Integrated, participatory, seasonal observations for land systems
Rajeswari S. Raina*, Anand Sharma and Zia Mohammed *Scientist, National Institute of Science, Technology and Development Studies (NISTADS), Dr. K. S. Krishnan Road, New Delhi - 110 012. Officer-in-charge, and Systems Manager, IPSOS project, Gram Vikas Kendra, IDC- Field Office, Village Rahepwa, P.O. Pinangwan, Gurgaon District, Haryana. *Email: rajeswari_raina@yahoo.com Introduction This paper draws attention to seasonality as an essential concept in planning, implementing, monitoring and evaluating land-based rural development programmes. It presents the need for a conceptual re-orientation in land-based rural development programmes. The case of an information facility in Rahepwa village in Mewat, Haryana State is used to illustrate the critical role of integrated and participatory seasonal observations for rural development. Rural knowledge is conditioned by the exigencies of rural livelihoods. Seasonality, with low mean incomes and high seasonal variance in incomes, is one of the primary causes of distress in rural livelihoods. Seasonality of rural livelihoods is not confined to the economics of income. Seasonal changes also aggravate the gamut of existing economic, social, political and cultural handicaps that directly determine or indirectly influence the well-being of the rural population. This paper presents participatory generation and use of meaningful information, within the framework of the seasonality of rural livelihoods, as a crucial input for sustainable land-based development. Section II here presents the case for a season-sensitive land information base. It is argued that information for development must be generated and used by the rural population, by integrating different sources of information, starting with peoples primary perceptions. Section III calls for the use of systems concepts in land information base to solve the seasonality problem in persistent poverty and under-development. Systems concepts inform all the important stages of an “integrated participatory seasonal observation system” (IPSOS hereafter), and participatory project formulation, implementation, monitoring and evaluation. Section IV presents crucial insights gained from the IPSOS project in Rahepwa village in Mewat. We conclude that land information in a systems format, as in the IPSOS case, is a desirable institutional change for rural empowerment. Seasonal observations for sustainable development Seasonality is and will continue to be a major stumbling block in rural development in every LDC, where agricultural and rural livelihoods depend on seasonal fluctuations in access to food, employment, income, and seasonal changes in status of health/morbidity. The developed countries are also subject to seasonal changes. But rural livelihoods there are not so absolutely dependent on seasonal fluctuations. Food, for instance is never completely absent or inaccessible. Moreover, in the North in general, “harvest, the main agricultural labour peak, comes at a healthy time of year.” (Chambers, 1979, p.13). Even with capital intensive labour saving technologies, the rural population in developed countries experience minimal seasonal migration or displacement. Along with developing appropriate (location specific) counter-seasonal technologies, these countries have also “shifted resources” (labour and capital) from “seasonal industries to non-seasonal ones.” (Gill, 1992, p.7) In terms of rural livelihoods, the most significant implication of this shift of resources to non-seasonal industries, is a lower variance in income during the year. Besides the Engel’s coefficient being low in these developed countries, the seasonal consumables occupy a relatively low share in the consumption basket of the rural population in these countries. High levels and quality of material and social infrastructure ensures that any loss of or reduction in seasonal production or income is accounted only as additional production costs and is duly ‘passed on to the consumer’. (Gill, 1992, p.18) The case is quite the reverse in the LDCs, where the incidence of poverty and seasonal industries is high, and the market and State infrastructure favours the consumer more than the producer. More recently, research on the impact of global climate change shows that there will be distributional impacts, with developing countries generally worse off than developed countries. (Rosenzweig, et al, 1993, and Kaiser, 1994) A significant point emerging from studies on global climate change and agriculture, is the increase in seasonality (climatic variability) that may arise from a changed climate. (Oram, 1985). It is this seasonal variation in temperature/ precipitation that will influence crop yields more, than the effects of an overall change in climate. Climate change is afterall not any discrete change, but a gradual dynamic evolving phenomenon of changes in temperature and precipitation. Therefore, more studies are needed to tell us “how climate change will impact the variability of climatic variables.” (Kaiser, 1994, p. 9) We need to take a fresh look at climate change and the information needed to analyse the impact of climate change. Technically, conceptualizing and modelling climate as a gradual, evolving phenomenon, or reducing the grid sizes of general circulation models, or improvements in the representation of land surfaces/ clouds, will be required. (Kaiser et al, 1991 as given in Kaiser, 1994, p.9). On the economic and social front, a new conceptual framework is needed to understand the social impacts of climate change. (Sonka and Lamb, 1987, given in Kaiser, 1994). What is imperative in these studies though is “adequate information” on how climate change affects land systems, plants and animals. It is important to realize that in a world with changed climate, there will be a changed world; there is a highly complex and dialectic relationship between the world (of land and agriculture) and the climatic factors that affect it. (Rosenberg, 1992). Seasonality is now accepted as a central concern in the proverty and underdevelopment problem in LDCs. (Chambers et al, 1981 and Longhurst, 1986). There have been attempts to analyze and explain the relationship between seasonality and employment, (under) nutrition, poverty, health, working capacity / stress, and gender bias. But little effort has been made to translate these explanations / conclusions to tangible counter-seasonal development strategies. On the contrary, several development projects and programmes have aggravated the seasonality problem in LDCs, thereby bringing more misery to rural areas, especially to the poorest households. In this context, Chambers (1995) has been vociferous in demanding “a paradigm of reversals and altruism”, one in which the rural poor have the right to conduct their own analysis. Several conceptual and action oriented changes or reversals have been suggested.