Rana et al._PGRN_2007.pdf

58 Plant Genetic Resources Newsletter, 2007, No. 152 Genetic Resources Newsletter, 2007, No. 152: 58–64 Plant ARTICLE On-farm management of rice genetic diversity: understanding farmers’ knowledge on rice ecosystems and varietal deployment R.B. Rana,1* C.J. Garforth,2 B.R. Sthapit,3 A. Subedi,4 P. Chaudhary5 and D.I. Jarvis6 1 Programme Officer, LI-BIRD, Nepal (currently Resource Mobilisation Coordinator, Britain Nepal Medical Trust (BNMT), Nepal) E-mail: rmc@bnmt.org.np 2 Professor of Agricultural Extension and Rural Development, The University of Reading, UK 3 Scientist, Bioversity International – APO Region 4 Executive Director, LI-BIRD (currently Chief Executive Officer, BNMT, Nepal) 5 Project Officer, LI-BIRD, Nepal 6 Senior Scientist, Bioversity International, Rome, Italy Summary Résumé Resumen On-farm management of rice genetic diversity: understanding farmers’ knowledge on rice ecosystems and varietal deployment Gestion de la diversité génétique du riz on farm : valorisation de la connaissance des agriculteurs relative aux écosystèmes rizicoles et exploitation variétale Ordenamiento de la diversidad genética del arroz en la granja: conocimientos campesinos acerca de los ecosistemas del arroz y el despliegue varietal The paper highlights the methodological development of identifying and characterizing rice (Oryza sativa L.) ecosystems and the varietal deployment process through participatory approaches. Farmers have intricate knowledge of their rice ecosystems. Evidence from Begnas (mid-hill) and Kachorwa (plain) sites in Nepal suggests that farmers distinguish ecosystems for rice primarily on the basis of moisture and fertility of soils. Farmers also differentiate the number, relative size and speciic characteristics of each ecosystem within a given geographic area. They allocate individual varieties to each ecosystem, based on the principle of ‘best it’ between ecosystem characteristics and varietal traits, indicating that competition between varieties mainly occurs within the ecosystems. Land use and ecosystems determine rice genetic diversity, with marginal land having fewer options for varieties than more productive areas. Modern varieties are mostly conined to productive land, whereas landraces are adapted to marginal ecosystems. Researchers need to understand the ecosystems and varietal distribution within ecosystems better in order to plan and execute programmes on agrobiodiversity conservation onfarm, diversity deployment, repatriation of landraces and monitoring varietal diversity. Simple and practical ways to elicit information on rice ecosystems and associated varieties through farmers’ group discussion at village level are suggested. L’identiication et la caractérisation des écosystèmes rizicoles (Oryza sativa L.) ainsi que l’exploitation variétale sont étudiées par des approches participatives. Des observations à Begnas (collines d’altitude moyenne) et à Kachorwa (plaine), Népal, montrent que les agriculteurs distinguent les écosystèmes rizicoles principalement sur la base de l’humidité et de la fertilité des sols. Les agriculteurs prennent également en compte le nombre, la taille relative et les caractéristiques spéciiques de chaque écosystème dans une zone géographique donnée. Ils établissent un lien entre les différentes variétés et chaque écosystème, identiiant « le meilleur compromis » entre les caractéristiques de l’écosystème et les caractères variétaux, ce qui implique une compétition entre variétés au sein des écosystèmes. L’utilisation du sol et des écosystèmes conditionne la diversité génétique du riz, les sols marginaux limitant davantage le choix des variétés que les zones plus productives. Les variétés modernes sont principalement coninées aux sols fertiles, tandis que les variétés locales sont adaptées aux sols marginaux. Les chercheurs doivent mieux comprendre les écosystèmes et la distribution variétale pour pouvoir planiier et mettre en œuvre les programmes de conservation on farm, l’exploitation de l’agrobiodiversité, le rétablissement des variétés locales et le suivi de la diversité variétale. Des moyens simples et pratiques sont proposés pour aborder le thème des écosystèmes rizicoles et variétés associées par des discussions de groupes d’agriculteurs au niveau des villages. Este documento destaca la metodología de identiicación y caracterización de los ecosistemas del arroz (Oryza sativa L.) y del despliegue varietal, a través de métodos participativos. Los conocimientos de los agricultores acerca de sus ecosistemas arroceros son complicados. Datos de Begnas (colinas medianas) y Kachorwa (planicie) en Nepal indican que los