Red, dirt road leading to Puerto Maldonado, Madre de Dios, Peru. This road is the Interoceanica highway, going through Brazil and finishing at the Pacific coast in Peru. © Brent Stirton / Getty Images / WWF
The pressure that our natural world is under is enormous. Wildlife populations around the globe are in rapid decline, while extinction rates continue to surge. Not only is our inherited wealth of biodiversity at risk, but human wellbeing too is becoming increasingly endangered.
Part of the problem facing conservationists in meeting these challenges is how to effectively assess the impact of human activities across the globe to inform action. Traditionally, the information on development threats and human activities – such as agriculture, oil and gas concessions, fishing and deforestation – was obtained through static evidence pieces. Reports and academic publications would examine the extent of some specific human activity on some area of the environment.
But in an ever-changing world, more complex and fast-changing than ever, this approach is less valid. Delayed academic releases mean that reports can often be as much as six months out of date by the time they’re published. Even more problematic is that, save for a large change in data, media outlets and publishers have little interest in repeating the same study next month or next year. Typically, then, a conservationist’s understanding on global human impact is through a patchwork of assessments, with no comparable results or integrated formats, different lenses methodologies, spatial and temporal scales and often using different datasets.
But if we are to scale the extent of these threats over time to provide conservationists with a situation awareness of what’s happening to provide context to their efforts on the ground, we need exactly the opposite.
The old methods of reporting on human threats do not provide the consistent intelligence necessary to answer the really big questions facing us now. To effectively address emerging trends and provide accountability to key actors for the environment, such as governments, companies and investors, up-to-date intelligence is crucial. Consistent, comparable results over time will make it possible to understand the rapid rates of change facing the planet.
The emergence of Conservation Intelligence
Fortunately for the conservation sector, understanding these threats has never looked more possible. Dramatic improvements in earth observation satellite and airborne data have taken place over the past decade. The availability of open datasets has opened up our knowledge of threats more than ever, on areas from deforestation to illegal fishing, extractives to agricultural expansion. Rather than reactively responding to threats when it’s too late, it is now possible to monitor emerging and proposed developments as they happen, and to counter them effectively.
The conservation sector has been working hard to capitalise on this. A proliferation of platforms from different organisations, such as Global Forest Watch, OceanMind, IBAT, SPOTT, WWF-SIGHT and Global Fishing Watch, are providing answers in research areas unimaginable even ten years ago. The use of proprietary datasets combined with open datasets is widening our scope even further. Global Fishing Watch uses commercial Satellite AIS datasets to track shipping vessels in near real-time. Global Forest Watch uses a time-series analysis of openly available Landsat satellite images to characterize forest extent and change. A new era of conservation intelligence is dawning, based on data that is quickly obtainable and globally relevant.
These projects so far are showing impressive results. Brazil’s PRODES program, which highlights in near real time illegal land-use to inform enforcement agencies, is thought to be a key driver in why deforestation has decreased by ≥75% in the Brazilian Amazon over the last decade. Oceanmind reviewed illegal fishing within the Chilean Exclusive Economic Zone, using VMS and AIS data supplemented with SAR imagery to identify the vessels suspected of illegal fishing and enabling the Chilean Navy to prioritise its air and sea patrols to support enforcement.
With the proliferation of varied tools from across the conservation sector, a huge quantity of data is now at the fingertips of major conservation organisations across the world. The large variety of tools available are incredibly useful for specific applications, such as niche tools assessing one isolated environmental factor. But with so many tools now available, conservation intelligence risks facing some of the exact same limitations that challenge traditional research methods – different methodologies, scales, formats and datasets leading to an inconsistent patchwork of assessments and results.
Flying over Sudbury Reef. Inshore reefs are particularly vulnerable to agricultural run-off carrying sediment, nutrient and pesticides. © WWF / James Morgan
The next iteration of conservation intelligence?
To provide an overview of the challenges facing the natural world, as well as consistency across sectors and threats, a tool is needed that ties all this data together into one online mapping and analytics package. A regularly updated tool could look at all of human development – mining, oil and gas concessions, fishing, shipping, roads, rail, dams, pipelines, agriculture, and logging – and plot them against environmental assets: forest cover, protected areas, key biodiversity areas, mangroves, coral reefs, and species populations.
