studies have researched the relationship between P-only fertilization and
microbial P, and even fewer have done so on forest soils; and there is little information
on microbial biomass or microbial P in Flatwoods soils. Prior to this study there was no
information on the influence that water potential has on microbial P sequestration of P-
only fertilization. Prior to this study, it was not known that microbial P was not limited
by P bioavailability in this soil type; and prior to this study it was not clear that microbial
biomass could sequester enough P from P fertilization to supply the demands of a young,
developing pine stand. This study has significantly increased our knowledge of microbial
P in forested soils of the southeastern coastal plain and provided a guide as to what would
be productive avenues to continue this type of research. These are itemized below.

78
Future Research
The above results do not answer all the potential questions regarding the role that
microbial biomass plays in fertilizer P sequestration and subsequent bioavailability to a
developing pine stand. Future avenues of research that are logical extensions of this
dissertation are suggested below:
1. Extending the results of this study, it seems reasonable to think that Kp factors
change with nutrient availability. Some microbial species may become more
dominant when they grow in a nutrient non-limiting environment. Since Kp is
related to microbial communities, this may cause changes in the Kp factor.
Measuring the Kp factors from soil with different rates of P fertilizer plus N and P
fertilizer should provide this information.
2. These data showed that microbial sequestration of fertilizer P was rapid, but the
time frame of these studies was too gross to adequately describe the kinetics of this
P absorption. A more refined time scale that defines these kinetics would better
describe the ability and rapidity of microbial P uptake. These kinetics are crucial if
one is to know if microbial uptake is in a competitive time frame with P leaching
following fertilization. A comparative study of these kinetics with and without
leaching events would further define how important P sequestering by the
microbial biomass can be.
3. Once the comparative kinetics are addressed, field tests of fertilizer events,
microbial sequestering, and the time subsequent release of microbial P to plants is
appropriate. Does microbial P release fertilizer P at a rate and in the appropriate
time frame to make the P available to developing pine. The mechanism of release
over time needs to be elucidated and tested under field conditions.
4. It was clear P did not limit microbial biomass. It was also clear that high rates of
DAP did overcome limitations to microbial biomass development. A factorial
approach to define what nutrient conditions limit microbial biomass development
and how the biomass responds to increasing nutrients would be useful. It could also
be done in conjunction with # 1 above.
5. Information on microbial biomass and microbial P in the spodic horizon is lacking
and should be addressed in both a laboratory and field study.

K„ factor
APPENDIX A
KP FACTOR FIGURES
1.0
0.8
0.6
0.4
0.2
0.0
Figure A-l. Inorganic Kp factors by extractant within each water potential for the a) A
horizon, b) E horizon, and c) Bh horizon
79

Kp factor Kp factor
80
Water potential (kPa)
0
â–¡
NaHC03
1 mM Oxalate
2 mM Oxalate
3 mil Oxalate
Bray & Kurtz
Mehlich 1
Water potential (kPa)
Figure A-1 continued

Kp factor Kp factor
81
a
-0.1 -3 -8 -15 -1000
Water potential (kPa)
0 NaHC03
â–¡ 1 mM Oxalate
0 2 mM Oxalate
â–  3 mM Oxalate
â–¡ Bray & Kurtz
â–¡ Mehlich 1
-15 -1000
Water potential (kPa)
Figure A-2. Total Kp factors by extractant within each water potential for the a) A horizon
and b) Bh horizon

Kp factor Kp factor
82
El-0.1 kPa
â–¡ -3 kPa
NaHC03 Oxl 0x2 0x3 BK Mehlich 1
Figure A-3. Inorganic Kp factors by water potential within each extractant in the a) A
horizon, b) E horizon, and c) Bh horizon NaHC03 = 0.5 MNalICO3, Oxl = 1
mM oxalate, 0x2 = 2 mM oxalate, 0x3 = 3 mM oxalate, and BK = Bray and
Kurtz

Kp factor
83
c
1.0
0.8 -
0.6 -
0.4 -
â–¡ -0.1 kPa
â–¡ -3 kPa
H -8 kPa
â–¡ -15 kPa
â–  -1000 kPa
0.2
0.0
NaHC03
Oxl 0x2 0x3 Mehlich 1
Figure A-3 continued

Kp factor Kp factor
84
a
1.2 -i
NaHC03 Oxl 0x2 0x3
BK Mehlich 1
â–¡ -0.1 kPa
â–¡ -3 kPa
@-S kPa
â–¡ -15 kPa
â–  -1000 kPa
0x3 Mehlich 1
Figure A-4. Total Kp factors by water potential within each extactant for the a) A horizon
and b) Bh horizon NaHC03 = 0.5 MNaHCOs, Oxl = 1 mMoxalate, 0x2 = 2
mM oxalate, 0x3 = 3 mM oxalate, and BK = Bray and Kurtz

K„ factor ^ K„ factor
85
a
Water potential (kPa)
â–¡ A Horizon
^ E Horizon
â–  Bh Horizon
Water potential (kPa)
Figure A-5. Inorganic Kp factors by horizon within each water potential in a) 0.5 M
NaHCC>3, b) 1 mM oxalate, c) 2 mM oxalate, d) 3 mil oxalate, e) Bray and
Kurtz, and f) Mehlich 1

K„ factor Kp factor
86
Water potential (kPa)
1.0
0.8
0.6
0.4
0.2
0.0
-0.1 -3 -8 -15
-1000
â–¡ A Horizon
M E Horizon
â–  Bh Horizon
Water potential (kPa)
Figure A-5 continued

K„ factor
87
1.0 -i
Water potential (kPa)
â–¡ A Horizon
H E Horizon
â–  Bh Horizon
Water potential (kPa)
Figure A-5 continued

Kp factor a- Kp factor
88
a
0.8
0.7 «
0.6 . ' ' ,
0.5 -
0.4
0.3 -
0.2 -
0.1
0.0
0.1
Kp= 0.489 -0.127*log(^) + 0.038*log(v)f)2
R2 = 0.65
* % •
1 10 100
Log water potential (-kPa)
É
1000
0.8
0.7
0.6
0.5
0.4 H
0.3
0.2 -
0.1
0.0
Kp = 0.696 - 0.243 *Iog(t|/) \*
- 0.219*log(y)2 •
R2 = 0.92
Kp = 0.346*log(t|/)°
R2 = 0.63
0.1
1 10 100
Log water potential (-kPa)
1000
Figure A-6. Regression curves for inorganic Kp factors in the A horizon for a) 0.5 M
NaHCOs, b) 1 mM oxalate, c) 2 mM oxalate, d) 3 mM oxalate, e) Bray and
Kurtz, and f) Mehlich 1

Kp factor o. K„ factor
89
0.8
0.7 •
0.8
0.7
0.6
0.5
0.4
0.3 -
0.2 -
0.1 -
0.0
• >
• '
A,, = 0.681 - 0.052* (y)
R2 = 0.85
Kp=0.370*log(t|/)0
R2 = 0.70
0.1
1 10 100
Log water potential (-kPa)
1000
0.8
0.7
0.6
► —
0.5
\
•
0.4
•
0.3 -
Kp = 0.664 - 0.008* (vp)
R2 = 0.92
0.2
0.1 -
0.0
Kp =0.389*log(v|/)0341
R2 = 0.64
0.1 1 10 100 1000
Log water potential (-kPa)
Figure A-6 continued

Kp factor «, K„ factor
90
e
0.8
0.7 -
0.6 -
0.5 -
Kp = 0.396 - 0.282*log(t|/) - 0.008*log (v|if
+ 0.283* log(vj/)3
R2 = 0.91 ,|.
• ' ■ ,
0.4
0.3
0.2
J
Kp = 0.667 -0.130*log(v|/) e
R2 = 0.95
0.1 -
0.0
0.1 1 10 100 1000
Log water potential (-kPa)
J.8
0.7 -
0.6 -
0.5 -
0.4
0.3 -
0.2 I
0.1 -
0.0 --
Kp = 0.198- 0.00005* (y)
R2 = 0.55
~ ' •
10 100 1000
Log water potential (-kPa)
Figure A-6 continued

K„ factor
91
1.2
1.0 *
0.8
0.6
0.4
0.2 -
0.0 --
0.1
Kp = 0.788 - 0.158*log(v|/) + 0.046*log(v(/)2
R2 = 0.74
1 10 100 1000
Log water potential (-kPa)
1.2 n
1.0
0.8,
S
Ǥ0.6
0.4 -
0.2 -
0.0
v«
*
Kp= 1.158 -0.131*log(v)/)- '
0.629*log(v|/)2 •
R2 = 0.92 #
^ Kp = 0.52 + 0.60*log(\j/)
R2 = 0.13
0.1
1 10 100
Log water potential (-kPa)
1000
Figure A-7. Regression curves for inorganic Kp factors in the E horizon for a) 0.5 M
NaHCC>3, b) 1 mM oxalate, c) 2 mM oxalate, d) 3 mM oxalate, e) Bray and
Kurtz, and f) Mehlich 1

K„ Factor o. K„ factor
92
i.2
1.0
0.8
0.6
0.4
0.2 -
0.0
t
K„ = 0.913- 0.037(t|/)
R2 = 0.74
Kp = 0.500 + 0.121 *log(t|/)
R2 = 0.86
0.1
1 '00
Log water potential (-kPa)
1000
1.2
1.0 -
0.8
0.6 -
0.4 -
Kp= 1.138-0.190*log(t|t) ' ^
- 0.592*log(H/)2 j" *
R2 = 0.87
Kp = -0.287 + 1.059*logO)
- 0.228*]og(t|t)2
R2 = 0.78
0.2 -
0.0 j T T I
0.1 1 10 100 1000
Log water potential (-kPa)
Figure A-7 continued

Kp factor «, K„ factor
93
1.2 -i
1.0
0.8
0.6
0.4
0.2 -
0.0
Kp = 0.735 -0.280*log(i|/)'
Kp = 0.224 + 0.125*log(\)r)
R2 = 0.67
- 0.228*log(\|/)
R2 = 0.98
0.1
1 10 100
Log water potential (-kPa)
1000
AT,, = 0.431 -0.024(y)
- 0.228*log(v|/)2
R2 = 0.87
Kp = 0.202 + 0.026*log(y)
R2 = 0.12
100
1000
Figure A-7 continued
10
Log water potential (-kPa)

Kp Factor Kp factor
94
a
0.9
0.8
0.7 -
0.6 -
0.5 -
0.4 "
0.3 -
0.2 -
0.) -
0.0 —
0.1
Kp = 0.285 - 0.016*log(t|/) + 0.053*log(v)2
R2 = 0.92
•
. t
1 10 100 1000
Log water potential (-kPa)
0.9 -
0.8 -
0.7 -
0.6
0.5 -
0.4 -
0.3 -
0.2 f
0.1
Kp = 0.105 + 0.016*log(t|/)
+ 0.061 *Iog(t)/)2
R2 = 0.02
0.0
0.1 1 10
Kp = 0.188- 0.019*log(t|/)
R2 = 0.45
- I
100 1000
Log water potential (-kPa)
Figure A-8. Regression curves for inorganic Kp factors in the Bh horizon for each
extractant a) 0.5 MNaHCCb, b) 1 mM oxalate, c) 2 mM oxalate, d) 3 mM
oxalate, and e) Mehlich 1

Kp factor ^ Kp factor
95
c
0.9
0.8 -
0.7
0.6
0.5 -
0.4 -
0.1 -
Kp = 0.147 + 0.001 *log(i|/) +
0.106*log(v|/)2
R2 = 0.67
Kp = 0.253 - 0.22*logO)
R2 = 0.54
0.0 -I 1 1 i—
0.1 1 10 100
Log water potential (-kPa)
0.9 -i
0.8 -
0.7 -
0.6 -
0.5 °
0.4 i,
0.3 -
0.2 -
0.1 -
0.0
0.1
Kp = 0.361 - 0.056*log(t|/)
R2 = 0.64
10 100
Log water potential (-kPa)
I
1000
:
1000
Figure A-8 continued

