Evaluation of forest inventory processes in a forest under concession in the southwestern Brazilian Amazon

ABSTRACT Forest inventory procedures are of utmost importance to studies of wood volume stocks, and forest structure and diversity, which provide relevant information to public policies, management plans and ecological research. The present work focused on the performance of inventory techniques in the Amazon region to evaluate wood volume stocks with higher levels of accuracy while maintaining sampling intensity fixed. Two sampling processes were assessed: simple random sampling and two-stage cluster sampling. The processes were evaluated through the allocation of sampling units with different dimensions, and the effectiveness of the generated estimators was analyzed as a function of stand density and basal area. Simple random sampling resulted in the smallest errors, reaching 9% when all species were sampled together. The method depicted forest phytosociological parameters with greater sensitivity, whereas two-stage cluster sampling produced the least accurate estimators and presented slower responses to variation in phytosociological parameters.【摘要】森林清查规程对于林木蓄积量、森林结构与多样性研究至关重要，相关研究成果可为公共政策制定、经营规划及生态学研究提供关键支撑。本研究聚焦亚马逊地区的清查技术性能，旨在固定抽样强度的同时，以更高精度评估林木蓄积量。本次研究评估了两种抽样方法：简单随机抽样与两阶段整群抽样。通过设置不同尺度的抽样单元对两种方法开展评估，并基于林分密度与林分断面积，分析所得估计量的有效性。结果显示，简单随机抽样的误差最小，当对所有树种合并抽样时，其误差可达9%；该方法对森林植物社会学参数的响应灵敏度更高，而两阶段整群抽样所得估计量的精度最低，且对植物社会学参数变化的响应速度更为迟缓。