HETEROFOR 1.0: a spatially explicit model for exploring the response of structurally complex forests to uncertain future conditions – Part 2: 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 models operates at stand level, one now needs spatially explicit individual-based approaches in order to account for individual variability, local environment modification and tree adaptive behaviour in mixed and uneven-aged forests that are supposed to be more resilient under stressful conditions. The local environment of a tree is strongly influenced by the neighbouring trees, which modify the resource level through positive and negative interactions with the target tree. Among other things, drought stress and vegetation period length vary with tree size and crown position within the canopy. In this paper, we describe the phenology and water balance modules integrated in the tree growth model HETEROFOR (HETEROgenous FORest) and evaluate them on six heterogeneous sessile oak and European beech stands with different levels of mixing and development stages and installed on various soil types. 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. Two two-phase models differing regarding their response function to temperature during the chilling period (optimum and sigmoid functions) and a simplified one-phase model are used to predict budburst date. The two-phase model with the optimum function is the least biased (overestimation of 2.46 d), while the one-phase model best accounts for the interannual variability (Pearson's r=0.68). For the leaf development, yellowing and fall, predictions and observations 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 are well reproduced for all the study sites (Pearson's r was between 0.893 and 0.950, and bias was between −1.81 and −9.33 %). The model also reproduced well the individual transpiration for sessile oak and European beech, with similar performances at the tree and stand scale (Pearson's r of 0.84–0.85 for sessile oak and 0.88–0.89 for European beech). The good results of the model assessment will allow us to use it reliably in projection studies to evaluate the impact of climate change on tree growth in structurally complex stands and test various management strategies to improve forest resilience.

Contribution of deep soil layers to the transpiration of a temperate deciduous forest: quantification and implications for the modelling of productivity

“…However, SWHC values similar to, or even higher than our estimate of 390 mm have been published for temperate forests (e.g. 338 mm for the Hesse Beech forest in North-Eastern France, De La Motte et al, 2020, or 450 mm for a mixed Beech-Oak forest near Louvain-la-Neuve in Belgium, De Wergifosse et al, 2020). The value of 390 mm for SWHC was 1.9 times higher than the database estimate of 207 mm for the FR-Fon grid point (Badeau et al, 2010).…”

CO2 fertilization, transpiration deficit and vegetation period drive the response of mixed broadleaved forests to a changing climate in Wallonia

“…With our simulations, we were unable to distinguish between the transpiration deficit under constant and timedependent atmospheric CO 2 concentration since the water balance is calculated before photosynthesis in HETEROFOR and the stomatal conductance for water does not depend on atmospheric CO 2 concentration contrary to that for CO 2 (Dufrêne et al, 2005;Jonard et al 2020;de Wergifosse et al 2020a). Therefore, our transpiration simulations are more reliable for the constant atmospheric CO 2 modality.…”

“…In the same study, the simulated GPP was related to the NPP reconstructed from tree growth measurement and this relationship displayed high Pearson's correlation coefficients (0.89 and 0.91 for sessile oak and European beech, respectively). Regarding water balance evaluated in de Wergifosse et al (2020a), the model satisfactorily simulated the soil water content temporal dynamics (correlation coefficients between simulations and observations ranging from 0.83 to 0.95 according to the site) and the individual transpiration (0.85 and 0.89 for oak and beech, respectively). Finally, the budburst model previously described, a one-phase model based on the Uniforc model (Chuine 2000), which simulates the forcing period, has been chosen among two other budburst models (two-phase models accounting for the forcing and chilling periods) implemented in HETEROFOR as it reproduced best the interannual variability.…”

“…Hereafter, we present a brief overview of the model functioning limited to the description of the options retained for the simulation experiments carried out in this study. For a more in-depth description, we refer the reader to Jonard et al (2020) andde Wergifosse et al (2020a).…”

“…In this study, we will address the question of how and to what extent changing climate and CO 2 conditions will impact forest productivity in six contrasting and structurally complex stands in Wallonia and assess how the site components and thinning operations modulate the response. To do so, we will use HETEROFOR (Jonard et al 2020;de Wergifosse et al 2020a), a process-based tree growth model running at the individual level with different climate projections based on three GHG emission scenarios.…”