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The dynamics of historical and recent range shifts in the ruffed grouse (Bonasa umbellus)

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Abstract

Climate variability is the most important force affecting distributional range dynamics of common and widespread species with important impacts on biogeographic patterns. This study integrates phylogeography with distributional analyses to understand the demographic history and range dynamics of a widespread bird species, the Ruffed Grouse (Bonasa umbellus), under several climate change scenarios. For this, I used an ecological niche modeling approach, together with Bayesian based phylogeographic analysis and landscape genetics, to develop robust inferences regarding this species’ demographic history and range dynamics. The model’s predictions were mostly congruent with the present distribution of the Ruffed Grouse. However, under the Last Glacial Maximum bioclimatic conditions, the model predicted a substantially narrower distribution than the present. The predictions for the Last Glacial Maximum also showed three allopatric refugia in south-eastern and west-coast North America, and a cryptic refugium in Alaska. The prediction for the Last Interglacial showed two separate distributions to the west and east of the Rocky Mountains. In addition, the predictions for 2050 and 2070 indicated that the Ruffed Grouse will most likely show slight range shifts to the north and will become more widely distributed than in the past or present. At present, effective population connectivity throughout North America was weakly positively correlated with Fst values. That is, the species’ distribution range showed a weak isolation-by-resistance pattern. The extended Bayesian Skyline Plot analysis, which provided good resolution of the effective population size changes over the Ruffed Grouse’s history, was mostly congruent with ecological niche modelling predictions for this species. This study offers the first investigation of the late-Quaternary history of the Ruffed Grouse based on ecological niche modelling and Bayesian based demographic analysis. The species’ present genetic structure is significantly affected by past climate changes, particularly during the last 130 kybp. That is, this study offers valuable evidence of the ‘expansion–contraction’ model of North America’s Pleistocene biogeography.

Zusammenfassung

Dynamik historischer und rezenter Arealverschiebungen beim Kragenhuhn (Bonasa umbellus)

Klimatische Veränderungen sind die Haupttriebfeder für die Dynamik der Vorkommen häufiger und weitverbreiteter Arten und haben weitreichende Auswirkungen auf biogeografische Muster. In dieser Untersuchung kombinieren wir Phylogeografie mit Verbreitungsanalysen, um die Demografiegeschichte und die Dynamik der Vorkommen einer weitverbreiteten Vogelart, des Kragenhuhns (Bonasa umbellus), im Kontext verschiedener Klimawandelszenarien nachzuvollziehen. Dabei wurde eine Kombination aus ökologischer Nischenmodellierung, Bayes’scher phylogeografischer Analyse sowie Landschaftsgenetik eingesetzt, um belastbare Erkenntnisse bezüglich der Demografiegeschichte und der Verbreitungsdynamik dieser Art zu gewinnen. Die Vorhersagen aus diesem Modell deckten sich zum Großteil mit der heutigen Verbreitung des Kragenhuhns. Allerdings sagte das Modell für die bioklimatischen Bedingungen des Letzten Eiszeitlichen Minimums eine deutlich engere Verbreitung als die heutige voraus. Außerdem wiesen die Vorhersagen für das Letzteiszeitliche Maximum drei allopatrische Refugien im Südosten und an der Westküste Nordamerikas sowie ein kryptisches Refugium in Alaska aus. Die Vorhersagen für das letzte Interglazial zeigten zwei getrennte Vorkommen westlich beziehungsweise östlich der Rocky Mountains. Darüber hinaus ließen die Vorhersagen für 2050 und 2080 erkennen, dass sich die Areale aller Voraussicht nach leicht nordwärts verschieben und diese Art weiter verbreitet sein wird als heute oder in der Vergangenheit. Für die Jetztzeit korrelierte die effektive Populationskonnektivität schwach positiv mit den Fst-Werten. Dies bedeutet, dass das Verbreitungsgebiet der Art ein schwaches Muster einer durch die Landschaft bedingten Isolation aufweist. Die erweiterte Bayes’sche Skyline-Plot-Analyse, welche eine gute Darstellung der effektiven Populationsgrößenveränderungen in Verlauf der Geschichte des Kragenhuhns erlaubte, deckte sich weitgehend mit den Vorhersagen der ökologischen Nischenmodellierung für diese Art. Diese Studie liefert die erste Untersuchung der spätquartären Geschichte des Kragenhuhns auf der Grundlage ökologischer Nischenmodellierung und Bayes’scher Demografieanalyse. Die heutige genetische Struktur der Art ist signifikant durch frühere Klimaveränderungen bedingt, speziell während der letzten 130,000 Jahre. Daraus folgt, dass diese Arbeit wertvolle Argumente für das biogeografische Modell der Ausdehnung und Zusammenziehung im pleistozänen Nordamerika zur Verfügung stellt.

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Acknowledgements

Can Elverici kindly prepared the base map for the ecological niche modelling analyses. Editors, Liviu Parau, and an anonymous reviewer greatly improved the manuscript. Logistic support for the ecological niche modelling analysis was provided by a research project supported by Hacettepe University (project number: FHD-2018-17059). For GenBank accession numbers of sequences that I used in this study, see Jensen et al. 2019 (MK603980–MK604036), and the additional file 2 in Honeycutt et al. 2019.

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Correspondence to Utku Perktaş.

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10336_2020_1828_MOESM1_ESM.pdf

Supplement 1. View of Ruffed Grouse distribution in geographic and environmental space. The top figure shows occurrence records on the map. The bottom figure plots known occurrences in a space summarizing annual mean temperature and temperature annual range. Dots with three different colors show G (geographic space), M (dispersal potential of the species), and E (actual species occurrence records) (PDF 11795 kb)

Supplement 2. Three projections of Last Glacial Maximum (A-CCSM4, B-MIROC-ESM and C-MPI-ESM-P). (PDF 535 kb)

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Perktaş, U. The dynamics of historical and recent range shifts in the ruffed grouse (Bonasa umbellus). J Ornithol 162, 43–52 (2021). https://doi.org/10.1007/s10336-020-01828-y

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