Globally, more than one million species are threatened with extinction, but often interventions intended to protect biodiversity are not rooted in robust research. The field has an opportunity to change that.
Studies from Himachal Pradesh in northern India (pictured) have found that tree-planting schemes have not increased forest canopy cover.Credit: Pallava Bagla/Getty
Biodiversity loss is continuing at an unprecedented rate, with species becoming extinct at between 100 and 1,000 times the average pre-human, or ‘background’, rate. Human activities are the main cause. Although there are hundreds of local, regional and international initiatives to conserve and sustainably use species and ecosystems, many conservation scientists worry that measures such as interventions to conserve individual species or incentives to create protected areas are not supported by strong evidence from research1.
Scientists are building giant ‘evidence banks’ to create policies that actually work
“It always astonishes me how, while drowning in an ocean of information, we still don’t have the scientifically based answers to very simple questions,” says Sandra Díaz, an ecologist at the National University of Córdoba in Argentina.
This week, scientists are meeting in Manchester, UK, for the annual conference of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES). This is to biodiversity what the Intergovernmental Panel on Climate Change (IPCC) is to climate — a body of the world’s researchers that provides authoritative scientific assessments in response to requests from governments. How to improve both the availability and use of good evidence in policymaking does not necessarily make headlines, but it is something that needs to be high on the agenda for IPBES, as it is for the IPCC.
Last month, conservation scientists and practitioners met in Cambridge, UK, to discuss what one of Europe’s largest conservation groups, the UK-based Wildlife Trusts, is calling an “evidence emergency”. There was a consensus on at least two points. First, the quality of evidence used in drawing up conservation policies needs to improve. In northern India, for example, decades of tree-planting schemes have not increased forest canopy cover because of a failure to account for the reasons why cover was being lost to begin with2.
Second, it has been difficult for those outside academia to find evidence for what works and what doesn’t. The academic literature in particular is not organized in a way that allows such users to readily find answers to their queries. “There’s a tremendous amount of information in the scientific literature, but it’s largely inaccessible,” says Shahid Naeem, an ecologist at Columbia University in New York City, who was not at the meeting.
This is changing, thanks to a solution inspired by the synthesis of literature reviews commonly seen in medicine. A prominent example is the initiative Conservation Evidence, which is based at the University of Cambridge. It is an enormous undertaking involving hundreds of researchers, who have spent two decades working their way through more than 1.2 million research papers in 18 languages to identify studies that test the impact of conservation interventions. The team has summarized and indexed studies that qualify, and the results are available through a website that is free to access and can be searched by keyword (see go.nature.com/4tgddxj). In just one of several thousand examples, 47 studies have been reviewed to evaluate the effectiveness of schemes in which farmers are paid to alter their agricultural practices in the interests of conserving biodiversity.
Will AI speed up literature reviews or derail them entirely?
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