Summary:
Focus: global-scale assessment of soils
Soils
Store 2500 GTons of C in top 2m
CO2 emissions 60GTons/year
Trees absorb 750 GTons/year
Small changes to soil/plant dynamics have huge impact on global climate
Geochemistry
Microorganisms
Soil carbon dynamics:
Deposited by plants from above
Captured on minerals or bodies of microbes, or emitted
However, dynamics of soils are highly uncertain due to complex dynamics and limited data availability
Research landscape:
Microbial controls on decomposition
Geochemical controls
Representation of soils in Earth System Models
Goal: inform policy and management
Combines: lab&field experiments, data analysis and modeling
Scales from microns to the globe
Global soil dynamics
110GTons lost due to anthropogenic land use
Significant interest in storing it back
Major improvements to agricultural productivity and stability due to increasing soil carbon
Are the limits on carbon storage effectiveness, how does this inform policy?
Intervention dynamics:
Increase biomass inputs into soils
Decrease vectors of C leakage from soils
Promote storage in soils
Protect soils from leakage drivers (e.g. wind erosion)
Key carbon pools:
POC: Particulate organic (larger sized carbon fragments) (~25% of global soil carbon)
MAOC: Mineral associated organic carbon (smaller particles attached to minerals) (~45% of global soil carbon)
Hard for microbes to digest
Good for long-term carbon storage
Finite mineral surface area means that this pool can saturate
MAOC capacity
As C inputs rise,
MAOC should saturate but stay stable
MOCmax: maximum C capacity of MAOC in a given soil’s texture and mineralogy
Sandy soils (bigger mineral particles): less surface area, so lower MOCmax
Clay soils (smaller mineral particles): more surface area, so higher MOCmax
Can intervene to add biochar or clay content to increase MOCmax
Rate of C input depends on above ground ecology and climate
POC should rise indefinitely but more vulnerable to release
Interventions can affect these dynamics
Tillage causes C release, avoiding it can increase carbon storage
Addition of biochar can increase MOCmax
MOCmax is hard to estimate
Maximum observed C capacity in the field is a lower bound on the true value
Collect data on SOC vs MAOC to see where it plateaus
Challenge: the relationship is controlled by many other factors
Real data shows a significant variability in MAOC for the same soil clay/silt content and SOC
Part of of the noise is soils where MAOC has not been reached
The maximum of these measurements for a given soil clay/silt content should be MOCmax
Estimating the max metric requires a lot of data
1100 global observations of MAOC vs SOC
Need to estimate reasons for why MAOC is not saturated and how its varies due to management and depth
Saturation is higher in un-managed land (grasslands/forests)
Also higher in forests (~50%) than grasslands (45%), which are higher than cropland (~25%)
Lower saturation in deeper
Geospatial analysis of MAOC shows significant regional patterns to
MAOC vs POC
MOCmax
MAOC and POC in process-based models
MOCmax is a major parameter in most soil models
In the past this parameter was constrained by lab experiments, which significantly underestimate it because they are done in
sterile soils (no fungi and bacteria) and
homogeneous mineral types
Mis-estimated MOCmax points to incorrect carbon storage priorities (need to prioritize soils further away from saturation)
Analysis of 103 soil profiles shows that more carbon was accrued in soils that were further away from saturation
In addition to physical constraints, there are also economic and political considerations
How will soils respond to warming?
Network of warming experiments across the world (limited due to cost)
Climate gradient analysis: similar soils at different temperatures (space for time substitution may have limitations for making inferences about dynamics)
~9k WoSIS profiles
Estimate proportional decline in soil C for every 10deg C of temp increase
Low clay: high temp sensitivity
High clay: low temp sensitivity
POC has a much higher temp sensitivity than MAOC
Soil models must capture this sensitivity
Models are pretty good at estimating total soil C
Estimates of different pools are much more variable
Models have too much carbon in fast-cycling pools and too little in slow cycling pools, which causes Earth System models to cycle carbon too fast
Unclear how much of the uncertainty comes from poor estimates of how much C comes into soils from aboveground