A sink-limited growth model improves biomass estimation along boreal and alpine tree lines

Aim: Despite increasing evidence for plant growth often being limited by sink (meristem) activity rather than source (photosynthesis) activity, all currently available dynamic global vegetation models (DGVMs) simulate plant growth via source-limited processes. For a given climatic region, this may lead to an overestimation of carbon stock per unit surface area, particularly if a model fails to correctly predict forest cover. Our aim is to improve the Lund-Potsdam-Jena (LPJ) DGVM by replacing the source-limited (SoL) tree growth algorithm by a sink-limited (SiL) one. Location: Our analysis focuses on the cold tree line at high latitudes and altitudes. We study two altitudinal transects in the Swiss Alps and the northern tree line. Methods: We limit annual net primary productivity of the LPJ DGVM by an algorithm based on the annual sum of growing degree-days (GDD), assuming that maximum plant growth is reached asymptotically with increasing GDD. Results: Comparing simulation results with observational data, we show that the locations of both the northern and the alpine tree line are estimated more accurately when using a SiL algorithm than when using the commonly employed SoL algorithm. Also, simulated carbon stocks decrease in a more realistic manner towards the tree line when the SiL algorithm is used. This has far-reaching implications for estimating and projecting present and future carbon stocks in temperature-limited ecosystems. Main conclusions: In the range of 60-80°N over Europe and Asia, carbon stored in vegetation is estimated to be c. 50% higher in the LPJ standard version (LPJ-SoL) compared with LPJ-SiL, resulting in a global difference in estimated biomass of 25 Pg (c. 5% of the global terrestrial standing biomass). Similarly, the simulated elevation of the upper tree line in the European Alps differs by c. 400m between the two model versions, thus implying an additional overestimation of carbon stored in mountain forests around the world.