ArticleBMC ecology and evolution2021
Impact of model assumptions on demographic inferences: the case study of two sympatric mouse lemurs in northwestern Madagascar.
Article in BMC ecology and evolution, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Estimating the Effective Population Size Across Space and Time in the Critically Endangered Western Chimpanzee in Guinea-Bissau: Challenges and Implications for Conservation Management.Evolutionary applications · 2025Article
- Global spatiotemporal patterns of demographic fluctuations in terrestrial vertebrates during the Late Pleistocene.Science advances · 2025Article
- Population genomics of seal lice provides insights into the postglacial history of northern European seals.Molecular ecology · 2024Article
- Past volcanic activity predisposes an endemic threatened seabird to negative anthropogenic impacts.Scientific reports · 2024Article
- Diversification processes in Gerp's mouse lemur demonstrate the importance of rivers and altitude as biogeographic barriers in Madagascar's humid rainforests.Ecology and evolution · 2023Article
- Species-specific traits mediate avian demographic responses under past climate change.Nature ecology & evolution · 2023Article
- Genomics, Population Divergence, and Historical Demography of the World's Largest and Endangered Butterfly, The Queen Alexandra's Birdwing.Genome biology and evolution · 2023Article
- The importance of well protected forests for the conservation genetics of West African colobine monkeys.American journal of primatology · 2023Article
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10 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundQuaternary climate fluctuations have been acknowledged as major drivers of the geographical distribution of the extraordinary biodiversity observed in tropical biomes, including Madagascar. The main existing framework for Pleistocene Malagasy diversification assumes that forest cover was strongly shaped by warmer Interglacials (leading to forest expansion) and by cooler and arid glacials (leading to forest contraction), but predictions derived from this scenario for forest-dwelling animals have rarely been tested with genomic datasets.
resultsWe generated genomic data and applied three complementary demographic approaches (Stairway Plot, PSMC and IICR-simulations) to infer population size and connectivity changes for two forest-dependent primate species (Microcebus murinus and M. ravelobensis) in northwestern Madagascar. The analyses suggested major demographic changes in both species that could be interpreted in two ways, depending on underlying model assumptions (i.e., panmixia or population structure). Under panmixia, the two species exhibited larger population sizes across the Last Glacial Maximum (LGM) and towards the African Humid Period (AHP). This peak was followed by a population decline in M. ravelobensis until the present, while M. murinus may have experienced a second population expansion that was followed by a sharp decline starting 3000 years ago. In contrast, simulations under population structure suggested decreasing population connectivity between the Last Interglacial and the LGM for both species, but increased connectivity during the AHP exclusively for M. murinus.
conclusionOur study shows that closely related species may differ in their responses to climatic events. Assuming that Pleistocene climatic conditions in the lowlands were similar to those in the Malagasy highlands, some demographic dynamics would be better explained by changes in population connectivity than in population size. However, changes in connectivity alone cannot be easily reconciled with a founder effect that was shown for M. murinus during its colonization of the northwestern Madagascar in the late Pleistocene. To decide between the two alternative models, more knowledge about historic forest dynamics in lowland habitats is necessary. Altogether, our study stresses that demographic inferences strongly depend on the underlying model assumptions. Final conclusions should therefore be based on a comparative evaluation of multiple approaches.
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