What is it about?
To summarize and discuss main results about the estimation of diversity indices and profiles when tree species abundance is estimated by means of plots placed onto the surveyed area in accordance with the probabilistic schemes usually adopted in forest inventories
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Why is it important?
A number of international agreements and commitments emphasize the importance of appropriate monitoring protocols and assessments as prerequisites for sound conservation and management of the world’s forest ecosystems. Mandated periodic surveys, like forest inventories, provide a unique opportunity to identify and properly satisfy natural resource management information needs. Distinctively, there is an increasing need for detecting diversity by means of unambiguous diversity measures
Perspectives
Inference on tree species diversity is greatly affected by the sampling scheme adopted for performing the forest survey. We have emphasized how the Tesselated Stratified Sampling allocation of plots provides statistically sound estimators of indices and profiles. The resulting estimators are consistent, asymptotically normal, abd super-efficient; their variances can be conservatively estimated, and confidence intervals or bands with asymptotic coverage greater than the nominal level are possible. It should be noticed that inference on diversity is usually performed in literature under the assumption that individuals are selected from the community by means of simple random sampling with replacement. In our opinion, these works are of little utility for estimating diversity indices and profiles from forest surveys, because trees cannot be selected from forest stands like balls from an urn.
Piermaria Corona
CREA Research Centre for Forestry and Wood
Read the Original
This page is a summary of: Inference on diversity from forest inventories: a review, Biodiversity and Conservation, October 2015, Springer Science + Business Media,
DOI: 10.1007/s10531-015-1017-2.
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