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The microbial contribution to carbon 
and nutrient cycling across a variable 
tropical landscape 
Madeleine M. Stone 
Dissertation Defense 
November 21, 2014
Tropical forests dominate carbon fluxes in the 
terrestrial biosphere 
Amazon Basin
Soils are largest terrestrial carbon pool 
(1500 — 2000 Pg C) 
Tropical forests contribute disproportionately to 
subsoil C stocks, which have high potential for 
long-term C stabilization
Most carbon in soils exists as soil organic matter 
Schmidt et al. 2011, Nature 
Dissertation Proposal | October 19, 2012
Soil is the most biologically diverse habitat on Earth 
(thousands — millions species per gram) 
Soil microbial communities produce, maintain and 
decompose soil organic matter
Exo-enzymes link microbial ecology and soil biogeochemistry 
Substrate 
signaling 
Catabolic repression 
Product formation 
Enzyme 
production
Microbial stoichiometry links carbon, nitrogen and phosphorus cycling 
Substrate 
signaling 
Catabolic repression 
P 
P 
N 
N 
C 
C 
C 
C 
C 
C 
C 
C 
C 
Product formation 
60 : 7 : 1 
“Redfield ratio” for soil 
microbes? 
Enzyme 
production
In their search for energy and nutrients, 
microbes drive biogeochemical cycles of 
carbon, nitrogen and phosphorus. 
But what controls the microbes?
Luquillo Mountains, Puerto Rico 
Oxisol Inceptisol
Gradients in climate, vegetation 
Pre-montane forest 
(Colorado) 
Lowland forest 
(Tabonuco) ridge 
slope 
valley 
ridge 
slope 
valley
Environmental gradients with depth 
High resource 
surface soils 
Δ C, Nutrients, 
pH, moisture, 
oxygen 
Low resource subsoils
20 cm 
50 cm 
80 cm 
110 cm
What controls the 
biogeochemical capacity of soil 
microbes throughout the Luquillo 
Critical Zone?
1. Patterns in soil resources 
Stone, M.M., DeForest, J.L., Plante, A.F. (2014), Soil Biology & 
Biochemistry (Dissertation Chapter 3) 
Stone, M.M., Hockaday, W.C., Plante, A.F. In Preparation. 
(Dissertation Chapter 6) 
2. Patterns in soil microbes 
Stone, M.M., DeForest, J.L., Plante, A.F. (2014), Soil Biology & 
Biochemistry (Dissertation Chapter 3) 
Stone M. M., Plante, A.F. (2014) Soil Biology and Biochemistry 
(Dissertation Chapter 5) 
Stone, M.M., Plante, A.F. In preparation.
Sample Set 
Variable Forest Types Soil Types Landscape 
Positions 
Depths 
Basic soil 
characterization 
Colorado, 
Tabonuco 
Oxisol (VC), 
Inceptisol (QD) 
Ridge, 
(Slope x3), 
Valley 
0-140 cm 
(300 samples) 
Carbon 
Chemistry 
Colorado, 
Tabonuco 
Oxisol (VC), 
Inceptisol (QD) 
Ridge, Slope, 
Valley 
Various [C] > 
1% 
(34 samples) 
Microbial 
Biomass, 
Activity & 
Community 
Structure 
Colorado, 
Tabonuco 
Oxisol (VC), 
Inceptisol (QD) 
Ridge, Slope, 
Valley 
0, 20, 50, 80, 
110 & 140 cm 
(72 samples)
1. Patterns in soil resources 
Stone, M.M., DeForest, J.L., Plante, A.F. (2014), Soil Biology & 
Biochemistry (Dissertation Chapter 3) 
Stone, M.M., Hockaday, W.C., Plante, A.F. In Preparation. 
(Dissertation Chapter 6) 
2. Patterns in soil microbes 
Stone, M.M., DeForest, J.L., Plante, A.F. (2014), Soil Biology & 
Biochemistry (Dissertation Chapter 3) 
Stone M. M., Plante, A.F. (2014) Soil Biology and Biochemistry 
(Dissertation Chapter 5) 
Stone, M.M., Plante, A.F. In preparation.
