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  Investigating effects of environmental stressors on ecosystem function using hyperspectral leaf reflectance

   Faculty of Engineering, Computing and the Environment

   Applications accepted all year round  Self-Funded PhD Students Only

About the Project

There is an increasing urgency to understand the biochemical and physiological responses of plants to global environmental change. This is because environmental stressors––climate and land-use change, environmental pollution (e.g., nitrogen deposition) experience in the vicinity of urban areas––directly influence species’ survival, growth and reproduction, which in turn determine community structure and function, as well as ecosystem processes. In effect, environmental stressors drive permanent, long-term changes in ecosystems. Equally important, plant functional traits can be altered as plants adapt (acclimate) to environmental constraints, and therefore, variation in plant responses and tolerances to environmental stressors can be captured by directly measuring fluctuation in the most relevant functional traits. However, retrieving rapid, reliable, and repeatable measurement of key plant traits indicative of plant stress has proven challenging. It is within this framework that we will investigate climate-driven environmental stressors using hyperspectral (HS) leaf reflectance to better understand plant responses to drivers of environmental change.

The project will focus on observations collected near urban and peri-urban landscapes, where ecosystems are continuously exposed to multiple environmental stressors, including climatic abnormalities (e.g., high sunlight radiation, extreme temperatures, highly variable water inputs) and high levels of ozone and other air pollutants (Tausz et al. 2007, Bussotti 2008, Paoletti et al. 2010, Sharma et al. 2012). These environmental conditions can induce plant oxidative stress because of increased production of reactive oxygen in plant cells. Plants exhibit species-specific tolerances against such oxidative injury, which is modulated by their efficiency at mobilizing antioxidant defences (i.e., balancing pro-oxidant and antioxidant levels). Recent studies have established that both Non-enzymatic (e.g., carotenoids, ascorbic acid and glutathione) and enzymatic substances (e.g., superoxide dismutase, catalase, ascorbate peroxidase and glutathione reductase) are important antioxidants, and can therefore be used to characterise plant susceptibility to natural and anthropogenic oxidative stress (Iriti and Faoro 2008, Foyer and Noctor 2011, Foyer and Shigeoka 2011). Additionally, other leaf compounds, such as the levels of chlorophyll or hydroperoxide, may also help characterise plant susceptibility to oxidative reactions (Gratao et al. 2012). Equally important, plant functional traits can be altered as plants acclimate to environmental constraints and their responses to environmental stressors can be captured by directly measuring fluctuation in plant functional traits, such as biochemical leaf traits. This project will investigate species-level physiological tolerances to environmental stressors and up-scale to community -and- ecosystem-scales. We will focus on biochemical leaf and root traits that are ideal for measuring plant tolerance to (against) environmental stressors. The project involves multidisciplinary work including acquisition of HS data, exploration of the spatial distribution of the environmental stressors in relation to urban areas, and application of artificial intelligence and spectral imaging techniques to create predictive models.

Biological Sciences (4) Computer Science (8) Engineering (12) Environmental Sciences (13) Geography (17)

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