Identification of reliable predictors of golden sun moth Synemon plana habitat over multiple survey years can benefit conservation, restoration and surveys for new populations

Abstract

Native grasslands, and the fauna that inhabit them, are globally some of the most threatened ecosystems and organisms. Knowledge of the relative importance of climate, landscape context and site-based resources for local insect populations is critical for the restoration and conservation of these communities. We investigated the site and landscape-scale best predictors of occurrence and abundance over three consecutive years of sampling, for the critically endangered golden sun moth Synemon plana in south-eastern Australia. We found eight vegetation factors to be significantly associated with golden sun moth occurrence using data from combined survey data and data for each year alone; we identified just three common factors from year to year. Modelling indicated that Austrostipa and Rytidosperma species richness was the most consistent parameter, but for each year alone, there was a combination of aspect, landscape position and Austrostipa and Rytidosperma species richness. Our study shows that environmental characteristics where golden sun moth occur are relatively predictable over multiple years. This information can be used to protect sites where monitoring of extant populations is yet to occur, predict the location of new populations in the region, and restore adjacent habitat that is suitable but degraded.