1. Carbon and nutrient concentrations will decline rapidly from 
Plant inputs 
High resource 
surface soils 
Increased decomposition, 
Low resource subsoils 
Mineral association 
the surface 
2. Shifts in SOM chemistry from plant — microbial
1. Leaf litter chemistry (forest) will be important in determining 
surface soil organic matter composition 
2. Mineral associations (soil type) will be important in 
determining subsoil organic matter composition 
Plant inputs 
Increased decomposition, 
Mineral association
Basic soil characterization 
• Total C and N measured by combustion 
analysis 
• “Labile” P quantified using partial 
sequential Hedley fractionation (NaHCO3 
& NaOH-extractable) 
• Soil pH measured in DI water
Exponential declines in carbon and nutrients… 
mg g-1 soil mg g-1 soil mg kg-1 soil
More carbon in higher elevation 
forest 
Carbon and nitrogen along the upper 80 cm of soil profiles
13C Nuclear magnetic resonance spectroscopy (NMR)
• High O-alkyl C in soils, plant and microbial tissues 
• Enrichment in N-alkyl and amide C in fungal biomass 
• Enrichment in Alkyl C in SOM
Carbon Chemistry Distinct Across Forests 
Root 
Litter 
Fungi 
Colorado Forest Soil 
Tabonuco Forest Soil 
Root 
Phenolic Aromatic 
−0.2 −0.1 0.0 0.1 0.2 
−0.2 −0.1 0.0 0.1 0.2 
PC1 42 % 
DiOAlkyl 
PC2 32 % 
−4 −2 0 2 4 
−4 −2 0 2 4 
Alkyl 
Nalkyl 
Oalkyl 
Amide 
ColDys5 
Fungi 
Litter 
Alkyl 
DiOAlkyl 
Oalkyl 
Distinct Alkyl: O-alkyl ratios 
Root: 0.3 ± 0.0 
Fungi: 0.4 ± 0.2 
Litter: 0.6 ± 0.0 
Tabonuco: 0.7 ± 0.1 
Colorado: 2.1 ± 0.3
Depth trends in 
carbon chemistry 
observed at the 
individual soil profile 
level 
But different 
patterns were 
observed in each 
pit. 
Oxisol Valley Depth Profile 
Amide Aromatic O-Alkyl Alkyl
Greater amounts of poorer quality C in Colorado forest 
No differences across soil types! 
Changes in SOM chemistry with depth are observable at the level 
of individual profiles 
Alkyl C (lipids) may be particularly important for long-term tropical 
C storage
1. Patterns in soil resources 
Stone, M.M., DeForest, J.L., Plante, A.F. (2014), Soil Biology & 
Biochemistry (Dissertation Chapter 3) 
Stone, M.M., Hockaday, W.C., Plante, A.F. In Preparation. 
(Dissertation Chapter 6) 
2. Patterns in soil microbes 
Stone, M.M., DeForest, J.L., Plante, A.F. (2014), Soil Biology & 
Biochemistry (Dissertation Chapter 3) 
Stone M. M., Plante, A.F. (2014) Soil Biology and Biochemistry 
(Dissertation Chapter 5) 
Stone, M.M., Plante, A.F. In preparation.
1. Soil microbial biomass and activity will decline with 
depth, tracking declines in C and nutrients 
2. Specific metabolic activities will shift with depth, 
reflecting shifts in resource allocation 
3. Microbial community structure will shift with depth, 
tracking changing environment 
High resource 
surface soils 
Low resource subsoils
In subsoils, microbial 
In abundance, surface soils, activity microbial 
and 
structure abundance, will activity relate to and 
the 
physiochemical environment 
structure will relate to vegetation 
(soil type)
Phospholipid Fatty Acid Analysis 
Wikimedia 
Commons
Extract and quantify 
phospholipids for : 
1. Viable biomass 
2. Broad microbial 
community structure 
Fungi 
Actinobacteria
Soil Respiration 
CO2 evolution 
measured during 
90-day respiration 
experiment 
Respiration rate 
normalized to soil 
C and microbial C 
concentrations to 
determine specific 
metabolic activity
Fluorimetric Enzyme Assays 
α – glucosidase (starch) 
β-glucosidase (cellulose dimers) 
Natural process 
β-xylosidase (hemicellulose) 
cellobiohydrolase (cellulose oligomers) 
Fluorimetric assay 
N-acetyl glucosaminidase (chitin) 
acid phosphatase (organic phosphate) 
Total Potential Activity 
Specific Activity 
(Per carbon or biomass)
No substantial differences among landscape 
units (3-way ANOVA): 
Microbial 
biomass 
Cumulative 
respiration 
Total Enzyme 
Activity 
P value 
Soil parent material 
(VC vs. QD) 
0.85 0.39 0.27 
Forest type (Col vs. 
