Databasing 44 years of New Zealand Lepidoptera observations to assess large-scale changes in moth and butterfly diversity

The order Lepidoptera is an ecologically important insect group which undertake a range of ecosystem services, including herbivory, decomposition, and most notably pollination. Numerous studies on Lepidoptera abundance and diversity in the Northern Hemisphere have revealed large, sustained declines in population numbers and alterations to range size over an alarmingly high proportion of species for several decades. The overwhelming trend is one of ongoing net loss of biodiversity at a global scale. Land-use changes resulting in a lack of nectar sources, a loss of critical host plants, and the interaction of these impacts with the increasing pressures wrought by climate change on already vulnerable taxa are thought to be the main drivers behind the temporal patterns of decline being seen. New Zealand’s Lepidoptera fauna is globally significant for its unique assemblage of endemic moths and butterflies. Despite this, population trends of New Zealand’s moths and butterflies are so far largely undocumented, as the long-term monitoring regimes responsible for recording declines in other countries is lacking in New Zealand. To begin to fill this gap in knowledge, databasing methods are being undertaken on 44 years’ worth of expert Lepidopterist Brian Patrick’s personal records, in order to achieve a workable dataset conducive to statistical analysis and ongoing use. Preliminary results of observations spanning 10 years indicate declines in Lepidoptera at lower elevation sites and in agricultural areas. This has significant implications for the future of conservation for our native pollinator species. Refinement of the database is needed, and ongoing exploration of the dataset with the addition of earlier observations will be valuable for strengthening trends. It is hoped that these results will inform the conservation of a key order of New Zealand’s biota and serve as a case study for the value of curiosity driven, unfunded data-collection in achieving much-needed long-term datasets.