(Chambers 1995). In this paper we present systems concepts and the generation and utilization of information within the framework of seasonality, as the conceptual and action oriented changes that can lead to sustainable agricultural development. One crucial input that can help rural people conduct their own analysis is their access to the information and data about themselves. We present seasonality, or the existence of the rural poor “in-time” unlike our “season-proof” existence, as the principle around which the information base for the rural poor can be built. This calls for a season-sensitive information base. The case for seasonal land observations Seasonality, in the context of developed countries, is not a problem in itself. In the LDCs, poverty (low mean income) and seasonality (high variance), leads to a critical minimum level of consumption. This, the low mean high variance income matrix gives us the basic framework within which rural development action is located. Poverty, in most LDCs is not determined by income (cash and kind) alone. Several other factors like caste, traditional occupations, social contracts, and labour relationships, influence income, employment and consumption decisions. Poverty, the low mean income, does add to this nexus of problems, determining the adjustments / adaptations that people make to seasonal changes. What according to the rural poor, is the most preferred and effective counter-seasonal strategy? Jodha (1988) highlighted the “development paradox” (also called “Jodha’s paradox” -See Chambers 1995). Villagers in Rajasthan, on defining their own categories and criteria of economic status, scored themselves better off but poorer in 1982-84 than in 1964-66. The paradox came with their criteria, 37 out of 38, which revealed that they were on the average better off despite being poorer in terms of per capita real incomes. Another participatory analysis (Chambers 1995, p. 16) in Pakistan revealed that “more income” was the 9th or 10th preferred in a list of some 20 criteria. Coming back to Jodha’s development paradox, and the criteria of well-being listed by the villagers, it is obvious that all these criteria relate directly or indirectly to the seasonality of their existence. An increase in well-being is a function of a decline in the seasonality of existence. To understand the seasonal problems and well being, and to design appropriate and feasible counter-seasonal development projects, it is essential to perceive changes in seasonality and well-being as part of the overall system dynamics of the village. Land being the most critical resource for food production and for employment, we consider how information on land is used in a counter-seasonal development project. In India, the State Agricultural Statistics Authorities generate data on agricultural and livestock production at the State level, which are aggregated by the Directorate of Economics and Statistics of the Central Ministry of Agriculture. Given the processes of collection and the treatment of inputs as common to both sectors, the Gross Domestic Product figures are not available separately for the agriculture and livestock sub-sectors. (Kulshreshtha, 1997, p. 1652). In each State the crop yield estimates by the General Crop Estimation Surveys (GCES) is prepared crop-wise, based on scientifically designed crop cutting experiments. The GCES is dependent on timely completion of basic records; the theoretical design of GCES is disturbed by incomplete primary land use statistics. (ibid, p.1653) Given the difference in sowing time (ranging about two months during each season) even within the same agro-ecological zone in a State (there may be 5 - 12 agro-ecological zones in a State) the problems of timely reporting of yield or non-completion of yield statements, are major drawbacks and important sources of non-sampling error in the estimation of crop yield in each season (Kharif and Rabi). (ibid , Table 5) Agricultural statistics in India is sufficiently decentralized in terms of location or points of data collection. The centralization is in terms of time; the data on area sown (land use statistics), crop yield (GCES), prices (value of output) are all collected at specific points of time for each for the entire district. A district often covers different agro-ecological zones, with sowing dates, harvest, and market transactions ranging over two months for each, even within the same agro-ecological zone. The likelihood of over or underestimation of domestic product from the agricultural sector is significant. In the case of prices, secondary data is particularly insensitive to the actual farm income; “the output of a district is treated as transacted at the average price prevailing in different primary marketing centres during the peak marketing period in a district.” (ibid, p. 1654). Given the size of the country and the enormous coverage of the agriculture and livestock sectors, it is perhaps difficult to collect farm gate prices (the first point of transaction) at regular intervals during the harvest season in each agro-ecological zone, with statistically accurate aggregations for estimation of volume and value of produce transacted at each level, district, State and national. But if the problems associated with the seasonality of rural livelihoods are to be solved, the information has to be meaningfully decentralized and disaggregated both in space and time - location-wise and season-wise. Information across institutions and through intra- and inter-seasonal intervals in time, is essential