Ecological niche models and species distribution models (ENM and SDM, respectively) are tools that have seen massive use and considerable improvement during the last twenty years. The choice of calibration areas for such models has strong effects on model outcomes and model interpretation, as well as on model transfer to distinct environmental settings. However, approaches to selecting these areas remain simple and/or unlinked to biological concepts. Such models should be calibrated within areas that the species of interest has explored throughout its recent history, the accessible area (M). In this paper, we provide a simulation approach for estimating a species' M considering processes of dispersal, colonization, and extinction in constant current climate or glacial-interglacial climate change frameworks, implemented within a new R package we developed called grinnell. Using the avian genus Aphelocoma, we explored different parameterizations of our simulation, and compared them to current approaches for M selection, in terms of model performance and risk of extrapolation using the algorithm Maxent and mobility-oriented parity analyses. Model calibration exercises from all approaches resulted in at least one model meeting optimal performance criteria for each species; however, we noted high variability among taxa and M selection methods. More importantly, M hypotheses derived directly from simulations of key biological processes, rather than being based on simple proxies of those processes, and as such are better suited to erecting biologically appropriate contrasts in model calibration, and to characterizing the potential for model extrapolation more rigorously. Major factors in our simulations were environmental layer resolution, dispersal kernel characteristics, and the inclusion of a changing framework of climatic conditions. This contribution represents the first simulation-based method for selecting calibration areas for ENM and SDM, offering a quantitative approach to estimate the accessible area of a species while considering its dispersal ability, along with patterns of change in environmental suitability across space and time. Highlights! We present a simulation-based method to delimit areas that have been accessible for species during relevant periods of time (M) and that represent appropriate calibration areas in ecological niche modeling and species distribution modeling. ! We explored implications of using calibration areas, created with common methods and simulations, on performance of models and on their predictions. ! Our results show that simulated M areas differ in geographic pattern and extent from those created with other methods. ! Although M areas derived from simulations are still hypotheses, they are closer to the regions that could have been explored by a species; comparisons of model outputs showed that these differences have effects in model prediction and interpretation.

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AimThe Pleistocene glacial cycles play a prominent role in shaping phylogeographical patterns of organisms, while few studies have focused on the regional difference of glacial effects. By acquiring comprehensive knowledge of the origin, diversification and historical demography of an intensively studied passerine species complex, Great Tit, we aim to test the regional variation of the Late Pleistocene glaciation impacts on this widely distributed bird lineage.LocationEurasia and associated peninsulas and archipelagos.TaxaParus major species complex.MethodsPhylogeny, divergence times and demographic dynamics were estimated with Bayesian methods. Population structure, genetic diversity and correlation between genetic and physical distances were estimated based on mtDNA variation. Glacial‐to‐present distributional changes were assessed via ecological niche modelling (ENM).ResultsFive major clades (Central Asia, Eastern Asia, Eastern Himalaya, Northern and Western Eurasia and Southern Asia) were detected, with divergence times ranging 1.57–0.50 million years ago. Genetic diversity values and Bayesian skyline plots suggest that the three eastern clades had a deeper population history. A more complex geographic structure was observed in East Asia. Demographic expansion during the last glacial cycle was indicated for all five clades. ENM results showed broad conservatism of traits related to climate tolerances, and generally broader and more continuous distributional patterns under glacial conditions.Main ConclusionsThe Great Tit complex probably originated in Southeast Asia. Geographic barriers, such as the deserts of Central Asia and the Qinghai–Tibet Plateau appear to be related to the lineage divergence. Late Pleistocene climate cycles influenced both demographic dynamics and divergence, especially in terms of east–west differences in relation to geographic complexity.

The field of distributional ecology has seen considerable recent attention, particularly surrounding the theory, protocols, and tools for Ecological Niche Modeling (ENM) or Species Distribution Modeling (SDM). Such analyses have grown steadily over the past two decades—including a maturation of relevant theory and key concepts—but methodological consensus has yet to be reached. In response, and following an online course taught in Spanish in 2018, we designed a comprehensive English-language course covering much of the underlying theory and methods currently applied in this broad field. Here, we summarize that course, ENM2020, and provide links by which resources produced for it can be accessed into the future. ENM2020 lasted 43 weeks, with presentations from 52 instructors, who engaged with >2500 participants globally through >14,000 hours of viewing and >90,000 views of instructional video and question-and-answer sessions. Each major topic was introduced by an “Overview” talk, followed by more detailed lectures on subtopics. The hierarchical and modular format of the course permits updates, corrections, or alternative viewpoints, and generally facilitates revision and reuse, including the use of only the Overview lectures for introductory courses. All course materials are free and openly accessible (CC-BY license) to ensure these resources remain available to all interested in distributional ecology.

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