About Add-my-pet

Overview of the collection

The collection is complete for large phyla. Chordates are complete at order level, primates at family level.
A variety of related models captures animal life-cycle diversity and quantifies properties in parameters.

Although Dynamic Energy Budget (DEB) theory applies to all organisms, the AmP collection only deals with animals. The reason is that animals eat other organisms, which don't vary that much in chemical composition. Given the habitat, their environment can be characterized by the variables food availability and temperature as a first rough approximation. This characterisation is hard to make "complete" for other organisms, which hampers comparison. Comparison is the most useful asset of this collection.

At 2018/01/01, when the collection had 1000 entries, there were 112 zero-variate data types, and 153 univariate data types, in 588 combinations, written by 125 authors. So, few entries share the same data type combination and the number of data types is very much larger than the number of parameters. This argues for comparison on the basis of parameters, since all parameters were estimated for all species. Moreover, by being mechanistic (= based on first principles), DEB models interprete data, rather than just describe it, so can reveal inconsistencies in data and predict un-measured properties of species as functions of parameters.

Apart from extant species, the collection also has a number of extinct ones, demonstrating that DEB models can still be applied if data availability is poor. Examples are: Deinosuchus, Pterodaustro, Tyrannosaurus, Archaeopteryx and great auk. Needless to say, however: more data generally reduces uncertainty in parameter values.

Data completeness and mean relative errors

Survivor function of data completness.
The relationship between mean relative error and data completeness.
The relationship between symmetric mean squared error (SMSE) and mean relative error.


Add-my-pet is optimized for learning, training and research. Some of the text on this website might be simplified to improve reading and basic understanding. Files, references, and code are constantly reviewed to avoid errors, but we cannot warrant full correctness of all content.

The entries continue to change as the collection grows for several reasons: errors are spotted and corrected; more data is included; assumptions about data quality change; entries are split up by population; our understanding of what are the best priors to use for particular taxa increases; algorithms for estimation are improved; the model changed.

Add-my-pet makes explicit a number of wide spread scientific problems such as: data quality, differences between experiments etc. The resulting parameter estimates depend on a lot of assumptions concerning which data we choose to include and exclude as well as how the data is interpreted (e.g. what we are willing to assume about the initial conditions of the organism.)