Trotsiuk, Volodymyr and Hartig, Florian and Cailleret, Maxime and Babst, Flurin and Forrester, David I. and Baltensweiler, Andri and Buchmann, Nina and Bugmann, Harald and Gessler, Arthur and Gharun, Mana and Minunno, Francesco and Rigling, Andreas and Rohner, Brigitte and Stillhard, Jonas and Thurig, Esther and Waldner, Peter and Ferretti, Marco and Eugster, Werner and Schaub, Marcus (2020) Assessing the response of forest productivity to climate extremes in Switzerland using model-data fusion. GLOBAL CHANGE BIOLOGY, 26 (4). pp. 2463-2476. ISSN 1354-1013, 1365-2486
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The response of forest productivity to climate extremes strongly depends on ambient environmental and site conditions. To better understand these relationships at a regional scale, we used nearly 800 observation years from 271 permanent long-term forest monitoring plots across Switzerland, obtained between 1980 and 2017. We assimilated these data into the 3-PG forest ecosystem model using Bayesian inference, reducing the bias of model predictions from 14% to 5% for forest stem carbon stocks and from 45% to 9% for stem carbon stock changes. We then estimated the productivity of forests dominated by Picea abies and Fagus sylvatica for the period of 1960-2018, and tested for productivity shifts in response to climate along elevational gradient and in extreme years. Simulated net primary productivity (NPP) decreased with elevation (2.86 +/- 0.006 Mg C ha(-1) year(-1) km(-1) for P. abies and 0.93 +/- 0.010 Mg C ha(-1) year(-1) km(-1) for F. sylvatica). During warm-dry extremes, simulated NPP for both species increased at higher and decreased at lower elevations, with reductions in NPP of more than 25% for up to 21% of the potential species distribution range in Switzerland. Reduced plant water availability had a stronger effect on NPP than temperature during warm-dry extremes. Importantly, cold-dry extremes had negative impacts on regional forest NPP comparable to warm-dry extremes. Overall, our calibrated model suggests that the response of forest productivity to climate extremes is more complex than simple shift toward higher elevation. Such robust estimates of NPP are key for increasing our understanding of forests ecosystems carbon dynamics under climate extremes.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | NET PRIMARY PRODUCTION; GROSS PRIMARY PRODUCTIVITY; MULTIPLE DATA STREAMS; DATA ASSIMILATION; CARBON-CYCLE; BAYESIAN CALIBRATION; SPECIES INTERACTIONS; TEMPORAL DYNAMICS; CONSTANT FRACTION; PINUS-SYLVESTRIS; Bayesian inference; carbon cycling; data assimilation; drought; ecosystem productivity; extreme events; Fagus sylvatica; inverse modeling; model calibration; Picea abies |
| Subjects: | 500 Science > 580 Botanical sciences |
| Divisions: | Biology, Preclinical Medicine > Institut für Pflanzenwissenschaften > Group Theoretical Ecology (Prof. Dr. Florian Hartig) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 30 Mar 2021 08:27 |
| Last Modified: | 30 Mar 2021 08:27 |
| URI: | https://pred.uni-regensburg.de/id/eprint/45102 |
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