In autumn 2014, an open-top chamber experiment was deployed at Kongsfjordneset (78° 58′ 25″ N, 11° 28′ 51″ E), close to Ny-Ålesund on the Brøgger Peninsula on Svalbard (Fig. 1a; see also https://www.youtube.com/watch?v=lAQUWjAO5ZI). The experiment consists of 48 plots, 24 of which are passively warmed with open top chambers (OTCs, warming soil by c. 1 °C during summer) and 24 of which are bi-annually irrigated, simulating summertime rainfall. Digital images taken from directly above each plot in August 2015, 2017, 2018, 2019 and 2020 will be photogrammetrically analysed to measure rates of shrub expansion (Objective 1, see Table 1 and Fig. 1b, c). Following orthorectification, the student will determine fractional vegetation cover (FVC) in each image using a digital adaptation of the field-based point frame technique(12). The relationship between FVC and leaf area index (LAI) will be analysed in leaves previously sampled from the experiment. These analyses will also account for canopy height, using a digital point frame method(13).
Through a collaboration with Dr Shridhar Jawak at the Svalbard Integrated Arctic Earth Observing System, an expert in the remote sensing of polar vegetation, the student will analyse changes to plant cover on the Brøgger Peninsula in recent decades. The primary source of satellite imagery will be a 10 × 10 km very high resolution (31 cm per pixel) WorldView-2 (WV-2) panchromatic visible and near infrared (VNIR) image of the Brøgger Peninsula, taken as near as possible to August 2023 (Objective 2, see Table 1). The student will compare this image with two additional high-resolution (e.g., Worldview-2, Quickbird or IKONOS) cloud-free archive images from 2000 and 2011. The bands available in WV-2 imagery will enable the calculation of a wide range of vegetation indices (VIs). Statistical models (based on linear regressions and generalised linear models) will be used to calculate which VIs have most explanatory power with regard to the expansion of deciduous shrubs and spatial vegetation dynamics(14). Through a collaboration with Dr Clare Robinson, data gathered in this way will be compared with those reported from experiments set up near Ny-Ålesund in summers 1991 and 2000(15,16) in order to determine if vegetation cover has changed on the Brøgger Peninsula over the last 23–32 years, when mean annual air temperature on Svalbard has risen by 2–3 °C(8).
In 2023, S. polaris and B. vivipara will be sampled from each plot of the warming experiment at Kongsfjordneset (Fig. 1a), either by British Antarctic Survey staff or Norwegian Polar Institute staff based permanently at Ny-Ålesund. Leaves of plants will be analysed for N concentrations and natural abundance of 15N, which is depleted in ECM plants in the High Arctic owing to isotopic fractionation of organic N during uptake by fungi(17). Root tips colonised by ECM fungi (Fig. 1d) will be counted, excised and surface sterilised, and, following protocols developed by our collaborator Dr Filipa Cox(18), DNA will be extracted from individual tips using kits. Internal transcribed spacer (ITS) regions of fungal ribosomal DNA will be amplified using the ITS1F/ITS4 primer set and 480 amplicons bidirectionally sequenced at a commercial facility. The sequences will be compared with those deposited in UNITE (https://unite.ut.ee/), a publicly-accessible database of fungal ITS sequences. Using regression and generalised linear models, the student will compare the frequency of ECM taxa with leaf δ15N values and N concentrations and will determine treatment effects on the abundance and identity of ECM fungi, with the specific aim of determining if fungal taxa that are efficient at soil N capture are more frequent on roots of warmed and irrigated plants (Objective 3, see Table 1).
Collectively, the analyses described above will break new ground in understanding the rate of shrubification in the High Arctic, and the role of ECM in this process. We anticipate several peer-reviewed scientific articles from the analyses, in which the student will contribute significantly to current knowledge.