When I was younger, the term “high seas” conjured up images of pirates, and big galleons, and sea monsters.  Perhaps a little less exciting to my younger self, the high seas are actually international waters – those that lie outside the Economic Exclusive Zone (EEZ) of any country.  

The area of high seas is vast – comprising 58% of the ocean, so it’s not surprising that the high seas are full of life.  Just like inside EEZ’s, the high seas area heavily utilized by people, and just as in our own waters, marine biodiversity needs protection to ensure its long-term persistence.  Sounds good so far.  Leaving aside the political issues of managing human activity in international waters, there are problems for effective conservation – assessing where areas of significant biodiversity are to implement meaningful areas of protection.

Some of this is down to logistics – like the cost of sampling areas of the ocean far from land.  Some of this comes from the high mobility of marine species that are found in the high seas; if we see them here today, they are probably somewhere else next week.  Some of these critters are undergoing migrations, some change location depending on where in their life cycle they are, and some appear much more ‘free’ (though aren’t wandering around aimlessly).  If our knowledge gaps on marine biodiversity in coastal waters are big, they are vast when it comes to the high seas.  We need a plan, and we need it sooner than later.  And integral to that plan, argue Ei Fujioka and Patrick Halpin, both from Duke University, is a “publically accessible online framework that provides interactive tools to assess marine biodiversity from a variety of perspectives”.  There wasn’t one, so these guys set about setting a prototype up.

Ei and Patrick are no strangers to the mapping of marine critters, and already heavily involved in OBIS - a repository of marine mammal, seabird and sea turtle observations from across the globe.  Running for over 10 years, it has more than 2.9 million records for some 311 different species.  The data within it comes from a number of different sources, such as photographs, and tagging animals.  Some of the data gives on-off records of sightings, some tracks individual movements over a period of time.  This is a veritable treasure-trove of data, and some relates to the high-seas.  The next step is to pool all of this data together into something usable, something succinct, so that researchers – and indeed the public – can understand where our fellow marine critters like to hang out, where the areas of greatest biodiversity are.

There are actually many ways of measuring biodiversity.  The simplest is species richness – simply a count of the number of different species found in any given sample.   This does not take account of the relative abundance of each species – known as species evenness, so for this there are a number of different indices, each with its own formula for calculating diversity.  Alongside species richness, the researchers included 3 of these indices into the mapping – the Shannon-Wiener, the Simpson, and the Hulbert index.  This is quite handy.  With different ways of quantifying how much diversity, like-for-like comparisons can be more difficult.  Providing a range of indices allows the data to be used in more ways than if just a single index was provided, and crucially because all areas have the same indices, they can easily be compared on a like-for-like basis.

Of course no prototype is complete without a case study.  For this, Ei and Patrick chose the Sargasso Sea – a high seas gyre ecosystem in the mid-North Atlantic Ocean that is named after the floating mats of Sargassum - a brown seaweed that accumulate there.  Previous work by a number of different researchers has already indicated that the Sargasso Sea is a key are for biodiversity,  and the OBIS-SEAMAP data-house itself hold some 5,825 observation records, and 32 datasets for this area.  These records go from 1966 to 2013, making it possible to assess how biodiversity across the four indices (Hurlbert, Shannon, and Simpson, and species richness) has changed decadally (every 10 years).  The indices that took into account species abundance – that’s Hurlbert, Shannon, and Simpson – all pointed towards a decline in biodiversity since the 1960's (excluding the 1980's – they only had one record for that year, so assessment couldn’t really be done), with an increase in the 2010's.  Species richness on the other hand was a bit more all over the place.  This may partly be down to ‘effort hours’ in collecting the data, which has a statistically significant impact on species richness scores, but not on the other 3 indices.  But crucially the case study has demonstrated that it is possible to bring together different datasets to produce some meaningful analysis, and present it in a format that is useful for the public and researchers alike.  This pooling together of data – particularly high quality data - is useful for all types of ecological study and conservation planning.  Where data is much sparser, just like on the high seas, pooling together is even more important.

Ei and Pat also note that the prototype is flexible, and can incorporate all sorts of different measures of biodiversity, tailored to achieving different goals and objectives, or answering questions to guide us in making good conservation decisions.  As a prototype, its pretty good.  Don’t forget the OBIS-SEAMAP is also publicly available, and free to use – so why not have a play yourself.

The original paper appears in the journal Endangered Species Research.  The researchers have paid for the paper to be made open access – you can access it here http://ow.ly/yhYd0 .