Abstract
Little is known about the biomass production and bioenergy potential of low-input high-diversity (LIHD) systems in temperate nonforest conservation areas. In order to assess the potential of the biomass for energetic or other purposes, accurate yield data from LIHD systems are needed. We quantified the biomass yield in a wide range of seminatural systems (grasslands, marshes, tall-herb vegetation, and heathlands). Our results show a considerable variation in annual biomass yield ranging between 0.69 and 6.49 tDM ha−1 year−1. In addition, we provide an accurate method to determine the standing stock of harvestable biomass in the field. We developed four predictive models: one multiple linear regression (MLR) model and three boosted regression tree (BRT) models: (i) a vegetation model with variables that are easy to measure in the field, (ii) a soil model with soil physical and chemical variables, and (iii) a vegsoil model with all available variables. Due to its ability to fit nonlinear response functions and threshold values, the boosted regression tree technique outperformed the classical multiple linear regression. The vegetation model is the preferred model because it combines a good predictive performance (R 2adj = 0.75 and R 2adjCV = 0.51) with a relatively simple application.
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Acknowledgments
We would like to thank Natuurpunt vzw and the Agency of Nature and Forestry (ANB) of the Flemish Government for the access to the nature reserves and Andreas Demey for the permission to sample his permanent plots. The comments and suggestions of the anonymous reviewers were greatly acknowledged. This research was funded by a Ph.D. grant of the Agency for Innovation by Science and Technology (IWT).
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Van Meerbeek, K., Van Beek, J., Bellings, L. et al. Quantification and Prediction of Biomass Yield of Temperate Low-Input High-Diversity Ecosystems. Bioenerg. Res. 7, 1120–1130 (2014). https://doi.org/10.1007/s12155-014-9444-6
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DOI: https://doi.org/10.1007/s12155-014-9444-6