2 eDNA metabarcoding represents a new tool for community biodiversity assessment 22 in a broad range of aquatic and terrestrial habitats. However, much of the existing 23 literature focuses on methodological development rather than testing of ecological 24hypotheses. Here, we use presence-absence data generated by eDNA 25 metabarcoding of over 500 UK ponds to examine: 1) species associations between 26 the great crested newt (Triturus cristatus) and other vertebrates, 2) determinants of 27 great crested newt occurrence at the pondscape, and 3) determinants of vertebrate 28 species richness at the pondscape. The great crested newt was significantly 29 associated with nine vertebrate species. Occurrence in ponds was broadly reduced 30 by more fish species, but enhanced by more waterfowl and other amphibian species. 31Abiotic determinants (including pond area, depth, and terrestrial habitat) were 32 identified, which both corroborate and contradict existing literature on great 33 crested newt ecology. Some of these abiotic factors (pond outflow) also determined 34 species richness at the pondscape, but other factors were unique to great crested 35 newt (pond area, depth, and ruderal habitat) or the wider biological community 36 (pond density, macrophyte cover, terrestrial overhang, rough grass habitat, and 37 overall terrestrial habitat quality) respectively. The great crested newt Habitat 38 Suitability Index positively correlated with both eDNA-based great crested newt 39 occupancy and vertebrate species richness. Our study is one of the first to use eDNA 40 metabarcoding to test abiotic and biotic determinants of pond biodiversity. eDNA 41 metabarcoding provided new insights at scales that were previously unattainable 42 using established methods. This tool holds enormous potential for testing ecological 43 hypotheses alongside biodiversity monitoring and pondscape management. 44Freshwater ecosystems comprise <1% of the Earth's surface but provide vital 45 . CC-BY-NC-ND 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/278309 doi: bioRxiv preprint first posted online Mar. 7, 2018; 3 ecosystem services and are hotspots of biodiversity [1][2][3] 4,7,8 . Effective management of pondscapes requires knowledge of abiotic and 55 biotic factors that influence biodiversity, community structure and productivity. 56Moreover, the biodiversity that ponds support individually and in combination must be 57 examined, but can only be maintained if stressors and threats to these systems are 58 understood 4,5,7,8,10 . Exhaustive sampling of pond biodiversity is impeded by the 59 complexity of these species-rich habitats, and numerous tools required for different taxa 60 with associated bias 11 and cost 12 . However, large-scale community-level monitoring, 61 encompassing alpha (site), beta (between-site) and gamma (landscape) diver...