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Mechanisms driving behavioral variation in ecologically distinct Peromyscus mice

2020· dissertation· en· W3216187787 sur OpenAlexaboutno aff
Felix Baier

Notice bibliographique

RevueDigital Access to Scholarship at Harvard (DASH) (Harvard University) · 2020
Typedissertation
Langueen
DomaineEnvironmental Science
ThématiqueAnimal Ecology and Behavior Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPeromyscusVariation (astronomy)EcologyBiologyGeography
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Animal behavior is shaped both by ultimate and proximate forces. While evolutionary biologists have focused primarily on understanding the ultimate mechanisms driving behavioral variation in natural populations, geneticists and neurobiologists have largely been concerned with proximate mechanisms affecting behavior in laboratory model species. However, few studies have combined these approaches to investigate the genetic or neural basis of adaptive behavior in natural populations with known evolutionary history. Here, I present two independent studies that examine the proximate mechanisms (e.g., genetic and neural basis) of aggressive and defensive behavior in closely related, yet ecologically distinct deer mice (genus Peromyscus). In Chapter 1, I focus on the “island syndrome”, the iconic observation that island animals often share consistent differences in morphology and behavior compared to their closest relatives on the mainland. These traits are thought to be adaptations to island environments, but the extent to which they are heritable or instead represent plastic responses to environmental extremes is poorly understood. Specifically, I re-visit a classic case of deer mice (Peromyscus maniculatus) in British Columbia, Canada. Previous field studies in the 1970s and 1980s showed that density in the derived island population is increased, and island mice are heavier and less aggressive than ancestral mainland mice. To examine the genetic heritability of both the unique morphology and behavior of island mice, I first establish laboratory colonies from wild-derived mice to minimize environmental effects on phenotypes. I show that the body size differences are strongly heritable and controlled both by offspring and maternal genotypes, consistent with ecological predictions. Second, I confirm that wild-born island mice show a striking reduction of aggressive behavior, compared to high levels of aggression in mainland mice. Surprisingly, however, these differences disappear in captive-born mice island and mainland mice. Thus, my experiments point to a variable proximate response of morphological and behavioral traits to the environmental conditions on the island, and suggest that individual experience may influence the expression of ecologically relevant behavior. In Chapter 2, I examine the neural mechanisms underlying heritable variation in defensive behavior to overhead visual threat in ecologically distinct deer mice: P. maniculatus occurs in densely vegetated prairie and forest habitats, while P. polionotus inhabits open habitats with little vegetative cover. I first discover striking behavioral differences between these closely related species: P. maniculatus escape from a looming stimulus, while P. polionotus briefly pause, a behavior reminiscent of threat assessment. By varying threat intensity, I demonstrate that these differences arise because P. maniculatus have a lower escape threshold. Using expression of c-Fos as a readout of neuronal activity, I show that neuronal activation in the deep layers of the superior colliculus, a brain region encoding threat intensity, is proportional to escape magnitude in both species. By contrast, neuronal activation in the dorsal periaqueductal gray (dPAG), a downstream brain region that gates and initiates escape, is proportional to escape magnitude in P. maniculatus, but I do not find evidence for dPAG activation in P. polionotus, even in strongly escaping mice. To further probe the role of dPAG in these two species, I (with collaborators) establish optogenetics for the first time in Peromyscus mice. By activating the dPAG, I find that both species pause in response to low laser powers, consistent with observations that both species pause to low threat intensity. However, P. maniculatus switch to escape with increasing laser powers, while P. polionotus tend to pause more strongly. These results suggest that evolution may have acted on a central brain circuit such that two closely related, but ecologically distinct, species respond to the same external stimulus in different ways. Together, these two studies demonstrate how the proximate mechanisms underlying behavior in wild-derived animal populations can be modified over ontogenetic and evolutionary time to flexibly allow animals to adapt to their natural environment.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,032
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,000
Communication savante0,0010,004
Science ouverte0,0020,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0070,009

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,025
Tête enseignante GPT0,258
Écart entre enseignants0,233 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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