Changes in soil viable microbial biomass and composition reflect disturbance impacts and may serve as quantitative end points for reversibility

1
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
2
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 gtgtgt single
  species for Quantitative Toxicity Assessment
• 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 181?9c, 164?3, 182?6,
  161?13t ? with toxicity
• Diatoms 226?6, 205?3, 140, 182?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.

3
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 gtgtgt single
species for Quantitative Toxicity Assessment (3
dates) .
Most Impacted
Least Impacted
226?6 205?3 140 182?6 ? Diatoms
181?9c, 164?3, 182?6, 161?13t ?
Green Filamentous Algae

Intermediate Impacted
4
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. ? Cyclo170/161?7c ?
Cyclo190/181?7c (Stress) 4. 1617t/167c
(Toxicity), often ?   5. ? 161?9c/161?7c
(Decreased Aerobic Desaturase) 6. ? 10Me160
Br171 PLFA (Sulfate-reducing bacteria) 7. ?
10Me180 (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
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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 gtgtgt 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.

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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 gtgtgt 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 ltlt0.01
Cells in sand away from roots ? PHA/PLFA gt 6


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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 gtgtgt 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

8
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 gtgtgt 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 -

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Disturbance Intensity Gradient
Heavy Moderate
Light Control
Remediated --Tank Maneuvers--- Turning in
Drive on Neutral 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
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Hierarchical Time Overlap of Ecological
Disturbance Indicators
Centuries Decades
Years Days Hours Spatial
Distribution of Cover Plants
Age Distribution of
Trees Composition
Distribution of Understory Vegetation
Macroinvertebrate Compositi
on Stream Metabolism Storm
Concentration Macroinvertebrate
Populations
-------SOIL
MICROORGANISMS------
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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 gtgtgt single
species for Quantitative Toxicity Assessment
3. Exposure of pine forest surface soils to
vehicular traffic Fort Benning GA
Traffic ? disturbance ?
viable biomass (PLFA)
? 180, 200, Me Br saturated
? mono and poly unsaturated, 140, 150,
160 with ? disturbance ? in actinomycetes
spore-former Gram positives
? in gram-negative bacteria and
microeukaryotes
RECOVERY APPROACHES REFERENCE

12
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 gtgtgt 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

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Tree Diagram for 28 PLFA Variables
Wards method
1-Pearson r
i140
i140
140
140
150
150
161w7c
161w7c
160
160
161w5c
161w5c
Eukaryote and Gram-negative Bacterial PLFA
Eukaryote and Gram-negative Bacterial PLFA
151
151
br160b
br160b
? in Gram-negative bacteria and microeukaryotes
182w6
182w6
181w9c
181w9c
181w5c
181w5c
203w3
203w3
poly20b
poly20b
171
171
20sat
20sat
poly20a
poly20a
cy190
cy190
i160
i160
i171w7c
i171w7c
Actinomycete
Type PLFA
Actinomycete,
Gram-positive Type PLFA
10Me160
10Me160
br160a
br160a
? in actinomycetes spore-forming bacteria
i170
i170
i10Me160
i10Me160
12Me180
12Me180
a170
a170
170
170
180
180
200
200
0
2
4
6
8
10
0
2
4
6
8
10
Linkage Distance
Two clades of microbes ? disturbance ? in
actinomycetes spore-former Gram positives, ?
in Gram-negative bacteria and microeukaryotes
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PLFA used in Discriminant Analysis
a150 i170 181w9c i160 a170
180 161w7c Cy170 10Me180 i171w7c 170
Cy190 10Me160 i10Me160 20s sat
182w6
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.
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Median Neural Network
61 Inputs (PLFA) 5 Hidden Nodes 4 Outputs R20.97
16
Variables with ANN Sensitivity Values over 2
10.00
0.00
i160
i171
160
180
171
150
i161
170
a150
a170
181w7t
181w9c
br191a
poly20b
161w7c
12me160
181w5c
Gram-Negative, Microeukaryotes, Gram-positive,
Actinomycetes
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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

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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

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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
• 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