The Design Document page provides a description of the algorithms, implementation and planned testing including unit, verification, validation and performance testing.

Design Document

Click here for instructions to fill up the table below ......

The first table in Design Document gives overview of this document, from this info the Design Documents Overview page is automatically created.

In the table below, 4.Equ means Equations and Algorithms, 5.Ver means Verification, 6.Perf - Performance, 7. Val - Validation

Equations: Document the equations that are being solved and describe algorithms
Verification Plans: Define tests that will be run to show that implementation is correct and robust. Involve unit tests to cover range of inputs as well as benchmarks.
Performance expectations: Explain the expected performance impact from this development
Validation Plans: Document what process-based, stand-alone component, and coupled model runs will be performed, and with what metrics will be used to assess validity

Use the symbols below (copy and paste) to indicate if the section is in progress or done or not started.

In the table below, 4.Equ means Equations and Algorithms, 5.Ver means Verification, 6.Perf - Performance, 7. Val - Validation, - completed, - in progress, - not done

Overview table for the owner and an approver of this feature

1.Description	CNP model with root uptake kinetics, leaf level physiology, soil nutrient competition, N-P interactions through N2 fixation and phosphatase activity
2.Owner	Qing Zhu,William Riley (Unlicensed)
3.Created	28 Aug 2015
4.Equ
5.Ver
6.Perf
7.Val
8.Approver	William Riley (Unlicensed), Peter Thornton
9.Approved Date	24 Sep 2015
V1.0	Accepted

Click here for Table of Contents ...

Table of Contents

Title: Nutrient COMpetition (N-COM): a mechanistic treatment of plant-soil nutrient interactions

Requirements and Design

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 (2016), Representing leaf and root physiology in CLM results in improved global carbon and nitrogen cycling predictions, DOI: 10.1002/2015MS000538, 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 (2015), 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 (2016), Multiple soil nutrient competition between plants, microbes, and mineral surfaces: Model development, parameterization, and example applications in several tropical forests, Biogeosciences, 13, 341-363.
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: 31 Aug 2015

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) Predict the nutrient uptake profile based on ECA kinetics

(4) Link photosynthesis capacity with leaf nitrogen and phosphorus levels to facilitate ECA kinetics implementation

(5) Impelement dynamic allocation scheme considering nutrient, water, and light resource supplies

(6) Modify N2 fixation, mechanistically implement N2 fixation and its interaction with nitrogen and phosphorus availability to allow ECA kinetics framework to uniformly treat competition

(7) Mechanistically implement phosphatase activity and its interaction with nitrogen and phosphorus availability in the ECA kinetics framework

Algorithmic Formulations

Design solution: New modules are added to facilitate ECA kinetics and multi-nutrient competition

Date last modified: 31 Aug 2015

Contributors: Qing Zhu, William Riley (Unlicensed)

Two competition algorithms are implemented (Zhu et al. 2015, 2016):

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
Plant-microbe competition is scaled by 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 N (Ghimire et al. 2016) 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 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: 31 Aug 2015
Contributors: Qing Zhu, William Riley (Unlicensed)

Initial prototype of the N-COM model has been developed, tested, and published (Zhu et al. 2015, 2016).
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

Date last modified: 31 Aug 2015

Contributors: Qing Zhu, William Riley (Unlicensed)

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, regional, and site-level datasets

Date last modified: 31 Aug 2015

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 integration have been (N components; Ghimire et al. 2016), 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

Date last modified: 31 Aug 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
Computational performance will be evaluated for offline and coupled global simulations using the ACME timing tools.

Browser not supported