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Changes in soil viable microbial biomass and composition
reflect disturbance impacts and may serve as quantitative
end points for reversibility
David C. White1, Aaron Peacock1,
Sareh. J. Macnaughton2, James M. Cantu1, Virginia H. Dale3,
1.Center
for Biomarker Analysis, University of Tennessee,
Knoxville, TN 37932, 2AEA Technology Environment, Harwell,
Oxon, UK. 3Environmental Sciences Division Oak Ridge
National Laboratory, Oak Ridge, TN.
CBA
Changes in soil viable microbial biomass and composition
reflect disturbance impacts and may serve as quantitative
end points for reversibility
Microbial community provides multi-species multi-trophic level is analysis >>>
single species for Quantitative Toxicity Assessment
1. Surface Water Pollution Impact quantitatively reflected in the viable
biomass and community composition of the periphyrton microbiota*
Parallels Cerodaphnia and Pimephales promelas In acute & chronic tests
a) Most sensitive indicator is the increase in filamentous green algae and
decrease in diatoms with increasing pollution
Reflected in the phospholipid fatty acid analysis (PLFA)
Green algae 18:19c, 16:43, 18:26, 16:113t  with toxicity
Diatoms 22:66, 20:53*, 14:0, 18:26  with toxicity.
b).  PHA/PLFA & TG/PLFA [Storage/membrane lipid] with increasing toxic
exposure
Not need qualified personnel and tedious microscopic counts
*Guckert, J. B., S. C. Nold, H. L. Boston, and D. C. White. 1992. Periphyton response along an industrial effluent
gradient: Lipid-based physiological stress analysis and pattern recognition of microbial community structure.
Canad. J. Fish. Aquat Sci. 49: 2579-2587.
Changes in soil viable microbial biomass and composition
reflect disturbance impacts and may serve as quantitative
end points for reversibility
Microbial community provides multi-species multi-trophic level is analysis >>>
single species for Quantitative Toxicity Assessment (3 dates)
Least Impacted
.
22:66
20:53*
14:0
18:26

Diatoms
Most Impacted
18:19c,
16:43,
18:26,
16:113t
 Green
Filamentous
Algae
Intermediate Impacted
Pollution Impacts in Soils
Petroleum Bioremediation of soils at Kwajalein
Nutrient Amendment and Ex Situ Composting vs Control Showed:
1.  VIABLE BIOMASS (PLFA)
2. SHIFT PROPORTIONS: Gram + , Gram - 
(Terminal branched PLFA,  :: Monoenoic, normal PLFA )
3.  Cyclo17:0/16:17c ::  Cyclo19:0/18:17c (Stress)
4. = 16:17t/16:7c (Toxicity), [often ]
5.  16:19c/16:17c (Decreased Aerobic Desaturase)
6.  % 10Me16:0 & Br17:1 PLFA (Sulfate-reducing bacteria)
7.  % 10Me18:0 (Actinomycetes)
8. = PROTOZOA, FUNGI + (Polyenoic PLFA) [ often  ]
In other studies also usually see:
1.  PHA/PLFA (Decreased Unbalanced Growth)
2.  RATIO BENZOQUINONE/NAPHTHOQUINONE
(Increased Aerobic Metabolism)
DEGREE OF SHIFT IN SIGNATURE LIPID BIOMARKERS PROPORTIONAL
TO DEGRADATION
Changes in soil viable microbial biomass and composition
reflect disturbance impacts and may serve as quantitative
end points for reversibility
Microbial community provides multi-species multi-trophic level is analysis >>>
single species for Quantitative Toxicity Assessment
2. Exposure to petroleum hydrocarbons acute & chronic tests
Shifts showed reversibility with time and distance plume had migrated
 biomass, Gram- negatives, UQ/MK,
 Gram- positive, branched PLFA,
PHA/PLFA
*Stephen, J. R., Y-J. Chang, Y. D. Gan, A. Peacock, S. M. Pfiffner, M. J. Barcelona, S. M. D. C.
