Notes

Protective effect of dexmedetomidine on neuronal hypoxic harm by means of inhibition involving miR-134.
When we accounted for environmental change, predictions better matched observations in the common-garden experiments, although substantial uncertainty remained. Our results demonstrate that predictions of evolution are unreliable if environmental change is not appropriately captured in models.AbstractAdaptive topography is a central concept in evolutionary biology, describing how the mean fitness of a population changes with gene frequencies or mean phenotypes. We use expected population size as a quantity to be maximized by natural selection to show that selection on pairwise combinations of reproductive traits of collared flycatchers caused by fluctuations in population size generated an adaptive topography with distinct peaks often located at intermediate phenotypes. This occurred because r- and K-selection made phenotypes favored at small densities different from those with higher fitness at population sizes close to the carrying capacity K. Fitness decreased rapidly with a delay in the timing of egg laying, with a density-dependent effect especially occurring among early-laying females. The number of fledglings maximizing fitness was larger at small population sizes than when close to K. Finally, there was directional selection for large fledglings independent of population size. We suggest that these patterns can be explained by increased competition for some limiting resources or access to favorable nest sites at high population densities. Thus, r- and K-selection based on expected population size as an evolutionary maximization criterion may influence life-history evolution and constrain the selective responses to changes in the environment.AbstractAn extension of the climate variability hypothesis is that relatively stable climate, such as that of the tropics, induces distinct thermal bands across elevation that render dispersal over tropical mountains difficult compared with temperate mountains. Yet ecosystems are not thermally static in space-time, especially at small scales, which might render some mountains greater thermal isolators than others. Here we provide an extensive investigation of temperature drivers from fine to coarse scales, and we demonstrate that the degree of similarity in temperatures at high and low elevations on mountains is driven by more than just absolute mountain height and latitude. selleck compound We compiled a database of 29 mountains spanning six continents to characterize thermal overlap by vertically stratified microhabitats and biomes and owing to seasonal changes in foliage, demonstrating via mixed effects modeling that micro- and mesogeography more strongly influence thermal overlap than macrogeography. Impressively, an increase of 1 m of vertical microhabitat height generates an increase in overlap equivalent to a 5.26° change in latitude. In addition, forested mountains have reduced thermal overlap-149% lower-relative to nonforested mountains. We provide evidence in support of a climate hypothesis that emphasizes microgeography as a determinant of dispersal, demographics, and behavior, thereby refining the classical theory of macroclimate variability as a prominent driver of biogeography.AbstractEvolution and plasticity can drive population-level phenotypic change (e.g., changes in the mean phenotype) on timescales comparable to changes in population densities. However, it is unclear whether phenotypic change has the potential to be just as fast as changes in densities or whether comparable rates of change occur only when densities are changing slow enough for phenotypes to keep pace. Moreover, it is unclear whether this depends on the mode of adaptation. Using scaling theory and fast-slow dynamical systems theory, we develop a method for comparing maximum rates of density and phenotypic change estimated from population-level time-series data. We apply our method to 30 published empirical studies where changes in morphological traits are caused by evolution, plasticity, or an unknown combination. For every study, the maximum rate of phenotypic change was between 0.5 and 2.5 times faster than the maximum rate of change in density. Moreover, there were no systematic differences between systems with different modes of adaptation. Our results show that plasticity and evolution can drive phenotypic change just as fast as changes in densities. We discuss the implications of our results in terms of the strengths of feedbacks between population densities and traits.AbstractAnimals challenged with disease may select specific habitat conditions that help prevent or reduce infection. Whereas preinfection avoidance of habitats with a high risk of disease exposure has been documented in both captive and free-ranging animals, evidence of switching habitats after infection to support the clearing of the infection is limited to laboratory experiments. The extent to which wild animals proximately modify habitat choices in response to infection status thus remains unclear. We investigated preinfection behavioral avoidance and postinfection habitat switching using wild, radio-tracked boreal toads (Anaxyrus boreas boreas) in a population challenged with Batrachochytrium dendrobatidis (Bd), a pathogenic fungus responsible for a catastrophic panzootic affecting hundreds of amphibian species worldwide. Boreal toads did not preemptively avoid microhabitats with conditions conducive to Bd growth. Infected individuals, however, selected warmer, more open habitats, which were associated with elevated body temperature and the subsequent clearing of infection. Our results suggest that disease can comprise an important selective pressure on animal habitat and space use. Habitat selection models, therefore, may be greatly improved by including variables that quantify infection risk and/or the infection status of individuals through time.AbstractDespite the rich biodiversity found in nature, it is unclear to what extent some combinations of interacting species, while conceivable in a given place and time, may never be realized. Yet solving this problem is important for understanding the role of randomness and predictability in the assembly of ecological communities. Here we show that the specific combinations of interacting species that emerge from the ecological dynamics within regional species pools are not all equally likely to be seen; rather, they are among the most likely to persist under changing environments. First, we use niche-based competition matrices and Lotka-Volterra models to demonstrate that realized combinations of interacting species are more likely to persist under random parameter perturbations than the majority of potential combinations with the same number of species that could have been formed from the regional pool. We then corroborate our theoretical results using a 10-year observational study, recording 88 plant-herbivore communities across three different forest successional stages.
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