NWPC-2023

Forest resource assessment is essential requirement for sustainable management of the forests and its biodiversity as enshrined in the National Forest Policy, encompassing the ecological, economic and social dimensions. This understanding drives the information needs for the planning and accordingly surveys are planned to generate desired information with desired level of accuracy and/or precision. Working plan is one such important tool which helps in evaluating he status of forest resources, assessing the impacts of past management practices and deciding bout suitable management interventions for the future. This unit provides methodology for assessments of forest resources, dependence of communities on forests & TOF along with data collection formats, processing techniques. n the present changing scenario of forest resources management at the global level with regard to biodiversity, climate change and carbon emission/sequestration, it is necessary to have assessment, estimation and monitoring of forest resources on the basis of sound statistically robust sampling design Sample design:Forest Inventory is mostly a sampling-based exercise. The purpose of sampling s to select a representative sample which represents characteristics of the population, so that precise inference could be drawn. Determination of sample size is one of the most important steps in constructing a sampling design. A systematic sampling design is recommended as the sampling scheme for forest resource assessment (FAO, 2002). The systematic sampling design which is being proposed for forest areas is a grid-based design and is preferred in areas having natural vegetation to ensure: • Spatial balance in the design. • Sufficient distance between two consecutive sampling plots to capture variability. In technical terms, the systematic sampling is more precise than Simple Random Sampling (SRS) & Stratified Random Sampling with proportional allocation when sampling in natural vegetation areas. But it is marginally less precise than stratified random sampling with optimum allocation. Further, the post-stratification techniques can be used for estimation of parameters, in this design, if required. For area sampling situation, sampling intensity is not very relevant but just indicative (NWPC, 2014). Therefore, the optimum sample size i.e. optimum number of plots to be included in the sample which may provide the estimate of population parameter within prescribed limit of error is more important. Determination of optimum sample size is a crucial decision in any sample survey design. The size of sample depends on the variability of main characteristic in the population (say volume/ha), allowable error in the estimate, time and cost factors. Generally, time and cost is not considered in the calculation. It is the variability of the population parameter (characteristic/attribute) allowable error that decides the sample size. It may kindly be noted that a technical document on optimum same size "Variability in forests and optimum sample size for estimation of Growing Stock different districts of the country, a ready reckoner for working plan preparation or any other forest resource assessment exercise" has been published by FSI (Source: FSI Technical Information Series Volume 2, No. different districts 3. 2020). This document provides optimum sample size far of the country for conducting inventory to estimate growing stock. It gives district wise information on coefficient of variation (CV) and sampling intensity of growing stock at different allowable errors.