distinguen principalmente por la humedad de los suelos. También por la cantidad, tamaño y características especíicas de cada ecosistema en una zona geográica dada, asignando cada variedad según el principio de la “mejor adecuación” entre las características del ecosistema y los rasgos varietales, pues la competencia entre las variedades acaece principalmente dentro de los ecosistemas. Los ecosistemas y el uso de la tierra determinan la diversidad genética del arroz porque las variedades tienen menos opciones en tierras marginales que en zonas más productivas. Las variedades modernas se concentran sobre todo en las tierras productivas, mientras que las locales se adaptan a los ecosistemas marginales. Los investigadores necesitan comprender mejor los ecosistemas y la distribución varietal dentro de ellos a in de planiicar y ejecutar programas para conservar la agrobiodiversidad en las explotaciones agrícolas, desplegar y monitorear la diversidad varietal, y repatriar variedades locales. Se sugieren maneras sencillas y prácticas de obtener información relativa a los ecosistemas arroceros y sus variedades asociadas, valiéndose de los debates de campesinos agrupados a nivel de aldea. Key words: On-farm conservation, crop genetic diversity, ecosystems, varietal deployment, Nepal Plant Genetic Resources Newsletter, 2007, No. 152 Introduction The scientific community has come to realize the complementary nature of ex situ and in situ conservation methods in addressing different aspects of conservation of genetic resources (Brush 2000). As a result, there is an increased interest in understanding the functioning of in situ conservation in relation to agrobiodiversity. In situ conservation for local crop diversity effectively implies on-farm management, which has been deined as “farmers’ continued cultivation and management of a diverse set of crop populations in the agro-ecosystems where the crops evolved” (Bellon et al. 1997). Since in situ conservation of agrobiodiversity on-farm is a relatively new subject, limited experience exists concerning its management, both at national and international levels. There are gaps in understanding of the subject matter and also of the methods, tools and techniques, and institutional settings for conserving and utilizing agrobiodiversity for the beneit of farmers (Wood and Lenne 1997). With the implementation of an IPGRI (now Bioversity International) coordinated global project on ‘Understanding the Scientiic Basis of In Situ Conservation of Agrobiodiversity On-farm’ in nine different countries, signiicant progress has been made in developing tools and techniques for conserving, monitoring and utilizing agrobiodiversity on-farm. The rationale for studying farmers’ local knowledge of ecosystems and varietal (landraces and modern varieties (MV)) deployment rests on the tenet that agrobiodiversity and local knowledge held by farmers are two faces of the same coin (Rajasekaran and Warren 1994). Therefore, it is vital for researchers to document and analyse farmers’ local knowledge, not only in terms of ‘what’ and ‘how’, but also ‘why’, so that the blending of scientiic knowledge and local knowledge is achieved for strengthening farmers’ capacity to continue growing landraces and to contribute to on-farm conservation. The present article deals with the methodological development of a rice (Oryza sativa L.) ecosystem classiication and varietal deployment tool, and explains how the exercise contributes to on-farm conservation, varietal deployment and the monitoring of varietal dynamics on-farm over time by practitioners in the ield. Methodology The methodology adopted for the study comprised Participatory Rural Appraisal (PRA) tools—Focus Group Discussions (FGD), transect walks, and direct observations— that were employed to elicit farmers’ knowledge on rice ecosystems, varieties and their deployment in different ecosystems. The study was conducted in two contrasting ecosites: Begnas village, representing mid-hill (600–1400 masl) conditions characterized by limited intervention from research and extension agencies, with medium level of road and market access; and Kachorwa village, representing plain (<100 masl) conditions, with high intervention from research and extension agencies, and good road and market access. FGDs conducted at site level were speciically used to identify different criteria used by farmers to delineate rice 59 ecosystems. During FGDs, farmers were asked to list criteria they use to identify different ecosystems for rice in their locality. Once the group agreed with the criteria, then they classiied and characterized different ecosystems based on the