On the art of ecological modelling

An article by Ian Boyd from this week’s Science argues that there is a systemic problem of researchers under acknowledging the limits of model prediction:

Many of today’s ecological models have excessively optimistic ambitions to predict ecosystem and population dynamics.

And:

The main models are general population models (16) and data-driven, heuristic, ecosystem models (17,18), which are rarely validated and often overparameterized.

The good news is that:

Some recent studies (35)—including that by Mougi and Kondoh (6) on page 349 of this issue—help to specify where the limits of prediction may lie.

Initially, I thought that these articles (3-6) might be the answer that I’ve been searching for, but it seems that Dai et al. (2012), Allesina and Tsang (2012; see also here) and Mougi and Kondoh (2012) are examples of well derived models for specific questions, not rules for deciding how complex is too complex for a general range of ecological questions. Liu et al. (2011) is a general result, but asks a different question in speaking to the difficulty of controlling real complex systems.

Ian Boyd’s article raises more questions than answers, but it draws attention to an important question, which is highly worthwhile in-of-itself.

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This entry was posted in Just simple enough, Model derivation by Amy Hurford. Bookmark the permalink.

About Amy Hurford

I am a theoretical biologist. I became aware of mathematical biology as an undergraduate when I conducted an internet search to learn about the topic. Now, twelve years later, I want to know, what is it that makes great models great? This blog is the chronology of my thoughts as I explore this topic.

One thought on “On the art of ecological modelling

  1. Yeah, I don’t see why Boyd framed that piece as being about the “limits of prediction” at all. Neither the paper that Boyd’s piece is nominally about, nor any of the others Boyd cites, has anything to do with that issue. I’m guessing the issue must be a hobbyhorse of Boyd’s.

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