Understanding Global Warming: Case Study

Methods

The process of finding out starts with extensive planning and background research. Once an appropriate research plan had been formulated, Ceridwen began collecting her samples from sites around New Zealand, the subantarctic islands, Chile and the Falkland Islands. Ceridwen travelled to these places over a period of two years, with the help of other scientists that had been contacted during the planning process. This work enabled her to make observations and collect samples of kelp, as well as invertebrates found living in the kelp, to bring back to the lab.   

Of course, most people can’t bring samples of seaweeds into New Zealand because of biosecurity regulations, so Ceridwen needed special permits from the Ministry of Agriculture and Forestry. Ever since, these samples have been carefully stored in isolation within a specially regulated laboratory. 

Back in the lab Ceridwen and the team used modern molecular biotechnologies to find out how closely related the different species were. These analyses allowed Ceridwen to infer what had happened to this species during the last glacial period.  

The techniques used were: 

• Extraction of DNA 
• Polymerase Chain Reaction to amplify specific DNA targets   
• DNA sequencing 
• Analysis of variation in genes   
• Phylogenetic analyses to reveal relatedness

By using these techniques Ceridwen and the team were able to build up a picture of the genetic relatedness of the different populations of kelp. 

Why would these habitats have been available? This diagram on the left shows the estimated extent of winter sea ice (WSI) in the Southern Ocean at the peak of the last ice age, the so‐called Last Glacial Maximum (LGM). These estimates were made using geological data compiled from sea‐floor sediment cores containing fossil diatoms. Diatoms are single‐celled algae, which occur in many habitats, and some species are most commonly found in sea ice. Geologists infer whether a core comes from an area that was under sea ice at the Last Glacial Maximum by looking at which diatom species are in the core. The blue dots on the diagram show the location of cores that indicate sea ice was present; the green‐and‐black dots show where the edge of the sea ice is thought to have been, and yellow dots represent cores that showed no evidence of sea ice.

Studies previously published by other scientists (researched by Ceridwen in her planning) show that Bull Kelp cannot survive where sea ice occurs. Could sea ice explain the genetic patterns found in Bull Kelp? Subantarctic populations could have been destroyed by sea ice during the last ice age. When the climate warmed and the ice receded, the kelp could have recolonised the newly‐freed islands by floating across the oceans from somewhere beyond the reach of the sea ice. This scenario could certainly explain the near‐complete genetic uniformity of the kelp populations throughout much of the subantarctic, versus the higher genetic diversity in places further north (such as in New Zealand and Chile) that remained free of ice.

The problem with this hypothesis was that sea ice at the Last Glacial Maximum was not thought to extend as far north as many of the supposedly recolonised islands (see Figure 10, above). The islands labelled in red are those that seem to have been recently recolonised by Bull Kelp, but some – such as Marion and Macquarie Islands – lie beyond the estimated range of Last Glacial Maximum sea ice. These islands, however, are in areas that have little geological data supporting the estimated limit of the sea‐ice. You can see from the diagram that, although geologists have taken numerous cores, data is still lacking in many places. Sea ice might, therefore, have been more extensive at the Last Glacial Maximum than previous studies have suggested.

This exciting research not only shows how organisms can be affected by climate change, but also how biological studies can give us great insights into past environmental conditions. Understanding ancient climate change and its evolutionary impacts is a crucial part of making good predictions about the effects of future climate change – whether natural or human‐induced.