There are two approaches to land use planning: hierarchical and participatory. Hierarchical planning takes into account regional or national objectives. Physical constrains are estimated through land evaluation. The project covers large areas. Project guidelines are general. While being efficient this approach frequently faces indifference or even opposition on the side of the local inhabitant with respect to the project guidelines. Participatory planning incorporates the local inhabitant. Objectives and restrictions are defined at a local level. The project comprises narrow areas. Project guidelines are specific. Local co-operation is stimulated. However, the approach is inefficient if the project area is enlarged beyond the local level.
Integrating both approaches, based on functional hierarchy (landscape theory) may make it possible to design large projects at the local as well as at the regional level. The physical environment and local practices may be characterised through land evaluation in conjunction with participatory research. Socio-economic and ecological land use impact may be quantified combining farming analysis and landscape analysis at the individual farm level. Geographical information systems (GIS) allow to extend the project area beyond the local level and to increase methodological flexibility. Model analysis may be adapted to the land use planning participants’ objectives and restrictions. Results may be presented as reports, statistical summaries, graphics or maps. By incorporating the local knowledge and integrating the local inhabitant as planner, this methodology may work as a tool for participatory agriculture development project analysis at the local as well as at the regional level.
The work presented here analyses agricultural socio-economic performance and its interaction with the natural environment based on a case study. Specifically it concerns the A. Guacurarí District located at the north-eastern border of Argentine. Theming system is modelled. The model divides the farms into five classes, distinguished by farm size and major crop, and in eleven types, differentiated by production type, yield, inputs, machines and hired labour. The physical location of the farm is verified and the individual farm is characterised. The model accounts for land use official regulations. Economic indicators are calculated: intensity, productivity and profit. Landscape analysis provides ecological indicators: connectivity, fragmentation and variegation, among others. The underlying data have been collected trough participatory research, between 1997 and 1998, through the analysis and classification of remote sensing material and through literature research.
Spatial analysis shows that only the largest farms, cattle producers, present a homogeneous physical environment. The general picture suggests a clustering which may imply a potential for production co-operation between similar farms. With the distance to urban centres growing for the smallholders, their access to social services becomes more difficult. In terms of agricultural performance, results show that crop yields and profit as well as return to labour increase with total farm size. Labour intensity behaves inversely. 50% of the farms presents intermediate land use intensity. Extensive lines of production, mate-tea and cattle, provide the highest total crop income. Coincident with this result, total farm income is most closely related to agricultural area. Per hectare profit is higher in intermediate classes, with higher incidence of intensive land use activities. Parametric variation of initial values allows defining scenarios. These assume that all available agricultural land is under farm production. In the first scenario, crop area extends proportionally to the initial farming program. Total profit behaves positively with the farm size, since per hectare profit standardises. Labour return differences increase. In the second scenario, specialisation, management improvement and soil protection are assumed. Total profit moves to a higher level. Labour intensity relates to farm class. Hired labour demand increases. These results were validated by interviews with farmers. Scenario results agree with assumptions.
The methodology was applied to evaluate socio-economic and ecological costs and benefits arising from the conservation regional project: “Green Corridor of Misiones”. The results show that connectivity between protected areas does not increase substantially. Spontaneous ecosystem covers 45% of the area. The native forest is insulated and variegated. This ecosystem has narrow interior space, high edge effect and it shows strip corridor arrangement in 55% of the area. The project affects 39% of total farms of the district. 20% farms will achieve an income lower than the official line poverty index value. Amelioration and opportunity costs to achieve the “Green Corridor” project objectives could demand US$64mill. From a socio-economic and conservation point of view, more successful projects at extremely lower costs would concentrate on: designing and conserving local corridors, advising farmers about soil protection techniques and its benefits and promoting individually “alternative activities" as well as nature conservation efforts.
The applied methodology allows farming system classification and analysis up to the farm level. Remote sensing and participatory research information are combined through GIS. Farmland use is accurately characterised at the field level. Agricultural performance and its relationship with the natural environment are quantified. The methodology is flexible. Initial land use analysis and the presentation of results can be modified or extended in accordance with the participants’ requirements, with relatively low difficulty and without reduction in accuracy. The results indicate that the methodology can be applied for land evaluation at the regional level with local accuracy and as a communication tool for participatory project analysis.
Agricultural research should attempt to develop an international database for comparison among agricultural systems, to adapt the methodology to regions without cadastral system, as well as to assign a dynamic character to temporary parameters. Such work would enlarge field knowledge and improve methodology capacity for participatory project analysis of land use in different farming systems at the various planning levels.
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