Models of Arctic-alpine refugia highlight importance of climate and local topography

Abstract

This study aims to determine the effects of environmental factors on the distribution and species richness of refugia for arctic-alpine vegetation. We will assess the main drivers for the arctic-alpine refugia in our study areas in N Europe, defined as isolated pockets with multiple species occurrences outside their main distribution area, and how well they can be modelled. The study is based on a comprehensive vascular plant distribution data set combined with abiotic environmental data at a resolution of 1 km². Cross-validated Boosted Regression Tree (BRT) modelling was employed to examine the effects of the climatic, topographic and geologic variables on refugia distribution and refugia species richness. Model testing was performed incrementally, i.e. first climate alone, then with additions of topography or geology, and concluding with a model including all predictors. All refugia distribution models (climate-only and different predictor combinations) performed well with mean area under curve (AUC) values higher than 0.85 and true skill statistics (TSS) values higher than 0.57. The inclusion of topography significantly improved model performance for both refugia distribution and refugia species richness. Climate has a central role in controlling the occurrence of refugia. However, topographic variables aid in recognizing the locally heterogeneous environments that sustain refugia. Refugia are thus driven by joint impacts of climatic and topographic factors that determine local thermal and moisture conditions. Our study demonstrates that the spatial patterns of refugia can be successfully modelled but emphasizes a need for high-quality data sampled at resolutions reflecting significant environmental gradients.

Ecological indicator values reveal missing predictors of species distributions

“…This strongly suggests that site EIVs represent more than simple combinations of easily available environmental predictors typically used in SDMs, and highlights their distinct and informative content. While site EIVs represent an integrated signal of the long-term local environmental conditions 17,19 (depending on the ecosystem, from years to centuries), the commonly used environmental GIS layers represent interpolated or modelled trends not accounting sufficiently for local modifications of www.nature.com/scientificreports www.nature.com/scientificreports/ environmental conditions 32,34,35 , which seem to be very important when modelling species distributions at such fine spatial resolutions 36,37 .…”

Hiding from the climate: Characterizing microrefugia for boreal forest understory species

“…The (micro)refugia concept has been studied and discussed around the globe, across taxa and ecosystems (Andrew & Warrener, 2017;Hannah et al, 2014;Kiedrzyński, Zielińska, Kiedrzyńska, & Rewicz, 2017;Niskanen et al, 2016;Osman et al, 2018;Scheffers, Edwards, Diesmos, Williams, & Evans, 2014;Schut et al, 2014;Terribile et al, 2012) and a considerable amount of speculation and expectation has been expressed on the carrying role of microrefugia to slow down ongoing climate-driven loss of species and genetic biodiversity (Abeli et al, 2018;Hampe & Petit, 2005;Keppel et al, 2012;Provan & Maggs, 2011). Much of the work has been theoretical, and more empirical studies, like ours, are needed to understand the characteristics of microrefugia, to make realistic predictions and to give adequate advice to conservation and management.…”

Drivers of high-latitude plant diversity hotspots and their congruence

“…czerepanovii) and alpine tundra above the tree-line in the north (Sormunen et al 2011, le Roux et al 2012. See Niskanen et al (2016aNiskanen et al ( , 2016b for further details on the study area.…”