Method Factsheet - State and Transition Models

State-and-transition models (STMs) are conceptual models of ecosystem dynamics after disturbances based on alternate state theory (Kachergis et al. 2011). STMs combine the representation of alternate states and the factors that drive the transitions among states with tables of qualitative descriptions of the states. They are diagrammatic, low cost, flexible and suit participatory modelling (Nicholson & Flores 2011) which brings together diverse knowledge holders and builds shared understanding about complex systems. When implemented as Bayesian Belief Networks, they can be a powerful tool to communicate uncertainty about state categorisation and the factors that trigger transitions between states.

Implementation

Ecosystem management

Topics

Sustainability
Thresholds

Constraints

They are specific to an ecological site, so extrapolation to other conditions is limited, but knowledge on similar or comparable sites may be used to complete missing information (Bestelmeyer et al. 2010)
The identification of thresholds and alternative states is sometimes management driven, with limited correspondence with ecological processes and real ecological thresholds. The thresholds may then be misleading. However, the models must not be understood as static, but rather as representing the best ecological knowledge about a system at a particular time, which should be tested and updated as more knowledge is generated
Ecological thresholds can be triggered by interacting drivers at various spatial scales (Peters et al. 2004). These may be difficult to capture without appropriate data and analysis, and/or with other knowledge based on long-term experience (Knapp et al. 2011). Also in this case, STMs must be seen as a representation of the existing knowledge about the system that needs to be open to updates as new knowledge is available

Product requirements

STMs are built using different kinds of knowledge sources (both quantitative and qualitative), i.e. historical maps and remote sensing data, time series/monitoring data, field measurements and ground-truthing, experiments, expert and practitioner's knowledge (Bestelmeyer et al. 2010).
There is no need for any specific software to build an STM. But, if implemented as a Bayesian Belief Network (BBN), the model will require the corresponding software (see BBN).

Advantages

Easy to use: The graphical approach, the independence from any pre-defined functional relationships and the possibility of including different sources of knowledge makes STMs a very flexible and easy to use approach
STMs are increasingly being applied as an approach to guide the management of ecosystems and their ES, including to assess the risk of degradation of ecosystem condition
to take proactive measures to avoid degradation

Links

OpenNESS homepage

Project lead contact details

Dr Paula Harrison,
Land Use Group,
Centre for Ecology and Hydrology,
Lancaster Environment Centre,
Library Avenue,
Bailrigg,
Lancs,
LA1 4AP
+44 (0) 1524 595858
paulaharrison@ceh.ac.uk

methodfactsheetstm.pdf

Method Factsheet - State and Transition Models

Associated Oppla members

Paula Harrison