The biodiversity impacts of non-native species should not be extrapolated from biased single-species studies

Abstract

The presence, diversity and abundance of non-native plant species in natural vegetation are common condition indicators used to determine conservation status, with consequences for management strategies and investment. The rationale behind non-native species metrics as condition indicators is the assumption that non-natives have negative consequences on native biodiversity and habitat condition. The case against non-native species is not so clear-cut, with some studies reporting neutral or even facilitative interactions, often depending on spatial scale. Observational and experimental evaluations of the impact of particular non-native species on biodiversity provide a vital evidence-base for general conservation management strategies. Unintentionally though, many studies that quantify the impacts of non-native species have resulted in a publication bias in which species with known impacts are selected for investigation far more often than benign species. Here we argue that meta-analyses of the impacts of individual non-native species on natives, no matter how meticulous or objective, should not be generalized beyond the set of ‘training’ species. The likelihood of such extrapolation is increased when metaanalyses are reported with little qualification as to the skewed sampling towards problematic species, and because alternative findings such as non-native assemblages having positive interactions with native biodiversity, are under-reported. To illustrate, we discuss two meta-analyses that make general conclusions from impact studies skewed towards ‘transformers’, the most extreme invaders. We warn that if generic non-native species management strategies were to be based on these conclusions, they could not only fail to meet objectives but in some instances harm native biodiversity.