Combining correlative and mechanistic niche models with human activity data to elucidate the invasive potential of a sub‐Antarctic insect. (30th December 2019) - Pertierra, Luis R.; Bartlett, Jesamine C.; Duffy, Grant A.; Vega, Greta C.; Hughes, Kevin A.; Hayward, Scott A. L.; Convey, Peter; Olalla‐Tarraga, Miguel A.; Aragón, P.
Abstract: Aim: Correlative species distribution models (SDMs) are subject to substantial spatio‐temporal limitations when historical occurrence records of data‐poor species provide incomplete and outdated information for niche modelling. Complementary mechanistic modelling techniques can, therefore, offer a valuable contribution to underpin more physiologically informed predictions of biological invasions, the risk of which is often exacerbated by climate change. In this study we integrate physiological and human pressure data to address the uncertainties and limitations of correlative SDMs and to better understand, predict and manage biological invasions. Location: Western archipelagos of the Southern Ocean and martime Antarctica. Taxon: Eretmoptera murphyi (Chironomidae), invertebrates. Methods: Mahalanobis Distances were used for correlative SDM construction for a species with few records. A mechanistic SDM was built around different fitness components (larval survival and life stage progression) as a function of temperature. SDM predictions were combined with human activity levels in Antarctica to generate a site vulnerability index to the assess colonization risk of E. murphyi . Future scenarios of ecophysiological suitability were built around the warming trends in the region. Results: Both SDMs converge to predict high environmental suitability in the species' native and introduced ranges. However, the mechanistic model indicates a slightly larger invasive potential based on larval performance at different temperatures. Human activity levels across the Antarctic Peninsula play a key role in discerning site vulnerabilities. Niche suitability in Antarctica grows considerably under long‐term climate scenarios, leading to a substantially higher invasive threat to the Antarctic ecosystems. In turn changing conditions result in growing physiological mismatches with the environment in the native range in South Georgia. Main conclusions: Long‐term studies of invasion potential under climate benefit from integrating correlative predictions with physiological experiments, as the invasion potential varies depending on the area and the timescale examined. This study also highlights a conservation paradox whereby the accidental introduction of an insect represents a threat to the Antarctic ecoystems that contrasts with its endangered status at the native range.