96
0.9
0.8
0.7 -
0.6 -
0.5
0.4
0.3
0.2
0.1 T
0.0
0.1
Kp = 0.127 -0.017*log(v|/) + 0.015*log(t|/)2
R2 = 0.73
1 10 100
Log water potential (-kPa)
1
1000
Figure A-8 continued

APPENDIX B
ANALYSIS OF VARIANCE TABLES
Table B-l. Analysis of variance table for inorganic Kr factors
Type 3 Tests of Fixed Effects
Num Den
Effect
DF
DF
F Value
Pr > F
horizon
2
140
853.72
<.0001
water
4
140
79.45
<.0001
extract
6
140
167.01
<.0001
horizon*water
7
140
24.44
<.0001
horizon*extract
11
140
28.43
<.0001
horizon* water* extract
63
140
6.98
<.0001

Table B-l continued
Least Squares Means
Standard
Effect
horizon
water (kPa)
extract
Estimate
Error
DF
t Value
Pr> ttl
horizon* water * extract
A
-0.1
BK
0.3875
0.03236
140
11.97
<.0001
horizon* water*extract
A
-0.1
DA
0.2153
0.03236
140
6.65
<.0001
horizon* water * extract
A
-0.1
NaHC03
0.6539
0.03236
140
20.21
<.0001
horizon* water* extract
A
-0.1
Oxl
0.7210
0.03236
140
22.28
<.0001
horizon* water*extract
A
-0.1
0x2
0.7091
0.03963
140
17.89
<.0001
horizon*water*extract
A
-0.1
0x3
0.6663
0.03236
140
20.59
<.0001
horizon* water*extract
A
-3
BK
0.2907
0.03236
140
8.98
<.0001
horizon* water* extract
A
-3
DA
0.2065
0.03236
140
6.38
<.0001
horizon*water* extract
A
-3
NaHC03
0.4186
0.03236
140
12.94
<.0001
horizon * water*extract
A
-3
Oxl
0.5301
0.03236
140
16.38
<.0001
horizon* water* extract
A
-3
0x2
0.4277
0.03963
140
10.79
<.0001
horizon*water* extract
A
-3
0x3
0.6476
0.03236
140
20.02
<.0001
horizon* water* extract
A
-8
BK
0.3431
0.03236
140
10.60
<.0001
horizon*water*extract
A
-8
DA
0.1857
0.03236
140
5.74
<0001
horizon*water*extract
A
-8
NaHC03
0.3482
0.03236
140
10.76
<0001
horizon*water* extract
A
-8
Oxl
0.2972
0.03236
140
9.19
<0001
horizon* water*extract
A
-8
0x2
0.2936
0.03963
140
7.41
<0001
horizon* water* extract
A
-8
0x3
0.3142
0.03236
140
9.71
<.0001
horizon* water*extract
A
-15
BK
0.5134
0.03236
140
15.87
<0001
horizon*water*extract
A
-15
DA
0.1838
0.03236
140
5.68
<.0001
horizon*water*extract
A
-15
NaHC03
0.4503
0.03236
140
13.92
<.0001
horizon* water*extract
A
-15
Oxl
0.4096
0.03236
140
12.66
<0001
horizon* water*extract
A
-15
0x2
0.4737
0.03963
140
11.95
<0001
horizon*water*extract
A
-15
0x3
0.4850
0.03236
140
14.99
<.0001
horizon* water*extract
A
-1000
BK
0.2750
0.03236
140
8.50
<0001
horizon* water*extract
A
-1000
DA
0.1441
0.03236
140
4.45
<0001

Table B-l. continued
Effect
horizon
water ikPat
extract
Standard
Estimate Error
DF
t Value
Pr > Itl
horizon* water* extract
A
-1000
NaHC03
0.3799
0.03236
140
11.74
<.0001
horizon * water* extract
A
-1000
Oxl
0.5074
0.03236
140
15.68
<.0001
horizon*water*extract
A
-1000
0x2
0.6329
0.03963
140
15.97
<.0001
horizon*water*extract
A
-1000
0x3
0.5559
0.03236
140
17.18
<.0001
horizon* water* extract
Bh
-0.1
DA
0.1613
0.03236
140
4.98
<.0001
horizon*water*extract
Bh
-0.1
NaHC03
0.3569
0.03236
140
11.03
<.0001
horizon*nwater*extract
Bh
-0.1
Oxl
0.1509
0.03236
140
4.67
<.0001
horizon*water*extract
Bh
-0.1
0x2
0.2619
0.03963
140
6.61
<.0001
horizon* water*extract
Bh
-0.1
0x3
0.4530
0.03236
140
14.00
<.0001
horizon*water*extract
Bh
-3
DA
0.1136
0.03236
140
3.51
0.0006
horizon * water* extract
Bh
-3
NaHC03
0.2723
0.03236
140
8.42
<.0001
horizon* water*extract
Bh
-3
Oxl
0.1280
0.03236
140
3.96
0.0001
horizon* water*extract
Bh
-3
0x2
0.1618
0.03963
140
4.08
<.0001
horizon* water* extract
Bh
-3
0x3
0.2833
0.03236
140
8.76
<.0001
horizon* water* extract
Bh
-8
DA
0.1370
0.03963
140
3.46
0.0007
horizon* water* extract
Bh
-8
NaHC03
0.3303
0.03236
140
10.21
<.0001
horizon * water* extract
Bh
-8
Oxl
0.1713
0.03236
140
5.29
<.0001
horizon* water*extract
Bh
-8
0x2
0.2437
0.03963
140
6.15
<.0001
horizon*water*extract
Bh
-8
0x3
0.3045
0.03963
140
7.69
<.0001
horizon* water*extract
Bh
-1000
DA
0.2060
0.03236
140
6.37
<.0001
horizon* water*extract
Bh
-1000
NaHC03
0.7152
0.03236
140
22.10
<.0001
horizon*water*extract
Bh
-1000
Oxl
0.1307
0.03236
140
4.04
<.0001
horizon* water*extract
Bh
-1000
0x2
0.1894
0.03963
140
4.78
<0001
horizon*water*extract
Bh
-1000
0x3
0.2238
0.03963
140
5.65
<.0001
horizon*water*extract
E
-0.1
BK
0.7880
0.03236
140
24.35
<.0001
horizon*water* extract
E
-0.1
DA
0.4294
0.03236
140
13.27
<.0001
horizon*water*extract
E
-0.1
NaHC03
0.9935
0.03236
140
30.71
<0001
horizon*water*extract
E
-0.1
Oxl
0.6599
0.03236
140
20.39
<0001

Table B-1. continued
Effect
horizon
water ikPal
extract
Estimate
Standard
Error
DF
t Value
Pr > Itl
horizon* water* extract
E
-0.1
0x2
0.8303
0.03963
140
20.95
<.0001
horizon*water*extract
E
-0.1
0x3
0.7358
0.03236
140
22.74
<.0001
horizon* water*extract
E
-3
BK
0.5501
0.03236
140
17.00
<.0001
horizon*water*extract
E
-3
DA
0.3519
0.03236
140
10.88
<.0001
horizon* water*extract
E
-3
NaHC03
0.7513
0.03236
140
23.22
<.0001
horizon*water*extract
E
-3
Oxl
0.9520
0.03236
140
29.42
<.0001
horizon* water*extract
E
-3
0x2
0.8769
0.03963
140
22.13
<.0001
horizon*water*extract
E
-3
0x3
0.9127
0.03236
140
28.21
<.0001
horizon* water*extract
E
-8
BK
0.2966
0.03236
140
9.17
<.0001
horizon* water*extract
E
-8
DA
0.1909
0.03236
140
5.90
<.0001
horizon* water*extract
E
-8
NaHC03
0.5976
0.03236
140
18.47
<.0001
horizon* water* extract
E
-8
Oxl
0.5258
0.03236
140
16.25
<.0001
horizon* water* extract
E
-8
0x2
0.5720
0.03963
140
14.43
<.0001
horizon* water*extract
E
-8
0x3
0.4831
0.03963
140
12.19
<0001
horizon* water*extract
E
-15
BK
0.4190
0.03236
140
12.95
<0001
horizon*water*extract
E
-15
DA
0.2755
0.03236
140
8.51
<0001
horizon*water*extract
E
-15
NaHC03
0.7276
0.03236
140
22.49
<0001
horizon*water*extract
E
-15
Oxl
0.7012
0.03963
140
17.69
<0001
horizon* water* extract
E
-15
0x2
0.6900
0.03963
140
17.41
<0001
horizon*water*extract
E
-15
0x3
0.6425
0.03236
140
19.86
<0001
horizon*water*extract
E
-1000
BK
0.5939
0.03236
140
18.35
<0001
horizon*water*extract
E
-1000
DA
0.2780
0.03236
140
8.59
<0001
horizon*water*extract
E
-1000
NaHC03
0.7274
0.03236
140
22.48
<0001
horizon* water* extract
E
-1000
Oxl
0.7077
0.03236
140
21.87
<0001
horizon*water*extract
E
-1000
0x2
0.8432
0.03963
140
21.28
<0001
horizon* water*extract
E
-1000
0x3
0.8329
0.03963
140
21.02
<0001

Table B-2. Analysis of variance table for microbial P from the P-only fertilizer treatments. Trt = fertilizer treatment, PI 00
100 kg P harl. P60 = 60 kg P ha'1. P30 = 30 kg P ha1. CTL = control (0 kg P ha'1)
Type 3 Tests of Fixed Effects
Num Den
Effect
DF
DF
F Value
Pr > F
water
4
40
8.28
<.0001
trt
4
40
157.83
<.0001
day
6
193
36.62
<.0001
water* trt
12
40
1.70
0.1030
water*day
22
193
3.13
<.0001
trt*day
18
193
7.36
<.0001
water* trt*dav
65
193
1.55
0.0118
Least Squares Means
Effect
water IkPal
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > |t|
water*trt*day
-0.1
P100
0
0.9394
3.4599
193
0.27
0.7863
water* trt* day
-0.1
P100
3
24.3771
3.2738
193
7.45
<.0001
water*trt*day
-0.1
P100
7
40.0099
4.3475
193
9.20
<.0001
water* trt*day
-0.1
P100
14
24.1528
3.9805
193
6.07
<.0001
water*trt*day
-0.1
P100
28
37.4754
3.9950
193
9.38
<.0001
water* trt*day
-0.1
PI 00
49
22.4519
6.8445
193
3.28
0.0012
water*trt*day
-0.1
P100
77
14.3149
4.8404
193
2.96
0.0035
water*trt*dav
-0.1
P30
0
0.7358
3.2740
193
0.22
0.8224

