Biotic Ligand Model Engine
Make a blank inputs list object
Make a blank input problem list object
Make a blank input problem list object
Make a blank WHAM parameter list object
Read a WHAM file and make a WHAM list
Write a BLM input file
Write a BLM Parameter File
Write a WHAM Parameter File
Define the speciation problem
Convert From a Windows BLM Parameter File
Edit Critical Values Table
Run the Biotic Ligand Model
BLMEngineInR: Biotic Ligand Model Engine
Check an object for use in the BLMEngineInR package
CHemical Equilibria in Soils and Solutions
Create a file that shows the problem in a different, human-friendly fo...
Common Parameter Definitions
Add or remove components in the problem
Convert from a WHAM V thermodynamic database file
Get data from the input file
Add or remove input labels in a problem
Add or remove a input variables in a problem
List Critical Accumulation Table
Add or remove mass compartments in a problem
Match Inputs to Problem
Add or remove phase reactions in a problem
Problem Conversion functions
Read a BLM Input File
Add or remove species definitions
Add or remove a species reactions in a problem
Stoichiometry conversion functions
Write a VERY Detailed Output File
A chemical speciation and toxicity prediction model for the toxicity of metals to aquatic organisms. The Biotic Ligand Model (BLM) engine was originally programmed in 'PowerBasic' by Robert Santore and others. The main way the BLM can be used is to predict the toxicity of a metal to an organism with a known sensitivity (i.e., it is known how much of that metal must accumulate on that organism's biotic ligand to cause a physiological effect in a certain percentage of the population, such as a 20% loss in reproduction or a 50% mortality rate). The second way the BLM can be used is to estimate the chemical speciation of the metal and other constituents in water, including estimating the amount of metal accumulated to an organism's biotic ligand during a toxicity test. In the first application of the BLM, the amount of metal associated with a toxicity endpoint, or regulatory limit will be predicted, while in the second application, the amount of metal is known and the portions of that metal that exist in various forms will be determined. This version of the engine has been re-structured to perform the calculations in a different way that will make it more efficient in R, while also making it more flexible and easier to maintain in the future. Because of this, it does not currently match the desktop model exactly, but we hope to improve this comparability in the future.