Can Plant Traits Predict Ecosystem Properties?

By Vicky Temperton, Jörn Fischer and Marina Frietsch

Ecosystems around the world are subjected to changes driven by both natural dynamics and human activities. The functional traits of individual organisms shape their growth and reproduction and are thus key to understanding their response to global change. In addition, traits do not only affect individual performance but may also drive various ecosystem properties – from biomass production to pollination – and the services these properties provide to human well-being. Hence, functional ecology scholars seek to understand patterns of individual traits and ecosystem properties. In a recent study, van der Plas et al. (2020) test the general hypothesis that plant traits per se can be sufficient for predicting levels of ecosystem properties within and across years. 

Restored calcareous grassland (Valkenburg, NL) with many species from different plant functional groups (legumes, grasses, forbs) that together contribute many different traits to the whole system. The species that dominate the grassland change each year, and this is affected by the weather interacting with growth, acquisition and reproductive traits, as well as interactions with the overall plant-soil-microbe continuum in the soil.

The scientific community is divided regarding the role plant traits play as drivers of ecosystem properties: while some scholars primarily emphasize traits as key drivers, others highlight the simultaneous importance of environmental conditions, including for example topography and disturbances, in addition to traits as direct drivers of ecosystem processes. The former understanding is widely embraced in ecological studies. To test this assumption, van der Plas et al. (2020) explore the general capacity of plant trait data to predict levels of ecosystem properties. To this end, they conducted a literature review of general trait studies and also analysed a vast trait dataset from the Jena Experiment, one of the world’s longest running and largest Biodiversity-Ecosystem-Functioning (BEF) experiments located in the state of Thuringia, Germany. This set of field experiments has the overall goal of elucidating the underlying ecological and evolutionary mechanisms of positive biodiversity effects. It has a gradient of different herbaceous plant diversity treatments ranging from 1 to 16 and 60 (total species pool) species richness and all possible combinations of 1 to 4 different plant functional groups (grasses, small forbs, large forbs, legumes). The trait analysis was based on the diversity and composition of 78 plant communities which were collected over 10 years in this grassland BEF field experiment.

The literature review of 100 recent studies focused on which and how many traits were measured when attempting to link traits within plant communities to ecosystem properties. The findings illustrate clear trends in the literature: most studies analysed six traits, and only two studies assessed more than 15. Moreover, traits describing above-ground plant parts and leaf characteristics are most frequently measured. The field experiment was used to investigate to what extent a much higher number of traits could explain variation in ecosystem properties. Here, van der Plas et al. (2020) found that plant traits per se explained a very low proportion of variance in ecosystem properties. More importantly, the proportion of variance explained by the unprecedented number of traits measured was rather moderate (32.6%) within years and much lower between years (12.7 %). When only focusing on six traits commonly measured in most other studies these numbers reduced to 4.8% of variance explained by traits between years, and only 12.2 % overall in significant predictors among ecosystem properties. In other words, plant traits explain a certain proportion of ecosystem functions within years, but between years this value drops significantly. This highlights that there is a limit to extent to which traits per se can predict long term functioning (and hence perhaps also ecosystem services).

The relative importance of different and multiple traits regarding ecosystem properties across years. a = Number of analysed properties significantly driven by each trait. Traits analysed in >10% of the reviewed papers are shown in yellow. b = Number of significant predictors in final models for each ecosystem property. c = Marginal R2 values in final models for each ecosystem property. (Figure from van der Plas et al. 2020, p.3).

There is another fascinating story in this paper however, as any grassland ecologist can tell you, the species that dominate in a grassland differ from year to year, and as such the traits that contribute to ecosystem functions do too. It seems that the van der Plas et al. (2020) study is picking up on this phenomenon and underscoring an early Jena Experiment study (Allan et al. 2011) that found that dominant species drive ecosystem properties but the species that dominate change each year. This highlights how strong dynamics in species turnover between years make such systems very resilient against extreme weather events, as the community, if species-rich enough, can filter out different winners and losers in each year. Recent meta-analyses of biodiversity metrics in many different ecosystems confirm that turnover is a metric we need to focus on as much as species richness or functional richness. Grassland ecosystems will be different to forest ecosystems in this regard, however as species can change their dominance much more easily than trees or understory vegetation dominated by clonal and geophyte species can.

A restored calcareous species-rich grassland in Valkenburg, Netherlands. Such habitats form some of the most species-rich habitats on the planet, at small scales. The world record for plant diversity at small scales was recorded in Transylvania, Romania (Wilson et al 2012), in grasslands that have been extensively managed for millennia.

The authors propose five explanations for their finding that plant traits are rather poorly linked to ecosystem properties. First, they point out that variation in plant community composition and levels of ecosystem properties may even exist within plots. Hence, spatial mismatches between within-plot locations of ecosystem property measurements and vegetation surveys could have weakened links between traits and ecosystem properties. Second, they argue that traits can vary substantially among individuals within species. Third, the authors suggest that important traits may simply be overlooked when trying to understand drivers of ecosystem properties. Next, they reason that links between traits and levels of ecosystem properties may be stronger across ecosystems, for example when comparing grasslands with forests. Finally, van der Plas et al. (2020) reflect on the importance of environmental contexts for the understanding of how traits drive ecosystem properties. This last explanation is closely linked to the finding that links between traits and ecosystem properties were much stronger within years than across years as well as with the phenomenon that dominant species change each year: depending on contextual environmental factors such as weather or disturbance for example, species with specific traits can become more abundant and thus strongly influence ecosystem properties in one year. The next year, however, might be accompanied by completely different weather or disturbance patterns, hence favoring other plant species tied to different ecosystem properties. 

Species-rich meadow in northern Luxembourg in 2018, restored for beekeeping. The adjacent crop was quiet whereas the soundscape over the meadow was entirely different, full of the sound of insects.

The comprehensive study by van der Plas et al. (2020) shows that while traits can be strongly linked to ecosystem properties within years, the capacity to predict levels of multiple ecosystem properties across years is strongly limited. The authors thus conclude that additional data, such as information on abiotic conditions such as soil factors or climate and their interactions with plant traits should be considered to improve links with ecosystem properties. When context dependencies of links between plant traits and ecosystem properties are ignored, van der Plas et al. (2020) argue that ecosystem-level consequences of ongoing biodiversity change are difficult to predict. However, ecosystem properties underpin ecosystem services and are thus central to human well-being. As global change affects ecosystem functioning it is thus key to gain a thorough understanding of drivers of ecosystem properties. 

To learn about the findings of van der Plas et al. (2020) in more detail take a look at the original paper.

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