Over the last fifteen years, I have been associated with an exercise of reviewing what countries are doing to safeguard their biodiversity and ecosystems. The obvious source of information for this are the National Reports that countries submit to the Convention on Biological Diversity (CBD), a multilateral agreement that was adopted by United Nations member states in 1992, along with the UN Framework Convention on Climate Change (UNFCCC) and the Convention to Combat Desertification (UNCCD).
These reports are in addition to the National Biodiversity Strategies and Action Plans (NBSAPs), developed by more than 180 countries around the world that lay the foundation for what these countries intend to do for conservation.
Recently, I completed an analysis and review of the NBSAPs of about 162 countries, developed after 2010 when new strategic plan for biodiversity along with twenty targets were adopted by the Convention on Biological Diversity, along with my colleague and co-author Christian Prip.
The one sentence summary of the painstaking review is that many countries fall short of taking big and bold steps for securing the ecosystems and biodiversity.
A review of the National Reports submitted to the Convention also reveals a stark picture that does not give the full and complete picture of actions on the ground. The data and information provided is scanty and does not add up to the intent of the Convention and its decisions.
In this blog, I wish to focus on one new area of scientific application that can help countries to become more robust in dealing with conservation, sustainable use and sharing of benefits of biological diversity – using big data that support innovations to better conserve and manage our biodiversity and share benefits.
Relevance of Big Data in Conservation
The mere availability of data and information, though scattered and scanty, collected by a large number of agencies and institutions on biodiversity and ecosystems has been immense. Currently, there is no one place or a method to use this data and information for decision making. Each country, institution and individual working on issues of conservation have kept the data and information for themselves making any consolidation impossible and decision making suffers due to this.
This is compounded by the fact that countries are reluctant to use the information and data from sources other than their own while preparing national reports. This provides a very skewed picture of our conservation efforts at various levels.
Case in point is the current implementation status of actions for achieving the Aichi biodiversity targets, where indications are that we will reach 2020 only to say ‘sorry’ to the world that once again we failed to live up to their expectations to achieving global biodiversity goals that we set out for ourselves in 2010 at the Convention on Biological Diversity (CBD) Conference of Parties (COP 10).
The New Solution?
Big data and machine learning can help to transform the way we deal with conservation. Not just data but the tools where such information and data are used, such as block chain technology, artificial intelligence are here to come to our help if we can use these techniques and technologies for purposes of better decision making in conservation, including dealing with illicit trade, legal trade, tacking use of resources and influencing decision making systems around the world for future conservation.
What are Artificial Intelligence, Blockchain Technology?
Artificial intelligence is the simulation of human intelligence by machines, especially computer systems that deals with learning, reasoning and self-correction. Coined in 1956, it started as research into neural networks (1960s) evolving into machine learning (1990s) and then to deep learning (present day).
AI automates repetitive learning and discovery through data, adds intelligence, analyses more and deeper data, achieves incredible accuracy and get the most out of data.
Blockchain Technology is a new filing system for digital information, which stores data in an encrypted, distributed ledger format. It enables the creation of tamper-proof, highly robust databases.
Where AI can help the Conservation?
- Address real-time impact and compliance to Multilateral Environmental Agreements
This has been a huge issue for many. While countries strive to focus on format-based reporting, often with different sets of data sets and points being used for reporting makes it difficult for monitoring compliance to the Agreements in general.
For example, if one has to look at the reporting for the Convention on Biological Diversity, almost all the national reports prepared have a different kind of information on implementation, thanks to changing formats.
With close to 155 biodiversity related multilateral and bilateral agreements, reviewing the information provided in country reports in myriad formats is just not possible. More than a decade has been spent, with limited impact, on joint reporting and streamlining reports. All of this makes consolidated impact assessment of actions difficult across a number of actors and action.
Using block chain technology, combined with elements of AI can come handy to review the information and suggest correct approaches since these technologies can also work with un-structured data as well.
- Track overall investments and actions related to conservation
In 2010, the United Nations University-Institute of Advanced Studies (UNU-IAS) prepared a report on the kind of investments that went into building capacity for issues related to biosafety over a 7-year period. The findings were startling. A total of USD 135 million were spent on this activity across countries by multiple donors. Some countries received funding from nine different sources for the same kind of activities. History will repeat itself if one totals the amount of money spent on building capacities related to access and benefit sharing (ABS) now.
Block chain technology and AI can help all those investing in conservation action to channel the resources where it is needed and where it can have an impact. Such decisions being made by a large number of donors are relatively subjective. These technologies will minimise the errors in decision making on such investment options.
In addition, recipients of the funding can become more accountable.
- Align incentives for progressive actions, automatically
Significant part of the incentives for progressive actions need to be backed up with accurate information on those who deserve and the impacts of such incentivisation.
Current actions on incentives are again, subjective and are based on impact assessments can benefit from the use of big data analytics, AI and the related.
In addition to focusing on supporting actions that are impactful, these technologies can help scale-up actions and replicate initiatives using modelling and analytics that are currently not available for the conservation community.
- Deal with supply chains and issues related to access and benefit sharing
There are already few initiatives that was rolled out recently in using block chain technology for use in dealing with issues of access to resources and benefit sharing.
With increasing technological interventions that will minimise the need for physical access to resources, mere gene data is enough for deriving products for commercial application. Once such technologies such as these become commonplace, actions related to ASB will be replaced by intellectual property related issues that many stakeholders are still slow to recognise within the conservation community.
The more scientific disciplines like synthetic biology progress, there is a need for the conservation community to embrace technologies like block chain and AI.
- Access real time data on country-wide initiatives
Given the ability to deal with big data and using multiple data sets, in real time, the new technologies can help countries deal with conservation and related actions across multiple actors in multitude locations. This will help deal with data leaks and combine multi-layered information assessment, an area of key importance to monitor biodiversity conservation and ecosystem changes in real time.
In addition, block chain technology, AI and big data analytics can effectively deal with issues such as modelling, illicit wildlife trade, long-term assessments and predictions of ecosystem goods and services on multiple layers such as soil, climate as well as systems such as tenure, access and the like.
It is time the conservation community embraces these technologies for better securing the future of this Planet!