Patagonia case study: STM Model
By: Graciela Rusch (NINA), Veronica Rusch (INTA), Santiago Varela (INTA), and Anders L. Madsen (HUGIN)
14 September 2016
Introduction
State-and-Transition models (STMs) when applied to managed systems are graphical, heuristic models that make use of ecological knowledge from diverse sources to describe quantitatively ecosystem responses to management. STMs are models of ecosystem condition that integrate use and management as ecological factors driving ecological change. We built an STM of native Nothofagus antarctica (Ñire) forest under silvopastoral use (cattle production and fuel wood extraction) in northern Patagonia, Argentina. There are indications that some levels of use are likely to be unsustainable, i.e., they can drive the silvopastoral system to a condition with low tree cover where critical ecosystem services are lost with time. Logging can exceed the capacity of the system to produce wood and cattle grazing damages tree seedlings and saplings, hindering the recruitment of new trees. Ñire trees are thought to live ca 150 years.
According to the National Law for Conservation of Native Forest, the tree cover and the ecosystem services generated by forest should be maintained in time. We have modelled the capacity to generate five ecosystem services by this system, i.e., fuel-wood production, habitat quality for native fauna, grass production, protection of soil and water and recreation quality. We model how this capacity may change with different levels of use.
By implementing the STM as a Bayesian Belief Network (BBN), we have incorporated levels of uncertainty linked our knowledge about the system.
Interactive Front-end
Below are some HUGIN widgets for interacting with the model.
State Variables (t)
Regeneration density
Mature stem density
Mature BA
Mature stem volume
Mature stem diameter
Cane cover
Herbaceous cover
Shrub cover
Dead wood
Acaena cover
Management Actions and Time
Logging
Grazing pressure
Ñire planting
Time
State Variables (t + time)
Regeneration density_1
0
0-400
400-600
Mature stem density (1)
0
0-50
50-200
200-400
400-600
>600
Mature BA (1)
Impossible
0
1-15
15-25
25-40
40-70
Mature stem volume (1)
Impossible
0-50
50-100
100-200
200-400
>400
Mature stem diameter (1)
0-10
10-20
20-30
30-40
>40
Cane cover (1)
<1
>1
Herbaceous cover (1)
Impossible
<15
15-50
50-75
>75
Shrub cover (1)
Impossible
0-10
10-30
30-60
>60
Dead wood (1)
<1
>1
Acaena cover (1)
Impossible
Low
High
Ecosystem Services
Production fuel wood
0
0.1-1.25
1.25-2.5
2.5-5
5-7.5
Habitat quality for native fauna
No habitat
<3
3-5
5-7
>7
Production grass
Impossible
<1000
1000-2500
>2500
Soil protection & Water quality
Impossible
Very low
Low
Intermediate
High
Recreation quality
Impossible
Low
Intermediate
High
References
Rusch, V. E., A. Goijman, P. Peri, D. Lopez, L. Claps, M. Sarasola, A. Cardozo, and G. M. Rusch. 2015. State-and-Transition models: A tool to analyse decision-making and ES delivery. Fourth International Congress of Ecosystem Services in the Neotropics, Mar del Plata, Argentina.
Rusch, V. E., D. Lopez, L. Cavallero, G. M. Rusch, P. Peri, A. Cardozo, N. Hansen, A. von Muller, L. A. Garibaldi, and M. Sarasola. 2015. An ecological framework to establish management boundaries. The case of ñire forests of northern Patagonia, Argentina. VIII Congreso Internacional de Sistemas Agroforestales, Puerto Iguazu, Misiones, Argentina.
Useful references for those interested in BBN include:
Kjærulff, U. B. and Madsen, A. L. (2013) Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis. Springer, Second Edition.
Contact information
For further details on the paper: Graciela Rusch
For further details on the use of Bayesian networks and web deployment of models contact: Anders L Madsen (alm(at)hugin(dot)com)