Tab) 
0.65 0.16 0.13* 
*2/4 carbon cycle enzymes significantly higher in Colorado forest
20 % 
P < 0.01
0 
0 
20 
20 
50 
50 
Depth (cm) 
Resp rate per unit soil 
Resp rate per unit soil 
0 
20 
50 
80 
80 
80 
110 
110 
110 
140 
Resp rate per unit soil 
0 2 4 6 
μg CO2g-1day-1 
Resp rate per unit soil C 
Resp rate per unit soil C 
Resp rate per unit soil C 
−1 0 1 
μg CO2mg C-1day-1 
Resp rate per unit microbial C 
Resp rate per unit microbial C 
Resp rate per unit microbial C 
0.2 0.4 0.6 
-1 day-1 
-1 day-1 
-1 day-1 
μg CO2mg Cmic 
140 
0 2 4 6 
μg CO2g-1day-1 
−1 0 1 
μg CO2mg C-1day-1 
0.2 0.4 0.6 
μg CO2mg Cmic 
7.8 x 
P = 0.07 
Depth (cm) 
140 
0 2 4 6 
μg CO2g-1day-1 
−1 0 1 
μg CO2mg C-1day-1 
0.2 0.4 0.6 
μg CO2mg Cmic
19 x 
P < 0.01
20 x 
(Mostly) NSD P < 0.01 
NSD 
High variability in deep soil enzyme activity 
Increased specific activity with depth driven largely by phosphatase
Why high specific metabolic activity in resource 
limited subsoils? 
Substrate 
signaling 
Catabolic repression 
Product formation 
Enzyme 
production
Stress due to resource scarcity? 
Substrate 
signaling 
Catabolic repression 
Product formation 
Enzyme 
production
Microbes strongly driven by energy availability
Decreased enzyme turnover rates? 
Substrate 
signaling 
Catabolic repression 
Product formation 
Enzyme 
production
High enzyme activity following sorption
Community shift? 
Substrate 
signaling 
Catabolic repression 
Product formation 
Enzyme 
production
Evidence for this! 
Depth P < 0.001 
66 % 
P = 0.01
1.7 
60.0 
What’s up with phosphatase? 
40% 
P = 0.01 
80% 
P = 0.01 
Increased phosphatase activity relative to C and N cycle enzymes suggests 
microbes at depth invest more in P acquisition 
Why?
Phosphatase activity driven by microbial carbon demand?
Energy availability drives microbial activity—much more than 
landscape differences 
Microbial biogeochemical capacity remains similar or increases 
with depth, per unit biomass 
High specific metabolic activity could be a stress response, 
decreased enzyme turnover, or community shifts 
Prevalence of phosphatase suggests a special role for this 
enzyme
Implications 
Microbes retain metabolic capacity for biogeochemical 
processes in low—energy subsoils 
“Stability” of deep soil carbon—microbial starvation? 
Starving – survival lifestyle?
Future Directions 
IPCC October, 2014
Thank you! 