White, and S. J. Macnaughton. 1999. Microbial Characterization of JP-4 fuel contaminated-site
using a combined lipid biomarker/PCR-DGGE based approach. Environmental Microbiology.
1: 231-241.
Changes in soil viable microbial biomass and composition
reflect disturbance impacts and may serve as quantitative
end points for reversibility
Microbial community provides multi-species multi-trophic level is analysis >>>
single species for Quantitative Toxicity Assessment
4. PHA/PLFA RATIO
Sensitive Measure Of Unbalanced Growth
Carbon Source + Terminal Electron Acceptor but Lacking Essential Nutrient(s)
Necessary For Cell Division
Cells attached to fine rootlets PHA/PLFA <<0.01
Cells in sand away from roots  PHA/PLFA > 6
Changes in soil viable microbial biomass and composition
reflect disturbance impacts and may serve as quantitative
end points for reversibility
Microbial community provides multi-species multi-trophic level is analysis >>>
single species for Quantitative Toxicity Assessment
4. PHA/PLFA
TOXICITY INCREASES RATIO WITH TREATMENT RATIO
DECREASES
Phytoremediation TCE  7 (2). In the rhizosphere of legume
0.0002 in nonvegetated soil
Subsurface Petroleum and TCE (+ propane & air) Bioremediation  ratio
between 5 & 35 compared to 0.08-0.2 without active remediation
Changes in soil viable microbial biomass and composition
reflect disturbance impacts and may serve as quantitative
end points for reversibility
Microbial community provides multi-species multi-trophic level is analysis >>>
single species for Quantitative Toxicity Assessment
3. Exposure of pine forest surface soils to vehicular traffic Fort Benning GA
Traffic
Reference ~ stands of longleaf pines (Pinus palustris) 28-74 years
Light ~ limited to infantry
Moderate ~ areas exposed to moderate amounts of tracked and light
vehicle maneuvers
Heavy ~ exclusively for heavy wheeled and tracked vehicle exercises
Remediated ~ Vehicles excluded & re-vegetated
-
Disturbance Intensity Gradient
Heavy
Moderate
Light
Control
Remediated
--Tank Maneuvers--Turning in
Neutral
Drive on
Tank Trails
----Target Practice--Heavy
Light
Artillery
Artillery
---Timber Harvest--Clear Cut
Selective
Thinning
---Infantry Training--Troop
Individual
Maneuvers
Orienteering
--Longleaf Pines –
24-74 years
Vehicles & Infantry
Excluded
Intensity of Disturbance
Hierarchical Time Overlap of Ecological Disturbance Indicators
Centuries
Decades
Years
Days
Spatial Distribution
of Cover Plants
Age Distribution of
Trees
Composition &
Distribution of
Understory Vegetation
Hours
Macroinvertebrate
Composition
Stream Metabolism
Storm Concentration
Macroinvertebrate
Populations
-------SOIL MICROORGANISMS------
Changes in soil viable microbial biomass and composition
reflect disturbance impacts and may serve as quantitative
end points for reversibility
Microbial community provides multi-species multi-trophic level is analysis >>>
single species for Quantitative Toxicity Assessment
3. Exposure of pine forest surface soils to vehicular traffic Fort Benning GA
Traffic
 disturbance  viable biomass (PLFA)
 18:0, 20:0, Me Br saturated
 mono and poly unsaturated, 14:0, 15:0, 16:0
with
 disturbance  in actinomycetes & spore-former Gram positives
 in gram-negative bacteria and microeukaryotes
RECOVERY APPROACHES REFERENCE
Changes in soil viable microbial biomass and composition
reflect disturbance impacts and may serve as quantitative
end points for reversibility
Microbial community provides multi-species multi-trophic level is analysis >>>
single species for Quantitative Toxicity Assessment
3. Exposure of pine forest surface soils to vehicular traffic Fort Benning GA
Traffic
 disturbance ~ changes in grasses, trees, bushes & stream properties
correlate with usage but requires Biological expertise to differentiate.
