Going beyond limitations of plant functional types when predicting global ecosystem–atmosphere fluxes: exploring the merits of traits‐based approaches

Abstract

Aim Despite their importance for predicting fluxes to and from terrestrial ecosystems, dynamic global vegetation models have insufficient realism because of their use of plant functional types (PFTs) with constant attributes. Based on recent advances in community ecology, we explore the merits of a traits-based vegetation model to deal with current shortcomings. Location Global.Methods A research review of current concepts and information, providing a new perspective, supported by quantitative analysis of a global traits database.Results Continuous and process-based trait-environment relations are central to a traits-based approach and allow us to directly calculate fluxes based on functional characteristics. By quantifying community assembly concepts, it is possible to predict trait values from environmental drivers, although these relations are still imperfect. Through the quantification of these relations, effects of adaptation and species replacement upon environmental changes are implicitly accounted for. Such functional links also allow direct calculation of fluxes, including those related to feedbacks through the nitrogen and water cycle. Finally, a traits-based model allows the prediction of new trait combinations and no-analogue ecosystem functions projected to arise in the near future, which is not feasible in current vegetation models. A separate calculation of ecosystem fluxes and PFT occurrences in traitsbased models allows for flexible vegetation classifications.Main conclusions Given the advantages described above, we argue that traitsbased modelling deserves consideration (although it will not be easy) if one is to aim for better climate projections.

Earth System Model Needs for Including the Interactive Representation of Nitrogen Deposition and Drought Effects on Forested Ecosystems

“…Using plant traits to capture whole-plant hydraulics has even been suggested to improve C and water use responses to drought [143]. The benefit of trait-based modeling is that the environment acts as a filter for trait composition, analogous to evolutional selection processes [140], and is not limited by climate and geography. This is particularly important considering that McNeil et al [144] found that species' foliar N responses to N deposition were dependent on two main plant traits, leaf mass area and shade tolerance.…”

“…The current PFT approach to modeling vegetation is limited to feedback that results from changes in species distribution since most models assume that attributes within a PFT do not change with climate [140]. To capture the adaptation and evolution of vegetation, the concept of trait-based modeling was introduced by Lavorel and Garnier [141].…”

Does predictability of fluxes vary between FLUXNET sites?

“…It is perhaps more likely that the widely used approach of analysing FLUXNET sites grouped by a small number of discrete plant functional types is too simplistic, as opposed to exploring differences at a species level, or relating differences to a spectrum of plant traits, plant life spans and metabolism (Kattge et al, 2011;Reich et al, 1997;Wright et al, 2004). Despite widely acknowledged issues with this PFT approach (Alton, 2011;Pavlick et al, 2013;Van Bodegom et al, 2012), this analysis framework is still used, partly declines). When they categorised their analysis on a PFT level, differences between sites and species were no longer distinct.…”

The effect of using the plant functional type paradigm on a data-constrained global phenology model

“…However, there are a number of disadvantages to using the PFT approach, mainly due to the fact that a PFT-type categorisation imposes fixed parameter values and cannot capture the continuous variation observed in plant traits within and among PFTs (see review by Van Bodegom et al, 2012). Capturing such heterogeneity not only may improve the prediction of biogeochemical and physical dynamics in Earth system models but also may improve predictions of other longer-term vegetation processes such as shifts in vegetation composition to climate change.…”