Artwork:

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M Stone- Dissertation Defense

  • 1. The microbial contribution to carbon and nutrient cycling across a variable tropical landscape Madeleine M. Stone Dissertation Defense November 21, 2014
  • 2. Tropical forests dominate carbon fluxes in the terrestrial biosphere Amazon Basin
  • 3. Soils are largest terrestrial carbon pool (1500 — 2000 Pg C) Tropical forests contribute disproportionately to subsoil C stocks, which have high potential for long-term C stabilization
  • 4. Most carbon in soils exists as soil organic matter Schmidt et al. 2011, Nature Dissertation Proposal | October 19, 2012
  • 5. Soil is the most biologically diverse habitat on Earth (thousands — millions species per gram) Soil microbial communities produce, maintain and decompose soil organic matter
  • 6. Exo-enzymes link microbial ecology and soil biogeochemistry Substrate signaling Catabolic repression Product formation Enzyme production
  • 7. Microbial stoichiometry links carbon, nitrogen and phosphorus cycling Substrate signaling Catabolic repression P P N N C C C C C C C C C Product formation 60 : 7 : 1 “Redfield ratio” for soil microbes? Enzyme production
  • 8. In their search for energy and nutrients, microbes drive biogeochemical cycles of carbon, nitrogen and phosphorus. But what controls the microbes?
  • 9.
  • 10. Luquillo Mountains, Puerto Rico Oxisol Inceptisol
  • 11. Gradients in climate, vegetation Pre-montane forest (Colorado) Lowland forest (Tabonuco) ridge slope valley ridge slope valley
  • 12. Environmental gradients with depth High resource surface soils Δ C, Nutrients, pH, moisture, oxygen Low resource subsoils
  • 13. 20 cm 50 cm 80 cm 110 cm
  • 14. What controls the biogeochemical capacity of soil microbes throughout the Luquillo Critical Zone?
  • 15. 1. Patterns in soil resources Stone, M.M., DeForest, J.L., Plante, A.F. (2014), Soil Biology & Biochemistry (Dissertation Chapter 3) Stone, M.M., Hockaday, W.C., Plante, A.F. In Preparation. (Dissertation Chapter 6) 2. Patterns in soil microbes Stone, M.M., DeForest, J.L., Plante, A.F. (2014), Soil Biology & Biochemistry (Dissertation Chapter 3) Stone M. M., Plante, A.F. (2014) Soil Biology and Biochemistry (Dissertation Chapter 5) Stone, M.M., Plante, A.F. In preparation.
  • 16. Sample Set Variable Forest Types Soil Types Landscape Positions Depths Basic soil characterization Colorado, Tabonuco Oxisol (VC), Inceptisol (QD) Ridge, (Slope x3), Valley 0-140 cm (300 samples) Carbon Chemistry Colorado, Tabonuco Oxisol (VC), Inceptisol (QD) Ridge, Slope, Valley Various [C] > 1% (34 samples) Microbial Biomass, Activity & Community Structure Colorado, Tabonuco Oxisol (VC), Inceptisol (QD) Ridge, Slope, Valley 0, 20, 50, 80, 110 & 140 cm (72 samples)
  • 17. 1. Patterns in soil resources Stone, M.M., DeForest, J.L., Plante, A.F. (2014), Soil Biology & Biochemistry (Dissertation Chapter 3) Stone, M.M., Hockaday, W.C., Plante, A.F. In Preparation. (Dissertation Chapter 6) 2. Patterns in soil microbes Stone, M.M., DeForest, J.L., Plante, A.F. (2014), Soil Biology & Biochemistry (Dissertation Chapter 3) Stone M. M., Plante, A.F. (2014) Soil Biology and Biochemistry (Dissertation Chapter 5) Stone, M.M., Plante, A.F. In preparation.