if a data-base for regional planning is to be built. The institutions include, depending on the specific eco-regional context, individuals / farms/ households, to village clusters / agri-business groups and labour contracts / caste systems. We present here, the ‘information transect’ for Rahepwa village in Mewat. This transect for two seasons in the village reveals the need for seasonal observations of the land, water and human resources systems to solve real problems in rural livelihoods. Information on the village system, its elements, and the nature of inter-seasonal variations, begins with the primary perceptions of the people inhabiting the village. These primary perceptions can then be validated and collated along with micro and meso level information on contexts and contents, and integrated with existing macro level information. Generation of data / information within the framework of seasonality of rural livelihoods is essentially a participatory process. In land use plans, information to formulate and implement counter-seasonal development projects must be contextualized within these seasonal variations. Particularly important are the inter- and intra-seasonal variations in the nature and use of the basic resources in the village- land, water and labour, - as mediated by relevant institutions within and outside the village. The basic characteristic of a meaningful land systems information set is its location “in-time”. For instance, a farming systems improvement project may assume that farmers crop layout, crop sequences,and land management operations are logical/ rational responses to a particular rural context. But for the farmer, his/ her farming system is inevitably the result of his/ her cumulative knowledge of events unfolding through a seasonal calendar. It is difficult for a development agency / sponsor to get to respond to the time factor involved in a particular crop layout or cropping sequence. In location specific information and /or technologies, the term location conveys only the spatial context, leaving the time or seasonal context often unrepresented. When a crop layout in a season or a cropping sequence in an year “result from” each farmer’s cumulative knowledge over time, it becomes imperative that a farming systems improvement project and the local farmers share the same spatial (locational) logic as well as the temporal logic (Richards, 1989). Meaningful land systems information is located within the rural time-scale, of cooking, cleaning, washing, feeding/ agricultural operations/ cattle grazing/ market dealings/ and such during the day; processing, storing/ cattle care/ and such during the week; crop layout/ agricultural operation plan and work/ cattle dealings (letting out, sale or purchase)/ market activities/ family decisions, delegation of responsibility, work share/ and such during the season. In addition, the rural time scale functions on the cumulative knowledge of previous days, months, seasons and years. To collect and use this highly disaggregated information, it is imperative to ensure a realistic “integration” of various sources, methods of collection, modes of interpretation and use, of data (quantitative and qualitative) as it exists in the village system. Systems concepts and seasonal information Systems theory provides a rich range of possiblities for generating and utilizing integrated participatory seasonal information. The basic concept from systems theory, that rural- especially agricultural- livelihood, is part of a complex set of interacting elements (Bawden, 1984), is applied here. Information about seasonal changes in livelihoods, therefore, is part and parcel of information about the whole village system. It is more than a list or aggregation of selected economic or social variables. Given the unpredictable nature of seasonal changes, a systemic perception is essential: ...(it) is sensitive to contextual issues from which unforseen problems can emerge. Indeed, it seeks to learn from the sources of those problems - other stakeholder perspectives, for example- and to encourage joint formulation of management solutions informed by both local and non-local knowledge. (Ison, Maiteny and Carr, 1997, p. 264). The systems linkages and their significance in the context of different livelihoods are evident with the participation of women, pastoralists, artisans, landless labourers, various groups/ types of farmers, external change agents like the extensionists, fertilizer dealers, flayers/ tanners/ other agro-processing business, the line Departments of the State, the local NGOs, etc., in a regular institutionalized process of data collection and use. Participation of the rural population in generating and utilizing their own seasonal information reveals how different people interpret the same seasonal context in different ways, “based in line with their experiences and worldviews, or Weltanschauung and purposes.” (Ison, Maiteny, and Carr, 1997, p. 260). Application of systems concepts to solving problems of seasonality of rural livelihoods demands that the “different, and sometimes conflicting perspectives of stakeholders” (ibid) must be taken into consideration. Information generated thus, brings scope for mutual understanding and negotiation at each phase of the project, starting from problem formulation, implementation of prioritised counter-seasonal strategy, through participatory monitoring and evaluation of the project, and follow-up activities. We present examples from our IPSOS facility in Rahepwa to show how integration of information within a systems perspective considers the systems information concepts:
