20th October 2020
Simple metrics based on complex data sets: our vision for post-2020 science-based targets for nature
Authors: Dr Kat Bruce, Founder and Katie Critchlow, CEO of NatureMetrics.
Simple targets to drive global, national and corporate progress on biodiversity should no longer be a pipedream thanks to new ways of providing big data on nature and ecosystems.
Biodiversity loss now sits alongside climate change as one of the top risks facing humanity but one of the single biggest blockers to progress is a lack of data and the simple targets and measures which data enables.
Unlike climate change, biodiversity does not have one single, simple measure like molecules of CO2, and this has dramatically impeded our capacity to address the biodiversity crisis. The Net Zero Emissions target for climate change is now being translated law, such as the net zero emissions laws in the UK and into formal corporate measures and reporting systems (e.g. TCFD). But for biodiversity, we learned last month that all 20 global targets set a decade ago have been missed and despite a recent surge in corporate interest in the concept of Net Positive Impact, it remains unclear how to measure success in achieving such a goal.
The first demand from business is, understandably, that biodiversity measures are simple. This is necessary for reporting at all levels, from setting global goals to managing risks in investment portfolios. But if we aim only for simplicity without taking into account the inherent complexity of biological communities, we simply generate meaningless, tick box measures which conceal the underlying rate of biodiversity loss and its impacts on lives and livelihoods.
In the past, between nature and data has sat binoculars, cameras, microscopes and waterproof notebooks, relying on human observers to record individuals and identify species one at a time.
Inevitably, such effort has focused on those components of biodiversity that are large in body size, small in number, and easily recognisable by visual characteristics. This has been time consuming, expensive, risky and unscalable. In addition, the threat to humanity posed by biodiversity loss is not driven by the potential loss of these charismatic megafauna that we can easily see and measure using traditional monitoring. Losing polar bears, orangutans and pandas is desperately sad but is not the biggest threat to business nor humanity. That comes from the unseen loss of the ‘small things that run the world’ – the invertebrate animals and microscopic organisms that are the building blocks of our ecosystems, cycling nutrients, maintaining soil health, protecting against outbreaks of disease or pests and maintaining the fine balance of nature that provides services from clean water to productive agriculture and healthy forests.
Linked to unscalable and expensive traditional monitoring is an overreliance on historical data in global databases to determine current or future impacts. These data sets provide a poor proxy for the current state of nature. A recent report by WWF estimated that we’d lost nearly 70% of natural populations in the last 50 years. A loss curve too steep to make data from even 5 years ago meaningful for understanding the marginal cost of destruction today. And that report, one of the most detailed assessments of global biodiversity loss available only measures 21,000 of the millions of species still living on earth today.
But the search for simple measures and targets that can be used globally and take into account the full and essential diversity in nature should no longer be a pipedream thanks to new ways of providing big data on nature and ecosystems.
There are now technologies that allow biodiversity data collection at an unprecedented pace and scale. Our business, NatureMetrics, provides biomonitoring using DNA, detecting organisms similarly to the way you might detect someone at the scene of a crime. We can detect whole communities of species – from bacteria to bats – from DNA isolated from water or soil. These DNA-based methods remove a huge bottleneck in the collection of data which previously required taxonomic experts to be present in the field, or to be looking down a microscope for every group of interest. Today, we can provide field sampling kits so simple that our kids have been able to take samples and get the same quality of data as our trained scientists. This democratizes data collection creates a scalable solution to monitoring the true diversity of life.
Meanwhile, other 21st century nature data providers such as drones and Earth Observation are revolutionizing vegetation surveys and even large mammal surveys across vast terrestrial ecosystems.
The current poor availability of data means that those putting their effort into trying to simplify nature into a single measure ‘top down’ without concern for the complexity of life are bound to fail.
That doesn’t mean that data on biodiversity can never be aggregated and simplified to set global goals or targets at the level of a supply chain or investment portfolio. But it does mean that we must lay the foundations of good data first. By building robust data baselines, we lay the foundations of our understanding and management of the natural world. We can then simplify this data from the ‘bottom up’ to portfolio level aggregate measures.
We are used to dealing with big data these days. Big data algorithms by definition take huge, complex, noisy datasets and use them to drive simple scales and visualisations.
