Light-driven tipping points in polar ecosystems - Casey Station, Antarctica

Some ecosystems can undergo abrupt transformation in response to relatively small environmental change. Identifying imminent "tipping points" is crucial for biodiversity conservation, particularly in the face of climate change. Here we describe a tipping point mechanism likely to induce widespread regime shifts in polar ecosystems. Seasonal snow and ice cover periodically block sunlight reaching polar ecosystems, but the effect of this on annual light depends critically on the timing of cover within the annual solar cycle. At high latitudes sunlight is strongly seasonal, and ice-free days around the summer solstice receive orders of magnitude more light than those in winter. Early melt that brings the date of ice-loss closer to midsummer will cause an exponential increase in the amount of sunlight reaching some areas per year. This is likely to drive ecological tipping points in which primary producers (plants and algae) flourish and out-compete dark-adapted communities. We demonstrate this principle on Antarctic shallow seabed ecosystems, which our data suggest are sensitive to small changes in the timing of sea-ice loss. Algae respond to light thresholds that are easily exceeded by a slight reduction in sea-ice duration. Earlier sea-ice loss is likely to cause extensive regime-shifts in which endemic shallow-water invertebrate communities are replaced by algae, reducing coastal biodiversity and fundamentally changing ecosystem functioning. Modeling shows that recent changes in ice and snow cover have already transformed annual light budgets in large areas of the Arctic and Antarctic, and both aquatic and terrestrial ecosystems are likely to experience further significant change in light. The interaction between ice loss and solar irradiance renders polar ecosystems acutely vulnerable to abrupt ecosystem change, as light-driven tipping points are readily breached by relatively slight shifts in the timing of snow and ice loss. This archive contains data and statistical code for the article: Graeme F. Clark, Jonathan S. Stark, Emma L. Johnston, John W. Runcie, Paul M. Goldsworthy, Ben Raymond and Martin J. Riddle (2013) Light-driven tipping points in polar ecosystems. Global Change Biology Data and code are organised into folders according to figures in the article. See the article for a full description of methods. Statistical code was written in R v. 2.15.0. In data files, rows are samples and columns are variables. Details for numerical variables in each data file are listed below. Figures 7 and 8 were made in MATLAB and code is not provided. Figure 1: rad_data.csv Solar irradiance data derived from: Suri M, Hofierja J (2004) A new GIS-based solar radiation model and its application to photovoltaic assessments. Transactions in GIS 8: 175-190. Figure 2: Fig. 2c.1.csv Light: Measured light at the seabed per day (mol photons m-2 d-1). Figure 2: Fig. 2c.2.csv Light: Measured light at the seabed per day (mol photons m-2 d-1). Light.mod.p: Light at the seabed per day (mol photons m-2 d-1) predicted from modeled seasonal variation. Figure 2: Fig. 2d.csv Light: Measured light at the seabed per day (mol photons m-2 d-1). Figure 3: Fig. 3a.csv Irradiance: Mean irradiance (micro mol photons m-2 s-1). P/R: Productivity/respiration ratios (micro mol photons O2-1 gFW-1 h-1). Figure 3: Fig. 3b.csv Light: Mean irradiance (micro mol photons m-2 s-1) in experimental treatments. Growth: Thallus growth (mm) of Palmaria decipiens under experimental treatments. Figure 3: Fig. 3c.csv Des, Him, Irr, Pal: Ice-free days required for minimum annual light budget Figure 3: Fig. 3c.bars.csv Prop: relative cover (sums to 1 per site) of algae and invertebrates, excluding Inversiula nutrix and Spirorbis nordenskjoldi. Figure 4: Fig. 4.csv Time: months after deployment Length: length of thalli (mm) Figure 5: Fig. 5c and d.csv Axis 1 and Axis 1: Values from first two axes of principal coordinate analysis IceCover: proportion of days that each site is free of sea-ice per year. Beta: Beta-diversity. Calculated as Jaccard similarity between the most ice-covered site (OB1) and each other site. Figure 5: Fig. 5e and f.csv IceCover: proportion of days that each site is free of sea-ice per year. Value: number of species per boulder (for Metric=Diversity), or percent cover per boulder (for Metric=Cover). Figure 6: Fig. 6a.csv Sites.lost: number of sites removed from dataset due to sea-ice loss. Ice: maximum ice-free days within the region (d yr-1). S: Total species richness across each subset of sites. Effort: relative sampling effort (number of sites sampled).