We present here, the systems framework and optimum land systems information being generated in Rahepwa, over the past one year. (Table 1: Overall Systems Data-base for Rahepwa) An illustration of counter-seasonal development animated with the application of systems concepts is presented in Figure 2. This information on a problem-determined system “enables the perception of the problem and the system as a socio-cultural construct as well as a bio-physical phenomenon.”(Ison, Maiteny and Carr, 1997, p. 261). The problem-determined system, unlike a system-determined problem, involves all relevant actors and enables expression of different stakeholder perceptions. The data-base in an integrated participatory seasonal observatory will thus have two broad components: an overall systems data-base, and the problem-determined systems data-base. The former will house information from secondary and primary sources, supplied on a regular basis (annual, monthly, weekly or daily) on the key components and linkages that describe the village system and are relevant to the seasonal well-being of the rural people. This will include information on the meso-level environment including seasonal changes in the basic resources of the village - its land, water and labour, the macro-level economic and political indicators, the meso and micro-level economic and social variables. The latter will contain observations -variables and relationships, on the specific problem-determined system that is perceived and analysed based on the first set of overall seasonal systems observations in the village. This information on selected variables influencing well-being in the context of specific problem-determined systems is then used to formulate and implement counter-seasonal development projects. Table 2: A problem-determined systems data-base. IPSOS enables incorporation of monitoring and evaluation criteria at the very outset of the counter-seasonal development project. The first part of the IPSOS data-base on the overall systems components and linkages will replace the base-line survey in usual development projects. This data-base, will be dynamic, may have new components added over time, sufficient flexibility to map and explain the interactions of each of the components with respect to their environments, and will continue to explore the possibility of equifinality. The first set of sustainability criteria / parameters can be drawn from the indicators of seasonal well-being as revealed by the overall systems data-base. These in turn, draw heavily on the information generated on seasonal changes in the basic resources of the village - land, water and labour. Thus, three basic criteria for participatory monitoring and evaluation are:
The information generated on each of these monitoring and evaluation criteria are fed into the overall systems data-base. The second part of the IPSOS data-base has information specific to the problem-determined system selected for implementation as the counter-seasonal development project. Here, specific parameters and performance measures are added based on the counter-seasonal development project formulated and the sustainability criteria derived from the overall systems data-base. Specific measures relating to seasonal well-being, in terms of daily events/ work loads/ leisure/ consumption, morbidity, etc., are added to specific measures derived from the three monitoring and evaluation criteria given above. Successful participatory monitoring and evaluation, is contingent upon the people making their decisions about expectations. This keeps the project keyed to realistic achievements / targets. Besides feeding into the final impact assessment of the project, these monitoring criteria are also tuned to change the course of the project if unintended changes are reported in the physical components / the environment or any of the institutions in the village. IPSOS is a tool for rural empowerment; these monitoring and evaluation criteria capture people’s perceptions of well-being in their own rural idiom or time scale. The potential for using the IPSOS data-base to correct / reinterpret secondary data- sources/ methods of collection, etc, is immense. Most significantly, however, IPSOS promises policy feed back from the rural population, based not on rhetoric or rumuor but on a tangible data-base and participatory decision-making in the use of the data-base. NGOs in their existing role as information sharing agents, (Meyer, 1997) have an even more powerful role to play in IPSOS. Empowered with the IPSOS data-base, NGOs can actively change the balance of power among States, markets and the rural population. But the usual assumption of “institution building”, that the NGOs create and build the institutions where none existed before, is avoided here. Information flows, access and denials to information, inter-generational transfer of knowledge /technology, gender roles and bias in knowledge and skills, and the like have been institutionalized in every village over centuries of human civilization. It is not assumed that the NGO will institutionalize IPSOS where no institutions for seasonal information or exchange existed. IPSOS must essentially be built on the strength of the existing institutions for information generation and management. IPSOS can have a long term impact on existing secondary data sources. Once IPSOS generates weekly and seasonal morbidity patterns, the data base can itself be a corrective measure for the local PHC which feeds data to the State Department. But in the case of data on the unorganized sector, IPSOS will take a long time to feed into existing secondary sources. The Central Statistical Organization publishing data for the organized and unorganized industries, can draw directly from the village level employment information which is stored in the IPSOS facility. Migration, partial/ marginal industrial employment, location of such unorganized employment, value added or income change from such unorganized work force, inter- and intra- sectoral movement of labour during the year, and female labour force participation in the organized and unorganized sectors can be accessed from the IPSOS facility. The integrated participatory land use data and decisions in Rahepwa are illustrate these points. Reference: [ An earlier version of this paper “Seasonality and Meaningful Information for Rural Development” was presented (by the first author here), at the session on Knowledge Generation for and by the rural poor, at the Global Knowledge 1997 Conference in Toronto, 22-25 June 1997. It was also used as a discussion paper for the session on “Participation: Planning, Formulation, Implementation, Monitoring and Evaluation of Development projects” in the Technical Consultation on Decentralization, 16-22nd December 1997, Rome. Italy.]
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