Category: qualitative modelling

qualitative modelling

Boolean qualitative modelling on Christmas Island

Conservation managers often want us to predict how species will respond to different management options when we don’t have enough data to parameterise a dynamical model. Previously, we found that a popular Qualitative Modelling technique involving probabilistic analysis has philosophical problems and produces contradictory results. We proposed a new method, based on Boolean analysis, that remedied these problems (Kristensen et al. 2019 Meth Ecol Evol). … Continue reading Boolean qualitative modelling on Christmas Island

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qualitative modelling

Boolean approach to qualitative network modelling

In a new paper in Methods in Ecology and Evolution (draft with supplementary here), we tackled an important question for ecological modellers: how do we predict an ecosystem’s behaviour when the data needed to parameterise a model are lacking? This problem is particularly important when our models are needed for conservation decision-making. For example, managers may be considering different pest-control programmes, which have the potential … Continue reading Boolean approach to qualitative network modelling

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qualitative modelling

Why does it matter to conservation decision-making if alternative Qualitative Modelling methods produce contradictory predictions?

Previously, I have written about how the probabilistic approach to Qualitative Modelling (QM) (e.g. Raymond et al. 2011) can lead to contradictory predictions of species response to a management intervention, and how this is similar to the paradoxes of the Principle of Indifference that we find in the philosophy literature. A reviewer of our new manuscript (Kristensen et al. 2019) asked us an interesting and … Continue reading Why does it matter to conservation decision-making if alternative Qualitative Modelling methods produce contradictory predictions?

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qualitative modelling

Network structural uncertainty in Qualitative Modelling

Background Imagine a situation in which we want to model the behaviour of a food web, but we don’t know what the species interaction strengths are, and we’re not 100 percent sure what the structure of the food web is, either. For example, in the figure below, experts are are uncertain about whether or not there is a direct interaction between species 4 and 5, … Continue reading Network structural uncertainty in Qualitative Modelling

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qualitative modelling, statistics

Some notes on the Principle of Indifference

A classical statement of the Principle of Indifference (PI) is as follows (p. 45 Keynes, 1921): if there is no known reason for predicating of our subject one rather than another of several alternatives, then relatively to such knowledge the assertions of each of these alternatives have an equal probability. Thus equal probabilities must be assigned to each of several arguments, if there is an … Continue reading Some notes on the Principle of Indifference

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dynamical systems, qualitative modelling

Fibonacci numbers and alternating signs in species responses to press perturbation in a food chain

In a paper from 2001, Dambacher and Rossignol made a curious observation: Fibonacci numbers appear in the adjoint and absolute feedback matrices that result from a weighted-predictions matrix type analysis (Dambacher et al. 2003) on food chains. The weighted-predictions matrix analysis is a way of predicting how species in a food web will respond to a the press perturbation of one of the species, so … Continue reading Fibonacci numbers and alternating signs in species responses to press perturbation in a food chain

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qualitative modelling, statistics

The Principle of Indifference is actually two principles in one

In a previous post, I wrote about the philosophical problems caused by the Principle of Indifference. The problems are illustrated with a variety of thought-experiments that create paradoxes, such as Bertrand’s paradox. I also discussed how a problem in ecological modelling for conservation decision-making seems closely related to this philosophical problem. When I realised this connection, it seemed to me that, in order to solve … Continue reading The Principle of Indifference is actually two principles in one

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code, python, qualitative modelling

“ValueError: expected a DNF expression” when trying espresso_exprs example from pyeda docs

I’ve recently been working on a qualitative modelling project where I am trying to uncover “truths” about the response of species in an ecosystem to control of invasive species. Long story short, I’ve been looking into various boolean minimisation techniques. I’ve been playing with Python EDA, a Python library that I think provides a front-end to the Robert Brayton and Richard Rudell espresso heuristic logic … Continue reading “ValueError: expected a DNF expression” when trying espresso_exprs example from pyeda docs

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