Response of Poikilotherms to Extreme Temperature Events
Notice bibliographique
Résumé
Mean temperature, the frequency of extreme climatic events, and temperature variability, are all projected to increase as a result of the current trends in climate change. In order to maximize our ability to mitigate the negative effects of climate change, it is important that we study the effects of extreme temperature events, and temperature variability. For populations whose development is temperature-dependent, these temperature variations can have strong effects on development and population dynamics. While small scale effects can be understood through experimental manipulations in the laboratory, population-level effects are more difficult to determine. Temperature change has been shown to shift tree lines towards higher altitudes, and affect the home-range of many biological systems, such as the expansion of red fox northward and the parallel retreat of the arctic fox. Although the effects of shifting range boundaries and isotherms are being actively studied, temperature variability has been given much less attention. Nonetheless, even without large increases in temperature, increased variability in climatic conditions can have a strong effect on species survival. Increased variability in precipitation is likely to have hastened the extinction of two well known butterfly populations while variability in temperature has been demonstrated to have an effect on the extinction time of long-lived shorebirds. For Zooplankton, temperature variability has a major effect on its growth rates and generation times. In this paper, we focus on poikilotherms, organisms whose development rate throughout each life stage is dictated by environmental temperature. Moreover, the different life stages of an organism, often separated by different morphologies, can develop at different rates over different temperature ranges. The developmental rates of an organism can be related to a host of processes including voltinism (number of generations per year), as well as the fecundity and mortality of the organism. The intrinsically non-linear relationship between ambient temperature and development is difficult to analyze without a mathematical model. Modeling with mathematics provides a relatively inexpensive alternative to field and/or laboratory studies, and a single model can be used as a basis for testing a wide variety of extreme temperature events superimposed on any plausible baseline annual temperature profile. We investigate a temperature driven model to simulate and analyze the generational effects of thermal perturbations on poikilotherms, where thermal perturbations include increases in mean annual temperature, increases in daily and annual temperature swings, and extreme temperature events. Using information about the temperature-dependent developmental rates (inverse developmental times) for each life stage, we can analyze the stability of the organism's life-cycle under different thermal perturbations. The model is based on the G-function (generation function) model developed by Powell (Powell & Logan (2005) Theoretical Population Biology 67(3):161-79).
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».