A planetary computer for Earth

Came across Microsoft's announcement of a "A planetary computer for a sustainable future through the power of AI", complete with a glossy video featuring Lucas Joppa @lucasjoppa (see also @Microsoft_Green and #AIforEarth).

On the one hand it's great to see super smart people with lots of resources tackling important questions, but it's hard not to escape the feeling that this is the classic technology company approach of framing difficult problems in ways that match the solutions they have to offer. Is the reason that biodiversity is declining simply because we have lacked computational resources, that our AI isn't good enough? And while forests that have been stripped of both their mega fauna and previous human inhabitants make for photogenic backdrops, biodiversity can be a lot messier (and dangerous). Still, it will be interesting to see how this plays out, and what sort of problems the planetary computer is used to tackle.

Possible project: Biodiversity dashboard

Despite the well deserved scepticism about dashboards voiced by Shannon Mattern @shannonmattern (see Mission Control: A History of the Urban Dashboard, I discovered this by reading Ignore the Bat Caves and Marketplaces: lets talk about Zoning by Leigh Dodds @ldodds) I'm intrigued by the idea a dashboard for biodiversity. We could have several different kinds of information, displayed in a single place.

Immediate information

There are sites such as Global Forest Watch Fires that track events that affect biodiversity and which are haoppoening right now. Some of this data can be harvested (e.g., from the NASA Fire Information for Resource Management System) to show real-time forest fires. Below is an image for the last 24 hours:

We could also have Twitter feeds of these sorts of events

Historical trends

We could have longer-term trends, such as changes in forest cover, or changes in abundance of species over time.

Trends in information

We could have feeds that show us how our knowledge is changing. For example, we could have a map of data from the newest datasets uploaded to GBIF, the lastest DNA barcodes, etc.

As an example, @wikiredlist tweets overtime an article about a species from the IUCN Red List is edited on the English language Wikipedia.

Tweets by @wikiredlist

Imagine several such streams, both as lists and as maps. As another example, a while ago I created a visualisation of new species discoveries:

Summary

I'm aware of the irony of drawing inspiration from a critique of dashboards, but I still think there is value in having an overview of global biodiversity. But we shouldn't loose site of the fact that such views will be biassed and constrained, and in many cases it will be much easy to visualise what is going on (or, at least, what our chosen sources reveal) than to effect change on those trends that we find most alarming.

Species wait 21 years to be described - show me the data

Benoît Fontaine et al. recently published a study concluding that average lag time between a species being discovered and subsequently described is 21 years.

Fontaine, B., Perrard, A., & Bouchet, P. (2012). 21 years of shelf life between discovery and description of new species. Current Biology, 22(22), R943–R944. doi:10.1016/j.cub.2012.10.029

The paper concludes:

With a biodiversity crisis that predicts massive extinctions and a shelf life that will continue to reach several decades, taxonomists will increasingly be describing from museum collections species that are already extinct in the wild, just as astronomers observe stars that vanished thousands of years ago.

This is a conclusion that merits more investigation, especially as the title of the paper suggests there is an appalling lack of efficiency (or resources) in the way we decsribe biodiversity. So, with interest I looked at the Supplemental Information for the data:

I was hoping to see the list of the 600 species chosen at random, the publication containing their original description, and the date of their first collection. Instead, all we have is a description of the methods for data collection and analysis. Where is the data? Without the data I have no way of exploring the conclusions, asking additional questions. For example, what is the distribution of date of specimen collection in each species? One could imagine situations where a number of specimens are recently collected, prompting recognition and description of a new species, and as part of that process rummaging through the collections turns up older, unrecognised members of that species. Indeed, if it takes a certain number of specimens to describe a species (people tend to frown upon descriptions based on single specimens) perhaps what we are seeing is the outcome of a sampling process where specimens of new species are rare, they take a while to accumulate in collections, and the distribution of collection dates will have a long tail.

These are the sort of questions we could have if we had the data, but the authors don't provide that. The worrying thing is that we are seeing a number of high-visibility papers that potentially have major implications for how we view the field of taxonomy but which don't publish their data. Another recent example is:

Joppa, L. N., Roberts, D. L., & Pimm, S. L. (2011). The population ecology and social behaviour of taxonomists. Trends in Ecology & Evolution, 26(11), 551–553. doi:10.1016/j.tree.2011.07.010

Biodiversity is a big data science, it's time we insisted on that data being made available.