The purpose of this study is to identify key home garden species in order to address basic research questions aimed at understanding farmers' home gardens management practices. The study was conducted in two contrasting Hill and Tarai sites in Nepal with households (HHs) ranging from 355 to 634. Unlike larger production systems, home gardens harbour many species in small areas often with a few crop varieties and species that are not well represented in larger fields. Given the number of species and their small population sizes, species and genetic diversity are best studied by identifying representative key species characterizing the complex productive niches within farms. Although species diversity within community is large (172 -342), 24 key species were identified for the study. There is no fixed size of a home garden. The log of home garden size and species richness was positively correlated (r ¼ 0.42, P , 0.001). Species richness was significantly higher in vegetable followed by fodder, fruits and spices. This paper also explores the diversity in home gardens to identify the composition and characteristics of the key species and how they are managed, used and conserved. Most of the farmers save the seeds of these home garden species for their own use, but many also exchange and buy and sell seed in local weekly market. Farmers' practices for selecting seed vary according to the reproductive biology of the key home garden species. Home gardens provide the HH with fresh and diverse supply of nutritious food, which improves their self-sufficiency, while conserving diversity on-farm. Despite this, they are neglected in research and development by policy makers and researchers.

Social seed systems are important for the maintenance of crop genetic diversity on farm. This is governed by local and informal system in the community through a farmers’ network. This paper analyses these local seed systems through application of social network analysis tools and mappings and examines the network member and its stability over space and time in a small rice farming community in Nepal. NetDraw software is used for data analysis and network mapping. We found that the dynamic network structure had key role in provisioning of traditional varieties and maintaining of crop genetic diversity on farm. We identify and ascertain the key network members, constituted either as nodal or bridging (connector) farmers, occupying central position in the network who promote seed flow of local crop diversity, thus strengthening crop genetic resource diversity on farm.

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Crop genetic resources (CGRs) are crucial natural resource which ensure food or livelihood security of billions of people today as well as ensure future agricultural innovations. However, the CGR diversity remaining in in situ, particularly in subsistence farming is becoming extinct due to change in economic and technological development over time. An optimal funding strategy is required for conservation of these CGRs. In this paper, I have discussed an economic perspective on why and how the de facto crop genetic resources (CGRs) diversity declines with changing economic and environmental context. The model maximizes the net revenue from the farmers land allocation strategy to different CGRs under economic and technical constraints with linear demand and cost functions. Furthermore, the model suggests how to minimize the cost of on farm conservation of these crop genetic resources in situ (or ex situ) without forfeiting farmer's well-being in a changing perspective of economics and technology. The theoretical model developed in this study is employed to demonstrate the applicability for on farm conservation of rice genetic diversity in Nepal. The study suggests an optimal fund allocation strategy that minimizes the cost of conservation by (i) identifying particular CGRs (rice landraces) that are prone to extinct from the community and (ii) categorizing the farmers in the community having minimum cost of conservation for those particular landraces. As the model maximizes the farmers' revenues, it could ensure better livelihood of individuals in the community while minimizing the cost of in situ conservation of biodiversity on farm.

We analyze a continuous, nonlinear bioeconomic model to demonstrate how stochasticity in the growth of fish stocks affects the optimal exploitation policy when prices are stochastic, mean-reverting and possibly harvest dependent. Optimal exploitation has nonlinear responses to the price signal and should be conservative at low levels of biological stochasticity and aggressive at high levels. Price stochasticity induces conservative exploitation with little or no biological uncertainty, but has no strong effect when the biological uncertainty is larger. We further observe that resource exploitation should be conservative when the price reverts slowly to the mean. Simulations show that, in the long run, both the stock level and the exploitation rate are lower than in the deterministic solution. With a harvest-dependent price, the long-run price is higher in the stochastic system. The price mean reversion rate has no influence on the long-run solutions.