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Forest carbon allocation modelling under climate change

Merganičová, Katarína; Merganič, Ján; Lehtonen, Aleksi; Vacchiano, Giorgio; Sever, Maša Zorana Ostrogović; Augustynczik, Andrey L D; Grote, Rüdiger; Kyselová, Ina; Mäkelä, Annikki; Yousefpour, Rasoul; Krejza, Jan; Collalti, Alessio; Reyer, Christopher P O

Abstract (englisch):
Carbon allocation plays a key role in ecosystem dynamics and plant adaptation to changing environmental conditions. Hence, proper description of this process in dynamic vegetation models is crucial for the simulations of the impact of climate change on carbon cycling in forests. Here we review how carbon allocation modelling is implemented in 31 dynamic vegetation models to identify the main gaps compared to our theoretical and empirical understanding of carbon allocation. We found that a hybrid approach based on combining several principles and/or types of carbon allocation modelling prevailed in examined models. The analysis revealed that although the number of carbon allocation studies over the last 10 years has substantially increased, some background processes are still insufficiently understood, and some issues in models are frequently oversimplified or even omitted. Hence, current challenges for carbon allocation modelling in forest ecosystems are (i) to overcome remaining limits in process understanding, particularly regarding the impact of disturbances on carbon allocation, accumulation and utilisation of non-structural carbohydrates, and carbon use by symbionts, and (ii) to implement existing knowledge to mechanistic description of carbon allocation in models that would integrate the impact of environmental conditions, disturbances, and seasonal variation in carbon allocation, or (iii) to improve more simplistic models by accounting for the impact of crucial factors affecting carbon allocation in particular environment.

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Verlagsausgabe §
DOI: 10.5445/IR/1000105781
Veröffentlicht am 12.02.2020
Originalveröffentlichung
DOI: 10.1093/treephys/tpz105
Scopus
Zitationen: 2
Coverbild
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU)
Publikationstyp Zeitschriftenaufsatz
Jahr 2019
Sprache Englisch
Identifikator ISSN: 1758-4469
KITopen-ID: 1000105781
Erschienen in Tree physiology
Band 39
Heft 12
Seiten 1937–1960
Vorab online veröffentlicht am 21.11.2019
Nachgewiesen in Scopus
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