Table B-2. continued
Effect
water tkPa't
trt
dav
Estimate
Standard
Error
DF
Pr > Itl
water*trt*day
-0.1
P30
3
17.6494
4.3292
193
4.08
<.0001
water* trt*day
-0.1
P30
7
9.7324
3.9804
193
2.45
0.0154
water*trt*day
-0.1
P30
14
8.1148
3.7042
193
2.19
0.0297
water*trt*day
-0.1
P30
28
15.6750
3.4597
193
4.53
<.0001
water*trt*day
-0.1
P30
49
9.2156
3.2737
193
2.82
0.0054
water*trt*day
-0.1
P30
77
11.3200
3.7043
193
3.06
0.0026
water*trt*day
-0.1
P60
0
0.8497
3.6931
193
0.23
0.8183
water*trt*day
-0.1
P60
3
32.7390
3.9806
193
8.22
<.0001
water*trt*day
-0.1
P60
7
11.4692
6.8454
193
1.68
0.0955
water*trt*day
-0.1
P60
14
19.4235
4.8662
193
3.99
<.0001
water*trt*day
-0.1
P60
28
27.5594
3.7046
193
7.44
<0001
water*trt*day
-0.1
P60
49
28.3621
6.9191
193
4.10
<.0001
water*trt*day
-0.1
P60
77
6.7027
4.8928
193
1.37
0.1723
water*trt*day
-0.1
CTL
0
0.9876
3.7044
193
0.27
0.7901
water*trt*day
-0.1
CTL
3
1.1641
3.2738
193
0.36
0.7225
water* trt*day
-0.1
CTL
7
1.2004
3.2737
193
0.37
0.7143
water*trt*day
-0.1
CTL
14
2.4590
3.2737
193
0.75
0.4535
water*trt*day
-0.1
CTL
28
1.6541
3.2738
193
0.51
0.6139
water*trt*day
-0.1
CTL
49
1.7775
3.7042
193
0.48
0.6319
water*trt*day
-0.1
CTL
77
2.3924
3.2739
193
0.73
0.4658
water*trt*day
-3
P100
0
1.4416
3.2740
193
0.44
0.6602
water*trt*day
-3
P100
3
27.3766
3.9950
193
6.85
<.0001
water* trt* day
-3
PI 00
7
25.1328
5.6289
193
4.46
<.0001
water*trt*day
-3
P100
14
20.4116
4.8928
193
4.17
<.0001
water*trt*day
-3
P100
28
17.7726
5.6292
193
3.16
0.0018
water*trt*day
-3
P100
77
4.1331
5.5885
193
0.74
0.4605
water*trt*dav
-3
P30
0
3.0149
3.4600
193
0.87
0.3846

Table B-2. continued
Effect
water tkPal
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water*trt*day
-3
P30
3
24.3614
4.8927
193
4.98
<.0001
water* trt* day
-3
P30
7
8.3155
4.8658
193
1.71
0.0891
water*trt*day
-3
P30
14
5.0833
3.9949
193
1.27
0.2047
water*trt*day
-3
P30
28
13.2463
3.4693
193
3.82
0.0002
water* trt* day
-3
P30
49
8.1907
3.9946
193
2.05
0.0417
water* trt*day
-3
P30
77
7.4046
3.2740
193
2.26
0.0248
water*trt*day
-3
P60
0
1.3526
3.4694
193
0.39
0.6971
water*trt*day
-3
P60
3
16.3684
4.8659
193
3.36
0.0009
water*trt*day
-3
P60
7
7.8561
6.9191
193
1.14
0.2576
water*trt*day
-3
P60
14
11.8528
4.8660
193
2.44
0.0158
water*trt*day
-3
P60
28
25.9356
4.3672
193
5.94
<.0001
water*trt*day
-3
P60
49
13.8203
9.6795
193
1.43
0.1550
water* trt*day
-3
P60
77
9.3039
3.7046
193
2.51
0.0128
water*trt*day
-3
CTL
0
1.8489
3.2739
193
0.56
0.5729
water*trt*day
-3
CTL
3
1.4787
3.7042
193
0.40
0.6902
water*trt*day
-3
CTL
7
1.4149
3.4597
193
0.41
0.6830
water*trt*day
-3
CTL
14
1.5876
3.4691
193
0.46
0.6477
water*trt*day
-3
CTL
28
1.7502
3.2738
193
0.53
0.5935
water*trt*day
-3
CTL
49
1.7407
3.2737
193
0.53
0.5955
water*trt*day
-3
CTL
77
1.1792
3.4692
193
0.34
0.7343
water*trt*day
-8
P100
0
2.6026
3.4694
193
0.75
0.4541
water* trt*day
-8
P100
3
33.7307
4.8399
193
6.97
<.0001
water*trt*day
-8
P100
7
30.2187
3.9949
193
7.56
<.0001
water* trt*day
-8
P100
14
15.9216
4.3663
193
3.65
0.0003
water*trt*day
-8
P100
28
14.7444
4.8659
193
3.03
0.0028
water*trt*day
-8
P100
49
15.8073
4.8662
193
3.25
0.0014
water*trt*day
-8
PI 00
77
19.6108
4.8662
193
4.03
<.000!
water* trt*dav
-8
P30
0
1.9490
3.4599
193
0.56
0.5739

Table B-2. continued
Effect
water IkPal
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water* trt* day
-8
P30
3
21.5060
4.3663
193
4.93
<.0001
water* trt* day
-8
P30
7
16.3082
3.4692
193
4.70
<.0001
water* trt*day
-8
P30
14
14.6546
3.6814
193
3.98
<.0001
water*trt*day
-8
P30
28
1 1.6570
3.2738
193
3.56
0.0005
water* trt*day
-8
P30
49
5.2997
4.3664
193
1.21
0.2263
water*trt*day
-8
P30
77
4.9910
3.9950
193
1.25
0.2131
water*trt*day
-8
P60
0
2.8997
3.2741
193
0.89
0.3769
water*trt*day
-8
P60
3
21.6210
6.8432
193
3.16
0.0018
water*trt*day
-8
P60
7
11.1918
4.3859
193
2.55
0.0115
water*trt*day
-8
P60
14
12.0415
3.6929
193
3.26
0.0013
water* trt*day
-8
P60
28
6.3255
4.3667
193
1.45
0.1491
water* trt* day
-8
P60
49
12.6950
4.3666
193
2.91
0.0041
water* trt*day
-8
P60
77
8.6095
5.5894
193
1.54
0.1251
water*trt*day
-8
CTL
0
3.5923
3.2739
193
1.10
0.2739
water*trt*day
-8
CTL
3
4.8885
3.2737
193
1.49
0.1370
water*trt*day
-8
CTL
7
5.1651
3.2737
193
1.58
0.1163
water* trt*day
-8
CTL
14
5.3151
3.2737
193
1.62
0.1061
water*trt*day
-8
CTL
28
3.5367
3.2737
193
1.08
0.2813
water*trt*day
-8
CTL
49
4.2458
3.2737
193
1.30
0.1962
water*trt*day
-8
CTL
77
2.9403
3.2739
193
0.90
0.3702
water*trt*day
-15
P100
0
7.9857
3.2740
193
2.44
0.0156
water*trt*day
-15
P100
3
37.1388
5.5874
193
6.65
<.0001
water* trt*day
-15
P100
7
51.5551
3.9948
193
12.91
<.0001
water*trt*day
-15
P100
14
21.0824
3.7045
193
5.69
<.0001
water*trt*day
-15
P100
28
16.6873
5.6292
193
2.96
0.0034
water* trt*day
-15
P100
77
14.2626
4.3481
193
3.28
0.0012
water*trt*day
-15
P30
0
7.7794
3.2740
193
2.38
0.0185
water*trt*dav
-15
P30
3
31.1716
3.9947
193
7.80
<0001

Table B-2. continued
Effect
water CkPa'I
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water* trt* day
-15
P30
7
22.6696
3.6816
193
6.16
<.0001
water*trt*day
-15
P30
14
9.2635
3.9947
193
2.32
0.0214
water*trt*day
-15
P30
28
9.1628
3.4599
193
2.65
0.0088
water*trt*day
-15
P30
77
13.0002
3.2741
193
3.97
0.0001
water*trt*day
-15
P60
0
9.5585
3.2740
193
2.92
0.0039
water*trt*day
-15
P60
3
16.5806
5.6704
193
2.92
0.0039
water* trt*day
-15
P60
7
37.5289
3.7044
193
10.13
<.0001
water*trt*day
-15
P60
14
26.0177
3.7044
193
7.02
<.0001
water*trt*day
-15
P60
28
7.3170
5.6292
193
1.30
0.1952
water*trt*day
-15
P60
77
14.7642
3.9951
193
3.70
0.0003
water*trt*day
-15
CTL
0
8.0598
3.2739
193
2.46
0.0147
water*trt*day
-15
CTL
3
5.9333
3.2737
193
1.81
0.0715
water*trt*day
-15
CTL
7
7.2249
3.2737
193
2.21
0.0285
water*trt*day
-15
CTL
14
5.9383
3.2737
193
1.81
0.0712
water*trt*day
-15
CTL
28
4.7241
3.2739
193
1.44
0.1507
water*trt*day
-15
CTL
77
4.7196
3.2741
193
1.44
0.1511
water*trt*day
-1000
PI 00
0
3.6630
3.2741
193
1.12
0.2646
water*trt*day
-1000
P100
3
23.3410
9.6774
193
2.41
0.0168
water* trt*day
-1000
P100
7
20.2399
3.6817
193
5.50
<.0001
water*trt*day
-1000
P100
14
30.2157
4.3665
193
6.92
<.0001
water*trt*day
-1000
P100
28
9.3629
3.7046
193
2.53
0.0123
water*trt*day
-1000
P100
77
13.7186
5.6292
193
2.44
0.0157
water*trt*day
-1000
P30
0
3.5741
3.2740
193
1.09
0.2763
water* trt*day
-1000
P30
3
19.3105
4.8662
193
3.97
0.0001
water*trt*day
-1000
P30
7
13.9861
3.9804
193
3.51
0.0006
water*trt*day
-1000
P30
14
14.6087
3.2738
193
4.46
<.0001
water*trt*day
-1000
P30
28
19.0419
3.2739
193
5.82
<.0001
water* trt*dav
-1000
P30
77
11.0840
3.4601
193
3.20
0.0016

Table B-2. continued
Effect
water fkPat
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water*trt*day
-1000
P60
0
3.3531
3.2740
193
1.02
0.3070
water*trt*day
-1000
P60
3
15.5323
5.6284
193
2.76
0.0063
water*trt*day
-1000
P60
7
30.6325
3.7044
193
8.27
<.0001
water*trt*day
-1000
P60
14
18.2643
3.7043
193
4.93
<.0001
water*trt*day
-1000
P60
28
9.8007
4.3858
193
2.23
0.0266
water* trt*day
-1000
P60
77
6.2005
3.9951
193
1.55
0.1223
water*trt*day
-1000
CTL
0
3.9818
3.2739
193
1.22
0.2254
water*trt*day
-1000
CTL
3
3.5124
3.2737
193
1.07
0.2847
water*trt*day
-1000
CTL
7
4.9740
3.2737
193
1.52
0.1303
water*trt*day
-1000
CTL
14
4.5143
3.2737
193
1.38
0.1695
water*trt*day
-1000
CTL
28
4.1864
3.2739
193
1.28
0.2025
water*trt*dav
-1000
CTL
77
3.2970
3.2741
193
1.01
0.3152

Table B-3. Analysis of variance table for microbial P from all fertilizer treatments, including DAP. Trt = fertilizer treatment,
P100 = 100 kg P ha'1. P6Q = 60 kg P ha1. P30 = 30 kg P ha'1. CTL = control (0 kg P ha'~l
Type 3 Tests of Fixed Effects
Num Den
Effect
DF
DF
F Value
Pr > F
water
4
50
9.71
<0.0001
trt
4
50
107.93
<0.0001
day
6
238
19.88
<0.0001
water*trt
16
50
5.99
<0.0001
water*day
22
238
3.52
<0.0001
trt*day
24
238
9.82
<0.0001
water*trt*dav
86
238
2.87
<0.0001
Least Sauares Means
Effect
water tkPat
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > ¡tl
water*trt*day
-0.1
DAP
0
0.4644
16.6171
238
0.03
0.9777
water*trt*day
-0.1
DAP
3
64.1684
15.6177
238
4.11
<.0001
water*trt*day
-0.1
DAP
7
56.6777
24.1942
238
2.34
0.0200
water*trt*day
-0.1
DAP
14
33.4222
15.6166
238
2.14
0.0334
water*trt*day
-0.1
DAP
28
203.72
14.7703
238
13.79
<.0001
water* trt* day
-0.1
DAP
49
111.18
17.8276
238
6.24
<.0001
water*trt*day
-0.1
DAP
77
94.2369
16.4415
238
5.73
<.0001
water*trt*day
-0.1
P100
0
1.2462
15.4627
238
0.08
0.9358
water*trt*day
-0.1
P100
3
23.9906
14.7682
238
1.62
0.1056
water* trt* day
-0.1
P100
7
40.3523
19.0691
238
2.12
0.0354
water* trt*day
-0.1
P100
14
23.5655
17.6086
238
1.34
0.1821
water*trt*day
-0.1
P100
28
37.7190
17.8450
238
2.11
0.0356
water*trt*day
-0.1
P100
49
22.4415
29.6935
238
0.76
0.4505
water*trt*dav
-0.1
P100
77
14.3187
21.0341
238
0.68
0.4967

