The unique Antarctic terrestrial vegetation serves as an early warning system in understanding ecosystem responses to climate change. This project evaluates the expansion of Antarctic vegetation cover and biomass and assesses its resilience by combining remote sensing and physiological measurements, improving our understanding of Antarctica’s terrestrial biosphere in the context of global carbon cycles.
Project Background: Climate change is impacting polar regions most severely. The Antarctic terrestrial biosphere, the vegetation of which is dominated by algae, bryophytes and lichens, is thought to be particularly sensitive and therefore considered to be one of the more significant baseline environments for the study of global climate change (1,2).
In situ data have revealed distribution shifts, and many species have expanded their ranges in a warming Antarctic. In the terrestrial realm habitat availability is predicted to increase by ~25% in the next century under current global warming scenarios (3). Deglaciated terrains can be colonised rapidly (4,5) and especially taxa with wider ecological response amplitudes are predicted to thrive (6,7). Warmer temperatures boost terrestrial ecosystem productivity: for instance, between 1991 and 2002, with increasing temperature, lichens increased their growth rates by 124% (8). Moss growth rates have quadrupled over the past ca. 50 years (9) and the two Antarctic native vascular plant species have proliferated (10).
Our previous studies provide mechanistic insight into possible biotic homogenisation (11, similar to Arctic environments) posing a threat for Antarctic ice-free habitats (12) and altering ecosystem functioning and productivity (13).
There is a need to assess the generality of these shifts on a larger spatial scale than can be achieved through manual field survey, and to exploit spatial gradients to explore environmental drivers of distribution shifts. The few currently available remote sensing vegetation surveys over Antarctica are based on coarse-scale NDVI measurements (14) or in the case of lichens, spectral unmixing approaches (15). ESA’s Sentinel 2 satellite now provides good coverage of the Antarctic coastal zone at 10 m resolution. This project will make use of several long term vegetation monitoring projects as well as existing hyperspectral imagery and reflectance data of Antarctic vegetation to assess an inverse radiative transfer model approach to monitoring Antarctic vegetation biomass and distribution using Sentinel 2 data.
- Determine the usefulness of Sentinel 2 data to estimate the biomass of Antarctic vegetation using a radiative transfer inversion approach.
- Assess biomass and ecological range changes for major Antarctic vegetation types using Sentinel 2 imagery.
- Measure the bioclimatic envelope of dominant vegetation types to assess species resilience.
Year 1: Desk study processing hyperspectral imagery collected at Cape Hallett and field spectra collected at Rothera and King George Island to test vegetation-biomass retrieval using a radiative transfer approach. Measurements of carbon fluxes for dominant vegetation units using growth chamber approaches with material collected during previous expeditions.
Year 2: Scale approach to Antarctic Peninsula using Sentinel 2 imagery to map biomass distribution of terrestrial vegetation. Validation of the model at other long term vegetation monitoring sites by using existing high-resolution hyperspectral imagery and concurrent transect data or in field, (if opportunity arises).
Year 3: Investigate changes at selected sites with suitable seasonal/multi-year record. Write up.
Training: In addition to the comprehensive training as part of the SENSE CDT, this PhD programme will benefit from international collaboration including with the University of Waikato, New Zealand, and the University of Madrid, Spain and will provide opportunities for the recruited student to develop their own targeted research questions including through supervisory experience.
Supervisory team: Claudia Colesie, Mat Williams, Andrew Gray (UoE); Kevin Newsham, Pete Convey (BAS)
This PhD is part of the NERC and UK Space Agency funded Centre for Doctoral Training "SENSE": the Centre for Satellite Data in Environmental Science. SENSE will train 50 PhD students to tackle cross-disciplinary environmental problems by applying the latest data science techniques to satellite data. All our students will receive extensive training on satellite data and AI/Machine Learning, as well as attending a field course on drones, and residential courses hosted by the Satellite Applications Catapult (Harwell), and ESA (Rome). All students will experience extensive training on professional skills, including spending 3 months on an industry placement. http://www.eo-cdt.org
1 Convey, P. 2017, Mod Life Sci; 2 Convey, P. et al. 2014, Ecol Monographs; 3 Lee et al. 2017, Nature; 4 Favero-Longo et al. 2012, Anta Sci; 5 Bajerski & Wagner 2013, FEMS; 6 Le Bars et al. 2016, Env Res; 7 Rinnan et al. 2009, Glob Change Biol; 8 Sancho et al. 2019, Sci Reports; 9 Amesbury et al. 2017, Curr Biol; 10 Cavieres et al. 2016, Plant Ecol; 11 Colesie et al 2018, Glob Change Biol; 12 Chown, S.L. & Convey, P. 2007, Phil Trans Royal Soc; 13 Clavel et al. 2011 Fron Ecol Env; 14 Hughes et al. 2011, Anta Sci; 15 Casanovas et al. 2015 Polar Res