Options that Leisa Farmers have

We do no longer have to argue in favour of an increase of necessary inputs. It has been generally accepted that without such improvements of i. soil fertility and other soil conditions that are basic to sustainable farming systems, ii. soil moisture conditions, iii. varieties, crop combinations and rotations and iv. land husbandry as a whole, there is no future for successful LEISA farming (e.g. Reijntjes et al., 1992; Shaxson et al., 1997; Olufayo et al., 1998). However, such improvements must be seen within their socio-economic context. The options that farmers have, to cope with (increasing) climate variability, apply to their actual conditions, which vary greatly geographically and agronomically.

Of the basic atmospheric conditions that limit agricultural outputs, radiation, CO2 and wind (flow of momentum) are changing. They will in the existing scenarios continue to change measurably over time, but their variability will not, peak winds during calamities excepted. To cope with this general variability, the LEISA farmer will generally not have to take precautions different from those that have been or could have been taken in the recent past and at present. The options defined by Stigter (e.g. 1988,1994), for microclimate improvement by management and manipulation of radiation and impacts of (consequences of) wind, including gas exchanges other than water vapour, also remain virtually the same. This is not true for such options coping with moisture and vapour flows, temperature and heat flows, mechanical impacts of rain and/or hail and technologies to fit cropping periods to the seasons. It is, therefore, also not true for the phenomena due to (mitigations of) drought, flood, water erosion and other related matters, such as those regarding desertification, forest and bush fires, pests and diseases. This differentiation is largely due to the role of these phenomena as limiting factors in agricultural and forest production and the expectations on their future variability. There may always be local exceptions to the above distinctions, such as in a particular variation in wind direction reported to be used in traditional forecasting of the strength of the monsoon (Anonymous, 2001).

The time scale for (new) options for farmers to cope with (increasing) climate variability may vary from several seasons to the ongoing (part of a) season. An example of the first end of the scale was given by Bakheit et al. (2001) and Stigter

(2002a, b), using work of Abdalla et al. (2002a). The Sudanese government was advised on a forecasted climate change scenario in which longer sequences of dry years would be intermitted with longer periods of wet growing seasons. The government proposed research on improved underground storage of sorghum, for longer storage periods. On a large scale, as practised in strategic grain reserves by the government (up to 300 tonnes), as well as on the small scale of mainly subsistence and other small farmers (2-10 tonnes). It was found from a questionnaire that the latter farmers experimented with pit linings to insulate the grain from the soil (Abdalla et al., 2001) and with shallower pits (Abdalla et al, 2002b). These innovations with respect to traditional methods were quantified and optimised. Wide surface caps were added from research experience. This way improved traditional underground grain storage microclimate assisted to cope with consequences of forecasted changes in the distribution of bad and good rainy seasons.

The shorter time context is exemplified by Anonymous (2001) in the proposal to use traditional knowledge in determination of the start of the growing season in India. The flowering peak of blooming of the Cassia fistula tree appears to do an admirable job in Gujarat of predicting whether the monsoon will come early or late. As these examples are dealing with traditional farming systems or more recently derived innovative indigenous knowledge, they fit this paper. However, for example, Ati et al. (2002) proposed to determine the start of the growing season on-line from soil moisture observations. This could replace a traditional method, based on the occurrence of the Ramadan, that in retrospect appeared inferior to scientific methods and kept yields considerably lower at all levels of fertilizing (Onyewotu et al., 1998). Probabilistic forecasting, through the use of the Southern Oscillation Index, may well be able to compete with the above-mentioned traditional knowledge in India (CLIMAG, in WMO, 2002). This shows that no generalized statements may be used on the value of traditional methods and that local case studies have to illustrate the usefulness of options. Organizing timely availability of the information and services, in the right form, then becomes a decisive factor in being able to use them in risk management decisions.

The options remaining valid with respect to wind have recently been exemplified for smallholder agroforestry by Stigter et al. (2001, 2002), while those of radiation are particularly scattered throughout the intercropping literature (e.g. Stigter and Baldy, 1993; Stigter, 1994; Baldy and Stigter, 1997). A wind example is the use of trees to combat desertification and limit damage by dry air through mitigation of wind speeds and turbulence, contributing to resource and crop protection (Onyewotu et al., 1998; Stigter et al., 2002; Onyewotu et al., 2003). Another is the reduction of wind erosion by keeping stubble in winter from summer intercropping belts on sloping land in Inner Mongolia (Zheng, internal publications, 1999; An and Tuo, 2001). Radiation examples may be found in i. shade protection; ii. pruning of trees in all kinds of agroforestry systems and iii. other intercropping systems aiming at resource sharing (Stigter and Baldy, 1993). Note that these risk management examples deal more with mitigation of the parameter itself and not with the climatological variability of that parameter. However, these short examples illustrate the importance of modifying a parameter, this way influencing the range of its variability. It should, in addition, also be stressed that these examples may play a key role in transfer of climate information for risk management strategies and agrometeorological services towards sustainability of LEISA farming systems with improving inputs, and therefore in their stability.

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