Biodiversity is a classic big data problem. At any given place and time, individuals belonging to thousands of species are responding to a huge variety of different factors. The responses of biological communities to these factors are varied and complex. So much so that if you pick just a small number of species to track, you may not see any significant response to an impact at all; but connecting data on the responses of many species reveals predictable response patterns at the community level.
Now as these biological data layers become available for the first time and on an unprecedented scale, we can unlock this powerful knowledge about how our life support systems respond to human impacts. Then we can improve those impacts before it is too late.
Understanding the bilateral flow of impact between natural and man-made assets is a vital piece of the puzzle. Here, we can learn lessons from the climate change debate, where businesses and investors finally woke up to the issue when it was no longer considered a nice addition to a sustainability report, but as a driver of critical physical, technological and regulatory risk to assets and business performance.
We must also learn the lessons from climate change and focus on the high impact sectors, the 20% of companies or sites that create 80% of the impact.
Many of these industries – energy, infrastructure, extractives, fisheries – are already accustomed to a level of regulated environmental monitoring. The exception here often being agriculture. This is curious as the sector probably has the most immediate business case for monitoring biodiversity given that the soil biome and insect diversity around it have such a direct economic impact upon it.
DNA based monitoring of marine sediment gives so much more data than by sight alone, enabling us to detect patterns and impacts not visible before.
The collection of vast data baselines for biodiversity is now both possible and economically feasible. For example, we have estimated that it would cost in the low tens of millions to baseline the biodiversity of every major river basin in the world.
When you consider the global importance of these freshwater ecosystems and how rapidly they are being degraded, the cost to gain this globally important data set is a drop in the ocean (or the river!).
This is data can tell us how our natural life support systems are coping, responding and functioning in relation to the stressors and remedies that we apply to them through mining, infrastructure, hydro dams etc. From agriculture to nature-based climate solutions – we rely on nature and nature relies on us and the time is now to figure out those interactions. This week a SwissRe report warned that failure to act on biodiversity loss has put a fifth of countries at risk of ecosystem collapse.
NatureMetrics and others devoted to 21t century nature data solutions can now deliver can deliver the insights that enable business and governments to set and measure targets to rapidly reverse biodiversity decline.
What does a data-driven bottom-up approach to biodiversity look like in practice?
Once we have the solid baseline data at the base of the pyramid, we can begin to build up the biodiversity picture as required by those assessing risk and strategy at every level.
Those managing the impact sites get the detailed site or landscape level biodiversity data’. Month-by-month or season-by-season they can get a detailed picture of what is going on at many different sites, and how this impacts their business. From meeting their regulatory obligations to building back the health of their soil.
We can maintain a ‘living’ interactive interface for site managers to see their biodiversity and associated natural wealth changing over time and with impact. PDFs are where data goes to die. With fully digitized data we can do so much more.
At this site level, rapid assessments of risk and baselines at project outset can completely change the way a project evolves to put biodiversity at the heart of decision making rather than applying ‘sticking plasters’ once a project is planned and implemented.
At the next level up, company decision makers might want to understand an aggregate measure of how their business is impacting on the stocks and flows of natural capital into or out of their system boundaries. Now, pairing the big data on nature with metadata for example on crop productivity, pollination services, disease resilience or local fish stocks will enable us to understand the real business, social and economic impacts of the changes to biodiversity being caused by the site.
Finally, at the top level, these indicators can be aggregated up to a clear Science Based Targets and enable meaningful measures for commitments such as Net Positive Impact on Biodiversity.
Through this globally connected understanding of nature will come many new ways to enhance our lives and all life on our planet. From improved productivity by working in harmony with the billions of organisms in our soil to understanding trophic interactions or migratory activities which could help to restore our fish stocks.
Our natural world hangs in the balance along with our climate. To save it we need global targets for governments, business and the finance sector. These targets must be set and measured using the same science-based rigor now being applied to climate change. Those with the greatest impacts must bear the responsibility for meaningful monitoring and use better data to drive real change. DNA-based monitoring puts the power to collect data in the hands of us all through simple sampling delivering robust results. With great data, will come the best opportunity yet to finally set and deliver on a new deal for people and nature.