Assessing the response of forest productivity to climate extremes in Switzerland using model-data fusion

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Trotsiuk , V , Hartig , F , Cailleret , M , Babst , F , Forrester , D I , Baltensweiler , A , Buchmann , N , Bugmann , H , Gessler , A , Gharun , M , Minunno , F , Rigling , A , Rohner , B , Stillhard , J , Thurig , E , Waldner , P , Ferretti , M , Eugster , W & Schaub , M 2020 , ' Assessing the response of forest productivity to climate extremes in Switzerland using model-data fusion ' , Global Change Biology , vol. 26 , no. 4 , pp. 2463-2476 . https://doi.org/10.1111/gcb.15011

Title: Assessing the response of forest productivity to climate extremes in Switzerland using model-data fusion
Author: Trotsiuk, Volodymyr; Hartig, Florian; Cailleret, Maxime; Babst, Flurin; Forrester, David I.; Baltensweiler, Andri; Buchmann, Nina; Bugmann, Harald; Gessler, Arthur; Gharun, Mana; Minunno, Francesco; Rigling, Andreas; Rohner, Brigitte; Stillhard, Jonas; Thurig, Esther; Waldner, Peter; Ferretti, Marco; Eugster, Werner; Schaub, Marcus
Contributor: University of Helsinki, Department of Forest Sciences
Date: 2020-04
Language: eng
Number of pages: 14
Belongs to series: Global Change Biology
ISSN: 1354-1013
URI: http://hdl.handle.net/10138/325012
Abstract: 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.
Subject: Bayesian inference
carbon cycling
data assimilation
drought
ecosystem productivity
extreme events
Fagus sylvatica
inverse modeling
model calibration
Picea abies
NET PRIMARY PRODUCTION
GROSS PRIMARY PRODUCTIVITY
MULTIPLE DATA STREAMS
DATA ASSIMILATION
CARBON-CYCLE
BAYESIAN CALIBRATION
SPECIES INTERACTIONS
TEMPORAL DYNAMICS
CONSTANT FRACTION
PINUS-SYLVESTRIS
1171 Geosciences
1172 Environmental sciences
1181 Ecology, evolutionary biology
4112 Forestry
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