Simulating soil fertility and poverty dynamics in Uganda: A bio-economic multi-agent systems approach

Schreinemachers, Pepijn; Berger, T.; Aune, Jens B.

doi:10.1016/j.ecolecon.2007.07.018

Cited by 64 publications

(55 citation statements)

References 36 publications

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“…Several other researchers have integrated MP in MAS, namely Berger (2001), Becu et al (2003), Schreinemachers et al (2007) and Valbuena et al (2008). Berger (2001) and Becu et al (2003) have applied MAS to the water management problem.…”

Section: Description Of the Manure Allocation Modelmentioning

confidence: 99%

“…Three, our model focuses only on the manure management problem given the current situation (crop-mix, types of livestock, profitability, etc). Other papers (Becu et al, 2003;Berger, 2001;Schreinemachers et al, 2007) combine the changes in resource use with the possibility of adapting farm activities to economic, ecological or other conditions. Our model is limited in capturing the adaptive capacity of farmers to new changes in 6 policies or economic conditions.…”

Section: Description Of the Manure Allocation Modelmentioning

confidence: 99%

“…The micro-level part of the MAS-system is represented by Mathematical Programming (MP), which simulates the decisions of individual agents while taking legal and other constraints into account. The use of MP at the core of the decision-making procedure captures agent heterogeneity and economic trade-offs while simultaneously focusing on policy-relevant constraints (Berger et al, 2006;Schreinemachers et al, 2007).…”

Section: Description Of the Manure Allocation Modelmentioning

confidence: 99%

“…The successful application to this sample size illustrates that MP-MAS can also be used for large scale applications. Two, we make use of a normative approach whereas Berger (2001) and Schreinemachers et al (2007) calibrated the model to a base situation (positive modelling approach) 1 . As the focus of the model is describing and exploring the current situation, it can be argued that normative modelling can be used (Buysse et al, 2007).…”

Section: Description Of the Manure Allocation Modelmentioning

confidence: 99%

“…Fourth, other researchers have used speciallydeveloped software, but we programmed our model using standard optimisation software (GAMS). Berger (2001) and Schreinemachers et al(2007) make use of MP-MAS framework developed at Hohenheim university and Becu et al (2003) uses the Cormas modelling framework (developed at CIRAD). Fifth, our model is comparative static, while other research depends on dynamic simulations of whole farm decisions.…”

Section: Description Of the Manure Allocation Modelmentioning

confidence: 99%

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Section: Description Of the Manure Allocation Modelmentioning

confidence: 99%

Section: Description Of the Manure Allocation Modelmentioning

confidence: 99%

Section: Description Of the Manure Allocation Modelmentioning

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Section: Description Of the Manure Allocation Modelmentioning

confidence: 99%

Section: Description Of the Manure Allocation Modelmentioning

confidence: 99%

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Scientific concepts for an integrated analysis of desertification

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The Global Drylands Observing System proposed in this issue should reduce the huge uncertainty about the extent of desertification and the rate at which it is changing, and provide valuable information to scientists, planners and policy-makers. However, it needs careful design if information outputs are to be scientifically credible and salient to the needs of people living in dry areas. Its design would benefit from a robust, integrated scientific framework like the Dryland Development Paradigm to guide/inform the development of an integrated global monitoring and assessment programme (both directly and indirectly via the use of modelling). Various types of dryland system models (e.g. environmental, socioeconomic, land-use cover change, and agent-based) could provide insights into how to combine the plethora of monitoring information gathered on key socioeconomic and biophysical indicators to develop integrated assessment models. This paper shows how insights from models can help in selecting and integrating indicators, interpreting synthetic trends, incorporating cross-scalar processes, representing spatio-temporal variation, and evaluating uncertainty. Planners could use this integrated global monitoring and assessment programme to help implement effective policies to address the global problem of desertification.

show abstract

Simulating soil fertility and poverty dynamics in Uganda: A bio-economic multi-agent systems approach

Cited by 64 publications

References 36 publications

A multi-agent simulation model for spatial optimisation of manure allocation

A multi-agent simulation model for spatial optimisation of manure allocation

Regional distribution of nitrogen fertilizer use and N-saving potential for improvement of food production and nitrogen use efficiency in China

Scientific concepts for an integrated analysis of desertification

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