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Mapping the next forest generation – the potential of national forest inventory data for identifying regeneration gaps
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Abstract
In light of global change and forest disturbances, there is an increasing recognition of the importance of forest regeneration to ensure future generations of trees. However, despite the importance of forest regeneration, there is a lack in spatial information on the current availability of trees in the seedling and sapling stage. In this study, we aimed to evaluate the potential to predict species-specific forest regeneration densities using regeneration data typically recorded within National Forest Inventories (NFIs). We then calculated three indicators for regeneration quantity and quality to locate potential gaps of regeneration under a changing climate. We successfully calibrated regeneration density models for 22 tree species using generalised additive models (GAMs) using regeneration density data from the 2012 German NFI and 44 environmental predictors. Subsequently, the models were used to create regeneration density maps for the German forest area at high spatial resolution (1 ha). Regeneration gaps were evaluated in terms of low total density (less than 1,000 ha-1), low species richness (≤2 species) and a high proportion (≥75%) of regeneration at high future cultivation risk. Our results indicate gaps in terms of total regeneration density and species richness for 13.4% and 47.1% of the forest area of Germany, respectively. A lack of climate-adapted species was found for 25.2%, exemplarily assessed for the Bavarian forest area. Along this example, we show how such results can be used to identify areas that require additional silvicultural intervention in order to increase the resilience of future forests. Our study highlights the potential of NFI data, particularly that on forest regeneration, and demonstrates the applicability of regeneration indicator maps for forest management and policymakers in times of change.
DOI
https://doi.org/10.32942/X2GS8X
Subjects
Forest Biology, Forest Management, Forest Sciences, Other Forestry and Forest Sciences, Plant Sciences
Keywords
forest regeneration, species distribution models SDMs, generalized additive models GAMs, sapling density, species richness, climate-adapted species, cultivation risk
Dates
Published: 2025-05-31 06:33
Last Updated: 2025-05-31 06:33
License
CC-BY Attribution-NonCommercial 4.0 International
Additional Metadata
Conflict of interest statement:
None
Data and Code Availability Statement:
Code is fully available at https://github.com/LeonieCG/GermanRegenerationMaps2012 and https://doi.org/10.5281/zenodo.15552196. Secondary data is fully and primary data partly available at https://doi.org/10.5281/zenodo.15550864, latter is only partly available due to restrictions in passing data to third parties.
Language:
English
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