agreed criteria. After that the farmers discussed ‘how’ and ‘why’ they deployed different landraces and MVs in particular ecosystems, based on their experience and knowledge of the ecosystems and varietal performance. The FGD exercise was followed by a transect walk by a combined team of farmers and researchers to visit rice ields to verify on the ground the deployment of varieties to different ecosystems. Findings Farmers indigenous method of characterization of rice ecosystems Farmers employ multiple criteria to characterize rice ecosystems (Tables 1 and 2). During the study, the farmers identiied eight different criteria to classify their rice ecosystems in the village. When characterizing rice ecosystems, the farmers considered physical properties of soil such as texture, colour and presence of pebbles. Ability to retain water (after rain or irrigation) for a longer period is an important criterion. The farmers also considered ease of ploughing and weeding. Finally, they considered attributes that directly contribute to crop yield, such as inherent fertility status of soil, as well as productivity potential inluenced by human-managed factors (application of compost/farmyard manure, chemical fertilizers and irrigation). Soils at the study sites were generally clay for marshy lands, loamy to clay in irrigated lands, sandy loam to clay for rainfed, and sandy loam to loam for upland. The colour varied, with red soil in upland, black in irrigated and marshy lands, and grey or yellowish white in rainfed land. Water holding capacity refers to the duration one can observe water on the plots after rain or irrigation stops, and this trait is very important in distinguishing rice ecosystems. Different ecosystems within and between sites vary greatly for this trait, ranging from a few hours to whole seasons. Upland has the least capacity to hold water due to soil type, presence of pebbles and lack of bunds along the edge of the ield, whereas marshy or pond ields hold water beyond the rice growing season. The amount of pebbles present in upland condition explains the better drainage of water, which implies that rice in upland suffers more frequently from moisture stress than in other categories of rice ecosystem. In general, ease of ploughing and ease of intercultural operations are important traits associated with irrigated land. Ploughing is most dificult in marshy land because of heavy (clay) soil with plenty of moisture, but weeding is easy as weeds are generally suppressed due to standing water throughout the rice growing period. Apart from water holding capacity, fertility status and production potential of plots are the major criteria farmers employ when classifying their rice ecosystems. Across the sites there was agreement that inherent fertility of soil is highest for marshy plots (pond in Kachorwa) and lowest for rainfed plots. In terms of productivity potential, the farmers identiied the 60 Plant Genetic Resources Newsletter, 2007, No. 152 Table 1. Characteristic features of the rice ecosystems at the Begnas ecosite. Parameter Rice ecosystem Ghaiya bari (upland) Tari (rainfed) khet Sinchit (irrigated) khet Dhab (marshy) khet Soil type Loam, sandy loam Clay Loam, clay Clay Soil colour Red, grey Grey, red Light black Medium to dark black Water holding capacity 1-2 hours 2-5 hours 5-7 days Monsoon and winter Limited Limited None Pebbles and small stones Plenty † Ease of ploughing 1 (easy) 3 2 4 (difficult) Ease of inter-cultural operations 4 (difficult) 3 1 (easy) 2 Fertility status 3 4 (lowest) 2 1 (highest) Productivity potential 3 4 (lowest) 1 (highest) 2 Area (%) 2-3 20-28 65-70 5-7 Notes: Key to ecosystem types: Ghaiya bari is unbunded upland where dryland rice called Ghaiya is cultivated; Tari khet is rainfed bunded field where puddle rice is cultivated; Sinchit khet is irrigated khet land with good drainage where puddle rice is grown; and Dhab khet has standing water with poor drainage and puddle rice is grown. † after a light shower, ploughing of Ghaiya bari is easy. Table 2. Characteristic features of rice ecosystems at the Kachorwa ecosite. Parameters Rice ecosystem† Ucha (rainfed) khet Samtal (irrigated) khet Nicha (marshy) khet Man/Pokhari (deep water/pond) Soil type Sandy loam Loam Clay Clay, clay mixed with sand Soil colour Yellowish white Light black Yellowish, black Dark black Water holding capacity Up to 7 days 7-15 days 21-30 days 10 months Pebbles and small stones None None Limited None Ease of ploughing 1 (easiest) 2 4 (difficult) 3 Ease of inter-cultural operation 4 (difficult) 2 1 (easiest) 3 Fertility status 4 (less fertile) 2 (fertile) 3 (medium) 1 (highly