Time-lagged response of siberian treeline forests revealed by individual-based modelling

Global warming allows arctic vegetation, which is mainly limited by temperatures, to move north. A change from tundra to taiga will cause a decrease of albedo which further fuels the warming through positive feedback mechanisms. This raises several questions of which we want to address here: (1) Wil...

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Bibliographic Details
Main Authors: Kruse, Stefan, Wieczorek, Mareike, Jeltsch, Florian, Herzschuh, Ulrike
Format: Conference Object
Language:unknown
Published: 2016
Subjects:
Online Access:https://epic.awi.de/id/eprint/41619/
https://epic.awi.de/id/eprint/41619/1/ICOP2016_Kruse_TimeLaggedResponse_IBM_LAVESI.pdf
https://hdl.handle.net/10013/epic.48494
https://hdl.handle.net/10013/epic.48494.d001
Description
Summary:Global warming allows arctic vegetation, which is mainly limited by temperatures, to move north. A change from tundra to taiga will cause a decrease of albedo which further fuels the warming through positive feedback mechanisms. This raises several questions of which we want to address here: (1) Will trees move northwards and thereby change vast treeless tundra areas to taiga? (2) And if so, how long does this response lags behind the temperature changes? To answer these questions we built an individual-based and spatially-explicit vegetation simulator model for larches in Siberia (LAVESI). We present the parameterization and validation of the model's incorporated processes which describe the full life-cycle of the simulated larch species Larix gmelinii. Furthermore, we share results of the first regional-scale simulations testing the model's performance at the Taymyr Peninsula, Russia, ranging from 64-80° N and 92-120° E. In a second experiment, we tested the influence of up to 6 °C warmer and cooler climates on simulated populations. Our results show that already the recent temperature rise will allow forests to expand farther north by roughly one degree, when no seed limitation hinders populations to migrate. Furthermore, climate warming caused populations to densify but with a time-lag of decades. We conclude that in the near future expanding taiga after its first establishment in the former tundra will rapidly form dense tree stands, thus ultimatively fueling the feedback loop of global warming. We show that simulation results of the newly-build vegetation model were reliable, and hence the model can be used as a tool to improve our knowledge about individual-based processes that are important to understand past and future treeline migration.