Table B-3. continued
Effect
water fkPal
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water* trt*day
-0.1
P30
0
0.9232
14.7801
238
0.06
0.9502
water* trt* day
-0.1
P30
3
17.6688
18.8029
238
0.94
0.3483
water*trt*day
-0.1
P30
7
8.9118
17.6062
238
0.51
0.6132
water* trt*day
-0.1
P30
14
8.1719
16.6054
238
0.49
0.6231
water*trt*day
-0.1
P30
28
15.5599
15.4527
238
1.01
0.3150
water*trt*day
-0.1
P30
49
9.0046
14.7655
238
0.61
0.5425
water* trt* day
-0.1
P30
77
1 1.5250
16.6127
238
0.69
0.4885
water*trt*day
-0.1
P60
0
0.9887
16.4413
238
0.06
0.9521
water*trt*day
-0.1
P60
3
32.4748
17.6148
238
1.84
0.0665
water*trt*day
-0.1
P60
7
9.7387
29.7555
238
0.33
0.7437
water*trt*day
-0.1
P60
14
19.7045
21.4182
238
0.92
0.3585
water*trt*day
-0.1
P60
28
27.3690
16.6302
238
1.65
0.1011
water*trt*day
-0.1
P60
49
28.3717
30.8797
238
0.92
0.3591
water*trt*day
-0.1
P60
77
6.5894
21.8568
238
0.30
0.7633
water*trt*day
-0.1
CTL
0
0.9971
16.6162
238
0.06
0.9522
water* trt*day
-0.1
CTL
3
1.1488
14.7662
238
0.08
0.9381
water*trt*day
-0.1
CTL
7
1.1699
14.7628
238
0.08
0.9369
water*trt*day
-0.1
CTL
14
2.4914
14.7628
238
0.17
0.8661
water* trt*day
-0.1
CTL
28
1.6484
14.7665
238
0.11
0.9112
water* trt*day
-0.1
CTL
49
1.7935
16.6028
238
0.11
0.9141
water*trt*day
-0.1
CTL
77
2.3899
14.7789
238
0.16
0.8717
water*trt*day
-3
DAP
0
1.8703
14.7828
238
0.13
0.8994
water*trt*day
-3
DAP
3
49.5407
21.8311
238
2.27
0.0241
water*trt*day
-3
DAP
7
37.1050
19.0977
238
1.94
0.0532
water*trt*day
-3
DAP
14
122.46
29.6932
238
4.12
<.0001
water*trt*day
-3
DAP
28
16.1004
19.4241
238
0.83
0.4080
water* trt*day
-3
DAP
77
32.1533
24.9008
238
1.29
0.1979
water*trt*dav
-3
P100
0
1.4179
14.7825
238
0.10
0.9237

Table B-3. continued
Effect
water fkPal
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water*trt*day
-3
P100
3
27.0973
17.8441
238
1.52
0.1302
water* trt*day
-3
P100
7
25.2111
24.8790
238
1.01
0.3119
water*trt*day
-3
P100
14
20.2706
21.8539
238
0.93
0.3546
water*trt*day
-3
P100
28
17.7272
24.9008
238
0.71
0.4772
water*trt*day
-3
P100
77
4.1331
24.2450
238
0.17
0.8648
water*trt*day
-3
P30
0
3.1524
15.4717
238
0.20
0.8387
water*trt*day
-3
P30
3
24.3619
21.8484
238
1.12
0.2660
water*trt*day
-3
P30
7
8.0889
21.3929
238
0.38
0.7057
water*trt*day
-3
P30
14
5.0559
17.8428
238
0.28
0.7772
water*trt*day
-3
P30
28
13.3226
15.6181
238
0.85
0.3945
water*trt*day
-3
P30
49
8.3395
17.8203
238
0.47
0.6402
water*trt*day
-3
P30
77
7.3981
14.7795
238
0.50
0.6171
water*trt*day
-3
P60
0
1.4645
15.6224
238
0.09
0.9254
water*trt*day
-3
P60
3
16.6944
21.4012
238
0.78
0.4361
water*trt*day
-3
P60
7
7.5273
30.8794
238
0.24
0.8076
water*trt*day
-3
P60
14
11.6390
21.4092
238
0.54
0.5872
water* trt* day
-3
P60
28
25.8474
19.4241
238
1.33
0.1846
water*trt*day
-3
P60
49
13.5560
41.9927
238
0.32
0.7471
water*trt*day
-3
P60
77
9.1417
16.6303
238
0.55
0.5830
water* trt*day
-3
CTL
0
1.8218
14.7789
238
0.12
0.9020
water* trt*day
-3
CTL
3
1.4912
16.6033
238
0.09
0.9285
water*trt*day
-3
CTL
7
.4235
15.4537
238
0.09
0.9267
water*trt*day
-3
CTL
14
1.5884
15.6028
238
0.10
0.9190
water*trt*day
-3
CTL
28
1.7432
14.7659
238
0.12
0.9061
water*trt*day
-3
CTL
49
1.7391
14.7637
238
0.12
0.9063
water*trt*day
-3
CTL
77
1.1767
15.6134
238
0.08
0.9400
water*trt*day
-8
DAP
0
2.0452
14.7826
238
0.14
0.8901
water*trt*dav
-8
DAP
3
190.24
19.0770
238
9.97
<0001

Effect
water ikPat
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water*trt*day
-8
DAP
7
245.51
16.6133
238
14.78
<.0001
water*trt*day
-8
DAP
14
314.92
20.9965
238
15.00
<.0001
water*trt*day
-8
DAP
28
49.7739
19.0939
238
2.61
0.0097
water* trt*day
-8
DAP
49
64.7657
41.8667
238
1.55
0.1232
water*trt*day
-8
DAP
77
62.6745
16.6303
238
3.77
0.0002
water* trt*day
-8
P100
0
2.6564
15.6209
238
0.17
0.8651
water*trt*day
-8
P100
3
33.6063
21.0074
238
1.60
0.1110
water* trt* day
-8
PI 00
7
30.0492
17.8414
238
1.68
0.0934
water* trt*day
-8
P100
14
16.6707
19.3662
238
0.86
0.3902
water*trt*day
-8
P100
28
14.4026
21.4032
238
0.67
0.5017
water*trt*day
-8
P100
49
16.1598
21.4183
238
0.75
0.4513
water*trt*day
-8
P100
77
19.7536
21.4184
238
0.92
0.3573
water*trt*day
-8
P30
0
1.5220
15.4683
238
0.10
0.9217
water*trt*day
-8
P30
3
21.2768
19.3606
238
1.10
0.2729
water*trt*day
-8
P30
7
6.6930
15.6094
238
1.07
0.2860
water* trt* day
-8
P30
14
14.7773
16.2407
238
0.91
0.3638
water* trt* day
-8
P30
28
11.6023
14.7720
238
0.79
0.4330
water*trt*day
-8
P30
49
5.2100
19.3708
238
0.27
0.7882
water*trt*day
-8
P30
77
5.0218
17.8456
238
0.28
0.7786
water*trt*day
-8
P60
0
2.8948
14.7876
238
0.20
0.8450
water*trt*day
-8
P60
3
21.6452
29.6140
238
0.73
0.4656
water*trt*day
-8
P60
7
11.3125
19.7126
238
0.57
0.5666
water*trt*day
-8
P60
14
12.0899
16.4314
238
0.74
0.4626
water*trt*day
-8
P60
28
5.9998
19.3922
238
0.31
0.7573
water*trt*day
-8
P60
49
12.6282
19.3834
238
0.65
0.5154
water* trt*day
-8
P60
77
8.6120
24.3024
238
0.35
0.7234
water*trt*day
-8
CTL
0
3.5808
14.7752
238
0.24
0.8087
water*trt*dav
-8
CTL
3
4.8899
14.7628
238
0.33
0.7408

Table B-3. continued
Effect
water fkPa'l
trt
dav
Estimate
Standard
Error
DF
t Value
A
>->
0-
water* trt*day
-8
CTL
7
5.1472
14.7628
238
0.35
0.7277
water* trt*day
-8
CTL
14
5.3338
14.7628
238
0.36
0.7182
water* trt*day
-8
CTL
28
3.5335
14.7628
238
0.24
0.8110
water*trt*day
-8
CTL
49
4.2510
14.7628
238
0.29
0.7736
water* trt*day
-8
CTL
77
2.9362
14.7752
238
0.20
0.8426
water*trt*day
-15
DAP
0
7.7449
14.7843
238
0.52
0.6009
water* trt*day
-15
DAP
3
193.70
29.6470
238
6.53
<.0001
water*trt*day
-15
DAP
7
266.20
15.6182
238
17.04
<.0001
water*trt*day
-15
DAP
14
273.10
17.3983
238
15.70
<.0001
water*trt*day
-15
DAP
28
82.2084
29.6934
238
2.77
0.0061
water*trt*day
-15
DAP
77
186.36
15.6280
238
11.92
<.0001
water* trt*day
-15
P100
0
7.7756
14.7833
238
0.53
0.5994
water*trt*day
-15
P100
3
37.0496
24.1779
238
1.53
0.1268
water* trt*day
-15
P100
7
52.1602
17.8370
238
2.92
0.0038
water* trt*day
-15
P100
14
21.3289
16.6231
238
1.28
0.2007
water*trt*day
-15
P100
28
16.7575
24.9006
238
0.67
0.5016
water*trt*day
-15
P100
77
14.3814
19.1080
238
0.75
0.4524
water*trt*day
-15
P30
0
7.8965
14.7825
238
0.53
0.5937
water* trt* day
-15
P30
3
30.7149
17.8285
238
1.72
0.0862
water* trt* day
-15
P30
7
22.5440
16.2551
238
1.39
0.1668
water*trt*day
-15
P30
14
8.8600
17.8282
238
0.50
0.6197
water* trt*day
-15
P30
28
9.2923
15.4677
238
0.60
0.5486
water* trt*day
-15
P30
77
12.9811
14.7876
238
0.88
0.3809
water*trt*day
-15
P60
0
9.5955
14.7835
238
0.65
0.5169
water* trt* day
-15
P60
3
16.6004
25.5829
238
0.65
0.5170
water*trt*day
-15
P60
7
37.1416
16.6179
238
2.24
0.0263
water*trt*day
-15
P60
14
25.9468
16.6179
238
1.56
0.1198
water* trt*dav
-15
P60
28
7.4643
24.9008
238
0.30
0.7646

