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  Evaluating the productivity of four main tree species in Germany under climate change with static reduced models

Gutsch, M., Lasch-Born, P., Suckow, F., Reyer, C. P. O. (2016): Evaluating the productivity of four main tree species in Germany under climate change with static reduced models. - Annals of Forest Science, 73, 2, 401-410.
https://doi.org/10.1007/s13595-015-0532-3

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Gutsch, Martin1, Autor              
Lasch-Born, Petra1, Autor              
Suckow, Felicitas1, Autor              
Reyer, Christopher P. O.1, Autor              
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: Key message We present simple models of forest net primary production (NPP) in Germany that show increasing productivity, especially in mountainous areas, under warming unless water becomes a limiting factor. They can be used for spatially explicit, rapid climate impact assessment. Context Climate impact studies largely rely on process-based forest models generally requiring detailed input data which are not everywhere available. Aims This study aims to derive simple models with low data requirements which allow calculation of NPP and analysis of climate impacts using many climate scenarios at a large amount of sites. Methods We fitted regression functions to the output of simulation experiments conducted with the process-based forest model 4C at 2342 climate stations in Germany for four main tree species on four different soil types and two time periods, 1951–2006 and 2031–2060. Results The regression functions showed a reasonable fit to measured NPP datasets. Temperature increase of up to 3 K leads to positive effects on NPP. In water-limited regions, this positive effect is dependent on the length of drought periods. The highest NPP increase occurs in mountainous regions. Conclusion Rapid analyses, using reduced models as presented here, can complement more detailed analyses with process-based models. Especially for dry sites, we recommend further study of climate impacts with process-based models or detailed measurements.

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 Datum: 2016
 Publikationsstatus: Final veröffentlicht
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 Ort, Verlag, Ausgabe: -
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 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1007/s13595-015-0532-3
PIKDOMAIN: Climate Impacts & Vulnerabilities - Research Domain II
eDoc: 6987
Research topic keyword: Climate impacts
Research topic keyword: Ecosystems
Model / method: 4C
Regional keyword: Germany
Organisational keyword: RD2 - Climate Resilience
Working Group: Forest and Ecosystem Resilience
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Titel: Annals of Forest Science
Genre der Quelle: Zeitschrift, SCI, Scopus, p3
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Seiten: - Band / Heft: 73 (2) Artikelnummer: - Start- / Endseite: 401 - 410 Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/151216
Publisher: Springer