HETEROFOR 1.0: a spatially explicit model for exploring the response of structurally complex forests to uncertain future conditions. II. Phenology and water cycle

Abstract

Abstract. Climate change affects forest growth in numerous and sometimes opposite ways and the resulting trend is often difficult to predict for a given site. Integrating and structuring the knowledge gained from the monitoring and experimental studies into process-based models is an interesting approach to predict the response of forest ecosystems to climate change. While the first generation of such models operates at stand level, we need now individual-based and spatially-explicit approaches in order to account for structurally complex stands whose importance is increasingly recognized in the changing environment context. Among the climate-sensitive drivers of forest growth, phenology and water availability are often cited as crucial elements. They influence, for example, the length of the vegetation period during which photosynthesis takes place and the stomata opening, which determines the photosynthesis rate. In this paper, we describe the phenology and water balance modules integrated in the tree growth model HETEROFOR and evaluate them on six Belgian sites. More precisely, we assess the ability of the model to reproduce key phenological processes (budburst, leaf development, yellowing and fall) as well as water fluxes. Three variants are used to predict budburst (Uniforc, Unichill and Sequential), which differ regarding the inclusion of chilling and/or forcing periods and the calculation of the coldness or heat accumulation. Among the three, the Sequential approach is the least biased (overestimation of 2.46 days) while Uniforc (chilling not considered) best accounts for the interannual variability (Pearson’s R = 0.68). For the leaf development, yellowing and fall, predictions and observation are in accordance. Regarding the water balance module, the predicted throughfall is also in close agreement with the measurements (Pearson’s R = 0.856, bias = −1.3 %) and the soil water dynamics across the year is well-reproduced for all the study sites (Pearson’s R comprised between 0.893 and 0.950, and bias between −1.81 and −9.33 %). The positive results from the model assessment will allow us to use it reliably in projection studies to evaluate the impact of climate change on tree growth and test how diverse forestry practices can adapt forests to these changes.

Simulating tree growth response to climate change in structurally diverse oak and beech forests

“…For the simulations, we used the spatially explicit, individual-and process-based model HETEROFOR that has been implemented in the CAPSIS simulator (Dufour-Kowalski et al, 2012) and is especially convenient for simulating the impact of climate change on structurally complex stands. In the following, we present a brief overview of the model functioning while we refer to Jonard et al (2020) and de Wergifosse et al (2020a) for a more in-depth description.…”

“…In the model version 1.0 (see Jonard et al, 2020;de Wergifosse et al, 2020a), water balance was calculated before photosynthesis, and the stomatal conductance for water did not depend on atmospheric CO 2 concentration. In the model version used here, the two processes were more closely coupled and the stomatal conductance was calculated in the same way for water and CO 2 using the formulation of Ball et al (1987) adapted to the tree level by accounting for the influence of tree height (Schäfer et al, 2000).…”

“…Only the optimum response function during chilling (Eq. (1) in de Wergifosse et al, 2020aWergifosse et al, , 2020b was different and had to be adapted to correspond to that given in Duputié et al (2015) (itself based on Wang and Engel, 1998). Leaf yellowing and fall parameters were empirically fitted with the observations provided for 13 of the study sites located in Belgium, Germany, France and Romania.…”

“…The HETEROFOR model has been specifically designed to simulate individual tree growth in structurally complex stands based on a resource-sharing approach and to test the ability of innovative silvicultural systems to improve forest resilience to climate change (de Wergifosse et al, 2020a;Jonard et al, 2020). So far, it has been calibrated and used to simulate the impact of climate change on a couple of forests in Southern Belgium (de Wergifosse et al, 2020b).…”