Animals interact in complex ways and form interconnected ecosystems. Even small changes to those complex systems could have potentially devastating consequences to the entire environmental system.

Because of this, predicting outcomes of conservation management actions can be challenging – even more so with poor data.

Researchers from the Centre of Excellence for Environmental Decisions have shown how fuzzy cognitive maps (FCM) could be a promising approach for predicting outcomes to management actions when we have little information available but management is urgent.

Fuzzy cognitive maps are a way of modelling social and political systems to help make decisions, across different disciplines.

In the paper, Informing network management using fuzzy cognitive maps, published in Biological Conservation, the research led by Dr Chris Baker showed that FCM can help make reliable predictions in complex and uncertain ecosystems.

FCMThe use of FCM has been growing significantly to inform ecosystem management, but two key issues hamper their application. First, expert knowledge to inform model parameters is frequently translated incorrectly into the FCM and sensitivity analyses are rarely conducted.

Translating knowledge from experts is a constant challenge in ecological modelling. While experts deliver ecological data about the behaviour of a system, modellers require values of model parameters that inform system behaviour.

The paper describes how to correctly incorporate expert knowledge about the interactions of species within ecosystem into FCMs, and describes how to appropriately conduct uncertainty and sensitivity analysis. They show the application of the model with a previously published network for feral cat and black rat control on Christmas Island.

The researchers say FCM are promising for ecological modelling, but require the methodological improvements presented in the paper.

The research is published in Biological Conservation.

Media: CEED Communications, Casey Fung, This email address is being protected from spambots. You need JavaScript enabled to view it., +614 433 638 643.