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ACME Land Group

Date: 8/28/2015
 

Summary


     The ECA kinetics (Tang and Riley 2013; 2015) is being integrated into the ACME Land Model v1 (ALMv1) to represent multiple nutrient (i.e., nitrogen and phosphorus in v1) interactions and competition between multiple consumers (microbes, abiotic surfaces, and plants). This work has followed the original proposed tasks, primarily under M3.10 and M3.14. The code is being integrated in such a way as to allow for straightforward testing of different competition hypotheses.
References for this document:
  • Ghimire, B., W. J. Riley, and C. D. Koven (2015), Representating leaf and root physiology in CLM results in improved global carbon and nitrogen cycling predictions, in review JAMES.
  • Tang, J. Y., and W. J. Riley (2015), Weaker soil carbon-climate feedbacks resulting from microbial and abiotic interactions, Nature Climate Change, 5,WOS:00034651390001956-60.
  • Zhu, Q., and W. J. Riley (2015a), Improved modeling of soil nitrogen losses, Nature Climate Change, 5, doi:10.1038/nclimate2696, 705-706.
  • Zhu, Q., W. J. Riley, J. Y. Tang, and C. D. Koven (2015b), Multiple soil nutrient competition between plants, microbes, and mineral surfaces: Model development, parameterization, and example applications in several tropical forests, Biogeosciences Discussion, 12, doi:10.5194/bgd-12-4057-2015, 4057-4106.
  • Tang, J. Y., and W. J. Riley (2013), A total quasi-steady-state formulation of substrate uptake kinetics in complex networks and an example application to microbial litter decomposition, Biogeosciences, 10,WOS:000329054600033, Doi 10.5194/Bg-10-8329-2013, 8329-8351.

 

Requirements

Requirement: Implement ECA kinetics to represent coupled N and P controls on carbon cycle processes

Date last modified:  

Contributors: Qing Zhu, William Riley (Unlicensed)

Implementing ECA kinetics to represent coupled N and P controls on carbon cycle processes requires the following code developments:
(1) Add nutrient competition through ECA kinetics: root, decomposing microbes, nitrate compete for NH4; root, decomposing microbes, denitrifier compete for NO3; root, decomposing microbes compete for POx
(2) Add root nutrient uptake kinetics to facilitate ECA kinetics implementation
(3)
Modify
Predict the nutrient uptake profile based on ECA kinetics
(4)
 Link leaf phosphorus level with photosynthesis capacity
 Link photosynthesis capacity with leaf nitrogen and phosphorus levels to facilitate ECA kinetics implementation
(5) Modify N2 fixation, mechanistically implement N2 fixation and its interaction with nitrogen
/
and phosphorus availability to allow ECA kinetics framework to uniformly treat competition
(6)
Phosphatase activities, mechanistically
Mechanistically implement phosphatase activity and its interaction with nitrogen
/phosphorus availability

 

Requirements

Requirement: name-of-requirement-here

Date last modified:  
Contributors:  (add your name to this list if it does not appear)

Each requirement is to be listed under a ”section” heading, as there will be a one-to-one correspondence between requirements, design, proposed imple- mentation and testing. Requirements should not discuss technical software issues, but rather focus on model capability. To the extent possible, require- ments should be relatively independent of each other, thus allowing a clean design solution, implementation and testing plan. 
and phosphorus availability in the ECA kinetics framework

Algorithmic Formulations

Design solution: New modules are added

for new developments

to facilitate ECA kinetics and multi-nutrient competition

Date last modified:

8/28/2015

 

Contributors: Qing Zhu, William Riley (Unlicensed)

Two competition algorithms are implemented (Zhu et al. 2015a, b):

  1. Soil microbes outcompete plants
    UPmic = min(Nav, UPmic)
    UPplant = min(max(Nav - UPmic,0), UPplant)
    UPmic and UPplant are microbial decomposer and plant nutrient uptake rate. Nav is soil available nutrient pool size
  2. Plant-microbe competition is scaled by
their
  1. functional traits (e.g., biomass density) through ECA formulation
    UPmic = VMAXmic * [Emic]*[Nav]/(KMmic + [Nav] + [Emic] + [Eplant]*KMmic/KMplant)
    UPplant = VMAXplant * [Eplant]*[Nav]/(KMplant + [Nav] + [Eplant] + [Emic]*KMplant/KMmic)
    VMAX and KM are kinetics parameters, Emic and Eplant are nutrient carrier enzyme abundance for decomposing microbes and plants

The ECA kinetics integration requires:

  • Leaf level physiology: how does N/P limitation on GPP occurN (Ghimire et al. in review) and P leaf levels affect GPP
  • VCMAX = f(leafN, leafP); JMAX = f(leafN, leafP)
    • VCMAX and JMAX are maximum carboxylation and electron transport rate for photosynthesis. 
    • Their relationships with leaf level N/P concentration are derived form the TRY database.

  • N2 fixation = f(carbon cost of root nitrogen uptake, carbon cost of N2 fixation, plant phosphorus status)
  • N2 fixation occur occurs only when roots are not able to acquire enough nitrogen. N2 fixation rate could be limited by plant phosphorus shortage.

  • Phosphatase activity = f(nitrogen cost, plant nitrogen status, plant phosphorus status)
  • Phosphatase activity is nitrogen expensive. It occur only when the benefit is larger than the cost. 
     

Design and Implementation

Implementation: Offline test with MATLAB codes plus online test within ACME Land Model (ALM)

Date last modified:

8/28/2015

 
Contributors: Qing Zhu, William Riley (Unlicensed)

 

  • Initial prototype of the N-COM model has been developed and tested in MATLAB, tested, and published (Zhu et al. 2015a,b).
  • The N-COM model is being integrated in ACME

 

  • following the Algorithmic Formulations described above.

Planned Verification and Unit Testing 

Verification and Unit Testing: Benchmarking

/28/2015

Date last modified:

8

  

Contributors: Qing Zhu, William Riley (Unlicensed)

 

ACME with N-COM codes will be evaluated using ILAMB benchmarking package.

Once integrated with Master, we will perform the offline simulations described below (Planned Validation Testing) as a first cut at Verification. Unit testing of model subcomponents will be designed and implemented over the 6 months following code freeze (Nov. 1, 2015)

 

Planned Validation Testing 

Validation Testing: Model validate with global

dataset

, regional, and site-level datasets

/28/2015

Date last modified:

8

  

Contributors: Qing Zhu, William Riley (Unlicensed)

 

The ECA representation of nutrient competition is being, and will continue to be, tested against site-level, regional syntheses, and global remote-sensed and meta-analyses products:

  • ACME with N-COM
codes,
  • integration have been (N components; Ghimire et al. in review), and will be, evaluated and validated using the International Land Model Benchmarking (ILAMB) package.
  • ACME with N-COM integration will be validated against global scale nitrogen
/
  • and phosphorus fertilization experiments, across multiple ecosystems
. 
  • . We plan to integrate this meta-analysis into the ILAMB package.

Planned Performance Testing 

Performance Testing: short-description-of-testing-here

Date last modified:

8/28/2015

  
Contributors: Qing Zhu, William Riley (Unlicensed)

 

The ACME Land Model N-COM code will be tested with historical 1850 simulations timing, and compared to baseline ALMv0 performance timing. . Preliminary results indicate no decrease in computational performance with integration of N-COM, but substantial increase in model simulation quality compared to observations.