For many decades, non-timber forest products (NTFPs) have been an important livelihood commodity in Nepal as a traditional source of food, fiber, and medicines. However, the importance of NTFPs have been recognized only recently. NTFPs form more than 5% of Nepal’s national gross domestic product and are facing threat due to anthropogenic drivers and changing climate. Understanding of the current distribution and future dynamics of NTFPs is essential for effective conservation planning and management. In the maiden attempt, we used the Maxent model to understand the current and predict the future distribution by 2050 of 10 major NTFPs in Chitwan Annapurna Landscape, Nepal. The prediction accuracy of the models calculated based on the area under curve was high (>90%) and the prediction by 2050 highlights potential increase in distribution range of seven NTFPs and potential decrease in that of three NTFPs in the study area. The results from our study could play an important role in planning and management of these NTFPs considering their high economic and ecological significance and sensitivity to predicted climate change.

Volume and taper equations are used for estimating timber volume and biomass of a tree. Despite their usefulness, precise and site specific equations are still lacking for commercially important tree species in Nepal. The study was carried out at Chandak Chatiya Mahila Community Forest in Bardia district and Lumbini Collaborative Forest of Saljhandi in Rupandehi district in western Terai of Nepal. A destructive sampling method was used and selected fifteen Sal trees (Shorea robusta Gaertn. f.) from Saljhandi (site 1) and eighteen trees from Bagnaha (site 2) randomly to calibrate an individual tree volume and a stem taper function. At first, a non-linear stem taper function was calibrated using stem diameters outside bark at different heights above ground as response variable and D (diameter at breast height), H (total height), h (height of interest) as predictors. Then, effect of crown characteristics on stem taper was evaluated. As stem HCB (height to crown base) was found to affect stem taper, its usefulness in existing stem volume equation was tested. Empirical relationships between V (stem volume) as a response variable and D, H, HCB and sites in Bardia and Rupandehi districts as predictors were established using a linear mixed modeling approach. Our result showed that, instead of H, use of HCB in stem volume equation increased model prediction accuracy and reduced prediction bias. Applicability of the suggested models for predicting individual S. robusta tree volume and stem taper is discussed.

Abstract

In Nepal, there is currently no volume function for economically valuable tree species like Shorea robusta Gaertn. prepared based on destructive sampling for stem and branches. Existing functions rely on solely diameter and height, despite research indicating the importance of crown dimensions for stem taper. The objective of this study was to collate harmonized data from destructive sampled S. robusta trees from far-west to east Nepal, spanning about 500 km and to prepare new stem and branch volume functions. For every tree (n = 219) diameter at breast height (DBH) and tree height (H) was measured. Thereof 188 trees had measurements of crown length (CL). For a subsample (n = 100) volume of branches (>10 cm diameter) were measured too. We fitted functions for stem and branch volume using regression mixed models with DBH, slenderness and crown ratio as covariates/predictors. We hypothesized that crown ratio is needed for accurate stem and branch volume predictions. Our results indicate that DBH and slenderness were the most important variables for predicting stem volume (marginal coefficient of determination R2 0.948), whereas the inclusion of crown ratio did not increase the explained variance. Crown ratio significantly increased explained variance in branch volume functions, suggesting that crown dimensions are needed to obtain accurate branch volume predictions (marginal R2 0.766). Estimating volume with only DBH, e.g. if more detailed H and CL measurements are missing, resulted in more precise estimates for stem (marginal R2 0.908) and fair estimates for branch volume (marginal R2 0.554). Our mixed model approach revealed that there were only small differences in volume from the different sampling sites and a similar accuracy can be assumed when applying the presented functions in other part of the country. Additionally, we demonstrated that log-transformation and currently used volume functions lead to biased volume estimates, in particular for large-sized trees. This study helps to provide reliable growing stock estimates of S. robusta (and in combination with density the carbon content) and considers the effects of wider spacing and longer crowns on stem taper and allocation patterns.