Natural History Museum, London, UK
a.purvis@nhm.ac.uk
Renewable energy production is necessary to halt climate change and thereby reverse associated biodiversity losses. Ironically, generating the required technologies and infrastructure drives an increase in the production of many metals, creating new mining threats for biodiversity. Mining is estimated to influence around 50 million km2 of Earth’s land surface, with much in protected areas, key biodiversity areas or wilderness. It follows that without strategic planning, extending this influence with additional threats to biodiversity could outstrip any effects the mitigation of climate change by renewable technologies could bring.
The PREDICTS model developed at the NHM [1] produces the ‘Biodiversity Intactness Index’ (BII) that has been used to calculate the impact that human activity has on biodiversity at local scales (~1 km). It captures features such as species richness, abundance, evenness, community biomass, turnover, and functional diversity. The BII is has been adopted as a core indicator by the Intergovernmental science-policy Platform for Biodiversity and Ecosystem Services (IPBES) and as such is likely to be a metric supported by the Convention on Biological Diversity (CBD) and as such will become an internationally recognised metric that measures the biodiversity impacts of change. It has been proposed as one of a minimal set of indicators that could allow tracking of progress towards the Convention on Biological Diversity’s 2050 goal of living in harmony with nature.
It is proposed that a PREDICTS approach, combined with an extinction modelling approach also developed at NHM, should be applied to mining projects where it can identify biodiversity hotspots and at-risk areas, mapping the locations of protected areas, threatened habitats and at-risk areas where mining would jeopardise unique biodiversity. This could produce local Biodiversity Intactness scores and map changes in biodiverse habitat areas and land use data showing recent drivers of change through mining operations. In the long term, such an approach could be developed into developing datasets auditing the biodiversity footprints of company assets and furthermore determine their exposure to biodiversity-related risks through future planned activities (e.g., enabling plans to achieve the ‘no net loss’ threshold) and operations and become a metric of equal import to other measures of project viability.
[1] https://onlinelibrary.wiley.com/doi/full/10.1002/ece3.2579
Biography
Andy’s group uses primarily comparative statistical approaches to study a wide range of fundamental questions in biodiversity science, using a range of taxa and often re-purposing data from the literature. Current projects include global modelling of how local terrestrial biodiversity responds to human impacts (PREDICTS: www.predicts.org.uk)
Andy Purvis is a Research Leader and Individual Merit Researcher at the Natural History Museum in London, and was previously Professor of Biodiversity at Imperial College London. His research largely involves statistical modelling of specially-compiled large data sets to answer a wide range of questions in biodiversity science, from macroevolution to conservation. He heads the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems), which aims to model globally how local terrestrial biodiversity responds to human pressures and to use these models to project potential biodiversity futures under alternative scenarios of socioeconomic development. He was a Coordinating Lead Author on chapter 2 of the first IPBES Global Assessment of biodiversity and ecosystem services, and scientific advisor on Sir David Attenborough’s documentary, “Extinction: The Facts”.
