You need to sign in or sign up before continuing. dismiss

Peter Breslin

and 2 more

Aim: Threats faced by narrowly distributed endemic plant species in the face of the Earth’s sixth mass extinction and climate change exposure are especially severe for taxa on islands. We investigated the current and projected distribution and range changes of Cochemiea halei, an island endemic cactus. This taxon is of conservation concern, currently listed as vulnerable on the International Union for the Conservation of Nature Red List and as a species of special concern under Mexican federal law. The goals of this study are to 1). identify the correlations between climate variables and current suitable habitat for C. halei; 2). determine if the species is a serpentine endemic or has a facultative relationship with ultramafic soils; 3). predict range changes of the species based on climate change scenarios. Location: The island archipelago in Bahía Magdalena on the Pacific coast, Baja California Sur, Mexico. Methods: We used temperature and precipitation variables at 30 arcsecond resolution and soil type, employing multiple species distribution modeling methods, to identify important climate and soil conditions driving current habitat suitability. The best model of current suitability is used to predict possible effects of four climate change scenarios based on best case to worst case representative concentration pathways, with projected climate data from two general circulation models, over two time periods. Main conclusions: The occurrence of the species is found to be strongly correlated with ultramafic soils. The most important climate predictor for habitat suitability is annual temperature range. The species is predicted to undergo range contractions from 21% to 53%, depending on the severity and duration of exposure to climate change. The broader implications for a wide range of narrowly adapted, threatened and endemic plant species indicate an urgent need for threat assessment based on habitat suitability and climate change modeling.