david c. white 1 , aaron peacock 1 ,
DESCRIPTION
Changes in soil viable microbial biomass and composition reflect disturbance impacts and may serve as quantitative end points for reversibility. David C. White 1 , Aaron Peacock 1 , Sareh. J. Macnaughton 2 , James M. Cantu 1 , Virginia H. Dale 3 ,. - PowerPoint PPT PresentationTRANSCRIPT
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 testsa) 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 18:19c, 16:43, 18:26, 16:113t with toxicity
Diatoms 22:66, 20:53*, 14:0, 18:26 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 Most Impacted
18:19c, 16:43, 18:26, 16:113t
GreenFilamentous Algae
22:66 20:53* 14:0 18:26
Diatoms
Intermediate Impacted
Pollution Impacts in Soils Petroleum Bioremediation of soils at KwajaleinNutrient Amendment and Ex Situ Composting vs Control Showed:
1. VIABLE BIOMASS (PLFA)
2. SHIFT PROPORTIONS: Gram + , Gram -
(Terminal branched PLFA, :: Monoenoic, normal PLFA )
3. Cyclo17:0/16:17c :: Cyclo19:0/18:17c (Stress)
4. = 16:17t/16:7c (Toxicity), [often ]
5. 16:19c/16:17c (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 GrowthCarbon 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 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
Hierarchical Time Overlap of Ecological Disturbance Indicators
Centuries Decades Years Days HoursSpatial Distribution of Cover Plants Age Distribution of Trees
Composition & Distribution ofUnderstory Vegetation
MacroinvertebrateComposition
Stream MetabolismStorm ConcentrationMacroinvertebrate 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
Linkage Distance
20:018:017:0
a17:012Me18:0i10Me16:0
i17:0br16:0a
10Me16:0i17:1w7c
i16:0cy19:0
poly20a20sat17:1
poly20b20:3w3
18:1w5c18:1w9c18:2w6br16:0b
15:116:1w5c
16:016:1w7c
15:014:0i14:0
0 2 4 6 8 10
Eukaryote and Gram-negative Bacterial PLFA
Actinomycete Type PLFA
Tree Diagram for 28 PLFA Variables
Ward`s method
1-Pearson r
Linkage Distance
20:018:017:0
a17:012Me18:0i10Me16:0
i17:0br16:0a
10Me16:0i17:1w7c
i16:0cy19:0
poly20a20sat17:1
poly20b20:3w3
18:1w5c18:1w9c18:2w6br16:0b
15:116:1w5c
16:016:1w7c
15:014:0i14:0
0 2 4 6 8 10
Eukaryote and Gram-negative Bacterial PLFA
Actinomycete, Gram-positive Type PLFA
Two clades of microbes disturbance in actinomycetes & spore-former
Gram positives, in Gram-negative bacteria and microeukaryotes
in Gram-negative bacteria and microeukaryotes
in actinomycetes & spore-forming bacteria
0 5 40 80
Reference
Light Moderate Heavy
Generalized Squared Distances Between Groups
0 5 40 80
Reference
Light Moderate Heavy
Generalized Squared Distances Between Groups
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 18:1w9c
i16:0 a17:0 18:0
16:1w7c Cy17:0 10Me18:0
i17:1w7c 17:0 Cy19:0
10Me16:0 i10Me16:0 20’s sat
18:2w6
PLFA used in Discriminant Analysis
Median Neural Network
61 Inputs (PLFA)5 Hidden Nodes4 OutputsR2=0.97
0.00%
1.00%
2.00%
3.00%
4.00%
5.00%
6.00%
7.00%
8.00%
9.00%
10.00%
16:1
w7c17
:0
18:1
w9c
16:0
18:0
i16:
0i1
7:1
a15:
0
12m
e16:
0
br19:
1a
18:1
w7t
18:1
w5c17
:1a1
7:0
15:0
poly20
b
i16:
1
Variables with ANN Sensitivity Values over 2%
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