Week 6 - Carbon in terrestrial ecosystems

Landscape soils and surface environments - Week 6 Workshop 1a

R.A. Viscarra Rossel & L. Walden

2026-03-23

Recap – Week 5

Rhizosphere as the plant–soil interface where roots, water, and microbes interact
Nutrient uptake mechanisms and how rhizosphere processes affect availability vs accessibility
Root exudates and rhizosphere microbes enhancing access to limiting nutrients (especially N and P)
Mycorrhizal networks extending root exploration and mediating C and nutrient exchange in plant communities

Learning Goals - Carbon

By the end of this session, you will be able to:

Describe carbon pools, fluxes, and residence time ((C = I - kC))
Explain SOC pools (POC, MAOC, PyC) and stabilisation mechanisms
Compare SCP sands vs Jarrah laterites for C storage potential
Discuss how vegetation and fire influence C storage
Connect soil C to SDGs and sustainable land management

Global carbon pools

Carbon is stored in distinct pools (atmosphere, vegetation, soils, ocean…)
The amount in a pool is its stock
Fluxes move C between pools (e.g. photosynthesis, respiration, fire)

Soils store more carbon than the atmosphere and vegetation combined.

Carbon in Australia and WA

Australian C = 27 (19–39) Gt C (0-30 cm)
Western Australia: 7.1 (5–10) Gt C (0-30 cm)

Vegetation	t C/ha	Total stock
Karri forest	High	Small (small area)
Jarrah forest	Moderate	Moderate
Banksia woodland	Moderate	Low
Grass/shrubland	Low	Large (big area)

Regional carbon in the SCP–Scarp

Two contrasting systems:

Swan Coastal Plain – deep sands, Banksia woodlands, little clay, low Fe/Al oxides. POC-dominated SOC.
Darling Scarp – lateritic profiles, Jarrah forests, more clay and oxides in saprolite. More MAOC in SOC.

Land‑use shifts:
native vegetation → pasture, plantation, urban.

Global (terrestrial) carbon cycle

Zooming into the soil carbon cycle

Carbon inputs: litter, roots, exudates (NPP)
Carbon outputs: microbial respiration, fire, erosion, leaching
Internal transfers: DOC movement, microbial biomass turnover, SOC transformation (POC → MAOC)
Stabilisation mechanisms: chemical (mineral binding), physical (aggregation), biochemical (recalcitrant compounds) (see these later in the workshop)

Pools, fluxes, residence time

How do we model these pools and fluxes?

Pools (stocks): amount at a time point e.g. soil organic C (t C/ha)
Fluxes (flows): movement per time e.g. litter input, decomposition (t C/ha/yr)
Residence time: pool ÷ output flux
e.g. 50 t/ha ÷ 2 t/ha/yr = 25 years

Gross and net carbon fluxes

Pandey et al. (2024)

Net Primary Productivity, NPP = GPP - R\(_a\) (recall week 4)

Gross Primary Productivity, GPP = all CO\(_2\) fixed by plants Autotrophic respiration, R\(_a\) = CO\(_2\) returned by plants

Net ecosystem productivity (NEP): \[\text{NEP} = \text{NPP} - \text{R}_h\]

Heterotrophic respiration, R\(_h\) = CO\(_2\) returned by microbes from SOM decomposition

Positive NEP = ecosystem gaining C; negative = losing C

Ecosystem carbon balance

Inputs: NPP (litter, roots, exudates)
Outputs: \(R_h\), fire, harvest, erosion…

Net ecosystem C change

\[ \Delta C_{\text{ecosystem}} = \text{inputs} - \text{outputs} \]

At steady state

\[ \Delta C_{\text{ecosystem}} \approx 0 \Rightarrow \text{inputs} \approx \text{outputs} \]

Worked example: Jarrah forest C balance

Hypothetical mature Jarrah forest:

NPP ≈ 5.0 t C/ha/yr (wood, litter, roots)
\(R_h\) ≈ 4.8 t C/ha/yr (decomposition)
Fire/other losses ≈ 0.1 t C/ha/yr

Net change:

\(\Delta C = 5.0 - 4.8 - 0.1 = +\ 0.1 \text{ t C/ha/yr}\)

Interpretation: slowly accumulating C, not quite at steady state

One‑pool carbon model

A simple dynamic model:

Input rate: \(I\) is constant
Loss proportional to pool: \(kC\), larger pool → faster loss

“First‑order loss” means

the pool grows when inputs are large, and shrinks faster when the pool itself is large.

Interactive demo: one-pool model

Click here to access the interactive model

or copy into your browser: https://ravr19.github.io/lsse_teaching/onepool_app.html

In the app, explore:

Different \(I\) and \(k\) values
How quickly C approaches steady state
Fast vs slow cycling systems

Test for different scenarios:

Banksia sands vs. Jarrah laterites vs. pasture

High \(k\) = warm, well‑drained Banksia sands
Low \(k\) = protected MAOC in Jarrah laterites

Soil organic carbon: multiple pools

SOC is not one homogeneous pool:

Dissolved organic C (DOC)
Particulate organic C (POC) (light, heavy fractions)
Microbial biomass C (MBC)
Mineral‑associated organic C (MAOC)
Pyrogenic C (charcoal from fire)

Soil C pools: different turnover times

Fast pool:

days–years
fresh inputs, DOC, MBC
rapidly decomposed, fast turnover, short‑term storage

Intermediate pool:

years–decades
POC (light and heavy)
some MAOC depend on protection mechanisms, moderate turnover

Slow pool:

decades–centuries
MAOC, pyrogenic C
very stable, slow turnover, long‑term storage

Key idea: small but very active fast pool; larger but more stable slow pool

How carbon gets stabilised in soil

Three main mechanisms: ❶ Chemical, ❷ physical, ❸ biochemical

WA example: Banksia sands vs Jarrah laterites

Soil carbon underpins soil health

SOC is critical for soil health, it supports physical, chemical, and biological functions:

Structure and aggregation
Water retention and infiltration
Nutrient holding and cycling
Habitat for soil biota

Soil health is defined as the

capacity of soil to function as an ecosystem that sustains life

Soil C and the Sustainable Development Goals

More SOC can support:

SDG 2: No poverty (productive soils)
SDG 2: Zero hunger (food security)
SDG 6: Clean water (filtering, storage)
SDG 12: Responsible production (sustainable land use)
SDG 13: Climate action (C sequestration)
SDG 15: Life on land (habitat, biodiversity)

Vegetation controls on soil carbon inputs: Three key controls

Australian sclerophylly and slow cycling

Nutrient‑poor soils drive plant traits:

Quantity — moderate NPP, long-lived leaves - Slow, steady litter inputs

Quality — high C:N, lignin, tannins - Resistant to decomposition — litter accumulates

Allocation — significant belowground investment - Roots and exudates feed soil C pools directly

Feedback loop: Poor soils → sclerophyll vegetation → slow cycling → poor soils

Fire as a carbon flux: effects on C pools

Rapid C release to atmosphere (combustion)
Pyrogenic C (char): aromatic structure resists microbial breakdown → very slow turnover

Post‑fire regrowth rates
Fire regime matters
(frequency, intensity)

Fire regimes: cultural burning vs hot wildfire

Cultural burning:

Patchy, low‑intensity, frequent
Moderate C loss, more char, fast regrowth

Hot wildfire:

Extensive, intense, infrequent
Large C pulse, less char, slower recovery

Question: Which regime leaves more C in long‑lived soil pools over centuries?

Activity - (handout 10 min) – C budgets

System A: Banksia woodland on SCP deep sand
System B: Jarrah forest on Scarp laterite
System C: Cleared pasture on ex‑Banksia or ex‑Jarrah land
For each:
Rank aboveground C stock
Rank soil C stock (0–30 cm)
Decide if \(\Delta C_{\text{ecosystem}}\) is ≈ 0, > 0, or < 0

Discussion – implications

Which system is most promising for long‑term soil C storage?
Where is C mainly stored: biomass or soil?
How do your answers change under different fire regimes?

Key takeaways

Soils store more C than vegetation + atmosphere combined → major lever for SDGs
Ecosystem C balance: inputs minus outputs; \(\Delta C = I - kC\) shows how pools grow or shrink
SOC has fast, intermediate, slow pools with different turnover and stabilisation mechanisms
SCP sands: weaker protection; Jarrah laterites: stronger MAOC stabilisation
Vegetation quality (including C:N ratio) and fire regime control C inputs and cycling

Next: We add N to see how it controls productivity and couples to C cycling