Biodiversity and its assessment in boreal and nemoral forests

Citation
Sg. Nilsson et al., Biodiversity and its assessment in boreal and nemoral forests, SC J FOR R, 2001, pp. 10-26
Citations number
187
Categorie Soggetti
Plant Sciences
Journal title
SCANDINAVIAN JOURNAL OF FOREST RESEARCH
ISSN journal
02827581 → ACNP
Year of publication
2001
Supplement
3
Pages
10 - 26
Database
ISI
SICI code
0282-7581(2001):<10:BAIAIB>2.0.ZU;2-T
Abstract
We review species richness in major organism groups, mainly using examples from northern Europe. A high proportion of these species is forest living, and large numbers are dependent on decaying wood. Biodiversity can be asses sed at various scales using two different principles. One is to use feature s. such as ancient and dead trees, known to be important for a large number of species. The other method is to choose species or groups of species kno wn to indicate high biodiversity or presence of many red-listed species. We argue that any serious biodiversity assessment method should include the m ost species rich organism groups, for example insects. In the present paper we point out the most important features for high biodiversity (old trees and large dead trees), and review the quantities of these features in near- virgin forests. The natural disturbance regime of a region should be the ba sis for defining a suitable scale and the appropriate features for biodiver sity assessment. Possible indicator species for high biodiversity in northe rn Europe are suggested. based on previous investigations. Among epiphytic lichens and wood-living beetles there are many potentially useful species i n addition to vascular plants in the nemoral forest. Among vertebrates, woo dpeckers and grouses seem to be the most useful. Validation tests for indic ator structures and species are largely lacking but urgently needed. The im plications of possible delayed local extinctions tire important to bear in mind when managing for sustainable forestry. The knowledge of forest histor y is useful when developing cost-efficient measures.