Satellite4Biodiversity - Large scale fast biodiversity observation from space

Biodiversity is declining rapidly globally, fast biodiversity monitoring methods are urgently required to fulfill the biodiversity data scarcity for supporting biodiversity and ecological conservation management.
In this project, we combine environmental DNA data from global observatory vigilife (www.vigilife.org) and remote sensing images to build the large-scale biodiversity observatory for the freshwater system. eDNA detects the genomics information of species from environmental samples, while multiple sources of remote sensing images from space are used to generate environmental variables, with a tight relationship with biodiversity and species distribution.
We aim at developing improved monitoring approach for biodiversity in rivers using a combination of remote sensing, eDNA metabarcoding data and machine learning driven model to monitor biodiversity temporally in a global scale and build a routine biodiversity observatory. Firstly, we will improve the sampling design of eDNA studies within large rivers to better represent the ecological preference of species. Secondly, we use eDNA collected in large rivers and remote sensing variables to model species distribution along the rivers to demonstrate that those methods can be efficiently combined. Thirdly, we use data on natural river sections globally to train a deep learning model to recognize pristine rivers with variables derived from remote sensing data to both test globally identification and generate a new derived variable to predict biodiversity. Lastly, we focus on a global combination of eDNA across 15 large rivers globally with remote sensing data to monitor biodiversity temporally and globally. Through this project, we will advance our capacity to monitor biodiversity at a large scale in river systems for policy-makers and stakeholders to make ecological management decisions.