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«C.J. STIGTER1, ZHENG DAWEI2, L.O.Z. ONYEWOTU3 and MEI XURONG4 TTMI/African Network & Asian PMP Liaison Office, Wageningen University, The ...»

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TTMI/African Network & Asian PMP Liaison Office, Wageningen University, The Netherlands

E-mail: kees.stigter@wur.nl

College of Resources and Environment, China Agricultural University, Beijing, P.R. China

TTMI-Project, Kano out-station, Forestry Research Institute of Nigeria, Kano, Nigeria Center for Water Resources and Conservation Technologies, Chinese Academy of Agricultural Sciences, Beijing, P.R. China Abstract. In agrometeorology and management of meteorology related natural resources, many traditional methods and indigenous technologies are still in use or being revived for managing low external inputs sustainable agriculture (LEISA) under conditions of climate variability. This paper starts with the introduction of an “end-to-end” climate information build up and transfer system in agrometeorology, in which the use of such methods and technologies must be seen to operate. It then reviews the options that LEISA farmers have in risk management of agrometeorological and agroclimatological calamities. This is based on the role that the pertinent meteorological/climatological parameters and phenomena play as limiting factors in agricultural production and the expectations on their variability. Subsequently, local case studies are given as examples of preparedness strategies to cope with i). variable water/moisture flows, including mechanical impacts of rain and/or hail, ii).

variable temperature and heat flows, including fires, and iii). fitting cropping periods to the varying seasons, everywhere including related phenomena as appropriate. The paper ends with a series of important additional considerations without which the indicated strategies cannot be successful on a larger scale and in the long run.

1. Introduction In a recent review of agrometeorology in tropical Africa, Olufayo et al. (1998) stated that consequences of climate variability show themselves at any time as the effects of the accumulated weather in the current growing season compared to those of the same period in previous years. There are countless farming communities which managed to survive and, in some cases, even to thrive by exploiting natural resource bases, which their forebears have used for generations (Reijntjes et al., 1992). Through a process of innovation and adaptation, traditional farmers have developed numerous different indigenous farming systems finely tuned to many aspects of their environment (LEISA, 2000). Such risk management strategies were in response to, among others, the limiting conditions of varying climate.

Over the microclimate they nevertheless exercised significant control, as numerous review publications have indicated (e.g. Smith, 1972; Wilken, 1972; Bunting, 1975;

Stigter, 1988, 1994; Stigter et al., 1992). However, new operational services in agricultural meteorology are badly needed for decision making in risk management for c Springer 2005 Climatic Change (2005) 70: 255–271 256 C. J. STIGTER ET AL.

specific on-farm conditions. These agricultural environments of peasants in nonindustrialized regions are now endangered by new and expanding hazards that rapidly change the living conditions in many places in the tropics and sub-tropics (e.g. Stigter and Baldy, 1993; Baldy and Stigter, 1997; Blench and Marriage, 1998).

Among much other literature, the IPCC reports, from many sources that they used, have convincingly reviewed the scenarios. Increasing climate variability, resulting in more frequent and more serious extreme meteorological and climatological events, will be a factor with which all farming systems will have to cope.

Salinger (2004) has unmistakably concluded that we are heading for hard times in agriculture and forestry. From Africa (e.g. Mungai and Stigter, 1993; Stigter, 1995; Baldy and Stigter, 1997) to Latin America (e.g. Wilken, 1987) and different parts of Asia (e.g. Anonymous, 2001; Luo, 2001; Manton, 2001), those working in rural areas have become convinced of two essential issues. Firstly, traditional knowledge, indigenous practices and identified local innovations (e.g.

LEISA, 2000, 2001) contain valuable information that should be used as a basis for improved farming systems practices to cope with the necessary changes in risk management. Secondly, contemporary science and new methodologies and technologies should, also in agrometeorology, be guided by appropriate policies, that themselves need a scientific basis and a humane socio-economic basis.

They should be locally applied to develop agrometeorological services to assist in the risk management transformations needed (e.g. Smith, 1972; ILEIA, 1995;

Stigter, 1999; Salinger et al., 2000; Stigter et al., 2000). Figure 1 reviews this systematically.

In their classic treatise, Brokensha et al. (1980) refuse to define indigenous knowledge and point to the case studies collected to describe it. Fifteen years later Warren et al. (1995) call it “the local knowledge that is unique to a given culture or society” and contrast it with the international knowledge system, which is generated through the global network of universities and research institutes, that we have called contemporary knowledge in Figure 1. Our context of LEISA farmers, this way defines traditional knowledge and indigenous technologies, also when, as may be expected, components of that knowledge have found their way into higher input and even high-tech growing systems. Local innovations are knowledge and technologies empirically generated by the, in this case LEISA, cultures and societies from within their present farming systems (LEISA, 2000). In line with the stewardship advocated by Houghton (1997) and the highest resilience emphasized by LEISA (2001), to the role of science applies the paradigm change worded by Norse and Tschirley (2000): technological change should no longer be driven by science but by environmental objectives and social concerns, like farmer innovations, operating through the market where appropriate. It is these policy environments that should guide the knowledge pools towards operational agrometeorological services for farm management decisions (Stigter 2002a, 2002b).

This paper exemplifies the valuable local knowledge of preparedness strategies.

It wants to work with case studies in which indigenously developed technologies


Figure 1. Relations between the three activity domains (A, B and C) defined, guided by agrometeorological action support systems on mitigating impacts of disasters (E1) and agrometeorological services supporting actions of producers (E2). This “end-to-end” system in agrometeorology, for transfer of climatological information, combines earlier ideas in Stigter et al. (2000), Norse and Tschirley (2000), Shumba (2001) and Stigter (2002a, b).

are used for agrometeorological services in risk management, illustrating this new paradigm in coping with climate variability. The context of this must be that particularly over the last two decades or so, developments in the field of meteorology, climatology and the environment as well as socio-economic changes occurred much faster than new adapted and innovative agrometeorological services could be established. This is due to difficulties in making interdisciplinary knowledge operational for sustainable agriculture in developing countries and to problems in having new information absorbed and applied in rural areas, against the background of a deteriorating infrastructure (Stigter, 2001). It is now widely accepted that only where households are fully incorporated in all phases and aspects of development processes, may future innovative services in agrometeorology make any difference for the income of LEISA farmers (e.g. Das, 2001; Norman, 2001).

We deal in an end-to-end system for build up and transfer of climate information in agrometeorology with the relations between sustainable livelihood systems (domain A in Figure 1), pools of knowledge allowing useful strategies towards 258 C. J. STIGTER ET AL.

agrometeorological services (domain B in Figure 1), and basic support systems (domain C in Figure 1) (Stigter et al., 2000; Norse and Tschirley, 2000; Shumba, 2001; Stigter 2002a; 2002b). After all, the good intentions of the agrometeorological action support systems on mitigating impacts of disasters that we established so far (E1 in Figure 1) did not lead to sufficient operational agrometeorological services to support farm management decisions (E2 in Figure 1). In LEISA, traditional methods, indigenous technologies and local innovations still have an important role to play. This shows the context of the approach in this paper.

2. 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;

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