Table B-3. continued
Effect
water fkPat
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water* trt* day
-15
P60
77
14.4753
17.8539
238
0.81
0.4183
water*trt*day
-15
CTL
0
8.0618
14.7752
238
0.55
0.5858
water* trt* day
-15
CTL
3
5.9317
14.7628
238
0.40
0.6882
water* trt*day
-15
CTL
7
7.2270
14.7628
238
0.49
0.6249
water*trt*day
-15
CTL
14
5.9317
14.7628
238
0.40
0.6882
water*trt*day
-15
CTL
28
4.7346
14.7752
238
0.32
0.7489
water*trt*day
-15
CTL
77
4.7166
14.7876
238
0.32
0.7500
water*trt*day
-1000
DAP
0
2.1792
14.7818
238
0.15
0.8829
water*trt*day
-1000
DAP
3
107.88
21.3890
238
5.04
<.0001
water* trt* day
-1000
DAP
7
101.95
18.1019
238
5.63
<.0001
water*trt*day
-1000
DAP
14
207.83
21.0048
238
9.89
<.0001
water* trt* day
-1000
DAP
28
77.0080
21.4035
238
3.60
0.0004
water*trt*day
-1000
DAP
77
130.92
21.0341
238
6.22
<.0001
water* trt*day
-1000
P100
0
3.6593
14.7876
238
0.25
0.8048
water*trt*day
-1000
P100
3
23.3468
41.8618
238
0.56
0.5776
water*trt*day
-1000
P100
7
19.9667
16.2630
238
1.23
0.2208
water* trt*day
-1000
P100
14
30.0454
19.3745
238
1.55
0.1223
water*trt*day
-1000
P100
28
9.5631
16.6302
238
0.58
0.5658
water*trt*day
-1000
P100
77
13.7498
24.9008
238
0.55
0.5813
water* trt* day
-1000
P30
0
3.6482
14.7830
238
0.25
0.8053
water*trt*day
-1000
P30
3
19.2018
21.4247
238
0.90
0.3710
water*trt*day
-1000
P30
7
13.8591
17.6053
238
0.79
0.4319
water*trt*day
-1000
P30
14
14.5878
14.7670
238
0.99
0.3242
water*trt*day
-1000
P30
28
19.0466
14.7752
238
1.29
0.1986
water*trt*day
-1000
P30
77
11.0907
15.4769
238
0.72
0.4743
water*trt*day
-1000
P60
0
3.2959
14.7833
238
0.22
0.8238
water*trt*day
-1000
P60
3
15.2756
24.8475
238
0.61
0.5393
water*trt*dav
-1000
P60
7
30.8287
16.6170
238
1.86
0.0648

Table B-3. continued
Effect
water fkPal
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water* trt* day
-1000
P60
14
17.9543
16.6122
238
1.08
0.2809
water*trt*day
-1000
P60
28
9.9830
19.7041
238
0.51
0.6129
water* trt* day
-1000
P60
77
6.1675
17.8539
238
0.35
0.7301
water*trt*day
-1000
CTL
0
3.9851
14.7752
238
0.27
0.7876
water* trt* day
-1000
CTL
3
3.5133
14.7628
238
0.24
0.8121
water* trt* day
-1000
CTL
7
4.9497
14.7628
238
0.34
0.7377
water*trt*day
-1000
CTL
14
4.5293
14.7628
238
0.31
0.7593
water*trt*day
-1000
CTL
28
4.1952
14.7752
238
0.28
0.7767
water*trt*dav
-1000
CTL
77
3.2877
14.7876
238
0.22
0.8242

Table B-4. Analysis of variance for microbial C from all P-only fertilizer treatments, Trt = fertilizer treatment, PI 00 = 100 kg
P haP60 = 60 kg P ha'. P30 = 30 kg P ha1. CTL = control (0 kg P ha')
Type 3 Tests of Fixed Effects
Effect
Num
DF
Den
DF
F Value
Pr > F
water
4
40
17.17
<.0001
trt
3
40
0.27
0.8468
day
6
191
4.02
0.0008
water*trt
12
40
2.47
0.0161
water* day
21
191
11.80
<0001
trt* day
18
191
2.73
0.0004
water* trt*dav
59
191
2.22
<.0001
l.east Sanares Means
Effect
water tkPal
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water*trt*day
-0.1
P100
0
46.53
38.4638
191
1.21
0.2278
water*trt*day
-0.1
PI 00
3
161.87
38.4453
191
4.21
<0001
water* trt*day
-0.1
P100
7
142.27
38.4453
191
3.70
0.0003
water*trt*day
-0.1
P100
14
101.76
38.4504
191
2.65
0.0088
water* trt*day
-0.1
P100
28
425.99
43.3185
191
9.83
<0001
water*trt*day
-0.1
P100
49
108.17
40.6713
191
2.66
0.0085
water* trt*day
-0.1
P100
77
92.20
43.3442
191
2.13
0.0347
water* trt*day
-0.1
P30
0
160.63
42.9696
191
3.74
0.0002
water*trt*day
-0.1
P30
3
173.57
40.3652
191
4.30
<0001
water*trt*day
-0.1
P30
7
62.25
43.3244
191
1.44
0.1524
water* trt* day
-0.1
P30
14
179.98
40.6750
191
4.42
<0001
water* trt* day
-0.1
P30
28
260.59
46.5832
191
5.59
<.0001
water*trt*day
-0.1
P30
49
164.03
40.3794
191
4.06
<0001
water*trt*day
-0.1
P30
77
174.32
57.0546
191
3.06
0.0026
water* trt*dav
-0.1
P60
0
208.62
40.6881
191
5.13
<0001

Table B-4. continued
Effect
water fkPal
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water*trt*day
-0.1
P60
3
174.65
38.4500
191
4.54
<.0001
water*trt*day
-0.1
P60
7
171.81
38.4482
191
4.47
<.0001
water*trt*day
-0.1
P60
14
170.09
43.3264
191
3.93
0.0001
water*trt*day
-0.1
P60
28
209.25
46.1179
191
4.54
<.0001
water*trt*day
-0.1
P60
49
179.88
38.4562
191
4.68
<.0001
water*trt*day
-0.1
P60
77
125.57
46.1387
191
2.72
0.0071
water*trt*day
-0.1
CTL
0
104.78
38.4638
191
2.72
0.0070
water*trt*day
-0.1
CTL
3
184.10
38.4567
191
4.79
<.0001
water*trt*day
-0.1
CTL
7
426.93
57.0272
191
7.49
<.0001
water*trt*day
-0.1
CTL
14
105.16
40.6787
191
2 59
0.0105
water* trt*day
-0.1
CTL
28
212.77
43.3193
191
4.91
<.0001
water*trt*day
-0.1
CTL
49
180.52
40.6713
191
4.44
<.0001
water* trt*day
-0.1
CTL
77
170.98
43.3442
191
3.94
0.0001
water*trt*day
-3
P100
0
198.12
40.6833
191
4.87
<.0001
water*trt*day
-3
P100
3
198.74
38.4466
191
5.17
<.0001
water* trt*day
-3
P100
7
138.02
38.4453
191
3.59
0.0004
water* trt*day
-3
P100
14
182.93
38.4453
191
4.76
<.0001
water*trt*day
-3
P100
28
136.76
38.4453
191
3.56
0.0005
water*trt*day
-3
P100
49
138.55
38.4638
191
3.60
0.0004
water* trt*day
-3
P100
77
64.52
110.49
191
0.58
0.5599
water* trt*day
-3
P30
0
108.89
46.6225
191
2.34
0.0205
water*trt*day
-3
P30
3
90.49
43.3375
191
2.09
0.0381
water* trt* day
-3
P30
7
135.81
38.4528
191
3.53
0.0005
water*trt*day
-3
P30
14
217.14
40.6792
191
5.34
<.0001
water* trt* day
-3
P30
28
66.81
46.5851
191
1.43
0.1531
water* trt*day
-3
P30
49
76.31
43.3467
191
1.76
0.0799
water*trt*day
-3
P30
77
53.92
6.2036
191
0.96
0.3385
water* trt* day
-3
P60
0
129.29
42.9698
191
3.01
0.0030

Table B-4. continued
Effect
water fkPat
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water*trt*day
-3
P60
3
97.76
40.6694
191
2.40
0.0172
water* trt* day
-3
P60
7
181.22
38.4577
191
4.71
<.0001
water* trt*day
-3
P60
14
258.02
50.6949
191
5.09
<.0001
water* trt*day
-3
P60
28
110.74
38.4564
191
2.88
0.0044
water*trt*day
-3
P60
49
243.12
38.4502
191
6.32
<.0001
water*trt*day
-3
P60
77
62.02
46.5898
191
1.33
0.1847
water*trt*day
-3
CTL
0
200.23
51.3845
191
3.90
0.0001
water* trt* day
-3
CTL
3
127.81
40.6799
191
3.14
0.0019
water* trt*day
-3
CTL
7
302.73
40.6670
191
7.44
<.0001
water* trt*day
-3
CTL
14
209.22
38.4530
191
5.44
<0001
water* trt*day
-3
CTL
28
61.67
46.5840
191
1.32
0.1871
water* trt*day
-3
CTL
49
45.79
50.7101
191
0.90
0.3677
water*trt*day
-3
CTL
77
83.33
38.4748
191
2.17
0.0316
water*trt*day
-8
P100
0
72.35
43.3640
191
1.67
0.0968
water* trt*day
-8
P100
3
66.90
110.49
191
0.61
0.5456
water* trt*day
-8
P100
7
116.56
38.4822
191
3.03
0.0028
water*trt*day
-8
P100
28
97.71
40.3785
191
2.42
0.0165
water* trt*day
-8
P100
49
157.90
40.3785
191
3.91
0.0001
water*trt*day
-8
P30
0
86.78
40.6833
191
2.13
0.0342
water* trt*day
-8
P30
3
150.06
38.4466
191
3.90
0.0001
water* trt*day
-8
P30
7
82.37
38.4574
191
2.14
0.0335
water*trt*day
-8
P30
14
17.99
63.8932
191
0.28
0.7785
water* trt*day
-8
P30
28
58.94
42.9746
191
1.37
0.1718
water* trt*day
-8
P30
49
69.15
50.6951
191
1.36
0.1741
water* trt*day
-8
P30
77
71.26
38.4711
191
1.85
0.0655
water*trt*day
-8
P60
0
88.72
42.9828
191
2.06
0.0404
water*trt*dav
-8
P60
3
32.96
46.5836
191
0.71
0.4800

Table B-4. continued
Effect
water ('kPa')
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water*trt*day
-8
P60
7
82.70
40.6909
191
2.03
0.0435
water*trt*day
-8
P60
14
79.45
65.2003
191
1.22
0.2245
water*trt*day
-8
P60
28
75.85
46.5900
191
1.63
0.1051
water*trt*day
-8
P60
49
27.12
46.5874
191
0.58
0.5610
water*trt*day
-8
P60
77
29.20
50.7292
191
0.58
0.5655
water*trt*day
-8
CTL
0
121.91
38.4684
191
3.17
0.0018
water*trt*day
-8
CTL
3
52.6771
40.6663
191
1.30
0.1968
water*trt*day
-8
CTL
7
136.31
38.4466
191
3.55
0.0005
water* trt*day
-8
CTL
28
139.92
38.4638
191
3.64
0.0004
water* trt*day
-8
CTL
49
17.7610
78.1593
191
0.23
0.8205
water* trt*day
-8
CTL
77
75.4055
42.6330
191
1.77
0.0785
water* trt*day
-15
P100
0
221.59
38.4650
191
5.76
<.0001
water* trt*day
-15
P100
3
211.82
40.6675
191
5.21
<.0001
water* trt* day
-15
P100
7
100.40
43.3438
191
2.32
0.0216
water* trt* day
-15
P100
28
17.29
57.1008
191
0.30
0.7623
water*trt*day
-15
P100
77
284.93
40.7052
191
7.00
<.0001
water*trt*day
-15
P30
0
231.01
38.4638
191
6.01
<.0001
water* trt*day
-15
P30
3
148.59
38.4508
191
3.86
0.0002
water*trt*day
-15
P30
7
60.81
43.3434
191
1.40
0.1622
water*trt*day
-15
P30
28
54.65
40.7052
191
1.34
0.1810
water*trt*day
-15
P30
77
155.55
38.4822
191
4.04
<0001
water* trt*day
-15
P60
0
237.17
38.4638
191
6.17
<0001
water*trt*day
-15
P60
3
154.60
38.4453
191
4.02
<0001
water*trt*day
-15
P60
7
112.38
38.4638
191
2.92
0.0039
water*trt*day
-15
P60
28
113.29
43.3640
191
2.61
0.0097
water* trt*day
-15
P60
77
217.17
40.3986
191
5.38
<.0001
water*trt*dav
-15
CTL
0
244.80
38.4638
191
6.36
<0001

