Preprints
https://doi.org/10.5194/bg-2023-55
https://doi.org/10.5194/bg-2023-55
12 Apr 2023
 | 12 Apr 2023
Status: this preprint is currently under review for the journal BG.

Connecting CSR theory and LPJmL 5.3 to assess the role of environmental conditions, management and functional diversity for grassland ecosystem functions

Stephen Björn Wirth, Arne Poyda, Friedhelm Taube, Britta Tietjen, Christoph Müller, Kirsten Thonicke, Anja Linstädter, Kai Behn, and Susanne Rolinski

Abstract. Forage supply and soil organic carbon storage are two important ecosystem functions of permanent grasslands, which are determined by climatic conditions, management and functional diversity. However, functional diversity is not independent of climate and management, and it is important to understand the role of functional diversity and these dependencies for ecosystem functions of permanent grasslands. Especially since functional diversity may play a key role in mediating impacts of changing conditions. Large-scale ecosystem models are used to assess ecosystem functions within a consistent framework for multiple climate and management scenarios. However, large-scale models of permanent grasslands rarely consider functional diversity. We implemented a representation of functional diversity based on the CSR theory and the global spectrum of plant form and function into the LPJmL dynamic global vegetation model forming LPJmL-CSR. Using a Bayesian calibration method, we parameterised new plant functional types and used these to assess forage supply, soil organic carbon storage and community composition of three permanent grassland sites. These are a temperate grassland, a hot and a cold steppe for which we simulated several management scenarios with different defoliation intensities and resource limitations. LPJmL-CSR captured the grassland dynamics well under observed conditions and showed improved results for forage supply and/or SOC compared to LPJmL 5.3 at three grassland sites. Furthermore, LPJmL-CSR was able to reproduce the trade-offs associated with the global spectrum of plant form and function and similar strategies emerged independent of the site specific conditions (e.g. the C- and R-PFTs were more resource exploitative than S-PFTs). Under different resource limitations, we observed a shift of the community composition. At the hot steppe for example, irrigation led to a more balanced community composition with similar C-, S- and R-PFT shares of above-ground biomass. Our results show, that LPJmL-CSR allows for explicit analysis of the adaptation of grassland vegetation to changing conditions while explicitly considering functional diversity. The implemented mechanisms and trade-offs are universally applicable paving the way for large-scale application. Applying LPJmL-CSR for different climate change and functional diversity scenarios may generate a range of future grassland productivity.

Stephen Björn Wirth et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2023-55', Anonymous Referee #1, 10 May 2023
  • RC2: 'Comment on bg-2023-55', Anonymous Referee #2, 19 May 2023

Stephen Björn Wirth et al.

Data sets

Code and data for Wirth et al., in discussion: Connecting CSR theory and LPJmL 5.3 to assess the role of environmental conditions, management and functional diversity for grassland ecosystem function Stephen Björn Wirth, Christoph Müller, and Susanne Rolinski https://zenodo.org/record/7727990

Stephen Björn Wirth et al.

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Short summary
In large scale projections of dynamic global vegetation models (DGVMs), the role of functional diversity for forage supply and soil organic carbon storage of grasslands is not explicitly taken into account. We introduced functional diversity into the LPJmL DGVM using CSR theory. The new model reproduced well known trade-offs between plant traits and can be used to quantify the role of functional diversity for climate change mitigation using different functional diversity scenarios.
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