Big data can help biodiversity conservation

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Ecology is one of the most complex scientific field in terms of variety of related areas of study. In the last years, researchers in ecology have tried to build up a model that relates data from ecology, paleontology, genomics and phylogenies, together with localization data and climate models. This effort has been made in order to create a scientifically strong model to prioritize biodiversity conservation policies. In July 2014, scientists from University of California announced that a first model of this kind has been created “taking both distribution and relationships into account to identify lineages that need preservation, in particular rare endemics”. The setting of priorities is particularly urgent, as a recent article on Science has shown that between 16 and 33 percent of species are threatened or in danger, with an average decline of 25 percent in their abundance. This could affect human well-being, as all species are linked each other in the so-called food chain. But, due to the complexity of ecological models, many studies on biodiversity are based on average or incomplete information. Moreover, many data about biodiversity can be found in a plethora of sources, such as scientific articles, museum, publications or individual studies.

Endemism as a measure of biodiversity

The first step made by Brent Mishler, the biologist at the University of California who built up the new model called CANAPE (Categorical Analysis of New And Paleo-Endemism) together with Australian colleagues, was to take into account also the digitalized information of Natural History Museums. His idea was to create a model that comprehended both the number of species in a specific area and the endemism, i.e. the variation among species and their geographic rarity.  Mishler argues that the resulting tree of life “gives more weight to those branches that are endemic, which means that is restricted in range. This relative phylogenetic endemism is a better measure of diversity and rarity, and should be what scientists and policymakers look at when considering whether to conserve an area”. In other words, CANAPE could lead to set a priority list of endangered species, fostering the endemic ones. The model is said to be ready to be applied to all good georeferenced database of species abundance and relatedness. Mishler and colleagues at Berkeley already received a US$ 390.000 grant to apply CANAPE model to the California State Plant Database.

Creating a “culture of data”

But, as said before, it is not just a question of “model”. Complete and usable datasets are also difficult to find. In 2013, a paper published by the University of California analyzed in detail the problem of creating a culture of data management for ecologists. Considering that often ecologists collect a large number of data, but lack a culture of curation, they proposed four actions scientists should follow to “treat data as an enduring product of research and not just a precursor of publications”. In particular, they suggested that scientists should:

  1. Organize, preserve and store data for posterity, using open source tools that writes Ecological Metadata Language (such as, for instance, Morpho).
  2. Share data through specialized network (such as DataONE), online University libraries or scientific journals.
  3. Collaborate and integrate data with a variety of colleagues from different fields of study, since ecology is a multi-related area.
  4. Address data management issues with students (through dedicated, hands-on activities) and peers.

A tool against a (new) future failure

In 2001, the European Heads of State at the EU Summit in Gothenburg (Sweden) decided that “biodiversity decline should be halted with the aim of reaching this objective by 2010”. Soon after it has been launched the “2010 Biodiversity Target”, enforced year after year by some implementation tools, such as the Kiev Resolution on Biodiversity or the “Message from Malahide”. Some nations decided to bind themselves to the 2010 Biodiversity Target by adopting individual Biodiversity Action Plans (here is the Italian one). Despite all these documents, the 2010 Biodiversity Target largely failed. This mainly was due to a lack of consensus on how to measure the biodiversity loss. Scientific models such as CANOPE can now bridge the gap and, through its results, set priorities easier to achieve.

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