Grasses are extremely cosmopolitan in distribution and comprise one of the largest biomes on Earth. They are important carbon stores, account for large amounts of terrestrial primary productivity, are home to much of the worlds mammalian diversity and contribute to the livelihoods of an estimated one fifth of the world population. Grasslands are culturally, economically and environmentally important and there is an increasing need to predict how these ecosystems are likely to respond to global anthropogenic change. In order to do so we must first understand how they are assembled, their structure and how they are maintained.
Read the EDITORS’ CHOICE article on which this post is based:
Jardine, EC, Thomas, GH, Forrestel, EJ, Lehmann, CER, Osborne, CP. (2020) The global distribution of grass functional traits within grassy biomes. Journal of Biogeography 47:553– 565. https://doi.org/10.1111/jbi.13764
Image (top): Sudanian tropical savanna with clumps of Andropogon gayannus courtesy of Marco Schmidt (Wikicommons)
(Left) Spinifex savanna in MacDonnell Ranges, Central Australia courtesy of Thomas Schoch. (Right) An example of short Steppe grassland between Morin and Erdenet, Mongolia, image courtesy of Jamie Ingram.
Trait based approaches to ecology make generalizations regardless of species identity, to predict individual plant responses to environmental variation which can scale up to explain the processes that are responsible for community assembly, ecosystem function and global vegetation dynamics. In this piece of work, we wanted to test whether predictions made by community ecological theory are more broadly applicable at larger scales, asking whether traits that explain performance at community scale have the same relationships to environment over global scales.
Studying the global relationships of traits with environment brings with it some challenges. Firstly, identifying which of the more than 11,000 species of grass we would sample and also finding data that document the distributions of these species across the globe. The precursor to this paper was a global map of the worlds grassy biomes which had been produced by a NESCENT working group. Using the descriptions and metadata from vegetation maps, colleagues had been able to identify different grassy vegetation types and the dominant grass species which characterise these for global grassy biomes. This map became the basis of the species sampling for this work.
We considered grasslands to include vegetation with an open canopy and continuous ground layer as shown in this photo taken near Grahamstown, South Africa.
The second problem was accessing plants from which to take trait measurements. Functional traits are usually measured from fresh material, however it was simply not within the scope of this project to collect fresh, wild material from all across the world. To overcome this problem, we developed methods for measuring functional traits from herbarium specimens. We were fortunate enough to be given access to the collection at the Royal Botanical Gardens, Kew. Here we found grasses that had been collected from all continents, spanning a global soil and climatic gradient and from all of the major and most minor grass phylogenetic clades. Herbaria document a staggering amount of the worlds flora and have long been important repositories for the study of taxonomy and geographic distributions. This work really exemplifies the importance of herbarium collections as a source of ecological and evolutionary information. Within the collection at Kew, we were able to sample around one quarter of the worlds globally dominant grass species and this was mostly constrained by time and not the collection.
Through this project we discovered weak relationships between commonly measured economic traits (specific leaf area, leaf tensile strength) and also size related traits with contemporary environment at global scales. We showed that evolutionary history explains more trait variation than contemporary climate and that large amounts of trait variation occurs at small scales (i.e. within rather than between vegetation types). This information is important for modellers interested in how ecosystems will respond to climate change.
Much of trait based ecology has to date focussed upon leaf economics, probably in part because these traits are quick and simple to measure. Our work indicates that some of the most commonly measured functional traits may not be able to improve our predictions of how species and ecosystems respond to global change. When relationships between economic traits and environment are not observed, this does not however mean that trait relationships do not exist; another axis of trait variation may be important in explaining contrasting species distributions. The findings of this study have prompted us to investigate other axes of trait variation beyond the leaf economic spectrum, including physiological and also underground traits and how these relate to environmental variation.
Written by: Emma Jardine
University of Sheffield.
Additional information: @emmacj23; https://grassissometimesgreenerblog.wordpress.com/author/grassissometimesgreener