fertile) Productivity potential 2 1 (highest) 3 4 (lowest) Area (%) 25 50 20 5 irrigated ecosystem as having the highest potential, followed by marshy ecosystem in Begnas, but rainfed in Kachorwa. The rainfed ecosystem had the least production potential for rice in Begnas, whereas the deep-water ecosystem was the least productive for Kachorwa. The farmers estimated that about 65 to 70% of the total rice area in Begnas was irrigated (temporary), followed by rainfed lowland (20–28%), while marshy areas and upland accounted for 5 to 7% and 2 to 3%, respectively, of the total rice area. Similarly, for Kachorwa, 50% of the rice ields were irrigated, 25% rainfed, 20% marshy and the remaining 5% being a deep-water ecosystem. Deployment of varieties across ecosystems After characterization of ecosystems, the farmers engaged themselves in deploying varieties to different ecosystems. Because of the numerous varieties to deal with, this process took much longer than expected at both ecosites. Moreover, there were several varieties that could be placed in more than one ecosystem, which also complicated the exercise. The list of varieties (landraces and MVs) currently grown at the study sites was irst developed. Varieties were then placed in extreme (marginal) ecosystems, and the exercise continued for more favourable ecosystems. The varieties deployed in different ecosystems for Begnas and Kachorwa are presented in Tables 3 and 4 respectively. Analysis of varieties across ecosystems at Begnas indicated that there was no MV in rainfed upland condition, though numerous landraces existed for the ecosystem. In other words, available MVs were less competitive than the existing landraces in rainfed upland conditions. Under rainfed conditions, there was a dearth of both landraces and MVs. Only three landraces were prevalent in this ecosystem, though it occupied 20–28% of the rice area. In the irrigated ecosystems there were plenty of varieties (options) for the farmers, with over 25 different landraces and 4 MVs available. Similarly, in marshy ecosystems, a number of landraces and MVs compete. As a result, there is competition between varieties for space in favourable ecosystems, whereas in marginal environments the farmers face a lack of varieties. Plant Genetic Resources Newsletter, 2007, No. 152 61 Table 3. Deployment of varieties across rice ecosystems at Begnas. Ecosystem Landraces Modern varieties (MVs) Ghaiya bari (upland) Seto Ghaiya, Jire Ghaiya, Kunchali Ghaiya, Jhayali Rato Ghaiya, Bichare Ghaiya, Lanare Ghaiya, Gurdi Ghaiya, Kanajire Ghaiya, Masino Ghaiya No MVs Tari (rainfed) Kathe Gurdi, Mansara, Anaga, Tunde, Jhauri, Pakhe Jarneli, Thapachini, Chobo, Rate, Pakhe Ramani CH-45 Sinchit (irrigated) Ekle, Thulo Madhese, Thulo Gurdi, Jethobudho, Pahele, Jhinuwa, Lahare Gurdi, Sano Madhase, Rato Anadi, Seto Anadi, Seto Bayarni, Naulo Madhese, Kalo Gurdi, Manamuri, Seto Gurdi, Gauriya, Seto Jhinuwa, Naltume, Baryani Jhinuwa, Jhinuwa Basmati, Kalo Tunde Jhinuwa, Kalo Baryani, Basmati, Kalo Jhinuwa, Biramphool, Tunde Jhinuwa Kanchi Mansuli, Mansuli, Radha-7, Radha-9 Dhab (marshy) Rato Anadi, Seto Anadi, Dhabe Jarneli, Gauriya, Mala, Lame, Tunde Jhinuwa, Barmali, Jhinuwa, Pahele, Jetho Budho, Bayarni Jhinuwa, Kalo Baryani Kanchi Mansuli, Mansuli Source: Focus group discussion (FGD) conducted at Begnas village. Note: Name in bold indicates the variety is best adapted to that ecosystem though grown in other ecosystems as well. Table 4. Deployment of varieties across rice ecosystems at Kachorwa. Ecosystem Landraces Modern varieties (MVs) Ucha (rainfed) Mutmur, Sotwa, Nakhi Saro, Sathi, Lalka Farm, Sokan, Ujarka Farm, Rango, Gajargaul, Khera, Aanga China 4, Chandina, Jiri, Philips, Television, Ch-45, BG 1442 Samtal (irrigated) Mutmur, Basmati, Sotwa, Nakhi Saro, Sathi, Lalka Farm, Sokan, Chatraj, Ujarka Faram, Lajhi, Rango, Ashani, Dipahi, Mallika, Dudhraj, Anadi, Batsar, Khera, Mansara, Aanga, Amaghauj, Kariya Kamod China 4, Masula, Sabetri, Chandina, Jiri, Philips, Masuli, Television, Meghdut, Jaya, Ekahatar, Radha 4, Kanchi Masuli, Nat Masula, CH-45, Radha-7, PD 1001, BG 1442 Nicha (marshy) Basmati, Chatraj, Lajhi, Karma, Kataus, Ashani, Dipahi, Laltanger, Mallika, Bhathi, Anadi, Batsar, Mansara, Silhaut, Amaghauj, Kariya Kamod Masula, Sabetri, Masuli, Meghdoot, Jaya, Ekahatar, Kanchi Mansuli, Nat Masula Man/Pokhari (deep-water) Karma, Kataus, Laltanger, Bhathi, Silhaut No MVs Source: Focus group discussion (FGD) conducted at Kachorwa village. Note: Name in bold indicates the variety is best adapted to that ecosystem, though grown in other ecosystems as well. Findings from Kachorwa also suggest that only a limited