By Andreas Merkl, President, Ocean Conservancy
Andreas Merkl, President, Ocean Conservancy
Andreas expertise lies in Management and Environmental Consulting, Strategic Planning, Entrepreneurship, Sustainable Development and other areas. His particular interest has been the deeply connected challenges of ocean ecosystem decline and climate change.
Incorporation of Data Analytics to Overcome Challenges
As ocean advocates, Ocean Conservancy is a classic environmental organization, working to treat oceans to preserve it in all its glory. The most significant ocean issue today is climate change. The ocean is a complex system, which is increasingly stressed by a warming climate. Climate change triggers a number of reactions in that complex ocean system, such as increased acidity, shifting currents, reduced levels of oxygen and more. Faced with this magnitude of stress, we must naturally ask ourselves: ‘Could parts of the ocean system change catastrophically?’ After all, in geologic history, the ocean has reacted to climate stress in drastic ways.
However, predicting what will happen to a system as complex as the ocean is out of reach we cannot build a process model capable of predicting precisely what will happen when and where. However, using tools from other fields, (like economics, epidemiology, and internet security), we can take advantage of the almost unlimited processing potential that Amazon has to offer and perform very sophisticated scenario-analysis on particular parts of the ocean. This in effect, helps with the prediction process in forecasting what is most likely going to go wrong, but more importantly, when. Our partnership with the Oxford, Stanford and George Mason Universities and Amazon has proven beneficial in collaboratively building a network-spaced model to monitor ocean stability under ocean stresses.
On a positive note, the ability to understand rather complex Earth systems—whether related to the atmosphere, the ocean or desert ecosystems—is exploding. If we understand the dynamics behind these systems faster than we are damaging them, we might be able to take corrective action in time. This is one reason—besides the obvious for-profit applications—why companies like Microsoft and IBM have started looking at Earth systems, be it observation, management or data, as an enormously important field.
General Challenges & How AWS Combats Them
Three pressing issues arise when working with complex systems. First in line is complete data abundance, which is essentially just a staggering amount of data. Satellites, buoys, etc, can create huge data sets – but data don’t necessarily lead to insight. The second issue has to do with having lesser data, equating to a learning problem. This is known as data scarcity and requires proxies to extrapolate from the lesser amount of data to render increasingly better representations of what the main system would resemble. The last in line is known as data dispersion, which involves bringing vastly diverse data onto the same scale: both spatial and temporal. The collaboration of artificial intelligence, machine learning, and cloud technology offers the solution to these three pivotal issues in the industry today. The ocean stability model we have built is highly data intensive which requires the capacity that AWS has to offer. With the help of their cloud resources, we are now able to perform massive simulations of the ocean system.
The sustainability of the ocean is a growing concern. Predicting its future is beyond the scope of traditional analytics, which is where the AWS services come into play. This collaboration is seen as an opportunity to save exhaustive natural resources by utilizing the processing capacity of the AWS.
Aligning with Future Trends
The ocean is a resilient medium – but not endlessly so. There are trouble spots where the system can respond to claim the stress in potentially catastrophic ways. This may manifest as huge dead zones in the ocean, extinction events, food chain crashes, current changes, etc. The alliance with partnership companies—that have both algorithmic knowledge as well as processing capacity—helps Ocean Conservancy look at these systems from a highly analytical perspective, enabling us to hone in on where the trouble starts from, and focus on making efforts to prevent it. Personally, I am optimistic about the process. In the end, building networks of friends and experts, and being open to feedback or constructive criticism is crucial.
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