Nine changes needed to deliver a radical transformation in biodiversity measurement
Abstract
Biodiversity is declining in many parts of the world. The measurement and monitoring of
biological diversity are fundamental to the assessment of the causes and consequences of
environmental changes, identification of key areas for the protection of biodiversity or
ecosystem services, determining the effectiveness of actions, and the creation of
decision-support tools critical to the maintenance of a sustainable planet. The measurement
of biodiversity is rapidly changing due to advances in citizen science, image recognition,
acoustic monitoring, environmental DNA, genomics, remote sensing and artificial
intelligence. In this perspective, we outline the exciting opportunities that these
developments offer, but also consider the challenges, especially the potential poisoning of
data by AI, lack of standardisation across methods, coverage gaps in data, concerns over
losing databases, and undervaluing of on-the-ground expertise and data-generation. Our key
recommendations are (1) ensure new technologies are calibrated with existing data; (2) use
emerging technologies to fill data gaps; (3) create living databases of trusted information to
increase reliability of data and reduce the risk of poisoning by false - or AI hallucinated -
information; (4) ensure data generation is valued; (5) ensure the respect and incorporation
of Indigenous Knowledge; (6) increase in-country capacity in the tropics; and (7) increase the
resilience of global datasets to technical and societal change. Radical new collaborations are
needed between computer scientists, engineers, molecular biologists, data scientists, field
ecologists, citizen scientists, Indigenous peoples, and local communities to create the
rigorous, resilient, accessible biodiversity information systems required to underpin policies
and practices that ensure the maintenance and restoration of ecological systems.
biological diversity are fundamental to the assessment of the causes and consequences of
environmental changes, identification of key areas for the protection of biodiversity or
ecosystem services, determining the effectiveness of actions, and the creation of
decision-support tools critical to the maintenance of a sustainable planet. The measurement
of biodiversity is rapidly changing due to advances in citizen science, image recognition,
acoustic monitoring, environmental DNA, genomics, remote sensing and artificial
intelligence. In this perspective, we outline the exciting opportunities that these
developments offer, but also consider the challenges, especially the potential poisoning of
data by AI, lack of standardisation across methods, coverage gaps in data, concerns over
losing databases, and undervaluing of on-the-ground expertise and data-generation. Our key
recommendations are (1) ensure new technologies are calibrated with existing data; (2) use
emerging technologies to fill data gaps; (3) create living databases of trusted information to
increase reliability of data and reduce the risk of poisoning by false - or AI hallucinated -
information; (4) ensure data generation is valued; (5) ensure the respect and incorporation
of Indigenous Knowledge; (6) increase in-country capacity in the tropics; and (7) increase the
resilience of global datasets to technical and societal change. Radical new collaborations are
needed between computer scientists, engineers, molecular biologists, data scientists, field
ecologists, citizen scientists, Indigenous peoples, and local communities to create the
rigorous, resilient, accessible biodiversity information systems required to underpin policies
and practices that ensure the maintenance and restoration of ecological systems.
Research Areas
