This paper aimed to reveal differences in growth response to climatic condition between sugi (Cryptomeria japonica) and hinoki (Chamaecyparis obtusa) by comparing parameters of a carbon balance based growth model. Seven carbon balance-based growth model parameters related to the rate of photosynthesis, temperature and humidity controls were parameterized by a Bayesian calibration using growth data derived from permanent plots. A hierarchical Bayes model was applied to this parameterization, where the common parameter was estimated frst and the species-specific parameters were derived from the common parameter thereafter. Simulated light-response curves using estimated parameters were similar and the photosynthetic rate of sugi was higher than that of hinoki. The patterns of response to temperature represented by estimated parameters were different between sugi and hinoki; sugi responded rapidly to changes in temperature while hinoki responded relatively slowly,resulting in a higher tolerance to low temperature than sugi. Estimated parameters indicated that the photosynthetic rate controlling function for humidity could not be implemented for either species in the model. The parameterization of a carbon balance-based growth model revealed differences in the potential photosynthetic ability and response to temperature of sugi and hinoki. However, we could not represent the control effect of humidity on the photosynthetic rate.
We propose an alternative approach for optimal forest stand aggregation for implementing harvest scheduling, which allows for multiple harvests using a compact formulated integer programming that seeks an optimal aggregated pattern among candidates for forest management units over the planning horizon. We deal with aggregation of small forest stands by introducing the concept of a "hyper unit" as a possible aggregated management unit, which is predefined with the use of adjacency relationship among the set of forest stands. Our proposed approach is based on an optimization framework of a traditional spatially constrained harvest scheduling problem which is used to choose the best set of treatments for the aggregated management units, as well as the original un-aggregated forest stands, while allowing for multiple harvests. We also apply adjacency constraints to create aggregated management units, which are separated from other units, as well as un-aggregated forest stands such that, no adjacent units are harvested in the same period.
In the growth analysis, when the research focus is environmental factor, the longitudinal growth part is essential but not our main interest. In such a situation, by regarding age dependent growth behavior as baseline, we can reconstruct the models to include a nuisance baseline. Such an approach makes it possible only to estimate parameters of interest (environmental factors) without information about the nuisance baseline. After estimating the main parameters, we can graph the baseline trend, non-parametrically. In this paper, the growth model was generated using data on Sugi (Cryptomeria Japonica) at Hoshino village in Japan. The results from this study showed an inverse relationship between altitude and tree growth, without modeling for longitudinal growth, i.e., higher altitude resulted in less tree growth. In practice the results can be explained by our knowledge based on two established facts. The first is based on the direction of water and nutrients flow from a higher elevation and accumulates at a lower elevation, and the second can be explained by the fact that trees are suppressed by strong winds at higher elevations. By using this data, we compared our model with traditionally used parametric growth models which are constructed without nuisance baseline. In statistical terms, both the variance of residual and the standard error for parameters in the proposed model were found to be the smallest among the other parametric alternatives. This implies that the estimate is stable in our model that is one of the advantage for statistical inference aspect.
The paper empirically examines the household-level importance of various income sources and the factors associated with the non-farm work participation of community forest user households in rural Nepal. Data for the study was collected using structured survey of 275 randomly selected households. The income data are presented in absolute and relative terms by different household categories. Determinants of non-farm work participation is tested using probit regression model. Results show that non-farm income constitute an average of 55.5% of the total household income. Non-farm income such as remittances (migration from work abroad) and pensions constitute the most important source of income for all categories of household. Larger sized non-dalits households, which hold relatively larger value of implements and smaller land area show significant association with non-farm work participation. The varying share of the non-farm income to the total household income resulting by the combination of household’s individual and socio-economic characteristics are discussed.The study suggests that typical policies such as improvement in human capital , e.g. improved literacy and skills, and rural infrastructures will remain important for promoting and making the poor benefit from the income opportunities through various non-farm sectors.