  • 18. 1. Carbon and nutrient concentrations will decline rapidly from Plant inputs High resource surface soils Increased decomposition, Low resource subsoils Mineral association the surface 2. Shifts in SOM chemistry from plant — microbial
  • 19. 1. Leaf litter chemistry (forest) will be important in determining surface soil organic matter composition 2. Mineral associations (soil type) will be important in determining subsoil organic matter composition Plant inputs Increased decomposition, Mineral association
  • 20. Basic soil characterization • Total C and N measured by combustion analysis • “Labile” P quantified using partial sequential Hedley fractionation (NaHCO3 & NaOH-extractable) • Soil pH measured in DI water
  • 21. Exponential declines in carbon and nutrients… mg g-1 soil mg g-1 soil mg kg-1 soil
  • 22. More carbon in higher elevation forest Carbon and nitrogen along the upper 80 cm of soil profiles
  • 23. 13C Nuclear magnetic resonance spectroscopy (NMR)
  • 24. • High O-alkyl C in soils, plant and microbial tissues • Enrichment in N-alkyl and amide C in fungal biomass • Enrichment in Alkyl C in SOM
  • 25. Carbon Chemistry Distinct Across Forests Root Litter Fungi Colorado Forest Soil Tabonuco Forest Soil Root Phenolic Aromatic −0.2 −0.1 0.0 0.1 0.2 −0.2 −0.1 0.0 0.1 0.2 PC1 42 % DiOAlkyl PC2 32 % −4 −2 0 2 4 −4 −2 0 2 4 Alkyl Nalkyl Oalkyl Amide ColDys5 Fungi Litter Alkyl DiOAlkyl Oalkyl Distinct Alkyl: O-alkyl ratios Root: 0.3 ± 0.0 Fungi: 0.4 ± 0.2 Litter: 0.6 ± 0.0 Tabonuco: 0.7 ± 0.1 Colorado: 2.1 ± 0.3
  • 26. Depth trends in carbon chemistry observed at the individual soil profile level But different patterns were observed in each pit. Oxisol Valley Depth Profile Amide Aromatic O-Alkyl Alkyl
  • 27. Greater amounts of poorer quality C in Colorado forest No differences across soil types! Changes in SOM chemistry with depth are observable at the level of individual profiles Alkyl C (lipids) may be particularly important for long-term tropical C storage
  • 28. 1. Patterns in soil resources Stone, M.M., DeForest, J.L., Plante, A.F. (2014), Soil Biology & Biochemistry (Dissertation Chapter 3) Stone, M.M., Hockaday, W.C., Plante, A.F. In Preparation. (Dissertation Chapter 6) 2. Patterns in soil microbes Stone, M.M., DeForest, J.L., Plante, A.F. (2014), Soil Biology & Biochemistry (Dissertation Chapter 3) Stone M. M., Plante, A.F. (2014) Soil Biology and Biochemistry (Dissertation Chapter 5) Stone, M.M., Plante, A.F. In preparation.
  • 29. 1. Soil microbial biomass and activity will decline with depth, tracking declines in C and nutrients 2. Specific metabolic activities will shift with depth, reflecting shifts in resource allocation 3. Microbial community structure will shift with depth, tracking changing environment High resource surface soils Low resource subsoils
  • 30. In subsoils, microbial In abundance, surface soils, activity microbial and structure abundance, will activity relate to and the physiochemical environment structure will relate to vegetation (soil type)
  • 31. Phospholipid Fatty Acid Analysis Wikimedia Commons
  • 32. Extract and quantify phospholipids for : 1. Viable biomass 2. Broad microbial community structure Fungi Actinobacteria
  • 33. Soil Respiration CO2 evolution measured during 90-day respiration experiment Respiration rate normalized to soil C and microbial C concentrations to determine specific metabolic activity
  • 34. Fluorimetric Enzyme Assays α – glucosidase (starch) β-glucosidase (cellulose dimers) Natural process β-xylosidase (hemicellulose) cellobiohydrolase (cellulose oligomers) Fluorimetric assay N-acetyl glucosaminidase (chitin) acid phosphatase (organic phosphate) Total Potential Activity Specific Activity (Per carbon or biomass)
  • 35. No substantial differences among landscape units (3-way ANOVA): Microbial biomass Cumulative respiration Total Enzyme Activity P value Soil parent material (VC vs. QD) 0.85 0.39 0.27 Forest type (Col vs. Tab) 0.65 0.16 0.13* *2/4 carbon cycle enzymes significantly higher in Colorado forest
  • 36. 20 % P < 0.01
