Model:CarboLOT

CarboLOT

Also known as
Model type	Modular
Model part of larger framework
Note on status model
Date note status model

Incorporated models or components:

Spatial dimensions	3D
Spatial extent	Global, Patch-Scale
Model domain	Marine, Carbonates and Biogenics
One-line model description	Population-ecology based model of shallow-ocean benthic carbonate accumulation
Extended model description	The carbonate production is modelled according to organism growth and survival rates moderated by habitat suitability (chiefly light, temperature, nutrient). The environmental inputs are extracted from global databases. At the seabed the model's vertical zonation allows for underground (diagenetic) processes, bed granular transport, lower stable framework, upper collapsable framework. This voxelation allows for the carbonate to be placed (accumulated) correctly within the bedding and clast fabrics. The stratigraphy and seabed elevation are built in this way. As conditions change (e.g., by shallowing) the biological communities respond in the simulation, and so too do the production rates and clast/binding arrangements. Events punctuate the record, and the organism assemblages adjust according to frequencies and severities. The population stocks are calculated by diffuse competition in a Lotke-Volterra scheme, or via cellular simulations of close-in interactions to represent competition by growth, recruitment.

Keywords:	carbonate sediments, population ecology, numerical model, benthic colonial organisms,

Name	Chris Jenkins
Type of contact	Project manager
Institute / Organization	INSTAAR Univ Colorado at Boulder
Postal address 1	1560 30th St
Postal address 2	UCB 450
Town / City	Boulder
Postal code	80309-0450
State	Colorado
Country	United States
Email address	chris.jenkins@colorado.edu
Phone	+1 720 840 3303
Fax	+1 303-492-6388

Supported platforms	Windows
Other platform
Programming language	Python
Other program language
Code optimized	Single Processor
Multiple processors implemented
Nr of distributed processors
Nr of shared processors
Start year development	2010
Does model development still take place?	Yes
If above answer is no, provide end year model development
Code development status
When did you indicate the 'code development status'?
Model availability
Source code availability (Or provide future intension)
Source web address
Source csdms web address
Program license type	Other
Program license type other	--
Memory requirements	Usual PC
Typical run time	2 hours for 1000 year run

Describe input parameters	Model setup: grid extent and resolution, time stepping and duration. Environmental inputs (from global datasets, automated methods): bathymetry, seawater bottom temperatures, benthic irradiance, seafloor hardness, ocean wave climate Organism characteristics (automated from Knowledge Base): dimensions, construction, reproduction and survivorship
Input format	ASCII, Binary
Other input format
Describe output parameters	Benthic carbonate accumulation; sediment character and thickness; organism stocks and remains; environmental history; 2D-3D map graphics; graphs of stocks and vacant seafloor through time.
Output format	ASCII
Other output format
Pre-processing software needed?	No
Describe pre-processing software
Post-processing software needed?	No
Describe post-processing software
Visualization software needed?	No
If above answer is yes
Other visualization software

Describe processes represented by the model	Population ecology represented by diffuse competition Lotke-Volterra calculus, cellular automaton, cellular stochastic models. Sediment transport arbitrated by slopes and wave energy pickup Bioerosion scaled to the seafloor presence of skeletal material
Describe key physical parameters and equations	Bathymetry, seawater temperatures, ocean wave climate, benthic irradiance, seafloor hardness
Describe length scale and resolution constraints	Cells are approximately 1-1000m in scale; map areas 10-100km on side.
Describe time scale and resolution constraints	Timestepping is usually annual, extending over 1000 years. However the model is capable of doing finer and longer runs.
Describe any numerical limitations and issues	Usual Python limitations on floating point precision. ODE's are solved on scales much finer than annual, and their performance is monitored.

Describe available calibration data sets	The model produces virtual core-logs which can be compared with Ocean Drilling Program and other descriptive core logs and with outcrops.
Upload calibration data sets if available:
Describe available test data sets
Upload test data sets if available:
Describe ideal data for testing

Do you have current or future plans for collaborating with other researchers?	Yes

Is there a manual available?	Yes
Upload manual if available:
Model website if any
Model forum / discussion board

Comments	Email to Chris.jenkins@colorado.edu for further details, manual, code, collaboration

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