Rainfall variability, plant functional traits and productivity in grasslands

Abstract

Grasslands are important ecosystems worldwide, and their diversity and productivity is strongly linked to rainfall patterns and soil nutrient availability. Changes in water and soil nutrients, associated with climate change and management regimes, are likely to have strong consequences for grasslands in the future. While the relationship between rainfall, nutrients, and grassland productivity has been well described, a mechanistic explanation as to why some grassland communities are more sensitive than others remains elusive. Plant functional traits are useful to address this issue on a global scale, as they represent life history strategies and are universal across all plant taxa. Such traits often represent the inevitable trade-off between rapidly acquiring resources and the increasing rate of tissue turnover. Such faster-growing species, referred to as acquisitive species, can be compared with conservative species, which are slower growing and have low rates of tissue turnover, along the resource-use axis. To address how grasslands may respond to future changes in rainfall and fertilisation, I conducted a series of experiments using grasses and grassland ecosystems to study how traits may be used to understand variation in sensitivity across species and communities. My research illustrates that the abundance of acquisitive and conservative plant species in a community can result in high levels of variation in productivity, a primary function of grasslands critical for pasture utilisation and carbon sequestration. I found that root traits of grasses were responsive to phosphorus fertilisation. As the primary organ for water uptake in plants, changes in root morphology associated with P availability may alter how grassland communities respond to changes in precipitation. In addition, I found grouping species based on their functional types was helpful in quantifying plant biomass in remote arid and semi-arid regions, where logistics of scientific investigation can be difficult. More specifically, I developed a set of allometric equations which use non-destructive proxies (plant cover and height) to estimate plant biomass. These estimates were improved by grouping species based on the functional type (i.e. rough morphological and life-history characteristics). Finally, I investigated how interspecific plant interactions (namely competition) may change under different timing and severity of droughts to identify key candidate grasses for multispecies pasture utilisation. Ultimately, this work contributes valuable information regarding the underlying mechanisms to varying sensitivity in productivity in grassland communities and individual grass species, which will be increasingly important to manage under future climatic scenarios.

Date of Award	2019
Original language	English