Modelling understorey dynamics in temperate forests under global change-Challenges and perspectives

The understorey harbours a substantial part of vascular plant diversity in temperate forests and plays an important functional role, affecting ecosystem processes such as nutrient cycling and overstorey regeneration. Global change, however, is putting these understorey communities on trajectories of change, potentially altering and reducing their functioning in the future. Developing mitigation strategies to safeguard the diversity and functioning of temperate forests in the future is challenging and requires improved predictive capacity. Process-based models that predict understorey community composition over time, based on first principles of ecology, have the potential to guide mitigation endeavours but such approaches are rare. Here, we review fourteen understorey modelling approaches that have been proposed during the last three decades. We evaluate their inclusion of mechanisms that are required to predict the impact of global change on understorey communities. We conclude that none of the currently existing models fully accounts for all processes that we deem important based on empirical and experimental evidence. Based on this review, we contend new models are needed to project the complex impacts of global change on forest understoreys. Plant functional traits should be central to such future model developments, as they drive community assembly processes and provide valuable information on the functioning of the understorey. Given the important role of the overstorey, a coupling of understorey models to overstorey models will be essential to predict the impact of global change on understorey composition and structure, and how it will affect the functioning of temperate forests in the future.

Contributions of climate, leaf area index and leaf physiology to variation in gross primary production of six coniferous forests across Europe: a model-based analysis

Gross primary production (GPP) is the primary source of all carbon fluxes in the ecosystem. Understanding variation in this flux is vital to understanding variation in the carbon sink of forest ecosystems, and this would serve as input to forest production models. Using GPP derived from eddy-covariance (EC) measurements, it is now possible to determine the most important factor to scale GPP across sites. We use long-term EC measurements for six coniferous forest stands in Europe, for a total of 25 site-years, located on a gradient between southern France and northern Finland. Eddy-derived GPP varied threefold across the six sites, peak ecosystem leaf area index (LAI) (all-sided) varied from 4 to 22 m(2) m(-2) and mean annual temperature varied from -1 to 13 degrees C. A process-based model operating at a half-hourly time-step was parameterized with available information for each site, and explained 71-96% in variation between daily totals of GPP within site-years and 62% of annual total GPP across site-years. Using the parameterized model, we performed two simulation experiments: weather datasets were interchanged between sites, so that the model was used to predict GPP at some site using data from either a different year or a different site. The resulting bias in GPP prediction was related to several aggregated weather variables and was found to be closely related to the change in the effective temperature sum or mean annual temperature. High R(2)s resulted even when using weather datasets from unrelated sites, providing a cautionary note on the interpretation of R(2) in model comparisons. A second experiment interchanged stand-structure information between sites, and the resulting bias was strongly related to the difference in LAI, or the difference in integrated absorbed light. Across the six sites, variation in mean annual temperature had more effect on simulated GPP than the variation in LAI, but both were important determinants of GPP. A sensitivity analysis of leaf physiology parameters showed that the quantum yield was the most influential parameter on annual GPP, followed by a parameter controlling the seasonality of photosynthesis and photosynthetic capacity. Overall, the results are promising for the development of a parsimonious model of GPP.

Suitability of a combined stomatal conductance and photosynthesis model for calculation of leaf-level ozone fluxes

Currently, the most important source of uncertainty in stomatal ozone flux ( FO3) modelling is the stomatal conductance ( gst) factor. Hence FO3 model accuracy will strongly depend on the gst model being implemented. In this study the recently developed semi-empirical Gst model of Dewar was coupled to the widely known biochemical photosynthesis ( An) model of Farquhar. The Gst performance of this model combination was evaluated with a 4-month time series of beech ( Fagus sylvatica L.) measurements. The Gst model was hereto optimized in two steps to a 4-day and a 8-day period. A comparison between the modelled and measured gst to O(3) (gstO3) revealed a rather good overall performance (R(2)=0.77). Errors between the model combination and the measurements are thought to be largely caused by a moderate performance of the AN model, due to poor parameterization. Two 2-day periods with distinctly differing soil and meteorological conditions were chosen to give a picture of the daily gst performance. Although instant relative differences between modelled and measured gstO3 are sometimes high, the model combination is able to simulate the rough daily courses of gstO3 and hence FO3 reasonably well. Further improvement on full parameterization of the gst model and a well-parameterized An model to be linked to are needed to draw founded conclusions about its performance. Future efforts hereto are certainly justified since the model's mechanistic nature makes it a tool able to model gst variation in space and time, O(3) effects on gst, and effective FO3.

Modelling ozone effects on adult beech trees through simulation of defence, damage, and repair costs: Implementation of the CASIROZ ozone model in the ANAFORE forest model

Ozone affects adult trees significantly, but effects on stem growth are hard to prove and difficult to correlate with the primary sites of ozone damage at the leaf level. To simulate ozone effects in a mechanistic way, at a level relevant to forest stand growth, we developed a simple ozone damage and repair model (CASIROZ model) that can be implemented into mechanistic photosynthesis and growth models. The model needs to be parameterized with cuvette measurements on net photosynthesis and dark respiration. As the CASIROZ ozone sub-model calculates effects of the ozone flux, a reliable representation of stomatal conductance and therefore ozone uptake is necessary to allow implementation of the ozone sub-model. In this case study the ozone sub-model was used in the ANAFORE forest model to simulate gas exchange, growth, and allocation. A preliminary run for adult beech (FAGUS SYLVATICA) under different ozone regimes at the Kranzberg forest site (Germany) was performed. The results indicate that the model is able to represent the measured effects of ozone adequately, and to distinguish between immediate and cumulative ozone effects. The results further help to understand ozone effects by distinguishing defence from damage and repair. Finally, the model can be used to extrapolate from the short-term results of the field study to long-term effects on tree growth. The preliminary simulations for the Kranzberg beech site show that, although ozone effects on yearly growth are variable and therefore insignificant when measured in the field, they could become significant at longer timescales (above 5 years, 5 % reduction in growth). The model offers a possible explanation for the discrepancy between the significant effects on photosynthesis (10 to 30 % reductions simulated), and the minor effects on growth. This appears to be the result of the strong competition and slow growth of the Kranzberg forest, and the importance of stored carbon for the adult beech (by buffering effects on carbon gain). We finally conclude that inclusion of ozone effects into current forest growth and yield models can be an important improvement into their overall performance, especially when simulating younger and less dense forests.