bioRxiv preprint doi: https://doi.org/10.1101/2020.06.01.107391; this version posted June 2, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 Using generalised dissimilarity modelling and targeted field surveys 2 to gap-fill an ecosystem surveillance network 3 4 Greg R. Guerin1,2*, Kristen J. Williams3, Emrys Leitch1,2, Andrew J. Lowe1, Ben Sparrow1,2 5 6 1School of Biological Science, The University of Adelaide, Adelaide, South Australia 5005, 7 Australia 8 2Terrestrial Ecosystem Research Network 9 3CSIRO Land and Water, Canberra, Australian Capital Territory 2601, Australia 10 11 *Email:
[email protected] 12 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.06.01.107391; this version posted June 2, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 13 Abstract 14 1. When considering which sites or land parcels complement existing conservation or 15 monitoring networks, there are many strategies for optimising ecological coverage in the 16 absence of ground observations. However, such optimisation is often implemented 17 theoretically in conservation prioritisation frameworks and real-world implementation is 18 rarely assessed, particularly for networks of monitoring sites. 19 2. We assessed the performance of adding new survey sites informed by predictive modelling 20 in gap-filling the ecological coverage of the Terrestrial Ecosystem Research Network’s 21 (TERN) continental network of ecosystem surveillance plots, Ausplots.