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Different distribution maps can be obtained for the same species if localities where species are present are mapped at different times. We analysed the accumulation of information over time for a group of dung beetle species in the Iberian Peninsula. To do this, we used all available information about the distribution of the group as well as data on selected species to examine if the process of discovery of species distribution has occurred in a climatically or spatially structured fashion. Our results show the existence of a well-defined pattern of temporal growth in distributional information; due to this, the date of capture of each specimen can be explained by the environmental and spatial variables associated to the collection sites. We hypothesize that such temporal biases could be the rule rather than the exception in most distributional data. These biases could affect the weighting of environmental factors that influence species distributions, as well as the accuracy of predictive distribution models. Systematic surveys should be a priority for the description of species geographical ranges in order to make robust predictions about the consequences of habitat and climate change for their persistence and conservation. [ABSTRACT FROM AUTHOR]

Species distribution models (SDMs) treat species as a single unit, neglecting intraspecific variation. Few studies address the impact of intraspecific variation on SDM performance, and none of them account for the well-known inter-algorithm variability in prediction performance. The endemic Iberian amphibian Lissotriton boscai comprises two geographically highly structured phylogenetic lineages, which allowed us to explore how intraspecific variation affects the overall performance of SDMs and the predicted ecological niche. We built species and lineage distribution models using three different presence-only algorithms. We also tested for niche overlap, niche equivalency and niche similarity, using an ordination technique. We found differences in the predicted potential distribution of the two lineages and the underlying environmental factors. Moreover, intraspecific differences in model predictive capacity existed irrespective of which algorithm was used to build the distribution models. This was coupled with lineages showing a low degree of niche overlap and occurring in relatively different environmental niches spaces. The intraspecific variation observed in L. boscai led to an improved intraspecific predictivity of the lineage level based-distribution models. There was partial spatial agreement between the niche overlap and independently reported secondary contact zones. Thus SDMs built only at the species level may be too naive to predict impacts of global change on species distributions., (Copyright © 2020 Elsevier GmbH. All rights reserved.)