Dataset Information

No evidence for a relationship between MHC heterozygosity and life history strategy in a sample of North American undergraduates.

ABSTRACT: Although allelic diversity at the major histocompatibility complex (MHC) has implications for adaptive immunity, mate choice, and social signalling, how diversity at the MHC influences the calibration of life history strategies remains largely uninvestigated. The current study investigated whether greater MHC heterozygosity was associated with markers of slower life history strategies in a sample of 789 North American undergraduates. Contrary to preregistered predictions and to previously published findings, MHC heterozygosity was not related to any of the psychological life history-relevant variables measured (including short- vs. long-term sexual strategy, temporal discounting, the Arizona life history battery, past and current health, disgust sensitivity, and Big Five personality traits). Further, no meaningful effects emerged when analysing women and men separately. Possible reasons for why the current results are inconsistent with previous work are discussed.

SUBMITTER: Murray DR

PROVIDER: S-EPMC7311407 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

No evidence for a relationship between MHC heterozygosity and life history strategy in a sample of North American undergraduates.

Murray Damian R DR Moran James B JB Prokosch Marjorie L ML Kerry Nicholas N

Scientific reports 20200623 1

Although allelic diversity at the major histocompatibility complex (MHC) has implications for adaptive immunity, mate choice, and social signalling, how diversity at the MHC influences the calibration of life history strategies remains largely uninvestigated. The current study investigated whether greater MHC heterozygosity was associated with markers of slower life history strategies in a sample of 789 North American undergraduates. Contrary to preregistered predictions and to previously publis ...[more]

PMID: 32576939

Similar Datasets

Project description:The geographic ranges of taxa change in response to environmental conditions. Yet whether rates of range movement (biotic velocities) are phylogenetically conserved is not well known. Phylogenetic conservatism of biotic velocities could reflect similarities among related lineages in climatic tolerances and dispersal-associated traits. We assess whether late Quaternary biotic velocities were phylogenetically conserved and whether they correlate with climatic tolerances and dispersal-associated traits. We used phylogenetic regression and nonparametric correlation to evaluate associations between biotic velocities, dispersal-associated traits, and climatic tolerances for 28 woody plant genera and subgenera in North America. The velocities with which woody plant taxa shifted their core geographic range limits were positively correlated from time step to time step between 16 and 7 ka. The strength of this correlation weakened after 7 ka as the pace of climate change slowed. Dispersal-associated traits and climatic tolerances were not associated with biotic velocities. Although the biotic velocities of some genera were consistently fast and others consistently slow, biotic velocities were not phylogenetically conserved. The rapid late Quaternary range shifts of plants lacking traits that facilitate frequent long-distance dispersal has long been noted (i.e., Reid's Paradox). Our results are consistent with this paradox and show that it remains robust when phylogenetic information is taken into account. The lack of association between biotic velocities, dispersal-associated traits, and climatic tolerances may reflect several, nonmutually exclusive processes, including rare long-distance dispersal, biotic interactions, and cryptic refugia. Because late Quaternary biotic velocities were decoupled from dispersal-associated traits, trait data for genera and subgenera cannot be used to predict longer-term (millennial-scale) floristic responses to climate change.

Project description:BackgroundIdentifying animal behaviors, life history states, and movement patterns is a prerequisite for many animal behavior analyses and effective management of wildlife and habitats. Most approaches classify short-term movement patterns with high frequency location or accelerometry data. However, patterns reflecting life history across longer time scales can have greater relevance to species biology or management needs, especially when available in near real-time. Given limitations in collecting and using such data to accurately classify complex behaviors in the long-term, we used hourly GPS data from 5 waterfowl species to produce daily activity classifications with machine-learned models using "automated modelling pipelines".MethodsAutomated pipelines are computer-generated code that complete many tasks including feature engineering, multi-framework model development, training, validation, and hyperparameter tuning to produce daily classifications from eight activity patterns reflecting waterfowl life history or movement states. We developed several input features for modeling grouped into three broad categories, hereafter "feature sets": GPS locations, habitat information, and movement history. Each feature set used different data sources or data collected across different time intervals to develop the "features" (independent variables) used in models.ResultsAutomated modelling pipelines rapidly developed easily reproducible data preprocessing and analysis steps, identification and optimization of the best performing model and provided outputs for interpreting feature importance. Unequal expression of life history states caused unbalanced classes, so we evaluated feature set importance using a weighted F1-score to balance model recall and precision among individual classes. Although the best model using the least restrictive feature set (only 24 hourly relocations in a day) produced effective classifications (weighted F1 = 0.887), models using all feature sets performed substantially better (weighted F1 = 0.95), particularly for rarer but demographically more impactful life history states (i.e., nesting).ConclusionsAutomated pipelines generated models producing highly accurate classifications of complex daily activity patterns using relatively low frequency GPS and incorporating more classes than previous GPS studies. Near real-time classification is possible which is ideal for time-sensitive needs such as identifying reproduction. Including habitat and longer sequences of spatial information produced more accurate classifications but incurred slight delays in processing.

Dataset Information

No evidence for a relationship between MHC heterozygosity and life history strategy in a sample of North American undergraduates.

Publications

No evidence for a relationship between MHC heterozygosity and life history strategy in a sample of North American undergraduates.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets