Optimality Principles in Earth System Models: More

Complexity Without MoreParameters

Silvia CaldararuTea Thum, Melanie Kern, Lin Yu, Marleen Pallandt, Jan Engel, Sönke

Zaehle

Integrated C, N, and P cycles Improving process

representation

Plant – soil interaction New soil model including phosphorus dynamics

QUINCY: Quantifying the effects of interacting nutrient cycles on terrestrial biosphere dynamics and their climate feedbacks

Plant optimality

Experiments say plants are plastic

Decrease of leaf N concentration during the course of the Oak Ridge FACE experiment

Decrease of leaf to root ratio during the course of the Oak Ridge FACE experiment

Models fail to represent observed plasticity

ObservationsModel ensemble mean

Zaehle 2014, New Phytologist

Optimality: what is it and how can it help?

The plant evolutionary strategy that results in maximising survival and offspring fitness.

Can use processes that already exist

in the model

In the case of trees it reduces to maximising

growth

No pre-defined thresholds

Best use of resources

Optimality in practice

Leaf level:photosynthetic nitrogen fractions

Canopy level:leaf nitrogen content

Plant level:biomass allocation

1

2

3

Study sites: 2 FACE experiments

Duke FACELoblolly pine evergreen plantationMaintained growth response until the end of the experiment

ORNL FACESweetgum deciduous plantationDecreased growth response towards the end of the experiment

Optimal photosynthetic nitrogen fractions

Amount of N allocated to each photosynthetic fraction changes dynamically to increase GPP

1

Vcmax25Jmax25

Structural N Photosynthetic N

Rubisco

Electron transport

Chlorophyll

Observations❶ Optimal N fractions

Optimal fractions under elevated CO21Structural N Photosynthetic N

Rubisco

Electron transport

Chlorophyll

V cmax

25/ N

area

Year

DUKE

Data from D. Ellsworth and K. Crous

Optimal fractions seasonality1Structural N Photosynthetic N

Rubisco

Electron transport

Chlorophyll

Optimal leaf nitrogen content

• Higher leaf N –increased GPP

• Lower leaf N –decreased respiration

2Change in canopy C:N ratio if

CNC

N

Optimal leaf nitrogen content

CN

C N

Labile pool – biomass available for growth Only increase canopy

N if there is sufficient N available for plant growth

2

Optimal leaf nitrogen under elevated CO22Observations❷ Optimal leaf N

Leaf nitrogen response relative to the start of the experiment

ORNL

DUKE

Optimal biomass allocation:nutrient response

C available for growth = N available for growth given specific tissue CN ratios

Labile pool – biomass available for growth

C

NC N

fleaf

froot

fwood

3

Optimal biomass allocation:plant hydraulics response

• Hydraulics condition: maintain water column

• Optimal condition: build new tissue (roots or sapwood) with maximum benefit over its lifespan

Magnani et al, 2000, Plant, cell and environment

Ψleaf

Ψsoil

3

Optimal allocation under elevated CO23

Observations❸ Optimal allocation

C

NC N

fleaf

froot

fwood

Leaf to root ratio response relative to the start of the experiment

ORNL

DUKE

Optimality: caveats

Mathematical optimality does

not mean it’s real

Don’t forget about structural constraints

Not every process is optimal

Optimality works at different timescales

Assumption: individual optimality scaled to the

ecosystem

There can always be missing processes

Data from manipulative experiments

Existing models

Optimality theory

Comparison with data

Hypothesis

New modelEvaluation

Summary

• Next generation land surface model: process-focused, explicitnutrient cycles, modular

• Optimality concepts are a way to include observed plant plastic responses in models

• Use of data from manipulative experiments to improve process understanding and representation

More info at:tinyurl.com/erc-quincy