Skip to Main Content
Development of a stand-scale forest biodiversity index based on the state forest inventoryAuthor(s): Diego Van Den Meersschaut; Kris Vandekerkhove
Source: In: Hansen, Mark; Burk, Tom, eds. Integrated tools for natural resources inventories in the 21st century. Gen. Tech. Rep. NC-212. St. Paul, MN: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station. 340-350.
Publication Series: General Technical Report (GTR)
Station: North Central Research Station
PDF: Download Publication (667.07 KB)
DescriptionEcological aspects are increasingly influencing silvicultural management. Estimating forest biodiversity has become one often major tools for evaluating management strategies. A stand-scale forest biodiversity index is developed, based on available data from the state forest inventory. The index combines aspects of forest structure, woody and herbal layer composition, and deadwood, as biodiversity indicators. The index is calculated by means of a score system following a standard procedure. It reflects the variability of forests in Flanders in a logical way and is sensitive enough to indicate changes for monitoring purposes.
- Check the Northern Research Station web site to request a printed copy of this publication.
- Our on-line publications are scanned and captured using Adobe Acrobat.
- During the capture process some typographical errors may occur.
- Please contact Sharon Hobrla, email@example.com if you notice any errors which make this publication unusable.
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationVan Den Meersschaut, Diego; Vandekerkhove, Kris. 2000. Development of a stand-scale forest biodiversity index based on the state forest inventory. In: Hansen, Mark; Burk, Tom, eds. Integrated tools for natural resources inventories in the 21st century. Gen. Tech. Rep. NC-212. St. Paul, MN: U.S. Dept. of Agriculture, Forest Service, North Central Forest Experiment Station. 340-350.
- Chapter 11: Assessing Wildlife Habitat from a Large-Scale Forest Inventory
- Statistical inference for forest structural diversity indices using airborne laser scanning data and the k-Nearest Neighbors technique
- Analyzing lichen indicator data in the Forest Inventory and Analysis Program
XML: View XML