Table B-4. continued
Effect
water tkPat
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water* trt*day
-15
CTL
3
207.93
38.4638
191
5.41
<.0001
water*trt*day
-15
CTL
28
95.54
38.4822
191
2.48
0.0139
water* trt*day
-15
CTL
77
250.46
43.3640
191
5.78
<.0001
water*trt*day
-1000
P100
0
66.41
43.3430
191
1.53
0.1271
water*trt*day
-1000
P100
3
331.75
38.4557
191
8.63
<.0001
water* trt*day
-1000
P100
7
70.29
42.9481
191
1.64
0.1033
water* trt*day
-1000
P100
14
95.46
38.4557
191
2.48
0.0139
water*trt*day
-1000
P100
28
87.69
50.7140
191
1.73
0.0854
water* trt*day
-1000
P100
77
533.44
38.4822
191
13.86
<.0001
water* trt*day
-1000
P30
0
62.57
63.8716
191
0.98
0.3284
water*trt*day
-1000
P30
3
267.04
38.4577
191
6.94
<.0001
water* trt*day
-1000
P30
7
183.02
38.4453
191
4.76
<.0001
water* trt*day
-1000
P30
14
144.17
38.4638
191
3.75
0.0002
water* trt*day
-1000
P30
28
75.94
110.69
191
0.69
0.4935
water*trt*day
-1000
P30
77
681.49
38.4822
191
17.71
<.0001
water* trt*day
-1000
P60
0
113.33
65.1970
191
1.74
0.0838
water* trt*day
-1000
P60
3
266.16
38.4682
191
6.92
<.0001
water*trt*day
-1000
P60
7
93.38
46.5750
191
2.00
0.0464
water* trt* day
-1000
P60
14
108.46
38.4513
191
2.82
0.0053
water*trt*day
-1000
P60
28
107.60
40.3772
191
2.66
0.0084
water*trt*day
-1000
P60
77
475.36
38.4822
191
12.35
<.0001
water* trt*day
-1000
CTL
0
112.17
78.2731
191
1.43
0.1535
water* trt*day
-1000
CTL
3
284.39
47.1308
191
6.03
<.0001
water* trt* day
-1000
CTL
7
55.64
56.1780
191
0.99
0.3232
water* trt* day
-1000
CTL
14
171.08
40.3906
191
4.24
<.0001
water* trt*dav
-1000
CTL
77
76.58
65.2383
191
1.17
0.2419

Table B-5. Analysis of variance table for microbial C from all fertilizer treatments (including DAP). Trt = fertilizer treatment,
P100 = 100 ke P ha'1. P60 = 60 ke P ha'1, P30 = 30 kg P ha'1. CTL = control (0 kg P ha’1)
Tvne 3 Tests of Fixed Effects
Num Den
Effect
DF
DF
F Value
Pr > F
water
4
50
3.17
0.0212
trt
4
50
77.00
<.0001
day
6
226
11.54
<.0001
water* trt
16
50
1.93
0.0394
water* day
21
226
6.05
<.0001
trt* day
24
226
10.18
<.0001
water*trt*dav
79
226
4.95
<.0001
Least Squares Means
Standard
Effect
water ikPal
trt
dav
Estimate
Error
DF
t Value
Pr > Itl
water*trt*day
-0.1
DAP
0
339.77
282.76
226
1.20
0.2308
water*trt*day
-0.1
DAP
3
1337.23
302.15
226
4.43
<.0001
water*trt*day
-0.1
DAP
7
1759.15
399.49
226
4.40
<.0001
water*trt*day
-0.1
DAP
14
1234.73
355.91
226
3.47
0.0006
water*trt*day
-0.1
DAP
28
1556.70
357.03
226
4.36
<.0001
water* trt*day
-0.1
DAP
49
2905.45
301.48
226
9.64
<.0001
water*trt*day
-0.1
DAP
77
888.35
356.47
226
2.49
0.0134
water* trt*day
-0.1
P100
0
47.75
266.68
226
0.18
0.8581
water*trt*day
-0.1
P100
3
160.41
266.67
226
0.60
0.5481
water*trt*day
-0.1
P100
7
142.90
266.67
226
0.54
0.5926
water* trt* day
-0.1
P100
14
105.68
266.68
226
0.40
0.6923
water*trt*day
-0.1
P100
28
430.50
302.15
226
1.42
0.1556
water* trt*dav
-0.1
P100
49
103.89
282.76
226
0.37
0.7137

Table B-5. continued
Effect
water fkPal
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water* trt*day
-0.1
P100
77
89.94
302.15
226
0.30
0.7662
water*trt*day
-0.1
P30
0
159.55
301.82
226
0.53
0.5976
water*trt*day
-0.1
P30
3
176.07
282.48
226
0.62
0.5337
water*trt*day
-0.1
P30
7
63.56
302.15
226
0.21
0.8336
water*trt*day
-0.1
P30
14
177.68
282.76
226
0.63
0.5304
water*trt*day
-0.1
P30
28
259.47
326.18
226
0.80
0.4272
water* trt*day
-0.1
P30
49
164.86
282.48
226
0.58
0.5601
water*trt*day
-0.1
P30
77
175.88
399.48
226
0.44
0.6602
water* trt* day
-0.1
P60
0
212.18
282.76
226
0.75
0.4538
water*trt*day
-0.1
P60
3
173.44
266.68
226
0.65
0.5161
water*trt*day
-0.1
P60
7
170.02
266.67
226
0.64
0.5244
water*trt*day
-0.1
P60
14
172.07
302.15
226
0.57
0.5696
water* trt*day
-0.1
P60
28
212.62
325.75
226
0.65
0.5146
water* trt*day
-0.1
P60
49
179.03
266.68
226
0.67
0.5027
water* trt* day
-0.1
P60
77
127.40
325.75
226
0.39
0.6961
water*trt*day
-0.1
CTL
0
107.51
266.68
226
0.40
0.6872
water*trt*day
-0.1
CTL
3
182.34
266.68
226
0.68
0.4948
water* trt* day
-0.1
CTL
7
433.89
399.48
226
1.09
0.2786
water* trt*day
-0.1
CTL
14
105.44
282.76
226
0.37
0.7096
water*trt*day
-0.1
CTL
28
214.35
302.15
226
0.71
0.4788
water*trt*day
-0.1
CTL
49
180.98
282.76
226
0.64
0.5228
water*trt*day
-0.1
CTL
77
169.20
302.15
226
0.56
0.5761
water* trt* day
-3
DAP
0
153.56
266.68
226
0.58
0.5653
water*trt*day
-3
DAP
3
1700.55
326.18
226
5.21
<.0001
water* trt* day
-3
DAP
7
1017.74
357.03
226
2.85
0.0048
water* trt* day
-3
DAP
14
3442.11
266.68
226
12.91
<.0001
water* trt*dav
-3
DAP
28
769.14
357.03
226
2.15
0.0323

Table B-5. continued
Effect
water fkPa'l
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water* trt*day
-3
DAP
49
947.61
357.03
226
2.65
0.0085
water* trt*day
-3
DAP
77
315.50
795.83
226
0.40
0.6922
water* trt*day
-3
P100
0
196.20
282.76
226
0.69
0.4885
water*trt*day
-3
P100
3
200.11
266.67
226
0.75
0.4538
water*trt*day
-3
P100
7
137.64
266.67
226
0.52
0.6063
water*trt*day
-3
P100
14
181.10
266.67
226
0.68
0.4978
water*trt*day
-3
P100
28
138.20
266.67
226
0.52
0.6048
water*trt*day
-3
P100
49
138.17
266.68
226
0.52
0.6049
water*trt*day
-3
P100
77
66.53
795.81
226
0.08
0.9334
water*trt*day
-3
P30
0
108.87
326.18
226
0.33
0.7389
water*trt*day
-3
P30
3
90.19
302.15
226
0.30
0.7656
water*trt*day
-3
P30
7
136.74
266.68
226
0.51
0.6086
water*trt*day
-3
P30
14
217.08
282.76
226
0.77
0.4435
water* trt*day
-3
P30
28
67.81
326.18
226
0.21
0.8355
water* trt*day
-3
P30
49
76.05
302.15
226
0.25
0.8015
water*trt*day
-3
P30
77
54.58
398.70
226
0.14
0.8912
water*trt*day
-3
P60
0
129.84
301.82
226
0.43
0.6675
water*trt*day
-3
P60
3
97.12
282.76
226
0.34
0.7315
water* trt*day
-3
P60
7
181.83
266.68
226
0.68
0.4960
water* trt*day
-3
P60
14
257.50
357.03
226
0.72
0.4715
water*trt*day
-3
P60
28
108.98
266.68
226
0.41
0.6832
water*trt*day
-3
P60
49
246.40
266.68
226
0.92
0.3565
water* trt*day
-3
P60
77
59.50
326.18
226
0.18
0.8554
water* trt*day
-3
CTL
0
200.88
357.60
226
0.56
0.5748
water*trt*day
-3
CTL
3
124.03
282.76
226
0.44
0.6613
water* trt* day
-3
CTL
7
305.01
282.76
226
1.08
0.2819
water*trt*day
-3
CTL
14
211.32
266.68
226
0.79
0.4289
water*trt*dav
-3
CTL
28
62.19
326.18
226
0.19
0.8490

Table B-5. continued
Effect
water
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water*trt*day
-3
CTL
49
45.91
357.03
226
0.13
0.8978
water*trt*day
-3
CTL
77
83.57
266.68
226
0.31
0.7543
water*trt*day
-8
DAP
0
108.38
282.76
226
0.38
0.7019
water*trt*day
-8
DAP
3
2103.15
398.70
226
5.27
<.0001
water* trt* day
-8
DAP
7
1103.06
562.74
226
1.96
0.0512
water*trt*day
-8
DAP
28
922.08
398.70
226
2.31
0.0216
water*trt*day
-8
DAP
49
5909.20
326.18
226
18.12
<.0001
water*trt*day
-8
P100
0
71.87
302.16
226
0.24
0.8122
water* trt*day
-8
P100
3
64.79
795.81
226
0.08
0.9352
water*trt*day
-8
P100
7
116.92
266.68
226
0.44
0.6615
water* trt*day
-8
PI 00
28
98.59
282.48
226
0.35
0.7274
water* trt*day
-8
P100
49
157.15
282.48
226
0.56
0.5785
water*trt*day
-8
P30
0
83.02
282.76
226
0.29
0.7693
water*trt*day
-8
P30
3
150.29
266.67
226
0.56
0.5736
water*trt*day
-8
P30
7
85.73
266.68
226
0.32
0.7481
water*trt*day
-8
P30
14
17.84
459.47
226
0.04
0.9691
water*trt*day
-8
P30
28
59.13
301.82
226
0.20
0.8448
water*trt*day
-8
P30
49
69.15
357.03
226
0.19
0.8466
water* trt* day
-8
P30
77
71.08
266.68
226
0.27
0.7901
water* trt*day
-8
P60
0
88.26
301.82
226
0.29
0.7702
water* trt*day
-8
P60
3
33.46
326.18
226
0.10
0.9184
water*trt*day
-8
P60
7
82.84
282.76
226
0.29
0.7698
water* trt*day
-8
P60
14
80.57
460.68
226
0.17
0.8613
water*trt*day
-8
P60
28
77.13
326.18
226
0.24
0.8133
water*trt*day
-8
P60
49
27.59
326.18
226
0.08
0.9327
water* trt* day
-8
P60
77
28.90
357.03
226
0.08
0.9355
water* trt* day
-8
CTL
0
121.37
266.68
226
0.46
0.6495
water* trt*dav
-8
CTL
3
2.02
282.76
226
0.18
0.8542

