Reconstruction of past landscape openness using the Landscape Reconstruction Algorithm (LRA) applied on three local pollen sites in a southern Swedish biodiversity hotspot

摘要

The Hornso-Allgunnen area in south-eastern Sweden has been known as a biodiversity hotspot for insects for about a century and is considered to host the most species-rich insect fauna in northern Europe. Several hypotheses for the causes behind this biodiversity have been put forward, but never tested for more than small parts of the area. We analyse here the possible role of the area's vegetation-cover history, in particular vegetation openness. We use pollen data from three sites in the Hornso-Allgunnen area and apply the recently developed Landscape Reconstruction Algorithm (LRA) for quantitative reconstruction of past vegetation abundance at the local spatial scale. The study suggests that the area was dominated by diverse, relatively open forest during at least the last 3,000 years. Several tree taxa, such as Pinus, Betula and Quercus that were all suggested to be important for the present diversity, have a long continuity at the local spatial scale and were common until recently. Small proportions of anthropogenic pollen indicators were found, suggesting small-scale agriculture, which however did not considerably affect the area's overall tree species composition. We propose that fire was the main cause for the open character of the area's wooded landscape during the Holocene and, indirectly, an important agent behind the high insect diversity. However, the richness of insects was (and is) most likely also favoured by the long continuity of Quercus, and by the warm and dry local climate. The LRA provides a more realistic estimate of the taxa composition as compared to pollen percentages alone, both for arboreal and non-arboreal taxa. The differences between pollen percentages and LRA-estimates of plant abundance can be important to consider when causes behind high modern diversity are interpreted from fossil pollen records. Our results demonstrate the benefits of using the LRA along with traditional pollen percentages.