number of varieties exist for extreme conditions, whereas plenty of options exist for favourable conditions. There is not a single MV suitable for deep-water ecosystems and only a limited number of landraces exist for such conditions. In contrast, there are many landraces and MVs competing for space in more favourable environments. As in Begnas, farmers have a greater choice of varieties in favourable compared with marginal ecosystems. From both study sites, it could be seen that MVs are conined to more favourable ecosystems, and the number of landraces in marginal conditions is much lower, relecting the problem of adaptation of the majority of these varieties. Farmers in marginal ecosystems have limited choice of genetic materials at their disposal, which greatly reduces their capacity to manipulate the production systems in such environments. Discussion Concept of ecosystems and variety deployment Key informants in any given community can provide very reliable information on ecosystems for rice. Similarly, farmers can provide detailed features of each ecosystem in terms of soil type, irrigation and drainage, fertility status, ease of cultivation, production potential, cropping patterns, relative coverage of area under different ecosystems and so forth. Based on analysis of the characteristics of different ecosystems across sites, and the distribution of landraces and MVs within and between ecosystems, an attempt has been made to develop a generalized model for rice ecosystems (Figure 1). In the following subsections, the characteristic features of the ecosystems are explained. Finally, we look at the implications of the exercise for conservation, variety deployment and monitoring of diversity on-farm. Number and size of ecosystems The number of ecosystems varies from place to place as conditions differ between sites. Ecosystem size also varies, with more extreme ecosystems being relatively smaller than more favourable ones, and, depending upon the geographical location (high-potential production systems versus marginal growing environments), the size of each ecosystem will vary. For instance, in marginal environments for rice, the extreme 62 Plant Genetic Resources Newsletter, 2007, No. 152 Conceptual model of rice ecosystems L1E1 L2E1 L3E1 Ecosystem 1 Transitional Zone 1 Many farmers Large area Many farmers Small area Few farmers Large area Few farmers Small area Ecosystem 2 Competition Transitional Zone 2 L1E3 L3E3 L2E3 Ecosystem 3 Transitional Zone3 L1E4 L2E4 Ecosystem 4 Figure 1. Generalized (conceptual) model of rice ecosystems and varietal deployment. Note: Two-way arrow indicates transitional zone; Competition between varieties; L = Landrace; E = Ecosystem. ecosystems will be relatively larger than other ecosystems, whereas in favourable environments the productive ecosystems will be relatively larger. Landrace and MV distribution across ecosystems Understanding the distribution of landraces and MVs across ecosystems, the features of those ecosystems, and the particular traits of varieties are fundamental to appreciating the complexity of farmers’ strategies to manage plant genetic resources to meet their multiple needs. The analysis clearly indicates that one landrace or MV is ‘best suited’ or most competitive in only one ecosystem, though farmers might grow the same variety in more than one ecosystem. This implies that a variety competes with other varieties from within the ecosystem, and that there is less competition between varieties across ecosystems, except when there is an overlap of varieties. This implies need for situationspeciic participatory crop improvement programmes. Overlap signiies the presence of transitional zones between ecosystems, which explains the presence of landraces and MVs in two different but adjacent ecosystems. Within ecosystems, farmers’ socio-economic status, market forces, cultural factors, preference for speciic traits, and abiotic and biotic factors explain the area and number of households growing the different landraces and MVs. Depending on the area coverage and number of households growing the variety, it could fall in any of four categories: many households + large area; many households + small area; few households + large area; and few households + small area. Although landraces and MVs may overlap in adjacent ecosystems, no case was found where a landrace or MV was found in more than two ecosystems. This suggests that varieties have speciic adaptations. It also reinforces the idea that a variety is most competitive in only one ecosystem. The indings suggest that competition for space between varieties primarily occurs within the ecosystem, and