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Innocent Bakam and Christopher Legg

System Dynamics for Landscape Modelling in Cameroon. Innocent Bakam and Christopher Legg. Outline. Modelling objectives Lessons learnt Difficulties Future developments. Modelling objectives. improve understanding of the delicate balance between humans and their environment

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Innocent Bakam and Christopher Legg

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  1. System Dynamics for Landscape Modelling in Cameroon Innocent Bakam and Christopher Legg

  2. Outline • Modelling objectives • Lessons learnt • Difficulties • Future developments

  3. Modelling objectives • improve understanding of the delicate balance between humans and their environment • assist in formulating policies for future development

  4. DEVELOPMENT OF THE MODEL USING SIMILE PLATFORM MULTIPLE HOUSEHOLDS MULTIPLE PATCHES HOUSEHOLD LAND PATCH INFORMATION TENURE POPULATION LABOUR SYSTEM 1 DECISIONS YIELDS SYSTEM 2 GIS INTERACTION GLOBAL GLOBAL VILLAGE LAND

  5. Where are we now? • Fieldwork and other data collection complete • Simile Models for Awae and Akok operational but not yet calibrated or validated • Simile model for Nkometou almost complete

  6. Main lessons learnt • Extreme complexity of cropping systems in African humid forests, evolved to ensure food security and minimise labour demands • Labour availability is critical to all farming activities and household decisions • Population pressures force gradual abandonment of traditional farming systems at densities greater than about 20 persons per square kilometre • Understanding land use and tenure patterns requires careful planning and development of sampling techniques

  7. A dominant dynamic is the conversion of forest and fallow to cultivation in a twice-yearly cycle of slash-and-burn

  8. Logged and Secondary Forest Wetland Maize Oil Palm Mixed Food System Melon/Plantain System Fallow 6-9 years Land use dynamics in the humid forest zone of Cameroon Cocoa System

  9. Main lessons learnt (2) • Agricultural intensification, with shorter fallows, smaller fields, and increasing emphasis on mono-culture cash-crops can support population densities in excess of 100 persons per square kilometre, but only at the cost of soil degradation or high levels of inputs • Forest bio-diversity is rarely maintained at population densities above 20/km2 • In areas where forest is still abundant, most clearing of forest is for nutritionally unproductive essep (forest melon) fields, not for mixed-food fields

  10. Available land per household decreases from 75 hectares in Awae to 7 hectares in Nkometou Population density increases from 8 persons per square kilometre to 85

  11. Average size of mixed-food fields declines from 0.24 hectares in Akok to 0.10 hectares in Nkometou Average size of cocoa fields declines from 1.32 hectares to 0.66 hectares Asane and essep are no longer cultivated in Nkometou because of land shortage and lack of forest. A range of market-orientated monocultures have become important instead

  12. Nkometou Awae Akok cocoa 26.2 41.2 41.8 mixed food 38.2 41.6 48.7 monocultures 35.6 8.4 2.2 forest melons 0.0 8.8 7.3 Proportion of cultivated land under mixed food crops declines from 49% in Akok to 38% in Nkometou Proportion under monocultures such as maize and tomatoes increases from 2% in Akok to 36% in Nkometou Forest melon/plantain fields decline from 7-9% in Akok and Awae to zero in Nkometou Relative importance of cocoa declines as more fallow is cultivated as monocultures

  13. Difficulties • Lack of data and agronomic expertise in modelling team to calibrate and validate the model • Lack of time to achieve the numerous challenges raised by the modelling activity (lead scientist only part-time in modelling programme for past two years) • Problems with the Simile platform which is still under development

  14. Futuredevelopments (dependent on funding) • Calibration, to ensure that outputs are in reasonable ranges • Validation of all sub models within a multi-disciplinary team (agronomist, pedologist, sociologist, economist, modeler), to ensure that the model is scientifically valid • Development of more friendly user interfaces to ease the adoption of the model by end-users

  15. The Model has become extremely complex

  16. Future developments (2) • Validation in the field with stakeholders (farmers, NGO, policy makers) to ensure that the model reflects the different points of view • Testing of different scenarios and development of appropriate development strategies • Extrapolation of outcomes to Benchmark and eco-zone • Dissemination of model results through publications, role games and seminars

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