Table B-5. continued
Effect
water
trt
dav
Estimate
Standard
Error
DF
t Value
Pr > Itl
water* trt* day
-8
CTL
7
136.28
266.67
226
0.51
0.6098
water*trt*day
-8
CTL
28
139.71
266.68
226
0.52
0.6009
water*trt*day
-8
CTL
49
16.99
562.73
226
0.03
0.9759
water*trt*day
-8
CTL
77
75.87
301.48
226
0.25
0.8015
water*trt*day
-15
DAP
0
227.73
266.68
226
0.85
0.3940
water*trt*day
-15
DAP
3
8581.38
282.76
226
30.35
<.0001
water*trt*day
-15
DAP
7
748.02
399.49
226
1.87
0.0624
water*trt*day
-15
DAP
28
549.44
795.83
226
0.69
0.4907
water*trt*day
-15
DAP
77
1720.11
795.83
226
2.16
0.0317
water*trt*day
-15
P100
0
222.57
266.68
226
0.83
0.4048
water*trt*day
-15
P100
3
211.73
282.76
226
0.75
0.4548
water*trt*day
-15
P100
7
99.34
302.15
226
0.33
0.7426
water*trt*day
-15
P100
28
17.13
399.49
226
0.04
0.9658
water*trt*day
-15
P100
77
286.24
282.76
226
1.01
0.3125
water*trt*day
-15
P30
0
231.39
266.68
226
0.87
0.3865
water* trt*day
-15
P30
3
147.71
266.68
226
0.55
0.5802
water* trt* day
-15
P30
7
60.56
302.15
226
0.20
0.8413
water*trt*day
-15
P30
28
54.58
282.76
226
0.19
0.8471
water* trt*day
-15
P30
77
155.30
266.68
226
0.58
0.5609
water*trt*day
-15
P60
0
236.38
266.68
226
0.89
0.3764
water* trt* day
-15
P60
3
154.76
266.67
226
0.58
0.5623
water*trt*day
-15
P60
7
111.77
266.68
226
0.42
0.6755
water*trt*day
-15
P60
28
111.40
302.16
226
0.37
0.7127
water* trt* day
-15
P60
77
216.38
282.48
226
0.77
0.4445
water* trt* day
-15
CTL
0
244.08
266.68
226
0.92
0.3610
water*trt*day
-15
CTL
3
208.10
266.68
226
0.78
0.4360
water*trt*day
-15
CTL
28
95.24
266.68
226
0.36
0.7213
water*trt*dav
-15
CTL
77
251.93
302.16
226
0.83
0.4053

Table B-S. continued
Effect
water
trt
day
Estimate
Standard
Error
DF
t Value
Pr > Itl
water* trt* day
-1000
DAP
0
156.65
562.74
226
0.28
0.7810
water* trt* day
-1000
DAP
3
1276.25
302.16
226
4.22
<.0001
water*trt*day
-1000
DAP
7
941.89
564.96
226
1.67
0.0969
water*trt*day
-1000
DAP
14
1207.66
459.48
226
2.63
0.0092
water*trt*day
-1000
DAP
28
766.18
398.70
226
1.92
0.0559
water*trt*day
-1000
DAP
77
2913.93
326.18
226
8.93
<.0001
water*trt*day
-1000
P100
0
65.78
302.15
226
0.22
0.8279
water* trt*day
-1000
P100
3
330.36
266.68
226
1.24
0.2167
water* trt*day
-1000
P100
7
67.74
301.81
226
0.22
0.8226
water*trt*day
-1000
P100
14
96.79
266.68
226
0.36
0.7170
water* trt*day
-1000
P100
28
88.46
357.03
226
0.25
0.8045
water*trt*day
-1000
PI 00
77
532.64
266.68
226
2.00
0.0470
water* trt*day
-1000
P30
0
62.91
459.47
226
0.14
0.8912
water* trt* day
-1000
P30
3
268.12
266.68
226
1.01
0.3158
water* trt*day
-1000
P30
7
182.30
266.67
226
0.68
0.4949
water*trt*day
-1000
P30
14
143.21
266.68
226
0.54
0.5918
water* trt*day
-1000
P30
28
76.30
795.83
226
0.10
0.9237
water* trt*day
-1000
P30
77
681.36
266.68
226
2.56
0.0113
water*trt*day
-1000
P60
0
114.87
460.68
226
0.25
0.8033
water* trt*day
-1000
P60
3
267.72
266.68
226
1.00
0.3165
water*trt*day
-1000
P60
7
92.30
326.18
226
0.28
0.7775
water*trt*day
-1000
P60
14
108.61
266.68
226
0.41
0.6842
water*trt*day
-1000
P60
28
107.69
282.48
226
0.38
0.7034
water*trt*day
-1000
P60
77
475.85
266.68
226
1.78
0.0757
water*trt*day
-1000
CTL
0
111.98
562.74
226
0.20
0.8424
water* trt*day
-1000
CTL
3
285.75
326.61
226
0.87
0.3826
water* trt* day
-1000
CTL
7
54.96
398.70
226
0.14
0.8905
water* trt*day
-1000
CTL
14
171.25
282.48
226
0.61
0.5450
water*trt*dav
-1000
CTL
77
76.81
460.68
226
0.17
0.8677

Microbial C (|tg g'1 soil)
APPENDIX C
FERTILIZATION STUDY FIGURES
— *— dayO
— * -day 3
— - day 7
—*—day 14
— * -day 28
—*— day 77
Figure C-1. Microbial C by day at each P fertilizer treatment within a) -0.1 kPa, b) -3
kPa, c) -8 kPa, d) -15 kPa, and e) -1000 kPa
125

Microbial C (ng g'1 soil) o Microbial C (ng g'1 soil)
126
800
700
600 -
500 )
800 -i
— •— day 0
— » -day 3
— - day 7
—x—day 14
— *• - day 28
—day 77
Figure C-1 continued

Microbial C (gg g'1 soil) a Microbial C (ng g'1 soil)
127
800
700 J
— ♦— dayO
— » -day 3
— -tr - day 7
—«—day 14
— * -day 28
—day 77
Figure C-l continued

Microbial P ((ig g"1 soil) o- Microbial P (gg g'1 soil)
128
â–  Control
Ü 30 kg P ha '
â–¡ 60 kg P ha
â–¡ 100 kg P ha
Figure C-2. Microbial P by P fertilizer treatment for each day within a) -0.1 kPa, b) -3
kPa, c) -8 kPa, d) -15 kPa, and e) -1000 kPa

Microbial P (ng g'1 soil) Microbial P (ng g'1 soil)
129
70 -|
â–  Control
M 30 kg P ha '
â–¡ 60 kg P ha'1
â–¡ 100 kg P ha
Figure C-2 continued

130
e
Days from beginning of study
â–  Control
M 30 kg P ha
â–¡ 60 kg P ha '
â–¡ 100 kg P ha
Figure C-2 continued

Microbial P (pg g'1 soil) a- Microbial P (pg g'1 soil)
131
a
60 -i
50 -
40 -
30 -
20 -
0 20 40 60 80
Days from beginning of study
-0.1 kPa
-3 kPa
—• - -8 kPa
i -15 kPa
—* 1000 kPa
Days from beginning of study
Figure C-3. Microbial P by water potential for each day within a) control, b) 30 kg P ha'1,
c) 60 kg P ha'1, and d) 100 kg P ha'1

Microbial P (ng g'1 soil) a. Microbial P (ng g'1 soil)
132
c
Days from beginning of study
—►—-0.1 kPa
—■— -3 kPa
—• - -8 kPa
- -15 kPa
—* 1000 kPa
Figure C-3 continued

Microbial P (pg g"' soil) Microbial P (pg g'1 soil)
133
60
60
50 -
40 -
0 30 60 100
P fertilizer added (kg P ha'1)
â–  -0.1 kPa
H-3 kPa
â–¡ -8 kPa
â–¡ -15 kPa
â–  -1000 kPa
Figure C-4. Microbial P by water potential in each P fertilizer treatment within a) day 0,
b) day 3, c) day 7, d) day 14, e) day 28, and f) day 77

134
c
O 30 60 100
P fertilizer added (kg P ha’1)
d
P fertilizer added (kg P ha'1)
â–  -0.1 kPa
M -3 kPa
â–¡ -8 kPa
â–¡ -15 kPa
H -1000 kPa
Figure C-4 continued

Microbial P (ng g'1 soil) Microbial P (jig g'! soil)
135
P fertilizer added (kg P ha"1)
P fertilizer added (kg P ha"1)
â–  -0.1 kPa
Ü-3 kPa
â–¡ -8 kPa
â–¡ -15 kPa
â–  -1000 kPa
Figure C-4 continued

Microbial C (pg g"1 soil) cr Microbial C (pg g"1 soil)
136
a
Days from beginning of study
— -0.1 kPa
-3 kPa
-8 kPa
-15 kPa
-1000 kPa
Figure C-5. Microbial C by water potential for each day within a) control, b) 30 kg P ha'
treatment, c) 60 kg P ha'1 treatment, and d) 100 kg P ha"1 treatment

137
c
700 -i
d
— 0.1 kPa
—■ --3 kPa
- - -8 kPa
—• 15 kPa
—« 1000 kPa
Days from beginning of study
Figure C-5 continued

Microbial C (pg g'1 soil) Microbial C (pg g1 soil)
138
700
600 -
500
P fertilizer added (kg ha'1)
— -0.1 kPa
— ■ —3 kPa
— - -8 kPa
—• 15 kPa
—m 1000 kPa
Figure C-6. Microbial C by water potential for each treatment for a) day 0, b) day 3, c)
day 7, d) day 14, e) day 28, and f) day 77

Microbial C (^g g'1 soil) Microbial C (ng g'1 soil)
139
700 -i
— « 0.1 kPa
— ■ —-3 kPa
— - -8 kPa
-15 kPa
-lOOOkPa
Figure C-6 continued

Microbial C (|rg g' soil) ■-*> Microbial C (ng g’1 soil)
140
— « 0.1 kPa
— ■ —-3 kPa
— - -8 kPa
—• 15 kPa
P fertilizer added (kg ha1)
Figure C-6 continued

141
a
b
—•—day 0
—■—day 3
day 7
—x—day 14
- - day 28
- - day 77
Figure C-7. Microbial P by day for each P fertilizer treatment within a) -0.1 kPa, b) -3
kPa, c) -8 kPa, d) -15 kPa, and e) -1000 kPa

Microbial P (ng g1 soil) ^ Microbial P (jig g1 soil)
142
—•—day 0
—■—day 3
a day 7
—x—day 14
- - day 28
- - day 77
Figure C-7 continued

143
e
O 20 40 60 80 100
P fertilizer added (kg P ha'1)
—♦—day 0
—■—day 3
- - - a- - • day 7
—*—day 14
- - day 28
- - day 77
Figure C-7 continued

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BIOGRAPHICAL SKETCH
Christine Bliss was bom to Barbara and Michael Bliss in Big Rapids, Michigan,
USA. She grew up in Reed City, Michigan, and attended Reed City High School until
she graduated in the top ten of her class in 1987. She then attended Michigan
Technological University and received a B.S. degree in forestry in 1991. During
summers, she enhanced her professional development by working for the U.S. Forest
Service, the Michigan Department of Natural Resources, and Mead Paper Corporation.
She continued to work as a field researcher and attend classes towards a graduate degree
the Michigan Tech. In the summer of 1994, she began to work towards a Ph.D. in the
Soil and Water Science Department at the University of Florida. Along the way, she has
furthered her professional skills while on break from the graduate work as a Program
Coordinator for the GREAN (Global Research on the Environmental and Agricultural
Nexus) Initiative. She intends to continue as a research scientist after receiving her
doctorate in forest soils.
154

