Hoanh, C.T.

Keulen, H., van

Rötter, R.P.

Wageningen Yield 

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Scientific challenges
H. Van Keulen1, R.P. Roetter2 and C.T. Hoanh2
1 Plant Production Systems Group, Wageningen University, P.O. Box 430, 6700
AK Wageningen, The Netherlands
E-mail: herman.vankeulen@pp.dpw.wag-ur.nl
2 International Rice Research Institute (IRRI), P.O. Box 3127, Makati Central
Post Office (MCPO), 1271 Makati City, Philippines
Introduction
This final report of the SysNet project presents proof of considerable progress in
the field of land use systems analysis, as a component of participatory land use
planning. It would be an illusion to think that this presents the ultimate word on
this issue, first of all because the issues and their relative importance
continuously change as a result of autonomous developments. Secondly,
technologies are continuously developing, leading to both increased possibilities
for the use of data and improved methodologies for analysis and integration.
Moreover, while scientists engaged in international agricultural research hope to
find novel solutions with an impact on rural development, they frequently
realize that the answer to one question leads to the formulation of at least two
new questions.
In this contribution, major challenges are identified for research in the field of
partcipatory land use analysis and land use planning, based on the SysNet-
experience.
Description of production activities (technologies)
Analysis of the possibilities for regional development as a tool for identification
of scope for improvement and attainment of various objectives strongly hinges
on accurate quantitative description of agricultural production technologies.
Current technologies, as practised in a region, generally do not represent the
potential situation, i.e., the production possibilities as dictated by factors that
cannot be or can hardly be affected by land users, such as radiation and
temperature. It often appears difficult to quantify the technical coefficients of
these technologies, as in traditional farm surveys such information is not
routinely collected. It would be necessary to include in farm survey handbooks
guidelines for collecting the technical information required for accurate
quantitative description of current production technologies.
For alternative production techniques that are not currently practised in a
region, technical coefficients can, in principle, be generated by applying (crop
growth) simulation models. Such models have been developed for various
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(major) crops, but, for many of the minor crops, for which subsistence and
market-oriented systems in developing countries can be of critical importance,
such tools are not available. This also holds true for most of the perennial crops
that often represent an important component in agricultural production systems in
tropical countries. It appears that, in agricultural research, development of such
tools does not have a high priority (anymore). In many low-external-input
farming systems, mixed cropping, i.e., the simultaneous growth of a mixture of
crop species and/or varieties, is a common technology, to reduce risks, to profit
from the spatial heterogeneity of the resource base or to make use of synergistic
effects. Also, for these types of crop systems, adequate simulation models are not
available. This lack of quantitative tools for generating accurate technical
coefficients of alternative production technologies seriously hampers their
inclusion in land use analysis.
Spatial analysis
The LUPAS methodology operates at the regional level and resource availability
and quality are defined at that level, i.e., the total area of land of a certain quality,
the total quantity of irrigation water, the total labour force, etc. However, the
spatial distribution of these resources is of major importance for the way in
which they are being, and can be used. This holds true for both the physical
characteristics (i.e., the spatial distribution of the water resources determines to
what extent they can be used for various purposes) and the socioeconomic
characteristics (such as the distance to markets, in absolute terms, or in terms of
transport possibilities, which determine whether production of a certain
commodity is economically attractive). The larger the distance, the higher the
transportation costs, and hence the more difficult the marketing of a commodity.
For some commodities, however, such as fresh milk or vegetables, distance may
be a prohibitive constraint.
First attempts to introduce the spatial dimension in models for land use
analysis have been made, but these have been shown to present serious
difficulties, so that no established methodology is available. Especially for
effective targeting of policy measures, this lack of spatial differentiation is a
serious drawback.
Integration of regional analysis and farm household analysis
The ultimate decision makers on land use are farm households, and the
possibilities to affect land use therefore depend on the criteria used by the farm
households in these decisions and their response to policy measures. The regional
land use analysis can illustrate the (bio)physical potentials of the natural
resources, but cannot identify the major socioeconomic constraints to modifying
land use at the farm household level. For that purpose, the regional analysis has
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to be integrated with the farm household analysis that incorporates farmers'
behaviour. Again, developments in this direction have started, but a much more
systematic analysis is necessary, that yields a methodology in which results of
regional models can be used to identify boundary conditions and/or objectives for
farm household models (FHMs). Results from FHMs, such as production and/or
price elasticities, in turn, should provide the revised scenario settings for
subsequent regional analysis, and so on.
Such integration is also hampered by the typical methodology applied in
socioeconomic analysis, which is based on the identification of so-called farm
types, distinguished by economic characteristics. Regional analysis on the basis
of upscaling of farm household results typically suffers from aggregation bias,
because non-linear relations play a major role in the process. Such biases could
be minimized when similar to the biophysical data, which have a long tradition in
being geo-referenced, socioeconomic information would also be presented,
incorporating its spatial dimension.
Uncertainty analysis
The scope for agricultural development is determined not only by the long-term
possibilities and constraints but also by the risks associated with uncertainty.
This plays a role in both the biophysical sense (weather cannot be predicted and
the more erratic the weather pattern in a region, the larger the uncertainty) and
the economic sense (in most situations, producers are price-takers that have no
influence on the market price of their commodities). In addition, in subsistence
farming systems, which have only weak links with the market economy, food
security is a major consideration, and that will lead to risk-aversive behaviour,
effectively constraining the possibilities for increased production at higher risks.
In explorative land use analysis, the possibility of taking into account this
uncertainty should therefore be incorporated.
Interaction with stakeholders
In the development of tools for land use analysis, the biggest challenge is
probably their implementation in the practice of land use planning and policy
analysis. That requires close cooperation with the various stakeholders, in which
it is important that the models be designed in such a way that answers are
generated to questions relevant to the stakeholders. Moreover, the stakeholders
need to develop confidence in the tools being applied. It appears not evident now
what the best package of procedures is to stimulate, maintain and
institutionalize that process.


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