Jonathan Seaquist
Head of department
A rapid NPP meta-model for current and future climate and CO2 scenarios in Europe
Author
Summary, in English
Net primary production (NPP) is the difference in gross photosynthetic assimilation of carbon and carbon loss due to autotrophic respiration, and is an important ecosystem variable that facilitates understanding of climate change impacts on terrestrial ecosystem productivity and ecosystem services. The aim of this study is to rapidly estimate the NPP of European potential natural vegetation for current and future climate and carbon-dioxide scenarios (CO2).
A NPP meta-model was developed and evaluated based on the dynamic global vegetation model LPJ-GUESS. LPJ-GUESS was used to simulate NPP under current and future climate change as well as CO2 scenarios. The NPP dataset produced from these simulations was used to determine the empirical relationships between NPP and driving climate variables (maximum temperature, minimum temperature, summer precipitation, winter precipitation) along with CO2 concentration. The climate variables’ relationships were combined in a synergistic function including CO2 relationships to estimate NPP. The meta-model was compared with randomly chosen NPP data originated from LPJ-GUESS. Furthermore, the meta-model's performance was evaluated on the European level with LPJ-GUESS simulations.
The meta-model performed reasonably well with regard to estimating total NPP while performances for species-specific NPP were poor. For total NPP, the meta-model generated an agreement of R2 = 0.68 and RMSE = 0.06 at CO2 = 350 ppm in comparison to LPJ-GUESS simulations. The consideration of all CO2 concentration scenarios yielded R2 = 0.62 and RMSE = 0.08.
A rapid synergistic approach is suggested that enables interactions between climate variables and their intra-annual variability to estimate NPP. This is a useful alternative to traditional empirical models that control NPP with the most limiting climate variable. The meta-model performed reasonably well for estimating total NPP for future climate change and CO2 scenarios. However, species-specific NPP estimates were unsatisfactory, implying that the synergistic approach cannot account for species specific dynamics. Comparison between the meta-model and LPJ-GUESS at the European scale showed that additional environmental variables (e.g. solar radiation) would be necessary to improve the meta-model.
A NPP meta-model was developed and evaluated based on the dynamic global vegetation model LPJ-GUESS. LPJ-GUESS was used to simulate NPP under current and future climate change as well as CO2 scenarios. The NPP dataset produced from these simulations was used to determine the empirical relationships between NPP and driving climate variables (maximum temperature, minimum temperature, summer precipitation, winter precipitation) along with CO2 concentration. The climate variables’ relationships were combined in a synergistic function including CO2 relationships to estimate NPP. The meta-model was compared with randomly chosen NPP data originated from LPJ-GUESS. Furthermore, the meta-model's performance was evaluated on the European level with LPJ-GUESS simulations.
The meta-model performed reasonably well with regard to estimating total NPP while performances for species-specific NPP were poor. For total NPP, the meta-model generated an agreement of R2 = 0.68 and RMSE = 0.06 at CO2 = 350 ppm in comparison to LPJ-GUESS simulations. The consideration of all CO2 concentration scenarios yielded R2 = 0.62 and RMSE = 0.08.
A rapid synergistic approach is suggested that enables interactions between climate variables and their intra-annual variability to estimate NPP. This is a useful alternative to traditional empirical models that control NPP with the most limiting climate variable. The meta-model performed reasonably well for estimating total NPP for future climate change and CO2 scenarios. However, species-specific NPP estimates were unsatisfactory, implying that the synergistic approach cannot account for species specific dynamics. Comparison between the meta-model and LPJ-GUESS at the European scale showed that additional environmental variables (e.g. solar radiation) would be necessary to improve the meta-model.
Department/s
- Dept of Physical Geography and Ecosystem Science
- BECC: Biodiversity and Ecosystem services in a Changing Climate
Publishing year
2015
Language
English
Pages
29-41
Publication/Series
Ecological Modelling
Volume
302
Links
Document type
Journal article
Publisher
Elsevier
Topic
- Physical Geography
Keywords
- NPP
- ecosystem model
- meta-modeling
- LPJ-GUESS
- climate change
- potential natural vegetation in Europe
- Ecology
- Ecosystem Science
Status
Published
ISBN/ISSN/Other
- ISSN: 0304-3800