  • 37. 0 0 20 20 50 50 Depth (cm) Resp rate per unit soil Resp rate per unit soil 0 20 50 80 80 80 110 110 110 140 Resp rate per unit soil 0 2 4 6 μg CO2g-1day-1 Resp rate per unit soil C Resp rate per unit soil C Resp rate per unit soil C −1 0 1 μg CO2mg C-1day-1 Resp rate per unit microbial C Resp rate per unit microbial C Resp rate per unit microbial C 0.2 0.4 0.6 -1 day-1 -1 day-1 -1 day-1 μg CO2mg Cmic 140 0 2 4 6 μg CO2g-1day-1 −1 0 1 μg CO2mg C-1day-1 0.2 0.4 0.6 μg CO2mg Cmic 7.8 x P = 0.07 Depth (cm) 140 0 2 4 6 μg CO2g-1day-1 −1 0 1 μg CO2mg C-1day-1 0.2 0.4 0.6 μg CO2mg Cmic
  • 38. 19 x P < 0.01
  • 39. 20 x (Mostly) NSD P < 0.01 NSD High variability in deep soil enzyme activity Increased specific activity with depth driven largely by phosphatase
  • 40. Why high specific metabolic activity in resource limited subsoils? Substrate signaling Catabolic repression Product formation Enzyme production
  • 41. Stress due to resource scarcity? Substrate signaling Catabolic repression Product formation Enzyme production
  • 42. Microbes strongly driven by energy availability
  • 43. Decreased enzyme turnover rates? Substrate signaling Catabolic repression Product formation Enzyme production
  • 44. High enzyme activity following sorption
  • 45. Community shift? Substrate signaling Catabolic repression Product formation Enzyme production
  • 46. Evidence for this! Depth P < 0.001 66 % P = 0.01
  • 47. 1.7 60.0 What’s up with phosphatase? 40% P = 0.01 80% P = 0.01 Increased phosphatase activity relative to C and N cycle enzymes suggests microbes at depth invest more in P acquisition Why?
  • 48. Phosphatase activity driven by microbial carbon demand?
  • 49. Energy availability drives microbial activity—much more than landscape differences Microbial biogeochemical capacity remains similar or increases with depth, per unit biomass High specific metabolic activity could be a stress response, decreased enzyme turnover, or community shifts Prevalence of phosphatase suggests a special role for this enzyme
  • 50. Implications Microbes retain metabolic capacity for biogeochemical processes in low—energy subsoils “Stability” of deep soil carbon—microbial starvation? Starving – survival lifestyle?
  • 51. Future Directions IPCC October, 2014

Notas do Editor

  1. Tropical forests make major contributions to the global carbon cycle. They harbor roughly 25 % of world’s biomass and account for roughly 1/3 of global annual NPP.
  2. Tropical forest soils store nearly 700 Petagrams of carbon, compared with 400 Petagrams of carbon in temperate and boreal forest soils combined Subsoils contain ~50% of soil C stocks
  3. 10 000 000 000 (10 biliion) individual cells per gram!
  4. And after soil and forest type, we have have DEPTH Is it the environment (Depth) Is it the environment (State factors) Is it the soil resources? (C and nutrient availability, C chemistry?) Is it community structure? Other factors
  5. So this was quite an interesting finding for us and we wanted to know why
  6. Remember, based on resource allocation theory microbes have little reason to produce enzymes that target substrates present in abundance. On the other hand… Stress due to decreased substrate availabiliy…. Then I could follow this slide with one showing the strong correlation between microbial activity and energy
  7. Would be nice to include “free” enzyme activity on these graphs, as well : Does it decline
  8. First point– that we do not see differences across soil types or forest types in microbial activity suggests microbes can obtain energy where it exists Second point– while everything declines with depth, subsoil microbial communities still have the CAPACITY to participate in cycles of carbon and nutrients. Thus, active carbon exists in deeper parts of these tropical soil profiles than is typically measured / modeled Third point— we don’t yet know WHY carbon starved microbes are not totally dormant. Are they producing additional enzymes and respiring at higher rates due to stress? Are those enzymes just kicking around for longer? Are community shifts responsible? Fourth point— microbes need to make ecological tradeoffs between energy and nutrient acquisition and energy investment to acquire those nutrients. Ultimately, the biogeochemical cycles these microbes drive may be the result of cost-benefit analyses on the part of the microbes.