I certify that I have read this study and that in my opinion it conforms to acceptable
standards of scholarly presentation and is fully adequate, in scope and quality, as a
dissertation for the degree of Doctor of Philosophy.
Nicholas B. Comerford, Chair '
Professor of Soil and Water Science
I certify that I have read this study and that in my opinion it conforms to acceptable
standards of scholarly presentation and is fully adequate, in scope and quality, as a
dissertation for the degree of Doctor of Philosophy
K.R. Reddy
Graduate Research Professor of Soil and
Water Science
I certify that I have read this study and that in my opinion it conforms to acceptable
standards of scholarly presentation and is fully adequate, in scope and quality, as a
dissertation for the degree of Doctor of Philosophy.
R.D. Rhue
Professor of Soil and Water Science
I certify that I have read this study and that in my opinion it conforms to acceptable
standards of scholarly presentation and is fully adequate, in scope and quality, as a
dissertation for the degree of Doctor of Philosophy. „
( L
E.J. Jokela'
Professor of Forest Resources and
Conservation
I certify that I have read this study and that in my opinion it conforms to acceptable
standards of scholarly presentation and is fully adequate, in scope and quality, as a
dissertation for the degree of Doctor of Philosophy.
R.M. Muchovej
Assistant Professor of Agronomy

This dissertation was submitted to the Graduate Faculty of the College of
Agricultural and Life Sciences and to the Graduate School and was accepted as partial
fulfillment of the requirements for the degree of Doctor of Philosophy:
August 2003
Dean, College of Agricultural ami
Sciences
Dean, Graduate School

UNIVERSITY OF FLORIDA
3 1262 08556 6171




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7DEOH %O FRQWLQXHG /HDVW 6TXDUHV 0HDQV 6WDQGDUG (IIHFW KRUL]RQ ZDWHU N3Df H[WUDFW (VWLPDWH (UURU ') W 9DOXH 3U! WWO KRUL]RQr ZDWHU r H[WUDFW $ %. KRUL]RQr ZDWHUrH[WUDFW $ '$ KRUL]RQr ZDWHUrH[WUDFW $ 1D+& KRUL]RQr ZDWHUr H[WUDFW $ 2[O KRUL]RQr ZDWHUrH[WUDFW $ [ KRUL]RQrZDWHUrH[WUDFW $ [ KRUL]RQr ZDWHUrH[WUDFW $ %. KRUL]RQr ZDWHUr H[WUDFW $ '$ KRUL]RQrZDWHUr H[WUDFW $ 1D+& KRUL]RQ r ZDWHUrH[WUDFW $ 2[O KRUL]RQr ZDWHUr H[WUDFW $ [ KRUL]RQrZDWHUr H[WUDFW $ [ KRUL]RQr ZDWHUr H[WUDFW $ %. KRUL]RQrZDWHUrH[WUDFW $ '$ KRUL]RQrZDWHUrH[WUDFW $ 1D+& KRUL]RQrZDWHUrH[WUDFW $ 2[O KRUL]RQr ZDWHUrH[WUDFW $ [ KRUL]RQr ZDWHUr H[WUDFW $ [ KRUL]RQr ZDWHUrH[WUDFW $ %. KRUL]RQrZDWHUrH[WUDFW $ '$ KRUL]RQrZDWHUrH[WUDFW $ 1D+& KRUL]RQr ZDWHUrH[WUDFW $ 2[O KRUL]RQr ZDWHUrH[WUDFW $ [ KRUL]RQrZDWHUrH[WUDFW $ [ KRUL]RQr ZDWHUrH[WUDFW $ %. KRUL]RQr ZDWHUrH[WUDFW $ '$

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7DEOH % FRQWLQXHG (IIHFW KRUL]RQ ZDWHU LN3DO H[WUDFW (VWLPDWH 6WDQGDUG (UURU ') W 9DOXH 3U ,WO KRUL]RQr ZDWHUr H[WUDFW ( [ KRUL]RQrZDWHUrH[WUDFW ( [ KRUL]RQr ZDWHUrH[WUDFW ( %. KRUL]RQrZDWHUrH[WUDFW ( '$ KRUL]RQr ZDWHUrH[WUDFW ( 1D+& KRUL]RQrZDWHUrH[WUDFW ( 2[O KRUL]RQr ZDWHUrH[WUDFW ( [ KRUL]RQrZDWHUrH[WUDFW ( [ KRUL]RQr ZDWHUrH[WUDFW ( %. KRUL]RQr ZDWHUrH[WUDFW ( '$ KRUL]RQr ZDWHUrH[WUDFW ( 1D+& KRUL]RQr ZDWHUr H[WUDFW ( 2[O KRUL]RQr ZDWHUr H[WUDFW ( [ KRUL]RQr ZDWHUrH[WUDFW ( [ KRUL]RQr ZDWHUrH[WUDFW ( %. KRUL]RQrZDWHUrH[WUDFW ( '$ KRUL]RQrZDWHUrH[WUDFW ( 1D+& KRUL]RQrZDWHUrH[WUDFW ( 2[O KRUL]RQr ZDWHUr H[WUDFW ( [ KRUL]RQrZDWHUrH[WUDFW ( [ KRUL]RQrZDWHUrH[WUDFW ( %. KRUL]RQrZDWHUrH[WUDFW ( '$ KRUL]RQrZDWHUrH[WUDFW ( 1D+& KRUL]RQr ZDWHUr H[WUDFW ( 2[O KRUL]RQrZDWHUrH[WUDFW ( [ KRUL]RQr ZDWHUrH[WUDFW ( [

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7DEOH % $QDO\VLV RI YDULDQFH WDEOH IRU PLFURELDO 3 IURP WKH 3RQO\ IHUWLOL]HU WUHDWPHQWV 7UW IHUWLOL]HU WUHDWPHQW 3, NJ 3 KD3 NJ 3 KDn 3 NJ 3 KD &7/ FRQWURO NJ 3 KDnf 7\SH 7HVWV RI )L[HG (IIHFWV 1XP 'HQ (IIHFW ') ') ) 9DOXH 3U ) ZDWHU WUW GD\ ZDWHUr WUW ZDWHUrGD\ WUWrGD\ ZDWHUr WUWrGDY /HDVW 6TXDUHV 0HDQV (IIHFW ZDWHU ,N3DO WUW GDY (VWLPDWH 6WDQGDUG (UURU ') W 9DOXH 3U _W_ ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3, ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGDY 3

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7DEOH % FRQWLQXHG (IIHFW ZDWHU WN3DW WUW GDY (VWLPDWH 6WDQGDUG (UURU ') 3U ,WO ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUr WUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWr GD\ 3, ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGDY 3

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7DEOH % FRQWLQXHG (IIHFW ZDWHU WN3DO WUW GDY (VWLPDWH 6WDQGDUG (UURU ') W 9DOXH 3U ,WO ZDWHUrWUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3, ZDWHUrWUWrGDY 3

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7DEOH % FRQWLQXHG (IIHFW ZDWHU ,N3DO WUW GDY (VWLPDWH 6WDQGDUG (UURU ') W 9DOXH 3U ,WO ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUr WUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3, ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGDY 3

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7DEOH % FRQWLQXHG (IIHFW ZDWHU IN3Dn, WUW GDY (VWLPDWH 6WDQGDUG (UURU ') W 9DOXH 3U ,WO ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ 3, ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUr WUWrGDY 3

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7DEOH % FRQWLQXHG (IIHFW ZDWHU IN3DW WUW GDY (VWLPDWH 6WDQGDUG (UURU ') W 9DOXH 3U ,WO ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGDY &7/

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7DEOH % $QDO\VLV RI YDULDQFH WDEOH IRU PLFURELDO 3 IURP DOO IHUWLOL]HU WUHDWPHQWV LQFOXGLQJ '$3 7UW IHUWLOL]HU WUHDWPHQW 34 NJ 3 KDn 34 NF 3 KD 3 NJ 3 KDn &7/ FRQWURO NJ 3 KDnW 7\SH 7HVWV RI )L[HG (IIHFWV 1XP 'HQ (IIHFW ') ') ) 9DOXH 3U ) ZDWHU WUW GD\ ZDWHUrWUW ZDWHUrGD\ WUWrGD\ ZDWHUrWUWrGDY /HDVW 6DXDUHV 0HDQV (IIHFW ZDWHU WN3DO WUW GDY (VWLPDWH 6WDQGDUG (UURU ') W 9DOXH 3U ,WO ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUr WUWr GD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGDY 3

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7DEOH % FRQWLQXHG (IIHFW ZDWHU IN3DO WUW GDY (VWLPDWH 6WDQGDUG (UURU ') W 9DOXH 3U ,WO ZDWHUr WUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ &7/ ZDWHUr WUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUr WUWrGD\ &7/ ZDWHUr WUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUr WUWrGD\ '$3 ZDWHUrWUWrGDY 3

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7DEOH % FRQWLQXHG (IIHFW ZDWHU IN3DO WUW GDY (VWLPDWH 6WDQGDUG (UURU ') W 9DOXH 3U ,WO ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ &7/ ZDWHUr WUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGDY '$3

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(IIHFW ZDWHU WN3DW WUW GDY (VWLPDWH 6WDQGDUG (UURU ') W 9DOXH 3U ,WO ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUr WUWrGD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWr GD\ 3, ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGDY &7/

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7DEOH % FRQWLQXHG (IIHFW ZDWHU IN3DnO WUW GDY (VWLPDWH 6WDQGDUG (UURU ') W 9DOXH $ !! ZDWHUr WUWrGD\ &7/ ZDWHUr WUWrGD\ &7/ ZDWHUr WUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUr WUWrGD\ &7/ ZDWHUrWUWrGD\ '$3 ZDWHUr WUWrGD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGDY 3

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7DEOH % FRQWLQXHG (IIHFW ZDWHU IN3DW WUW GDY (VWLPDWH 6WDQGDUG (UURU ') W 9DOXH 3U ,WO ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ &7/ ZDWHUr WUWr GD\ &7/ ZDWHUr WUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUr WUWr GD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUr WUWr GD\ '$3 ZDWHUrWUWrGD\ '$3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGDY 3

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7DEOH % FRQWLQXHG (IIHFW ZDWHU IN3DO WUW GDY (VWLPDWH 6WDQGDUG (UURU ') W 9DOXH 3U ,WO ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ &7/ ZDWHUr WUWr GD\ &7/ ZDWHUr WUWr GD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGDY &7/

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7DEOH % $QDO\VLV RI YDULDQFH IRU PLFURELDO & IURP DOO 3RQO\ IHUWLOL]HU WUHDWPHQWV 7UW IHUWLOL]HU WUHDWPHQW 3, NJ 3 KD3 NJ 3 KDn 3 NJ 3 KD &7/ FRQWURO NJ 3 KDnf 7\SH 7HVWV RI )L[HG (IIHFWV (IIHFW 1XP ') 'HQ ') ) 9DOXH 3U ) ZDWHU WUW GD\ ZDWHUrWUW ZDWHUr GD\ WUWr GD\ ZDWHUr WUWrGDY ,HDVW 6DQDUHV 0HDQV (IIHFW ZDWHU WN3DO WUW GDY (VWLPDWH 6WDQGDUG (UURU ') W 9DOXH 3U ,WO ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3, ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGDY 3

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7DEOH % FRQWLQXHG (IIHFW ZDWHU WN3DO WUW GDY (VWLPDWH 6WDQGDUG (UURU ') W 9DOXH 3U ,WO ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUr WUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUr WUWrGD\ &7/ ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWr GD\ 3

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7DEOH % FRQWLQXHG (IIHFW ZDWHU N3DW WUW GDY (VWLPDWH 6WDQGDUG (UURU ') W 9DOXH 3U ,WO ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUrWUWrGD\ &7/ ZDWHUr WUWrGD\ &7/ ZDWHUr WUWrGD\ &7/ ZDWHUr WUWrGD\ &7/ ZDWHUr WUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUr WUWr GD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUr WUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGD\ 3 ZDWHUrWUWrGDY &7/

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