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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.

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Presentation on theme: "Changes in soil viable microbial biomass and composition reflect disturbance impacts and may serve as quantitative end points for reversibility David C."— Presentation transcript:

1 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, 1. Center for Biomarker Analysis, University of Tennessee, Knoxville, TN 37932, 2 AEA Technology Environment, Harwell, Oxon, UK. 3 Environmental 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 >>> 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 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:

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 >>> single species for Quantitative Toxicity Assessment (3 dates). Least Impacted Most Impacted 18:1  9c, 16:4  3, 18:2  6, 16:1  13t  Green Filamentous Algae 22:6  6 20:5  3* 14:0 18:2  6  Diatoms 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.  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

5 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 Microbial Characterization of JP-4 fuel contaminated-site using a combined lipid biomarker/PCR-DGGE based approach. Environmental Microbiology. 1:

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 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

7 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 in nonvegetated soil Subsurface Petroleum and TCE (+ propane & air) Bioremediation  ratio between 5 & 35 compared to 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 >>> 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) 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 -

9 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 – years Vehicles & Infantry Excluded Intensity of Disturbance

10 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 Composition Stream Metabolism Storm Concentration Macroinvertebrate Populations SOIL MICROORGANISMS------

11 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

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 >>> 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

13 20:0 18:0 17:0 a17:0 12Me18:0 i10Me16:0 i17:0 br16:0a 10Me16:0 i17:1w7c i16:0 cy19:0 poly20a 20sat 17:1 poly20b 20:3w3 18:1w5c 18:1w9c 18:2w6 br16:0b 15:1 16:1w5c 16:0 16:1w7c 15:0 14:0 i14: Eukaryote and Gram-negative Bacterial PLFA ActinomyceteType PLFA Tree Diagram for 28 PLFA Variables Ward`s method 1-Pearson r Linkage Distance 20:0 18:0 17:0 a17:0 12Me18:0 i10Me16:0 i17:0 br16:0a 10Me16:0 i17:1w7c i16:0 cy19:0 poly20a 20sat 17:1 poly20b 20:3w3 18:1w5c 18:1w9c 18:2w6 br16:0b 15:1 16:1w5c 16:0 16:1w7c 15:0 14:0 i14: 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

14 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

15 Median Neural Network 61 Inputs (PLFA) 5 Hidden Nodes 4 Outputs R 2= 0.97

16 0.00% 1.00% 2.00% 3.00% 4.00% 5.00% 6.00% 7.00% 8.00% 9.00% 10.00% 16: 1w7c 17 :0 18:1w9c 16:018:0 i16:0 i17:1 a15:0 12me16:0 br19:1a 18:1w7t 18:1w5c 17:1 a17:0 15:0 poly20b i16:1 Variables with ANN Sensitivity Values over 2% Gram-Negative, Microeukaryotes, Gram-positive, Actinomycetes

17 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

18 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

19 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


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