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Supporting conservation planning in a national biodiversity hotspot – Projecting species composition across a groundwater level gradient using a demographic forest model

Author

Listed:
  • Elles, Lucian
  • Boyce, Jack
  • Henkel, Stefanie
  • Kasperidus, Hans D.
  • Scholz, Mathias
  • Schorn, Markus E.
  • Vieweg, Michael
  • Wirth, Christian
  • Rüger, Nadja

Abstract

The Leipzig floodplain forest is a biodiversity hotspot of national significance. However, it is an urban forest heavily impacted by human activities, including the alteration of the hydrological regime preventing floods and leading to a lower groundwater level. In parts of the Leipzig Floodplain Forest, the restoration of a near-natural hydrological regime with regular floods and a raise of the groundwater level is considered. However, it is unclear whether raising the groundwater level in particular would ensure the long-term conservation of typical floodplain tree species such as European ash (Fraxinus excelsior) and pedunculate oak (Quercus robur), which are considered key species for biodiversity conservation. To investigate this question, we quantified the relationships between groundwater table distance and the growth, mortality, and recruitment rates for eight common tree species in the Leipzig Floodplain Forest using forest inventory data from 60 plots and a spatial groundwater model. Based on these relationships, we simulated the long-term dynamics of species composition with and without a raise of the groundwater table using the Perfect Plasticity Approximation (PPA) forest model.

Suggested Citation

  • Elles, Lucian & Boyce, Jack & Henkel, Stefanie & Kasperidus, Hans D. & Scholz, Mathias & Schorn, Markus E. & Vieweg, Michael & Wirth, Christian & Rüger, Nadja, 2025. "Supporting conservation planning in a national biodiversity hotspot – Projecting species composition across a groundwater level gradient using a demographic forest model," Ecological Modelling, Elsevier, vol. 501(C).
  • Handle: RePEc:eee:ecomod:v:501:y:2025:i:c:s0304380024003843
    DOI: 10.1016/j.ecolmodel.2024.110996
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