Systematic adaptive cluster sampling for the assessment of rare tree species in Nepal

B. Acharya, G. Bhattarai, A. de Gier, A. Stein

Research output: Contribution to journalArticleAcademicpeer-review

47 Citations (Scopus)

Abstract

Sampling to assess rare tree species poses methodic problems, because they may cluster and many plots with no such trees are to be expected. We used systematic adaptive cluster sampling (SACS) to sample three rare tree species in a forest area of about 40 ha in Nepal. We checked its applicability and efficiency and compared it to conventional systematic sampling. Comparison of SACS to conventional systematic sampling showed that efficiency for density estimation increased 500␏or the clustered Schima wallichii, but reduced 40␏or the unclustered Daphniphyllum himalayense. The method was found to be more efficient for larger groups of individuals of a rare species than for extremely small groups. SACS may also be used to establish relationships with spatially referenced variables, but data availability was a constraint. SACS is a promising design for resource managers and survey specialists dealing with rare and endangered species in the context of biodiversity and sustainable forest management.
Original languageEnglish
Pages (from-to)65-73
JournalForest Ecology and Management
Volume137
DOIs
Publication statusPublished - 2000

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