PLANT COMMUNITIES & STREAM ECOLOGY PARALLEL MICROBES
 disturbance  in actinomycetes & spore-former Gram positives
 in gram-negative bacteria and microeukaryotes
Requires chemistry ~ following protocol. for analysis of lipid biomarkers.
RECOVERY APPROACHES REFERENCE
Tree Diagram for 28 PLFA Variables
Ward`s method
1-Pearson r
i14:0
14:0
15:0
16:1w7c
16:0
16:1w5c
15:1
br16:0b
18:2w6
18:1w9c
18:1w5c
20:3w3
poly20b
17:1
20sat
poly20a
cy19:0
i16:0
i17:1w7c
10Me16:0
br16:0a
i17:0
i10Me16:0
12Me18:0
a17:0
17:0
18:0
20:0
Eukaryote and Gram-negative Bacterial PLFA
 in Gram-negative bacteria and microeukaryotes
Actinomycete Gram-positive
Actinomycete,
Type PLFA
Type PLFA
 in actinomycetes & spore-forming bacteria
0
2
4
6
8
Linkage Distance
Two clades of microbes  disturbance  in actinomycetes & spore-former
Gram positives,
 in Gram-negative bacteria and microeukaryotes
10
PLFA used in Discriminant Analysis
Linear Discriminant analysis
showed that the reference and light
transects were very similar while the
moderate and heavy transects
greatly differed in regards to the
microbial community structure.
a15:0
i17:0
i16:0
a17:0
18:1w9c
18:0
16:1w7c Cy17:0 10Me18:0
i17:1w7c 17:0
Cy19:0
10Me16:0 i10Me16:0 20’s sat
18:2w6
Generalized Squared Distances Between Groups
Light
Moderate
Heavy
Reference
0 5
40
80
Median Neural Network
61 Inputs
(PLFA)
5 Hidden
Nodes
4 Outputs
R2=0.97
Variables with ANN Sensitivity Values over 2%
10.00%
9.00%
8.00%
7.00%
6.00%
5.00%
4.00%
3.00%
2.00%
1.00%
0.00%
Gram-Negative, Microeukaryotes, Gram-positive, Actinomycetes
ANN Analysis
• Was able to correctly predict classification
66% of the time (25% chance only)
• Allowed inspection of novelty indexes which
showed that remediated transects are very
different from all other treatments
HYSTERESES OF RECOVERY
Predictive Analysis of disturbance using the soil
microbial community
• TWO APPROACHES:
• Linear Discriminant model using 17 PLFA predictor
variables
• Two groups  disturbance  in actinomycetes & spore-former
Gram positive bacteria,  in gram-negative bacteria and
microeukaryotes
• Non-linear Artificial Neural Network Analysis using all
60 PLFAs and microbial biomass
• Predict classification 66% of time (Chance = 25%)
Hysteresis in recovery from sensitivity
Soil viable microbial biomass and composition reflect
disturbance impacts and may serve as quantitative end
points for reversibility
Rational (Defensible) End Point
[Multi species, multiple tropic level assessments [vs single species toxicity
assessment ]
Recovered ƒ Reversibility of Microbial Community Composition
When uncontaminated soil, periphyton has same, or is approaching
the same type of community composition as treated sediment
SURFACE WATER
1.
Biofilms for run-off Diatoms  Filamentous Algae (pollution)
SOIL
2. Petroleum Hydrocarbon Contamination
 Gram-negative, Biomasss Gram-positive
  reversed with recovery
3. PHA/PLFA  with pollution    recovery
4. Disturbance (traffic)  disturbance  in actinomycetes & spore-former Gram
positives,  in gram-negative bacteria and microeukaryotes   reversed with
recovery