Indicators for plant species richness in pine (Pinus sylvestris L.) forests of Germany

Chapter
Part of the Topics in Biodiversity and Conservation book series (TOBC, volume 7)

Abstract

Forestry is obliged to record as well as maintain and/or enhance biological diversity in forests due to national and international agreements. Accordingly, it is necessary to work out methodological approaches for the assessment of biodiversity in forests. In the study presented here, we focus on the total plant species pool (563 vascular plant and bryophyte species) of pine (Pinus sylvestris L.) forests in NE Germany to identify indicators for plant species richness. We distinguished several groups like “herb”, “grass-like”, “woody”, “endangered”, and “exotic species”, for which we detected indicators for low (class #1), intermediate (class #2), and high (class #3) species numbers. From a total of 84 species, which were identified by a three-step procedure, most indicators were found for class #3. Only few indicators have been revealed for intermediate species numbers, i.e. class #2. With help of Ellenberg’s ecological indicator values and information on the main occurrence in Central European vegetation types and plant communities, respectively, we characterized the indicator species ecologically. The ecological site preferences of the indicator species in general reflect the fact that species richness is highest in base-rich, light, and anthropogenically disturbed pine forests. On the contrary, species-poor forests were revealed by indicators, which mainly occur on acidic sites. It is concluded that a considerable set of indicators for species richness can help facilitate biodiversity assessments in forestry and ecosystem restoration practice.

Keywords

Biodiversity assessment Biodiversity indicators Bryophytes Endangered species Exotic species Species numbers Vascular plants 

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Copyright information

© Springer Science+Business Media B.V. 2007

Authors and Affiliations

  1. 1.Institute of Geobotany and Landscape EcologyUniversity GreifswaldGreifswaldGermany
  2. 2.Albrecht-von-Haller-Institute for Plant SciencesUniversity of GöttingenGöttingenGermany
  3. 3.Statistics and Mathematical Economics GroupTechnical University of BerlinBerlinGermany

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