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Record W7001213385

Investigating the impacts of Late Pleistocene climate change on Arctic mammals using palaeogenomics

2022· other· en· W7001213385 on OpenAlexaboutno aff

Bibliographic record

VenueKTH Publication Database DiVA (KTH Royal Institute of Technology) · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPleistoceneClimate changePopulationInterglacialDemographic historyArcticGlacial periodClimate oscillation
DOInot available

Abstract

fetched live from OpenAlex

The climatic fluctuations of the Late Pleistocene likely had a large impact on the evolutionary history of Arctic species. Palaeogenomics is a useful tool to shed light on how past populations responded to these climatic shifts and the associated ice sheet dynamics and sea level change. Here, I have used modern and ancient DNA data from four Arctic mammals in order to investigate the impacts of Late Pleistocene climate on their evolutionary histories, from population dynamics and demography, to speciation and gene flow, adaptation, and genome erosion. In Paper I, using ancient mitogenomes from across their Late Pleistocene range, I showed that the Eurasian collared lemming (Dicrostonyx torquatus) had a dynamic Late Pleistocene population structure in Europe. Furthermore, the Eemian interglacial likely led to a bottleneck in collared lemmings, after which the species diversified during the Last Glacial period. Nuclear genome data from a modern individual in northeastern Siberia suggests population stability in northeastern Siberia during the Holocene. In Paper II, I sequenced the nuclear genome of a ~18,500 year old woolly rhinoceros (Coelodonta antiquitatis) and used this in combination with mitochondrial data to explore the demographic history of the species. There was little geographic structuring in the northeast Siberian population, and stability in their effective population size just prior to extinction, which may indicate a subsequent rapid decline towards extinction, likely associated with the Bølling-Allerød interstadial. Additionally, I found that this species had mutations in TRPA1, a gene involved in temperature sensitivity. In a third study (Paper III), I used whole genome data from modern and ancient true lemmings (Lemmus sp.) to determine that the Norwegian lemming (L. lemmus) has one of the youngest speciation times (~37-34 ka BP) of mammals. Norwegian lemmings have mutations in genes involved in coat colour, colour perception, fat transport and reproduction, and likely evolved their unique colouration as a result of isolation after the recolonisation of Fennoscandia. Finally, we examined the consequences of long-term small effective population size in muskox (Ovibos moschatus) using 107 modern nuclear genomes and one 21,000 year old Siberian genome (Paper IV). While muskox survived the warming at the end of the Late Pleistocene, the successive founder events experienced during its colonisation of the Canadian Arctic and Greenland reduced the genetic diversity to some of the lowest values observed in mammals. However, the results suggest that the long-term small population size likely led to purging of strongly deleterious alleles in the muskox, allowing them to persist to today with limited evidence of inbreeding depression. From a technical point, this thesis presents four de-novo genome assemblies, and the first whole nuclear genomes for these Arctic species. Taken together, the results in this thesis show that the climatic fluctuations, in particular the Eemian interglacial and Bølling-Allerød interstadial, along with sea level change and the formation and retreat of ice sheets during the Last Glacial Maximum have influenced the evolutionary histories of these four Arctic mammals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.060
GPT teacher head0.297
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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Same venueKTH Publication Database DiVA (KTH Royal Institute of Technology)French-language works237,207