Blending both open source and proprietary datasets, as well as other conservation organisations’ datasets, the interplay between them could be assessed. Intelligence would be easier to obtain on current impacts and environmental exposure of asset holders and companies behind the developments, and insights into the performance of governments in the protection of their natural assets. By analysing the interplay every month, utilising automation, we could begin to document change over time to provide further accountability – a powerful global tool that could be used by the entire conservation sector.
Already some organisations are heading in this direction. Global Forest Watch already pulls together multiple spatial datasets defining both development and environmental datasets. At WWF, we’ve also been working on this problem. WWF-SIGHT, a tool developed by WWF, has brought together key open source and commercial environmental and development datasets. Recently an example of this approach has been launched, displaying data online in an easily understandable format that defines the interplay between extractive concessions and protected areas at a country level. From this, worrying statistics have become apparent, such as that Australia has approved an area the size of the UK to oil and gas concessions within its protected area network.
Caption: An example of WWF-SIGHT outputs. The interactive format shows the extent of a countries protected area network overlapped by mining and oil and gas concessions.
As well as informing conservation action, it isn’t hard to imagine a public facing interactive online portal that provides the high-level results of regular assessments. At a touch of a button, the environmental performance of each country could be defined, displaying the extent of current developmental threats and environmental degradation.
This could be extrapolated even further into a more visual way of understanding the vast amount of data. For instance, an ‘environmental ticker’ similar to a share price could graph country environmental performance, showing changes over time. Road developments within protected areas would lead to a drop in the ticker score; a decrease in oil and gas concessions within coral reefs would show an increase, showing the country is improving its environmental performance. A visual demonstration of environmental performance on a country-by-country basis, or by a company-by-company basis (for sectors with spatially defined assets i.e. mining) would provide comparable insights to inform investors, insurers and banks to their environmental exposure and urge compliance to important environmental standards.
But this isn’t something that can be achieved by one organisation alone; an inter-organisational system is needed that is both built by and that serves the entire conservation sector.
Strength in unity, weakness in division
Inter-organisational collaboration in the conservation sector has historically achieved great results. For instance, right now multiple actors are working together under United for Wildlife to address the challenges of the illegal wildlife trade. Although there will always be a need for niche topic specific platforms, all conservationists will need access to a general situational intelligence on a global scale to help understand the wider changes occurring and to provide context to conservation efforts on the ground.
A unified conservation spatial intelligence tool has the significant advantage of unifying the sector’s voice, placing weight on any outputs with external actors such as governments. It also utilises the different capacities of the sector, capitalising on the differing vectors of engagement that no single organisation can achieve alone to help make the data relevant to a wider audience base.
Most importantly of all, a shared conservation intelligence tool allows the sector to understand the changes occurring to our planet over time and be in a better position to protect it. By working together rather than separately, by fostering data equality rather than wasting resources, the sector can move away from disorganised patchwork reporting and work towards a comprehensive and consistent dynamic monitoring approach.
And in a world where right now, international agreements such as the Sustainable Development Goals or the G4 Sustainability Reporting Guidelines are helping countries and companies commit to critical environmental goals, the conservation sector needs more than ever a tool that helps to accurately and consistently question state parties’ or companies’ performance.
That’s not to say this approach is infallible; not all datasets are perfect, and there are still data omissions and inaccuracies. But interorganisational collaboration would, rather than heightening this, provide a catalyst for developing new ways of filling data gaps. All the datasets mentioned exist at a high enough accuracy, with enough global coverage, to begin to provide these important insights. The technical challenges in delivering such a platform are fairly easy to overcome, requiring no ground-breaking new technology or software.
A shared intelligence hub for the conservation sector is something that WWF has been working towards, to encourage collaboration in the conservation sector and to open the conversation on how we might develop a worldwide spatial conservation analytics tool. With the improvement of spatial and EO datasets, software and hardware occurring at a rapid rate, it’s not a question on if this will happen, but when. Sooner or later actors will bring multiple environmental and development datasets together and begin to systematically define their interplay. The question is, will interorganisational cooperation happen sooner rather than later for our most important biodiverse areas? Let’s hope so, because we need it; the pressures on the environment aren’t going away.
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