there is a lot of competition in favourable ecosystems compared with marginal ecosystems, owing to the presence of more varieties in the former. This shows that the landraces grown in marginal areas are less prone to genetic erosion than are those grown under favourable conditions. Favourable market prices or inherent quality traits in certain varieties may attract farmers to grow these varieties beyond their ‘best-it’ ecosystems, but such cases would be few. Agromorphological characterization work by Bajracharya (2003) on rice landraces collected from the study sites revealed that principal component analysis (PCA) outputs grouped Plant Genetic Resources Newsletter, 2007, No. 152 landraces according to ecosystems for Begnas and Kachorwa ecosites. Varieties falling within the same ecosystem are more likely to be similar in their genetic composition than are varieties from dissimilar ecosystems, as landraces have been conditioned over time by their continued cultivation and selection in speciic ecosystems. Thus, they have developed adaptive traits that are unique to landraces of that ecosystem. Farmers’ knowledge on rice ecosystems and variety deployment Field exercises at both the study sites have shown that farmers have intricate knowledge and understanding of rice ecosystems. They employ multiple criteria to classify and characterize the ecosystems, with the most prominent criteria being the availability of moisture in the soil and fertility status of soil. Catalan and Perez (2000) reported a similar inding while analysing the conservation and utilization of biodiversity in Mapuche communities in Chile. A high degree of similarity between farmers’ and scientists’ classiication of rice ecosystems (Khush 1984) suggests that there exist commonalities in farmers’ knowledge and scientiic knowledge, which gives more reason to better understand and appreciate each knowledge system for synergistic effect. Farmers use different varieties to manage ecological diversity present on their farm. Kieft (2001) reported that rice farmers in Timor use speciic varieties for speciic locations, and the decision on which variety to plant is very much based on the forecasts for the next rainy season. The process of allocating different varieties to different ecosystems affects the genetic diversity of farmers’ repertoire of varieties maintained on-farm (Cleveland and Soleri 2002). Analysis of varietal allocation across different ecosystems indicates that diversity of varieties is directly associated with diversity in ecosystems because of the speciicity of most varieties. The absence of a speciic ecosystem in a locality results in absence of varieties associated with that ecosystem. The inding also implies that changes in speciic land use systems and practices might threaten the survival of some landraces as the landrace best suited to such ecosystems can be eroded due to lack of benign environment. This has been shown statistically signiicant in multiple regression models, with the number of varieties maintained on-farm directly corresponding to diversity in rice ecosystems (Rana 2004). Implications The distribution of varieties in different ecosystems is the result of farmers’ experimentation with those varieties over the years. In other words, based on farmers’ judgement, the varieties are the ‘best it’ under the farmers’ particular management conditions. Therefore, in order to make any intervention in the present system, researchers deinitely need to know the characteristics of each ecosystem, as well as the speciic traits of landraces and MVs in each ecosystem and their distribution across ecosystems. 63 On-farm conservation Diversity analysis of varieties at aggregated community or landscape level ignores the inluence of ecosystems in determining the position of varieties in different ecosystems. The exercise also ignores the variety × ecosystems interaction and the speciicity of landraces to ecosystems. Thus, selecting landraces from an aggregated list of varieties based on weighted diversity might exclude certain strategically important landraces for conservation. Hence, there is a need for micro-level analysis of rice varietal distribution across ecosystems in order to target better conservation of speciic landraces per se that might harbour genes of important traits in certain ecosystems. Another means to conserve useful genes in landraces would be through a Participatory Plant Breeding (PPB) approach, where landraces are crossed with MVs and offspring selected by farmers in the target environment (Sthapit et al. 2002). Understanding the features of ecosystems and the distribution of landraces within