Shrubification in a changing High Arctic

Overview

Observational studies have shown a widespread greening of the Arctic, caused by ‘shrubification’, an increase in the coverage of shrubs(1,2). Shrubification is of huge potential importance to the fate of the vast stores of organic carbon currently sequestered in Arctic permafrost soils(3), yet the mechanisms explaining the process remain obscure(4), and the rate at which shrubification has occurred in the High Arctic, at the climatic extremes of the phenomenon, is poorly documented. This project uses DNA-based methods to investigate the role in shrubification of ectomycorrhizal fungi, symbionts associated with shrub roots that help plants to acquire nutrients from soil, and, using remote sensing, measures the rate at which shrubification has occurred in the High Arctic during recent decades.

The Arctic has warmed at more than twice the rate of the rest of the planet in recent decades. Summer 2020 has seen temperature records broken across the region, with highs of 38 °C in Siberia and a temperature of 22 °C on Svalbard, in June and July, respectively(5,6). Precipitation patterns are also changing, with rainfall now being more frequent in summer, and rain even falling during winter(7,8). These changes to the Arctic’s climate are having widespread impacts on its fauna and flora, with one of the most apparent effects being the rapid spread of shrubs such as Salix and Betula in the Low Arctic(1,2,4). However, in the climatically more extreme High Arctic, which is inhabited by prostrate dwarf shrubs, little is known of the rate of shrub expansion over recent decades(1,2). The precise mechanisms underlying shrubification remain obscure(4). However, a notable feature of the shrubs that are spreading in the Arctic is that their roots are routinely colonised by soil fungi, which form symbioses known as ectomycorrhizas (ECMs; 9). These symbioses, which are absent from plant species that are not spreading in the region, help plants to acquire nutrients, notably nitrogen (N), from soil, leading to enhanced growth(10). Warmed Low Arctic shrubs are frequently colonised by Cortinarius, an ECM taxon efficient at soil N acquisition(11), raising the possibility that ECMs have a significant role in shrubification. The project proposed here represents an excellent opportunity for a postgraduate student to examine this possibility using DNA-based methods, and, using remote sensing, to measure the rate at which dwarf shrubs have spread in the High Arctic.

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Methodology

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.

Project Timeline

Year 1

Student to train in remote sensing techniques, conduct literature review and to address Objective 1 (see Table 1)

Year 2

Student to train in molecular biological methods and to address Objectives 2 and 3 (see Table 1)

Year 3

Student to address Objective 3, to write thesis and papers, and to engage in outreach (see Table 1)

Year 3.5

Student to write thesis and papers, and to engage in outreach (see Table 1)

Training
& Skills

The postgraduate student will receive training in remote sensing and molecular biological methods (see Training Component)

References & further reading

(1)Epstein et al. (2011) doi:10.1088/1748-9326/7/1/015506
(2)Myers-Smith et al. (2020) doi:10.1038/s41558-019-0688-1
(3)Tarnocai et al. (2009) doi:10.1029/2008GB003327
(4)Mekkonen et al. (2018) doi:10.1029/2017JG004319
(5)www.livescience.com/hottest-arctic-circle-temperature-ever-siberia.html
(6)svalbardposten.no/nyheter/nesten-21-grader/19.12748
(7)Bintanja & Andry (2017) doi:10.1038/NCLIMATE3240
(8)Hanssen-Bauer et al. (2019) doi:10.13140/RG.2.2.10183.75687
(9)Väre et al. (1992) doi:10.1007/BF00203256
(10)Smith & Read (2008) doi:10.1016/B978-0-12-370526-6.X5001-6
(11)Deslippe et al. (2011) doi:10.1111/j.1365-2486.2010.02318.x
(12)Molau & Mølgaard (1996). ITEX Manual, 2nd ed., Copenhagen.
(13)Juutinen et al. (2017) doi:10.1088/1748-9326/aa7f85
(14)Guay et al. (2014) doi:10.1111/gcb.12647
(15)Robinson et al. (1998) doi:10.1890/0012-9658(1998)079[0856:PCRTSE]2.0.CO;2
(16)Madan et al. (2007) doi:10.1007/s00300-006-0213-7
(17)Michelsen et al. (1998) doi:10.1007/s004420050535
(18)Cox et al. (2010) doi: 10.1111/j.1461-0248.2010.01494.x

Further Information

Kevin Newsham, kne@bas.ac.uk

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