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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F20%3A84391" target="_blank" >RIV/60460709:41320/20:84391 - isvavai.cz</a>

Výsledek na webu

<a href="https://onlinelibrary.wiley.com/doi/10.1111/gcb.15011" target="_blank" >https://onlinelibrary.wiley.com/doi/10.1111/gcb.15011</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1111/gcb.15011" target="_blank" >10.1111/gcb.15011</a>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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 spec

Název v anglickém jazyce

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

Popis výsledku anglicky

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 spec

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

40102 - Forestry

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

GLOBAL CHANGE BIOLOGY

ISSN

1354-1013

e-ISSN

—

Svazek periodika

26

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

14

Strana od-do

1-14

Kód UT WoS článku

000513927400001

EID výsledku v databázi Scopus

2-s2.0-85079726198