In the proposed work, we will undertake select activities to advance the use of remote-sensing data for species distribution and abundance modelling. We are strategically including partners (as…

The National Aeronautics and Space Administration (NASA) awarded a $575,281.18 grant to Yale University on February 14, 2018 to advance the use of remote sensing data for species distribution and abundance modeling. The grant does not have a set-aside designation. The work will leverage existing projects and partnerships to improve inventory datasets, enhance modeling methods, and deliver spatial and spatio-temporal Essential Biodiversity Variable (EBV) products for species in North America, South Africa, and globally, including for invasive species. These EBVs will be used to provide improved information for biodiversity indicators endorsed by the Convention on Biological Diversity and the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. The proposal has endorsements from the Global Biodiversity Information Facility, Convention on Biological Diversity, IUCN Invasive Species Specialist Group, and South African Environmental Observation Network.

In the proposed work, we will undertake select activities to advance the use of remote-sensing data for species distribution and abundance modelling. We are strategically including partners (as CO-is and named collaborators) with ongoing projects in this area that allow US to combine a range of activities and achieve synergies. We are also able to benefit from GEO BON partner map of life (https://MOL.ORG, PI jetz, CO-i guralnick) as modelling and web- infrastructure that ensure the effective and continued delivery of results to GEO BON and national and global stakeholders. First, we will advance the use of inventory datasets such as camera trapping and plant plot survey data combined with remote sensing data, as these (in combination with broadly-available incidental point records) enable the use of more sophisticated models for assessing change in occurrence and abundance. Second, using these data we will improve and demonstrate modelling methods that are particularly well-suited for assessing population change when combined with remote sensing. Third, we will build on these two efforts to deliver a range of spatial and, as possible, spatio-temporal EBV products for select species in north america (birds, mammals), south africa (proteas), and globally (select terrestrial vertebrates), including in particular select invasive species. Fourth, we will use these ebvs to provide improved information for indicators that have been endorsed by the CBD (https://WWW.CBD.INT) and (as core indicator) by ipbes (http://WWW.ipbes.net). Our proposal thus responds to the key GEO BON call elements, including advancement of EBV methodology, EBV and indicator production, and provision of information relevant for bons. The proposed project is endorsed by the global biodiversity information facility, the convention on biological diversity, the iucn invasive species specialist group, and the south african environmental observation network.