them will facilitate decision-making about selecting landraces for conservation. Failing to do so could result in selecting landraces with similar genetic traits for conservation (via PPB) from limited ecosystems. This would lead to the neglect of some and overrepresentation of others in conservation efforts. Diversity deployment Diversity deployment means providing farmers with options of genetic material to choose from. The introduction of new genetic material results in temporal disequilibrium because of competition between existing and new material for space in farmers’ ields, for farm labour, for capital inputs, and so forth. As time elapses, the new entrant inds its rightful place in the given environment. This is the outcome of farmers constantly trying to maintain equilibrium while meeting their multiple objectives over time. Hence, the strategy for diversity deployment ought to begin by analysing the distribution of varieties across ecosystems. Once this is done, researchers would have a clear picture of each ecosystem, along with the distribution of landraces and MVs, and the dominance of certain varieties against others and associated reasons for dominance. In the absence of this information, any diversity deployment strategy would be precarious, and new genetic material might not it into ecosystems where it is intended to expand farmers’ choice of varieties. It could also happen that new genetic materials might compete with each other in similar ecosystems, resulting in limited impact of diversity deployment. An equally important aspect of diversity deployment is the repatriation of promising landraces, thereby increasing the chances of survival of these landraces on-farm. For repatriation of landraces to succeed, a thorough understanding needs to be established of speciic ecosystems where they could it well and compete with others. Monitoring varietal diversity on-farm In order to make decisions on conservation of landraces onfarm (or ex situ in genebanks) and diversity deployment at 64 Plant Genetic Resources Newsletter, 2007, No. 152 different scales, information on the varietal landscape over time is needed to observe the trends of varietal dynamics at ecosystem level. Monitoring varietal diversity on-farm is important because of its dynamic nature, with introduction of new genetic material and discarding material that no longer meets farmers’ changing needs. Therefore, monitoring of introduction and replacement of varieties at ecosystem level gives a better indication of where the introduced variety is going to it in, and which varieties are likely to be replaced in the process. Conclusion Delineation of rice ecosystems can be reliably done using focus group discussion with knowledgeable farmers from the given community. The ecosystems identiied and the associated varieties in each ecosystem have to be veriied through transect walks. Deployment of varieties in each ecosystem is the outcome of intimate understanding of ecosystem characteristics and varietal performance, and the interaction between the two, which represent the ‘best it’ under farmers’ given circumstances. Because of the speciicity of varieties to ecosystems, aggregated information at community or landscape level may not be very useful for making decisions pertaining to landrace conservation on-farm, diversity deployment or repatriation programmes. Ecosystem characterization and varietal deployment would contribute signiicantly in making conservation decisions, as well as to monitor varietal dynamics over time. For wider utility, the technique needs testing in diverse settings for different crops. Acknowledgement Authors are highly indebted to farmers of Begnas and Kachorwa for sharing their insights on rice ecosystems and varietal distribution across ecosystems. This work is an output of a PhD Study under the IPGRI [now Bioversity International] Global Project: Strengthening Scientiic Basis of In-situ Conservation of Agrobiodiversity On-farm: Nepal Country Component funded by the Netherlands Ministry of Foreign Affairs Development Cooperation DGIS (Activity number: ww104801), and IDRC and SDC. References Bajracharya J. 2003. Genetic diversity study in landraces of rice (Oryza sativa L.) by agro-morphological characters and microsatellite DNA markers. PhD Thesis, School of Agriculture and Forest Sciences, University of Wales, Bangor, UK. Bellon MR, Pham JL, Jackson MT. 1997. Genetic conservation: a role for rice farmers. In: N Maxted, BV Ford-Lloyd and J Hawkes (editors). Plant conservation: the in situ approach. Chapman and Hall, London, UK. Brush SB. 2000. 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