Periodic Reporting for period 3 - BIOSPACE (Monitoring Biodiversity from Space)
Reporting period: 2022-09-01 to 2024-02-29
Life, with all its diversity, is in crisis. As humans increasingly encroach on biologically complex semi-natural landscapes, no organism, place or ecological function remains unaffected. While all 196 parties (195 countries plus the European Union) to the UN Convention on Biodiversity (CBD) have agreed to monitor the state of biodiversity, the currently available methods to do so leave much to be desired.
The overall aim of the BIOSPACE project is to monitor biodiversity by upscaling field observations and genomic (eDNA) information using next generation satellite remote sensing. A further key aim is the deepening of our scientific understanding of how biodiversity is impacted by anthropogenic pressure as well as by natural environmental gradients.To synthesize global biodiversity on a fine granular scale, the first specific objective is to predict biodiversity over large areas using environmental DNA (eDNA) and next-generation hyperspectral and LiDAR satellite remote sensing. As the richness in ecological function remains mostly invisible to remote sensing, the second objective is that global biodiversity may be monitored through ecosystem function by satellite. This would allow ecosystem function, expressed through foliar chemistry (e.g. N:P or C:N ratios) or through plant traits to be parameterized and interpolated in next-generation satellite images using the functional genes from eDNA sequences. The third key objective will be to demonstrate and understand how the many available eDNA sequences interpolated by remote sensing for ecosystem function and taxonomy may be affected by environmental gradients and anthropogenic pressure
The overall aim of the BIOSPACE project is to monitor biodiversity by upscaling field observations and genomic (eDNA) information using next generation satellite remote sensing. A further key aim is the deepening of our scientific understanding of how biodiversity is impacted by anthropogenic pressure as well as by natural environmental gradients.To synthesize global biodiversity on a fine granular scale, the first specific objective is to predict biodiversity over large areas using environmental DNA (eDNA) and next-generation hyperspectral and LiDAR satellite remote sensing. As the richness in ecological function remains mostly invisible to remote sensing, the second objective is that global biodiversity may be monitored through ecosystem function by satellite. This would allow ecosystem function, expressed through foliar chemistry (e.g. N:P or C:N ratios) or through plant traits to be parameterized and interpolated in next-generation satellite images using the functional genes from eDNA sequences. The third key objective will be to demonstrate and understand how the many available eDNA sequences interpolated by remote sensing for ecosystem function and taxonomy may be affected by environmental gradients and anthropogenic pressure
The BIOSPACE project commenced with a full complement of appointments with a kickoff meeting in January 2020, just a month before the COVID pandemic shut down laboratory and field work in February 2020. However, despite these constraints and restrictions, we persevered and have major achievements.
Key achievements to date include:
i) Developed new methods for integrating remote sensing (Image spectroscopy) with environmental (e)DNA and submitted first exploratory paper on combining RS and eDNA.
ii) We link the technology with policy and industry requirements for monitoring the environment in general and specifically biodiversity. We published in 2021 a Nature (Nature Ecology and Evolution) paper on which Essential Biodiversity Variables to prioritize from a policy perspective, with an emphasis on remote sensing and eDNA.
iii) We have been in active communication and contact with several industry partners and managers. These discussions have primarily been around securing access to laboratory resources, field sites and assistance with field work data collection, developing contacts and ideas for valorization of results, and integrating outputs.
iv) 7 ISI papers have been published, with others in preparation or submitted.
We have combined statistical and machine learning technologies in novel methods to support these key inter-disciplinary achievements. Our initial knowledge transfer is through scientific publications and described in §1.3.
Key achievements to date include:
i) Developed new methods for integrating remote sensing (Image spectroscopy) with environmental (e)DNA and submitted first exploratory paper on combining RS and eDNA.
ii) We link the technology with policy and industry requirements for monitoring the environment in general and specifically biodiversity. We published in 2021 a Nature (Nature Ecology and Evolution) paper on which Essential Biodiversity Variables to prioritize from a policy perspective, with an emphasis on remote sensing and eDNA.
iii) We have been in active communication and contact with several industry partners and managers. These discussions have primarily been around securing access to laboratory resources, field sites and assistance with field work data collection, developing contacts and ideas for valorization of results, and integrating outputs.
iv) 7 ISI papers have been published, with others in preparation or submitted.
We have combined statistical and machine learning technologies in novel methods to support these key inter-disciplinary achievements. Our initial knowledge transfer is through scientific publications and described in §1.3.
The challenge is to combine two cutting-edge scientific disciplines – the techniques of next-generation satellite remote sensing and eDNA profiling – to generate synoptic terrestrial biodiversity metrics at a fine resolution.The integration of advanced hyperspectral and LiDAR remote sensing data with eDNA profiling will exponentially increase our ability to capture whole-ecosystem biodiversity metrics, offering insights into the rapid measurement of ecosystem function and ecosystem structure uninhibited by taxonomic or geographical boundaries. This innovative science will allow for the identification and quantification of fundamental ecological strategies and how communities respond to biotic conditions, competition, stress, and environmental change. The project is unique in combining two disciplines (viz. DNA profiling and imaging spectroscopy/LiDAR) that have, to date, remained separate. Innovations for handling and analyzing the big data generated by both disciplines will be combined, with the resulting cross-fertilization of ideas facilitating a scientific jump to the next level of understanding, monitoring and reporting on biodiversity.